Blue Marble Eastern Hemisphere

NASA Technical Reports Server (NTRS)

2002-01-01

Drawing on data from multiple satellite missions (not all collected at the same time), a team of NASA scientists and graphic artists created layers of global data for everything from the land surface, to polar sea ice, to the light reflected by the chlorophyll in the billions of microscopic plants that grow in the ocean. They wrapped these layers around a globe, set it against a black background, and simulated the hazy edge of the Earth's atmosphere (the limb) that appears in astronaut photography of the Earth. The land surface layer is based on photo-like surface reflectance observations (reflected sunlight) measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite in July 2004. The sea ice layer near the poles comes from Terra MODIS observations of daytime sea ice observed between August 28 and September 6, 2001. The ocean layer is a composite. In shallow water areas, the layer shows surface reflectances observed by Terra MODIS in July 2004. In the open ocean, the photo-like layer is overlaid with observations of the average ocean chlorophyll content for 2004. NASA's Aqua MODIS collected the chlorophyll data. The cloud layer shows a single-day snapshot of clouds observed by Terra MODIS across the planet on July 29, 2001. City lights on Earth's night side are visualized from data collected by the Defense Meteorological Satellite Program mission between 1994-1995. The topography layer is based on radar data collected by the Space Shuttle Endeavour during an 11-day mission in February of 2000. Topography over Antarctica comes from the Radarsat Antarctic Mapping Project, version 2.

Blue Marble Western Hemisphere

NASA Technical Reports Server (NTRS)

2002-01-01

Drawing on data from multiple satellite missions (not all collected at the same time), a team of NASA scientists and graphic artists created layers of global data for everything from the land surface, to polar sea ice, to the light reflected by the chlorophyll in the billions of microscopic plants that grow in the ocean. They wrapped these layers around a globe, set it against a black background, and simulated the hazy edge of the Earth's atmosphere (the limb) that appears in astronaut photography of the Earth. The land surface layer is based on photo-like surface reflectance observations (reflected sunlight) measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite in July 2004. The sea ice layer near the poles comes from Terra MODIS observations of daytime sea ice observed between August 28 and September 6, 2001. The ocean layer is a composite. In shallow water areas, the layer shows surface reflectances observed by Terra MODIS in July 2004. In the open ocean, the photo-like layer is overlaid with observations of the average ocean chlorophyll content for 2004. NASA's Aqua MODIS collected the chlorophyll data. The cloud layer shows a single-day snapshot of clouds observed by Terra MODIS across the planet on July 29, 2001. City lights on Earth's night side are visualized from data collected by the Defense Meteorological Satellite Program mission between 1994-1995. The topography layer is based on radar data collected by the Space Shuttle Endeavour during an 11-day mission in February of 2000. Topography over Antarctica comes from the Radarsat Antarctic Mapping Project, version 2.

Evaluation of MODIS and VIIRS Albedo Products Using Ground and Airborne Measurements and Development of Ceos/Wgcv/Lpv Albedo Ecv Protocols

NASA Astrophysics Data System (ADS)

Wang, Z.; Roman, M. O.; Schaaf, C.; Sun, Q.; Liu, Y.; Saenz, E. J.; Gatebe, C. K.

2014-12-01

Surface albedo, defined as the ratio of the hemispheric reflected solar radiation flux to the incident flux upon the surface, is one of the essential climate variables and quantifies the radiation interaction between the atmosphere and the land surface. An absolute accuracy of 0.02-0.05 for global surface albedo is required by climate models. The MODerate resolution Imaging Spectroradiometer (MODIS) standard BRDF/albedo product makes use of a linear "kernel-driven" RossThick-LiSparse Reciprocal (RTLSR) BRDF model to describe the reflectance anisotropy. The surface albedo is calculated by integrating the BRDF over the above ground hemisphere. While MODIS Terra was launched in Dec 1999 and MODIS Aqua in 2002, the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-NPP satellite was launched more recently on October 28, 2011. Thus a long term record of BRDF, albedo and Nadir BRDF-Adjusted Reflectance (NBAR) products from VIIRS can be generated through MODIS heritage algorithms. Several investigations have evaluated the MODIS albedo products during the growing season, as well as during dormant and snow covered periods. The Land Product Validation (LPV) sub-group of the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) aims to address the challenges associated with the validation of global land products. The validation of global surface radiation/albedo products is one of the LPV subgroup activities. In this research, a reference dataset covering various land surface types and vegetation structure is assembled to assess the accuracy of satellite albedo products. This dataset includes in situ data (Baseline Surface Radiation Network (BSRN), FLUXNET and Long Term Ecological Research network (LTER) etc.) and airborne measurements (e.g. Cloud Absorption Radiometer (CAR)). Spatially representative analysis is applied to each site to establish whether the ground measurements can adequately represent moderate spatial resolution remotely sensed albedo products.

MODIS Aerosol Optical Depth retrieval over land considering surface BRDF effects

NASA Astrophysics Data System (ADS)

Wu, Yerong; de Graaf, Martin; Menenti, Massimo

2016-04-01

Aerosols in the atmosphere play an important role in the climate system and human health. Retrieval from satellite data, Aerosol Optical Depth (AOD), one of most important indices of aerosol optical properties, has been extensively investigated. Benefiting from the high resolution at spatial and temporal and the maturity of the aerosol retrieval algorithm, MOderate Resolution Imaging Spectroradiometer (MODIS) Dark Target AOD product has been extensively applied in other scientific research such as climate change and air pollution. The latest product - MODIS Collection 6 Dark Target AOD (C6_DT) has been released. However, the accuracy of C6_DT AOD (global mean ±0.03) over land is still too low for the constraint on radiative forcing in the climate system, where the uncertainty should be reduced to ±0.02. The major uncertainty mainly lies on the underestimation/overestimation of the surface contribution to the Top Of Atmosphere (TOA) radiance since a lambertian surface is assumed in the C6_DT land algorithm. In the real world, it requires considering the heterogeneity of the surface reflection in the radiative transfer process. Based on this, we developed a new algorithm to retrieve AOD by considering surface Bidirectional Reflectance Distribution Function (BRDF) effects. The surface BRDF is much more complicated than isotropic reflection, described as 4 elements: directional-directional, directional-hemispherical, hemispherical-directional and hemispherical-hemispherical reflectance, and coupled into radiative transfer equation to generate an accurate top of atmosphere reflectance. The limited MODIS measurements (three channels available) allow us to retrieve only three parameters, which including AOD, the surface directional-directional reflectance and fine aerosol ratio η. The other three elements of the surface reflectance are expected to be constrained by ancillary data and assumptions or "a priori" information since there are more unknowns than MODIS measurements in our algorithm. We validated three case studies with AErosol Robotic NETwork (AERONET) AOD, and the results show that the AOD retrieval was improved compared to C6_DT AOD, with the increase of within expected accuracy ±(0.05 + 15%) by ranging from 2.7% to 7.5% for the best quality only (Quality Assurance =3), and from 5.8% to 9.5% for the marginal and better quality (Quality Assurance ≥ 1).

Clear-sky narrowband albedos derived from VIRS and MODIS

NASA Astrophysics Data System (ADS)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Arduini, Robert F.

2004-02-01

The Clouds and Earth"s Radiant Energy System (CERES) project is using multispectral imagers, the Visible Infrared Scanner (VIRS) on the tropical Rainfall Measuring Mission (TRMM) satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra, operating since spring 2000, and Aqua, operating since summer 2002, to provide cloud and clear-sky properties at various wavelengths. This paper presents the preliminary results of an analysis of the CERES clear-sky reflectances to derive a set top-of-atmosphere clear sky albedo for 0.65, 0.86, 1.6, 2.13 μm, for all major surface types using the combined MODIS and VIRS datasets. The variability of snow albedo with surface type is examined using MODIS data. Snow albedo was found to depend on the vertical structure of the vegetation. At visible wavelengths, it is least for forested areas and greatest for smooth desert and tundra surfaces. At 1.6 and 2.1-μm, the snow albedos are relatively insensitive to the underlying surface because snow decreases the reflectance. Additional analyses using all of the MODIS results will provide albedo models that should be valuable for many remote sensing, simulation and radiation budget studies.

The Time Series Technique for Aerosol Retrievals over Land from MODIS: Algorithm MAIAC

NASA Technical Reports Server (NTRS)

Lyapustin, Alexei; Wang, Yujie

2008-01-01

Atmospheric aerosols interact with sun light by scattering and absorbing radiation. By changing irradiance of the Earth surface, modifying cloud fractional cover and microphysical properties and a number of other mechanisms, they affect the energy balance, hydrological cycle, and planetary climate [IPCC, 2007]. In many world regions there is a growing impact of aerosols on air quality and human health. The Earth Observing System [NASA, 1999] initiated high quality global Earth observations and operational aerosol retrievals over land. With the wide swath (2300 km) of MODIS instrument, the MODIS Dark Target algorithm [Kaufman et al., 1997; Remer et al., 2005; Levy et al., 2007] currently complemented with the Deep Blue method [Hsu et al., 2004] provides daily global view of planetary atmospheric aerosol. The MISR algorithm [Martonchik et al., 1998; Diner et al., 2005] makes high quality aerosol retrievals in 300 km swaths covering the globe in 8 days. With MODIS aerosol program being very successful, there are still several unresolved issues in the retrieval algorithms. The current processing is pixel-based and relies on a single-orbit data. Such an approach produces a single measurement for every pixel characterized by two main unknowns, aerosol optical thickness (AOT) and surface reflectance (SR). This lack of information constitutes a fundamental problem of the remote sensing which cannot be resolved without a priori information. For example, MODIS Dark Target algorithm makes spectral assumptions about surface reflectance, whereas the Deep Blue method uses ancillary global database of surface reflectance composed from minimal monthly measurements with Rayleigh correction. Both algorithms use Lambertian surface model. The surface-related assumptions in the aerosol retrievals may affect subsequent atmospheric correction in unintended way. For example, the Dark Target algorithm uses an empirical relationship to predict SR in the Blue (B3) and Red (B1) bands from the 2.1 m channel (B7) for the purpose of aerosol retrieval. Obviously, the subsequent atmospheric correction will produce the same SR in the red and blue bands as predicted, i.e. an empirical function of 2.1. In other words, the spectral, spatial and temporal variability of surface reflectance in the Blue and Red bands appears borrowed from band B7. This may have certain implications for the vegetation and global carbon analysis because the chlorophyll-sensing bands B1, B3 are effectively substituted in terms of variability by band B7, which is sensitive to the plant liquid water. This chapter describes a new recently developed generic aerosol-surface retrieval algorithm for MODIS. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm simultaneously retrieves AOT and surface bi-directional reflection factor (BRF) using the time series of MODIS measurements.

An approach for the long-term 30-m land surface snow-free albedo retrieval from historic Landsat surface reflectance and MODIS-based a priori anisotropy knowledge

USDA-ARS?s Scientific Manuscript database

Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth’s radiative budget. While global climate studies can leverage albedo datasets from MODIS, VIIRS, and other coarse-reso...

An Approach for the Long-Term 30-m Land Surface Snow-Free Albedo Retrieval from Historic Landsat Surface Reflectance and MODIS-based A Priori Anisotropy Knowledge

NASA Technical Reports Server (NTRS)

Shuai, Yanmin; Masek, Jeffrey G.; Gao, Feng; Schaaf, Crystal B.; He, Tao

2014-01-01

Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth's radiative budget. While global climate studies can leverage albedo datasets from MODIS, VIIRS, and other coarse-resolution sensors, many applications in heterogeneous environments can benefit from higher-resolution albedo products derived from Landsat. We previously developed a "MODIS-concurrent" approach for the 30-meter albedo estimation which relied on combining post-2000 Landsat data with MODIS Bidirectional Reflectance Distribution Function (BRDF) information. Here we present a "pre-MODIS era" approach to extend 30-m surface albedo generation in time back to the 1980s, through an a priori anisotropy Look-Up Table (LUT) built up from the high quality MCD43A BRDF estimates over representative homogenous regions. Each entry in the LUT reflects a unique combination of land cover, seasonality, terrain information, disturbance age and type, and Landsat optical spectral bands. An initial conceptual LUT was created for the Pacific Northwest (PNW) of the United States and provides BRDF shapes estimated from MODIS observations for undisturbed and disturbed surface types (including recovery trajectories of burned areas and non-fire disturbances). By accepting the assumption of a generally invariant BRDF shape for similar land surface structures as a priori information, spectral white-sky and black-sky albedos are derived through albedo-to-nadir reflectance ratios as a bridge between the Landsat and MODIS scale. A further narrow-to-broadband conversion based on radiative transfer simulations is adopted to produce broadband albedos at visible, near infrared, and shortwave regimes.We evaluate the accuracy of resultant Landsat albedo using available field measurements at forested AmeriFlux stations in the PNW region, and examine the consistency of the surface albedo generated by this approach respectively with that from the "concurrent" approach and the coincident MODIS operational surface albedo products. Using the tower measurements as reference, the derived Landsat 30-m snow-free shortwave broadband albedo yields an absolute accuracy of 0.02 with a root mean square error less than 0.016 and a bias of no more than 0.007. A further cross-comparison over individual scenes shows that the retrieved white sky shortwave albedo from the "pre-MODIS era" LUT approach is highly consistent (R(exp 2) = 0.988, the scene-averaged low RMSE = 0.009 and bias = -0.005) with that generated by the earlier "concurrent" approach. The Landsat albedo also exhibits more detailed landscape texture and a wider dynamic range of albedo values than the coincident 500-m MODIS operational products (MCD43A3), especially in the heterogeneous regions. Collectively, the "pre-MODIS" LUT and "concurrent" approaches provide a practical way to retrieve long-term Landsat albedo from the historic Landsat archives as far back as the 1980s, as well as the current Landsat-8 mission, and thus support investigations into the evolution of the albedo of terrestrial biomes at fine resolution.

Reconstructed Solar-Induced Fluorescence: A Machine Learning Vegetation Product Based on MODIS Surface Reflectance to Reproduce GOME-2 Solar-Induced Fluorescence

NASA Astrophysics Data System (ADS)

Gentine, P.; Alemohammad, S. H.

2018-04-01

Solar-induced fluorescence (SIF) observations from space have resulted in major advancements in estimating gross primary productivity (GPP). However, current SIF observations remain spatially coarse, infrequent, and noisy. Here we develop a machine learning approach using surface reflectances from Moderate Resolution Imaging Spectroradiometer (MODIS) channels to reproduce SIF normalized by clear sky surface irradiance from the Global Ozone Monitoring Experiment-2 (GOME-2). The resulting product is a proxy for ecosystem photosynthetically active radiation absorbed by chlorophyll (fAPARCh). Multiplying this new product with a MODIS estimate of photosynthetically active radiation provides a new MODIS-only reconstruction of SIF called Reconstructed SIF (RSIF). RSIF exhibits much higher seasonal and interannual correlation than the original SIF when compared with eddy covariance estimates of GPP and two reference global GPP products, especially in dry and cold regions. RSIF also reproduces intense productivity regions such as the U.S. Corn Belt contrary to typical vegetation indices and similarly to SIF.

Evaluation and Intercomparison of MODIS and GEOV1 Global Leaf Area Index Products over Four Sites in North China

PubMed Central

Li, Zhenwang; Tang, Huan; Zhang, Baohui; Yang, Guixia; Xin, Xiaoping

2015-01-01

This study investigated the performances of the Moderate Resolution Imaging Spectroradiometer (MODIS) and GEOLAND2 Version 1 (GEOV1) Leaf Area Index (LAI) products using ground measurements and LAI reference maps over four sites in North China for 2011–2013. The Terra + Aqua MODIS and Terra MODIS LAI retrieved by the main algorithm and GEOV1 LAI within the valid range were evaluated and intercompared using LAI reference maps to assess their uncertainty and seasonal variability The results showed that GEOV1 LAI is the most similar product with the LAI reference maps (R2 = 0.78 and RMSE = 0.59). The MODIS products performed well for biomes with low LAI values, but considerable uncertainty arose when the LAI was larger than 3. Terra + Aqua MODIS (R2 = 0.72 and RMSE = 0.68) was slightly more accurate than Terra MODIS (R2 = 0.57 and RMSE = 0.90) for producing slightly more successful observations. Both MODIS and GEOV1 products effectively followed the seasonal trajectory of the reference maps, and GEOV1 exhibited a smoother seasonal trajectory than MODIS. MODIS anomalies mainly occurred during summer and likely occurred because of surface reflectance uncertainty, shorter temporal resolutions and inconsistency between simulated and MODIS surface reflectances. This study suggests that further improvements of the MODIS LAI products should focus on finer algorithm inputs and improved seasonal variation modeling of MODIS observations. Future field work considering finer biome maps and better generation of LAI reference maps is still needed. PMID:25781509

Improved MODIS aerosol retrieval in urban areas using a land classification approach and empirical orthogonal functions

NASA Astrophysics Data System (ADS)

Levitan, Nathaniel; Gross, Barry

2016-10-01

New, high-resolution aerosol products are required in urban areas to improve the spatial coverage of the products, in terms of both resolution and retrieval frequency. These new products will improve our understanding of the spatial variability of aerosols in urban areas and will be useful in the detection of localized aerosol emissions. Urban aerosol retrieval is challenging for existing algorithms because of the high spatial variability of the surface reflectance, indicating the need for improved urban surface reflectance models. This problem can be stated in the language of novelty detection as the problem of selecting aerosol parameters whose effective surface reflectance spectrum is not an outlier in some space. In this paper, empirical orthogonal functions, a reconstruction-based novelty detection technique, is used to perform single-pixel aerosol retrieval using the single angular and temporal sample provided by the MODIS sensor. The empirical orthogonal basis functions are trained for different land classes using the MODIS BRDF MCD43 product. Existing land classification products are used in training and aerosol retrieval. The retrieval is compared against the existing operational MODIS 3 KM Dark Target (DT) aerosol product and co-located AERONET data. Based on the comparison, our method allows for a significant increase in retrieval frequency and a moderate decrease in the known biases of MODIS urban aerosol retrievals.

Monitoring Land Surface Albedo and Vegetation Dynamics Using High Spatial and Temporal Resolution Synthetic Time Series from Landsat and the MODIS BRDF/NBAR/Albedo Product

NASA Technical Reports Server (NTRS)

Wang, Zhuosen; Schaaf, Crystal B.; Sun, Quingsong; Kim, Jihyun; Erb, Angela M.; Gao, Feng; Roman, Miguel O.; Yang, Yun; Petroy, Shelley; Taylor, Jeffrey R.;

Trend analysis of Terra/ASTER/VNIR radiometric calibration coefficient through onboard and vicarious calibrations as well as cross calibration with MODIS

NASA Astrophysics Data System (ADS)

Arai, Kohei

2012-07-01

More than 11 years Radiometric Calibration Coefficients (RCC) derived from onboard and vicarious calibrations are compared together with cross comparison to the well calibrated MODIS RCC. Fault Tree Analysis (FTA) is also conducted for clarification of possible causes of the RCC degradation together with sensitivity analysis for vicarious calibration. One of the suspects of causes of RCC degradation is clarified through FTA. Test site dependency on vicarious calibration is quite obvious. It is because of the vicarious calibration RCC is sensitive to surface reflectance measurement accuracy, not atmospheric optical depth. The results from cross calibration with MODIS support that significant sensitivity of surface reflectance measurements on vicarious calibration.

Application-ready expedited MODIS data for operational land surface monitoring of vegetation condition

USGS Publications Warehouse

Brown, Jesslyn; Howard, Daniel M.; Wylie, Bruce K.; Friesz, Aaron M.; Ji, Lei; Gacke, Carolyn

2015-01-01

Monitoring systems benefit from high temporal frequency image data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) system. Because of near-daily global coverage, MODIS data are beneficial to applications that require timely information about vegetation condition related to drought, flooding, or fire danger. Rapid satellite data streams in operational applications have clear benefits for monitoring vegetation, especially when information can be delivered as fast as changing surface conditions. An “expedited” processing system called “eMODIS” operated by the U.S. Geological Survey provides rapid MODIS surface reflectance data to operational applications in less than 24 h offering tailored, consistently-processed information products that complement standard MODIS products. We assessed eMODIS quality and consistency by comparing to standard MODIS data. Only land data with known high quality were analyzed in a central U.S. study area. When compared to standard MODIS (MOD/MYD09Q1), the eMODIS Normalized Difference Vegetation Index (NDVI) maintained a strong, significant relationship to standard MODIS NDVI, whether from morning (Terra) or afternoon (Aqua) orbits. The Aqua eMODIS data were more prone to noise than the Terra data, likely due to differences in the internal cloud mask used in MOD/MYD09Q1 or compositing rules. Post-processing temporal smoothing decreased noise in eMODIS data.

Early Evaluation of the VIIRS Calibration, Cloud Mask and Surface Reflectance Earth Data Records

NASA Technical Reports Server (NTRS)

Vermote, Eric; Justice, Chris; Csiszar, Ivan

2014-01-01

Surface reflectance is one of the key products fromVIIRS and as withMODIS, is used in developing several higherorder land products. The VIIRS Surface Reflectance (SR) Intermediate Product (IP) is based on the heritageMODIS Collection 5 product (Vermote, El Saleous, & Justice, 2002). The quality and character of surface reflectance depend on the accuracy of the VIIRS Cloud Mask (VCM), the aerosol algorithms and the adequate calibration of the sensor. The focus of this paper is the early evaluation of the VIIRS SR product in the context of the maturity of the operational processing system, the Interface Data Processing System (IDPS). After a brief introduction, the paper presents the calibration performance and the role of the surface reflectance in calibration monitoring. The analysis of the performance of the cloud mask with a focus on vegetation monitoring (no snow conditions) shows typical problems over bright surfaces and high elevation sites. Also discussed is the performance of the aerosol input used in the atmospheric correction and in particular the artifacts generated by the use of the Navy Aerosol Analysis and Prediction System. Early quantitative results of the performance of the SR product over the AERONET sites showthatwith the fewadjustments recommended, the accuracy iswithin the threshold specifications. The analysis of the adequacy of the SR product (Land PEATE adjusted version) in applications of societal benefits is then presented. We conclude with a set of recommendations to ensure consistency and continuity of the JPSS mission with the MODIS Land Climate Data Record.

Laser Pulse Bidirectional Reflectance from CALIPSO Mission

NASA Technical Reports Server (NTRS)

Lu, Xiaomei; Hu, Yongxiang; Yang, Yuekui; Liu, Zhaoyan; Vaughan, Mark; Lucker, Patricia; Trepte, Charles

2017-01-01

In this Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) study, we present a simple way of determining laser pulse bidirectional reflectance over snow/ice surface using the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) 532 nanometer polarization channels' measurements. The saturated laser pulse returns from snow and ice surfaces are recovered based on surface tail information. The method overview and initial assessment of the method performance will be presented. The retrieved snow surface bidirectional reflectance is compared with reflectance from both CALIOP cloud cover regions and Moderate Resolution Imaging Spectroradiometer (Earth Observing System (EOS)) (MODIS) Bi-directional Reflectance Distribution Function (BRDF) / Albedo model parameters. The comparisons show that the snow surface bidirectional reflectance over Antarctica for saturation region are generally reliable with a mean value of about 0.90 plus or minus 0.10, while the mean surface reflectance from cloud cover region is about 0.84 plus or minus 0.13 and the calculated MODIS reflectance at 555 nanometers from the BRDF / Albedo model with near nadir illumination and viewing angles is about 0.96 plus or minus 0.04. The comparisons here demonstrate that the snow surface reflectance underneath the cloud with cloud optical depth of about 1 is significantly lower than that for a clear sky condition.

a Comparative Analysis of Spatiotemporal Data Fusion Models for Landsat and Modis Data

NASA Astrophysics Data System (ADS)

Hazaymeh, K.; Almagbile, A.

2018-04-01

In this study, three documented spatiotemporal data fusion models were applied to Landsat-7 and MODIS surface reflectance, and NDVI. The algorithms included the spatial and temporal adaptive reflectance fusion model (STARFM), sparse representation based on a spatiotemporal reflectance fusion model (SPSTFM), and spatiotemporal image-fusion model (STI-FM). The objectives of this study were to (i) compare the performance of these three fusion models using a one Landsat-MODIS spectral reflectance image pairs using time-series datasets from the Coleambally irrigation area in Australia, and (ii) quantitatively evaluate the accuracy of the synthetic images generated from each fusion model using statistical measurements. Results showed that the three fusion models predicted the synthetic Landsat-7 image with adequate agreements. The STI-FM produced more accurate reconstructions of both Landsat-7 spectral bands and NDVI. Furthermore, it produced surface reflectance images having the highest correlation with the actual Landsat-7 images. This study indicated that STI-FM would be more suitable for spatiotemporal data fusion applications such as vegetation monitoring, drought monitoring, and evapotranspiration.

Effects of Surface BRDF on the OMI Cloud and NO2 Retrievals: A New Approach Based on Geometry-Dependent Lambertian Equivalent Reflectivity (GLER) Derived from MODIS

NASA Technical Reports Server (NTRS)

Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey

2017-01-01

The Ozone Monitoring Instrument (OMI) cloud and NO2 algorithms use a monthly gridded surface reflectivity climatology that does not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (GLER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. GLER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from MODIS over land and the Cox Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare GLER and climatological LER at 466 nm, which is used in the OMI O2-O2cloud algorithm to derive effective cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and GLERs is carried out. GLER and corresponding retrieved cloud products are then used as input to the OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with GLERs can increase NO2 vertical columns by up to 50 % in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

Use of Moderate-Resolution Imaging Spectroradiometer bidirectional reflectance distribution function products to enhance simulated surface albedos

NASA Astrophysics Data System (ADS)

Roesch, Andreas; Schaaf, Crystal; Gao, Feng

2004-06-01

Moderate-Resolution Imaging Spectroradiometer (MODIS) surface albedo at high spatial and spectral resolution is compared with other remotely sensed climatologies, ground-based data, and albedos simulated with the European Center/Hamburg 4 (ECHAM4) global climate model at T42 resolution. The study demonstrates the importance of MODIS data in assessing and improving albedo parameterizations in weather forecast and climate models. The remotely sensed PINKER surface albedo climatology follows the MODIS estimates fairly well in both the visible and near-infrared spectra, whereas ECHAM4 simulates high positive albedo biases over snow-covered boreal forests and the Himalayas. In contrast, the ECHAM4 albedo is probably too low over the Sahara sand desert and adjacent steppes. The study clearly indicates that neglecting albedo variations within T42 grid boxes leads to significant errors in the simulated regional climate and horizontal fluxes, mainly in mountainous and/or snow-covered regions. MODIS surface albedo at 0.05 resolution agrees quite well with in situ field measurements collected at Baseline Surface Radiation Network (BSRN) sites during snow-free periods, while significant positive biases are found under snow-covered conditions, mainly due to differences in the vegetation cover at the BSRN site (short grass) and the vegetation within the larger MODIS grid box. Black sky (direct beam) albedo from the MODIS bidirectional reflectance distribution function model captures the diurnal albedo cycle at BSRN sites with sufficient accuracy. The greatest negative biases are generally found when the Sun is low. A realistic approach for relating albedo and zenith angle has been proposed. Detailed evaluations have demonstrated that ignoring the zenith angle dependence may lead to significant errors in the surface energy balance.

Daily MODIS 500 m Reflectance Anisotropy Direct Broadcast (DB) Products for Monitoring Vegetation Phenology Dynamics

NASA Technical Reports Server (NTRS)

Shuai, Yanmin; Schaaf, Crystal; Zhang, Xiaoyang; Strahler, Alan; Roy, David; Morisette, Jeffrey; Wang, Zhuosen; Nightingale, Joanne; Nickeson, Jaime; Richardson, Andrew D.;

Thin Ice Area Extraction in the Seasonal Sea Ice Zones of the Northern Hemisphere Using Modis Data

NASA Astrophysics Data System (ADS)

Hayashi, K.; Naoki, K.; Cho, K.

2018-04-01

Sea ice has an important role of reflecting the solar radiation back into space. However, once the sea ice area melts, the area starts to absorb the solar radiation which accelerates the global warming. This means that the trend of global warming is likely to be enhanced in sea ice areas. In this study, the authors have developed a method to extract thin ice area using reflectance data of MODIS onboard Terra and Aqua satellites of NASA. The reflectance of thin sea ice in the visible region is rather low. Moreover, since the surface of thin sea ice is likely to be wet, the reflectance of thin sea ice in the near infrared region is much lower than that of visible region. Considering these characteristics, the authors have developed a method to extract thin sea ice areas by using the reflectance data of MODIS (NASA MYD09 product, 2017) derived from MODIS L1B. By using the scatter plots of the reflectance of Band 1 (620 nm-670 nm) and Band 2 (841 nm-876 nm)) of MODIS, equations for extracting thin ice area were derived. By using those equations, most of the thin ice areas which could be recognized from MODIS images were well extracted in the seasonal sea ice zones in the Northern Hemisphere, namely the Sea of Okhotsk, the Bering Sea and the Gulf of Saint Lawrence. For some limited areas, Landsat-8 OLI images were also used for validation.

Assessment of VIIRS daily BRDF/Albedo product using in situ measurement of SURFRAD sites and MODIS V006 daily BRDF/Albedo product

NASA Astrophysics Data System (ADS)

Liu, Y.; Wang, Z.; Sun, Q.; Schaaf, C.; Roman, M. O.

2014-12-01

Surface albedo is defined as the ratio of upwelling to downwelling radiative flux. It's important for understanding the global energy budget. Remote sensing albedo products provide global time continuous coverage to help capture global energy variability and change. The Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi-NPP satellite, launched on October 28, 2011, is aiming to provide continues data record with the MODerate resolution Imaging Spectroradiometer (MODIS), which has been providing Bidirectional Reflectance Distribution Function (BRDF)/Albedo product since 2000. By utilizing the same approach that was used for the most recently V006 daily MODIS BRDF/Albedo product, VIIRS has the ability to keep providing products for research and operational users. Validating albedo product of VIIRS using in situmeasured albedo can assure the quality for land surface climate and biosphere models, and comparing with MODIS product can assure time continues of BRDF/albedo product. The daily BRDF/Albedo product still uses 16-day period multispectral, cloud-cleared, atmospherically-corrected surface reflectances to fit the Ross-Thick/Li-Sparse-Reciprocal semi-empirical BRDF model. But the multiday observations are also weighted based on proximity to the production date in order to emphasis on that individual day. Surface Radiation Budget Network (SURFRAD) was established in 1993 through the support of NOAA's Office of Global Programs. In situ albedo was driven from downwelling and upwelling radiative flux measured from the towers. Fraction of diffuse sky light was calculated using the direct and diffuse solar recorded in the data. It was further used to translate VIIRS, MODIS black sky and white sky albedos into actual albedo at local solar noon. Results show that VIIRS, MODIS and in situ albedo agree well at SURFARD spatially representative sites. While the VIIRS surface reflectance, snow, and cloud algorithms are still undergoing revision, the result shows that VIIRS can provide comparable albedo products with MODIS. The accuracy of both products can meet the requirement for climate and biosphere models. In situ albedo also can be gained from Baseline Surface Radiation Network (BSRN), FLUXNET and Long Term Ecological Research network (LTER) etc., which will be used in future validation work.

Generating a Long-Term Land Data Record from the AVHRR and MODIS Instruments

NASA Technical Reports Server (NTRS)

Pedelty, Jeffrey; Devadiga, Sadashiva; Masuoka, Edward; Brown, Molly; Pinzon, Jorge; Tucker, Compton; Vermote, Eric; Prince, Stephen; Nagol, Jyotheshwar; Justice, Christopher;

Remote Sensing of Ecosystem Light Use Efficiency Using MODIS

NASA Astrophysics Data System (ADS)

Huemmrich, K. F.; Middleton, E.; Landis, D.; Black, T. A.; Barr, A. G.; McCaughey, J. H.; Hall, F.

2009-12-01

Understanding the dynamics of the global carbon cycle requires an accurate determination of the spatial and temporal distribution of photosynthetic CO2 uptake by terrestrial vegetation. Optimal photosynthetic function is negatively affected by stress factors that cause down-regulation (i.e., reduced rate of photosynthesis). Present modeling approaches to determine ecosystem carbon exchange rely on meteorological data as inputs to models that predict the relative photosynthetic function in response to environmental conditions inducing stress (e.g., drought, high/low temperatures). This study examines the determination of ecosystem photosynthetic light use efficiency (LUE) from remote sensing, through measurement of vegetation spectral reflectance changes associated with physiologic stress responses exhibited by photosynthetic pigments. This approach uses the Moderate-Resolution Spectroradiometer (MODIS) on Aqua and Terra to provide frequent, narrow-band measurements. The reflective ocean MODIS bands were used to calculate the Photochemical Reflectance Index (PRI), an index that is sensitive to reflectance changes near 531nm associated with vegetation stress responses exhibited by photosynthetic pigments in the xanthophyll cycle. MODIS PRI values were compared with LUE calculated from CO2 flux measured at four Canadian forest sites: A mature Douglas fir site in British Columbia, mature aspen and black spruce sites in Saskatchewan, and a mixed forest site in Ontario, all part of the Canadian Carbon Program network. The relationships between LUE and MODIS PRI were different among forest types, with clear differences in the slopes of the relationships for conifer and deciduous forests. The MODIS based LUE measurements provide a more accurate estimation of observed LUE than the values calculated in the MODIS GPP model. This suggests the possibility of a GPP model that uses MODIS LUE instead of modeled LUE. This type of model may provide a useful contrast to existing models driven by meteorological data. The main impediment to developing such a model is the lack of a MODIS product that provides surface reflectance for the MODIS ocean bands over land.

Application of Polarization to the MODIS Aerosol Retrieval Over Land

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Remer, Lorraine R.; Kaufman, Yoram J.

2004-01-01

Reflectance measurements in the visible and infrared wavelengths, from the Moderate Resolution Imaging Spectroradiometer (MODIS), are used to derive aerosol optical thicknesses (AOT) and aerosol properties over land surfaces. The measured spectral reflectance is compared with lookup tables, containing theoretical reflectance calculated by radiative transfer (RT) code. Specifically, this RT code calculates top of the atmosphere (TOA) intensities based on a scalar treatment of radiation, neglecting the effects of polarization. In the red and near infrared (NIR) wavelengths the use of the scalar RT code is of sufficient accuracy to model TOA reflectance. However, in the blue, molecular and aerosol scattering dominate the TOA signal. Here, polarization effects can be large, and should be included in the lookup table derivation. Using a RT code that allows for both vector and scalar calculations, we examine the reflectance differences at the TOA, with and without polarization. We find that the differences in blue channel TOA reflectance (vector - scalar) may reach values of 0.01 or greater, depending on the sun/surface/sensor scattering geometry. Reflectance errors of this magnitude translate to AOT differences of 0.1, which is a very large error, especially when the actual AOT is low. As a result of this study, the next version of aerosol retrieval from MODIS over land will include polarization.

Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic time series from Landsat and the MODIS BRDF/NBAR/albedo product

NASA Astrophysics Data System (ADS)

Wang, Zhuosen; Schaaf, Crystal B.; Sun, Qingsong; Kim, JiHyun; Erb, Angela M.; Gao, Feng; Román, Miguel O.; Yang, Yun; Petroy, Shelley; Taylor, Jeffrey R.; Masek, Jeffrey G.; Morisette, Jeffrey T.; Zhang, Xiaoyang; Papuga, Shirley A.

2017-07-01

Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warming/cooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF/NBAR/albedo products and 30 m Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDF/Albedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30 m Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16 days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30 m albedos for the intervening daily time steps in this study. These enhanced daily 30 m spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a bias within the range of ±0.006. These synthetic time series provide much greater spatial detail than the 500 m gridded MODIS data, especially over more heterogeneous surfaces, which improves the efforts to characterize and monitor the spatial variation across species and communities. The mean of the difference between maximum and minimum synthetic time series of albedo within the MODIS pixels over a subset of satellite data of Harvard Forest (16 km by 14 km) was as high as 0.2 during the snow-covered period and reduced to around 0.1 during the snow-free period. Similarly, we have used STARFM to also couple MODIS Nadir BRDF Adjusted Reflectances (NBAR) values with Landsat 5 reflectances to generate daily synthetic times series of NBAR and thus Enhanced Vegetation Index (NBAR-EVI) at a 30 m resolution. While normally STARFM is used with directional reflectances, the use of the view angle corrected daily MODIS NBAR values will provide more consistent time series. These synthetic times series of EVI are shown to capture seasonal vegetation dynamics with finer spatial and temporal details, especially over heterogeneous land surfaces.

Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic time series from Landsat and the MODIS BRDF/NBAR/albedo product

USGS Publications Warehouse

Wang, Zhuosen; Schaaf, Crystal B.; Sun, Qingson; Kim, JiHyun; Erb, Angela M.; Gao, Feng; Roman, Miguel O.; Yang, Yun; Petroy, Shelley; Taylor, Jeffrey; Masek, Jeffrey G.; Morisette, Jeffrey T.; Zhang, Xiaoyang; Papuga, Shirley A.

2017-01-01

Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warming/cooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF/NBAR/albedo products and 30 m Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDF/Albedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30 m Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16 days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30 m albedos for the intervening daily time steps in this study. These enhanced daily 30 m spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a bias within the range of ±0.006. These synthetic time series provide much greater spatial detail than the 500 m gridded MODIS data, especially over more heterogeneous surfaces, which improves the efforts to characterize and monitor the spatial variation across species and communities. The mean of the difference between maximum and minimum synthetic time series of albedo within the MODIS pixels over a subset of satellite data of Harvard Forest (16 km by 14 km) was as high as 0.2 during the snow-covered period and reduced to around 0.1 during the snow-free period. Similarly, we have used STARFM to also couple MODIS Nadir BRDF Adjusted Reflectances (NBAR) values with Landsat 5 reflectances to generate daily synthetic times series of NBAR and thus Enhanced Vegetation Index (NBAR-EVI) at a 30 m resolution. While normally STARFM is used with directional reflectances, the use of the view angle corrected daily MODIS NBAR values will provide more consistent time series. These synthetic times series of EVI are shown to capture seasonal vegetation dynamics with finer spatial and temporal details, especially over heterogeneous land surfaces.

Influence of Aerosols And Surface Reflectance On NO2 Retrieval Over China From 2005 to 2015

NASA Astrophysics Data System (ADS)

Liu, M.; Lin, J.

2016-12-01

Satellite observation is a powerful way to analysis annual and seasonal variations of nitrogen dioxide (NO2). However, much retrieval of vertical column densities (VCDs) of normally do not explicitly account for aerosol optical effects and surface reflectance anisotropy that vary with space and time. In traditional retrieval, aerosols' effects are often considered as cloud. However, China has complicated aerosols type and aerosol loading. Their optical properties may be very different from the cloud. Furthermore, China has undergone big changes in land use type in recent 10 years. Traditional climatology surface reflectance data may not have representation. In order to study spatial-temporal variation of and influences of these two factors on variations and trends, we use an improved retrieval method of VCDs over China, called the POMINO, based on measurements from the Ozone Monitoring Instrument (OMI), and we compare the results of without aerosol, without surface reflectance treatments and without both to the original POMINO product from 2005 to 2015. Furthermore, we will study correspondent spatial-temporal variations of aerosols, represented by MODIS aerosol optical depth (AOD) data and CALIOP extinction data; surface reflectance, represented by MODIS bidirectional reflectance distribution function (BRDF) data.

Can the physical properties associated with uncertainties in the NASA MODIS AOD retrievals in the western U.S. be determined?

NASA Astrophysics Data System (ADS)

Loria Salazar, S. M.; Holmes, H.; Panorska, A. K.; Arnott, W. P.; Barnard, J.

2016-12-01

Previous investigations have used satellite remote sensing to estimate surface air pollution concentrations. While most of these studies rely on models developed for the dark-vegetated eastern U.S., they are being used in the semi-arid western U.S without modifications. These models are not robust in the western U.S. due to: 1. Irregular topography that leads to complicated boundary layer physics, 2. Pollutant mixtures, 3. Heterogeneous vertical profile of aerosol concentrations, and 4. High surface reflectance. Here, results from Nevada and California demonstrate poor AOD correlation between AERONET MODIS retrievals. Smoke from wildfires strengthened the aerosol signal, but the MODIS versus AERONET AOD correlation did not improve significantly during fire events [r2 0.17 (non-fire), r2 0.2 (fire)]. Furthermore, aerosol from fires increased the normalized mean bias (NMB) of MODIS retrievals of AOD[NMB 82% (non-fire), NMB 146% (fire)]. Additional results of this investigation found that aerosol plumes confined with the boundary layer improves MODIS AOD retrievals. However, when this condition is not met (i.e., 70% of the time downwind of mountains regions) MODIS AOD has a poor correlation and high bias with respect to AERONET AOD. Fire injection height, complicated boundary layer mixing, and entrainment disperse smoke plumes into the free atmosphere. Therefore, smoke plumes exacerbate the complex aerosol transport typical in the western U.S. and the non-linear relationship between surface pollutant concentrations and conditions aloft. This work uses stochastic methods, including regression to investigate the influence of each of these physical behaviors on the MODIS, AERONET AOD discrepancy using surrogates for each physical phenomenon, e.g., surface albedo for surface reflectance, boundary layer height and elevation for complex mixing, aerosol optical height for vertical aerosol concentrations, and fire radiative power for smoke plume injection height.

Evaluation of the global MODIS 30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset

NASA Astrophysics Data System (ADS)

Sun, Qingsong; Wang, Zhuosen; Li, Zhan; Erb, Angela; Schaaf, Crystal B.

2017-06-01

Land surface albedo is an essential variable for surface energy and climate modeling as it describes the proportion of incident solar radiant flux that is reflected from the Earth's surface. To capture the temporal variability and spatial heterogeneity of the land surface, satellite remote sensing must be used to monitor albedo accurately at a global scale. However, large data gaps caused by cloud or ephemeral snow have slowed the adoption of satellite albedo products by the climate modeling community. To address the needs of this community, we used a number of temporal and spatial gap-filling strategies to improve the spatial and temporal coverage of the global land surface MODIS BRDF, albedo and NBAR products. A rigorous evaluation of the gap-filled values shows good agreement with original high quality data (RMSE = 0.027 for the NIR band albedo, 0.020 for the red band albedo). This global snow-free and cloud-free MODIS BRDF and albedo dataset (established from 2001 to 2015) offers unique opportunities to monitor and assess the impact of the changes on the Earth's land surface.

Atmospheric correction at AERONET locations: A new science and validation data set

USGS Publications Warehouse

Wang, Y.; Lyapustin, A.I.; Privette, J.L.; Morisette, J.T.; Holben, B.

2009-01-01

This paper describes an Aerosol Robotic Network (AERONET)-based Surface Reflectance Validation Network (ASRVN) and its data set of spectral surface bidirectional reflectance and albedo based on Moderate Resolution Imaging Spectroradiometer (MODIS) TERRA and AQUA data. The ASRVN is an operational data collection and processing system. It receives 50 ?? 50 km2; subsets of MODIS level 1B (L1B) data from MODIS adaptive processing system and AERONET aerosol and water-vapor information. Then, it performs an atmospheric correction (AC) for about 100 AERONET sites based on accurate radiative-transfer theory with complex quality control of the input data. The ASRVN processing software consists of an L1B data gridding algorithm, a new cloud-mask (CM) algorithm based on a time-series analysis, and an AC algorithm using ancillary AERONET aerosol and water-vapor data. The AC is achieved by fitting the MODIS top-of-atmosphere measurements, accumulated for a 16-day interval, with theoretical reflectance parameterized in terms of the coefficients of the Li SparseRoss Thick (LSRT) model of the bidirectional reflectance factor (BRF). The ASRVN takes several steps to ensure high quality of results: 1) the filtering of opaque clouds by a CM algorithm; 2) the development of an aerosol filter to filter residual semitransparent and subpixel clouds, as well as cases with high inhomogeneity of aerosols in the processing area; 3) imposing the requirement of the consistency of the new solution with previously retrieved BRF and albedo; 4) rapid adjustment of the 16-day retrieval to the surface changes using the last day of measurements; and 5) development of a seasonal backup spectral BRF database to increase data coverage. The ASRVN provides a gapless or near-gapless coverage for the processing area. The gaps, caused by clouds, are filled most naturally with the latest solution for a given pixel. The ASRVN products include three parameters of the LSRT model (kL, kG, and kV), surface albedo, normalized BRF (computed for a standard viewing geometry, VZA = 0, SZA = 45??), and instantaneous BRF (or one-angle BRF value derived from the last day of MODIS measurement for specific viewing geometry) for the MODIS 500-m bands 17. The results are produced daily at a resolution of 1 km in gridded format. We also provide a cloud mask, a quality flag, and a browse bitmap image. The ASRVN data set, including 6 years of MODIS TERRA and 1.5 years of MODIS AQUA data, is available now as a standard MODIS product (MODASRVN) which can be accessed through the Level 1 and Atmosphere Archive and Distribution System website ( http://ladsweb.nascom.nasa.gov/data/search.html). It can be used for a wide range of applications including validation analysis and science research. ?? 2006 IEEE.

Variability of albedo and utility of the MODIS albedo product in forested wetlands

USGS Publications Warehouse

Sumner, David M.; Wu, Qinglong; Pathak, Chandra S.

2011-01-01

Albedo was monitored over a two-year period (beginning April 2008) at three forested wetland sites in Florida, USA using up- and down-ward facing pyranometers. Water level, above and below land surface, is the primary control on the temporal variability of daily albedo. Relatively low reflectivity of water accounts for the observed reductions in albedo with increased inundation of the forest floor. Enhanced canopy shading of the forest floor was responsible for lower sensitivity of albedo to water level at the most dense forest site. At one site, the most dramatic reduction in daily albedo was observed during the inundation of a highly-reflective, calcareous periphyton-covered land surface. Satellite-based Moderate-Resolution Imaging Spectroradiometer (MODIS) estimates of albedo compare favorably with measured albedo. Use of MODIS albedo values in net radiation computations introduced a root mean squared error of less than 4.7 W/m2 and a mean, annual bias of less than 2.3 W/m2 (1.7%). These results suggest that MODIS-estimated albedo values can reliably be used to capture areal and temporal variations in albedo that are important to the surface energy balance.

Prototype Global Burnt Area Algorithm Using a Multi-sensor Approach

NASA Astrophysics Data System (ADS)

López Saldaña, G.; Pereira, J.; Aires, F.

2013-05-01

One of the main limitations of products derived from remotely-sensed data is the length of the data records available for climate studies. The Advanced Very High Resolution Radiometer (AVHRR) long-term data record (LTDR) comprises a daily global atmospherically-corrected surface reflectance dataset at 0.05Deg spatial resolution and is available for the 1981-1999 time period. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has been on orbit in the Terra platform since late 1999 and in Aqua since mid 2002; surface reflectance products, MYD09CMG and MOD09CMG, are available at 0.05Deg spatial resolution. Fire is strong cause of land surface change and emissions of greenhouse gases around the globe. A global long-term identification of areas affected by fire is needed to analyze trends and fire-clime relationships. A burnt area algorithm can be seen as a change point detection problem where there is an abrupt change in the surface reflectance due to the biomass burning. Using the AVHRR-LTDR and the aforementioned MODIS products, a time series of bidirectional reflectance distribution function (BRDF) corrected surface reflectance was generated using the daily observations and constraining the BRDF model inversion using a climatology of BRDF parameters derived from 12 years of MODIS data. The identification of the burnt area was performed using a t-test in the pre- and post-fire reflectance values and a change point detection algorithm, then spectral constraints were applied to flag changes caused by natural land processes like vegetation seasonality or flooding. Additional temporal constraints are applied focusing in the persistence of the affected areas. Initial results for years 1998 to 2002, show spatio-temporal coherence but further analysis is required and a formal rigorous validation will be applied using burn scars identified from high-resolution datasets.

Snow cover detection algorithm using dynamic time warping method and reflectances of MODIS solar spectrum channels

NASA Astrophysics Data System (ADS)

Lee, Kyeong-sang; Choi, Sungwon; Seo, Minji; Lee, Chang suk; Seong, Noh-hun; Han, Kyung-Soo

2016-10-01

Snow cover is biggest single component of cryosphere. The Snow is covering the ground in the Northern Hemisphere approximately 50% in winter season and is one of climate factors that affects Earth's energy budget because it has higher reflectance than other land types. Also, snow cover has an important role about hydrological modeling and water resource management. For this reason, accurate detection of snow cover acts as an essential element for regional water resource management. Snow cover detection using satellite-based data have some advantages such as obtaining wide spatial range data and time-series observations periodically. In the case of snow cover detection using satellite data, the discrimination of snow and cloud is very important. Typically, Misclassified cloud and snow pixel can lead directly to error factor for retrieval of satellite-based surface products. However, classification of snow and cloud is difficult because cloud and snow have similar optical characteristics and are composed of water or ice. But cloud and snow has different reflectance in 1.5 1.7 μm wavelength because cloud has lower grain size and moisture content than snow. So, cloud and snow shows difference reflectance patterns change according to wavelength. Therefore, in this study, we perform algorithm for classifying snow cover and cloud with satellite-based data using Dynamic Time Warping (DTW) method which is one of commonly used pattern analysis such as speech and fingerprint recognitions and reflectance spectral library of snow and cloud. Reflectance spectral library is constructed in advance using MOD21km (MODIS Level1 swath 1km) data that their reflectance is six channels including 3 (0.466μm), 4 (0.554μm), 1 (0.647μm), 2 (0.857μm), 26 (1.382μm) and 6 (1.629μm). We validate our result using MODIS RGB image and MOD10 L2 swath (MODIS swath snow cover product). And we use PA (Producer's Accuracy), UA (User's Accuracy) and CI (Comparison Index) as validation criteria. The result of our study detect as snow cover in the several regions which are did not detected as snow in MOD10 L2 and detected as snow cover in MODIS RGB image. The result of our study can improve accuracy of other surface product such as land surface reflectance and land surface emissivity. Also it can use input data of hydrological modeling.

eMODIS: A User-Friendly Data Source

USGS Publications Warehouse

Jenkerson, Calli B.; Maiersperger, Thomas; Schmidt, Gail

2010-01-01

The U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center is generating a suite of products called 'eMODIS' based on Moderate Resolution Imaging Spectroradiometer (MODIS) data acquired by the National Aeronautics and Space Administration's (NASA) Earth Observing System (EOS). With a more frequent repeat cycle than Landsat and higher spatial resolutions than the Advanced Very High Resolution Spectroradiometer (AVHRR), MODIS is well suited for vegetation studies. For operational monitoring, however, the benefits of MODIS are counteracted by usability issues with the standard map projection, file format, composite interval, high-latitude 'bow-tie' effects, and production latency. eMODIS responds to a community-specific need for alternatively packaged MODIS data, addressing each of these factors for real-time monitoring and historical trend analysis. eMODIS processes calibrated radiance data (level-1B) acquired by the MODIS sensors on the EOS Terra and Aqua satellites by combining MODIS Land Science Collection 5 Atmospherically Corrected Surface Reflectance production code and USGS EROS MODIS Direct Broadcast System (DBS) software to create surface reflectance and Normalized Difference Vegetation Index (NDVI) products. eMODIS is produced over the continental United States and over Alaska extending into Canada to cover the Yukon River Basin. The 250-meter (m), 500-m, and 1,000-m products are delivered in Geostationary Earth Orbit Tagged Image File Format (Geo- TIFF) and composited in 7-day intervals. eMODIS composites are projected to non-Sinusoidal mapping grids that best suit the geography in their areas of application (see eMODIS Product Description below). For eMODIS products generated over the continental United States (eMODIS CONUS), the Terra (from 2000) and Aqua (from 2002) records are available and continue through present time. eMODIS CONUS also is generated in an expedited process that delivers a 7-day rolling composite, created daily with the most recent 7 days of acquisition, to users monitoring real-time vegetation conditions. eMODIS Alaska is not part of expedited processing, but does cover the Terra mission life (2000-present). A simple file transfer protocol (FTP) distribution site currently is enabled on the Internet for direct download of eMODIS products (ftp://emodisftp.cr.usgs.gov/eMODIS), with plans to expand into an interactive portal environment.

USAID Expands eMODIS Coverage for Famine Early Warning

NASA Astrophysics Data System (ADS)

Jenkerson, C.; Meyer, D. J.; Evenson, K.; Merritt, M.

2011-12-01

Food security in countries at risk is monitored by U.S. Agency for International Development (USAID) through its Famine Early Warning Systems Network (FEWS NET) using many methods including Moderate Resolution Imaging Spectroradiometer (MODIS) data processed by U.S. Geological Survey (USGS) into eMODIS Normalized Difference Vegetation Index (NDVI) products. Near-real time production is used comparatively with trends derived from the eMODIS archive to operationally monitor vegetation anomalies indicating threatened cropland and rangeland conditions. eMODIS production over Central America and the Caribbean (CAMCAR) began in 2009, and processes 10-day NDVI composites every 5 days from surface reflectance inputs produced using predicted spacecraft and climatology information at Land and Atmosphere Near real time Capability for Earth Observing Systems (EOS) (LANCE). These expedited eMODIS composites are backed by a parallel archive of precision-based NDVI calculated from surface reflectance data ordered through Level 1 and Atmosphere Archive and Distribution System (LAADS). Success in the CAMCAR region led to the recent expansion of eMODIS production to include Africa in 2010, and Central Asia in 2011. Near-real time 250-meter products are available for each region on the last day of an acquisition interval (generally before midnight) from an anonymous file transfer protocol (FTP) distribution site (ftp://emodisftp.cr.usgs.gov/eMODIS). The FTP site concurrently hosts the regional historical collections (2000 to present) which are also searchable using the USGS Earth Explorer (http://edcsns17.cr.usgs.gov/NewEarthExplorer). As eMODIS coverage continues to grow, these geographically gridded, georeferenced tagged image file format (GeoTIFF) NDVI composites increase their utility as effective tools for operational monitoring of near-real time vegetation data against historical trends.

Bias Correction of MODIS AOD using DragonNET to obtain improved estimation of PM2.5

NASA Astrophysics Data System (ADS)

Gross, B.; Malakar, N. K.; Atia, A.; Moshary, F.; Ahmed, S. A.; Oo, M. M.

2014-12-01

MODIS AOD retreivals using the Dark Target algorithm is strongly affected by the underlying surface reflection properties. In particular, the operational algorithms make use of surface parameterizations trained on global datasets and therefore do not account properly for urban surface differences. This parameterization continues to show an underestimation of the surface reflection which results in a general over-biasing in AOD retrievals. Recent results using the Dragon-Network datasets as well as high resolution retrievals in the NYC area illustrate that this is even more significant at the newest C006 3 km retrievals. In the past, we used AERONET observation in the City College to obtain bias-corrected AOD, but the homogeneity assumptions using only one site for the region is clearly an issue. On the other hand, DragonNET observations provide ample opportunities to obtain better tuning the surface corrections while also providing better statistical validation. In this study we present a neural network method to obtain bias correction of the MODIS AOD using multiple factors including surface reflectivity at 2130nm, sun-view geometrical factors and land-class information. These corrected AOD's are then used together with additional WRF meteorological factors to improve estimates of PM2.5. Efforts to explore the portability to other urban areas will be discussed. In addition, annual surface ratio maps will be developed illustrating that among the land classes, the urban pixels constitute the largest deviations from the operational model.

Impact of Sensor Degradation on the MODIS NDVI Time Series

NASA Technical Reports Server (NTRS)

Wang, Dongdong; Morton, Douglas Christopher; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert

2012-01-01

Time series of satellite data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent satellite-based measurements. Here, the impact of sensor degradation on trend detection was evaluated using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Terra and Aqua platforms. For Terra MODIS, the impact of blue band (Band 3, 470 nm) degradation on simulated surface reflectance was most pronounced at near-nadir view angles, leading to a 0.001-0.004 yr-1 decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends in MODIS NDVI over North America were consistentwith simulated results,with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and Aqua (6.7%) MODIS sensors during 2002-2010. Planned adjustments to Terra MODIS calibration for Collection 6 data reprocessing will largely eliminate this negative bias in detection of NDVI trends.

Impact of Sensor Degradation on the MODIS NDVI Time Series

NASA Technical Reports Server (NTRS)

Wang, Dongdong; Morton, Douglas; Masek, Jeffrey; Wu, Aisheng; Nagol, Jyoteshwar; Xiong, Xiaoxiong; Levy, Robert; Vermote, Eric; Wolfe, Robert

2011-01-01

Time series of satellite data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent satellite-based measurements. Here, we evaluated the impact of sensor degradation on trend detection using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Terra and Aqua platforms. For Terra MODIS, the impact of blue band (Band 3, 470nm) degradation on simulated surface reflectance was most pronounced at near-nadir view angles, leading to a 0.001-0.004/yr decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends MODIS NDVI over North America were consistent with simulated results, with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and Aqua (6.7%) MODIS sensors during 2002-2010. Planned adjustments to Terra MODIS calibration for Collection 6 data reprocessing will largely eliminate this negative bias in NDVI trends over vegetation.

A sea surface reflectance model for (A)ATSR, and application to aerosol retrievals

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Thomas, G. E.; Grainger, R. G.

2010-07-01

A model of the sea surface bidirectional reflectance distribution function (BRDF) is presented for the visible and near-IR channels (over the spectral range 550 nm to 1.6 μm) of the dual-viewing Along-Track Scanning Radiometers (ATSRs). The intended application is as part of the Oxford-RAL Aerosols and Clouds (ORAC) retrieval scheme. The model accounts for contributions to the observed reflectance from whitecaps, sun-glint and underlight. Uncertainties in the parametrisations used in the BRDF model are propagated through into the forward model and retrieved state. The new BRDF model offers improved coverage over previous methods, as retrievals are possible into the sun-glint region, through the ATSR dual-viewing system. The new model has been applied in the ORAC aerosol retrieval algorithm to process Advanced ATSR (AATSR) data from September 2004 over the south-eastern Pacific. The assumed error budget is shown to be generally appropriate, meaning the retrieved states are consistent with the measurements and a priori assumptions. The resulting field of aerosol optical depth (AOD) is compared with colocated MODIS-Terra observations, AERONET observations at Tahiti, and cruises over the oceanic region. MODIS and AATSR show similar spatial distributions of AOD, although MODIS reports values which are larger and more variable. It is suggested that assumptions in the MODIS aerosol retrieval algorithm may lead to a positive bias in MODIS AOD of order 0.01 at 550 nm over ocean regions where the wind speed is high.

A sea surface reflectance model for (A)ATSR, and application to aerosol retrievals

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Thomas, G. E.; Grainger, R. G.

2010-03-01

A model of the sea surface bidirectional reflectance distribution function (BRDF) is presented for the visible and near-IR channels (over the spectral range 550 nm to 1.6 μm) of the dual-viewing Along-Track Scanning Radiometers (ATSRs). The intended application is as part of the Oxford-RAL Aerosols and Clouds (ORAC) retrieval scheme. The model accounts for contributions to the observed reflectance from whitecaps, sun-glint and underlight. Uncertainties in the parametrisations used in the BRDF model are propagated through into the forward model and retrieved state. The new BRDF model offers improved coverage over previous methods, as retrievals are possible into the sun-glint region, through the ATSR dual-viewing system. The new model has been applied in the ORAC aerosol retrieval algorithm to process Advanced ATSR (AATSR) data from September 2004 over the south-eastern Pacific. The assumed error budget is shown to be generally appropriate, meaning the retrieved states are consistent with the measurements and a priori assumptions. The resulting field of aerosol optical depth (AOD) is compared with colocated MODIS-Terra observations, AERONET observations at Tahiti, and cruises over the oceanic region. MODIS and AATSR show similar spatial distributions of AOD, although MODIS reports values which are larger and more variable. It is suggested that assumptions in the MODIS aerosol retrieval algorithm may lead to a positive bias in MODIS AOD of order 0.01 at 550 nm over ocean regions where the wind speed is high.

Response Versus Scan-Angle Corrections for MODIS Reflective Solar Bands Using Deep Convective Clouds

NASA Technical Reports Server (NTRS)

Bhatt, Rajendra; Angal, Amit; Doelling, David R.; Xiong, Xiaoxiong; Wu, Aisheng; Haney, Conor O.; Scarino, Benjamin R.; Gopalan, Arun

2016-01-01

The absolute radiometric calibration of the reflective solar bands (RSBs) of Aqua- and Terra-MODIS is performed using on-board calibrators. A solar diffuser (SD) panel along with a solar diffuser stability monitor (SDSM) system, which tracks the performance of the SD over time, provides the absolute reference for calibrating the MODIS sensors. MODIS also views the moon and deep space through its space view (SV) port for lunar-based calibration and computing the zero input radiance, respectively. The MODIS instrument views the Earths surface through a two-sided scan mirror, whose reflectance is a function of angle of incidence (AOI) and is described by response versus scan-angle (RVS). The RVS for both MODIS instruments was characterized prior to launch. MODIS also views the SD and the moon at two different assigned RVS positions. There is sufficient evidence that the RVS is changing on orbit over time and as a function of wavelength. The SD and lunar observation scans can only track the RVS variation at two RVS positions. Consequently, the MODIS Characterization Support Team (MCST) developed enhanced approaches that supplement the onboard calibrator measurements with responses from pseudo-invariant desert sites. This approach has been implemented in Level 1B (L1B) Collection 6 (C6) for selected short-wavelength bands. This paper presents an alternative approach of characterizing the mirror RVS to derive the time-dependent RVS correction factors for MODIS RSBs using tropical deep convective cloud (DCC) targets. An initial assessment of the DCC response from Aqua-MODIS band 1 C6 data indicates evidence of RVS artifacts, which are not uniform across the scans and are more prevalent in the left side Earth-view scans.

Response Versus Scan-Angle Corrections for MODIS Reflective Solar Bands Using Deep Convective Clouds

NASA Technical Reports Server (NTRS)

Bhatt, Rajendra; Angal, Amit; Doelling, David R.; Xiong, Xiaoxiong; Wu, Aisheng; Haney, Conor O.; Scarino, Benjamin R.; Gopalan, Arun

2016-01-01

The absolute radiometric calibration of the reflective solar bands (RSBs) of Aqua- and Terra-MODIS is performed using on-board calibrators. A solar diffuser (SD) panel along with a solar diffuser stability monitor (SDSM) system, which tracks the performance of the SD over time, provides the absolute reference for calibrating the MODIS sensors. MODIS also views the moon and deep space through its space view (SV) port for lunar-based calibration and computing the zero input radiance, respectively. The MODIS instrument views the Earth's surface through a two-sided scan mirror, whose reflectance is a function of angle of incidence (AOI) and is described by response versus scan-angle (RVS). The RVS for both MODIS instruments was characterized prior to launch. MODIS also views the SD and the moon at two different assigned RVS positions. There is sufficient evidence that the RVS is changing on orbit over time and as a function of wavelength. The SD and lunar observation scans can only track the RVS variation at two RVS positions. Consequently, the MODIS Characterization Support Team (MCST) developed enhanced approaches that supplement the onboard calibrator measurements with responses from pseudo-invariant desert sites. This approach has been implemented in Level 1B (L1B) Collection 6 (C6) for selected short-wavelength bands. This paper presents an alternative approach of characterizing the mirror RVS to derive the time-dependent RVS correction factors for MODIS RSBs using tropical deep convective cloud (DCC) targets. An initial assessment of the DCC response from Aqua-MODIS band 1 C6 data indicates evidence of RVS artifacts, which are not uniform across the scans and are more prevalent in the left side Earth-view scans.

Response versus scan-angle corrections for MODIS reflective solar bands using deep convective clouds

NASA Astrophysics Data System (ADS)

Bhatt, Rajendra; Angal, Amit; Doelling, David R.; Xiong, Xiaoxiong; Wu, Aisheng; Haney, Conor O.; Scarino, Benjamin R.; Gopalan, Arun

2016-05-01

The absolute radiometric calibration of the reflective solar bands (RSBs) of Aqua- and Terra-MODIS is performed using on-board calibrators. A solar diffuser (SD) panel along with a solar diffuser stability monitor (SDSM) system, which tracks the degradation of the SD over time, provides the baseline for calibrating the MODIS sensors. MODIS also views the moon and deep space through its space view (SV) port for lunar-based calibration and computing the background, respectively. The MODIS instrument views the Earth's surface using a two-sided scan mirror, whose reflectance is a function of the angle of incidence (AOI) and is described by response versus scan-angle (RVS). The RVS for both MODIS instruments was characterized prior to launch. MODIS also views the SD and the moon at two different AOIs. There is sufficient evidence that the RVS is changing on orbit over time and as a function of wavelength. The SD and lunar observation scans can only track the RVS variation at two AOIs. Consequently, the MODIS Characterization Support Team (MCST) developed enhanced approaches that supplement the onboard calibrator measurements with responses from the pseudo-invariant desert sites. This approach has been implemented in Level 1B (L1B) Collection 6 (C6) for select short-wavelength bands. This paper presents an alternative approach of characterizing the mirror RVS to derive the time-dependent RVS correction factors for MODIS RSBs using tropical deep convective cloud (DCC) targets. An initial assessment of the DCC response from Aqua-MODIS band 1 C6 data indicates evidence of RVS artifacts, which are not uniform across the scans and are more prevalent at the beginning of the earth-view scan.

Surface Albedo/BRDF Parameters (Terra/Aqua MODIS)

DOE Data Explorer

Trishchenko, Alexander

2008-01-15

Spatially and temporally complete surface spectral albedo/BRDF products over the ARM SGP area were generated using data from two Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on Terra and Aqua satellites. A landcover-based fitting (LBF) algorithm is developed to derive the BRDF model parameters and albedo product (Luo et al., 2004a). The approach employs a landcover map and multi-day clearsky composites of directional surface reflectance. The landcover map is derived from the Landsat TM 30-meter data set (Trishchenko et al., 2004a), and the surface reflectances are from MODIS 500m-resolution 8-day composite products (MOD09/MYD09). The MOD09/MYD09 data are re-arranged into 10-day intervals for compatibility with other satellite products, such as those from the NOVA/AVHRR and SPOT/VGT sensors. The LBF method increases the success rate of the BRDF fitting process and enables more accurate monitoring of surface temporal changes during periods of rapid spring vegetation green-up and autumn leaf-fall, as well as changes due to agricultural practices and snowcover variations (Luo et al., 2004b, Trishchenko et al., 2004b). Albedo/BRDF products for MODIS on Terra and MODIS on Aqua, as well as for Terra/Aqua combined dataset, are generated at 500m spatial resolution and every 10-day since March 2000 (Terra) and July 2002 (Aqua and combined), respectively. The purpose for the latter product is to obtain a more comprehensive dataset that takes advantages of multi-sensor observations (Trishchenko et al., 2002). To fill data gaps due to cloud presence, various interpolation procedures are applied based on a multi-year observation database and referring to results from other locations with similar landcover property. Special seasonal smoothing procedure is also applied to further remove outliers and artifacts in data series.

Impact of Spatial Sampling on Continuity of MODIS-VIIRS Land Surface Reflectance Products: A Simulation Approach

NASA Technical Reports Server (NTRS)

Pahlevan, Nima; Sarkar, Sudipta; Devadiga, Sadashiva; Wolfe, Robert E.; Roman, Miguel; Vermote, Eric; Lin, Guoqing; Xiong, Xiaoxiong

2016-01-01

With the increasing need to construct long-term climate-quality data records to understand, monitor, and predict climate variability and change, it is vital to continue systematic satellite measurements along with the development of new technology for more quantitative and accurate observations. The Suomi National Polar-orbiting Partnership mission provides continuity in monitoring the Earths surface and its atmosphere in a similar fashion as the heritage MODIS instruments onboard the National Aeronautics and Space Administrations Terra and Aqua satellites. In this paper, we aim at quantifying the consistency of Aqua MODIS and Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Reflectance (LSR) and NDVI products as related to their inherent spatial sampling characteristics. To avoid interferences from sources of measurement and/or processing errors other than spatial sampling, including calibration, atmospheric correction, and the effects of the bidirectional reflectance distribution function, the MODIS and VIIRSLSR products were simulated using the Landsat-8s Operational Land Imager (OLI) LSR products. The simulations were performed using the instruments point spread functions on a daily basis for various OLI scenes over a 16-day orbit cycle. It was found that the daily mean differences due to discrepancies in spatial sampling remain below 0.0015 (1) in absolute surface reflectance at subgranule scale (i.e., OLI scene size).We also found that the MODISVIIRS product intercomparisons appear to be minimally impacted when differences in the corresponding view zenith angles (VZAs) are within the range of -15deg to -35deg (VZA(sub v) - VZA(sub m)), where VIIRS and MODIS footprints resemble in size. In general, depending on the spatial heterogeneity of the OLI scene contents, per-grid-cell differences can reach up to 20.Further spatial analysis of the simulated NDVI and LSR products revealed that, depending on the user accuracy requirements for product intercomparisons, spatial aggregations may be used. It was found that if per-grid-cell differences on the order of 10(in LSR or NDVI) are tolerated, the product intercomparisons are expected to be immune from differences in spatial sampling.

A New, More Physically Based Algorithm, for Retrieving Aerosol Properties over Land from MODIS

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Kaufman, Yoram J.; Remer, Lorraine A.; Mattoo, Shana

2004-01-01

The MOD Imaging Spectrometer (MODIS) has been successfully retrieving aerosol properties, beginning in early 2000 from Terra and from mid 2002 from Aqua. Over land, the retrieval algorithm makes use of three MODIS channels, in the blue, red and infrared wavelengths. As part of the validation exercises, retrieved spectral aerosol optical thickness (AOT) has been compared via scatterplots against spectral AOT measured by the global Aerosol Robotic NETwork (AERONET). On one hand, global and long term validation looks promising, with two-thirds (average plus and minus one standard deviation) of all points falling between published expected error bars. On the other hand, regression of these points shows a positive y-offset and a slope less than 1.0. For individual regions, such as along the U.S. East Coast, the offset and slope are even worse. Here, we introduce an overhaul of the algorithm for retrieving aerosol properties over land. Some well-known weaknesses in the current aerosol retrieval from MODIS include: a) rigid assumptions about the underlying surface reflectance, b) limited aerosol models to choose from, c) simplified (scalar) radiative transfer (RT) calculations used to simulate satellite observations, and d) assumption that aerosol is transparent in the infrared channel. The new algorithm attempts to address all four problems: a) The new algorithm will include surface type information, instead of fixed ratios of the reflectance in the visible channels to the mid-IR reflectance. b) It will include updated aerosol optical properties to reflect the growing aerosol retrieved from eight-plus years of AERONE". operation. c) The effects of polarization will be including using vector RT calculations. d) Most importantly, the new algorithm does not assume that aerosol is transparent in the infrared channel. It will be an inversion of reflectance observed in the three channels (blue, red, and infrared), rather than iterative single channel retrievals. Thus, this new formulation of the MODIS aerosol retrieval over land includes more physically based surface, aerosol and radiative transfer with fewer potentially erroneous assumptions.

Ground based measurements on reflectance towards validating atmospheric correction algorithms on IRS-P6 AWiFS data

NASA Astrophysics Data System (ADS)

Rani Sharma, Anu; Kharol, Shailesh Kumar; Kvs, Badarinath; Roy, P. S.

In Earth observation, the atmosphere has a non-negligible influence on the visible and infrared radiation which is strong enough to modify the reflected electromagnetic signal and at-target reflectance. Scattering of solar irradiance by atmospheric molecules and aerosol generates path radiance, which increases the apparent surface reflectance over dark surfaces while absorption by aerosols and other molecules in the atmosphere causes loss of brightness to the scene, as recorded by the satellite sensor. In order to derive precise surface reflectance from satellite image data, it is indispensable to apply the atmospheric correction which serves to remove the effects of molecular and aerosol scattering. In the present study, we have implemented a fast atmospheric correction algorithm to IRS-P6 AWiFS satellite data which can effectively retrieve surface reflectance under different atmospheric and surface conditions. The algorithm is based on MODIS climatology products and simplified use of Second Simulation of Satellite Signal in Solar Spectrum (6S) radiative transfer code, which is used to generate look-up-tables (LUTs). The algorithm requires information on aerosol optical depth for correcting the satellite dataset. The proposed method is simple and easy to implement for estimating surface reflectance from the at sensor recorded signal, on a per pixel basis. The atmospheric correction algorithm has been tested for different IRS-P6 AWiFS False color composites (FCC) covering the ICRISAT Farm, Patancheru, Hyderabad, India under varying atmospheric conditions. Ground measurements of surface reflectance representing different land use/land cover, i.e., Red soil, Chick Pea crop, Groundnut crop and Pigeon Pea crop were conducted to validate the algorithm and found a very good match between surface reflectance and atmospherically corrected reflectance for all spectral bands. Further, we aggregated all datasets together and compared the retrieved AWiFS reflectance with aggregated ground measurements which showed a very good correlation of 0.96 in all four spectral bands (i.e. green, red, NIR and SWIR). In order to quantify the accuracy of the proposed method in the estimation of the surface reflectance, the root mean square error (RMSE) associated to the proposed method was evaluated. The analysis of the ground measured versus retrieved AWiFS reflectance yielded smaller RMSE values in case of all four spectral bands. EOS TERRA/AQUA MODIS derived AOD exhibited very good correlation of 0.92 and the data sets provides an effective means for carrying out atmospheric corrections in an operational way. Keywords: Atmospheric correction, 6S code, MODIS, Spectroradiometer, Sun-Photometer

The effect of variations in relative spectral response on the retrieval of land surface parameters from multiple sources of remotely sensed imagery

USGS Publications Warehouse

Meyer, D.J.; Chander, G.

2008-01-01

Airborne Visible Infrared Imaging Spectrometer (AVIRIS) images , collected over Sioux Falls, South Dakota, were used to quantify the effect of spectral response on different surface materials and to develop spectral "figures-of-merit" for spectral responses covering similar, but not identical spectral bands. In this simulation, AVIRIS images were converted to radiance, then spectrally resampled to six wavelength bands commonly used for terrestrial observation. Preliminary results indicate that differences between the simulations can be attributed to variations in surface reflectance within spectral bands, and suggest influences due to water vapor absorption. Radiance simulated from the spectrally narrow Moderate Resolution Imaging Spectroradiometer (MODIS) Relative Spectral Responses (RSR) was generally higher than that using the broader Enhanced Thematic Mapper Plus (ETM+) RSRs over most targets encountered over the test area. This is consistent with many MODIS bands being biased toward shorter wavelengths compared to corresponding ETM+ bands when viewing targets whose radiance decreases with wavelength. In some cases the higher radiance values appeared to occur where the MODIS RSR is better situated over peak reflected wavelengths. Simulation differences between MODIS & ETM+ bands in the near-infrared indicated higher MODIS radiance values that suggest the influence of water vapor absorption at 820 nanometers. This result agreed with water vapor values retrieved from the AVIRIS images themselves at around 2.7 cm precipitable water, and measurements made at a nearby AERONET node at around 2.8cm during the AVIRIS overflight ?? 2007 IEEE.

Multiplatform observations enabling albedo retrievals with high temporal resolution

NASA Astrophysics Data System (ADS)

Riihelä, Aku; Manninen, Terhikki; Key, Jeffrey; Sun, Qingsong; Sütterlin, Melanie; Lattanzio, Alessio; Schaaf, Crystal

2017-04-01

In this paper we show that combining observations from different polar orbiting satellite families (such as AVHRR and MODIS) is physically justifiable and technically feasible. Our proposed approach will lead to surface albedo retrievals at higher temporal resolution than the state of the art, with comparable or better accuracy. This study is carried out in the World Meteorological Organization (WMO) Sustained and coordinated processing of Environmental Satellite data for Climate Monitoring (SCOPE-CM) project SCM-02 (http://www.scope-cm.org/projects/scm-02/). Following a spectral homogenization of the Top-of-Atmosphere reflectances of bands 1 & 2 from AVHRR and MODIS, both observation datasets are atmospherically corrected with a coherent atmospheric profile and algorithm. The resulting surface reflectances are then fed into an inversion of the RossThick-LiSparse-Reciprocal surface bidirectional reflectance distribution function (BRDF) model. The results of the inversion (BRDF kernels) may then be integrated to estimate various surface albedo quantities. A key principle here is that the larger number of valid surface observations with multiple satellites allows us to invert the BRDF coefficients within a shorter time span, enabling the monitoring of relatively rapid surface phenomena such as snowmelt. The proposed multiplatform approach is expected to bring benefits in particular to the observation of the albedo of the polar regions, where persistent cloudiness and long atmospheric path lengths present challenges to satellite-based retrievals. Following a similar logic, the retrievals over tropical regions with high cloudiness should also benefit from the method. We present results from a demonstrator dataset of a global combined AVHRR-GAC and MODIS dataset covering the year 2010. The retrieved surface albedo is compared against quality-monitored in situ albedo observations from the Baseline Surface Radiation Network (BSRN). Additionally, the combined retrieval dataset is compared against MODIS C6 albedo/BRDF datasets to assess the quality of the multiplatform approach against current state of the art. This approach is not limited to AHVRR and MODIS observations. Provided that the spectral homogenization produces an acceptably good match, any instrument observing the Earth's surface in the visible and near-infrared wavelengths could, in principal, be included to further enhance the temporal resolution and accuracy of the retrievals. The SCOPE-CM initiative provides a potential framework for such expansion in the future.

An assessment of thin cloud detection by applying bidirectional reflectance distribution function model-based background surface reflectance using Geostationary Ocean Color Imager (GOCI): A case study for South Korea

NASA Astrophysics Data System (ADS)

Kim, Hye-Won; Yeom, Jong-Min; Shin, Daegeun; Choi, Sungwon; Han, Kyung-Soo; Roujean, Jean-Louis

2017-08-01

In this study, a new assessment of thin cloud detection with the application of bidirectional reflectance distribution function (BRDF) model-based background surface reflectance was undertaken by interpreting surface spectra characterized using the Geostationary Ocean Color Imager (GOCI) over a land surface area. Unlike cloud detection over the ocean, the detection of cloud over land surfaces is difficult due to the complicated surface scattering characteristics, which vary among land surface types. Furthermore, in the case of thin clouds, in which the surface and cloud radiation are mixed, it is difficult to detect the clouds in both land and atmospheric fields. Therefore, to interpret background surface reflectance, especially underneath cloud, the semiempirical BRDF model was used to simulate surface reflectance by reflecting solar angle-dependent geostationary sensor geometry. For quantitative validation, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data were used to make a comparison with the proposed cloud masking result. As a result, the new cloud masking scheme resulted in a high probability of detection (POD = 0.82) compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) (POD = 0.808) for all cloud cases. In particular, the agreement between the CALIPSO cloud product and new GOCI cloud mask was over 94% when detecting thin cloud (e.g., altostratus and cirrus) from January 2014 to June 2015. This result is relatively high in comparison with the result from the MODIS Collection 6 cloud mask product (MYD35).

Multitemporal cross-calibration of the Terra MODIS and Landsat 7 ETM+ reflective solar bands

USGS Publications Warehouse

Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng; Chander, Gyanesh; Choi, Taeyoung

2013-01-01

In recent years, there has been a significant increase in the use of remotely sensed data to address global issues. With the open data policy, the data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) sensors have become a critical component of numerous applications. These two sensors have been operational for more than a decade, providing a rich archive of multispectral imagery for analysis of mutitemporal remote sensing data. This paper focuses on evaluating the radiometric calibration agreement between MODIS and ETM+ using the near-simultaneous and cloud-free image pairs over an African pseudo-invariant calibration site, Libya 4. To account for the combined uncertainties in the top-of-atmosphere (TOA) reflectance due to surface and atmospheric bidirectional reflectance distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA reflectance to the same illumination and viewing geometry. In addition, the spectra from the Earth Observing-1 (EO-1) Hyperion were used to compute spectral corrections between the corresponding MODIS and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all MODIS and ETM+ data pairs, MODerate resolution atmospheric TRANsmission (MODTRAN) 5.0 simulations were also used to adjust for differences due to the presence or lack of absorption features in some of the bands. A MODIS split-window algorithm provides the atmospheric water vapor column abundance during the overpasses for the MODTRAN simulations. Additionally, the column atmospheric water vapor content during the overpass was retrieved using the MODIS precipitable water vapor product. After performing these adjustments, the radiometric cross-calibration of the two sensors was consistent to within 7%. Some drifts in the response of the bands are evident, with MODIS band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 MODIS processing.

Multitemporal Cross-Calibration of the Terra MODIS and Landsat 7 ETM+ Reflective Solar Bands

NASA Technical Reports Server (NTRS)

Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng; Changler, Gyanesh; Choi, Taeyoyung

2013-01-01

In recent years, there has been a significant increase in the use of remotely sensed data to address global issues. With the open data policy, the data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) sensors have become a critical component of numerous applications. These two sensors have been operational for more than a decade, providing a rich archive of multispectral imagery for analysis of mutitemporal remote sensing data. This paper focuses on evaluating the radiometric calibration agreement between MODIS and ETM+ using the near-simultaneous and cloud-free image pairs over an African pseudo-invariant calibration site, Libya 4. To account for the combined uncertainties in the top-of-atmosphere (TOA) reflectance due to surface and atmospheric bidirectional reflectance distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA reflectance to the same illumination and viewing geometry. In addition, the spectra from the Earth Observing-1 (EO-1) Hyperion were used to compute spectral corrections between the corresponding MODIS and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all MODIS and ETM+ data pairs, MODerate resolution atmospheric TRANsmission (MODTRAN) 5.0 simulations were also used to adjust for differences due to the presence or lack of absorption features in some of the bands. A MODIS split-window algorithm provides the atmospheric water vapor column abundance during the overpasses for the MODTRAN simulations. Additionally, the column atmospheric water vapor content during the overpass was retrieved using the MODIS precipitable water vapor product. After performing these adjustments, the radiometric cross-calibration of the two sensors was consistent to within 7%. Some drifts in the response of the bands are evident, with MODIS band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 MODIS processing.

A new technique for fire risk estimation in the wildland urban interface

NASA Astrophysics Data System (ADS)

Dasgupta, S.; Qu, J. J.; Hao, X.

A novel technique based on the physical variable of pre-ignition energy is proposed for assessing fire risk in the Grassland-Urban-Interface The physical basis lends meaning a site and season independent applicability possibilities for computing spread rates and ignition probabilities features contemporary fire risk indices usually lack The method requires estimates of grass moisture content and temperature A constrained radiative-transfer inversion scheme on MODIS NIR-SWIR reflectances which reduces solution ambiguity is used for grass moisture retrieval while MODIS land surface temperature emissivity products are used for retrieving grass temperature Subpixel urban contamination of the MODIS reflective and thermal signals over a Grassland-Urban-Interface pixel is corrected using periodic estimates of urban influence from high spatial resolution ASTER

Characterizing LEDAPS surface reflectance products by comparisons with AERONET, field spectrometer, and MODIS data

USGS Publications Warehouse

Maiersperger, Tom; Scaramuzza, Pat; Leigh, Larry; Shrestha, S.; Gallo, Kevin; Jenkerson, Calli B.; Dwyer, John L.

2013-01-01

This study provides a baseline quality check on provisional Landsat Surface Reflectance (SR) products as generated by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center using Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software. Characterization of the Landsat SR products leveraged comparisons between aerosol optical thickness derived from LEDAPS and measured by Aerosol Robotic Network (AERONET), as well as reflectance correlations with field spectrometer and Moderate Resolution Imaging Spectroradiometer (MODIS) data. Results consistently indicated similarity between LEDAPS and alternative data products in longer wavelengths over vegetated areas with no adjacent water, while less reliable performance was observed in shorter wavelengths and sparsely vegetated areas. This study demonstrates the strengths and weaknesses of the atmospheric correction methodology used in LEDAPS, confirming its successful implementation to generate Landsat SR products.

An operational MODIS aerosol retrieval algorithm at high spatial resolution, and its application over a complex urban region

NASA Astrophysics Data System (ADS)

Wong, Man Sing; Nichol, Janet E.; Lee, Kwon Ho

2011-03-01

Aerosol retrieval algorithms for the MODerate Resolution Imaging Spectroradiometer (MODIS) have been developed to estimate aerosol and microphysical properties of the atmosphere, which help to address aerosol climatic issues at global scale. However, higher spatial resolution aerosol products for urban areas have not been well-researched mainly due to the difficulty of differentiating aerosols from bright surfaces in urban areas. Here, an aerosol retrieval algorithm using the MODIS 500-m resolution bands is described, to retrieve aerosol properties over Hong Kong and the Pearl River Delta region. The rationale of our technique is to first estimate the aerosol reflectances by decomposing the top-of-atmosphere reflectances from surface reflectances and Rayleigh path reflectances. For the determination of surface reflectances, a Minimum Reflectance Technique (MRT) is used, and MRT images are computed for different seasons. For conversion of aerosol reflectance to aerosol optical thickness (AOT), comprehensive Look Up Tables specific to the local region are constructed, which consider aerosol properties and sun-viewing geometry in the radiative transfer calculations. Four local aerosol types, namely coastal urban, polluted urban, dust, and heavy pollution, were derived using cluster analysis on 3 years of AERONET measurements in Hong Kong. The resulting 500 m AOT images were found to be highly correlated with ground measurements from the AERONET (r2 = 0.767) and Microtops II sunphotometers (r2 = 0.760) in Hong Kong. This study further demonstrates the application of the fine resolution AOT images for monitoring inter-urban and intra-urban aerosol distributions and the influence of trans-boundary flows. These applications include characterization of spatial patterns of AOT within the city, and detection of regional biomass burning sources.

The Generation of Near-Real Time Data Products for MODIS

NASA Astrophysics Data System (ADS)

Teague, M.; Schmaltz, J. E.; Ilavajhala, S.; Ye, G.; Masuoka, E.; Murphy, K. J.; Michael, K.

2010-12-01

The GSFC Terrestrial Information Systems Branch (614.5) operate the Land and Atmospheres Near-real-time Capability for EOS (LANCE-MODIS) system. Other LANCE elements include -AIRS, -MLS, -OMI, and -AMSR-E. LANCE-MODIS incorporates the former Rapid Response system and will, in early 2011, include the Fire Information for Resource Management System (FIRMS). The purpose of LANCE is to provide applications users with a variety of products on a near-real time basis. The LANCE-MODIS data products include Level 1 (L1), L2 fire, snow, sea ice, cloud mask/profiles, aerosols, clouds, land surface reflectance, land surface temperature, and L2G and L3 gridded, daily, land surface reflectance products. Data are available either by ftp access (pull) or by subscription (push) and the L1 and L2 data products are available within an average of 2.5 hours of the observation time. The use of ancillary data products input to the standard science algorithms has been modified in order to obtain these latencies. The resulting products have been approved for applications use by the MODIS Science Team. The http://lance.nasa.gov site provides registration information and extensive information concerning the MODIS data products and imagery including a comparison between the LANCE-MODIS and the standard science-quality products generated by the MODAPS system. The LANCE-MODIS system includes a variety of tools that enable users to manipulate the data products including: parameter, band, and geographic subsetting, re-projection, mosaicing, and generation of data in the GeoTIFF format. In most instances the data resulting from use of these tools has a latency of less than 3 hours. Access to these tools is available through a Web Coverage Service. A Google Earth/Web Mapping Service is available to access image products. LANCE-MODIS supports a wide variety of applications users in civilian, military, and foreign agencies as well as universities and the private sector. Examples of applications are: Flood Mapping, Famine relief, Food and Agriculture, Hazards and Disasters, and Weather.

Evaluation of MODIS aerosol optical depth for semi­-arid environments in complex terrain

NASA Astrophysics Data System (ADS)

Holmes, H.; Loria Salazar, S. M.; Panorska, A. K.; Arnott, W. P.; Barnard, J.

2015-12-01

The use of satellite remote sensing to estimate spatially resolved ground level air pollutant concentrations is increasing due to advancements in remote sensing technology and the limited number of surface observations. Satellite retrievals provide global, spatiotemporal air quality information and are used to track plumes, estimate human exposures, model emissions, and determine sources (i.e., natural versus anthropogenic) in regulatory applications. Ground level PM2.5 concentrations can be estimated using columnar aerosol optical depth (AOD) from MODIS, where the satellite retrieval serves as a spatial surrogate to simulate surface PM2.5 gradients. The spatial statistical models and MODIS AOD retrieval algorithms have been evaluated for the dark, vegetated eastern US, while the semi-arid western US continues to be an understudied region with associated complexity due to heterogeneous emissions, smoke from wildfires, and complex terrain. The objective of this work is to evaluate the uncertainty of MODIS AOD retrievals by comparing with columnar AOD and surface PM2.5 measurements from AERONET and EPA networks. Data is analyzed from multiple stations in California and Nevada for three years where four major wildfires occurred. Results indicate that MODIS retrievals fail to estimate column-integrated aerosol pollution in the summer months. This is further investigated by quantifying the statistical relationships between MODIS AOD, AERONET AOD, and surface PM2.5 concentrations. Data analysis indicates that the distribution of MODIS AOD is significantly (p<0.05) different than AERONET AOD. Further, using the results of distributional and association analysis the impacts of MODIS AOD uncertainties on the spatial gradients are evaluated. Additionally, the relationships between these uncertainties and physical parameters in the retrieval algorithm (e.g., surface reflectance, Ångström Extinction Exponent) are discussed.

Generating Land Surface Reflectance for the New Generation of Geostationary Satellite Sensors with the MAIAC Algorithm

NASA Astrophysics Data System (ADS)

Wang, W.; Wang, Y.; Hashimoto, H.; Li, S.; Takenaka, H.; Higuchi, A.; Lyapustin, A.; Nemani, R. R.

2017-12-01

The latest generation of geostationary satellite sensors, including the GOES-16/ABI and the Himawari 8/AHI, provide exciting capability to monitor land surface at very high temporal resolutions (5-15 minute intervals) and with spatial and spectral characteristics that mimic the Earth Observing System flagship MODIS. However, geostationary data feature changing sun angles at constant view geometry, which is almost reciprocal to sun-synchronous observations. Such a challenge needs to be carefully addressed before one can exploit the full potential of the new sources of data. Here we take on this challenge with Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, recently developed for accurate and globally robust applications like the MODIS Collection 6 re-processing. MAIAC first grids the top-of-atmosphere measurements to a fixed grid so that the spectral and physical signatures of each grid cell are stacked ("remembered") over time and used to dramatically improve cloud/shadow/snow detection, which is by far the dominant error source in the remote sensing. It also exploits the changing sun-view geometry of the geostationary sensor to characterize surface BRDF with augmented angular resolution for accurate aerosol retrievals and atmospheric correction. The high temporal resolutions of the geostationary data indeed make the BRDF retrieval much simpler and more robust as compared with sun-synchronous sensors such as MODIS. As a prototype test for the geostationary-data processing pipeline on NASA Earth Exchange (GEONEX), we apply MAIAC to process 18 months of data from Himawari 8/AHI over Australia. We generate a suite of test results, including the input TOA reflectance and the output cloud mask, aerosol optical depth (AOD), and the atmospherically-corrected surface reflectance for a variety of geographic locations, terrain, and land cover types. Comparison with MODIS data indicates a general agreement between the retrieved surface reflectance products. Furthermore, the geostationary results satisfactorily capture the movement of clouds and variations in atmospheric dust/aerosol concentrations, suggesting that high quality land surface and vegetation datasets from the advanced geostationary sensors can help complement and improve the corresponding EOS products.

Scientific impact of MODIS C5 calibration degradation and C6+ improvements

NASA Astrophysics Data System (ADS)

Lyapustin, A.; Wang, Y.; Xiong, X.; Meister, G.; Platnick, S.; Levy, R.; Franz, B.; Korkin, S.; Hilker, T.; Tucker, J.; Hall, F.; Sellers, P.; Wu, A.; Angal, A.

2014-12-01

The Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) MODIS Terra and, to lesser extent, in MODIS Aqua geophysical data sets. Sensor degradation is largest in the blue band (B3) of the MODIS sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple MODIS C5 products including the dark target algorithm's aerosol optical depth over land and Ångström exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface reflectance and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad MODIS user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6+ calibration of the MODIS data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as detrending and Terra-Aqua cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the MODIS ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface reflectance (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on the order of several tenths of 1% of the top-of-atmosphere (TOA) reflectance in the visible and near-infrared MODIS bands B1-B4, and provides a good consistency between the two MODIS sensors. MAIAC analysis over the southern USA shows that the C6+ approach removed an additional negative decadal trend of Terra ΔNDVI ~ 0.01 as compared to Aqua data. This change is particularly important for analysis of vegetation dynamics and trends in the tropics, e.g., Amazon rainforest, where the morning orbit of Terra provides considerably more cloud-free observations compared to the afternoon Aqua measurements.

Scientific Impact of MODIS C5 Calibration Degradation and C6+ Improvements

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Xiong, X.; Meister, G.; Platnick, S.; Levy, R.; Franz, B.; Korkin, S.; Hilker, T.; Tucker, J.;

The global blue-sky albedo change between 2000 - 2015 seen from MODIS

NASA Astrophysics Data System (ADS)

Chrysoulakis, N.; Mitraka, Z.; Gorelick, N.

2016-12-01

The land surface albedo is a critical physical variable, which influences the Earth's climate by affecting the energy budget and distribution in the Earth-atmosphere system. Blue-sky albedo estimates provide a quantitative means for better constraining global and regional scale climate models. The Moderate Resolution Imaging Spectroradiometer (MODIS) albedo product includes parameters for the estimation of both the directional-hemispherical surface reflectance (black-sky albedo) and the bi-hemispherical surface reflectance (white-sky albedo). This dataset was used here for the blue-sky albedo estimation over the globe on an 8-day basis at 0.5 km spatial resolution for the whole time period covered by MODIS acquisitions (i.e. 2000 until today). To estimate the blue-sky albedo, the fraction of the diffused radiation is needed, a function of the Aerosol Optical Thickness (AOT). Required AOT information was acquired from the MODIS AOT product at 1̊ × 1̊ spatial resolution. Since the blue-sky albedo depends on the solar zenith angle (SZA), the 8-day mean blue-sky albedo values were computed as averages of the corresponding values for the representative SZAs covering the 24-hour day. The estimated blue-sky albedo time series was analyzed to capture changes during the 15 period. All computation were performed using the Google Earth Engine (GEE). The GEE provided access to all the MODIS products needed for the analysis without the need of searching or downloading. Moreover, the combination of MODIS products in both temporal and spatial terms was fast and effecting using the GEE API (Application Program Interface). All the products covering the globe and for the time period of 15 years were processed via a single collection. Most importantly, GEE allowed for including the calculation of SZAs covering the 24-hour day which improves the quality of the overall product. The 8-day global products of land surface albedo are available through http://www.rslab.gr/downloads.html

Discrepancy Between ASTER- and MODIS- Derived Land Surface Temperatures: Terrain Effects

PubMed Central

Liu, Yuanbo; Noumi, Yousuke; Yamaguchi, Yasushi

2009-01-01

The MODerate resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) are onboard the same satellite platform NASA TERRA. Both MODIS and ASTER offer routine retrieval of land surface temperatures (LSTs), and the ASTER- and MODIS-retrieved LST products have been used worldwide. Because a large fraction of the earth surface consists of mountainous areas, variations in elevation, terrain slope and aspect angles can cause biases in the retrieved LSTs. However, terrain-induced effects are generally neglected in most satellite retrievals, which may generate discrepancy between ASTER and MODIS LSTs. In this paper, we reported the terrain effects on the LST discrepancy with a case examination over a relief area at the Loess Plateau of China. Results showed that the terrain-induced effects were not major, but nevertheless important for the total LST discrepancy. A large local slope did not necessarily lead to a large LST discrepancy. The angle of emitted radiance was more important than the angle of local slope in generating the LST discrepancy. Specifically, the conventional terrain correction may be unsuitable for densely vegetated areas. The distribution of ASTER-to-MODIS emissivity suggested that the terrain correction was included in the generalized split window (GSW) based approach used to rectify MODIS LSTs. Further study should include the classification-induced uncertainty in emissivity for reliable use of satellite-retrieved LSTs over relief areas. PMID:22399955

The Global Aerosol System As Viewed By MODIS Today

NASA Technical Reports Server (NTRS)

Remer, Lorraine

2008-01-01

The MODerate resolution Imaging Spectroradiometer (MODIS) aerosol algorithms have been working steadily since early 2000 to transform the MODIS-measured spectral solar reflectance from the Earth's surface and atmosphere into a variety of aerosol products. In this lecture I will proceed through a survey of these products, answering the following questions as I proceed. What are the products? How do they compare with ground truth? How do we use these products to describe the global aerosol system? Are aerosols increasing or decreasing? How do aerosols affect climate and clouds?

Accessing and Understanding MODIS Data

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Jenkerson, Calli B.; Jodha, Siri

2003-01-01

The National Aeronautics and Space Administration (NASA) launched the Terra satellite in December 1999, as part of the Earth Science Enterprise promotion of interdisciplinary studies of the integrated Earth system. Aqua, the second satellite from the series of EOS constellation, was launched in May 2002. Both satellites carry the MODerate resolution Imaging Spectroradiometer (MODIS) instrument. MODIS data are processed at the Goddard Space Flight Center, Greenbelt, MD, and then archived and distributed by the Distributed Active Archive Centers (DAACs). Data products from the MODIS sensors present new challenges to remote sensing scientists due to specialized production level, data format, and map projection. MODIS data are distributed as calibrated radiances and as higher level products such as: surface reflectance, water-leaving radiances, ocean color and sea surface temperature, land surface kinetic temperature, vegetation indices, leaf area index, land cover, snow cover, sea ice extent, cloud mask, atmospheric profiles, aerosol properties, and many other geophysical parameters. MODIS data are stored in HDF- EOS format in both swath format and in several different map projections. This tutorial guides users through data set characteristics as well as search and order interfaces, data unpacking, data subsetting, and potential applications of the data. A CD-ROM with sample data sets, and software tools for working with the data will be provided to the course participants.

Using NASA's Interactive Visualization and Image Extraction Tool AppEEARS to Assess Differences between MODIS and VIIRS

NASA Astrophysics Data System (ADS)

Neeley, S.

2017-12-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor aboard the Suomi-NPP satellite is designed to provide data continuity with the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard NASA's Terra and Aqua satellites. VIIRS data products are generated in a similar format as MODIS using modified algorithms and aim to extend the data lifecycle of MODIS products, which are widely used in a variety of scientific disciplines. However, there are differences in the characteristics of the instruments that could influence decision making when conducting a study involving a combination of products from both sensors. Inter-sensor comparison studies between VIIRS and MODIS have highlighted some of the inconsistencies between the sensors, including calibrated radiances, pixel sizes, swath widths, and spectral response functions of the bands. These differences should be well-understood among the science community as these inconsistencies could potentially effect the results of time-series analyses or land change studies that rely on using VIIRS and MODIS data products in combination. An efficient method to identify and better understand differences between data products will allow for the science community to make informed decisions when conducting analyses using a combination of VIIRS and MODIS data products. NASA's Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) tool enables users to efficiently compare MODIS and VIIRS data products, including surface reflectance from 2012 to present. AppEEARS is a user-friendly image extraction tool used to order spatial and temporal data subsets, reproject data, and visualize output sample results before data download. AppEEARs allows users to compare MODIS and VIIRS data products by providing interactive visualizations and summary statistics of each dataset-either over a specific point or region of interest across a period of time. This tool enhances decision-making when using newly available VIIRS products combined with MODIS as it allows for data inconsistencies to be explored before the data is downloaded. Here, we demonstrate how AppEEARS enables users to perform comparisons across VIIRS and MODIS Surface Reflectance products and provide a detailed review of characteristic differences between the instruments.

Multi-Resolution Analysis of MODIS and ASTER Satellite Data for Water Classification

DTIC Science & Technology

2006-09-01

spectral bands, but also with different pixel resolutions . The overall goal... the total water surface. Due to the constraint that high spatial resolution satellite images are low temporal resolution , one needs a reliable method...at 15 m resolution , were processed. We used MODIS reflectance data from MOD02 Level 1B data. Even the spatial resolution of the 1240 nm

Effect of Spectrally Varying Albedo of Vegetation Surfaces on Shortwave Radiation Fluxes and Aerosol Direct Radiative Forcing

NASA Technical Reports Server (NTRS)

Zhu, L.; Martins, J. V.; Yu, H.

2012-01-01

This study develops an algorithm for representing detailed spectral features of vegetation albedo based on Moderate Resolution Imaging Spectrometer (MODIS) observations at 7 discrete channels, referred to as the MODIS Enhanced Vegetation Albedo (MEVA) algorithm. The MEVA algorithm empirically fills spectral gaps around the vegetation red edge near 0.7 micrometers and vegetation water absorption features at 1.48 and 1.92 micrometers which cannot be adequately captured by the MODIS 7 channels. We then assess the effects of applying MEVA in comparison to four other traditional approaches to calculate solar fluxes and aerosol direct radiative forcing (DRF) at the top of atmosphere (TOA) based on the MODIS discrete reflectance bands. By comparing the DRF results obtained through the MEVA method with the results obtained through the other four traditional approaches, we show that filling the spectral gap of the MODIS measurements around 0.7 micrometers based on the general spectral behavior of healthy green vegetation leads to significant improvement in the instantaneous aerosol DRF at TOA (up to 3.02Wm(exp -2) difference or 48% fraction of the aerosol DRF, .6.28Wm(exp -2), calculated for high spectral resolution surface reflectance from 0.3 to 2.5 micrometers for deciduous vegetation surface). The corrections of the spectral gaps in the vegetation spectrum in the near infrared, again missed by the MODIS reflectances, also contributes to improving TOA DRF calculations but to a much lower extent (less than 0.27Wm(exp -2), or about 4% of the instantaneous DRF). Compared to traditional approaches, MEVA also improves the accuracy of the outgoing solar flux between 0.3 to 2.5 micrometers at TOA by over 60Wm(exp -2) (for aspen 3 surface) and aerosol DRF by over 10Wm(exp -2) (for dry grass). Specifically, for Amazon vegetation types, MEVA can improve the accuracy of daily averaged aerosol radiative forcing in the spectral range of 0.3 to 2.5 micrometers at equator at the equinox by 3.7Wm(exp -2). These improvements indicate that MEVA can contribute to regional climate studies over vegetated areas and can help to improve remote sensing-based studies of climate processes and climate change.

Determination of the single scattering albedo and direct radiative forcing of biomass burning aerosol with data from the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite instrument

NASA Astrophysics Data System (ADS)

Zhu, Li

Biomass burning aerosols absorb and scatter solar radiation and therefore affect the energy balance of the Earth-atmosphere system. The single scattering albedo (SSA), the ratio of the scattering coefficient to the extinction coefficient, is an important parameter to describe the optical properties of aerosols and to determine the effect of aerosols on the energy balance of the planet and climate. Aerosol effects on radiation also depend strongly on surface albedo. Large uncertainties remain in current estimates of radiative impacts of biomass burning aerosols, due largely to the lack of reliable measurements of aerosol and surface properties. In this work we investigate how satellite measurements can be used to estimate the direct radiative forcing of biomass burning aerosols. We developed a method using the critical reflectance technique to retrieve SSA from the Moderate Resolution Imaging Spectroradiometer (MODIS) observed reflectance at the top of the atmosphere (TOA). We evaluated MODIS retrieved SSAs with AErosol RObotic NETwork (AERONET) retrievals and found good agreements within the published uncertainty of the AERONET retrievals. We then developed an algorithm, the MODIS Enhanced Vegetation Albedo (MEVA), to improve the representations of spectral variations of vegetation surface albedo based on MODIS observations at the discrete 0.67, 0.86, 0.47, 0.55, 1.24, 1.64, and 2.12 mu-m channels. This algorithm is validated using laboratory measurements of the different vegetation types from the Amazon region, data from the Johns Hopkins University (JHU) spectral library, and data from the U.S. Geological Survey (USGS) digital spectral library. We show that the MEVA method can improve the accuracy of flux and aerosol forcing calculations at the TOA compared to more traditional interpolated approaches. Lastly, we combine the MODIS retrieved biomass burning aerosol SSA and the surface albedo spectrum determined from the MEVA technique to calculate TOA flux and aerosol direct radiative forcing over the Amazon region and compare it with Clouds and the Earth's Radiant Energy System (CERES) satellite results. The results show that MODIS based forcing calculations present similar averaged results compared to CERES, but MODIS shows greater spatial variation of aerosol forcing than CERES. Possible reasons for these differences are explored and discussed in this work. Potential future research based on these results is discussed as well.

10 Years of Asian Dust Storm Observations from SeaWiFS: Source, Pathway, and Interannual Variability

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Tsay, S.-C.; King, M.D.; Jeong, M.-J.

2008-01-01

In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol optical thickness and single scattering albedo over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the satellite retrieved aerosol optical thickness with data from AERONET sunphotometers over desert and semi-desert regions. The comparisons show reasonable agreements between these two. These new satellite products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments. The multiyear satellite measurements (1998 - 2007) from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with these dust outbreaks in East Asia. The monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

MODIS Solar Diffuser Attenuation Screen Modeling Results

NASA Technical Reports Server (NTRS)

Waluschka, Eugene; Xuong, Xiaoxiong; Guenther, Bruce; Barnes, William

2004-01-01

On-orbit calibration of the reflected solar bands on the EOS Moderate Resolution Imaging Spectroradiometer (MODIS) is accomplished by have the instrument view a high reflectance diffuse surface illuminated by the sun. For some of the spectral bands this proves to be much too bright a signal that results in the saturation of detectors designed for measuring low reflectance (ocean) surfaces signals. A mechanical attenuation device in the form of a pin hole screen is used to reduce the signals to calibrate these bands. The sensor response to solar illumination of the SD with and without the attenuation screen in place will be presented. The MODIS detector response to the solar diffuser is smooth when the attenuation screen is absent, but has structures up to a few percent when the attenuation screen is present. This structure corresponds to non-uniform illumination from the solar diffuser. Each pin hole produces a pin-hole image of the sun on the solar diffuser, and there are very many pin hole images of the sun on the solar diffuser for each MODIS detector. Even though there are very many pin-hole images of the sun on the solar diffuser, it is no longer perfectly uniformly illuminated. This non-uniformly illuminated solar diffuser produces intensity variation on the focal planes. The results of a very detailed simulation will be discussed which show how the illumination of the focal plane changes as a result of the attenuation, and the impacts on the calibration will be discussed.

An Automatic Cloud Mask Algorithm Based on Time Series of MODIS Measurements

NASA Technical Reports Server (NTRS)

Lyapustin, Alexei; Wang, Yujie; Frey, R.

2008-01-01

Quality of aerosol retrievals and atmospheric correction depends strongly on accuracy of the cloud mask (CM) algorithm. The heritage CM algorithms developed for AVHRR and MODIS use the latest sensor measurements of spectral reflectance and brightness temperature and perform processing at the pixel level. The algorithms are threshold-based and empirically tuned. They don't explicitly address the classical problem of cloud search, wherein the baseline clear-skies scene is defined for comparison. Here, we report on a new CM algorithm which explicitly builds and maintains a reference clear-skies image of the surface (refcm) using a time series of MODIS measurements. The new algorithm, developed as part of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm for MODIS, relies on fact that clear-skies images of the same surface area have a common textural pattern, defined by the surface topography, boundaries of rivers and lakes, distribution of soils and vegetation etc. This pattern changes slowly given the daily rate of global Earth observations, whereas clouds introduce high-frequency random disturbances. Under clear skies, consecutive gridded images of the same surface area have a high covariance, whereas in presence of clouds covariance is usually low. This idea is central to initialization of refcm which is used to derive cloud mask in combination with spectral and brightness temperature tests. The refcm is continuously updated with the latest clear-skies MODIS measurements, thus adapting to seasonal and rapid surface changes. The algorithm is enhanced by an internal dynamic land-water-snow classification coupled with a surface change mask. An initial comparison shows that the new algorithm offers the potential to perform better than the MODIS MOD35 cloud mask in situations where the land surface is changing rapidly, and over Earth regions covered by snow and ice.

Retrieval of tropospheric aerosol properties over land from visible and near-infrared spectral reflectance: Application over Maryland

NASA Astrophysics Data System (ADS)

Levy, Robert Carroll

Aerosols are major components of the Earth's global climate system, affecting the radiation budget and cloud processes of the atmosphere. When located near the surface, high concentrations lead to lowered visibility, increased health problems and generally reduced quality of life for the human population. Over the United States mid-Atlantic region, aerosol pollution is a problem mainly during the summer. Satellites, such as the MODerate Imaging Spectrometer (MODIS), from their vantage point above the atmosphere, provide unprecedented coverage of global and regional aerosols over land. During MODIS' eight-year operation, exhaustive data validation and analyses have shown how the algorithm should be improved. This dissertation describes the development of the 'second-generation' operational algorithm for retrieval of global tropospheric aerosol properties over dark land surfaces, from MODIS-observed spectral reflectance. New understanding about global aerosol properties, land surface reflectance characteristics, and radiative transfer properties were learned in the process. This new operational algorithm performs a simultaneous inversion of reflectance in two visible channels (0.47 and 0.66 mum) and one shortwave infrared channel (2.12 mum), thereby having increased sensitivity to coarse aerosol. Inversion of the three channels retrieves the aerosol optical depth (tau) at 0.55 mum, the percentage of non-dust (fine model) aerosol (eta) and the surface reflectance. This algorithm is applied globally, and retrieves tau that is highly correlated (y = 0.02 + 1.0x, R=0.9) with ground-based sunphotometer measurements. The new algorithm estimates the global, over-land, long-term averaged tau ˜ 0.21, a 25% reduction from previous MODIS estimates. This leads to reducing estimates of global, non-desert, over-land aerosol direct radiative effect (all aerosols) by 1.7 W·m-2 (0.5 W·m-2 over the entire globe), which significantly impacts assessment of aerosol direct radiative forcing (contribution from anthropogenic aerosols only). Over the U.S. mid-Atlantic region, validated retrievals of tau (an integrated column property) can help to estimate surface PM2.5 concentration, a monitored criteria air quality property. The 3-dimensional aerosol loading in the region is characterized using aircraft measurements and the Community Multi-scale Air Quality Model (CMAQ) model, leading to some convergence of observed quantities and modeled processes.

Cross-calibration of the Oceansat-2 Ocean Colour Monitor (OCM) with Terra and Aqua MODIS

NASA Astrophysics Data System (ADS)

Angal, Amit; Brinkmann, Jake; Kumar, A. Senthil; Xiong, Xiaoxiong

2016-05-01

The Ocean Colour Monitor (OCM) sensor on-board the Oceansat-2 spacecraft has been operational since its launch in September, 2009. The Oceansat 2 OCM primary design goal is to provide continuity to Oceansat-1 OCM to obtain information regarding various ocean-colour variables. OCM acquires Earth scene measurements in eight multi-spectral bands in the range from 402 to 885 nm. The MODIS sensor on the Terra and Aqua spacecraft has been successfully operating for over a decade collecting measurements of the earth's land, ocean surface and atmosphere. The MODIS spectral bands, designed for land and ocean applications, cover the spectral range from 412 to 869 nm. This study focuses on comparing the radiometric calibration stability of OCM using near-simultaneous TOA measurements with Terra and Aqua MODIS acquired over the Libya 4 target. Same-day scene-pairs from all three sensors (OCM, Terra and Aqua MODIS) between August, 2014 and September, 2015 were chosen for this analysis. On a given day, the OCM overpass is approximately an hour after the Terra overpass and an hour before the Aqua overpass. Due to the orbital differences between Terra and Aqua, MODIS images the Libya 4 site at different scan-angles on a given day. Some of the high-gain ocean bands for MODIS tend to saturate while viewing the bright Libya 4 target, but bands 8-10 (412 nm - 486 nm) provide an unsaturated response and are used for comparison with the spectrally similar OCM bands. All the standard corrections such as bidirectional reflectance factor (BRDF), relative spectral response mismatch, and impact for atmospheric water-vapor are applied to obtain the reflectance differences between OCM and the two MODIS instruments. Furthermore, OCM is used as a transfer radiometer to obtain the calibration differences between Terra and Aqua MODIS reflective solar bands.

Cross-Calibration of the Oceansat-2 Ocean Colour Monitor (OCM) with Terra and Aqua MODIS

NASA Technical Reports Server (NTRS)

Angal, Amit; Brinkmann, Jake; Kumar, A. Senthil; Xiong, Xiaoxiong

2016-01-01

The Ocean Colour Monitor (OCM) sensor on-board the Oceansat-2 spacecraft has been operational since its launch in September, 2009. The Oceansat 2 OCM primary design goal is to provide continuity to Oceansat-1 OCM to obtain information regarding various ocean-colour variables. OCM acquires Earth scene measurements in eight multi-spectral bands in the range from 402 to 885 nm. The MODIS sensor on the Terra and Aqua spacecraft has been successfully operating for over a decade collecting measurements of the earth's land, ocean surface and atmosphere. The MODIS spectral bands, designed for land and ocean applications, cover the spectral range from 412 to 869 nm. This study focuses on comparing the radiometric calibration stability of OCM using near-simultaneous TOA measurements with Terra and Aqua MODIS acquired over the Libya 4 target. Same-day scene-pairs from all three sensors (OCM, Terra and Aqua MODIS) between August, 2014 and September, 2015 were chosen for this analysis. On a given day, the OCM overpass is approximately an hour after the Terra overpass and an hour before the Aqua overpass. Due to the orbital differences between Terra and Aqua, MODIS images the Libya 4 site at different scan-angles on a given day. Some of the high-gain ocean bands for MODIS tend to saturate while viewing the bright Libya 4 target, but bands 8-10 (412 nm - 486 nm) provide an unsaturated response and are used for comparison with the spectrally similar OCM bands. All the standard corrections such as bidirectional reflectance factor (BRDF), relative spectral response mismatch, and impact for atmospheric water-vapor are applied to obtain the reflectance differences between OCM and the two MODIS instruments. Furthermore, OCM is used as a transfer radiometer to obtain the calibration differences between Terra and Aqua MODIS reflective solar bands.

New Physical Algorithms for Downscaling SMAP Soil Moisture

NASA Astrophysics Data System (ADS)

Sadeghi, M.; Ghafari, E.; Babaeian, E.; Davary, K.; Farid, A.; Jones, S. B.; Tuller, M.

2017-12-01

The NASA Soil Moisture Active Passive (SMAP) mission provides new means for estimation of surface soil moisture at the global scale. However, for many hydrological and agricultural applications the spatial SMAP resolution is too low. To address this scale issue we fused SMAP data with MODIS observations to generate soil moisture maps at 1-km spatial resolution. In course of this study we have improved several existing empirical algorithms and introduced a new physical approach for downscaling SMAP data. The universal triangle/trapezoid model was applied to relate soil moisture to optical/thermal observations such as NDVI, land surface temperature and surface reflectance. These algorithms were evaluated with in situ data measured at 5-cm depth. Our results demonstrate that downscaling SMAP soil moisture data based on physical indicators of soil moisture derived from the MODIS satellite leads to higher accuracy than that achievable with empirical downscaling algorithms. Keywords: Soil moisture, microwave data, downscaling, MODIS, triangle/trapezoid model.

Land Surface Temperature Measurements from EOS MODIS Data

NASA Technical Reports Server (NTRS)

Wan, Zhengming

1997-01-01

We made modifications to the linear kernel bidirectional reflectance distribution function (BRDF) models from Roujean et al. and Wanner et al. that extend the spectral range into the thermal infrared (TIR). With these TIR BRDF models and the IGBP land-cover product, we developed a classification-based emissivity database for the EOS/MODIS land-surface temperature (LST) algorithm and used it in version V2.0 of the MODIS LST code. Two V2.0 LST codes have been delivered to the MODIS SDST, one for the daily L2 and L3 LST products, and another for the 8-day 1km L3 LST product. New TIR thermometers (broadband radiometer with a filter in the 10-13 micron window) and an IR camera have been purchased in order to reduce the uncertainty in LST field measurements due to the temporal and spatial variations in LST. New improvements have been made to the existing TIR spectrometer in order to increase its accuracy to 0.2 C that will be required in the vicarious calibration of the MODIS TIR bands.

An Algorithm for the Retrieval of 30-m Snow-Free Albedo from Landsat Surface Reflectance and MODIS BRDF

NASA Technical Reports Server (NTRS)

Shuai, Yanmin; Masek, Jeffrey G.; Gao, Feng; Schaaf, Crystal B.

2011-01-01

We present a new methodology to generate 30-m resolution land surface albedo using Landsat surface reflectance and anisotropy information from concurrent MODIS 500-m observations. Albedo information at fine spatial resolution is particularly useful for quantifying climate impacts associated with land use change and ecosystem disturbance. The derived white-sky and black-sky spectral albedos maybe used to estimate actual spectral albedos by taking into account the proportion of direct and diffuse solar radiation arriving at the ground. A further spectral-to-broadband conversion based on extensive radiative transfer simulations is applied to produce the broadband albedos at visible, near infrared, and shortwave regimes. The accuracy of this approach has been evaluated using 270 Landsat scenes covering six field stations supported by the SURFace RADiation Budget Network (SURFRAD) and Atmospheric Radiation Measurement Southern Great Plains (ARM/SGP) network. Comparison with field measurements shows that Landsat 30-m snow-free shortwave albedos from all seasons generally achieve an absolute accuracy of +/-0.02 - 0.05 for these validation sites during available clear days in 2003-2005,with a root mean square error less than 0.03 and a bias less than 0.02. This level of accuracy has been regarded as sufficient for driving global and regional climate models. The Landsat-based retrievals have also been compared to the operational 16-day MODIS albedo produced every 8-days from MODIS on Terra and Aqua (MCD43A). The Landsat albedo provides more detailed landscape texture, and achieves better agreement (correlation and dynamic range) with in-situ data at the validation stations, particularly when the stations include a heterogeneous mix of surface covers.

MODIS Measures Total U.S. Leaf Area

NASA Technical Reports Server (NTRS)

2002-01-01

This composite image over the continental United States was produced with data acquired by the Moderate-resolution Imaging Spectroradiometer (MODIS) during the period March 24 - April 8, 2000. The image is a map of the density of the plant canopy covering the ground. It is the first in a series of images over the continental U.S. produced by the MODIS Land Discipline Group (refer to this site June 2 and 5 for the next two images in the series). The image is a MODIS data product called 'Leaf Area Index,' which is produced by radiometrically measuring the visible and near infrared energy reflected by vegetation. The Leaf Area Index provides information on the structure of plant canopy, showing how much surface area is covered by green foliage relative to total land surface area. In this image, dark green pixels indicate areas where more than 80 percent of the land surface is covered by green vegetation, light green pixels show where leaves cover about 10 to 50 percent of the land surface, and brown pixels show virtually no leaf coverage. The more leaf area a plant has, the more sunlight it can absorb for photosynthesis. Leaf Area Index is one of a new suite of measurements that scientists use to understand how the Earth's land surfaces are changing over time. Their goal is to use these measurements to refine computer models well enough to simulate how the land biosphere influences the natural cycles of water, carbon, and energy throughout the Earth system. This image is the first of its kind from the MODIS instrument, which launched in December 1999 aboard the Terra spacecraft. MODIS began acquiring scientific data on February 24, 2000, when it first opened its aperture door. The MODIS instrument and Terra spacecraft are both managed by NASA's Goddard Space Flight Center, Greenbelt, MD. Image courtesy Steven Running, MODIS Land Group Member, University of Montana

Evaluation and sensitivity testing of a coupled Landsat-MODIS downscaling method for land surface temperature and vegetation indices in semi-arid regions

NASA Astrophysics Data System (ADS)

Kim, Jongyoun; Hogue, Terri S.

2012-01-01

The current study investigates a method to provide land surface parameters [i.e., land surface temperature (LST) and normalized difference vegetation index (NDVI)] at a high spatial (˜30 and 60 m) and temporal (daily and 8-day) resolution by combining advantages from Landsat and moderate-resolution imaging spectroradiometer (MODIS) satellites. We adopt a previously developed subtraction method that merges the spatial detail of higher-resolution imagery (Landsat) with the temporal change observed in coarser or moderate-resolution imagery (MODIS). Applying the temporal difference between MODIS images observed at two different dates to a higher-resolution Landsat image allows prediction of a combined or fused image (Landsat+MODIS) at a future date. Evaluation of the resultant merged products is undertaken within the Southeastern Arizona region where data is available from a range of flux tower sites. The Landsat+MODIS fused products capture the raw Landsat values and also reflect the MODIS temporal variation. The predicted Landsat+MODIS LST improves mean absolute error around 5°C at the more heterogeneous sites compared to the original satellite products. The fused Landsat+MODIS NDVI product also shows good correlation to ground-based data and is relatively consistent except during the acute (monsoon) growing season. The sensitivity of the fused product relative to temporal gaps in Landsat data appears to be more affected by uncertainty associated with regional precipitation and green-up, than the length of the gap associated with Landsat viewing, suggesting the potential to use a minimal number of original Landsat images during relatively stable land surface and climate conditions. Our extensive validation yields insight on the ability of the proposed method to integrate multiscale platforms and the potential for reducing costs associated with high-resolution satellite systems (e.g., SPOT, QuickBird, IKONOS).

The Operational MODIS Cloud Optical and Microphysical Property Product: Overview of the Collection 6 Algorithm and Preliminary Results

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, G. Thomas

2012-01-01

Operational Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of cloud optical and microphysical properties (part of the archived products MOD06 and MYD06, for MODIS Terra and Aqua, respectively) are currently being reprocessed along with other MODIS Atmosphere Team products. The latest "Collection 6" processing stream, which is expected to begin production by summer 2012, includes updates to the previous cloud retrieval algorithm along with new capabilities. The 1 km retrievals, based on well-known solar reflectance techniques, include cloud optical thickness, effective particle radius, and water path, as well as thermodynamic phase derived from a combination of solar and infrared tests. Being both global and of high spatial resolution requires an algorithm that is computationally efficient and can perform over all surface types. Collection 6 additions and enhancements include: (i) absolute effective particle radius retrievals derived separately from the 1.6 and 3.7 !-lm bands (instead of differences relative to the standard 2.1 !-lm retrieval), (ii) comprehensive look-up tables for cloud reflectance and emissivity (no asymptotic theory) with a wind-speed interpolated Cox-Munk BRDF for ocean surfaces, (iii) retrievals for both liquid water and ice phases for each pixel, and a subsequent determination of the phase based, in part, on effective radius retrieval outcomes for the two phases, (iv) new ice cloud radiative models using roughened particles with a specified habit, (v) updated spatially-complete global spectral surface albedo maps derived from MODIS Collection 5, (vi) enhanced pixel-level uncertainty calculations incorporating additional radiative error sources including the MODIS L1 B uncertainty index for assessing band and scene-dependent radiometric uncertainties, (v) and use of a new 1 km cloud top pressure/temperature algorithm (also part of MOD06) for atmospheric corrections and low cloud non-unity emissivity temperature adjustments.

Results and Validation of MODIS Aerosol Retrievals Over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, Lorraine; Einaudi, Franco (Technical Monitor)

2001-01-01

The MODerate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra spacecraft has been retrieving aerosol parameters since late February 2000. Initial qualitative checking of the products showed very promising results including matching of land and ocean retrievals at coastlines. Using AERONET ground-based radiometers as our primary validation tool, we have established quantitative validation as well. Our results show that for most aerosol types, the MODIS products fall within the pre-launch estimated uncertainties. Surface reflectance and aerosol model assumptions appear to be sufficiently accurate for the optical thickness retrieval. Dust provides a possible exception, which may be due to non-spherical effects. Over ocean the MODIS products include information on particle size, and these parameters are also validated with AERONET retrievals.

Results and Validation of MODIS Aerosol Retrievals over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Ichoku, C.; Chu, D. A.; Mattoo, S.; Levy, R.; Martins, J. V.; Li, R.-R.; Einaudi, Franco (Technical Monitor)

2000-01-01

The MODerate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra spacecraft has been retrieving aerosol parameters since late February 2000. Initial qualitative checking of the products showed very promising results including matching of land and ocean retrievals at coastlines. Using AERONET ground-based radiometers as our primary validation tool, we have established quantitative validation as well. Our results show that for most aerosol types, the MODIS products fall within the pre-launch estimated uncertainties. Surface reflectance and aerosol model assumptions appear to be sufficiently accurate for the optical thickness retrieval. Dust provides a possible exception, which may be due to non-spherical effects. Over ocean the MODIS products include information on particle size, and these parameters are also validated with AERONET retrievals.

Surface spectral emissivity derived from MODIS data

NASA Astrophysics Data System (ADS)

Chen, Yan; Sun-Mack, Sunny; Minnis, Patrick; Smith, William L.; Young, David F.

2003-04-01

Surface emissivity is essential for many remote sensing applications including the retrieval of the surface skin temperature from satellite-based infrared measurements, determining thresholds for cloud detection and for estimating the emission of longwave radiation from the surface, an important component of the energy budget of the surface-atmosphere interface. In this paper, data from the Terra MODIS (MODerate-resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 10.8, 12.0 micron are used to simultaneously derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of the clear-sky temperatures that are determined by the CERES (Clouds and Earth's Radiant Energy System) scene classification in each channel during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7 micron data. A set of simultaneous equations is then solved to derive the emissivities. Global results are derived from MODIS. Numerical weather analyses are used to provide soundings for correcting the observed radiances for atmospheric absorption. These results are verified and will be available for remote sensing applications.

Monitoring the dynamics of surface water fraction from MODIS time series in a Mediterranean environment

NASA Astrophysics Data System (ADS)

Li, Linlin; Vrieling, Anton; Skidmore, Andrew; Wang, Tiejun; Turak, Eren

2018-04-01

Detailed spatial information of changes in surface water extent is needed for water management and biodiversity conservation, particularly in drier parts of the globe where small, temporally-variant wetlands prevail. Although global surface water histories are now generated from 30 m Landsat data, for many locations they contain large temporal gaps particularly for longer periods (>10 years) due to revisit intervals and cloud cover. Daily Moderate Resolution Imaging Spectrometer (MODIS) imagery has potential to fill such gaps, but its relatively coarse spatial resolution may not detect small water bodies, which can be of great ecological importance. To address this problem, this study proposes and tests options for estimating the surface water fraction from MODIS 16-day 500 m Bidirectional Reflectance Distribution Function (BRDF) corrected surface reflectance image composites. The spatial extent of two Landsat tiles over Spain were selected as test areas. We obtained a 500 m reference dataset on surface water fraction by spatially aggregating 30 m binary water masks obtained from the Landsat-derived C-version of Function of Mask (CFmask), which themselves were evaluated against high-resolution Google Earth imagery. Twelve regression tree models were developed with two approaches, Random Forest and Cubist, using spectral metrics derived from MODIS data and topographic parameters generated from a 30 m spatial resolution digital elevation model. Results showed that accuracies were higher when we included annual summary statistics of the spectral metrics as predictor variables. Models trained on a single Landsat tile were ineffective in mapping surface water in the other tile, but global models trained with environmental conditions from both tiles can provide accurate results for both study areas. We achieved the highest accuracy with Cubist global model (R2 = 0.91, RMSE = 11.05%, MAE = 7.67%). Our method was not only effective for mapping permanent water fraction, but also in accurately capturing temporal fluctuations of surface water. Based on this good performance, we produced surface water fraction maps at 16-day interval for the 2000-2015 MODIS archive. Our approach is promising for monitoring surface water fraction at high frequency time intervals over much larger regions provided that training data are collected across the spatial domain for which the model will be applied.

Assessment of Terra MODIS On-Orbit Polarization Sensitivity Using Pseudoinvariant Desert Sites

NASA Technical Reports Server (NTRS)

Wu, Aisheng; Geng, Xu; Wald, Andrew; Angal, Amit; Xiong, Xiaoxiong

2017-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is currently flying on NASA's Earth Observing System Terra and Aqua satellites, launched in 1999 and 2002, respectively. MODIS reflective solar bands in the visible wavelength range are known to be sensitive to polarized light based on prelaunch polarization sensitivity tests. After about five years of on-orbit operations, it was discovered that the polarization sensitivity at short wavelengths had shown a noticeable increase. In this paper, we examine the impact of polarization on measured top-of-atmosphere (TOA) reflectance based on MODIS Collection-6 L1B over pseudo invariant desert sites. The standard polarization correction equation is used in combination with simulated at-sensor radiances using the second simulation of a satellite signal in the Solar Spectrum, Vector Radiative Transfer Code (6SV). We ignore the polarization contribution from the surface and a ratio approach is used for both 6SV-derived in put parameters and observed TOA reflectance. Results indicate that significant gain corrections up to 25% are required near the end of scan for the 412 and 443 nm bands. The polarization correction reduces the seasonal fluctuations in reflectance trends and mirror side ratios from 30% and 12% to 10% and 5%, respectively, for the two bands. Comparison of the effectiveness of the polarization correction with the results from the NASA Ocean Biology Processing Group shows a good agreement in the corrected reflectance trending results and their seasonal fluctuations.

Comparisons of MODIS vegetation index products with biophysical and flux tower measurements

NASA Astrophysics Data System (ADS)

Sirikul, Natthanich

Vegetation indices (VI) play an important role in studies of global climate and biogeochemical cycles, and are also positively related to many biophysical parameters and satellite products, such as leaf area index (LAI), gross primary production (GPP), land surface water index (LSWI) and land surface temperature (LST). In this study we found that VI's had strong relationships with some biophysical products, such as gross primary production, yet were less well correlated with biophysical structural parameters, such as leaf area index. The relationships between MODIS VI's and biophysical field measured LAI showed poor correlation at semi-arid land and broadleaf forest land cover type whereas cropland showed stronger correlations than the other vegetation types. In addition, the relationship between the enhanced vegetation index (EVI)-LAI and normalized difference vegetation index (NDVI)-LAI did not show significant differences. Comparisons of the relationships between the EVI and NDVI with tower-measured GPP from 11 flux towers in North America, showed that MODIS EVI had much stronger relationships with tower-GPP than did NDVI, and EVI was better correlated with the seasonal dynamics of GPP than was NDVI. In addition, there were no significant differences among the 1x1, 3x3 and 7x7 pixel sample sizes. The comparisons of VIs from the 3 MODIS products from which VI's are generated (Standard VI (MOD13)), Nadir Adjusted Surface Reflectance (NBAR (MOD43)), and Surface Reflectance (MOD09)), showed that MODIS NBAR-EVI (MOD43) was best correlated with GPP compared with the other VI products. In addition, the MODIS VI - tower GPP relationships were significantly improved using NBAR-EVI over the more complex canopy structures, such as the broadleaf and needleleaf forests. The relationship of tower-GPP with other MODIS products would be useful in more thorough characterization of some land cover types in which the VI's have encountered problems. The land surface temperature (LST) product were found useful for empirical estimations of GPP in needleleaf forests, but were not useful for the other land cover types, whereas the land surface water index (LSWI) was more sensitive to noise from snowmelt, ground water table levels, and wet soils than to the canopy moisture levels. Also the MODIS EVI was better correlated with LST than was NDVI. Finally, the cross-site comparisons of GPP and multi-products from MODIS showed that the relationships between EVI and GPP were the strongest while LST and GPP was the weakest. EVI may thus be useful in scaling across landscapes, including heterogeneous ones, for regional estimations of GPP, especially if BRDF effects have been taken into account (such as with the NBAR product). Thus, the relationships of EVI-GPP over space and time would potentially provide much useful information for studies of the global carbon cycle.

GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during DRAGON-NE Asia 2012 campaign

NASA Astrophysics Data System (ADS)

Choi, M.; Kim, J.; Lee, J.; Kim, M.; Park, Y. Je; Jeong, U.; Kim, W.; Holben, B.; Eck, T. F.; Lim, J. H.; Song, C. K.

2015-09-01

The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorology Satellites (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm over ocean and land together with validation results during the DRAGON-NE Asia 2012 campaign. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single scattering albedo (SSA) at 440 nm, Angstrom exponent (AE) between 440 and 860 nm, and aerosol type from selected aerosol models in calculating AOD. Assumed aerosol models are compiled from global Aerosol Robotic Networks (AERONET) inversion data, and categorized according to AOD, FMF, and SSA. Nonsphericity is considered, and unified aerosol models are used over land and ocean. Different assumptions for surface reflectance are applied over ocean and land. Surface reflectance over the ocean varies with geometry and wind speed, while surface reflectance over land is obtained from the 1-3 % darkest pixels in a 6 km × 6 km area during 30 days. In the East China Sea and Yellow Sea, significant area is covered persistently by turbid waters, for which the land algorithm is used for aerosol retrieval. To detect turbid water pixels, TOA reflectance difference at 660 nm is used. GOCI YAER products are validated using other aerosol products from AERONET and the MODIS Collection 6 aerosol data from "Dark Target (DT)" and "Deep Blue (DB)" algorithms during the DRAGON-NE Asia 2012 campaign from March to May 2012. Comparison of AOD from GOCI and AERONET gives a Pearson correlation coefficient of 0.885 and a linear regression equation with GOCI AOD =1.086 × AERONET AOD - 0.041. GOCI and MODIS AODs are more highly correlated over ocean than land. Over land, especially, GOCI AOD shows better agreement with MODIS DB than MODIS DT because of the choice of surface reflectance assumptions. Other GOCI YAER products show lower correlation with AERONET than AOD, but are still qualitatively useful.

Influence of crop type specification and spatial resolution on empirical modeling of field-scale Maize and Soybean carbon fluxes in the US Great Plains

NASA Astrophysics Data System (ADS)

McCombs, A. G.; Hiscox, A.; Wang, C.; Desai, A. R.

2016-12-01

A challenge in satellite land surface remote-sensing models of ecosystem carbon dynamics in agricultural systems is the lack of differentiation by crop type and management. This generalization can lead to large discrepancies between model predictions and eddy covariance flux tower observations of net ecosystem exchange of CO2 (NEE). Literature confirms that NEE varies remarkably among different crop types making the generalization of agriculture in remote sensing based models inaccurate. Here, we address this inaccuracy by identifying and mapping net ecosystem exchange (NEE) in agricultural fields by comparing bulk modeling and modeling by crop type, and using this information to develop empirical models for future use. We focus on mapping NEE in maize and soybean fields in the US Great Plains at higher spatial resolution using the fusion of MODIS and LandSAT surface reflectance. MODIS observed reflectance was downscaled using the ESTARFM downscaling methodology to match spatial scales to those found in LandSAT and that are more appropriate for carbon dynamics in agriculture fields. A multiple regression model was developed from surface reflectance of the downscaled MODIS and LandSAT remote sensing values calibrated against five FLUXNET/AMERIFLUX flux towers located on soybean and/or maize agricultural fields in the US Great Plains with multi-year NEE observations. Our new methodology improves upon bulk approximates to map and model carbon dynamics in maize and soybean fields, which have significantly different photosynthetic capacities.

Monitoring on-orbit calibration stability of the Terra MODIS and Landsat 7 ETM+ sensors using pseudo-invariant test sites

USGS Publications Warehouse

Chander, G.; Xiong, X.(J.); Choi, T.(J.); Angal, A.

2010-01-01

The ability to detect and quantify changes in the Earth's environment depends on sensors that can provide calibrated, consistent measurements of the Earth's surface features through time. A critical step in this process is to put image data from different sensors onto a common radiometric scale. This work focuses on monitoring the long-term on-orbit calibration stability of the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors using the Committee on Earth Observation Satellites (CEOS) reference standard pseudo-invariant test sites (Libya 4, Mauritania 1/2, Algeria 3, Libya 1, and Algeria 5). These sites have been frequently used as radiometric targets because of their relatively stable surface conditions temporally. This study was performed using all cloud-free calibrated images from the Terra MODIS and the L7 ETM+ sensors, acquired from launch to December 2008. Homogeneous regions of interest (ROI) were selected in the calibrated images and the mean target statistics were derived from sensor measurements in terms of top-of-atmosphere (TOA) reflectance. For each band pair, a set of fitted coefficients (slope and offset) is provided to monitor the long-term stability over very stable pseudo-invariant test sites. The average percent differences in intercept from the long-term trends obtained from the ETM + TOA reflectance estimates relative to the MODIS for all the CEOS reference standard test sites range from 2.5% to 15%. This gives an estimate of the collective differences due to the Relative Spectral Response (RSR) characteristics of each sensor, bi-directional reflectance distribution function (BRDF), spectral signature of the ground target, and atmospheric composition. The lifetime TOA reflectance trends from both sensors over 10 years are extremely stable, changing by no more than 0.4% per year in its TOA reflectance over the CEOS reference standard test sites.

Global Enhanced Vegetation Index

NASA Technical Reports Server (NTRS)

2002-01-01

By carefully measuring the wavelengths and intensity of visible and near-infrared light reflected by the land surface back up into space, the Moderate-resolution Imaging Spectroradiometer (MODIS) Team can quantify the concentrations of green leaf vegetation around the world. The above MODIS Enhanced Vegetation Index (EVI) map shows the density of plant growth over the entire globe. Very low values of EVI (white and brown areas) correspond to barren areas of rock, sand, or snow. Moderate values (light greens) represent shrub and grassland, while high values indicate temperate and tropical rainforests (dark greens). The MODIS EVI gives scientists a new tool for monitoring major fluctuations in vegetation and understanding how they affect, and are affected by, regional climate trends. For more information, read NASA Unveils Spectacular Suite of New Global Data Products from MODIS. Image courtesy MODIS Land Group/Vegetation Indices, Alfredo Huete, Principal Investigator, and Kamel Didan, University of Arizona

MODIS land data at the EROS data center DAAC

USGS Publications Warehouse

Jenkerson, Calli B.; Reed, B.C.

2001-01-01

The US Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center (EDC) in Sioux Falls, SD, USA, is the primary national archive for land processes data and one of the National Aeronautics and Space Administration's (NASA) Distributed Active Archive Centers (DAAC) for the Earth Observing System (EOS). One of EDC's functions as a DAAC is the archival and distribution of Moderate Resolution Spectroradiometer (MODIS) Land Data collected from the Earth Observing System (EOS) satellite Terra. More than 500,000 publicly available MODIS land data granules totaling 25 Terabytes (Tb) are currently stored in the EDC archive. This collection is managed, archived, and distributed by EOS Data and Information System (EOSDIS) Core System (ECS) at EDC. EDC User Services support the use of MODIS Land data, which include land surface reflectance/albedo, temperature/emissivity, vegetation characteristics, and land cover, by responding to user inquiries, constructing user information sites on the EDC web page, and presenting MODIS materials worldwide.

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.

2001-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands from 0.415 to 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation I will review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of: (1) developing a cloud mask for distinguishing clear sky from clouds, (2) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (3) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (4) determining atmospheric profiles of moisture and temperature, and (5) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 deg (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented. Finally, I will present some highlights from the land and ocean algorithms developed for processing global MODIS observations, including: (1) surface reflectance, (2) vegetation indices, leaf area index, and FPAR, (3) albedo and nadir BRDF-adjusted reflectance, (4) normalized water-leaving radiance, (5) chlorophyll-a concentration, and (6) sea surface temperature.

Capability of Integrated MODIS Imagery and ALOS for Oil Palm, Rubber and Forest Areas Mapping in Tropical Forest Regions

PubMed Central

Razali, Sheriza Mohd; Marin, Arnaldo; Nuruddin, Ahmad Ainuddin; Shafri, Helmi Zulhaidi Mohd; Hamid, Hazandy Abdul

2014-01-01

Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions. PMID:24811079

Capability of integrated MODIS imagery and ALOS for oil palm, rubber and forest areas mapping in tropical forest regions.

PubMed

Razali, Sheriza Mohd; Marin, Arnaldo; Nuruddin, Ahmad Ainuddin; Shafri, Helmi Zulhaidi Mohd; Hamid, Hazandy Abdul

2014-05-07

Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions.

A Continental United States High Resolution NLCD Land Cover – MODIS Albedo Database to Examine Albedo and Land Cover Change Relationships

EPA Science Inventory

Surface albedo influences climate by affecting the amount of solar radiation that is reflected at the Earth’s surface, and surface albedo is, in turn, affected by land cover. General Circulation Models typically use modeled or prescribed albedo to assess the influence of land co...

A New Algorithm for Retrieving Aerosol Properties Over Land from MODIS Spectral Reflectance

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Remer, Lorraine A.; Mattoo, Shana; Vermote, Eric F.; Kaufman, Yoram J.

2006-01-01

Since first light in early 2000, operational global quantitative retrievals of aerosol properties over land have been made from MODIS observed spectral reflectance. These products have been continuously evaluated and validated, and opportunities for improvements have been noted. We have replaced the original algorithm by improving surface reflectance assumptions, the aerosol model optical properties and the radiative transfer code used to create the lookup tables. The new algorithm (known as Version 5.2 or V5.2) performs a simultaneous inversion of two visible (0.47 and 0.66 micron) and one shortwave-IR (2.12 micron) channel, making use of the coarse aerosol information content contained in the 2.12 micron channel. Inversion of the three channels yields three nearly independent parameters, the aerosol optical depth (tau) at 0.55 micron, the non-dust or fine weighting (eta) and the surface reflectance at 2.12 micron. Finally, retrievals of small magnitude negative tau values (down to -0.05) are considered valid, thus normalizing the statistics of tau in near zero tau conditions. On a 'test bed' of 6300 granules from Terra and Aqua, the products from V5.2 show marked improvement over those from the previous versions, including much improved retrievals of tau, where the MODIS/AERONET tau (at 0.55 micron) regression has an equation of: y = 1.01+0.03, R = 0.90. Mean tau for the test bed is reduced from 0.28 to 0.21.

Updated MISR Dark Water Research Aerosol Retrieval Algorithm - Part 1: Coupled 1.1 km Ocean Surface Chlorophyll a Retrievals with Empirical Calibration Corrections

NASA Technical Reports Server (NTRS)

Limbacher, James A.; Kahn, Ralph A.

2017-01-01

As aerosol amount and type are key factors in the 'atmospheric correction' required for remote-sensing chlorophyll alpha concentration (Chl) retrievals, the Multi-angle Imaging SpectroRadiometer (MISR) can contribute to ocean color analysis despite a lack of spectral channels optimized for this application. Conversely, an improved ocean surface constraint should also improve MISR aerosol-type products, especially spectral single-scattering albedo (SSA) retrievals. We introduce a coupled, self-consistent retrieval of Chl together with aerosol over dark water. There are time-varying MISR radiometric calibration errors that significantly affect key spectral reflectance ratios used in the retrievals. Therefore, we also develop and apply new calibration corrections to the MISR top-of-atmosphere (TOA) reflectance data, based on comparisons with coincident MODIS (Moderate Resolution Imaging Spectroradiometer) observations and trend analysis of the MISR TOA bidirectional reflectance factors (BRFs) over three pseudo-invariant desert sites. We run the MISR research retrieval algorithm (RA) with the corrected MISR reflectances to generate MISR-retrieved Chl and compare the MISR Chl values to a set of 49 coincident SeaBASS (SeaWiFS Bio-optical Archive and Storage System) in situ observations. Where Chl(sub in situ) less than 1.5 mg m(exp -3), the results from our Chl model are expected to be of highest quality, due to algorithmic assumption validity. Comparing MISR RA Chl to the 49 coincident SeaBASS observations, we report a correlation coefficient (r) of 0.86, a root-mean-square error (RMSE) of 0.25, and a median absolute error (MAE) of 0.10. Statistically, a two-sample Kolmogorov- Smirnov test indicates that it is not possible to distinguish between MISR Chl and available SeaBASS in situ Chl values (p greater than 0.1). We also compare MODIS-Terra and MISR RA Chl statistically, over much broader regions. With about 1.5 million MISR-MODIS collocations having MODIS Chl less than 1.5 mg m(exp -3), MISR and MODIS show very good agreement: r = 0.96, MAE = 0.09, and RMSE = 0.15. The new dark water aerosol/Chl RA can retrieve Chl in low-Chl, case I waters, independent of other imagers such as MODIS, via a largely physical algorithm, compared to the commonly applied statistical ones. At a minimum, MISR's multi-angle data should help reduce uncertainties in the MODIS-Terra ocean color retrieval where coincident measurements are made, while also allowing for a more robust retrieval of particle properties such as spectral single-scattering albedo.

Updated MISR dark water research aerosol retrieval algorithm - Part 1: Coupled 1.1 km ocean surface chlorophyll a retrievals with empirical calibration corrections

NASA Astrophysics Data System (ADS)

Limbacher, James A.; Kahn, Ralph A.

2017-04-01

As aerosol amount and type are key factors in the atmospheric correction required for remote-sensing chlorophyll a concentration (Chl) retrievals, the Multi-angle Imaging SpectroRadiometer (MISR) can contribute to ocean color analysis despite a lack of spectral channels optimized for this application. Conversely, an improved ocean surface constraint should also improve MISR aerosol-type products, especially spectral single-scattering albedo (SSA) retrievals. We introduce a coupled, self-consistent retrieval of Chl together with aerosol over dark water. There are time-varying MISR radiometric calibration errors that significantly affect key spectral reflectance ratios used in the retrievals. Therefore, we also develop and apply new calibration corrections to the MISR top-of-atmosphere (TOA) reflectance data, based on comparisons with coincident MODIS (Moderate Resolution Imaging Spectroradiometer) observations and trend analysis of the MISR TOA bidirectional reflectance factors (BRFs) over three pseudo-invariant desert sites. We run the MISR research retrieval algorithm (RA) with the corrected MISR reflectances to generate MISR-retrieved Chl and compare the MISR Chl values to a set of 49 coincident SeaBASS (SeaWiFS Bio-optical Archive and Storage System) in situ observations. Where Chlin situ < 1.5 mg m-3, the results from our Chl model are expected to be of highest quality, due to algorithmic assumption validity. Comparing MISR RA Chl to the 49 coincident SeaBASS observations, we report a correlation coefficient (r) of 0.86, a root-mean-square error (RMSE) of 0.25, and a median absolute error (MAE) of 0.10. Statistically, a two-sample Kolmogorov-Smirnov test indicates that it is not possible to distinguish between MISR Chl and available SeaBASS in situ Chl values (p > 0.1). We also compare MODIS-Terra and MISR RA Chl statistically, over much broader regions. With about 1.5 million MISR-MODIS collocations having MODIS Chl < 1.5 mg m-3, MISR and MODIS show very good agreement: r = 0. 96, MAE = 0.09, and RMSE = 0.15. The new dark water aerosol/Chl RA can retrieve Chl in low-Chl, case I waters, independent of other imagers such as MODIS, via a largely physical algorithm, compared to the commonly applied statistical ones. At a minimum, MISR's multi-angle data should help reduce uncertainties in the MODIS-Terra ocean color retrieval where coincident measurements are made, while also allowing for a more robust retrieval of particle properties such as spectral single-scattering albedo.

Assessment of the short-term radiometric stability between Terra MODIS and Landsat 7 ETM+ sensors

USGS Publications Warehouse

Choi, Taeyoung; Xiong, Xiaoxiong; Chander, Gyanesh; Angal, A.

2009-01-01

Short-term radiometric stability was evaluated using continuous ETM+ scenes within a single orbit (contact period) and the corresponding MODIS scenes for the four matching solar reflective visible and near-infrared (VNIR) band pairs between the two sensors. The near-simultaneous earth observations were limited by the smaller swath size of ETM+ (183 km) compared to MODIS (2330 km). Two sets of continuous granules for Terra MODIS and Landsat 7 ETM+ were selected and mosaicked based on pixel geolocation information for noncloudy pixels over the African continent. The matching pixel pairs were resampled from a fine to a coarse pixel resolution, and the at-sensor spectral radiance values for a wide dynamic range of the sensors were compared and analyzed, covering various surface types. The following study focuses on radiometric stability analysis from the VNIR band-pairs of ETM+ and MODIS. The Libya-4 desert target was included in the path of this continuous orbit, which served as a verification point between the short-term and the long-term trending results from previous studies. MODTRAN at-sensor spectral radiance simulation is included for a representative desert surface type to evaluate the consistency of the results.

Atmospheric Correction at AERONET Locations: A New Science and Validation Data Set

NASA Technical Reports Server (NTRS)

Wang, Yujie; Lyapustin, Alexei; Privette, Jeffery L.; Morisette, Jeffery T.; Holben, Brent

2008-01-01

This paper describes an AERONET-based Surface Reflectance Validation Network (ASRVN) and its dataset of spectral surface bidirectional reflectance and albedo based on MODIS TERRA and AQUA data. The ASRVN is an operational data collection and processing system. It receives 50x50 square kilometer subsets of MODIS L1B data from MODAPS and AERONET aerosol and water vapor information. Then it performs an accurate atmospheric correction for about 100 AERONET sites based on accurate radiative transfer theory with high quality control of the input data. The ASRVN processing software consists of L1B data gridding algorithm, a new cloud mask algorithm based on a time series analysis, and an atmospheric correction algorithm. The atmospheric correction is achieved by fitting the MODIS top of atmosphere measurements, accumulated for 16-day interval, with theoretical reflectance parameterized in terms of coefficients of the LSRT BRF model. The ASRVN takes several steps to ensure high quality of results: 1) cloud mask algorithm filters opaque clouds; 2) an aerosol filter has been developed to filter residual semi-transparent and sub-pixel clouds, as well as cases with high inhomogeneity of aerosols in the processing area; 3) imposing requirement of consistency of the new solution with previously retrieved BRF and albedo; 4) rapid adjustment of the 16-day retrieval to the surface changes using the last day of measurements; and 5) development of seasonal back-up spectral BRF database to increase data coverage. The ASRVN provides a gapless or near-gapless coverage for the processing area. The gaps, caused by clouds, are filled most naturally with the latest solution for a given pixels. The ASRVN products include three parameters of LSRT model (k(sup L), k(sup G), k(sup V)), surface albedo, NBRF (a normalized BRF computed for a standard viewing geometry, VZA=0 deg., SZA=45 deg.), and IBRF (instantaneous, or one angle, BRF value derived from the last day of MODIS measurement for specific viewing geometry) for MODIS 500m bands 1-7. The results are produced daily at resolution of 1 km in gridded format. We also provide cloud mask, quality flag and a browse bitmap image. The new dataset can be used for a wide range of applications including validation analysis and science research.

Mapping high-resolution incident photosynthetically active radiation over land surfaces from MODIS and GOES satellite data

NASA Astrophysics Data System (ADS)

Liang, S.; Wang, K.; Wang, D.; Townshend, J.; Running, S.; Tsay, S.

2008-05-01

Incident photosynthetically active radiation (PAR) is a key variable required by almost all terrestrial ecosystem models. Many radiation efficiency models are linearly related canopy productivity to the absorbed PAR. Unfortunately, the current incident PAR products estimated from remotely sensed data or calculated by radiation models at spatial and temporal resolutions are not sufficient for carbon cycle modeling and various applications. In this study, we aim to develop incident PAR products at one kilometer scale from multiple satellite sensors, such as Moderate Resolution Imaging Spectrometer (MODIS) and Geostationary Operational Environmental Satellite (GOES) sensor. We first developed a look-up table approach to estimate instantanerous incident PAR product from MODIS (Liang et al., 2006). The temporal observations of each pixel are used to estimate land surface reflectance and look-up tables of both aerosol and cloud are searched, based on the top-of-atmosphere reflectance and surface reflectance for determining incident PAR. The incident PAR product includes both the direct and diffuse components. The calculation of a daily integrated PAR using two different methods has also been developed (Wang, et al., 2008a). The similar algorithm has been further extended to GOES data (Wang, et al., 2008b, Zheng, et al., 2008). Extensive validation activities are conducted to evaluate the algorithms and products using the ground measurements from FLUXNET and other networks. They are also compared with other satellite products. The results indicate that our approaches can produce reasonable PAR product at 1km resolution. We have generated 1km incident PAR products over North America for several years, which are freely available to the science community. Liang, S., T. Zheng, R. Liu, H. Fang, S. C. Tsay, S. Running, (2006), Estimation of incident Photosynthetically Active Radiation from MODIS Data, Journal of Geophysical Research ¡§CAtmosphere. 111, D15208,doi:10.1029/2005JD006730. Wang, D., S. Liang, and Zheng, T., (2008a), Integrated daily PAR from MODIS. International Journal of Remote Sensing, revised. Wang, K., S. Liang, T. Zheng and D. Wang, (2008b), Simultaneous estimation of surface photosynthetically active radiation and albedo from GOES, Remote Sensing of Environment, revised. Zheng, T., S. Liang, K. Wang, (2008), Estimation of incident PAR from GOES imagery, Journal of Applied Meteorology and Climatology. in press.

Estimating Terra MODIS Polarization Effect Using Ocean Data

NASA Technical Reports Server (NTRS)

Wald, Andrew E.; Brinkmann, Jake; Wu, Aisheng; Xiong, Jack

2016-01-01

Terra MODIS has been known since pre-launch to have polarization sensitivity, particularly in shortest-wavelength bands 8 and 9. On-orbit reflectance trending of pseudo-invariant sites show a variation in reflectance as a function of band and scan mirror angle of incidence consistent with time-dependent polarization effects from the rotating double-sided scan mirror. The MODIS Characterization Support Team [MCST] estimates the Mueller matrix trending from this variation as observed from a single desert site, but this effect is not included in Collection 6 [C6] calibration. Here we extend the MCSTs current polarization sensitivity monitoring to two ocean sites distributed over latitude to helpestimate the uncertainties in the derived Mueller matrix. The Mueller matrix elements derived for polarization-sensitive Band 8 for a given site are found to be fairly insensitive to surface brdf modeling. The site-to-site variation is a measure of the uncertainty in the Mueller estimation.Results for band 8 show that the polarization correction reduces mirror-side striping by up to 50% and reduces the instrument polarization effect on reflectance time series of an ocean target.

Quantifying the Significance of Heterogeneity in Supraglacial Reflectance Characteristics for Meltwater Production in Southwest Greenland

NASA Astrophysics Data System (ADS)

Irvine-Fynn, T. D.; Bunting, P.; Cook, J.; Hardy, A. J.; Hodson, A. J.; Holt, T.; Hubbard, A.; Naegeli, K.; Nilsson, J.; Ryan, J.; Roberts, O.; Tedstone, A.; Tranter, M.; Williamson, C.

2017-12-01

The seasonal melt on the southwestern margin of the Greenland Ice Sheet has been enhanced due to processes affecting the ablation area's ice surface reflectance (albedo). Recent trends in surface reflectance in the region suggest a decline potentially linked to an albedo-feedback associated with regional climate warming, emergence of organic and mineral particulates, and expansion of melt area. However, the heterogeneity of reflectance over bare ice areas in space and time has remained relatively poorly characterised. Numerous surface mass balance models utilise albedo products derived from remote sensing platforms with coarse scale resolution. Such products provide reasonable albedo estimates, but quantification of local variability in reflectance remains lacking. Consequently, there is a need to better define the distribution and representativeness of ice surface reflectance at and below the scale of satellite sensor pixel footprints to facilitate examination of albedo parameterisations. Here, we present reflectance data repeatedly collected in SW Greenland during the 2016 summer melt season over a 0.0625 km2 area proximate to the IMAU K-transect site S6 (67°04.5'N, 49°21.0'W). The Moderate Resolution Imaging Spectrometer (MODIS) albedo product MOD10A1(c6) for the study site was compared to reflectance data from Sentinel-2, centimetre resolution calibrated 12Mpix optical imagery collected using an Unmanned Aerial Vehicle (UAV) flown at a height of 70 m above the ice surface, and ground-based reflectance survey data acquired using a StellarNet Red-Dwarf/Blue-Wave visible-infrared dual system (250-1700nm) at 30 sites distributed over the area of interest. Our data highlight variability in the spatial distribution of ice surface reflectance characteristics over time. Specifically, data demonstrate marked changes in the distribution of reflectance values, despite maintaining a broadly equitable mean and median during July and August. The influence of the varied surface heterogeneity is explored further using surface energy balance modelling to quantify the impact of such changes on melt production. The findings determine the necessity to account for local variability underlying the pixel-averaged values retrieved from remote sensing platforms such as MODIS.

High-frequency remote monitoring of large lakes with MODIS 500 m imagery

USGS Publications Warehouse

McCullough, Ian M.; Loftin, Cynthia S.; Sader, Steven A.

2012-01-01

Satellite-based remote monitoring programs of regional lake water quality largely have relied on Landsat Thematic Mapper (TM) owing to its long image archive, moderate spatial resolution (30 m), and wide sensitivity in the visible portion of the electromagnetic spectrum, despite some notable limitations such as temporal resolution (i.e., 16 days), data pre-processing requirements to improve data quality, and aging satellites. Moderate-Resolution Imaging Spectroradiometer (MODIS) sensors on Aqua/Terra platforms compensate for these shortcomings, although at the expense of spatial resolution. We developed and evaluated a remote monitoring protocol for water clarity of large lakes using MODIS 500 m data and compared MODIS utility to Landsat-based methods. MODIS images captured during May–September 2001, 2004 and 2010 were analyzed with linear regression to identify the relationship between lake water clarity and satellite-measured surface reflectance. Correlations were strong (R² = 0.72–0.94) throughout the study period; however, they were the most consistent in August, reflecting seasonally unstable lake conditions and inter-annual differences in algal productivity during the other months. The utility of MODIS data in remote water quality estimation lies in intra-annual monitoring of lake water clarity in inaccessible, large lakes, whereas Landsat is more appropriate for inter-annual, regional trend analyses of lakes ≥ 8 ha. Model accuracy is improved when ancillary variables are included to reflect seasonal lake dynamics and weather patterns that influence lake clarity. The identification of landscape-scale drivers of regional water quality is a useful way to supplement satellite-based remote monitoring programs relying on spectral data alone.

eMODIS Expedited: Overview of a Near Real Time MODIS Production System for Operational Vegetation Monitoring

NASA Astrophysics Data System (ADS)

Jenkerson, C.; Meyer, D. J.; Werpy, J.; Evenson, K.; Merritt, M.

2010-12-01

The expedited MODIS, or eMODIS production system derives near-real time Normalized Difference Vegetation Index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance provided by the Land and Atmosphere Near-real time Capability for EOS (LANCE). There are currently three regions covered by this U.S. Geological Survey (USGS) capability, including the continental U.S., Africa, and the Central America/Caribbean regions. Each of the eMODIS production streams is configured to output its data in map projections, compositing intervals, spatial resolutions, and file formats specific to its region and user community. The challenges of processing 1,000-meter, 500-m, and especially 250-m products by midnight on the last day of a product interval have been met with increasingly effective software and system architecture. An anonymous file transfer protocol (FTP) distribution site (ftp://emodisftp.cr.usgs.gov/eMODIS) allows users direct access to eMODIS NDVI products for operational (near-real time) monitoring of vegetation conditions like drought, crop failure, insect infestation, and other threats, thus supporting subsequent early warning of famine and the targeting of vulnerable populations for insecure food situations.

Optimal Grid Size for Inter-Comparability of MODIS And VIIRS Vegetation Indices at Level 2G or Higher

NASA Astrophysics Data System (ADS)

Campagnolo, M.; Schaaf, C.

2016-12-01

Due to the necessity of time compositing and other user requirements, vegetation indices, as well as many other EOS derived products, are distributed in a gridded format (level L2G or higher) using an equal area sinusoidal grid, at grid sizes of 232 m, 463 m or 926 m. In this process, the actual surface signal suffers somewhat of a degradation, caused by both the sensor's point spread function and this resampling from swath to the regular grid. The magnitude of that degradation depends on a number of factors, such as surface heterogeneity, band nominal resolution, observation geometry and grid size. In this research, the effect of grid size is quantified for MODIS and VIIRS (at five EOS validation sites with distinct land covers), for the full range of view zenith angles, and at grid sizes of 232 m, 253 m, 309 m, 371 m, 397 m and 463 m. This allows us to compare MODIS and VIIRS gridded products for the same scenes, and to determine the grid size at which these products are most similar. Towards that end, simulated MODIS and VIIRS bands are generated from Landsat 8 surface reflectance images at each site and gridded products are then derived by using maximum obscov resampling. Then, for every grid size, the original Landsat 8 NDVI and the derived MODIS and VIIRS NDVI products are compared. This methodology can be applied to other bands and products, to determine which spatial aggregation overall is best suited for EOS to S-NPP product continuity. Results for MODIS (250 m bands) and VIIRS (375 m bands) NDVI products show that finer grid sizes tend to be better at preserving the original signal. Significant degradation for gridded NDVI occurs when grid size is larger then 253 m (MODIS) and 371 m (VIIRS). Our results suggest that current MODIS "500 m" (actually 463 m) grid size is best for product continuity. Note however, that up to that grid size value, MODIS gridded products are somewhat better at preserving the surface signal than VIIRS, except for at very high VZA.

Validation of MODIS Aerosol Optical Depth Retrieval Over Land

NASA Technical Reports Server (NTRS)

Chu, D. A.; Kaufman, Y. J.; Ichoku, C.; Remer, L. A.; Tanre, D.; Holben, B. N.; Einaudi, Franco (Technical Monitor)

2001-01-01

Aerosol optical depths are derived operationally for the first time over land in the visible wavelengths by MODIS (Moderate Resolution Imaging Spectroradiometer) onboard the EOSTerra spacecraft. More than 300 Sun photometer data points from more than 30 AERONET (Aerosol Robotic Network) sites globally were used in validating the aerosol optical depths obtained during July - September 2000. Excellent agreement is found with retrieval errors within (Delta)tau=+/- 0.05 +/- 0.20 tau, as predicted, over (partially) vegetated surfaces, consistent with pre-launch theoretical analysis and aircraft field experiments. In coastal and semi-arid regions larger errors are caused predominantly by the uncertainty in evaluating the surface reflectance. The excellent fit was achieved despite the ongoing improvements in instrument characterization and calibration. This results show that MODIS-derived aerosol optical depths can be used quantitatively in many applications with cautions for residual clouds, snow/ice, and water contamination.

Estimation of Multiple Parameters over Vegetated Surfaces by Integrating Optical-Thermal Remote Sensing Observations

NASA Astrophysics Data System (ADS)

Ma, H.

2016-12-01

Land surface parameters from remote sensing observations are critical in monitoring and modeling of global climate change and biogeochemical cycles. Current methods for estimating land surface parameters are generally parameter-specific algorithms and are based on instantaneous physical models, which result in spatial, temporal and physical inconsistencies in current global products. Besides, optical and Thermal Infrared (TIR) remote sensing observations are usually separated to use based on different models , and the Middle InfraRed (MIR) observations have received little attention due to the complexity of the radiometric signal that mixes both reflected and emitted fluxes. In this paper, we proposed a unified algorithm for simultaneously retrieving a total of seven land surface parameters, including Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), land surface albedo, Land Surface Temperature (LST), surface emissivity, downward and upward longwave radiation, by exploiting remote sensing observations from visible to TIR domain based on a common physical Radiative Transfer (RT) model and a data assimilation framework. The coupled PROSPECT-VISIR and 4SAIL RT model were used for canopy reflectance modeling. At first, LAI was estimated using a data assimilation method that combines MODIS daily reflectance observation and a phenology model. The estimated LAI values were then input into the RT model to simulate surface spectral emissivity and surface albedo. Besides, the background albedo and the transmittance of solar radiation, and the canopy albedo were also calculated to produce FAPAR. Once the spectral emissivity of seven MODIS MIR to TIR bands were retrieved, LST can be estimated from the atmospheric corrected surface radiance by exploiting an optimization method. At last, the upward longwave radiation were estimated using the retrieved LST, broadband emissivity (converted from spectral emissivity) and the downward longwave radiation (modeled by MODTRAN). These seven parameters were validated over several representative sites with different biome type, and compared with MODIS and GLASS product. Results showed that this unified inversion algorithm can retrieve temporally complete and physical consistent land surface parameters with high accuracy.

Generating daily high spatial land surface temperatures by combining ASTER and MODIS land surface temperature products for environmental process monitoring.

PubMed

Wu, Mingquan; Li, Hua; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-08-01

There is a shortage of daily high spatial land surface temperature (LST) data for use in high spatial and temporal resolution environmental process monitoring. To address this shortage, this work used the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), and the Spatial and Temporal Data Fusion Approach (STDFA) to estimate high spatial and temporal resolution LST by combining Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LST and Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. The actual ASTER LST products were used to evaluate the precision of the combined LST images using the correlation analysis method. This method was tested and validated in study areas located in Gansu Province, China. The results show that all the models can generate daily synthetic LST image with a high correlation coefficient (r) of 0.92 between the synthetic image and the actual ASTER LST observations. The ESTARFM has the best performance, followed by the STDFA and the STARFM. Those models had better performance in desert areas than in cropland. The STDFA had better noise immunity than the other two models.

Analysis of Accuracy of Modis BRDF Product (MCD43 C6) Based on Misr Land Surface Brf Product - a Case Study of the Central Part of Northeast Asia

NASA Astrophysics Data System (ADS)

Li, J.; Chen, S.; Qin, W.; Murefu, M.; Wang, Y.; Yu, Y.; Zhen, Z.

2018-04-01

EOS/MODIS land surface Bi-directional Reflectance Distribution Function (BRDF) product (MCD43), with the latest version C6, is one of the most important operational BRDF products with global coverage. The core sub-product MCD43A1 stores 3 parameters of the RossThick-LiSparseR semi-empirical kernel-driven BRDF model. It is important for confident use of the product to evaluate the accuracy of bi-directional reflectance factor (BRF) predicted by MCD43A1 BRDF model (mBRF). A typical region in the central part of Northeast Asia is selected as the study area. The performance of MCD43A1 BRDF model is analyzed in various observation geometries and phenological phases, using Multi-angle Imaging SpectroRadiometer (MISR) land-surface reflectance factor product (MILS_BRF) as the reference data. In addition, MODIS products MCD12Q1 and MOD/MYD10A1 are used to evaluate the impacts of land cover types and snow covers on the model accuracy, respectively. The results show an overall excellent performance of MCD43A1 in representing the anisotropic reflectance of land surface, with root mean square error (RMSE) of 0.0262 and correlation coefficient (R) of 0.9537, for all available comparable samples of MILS_BRF and mBRF pairs. The model accuracy varies in different months, which is related to the phenological phases of the study area. The accuracy for pixels labelled as `snow' by MCD43 is obviously low, with RMSE/R of 0.0903/0.8401. Ephemeral snowfall events further decrease the accuracy, with RMSE/R of 0.1001/0.7715. These results provide meaningful information to MCD43 users, especially those, whose study regions are subject to phenological cycles as well as snow cover and change.

Accounting for the effects of surface BRDF on satellite cloud and trace-gas retrievals: a new approach based on geometry-dependent Lambertian equivalent reflectivity applied to OMI algorithms

NASA Astrophysics Data System (ADS)

Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey

2017-01-01

Most satellite nadir ultraviolet and visible cloud, aerosol, and trace-gas algorithms make use of climatological surface reflectivity databases. For example, cloud and NO2 retrievals for the Ozone Monitoring Instrument (OMI) use monthly gridded surface reflectivity climatologies that do not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun-sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (LER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. The geometry-dependent LER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from the Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the Cox-Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare the geometry-dependent and climatological LERs for two wavelengths, 354 and 466 nm, that are used in OMI cloud algorithms to derive cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and geometry-dependent LERs is carried out. Geometry-dependent LER and corresponding retrieved cloud products are then used as inputs to our OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with geometry-dependent LERs can increase NO2 vertical columns by up to 50 % in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

Accounting for the Effects of Surface BRDF on Satellite Cloud and Trace-Gas Retrievals: A New Approach Based on Geometry-Dependent Lambertian-Equivalent Reflectivity Applied to OMI Algorithms

NASA Technical Reports Server (NTRS)

Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey

2017-01-01

Most satellite nadir ultraviolet and visible cloud, aerosol, and trace-gas algorithms make use of climatological surface reflectivity databases. For example, cloud and NO2 retrievals for the Ozone Monitoring Instrument (OMI) use monthly gridded surface reflectivity climatologies that do not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun-sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (LER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. The geometry-dependent LER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from the Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the Cox-Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare the geometry-dependent and climatological LERs for two wavelengths, 354 and 466 nm, that are used in OMI cloud algorithms to derive cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and geometry-dependent LERs is carried out. Geometry-dependent LER and corresponding retrieved cloud products are then used as inputs to our OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with geometry-dependent LERs can increase NO2 vertical columns by up to 50% in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

NASA Technical Reports Server (NTRS)

Wang, Zhuosen; Erb, Angela M.; Schaaf, Crystal B.; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A.; Roman, Miguel O.

2016-01-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data

PubMed Central

Wang, Zhuosen; Erb, Angela M.; Schaaf, Crystal B.; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A.; Román, Miguel O.

2018-01-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (< 100m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high- burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems. PMID:29769751

Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data.

PubMed

Wang, Zhuosen; Erb, Angela M; Schaaf, Crystal B; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A; Román, Miguel O

2016-11-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (< 100m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high- burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Estimating photosynthetic vegetation, non-photosynthetic vegetation and bare soil fractions using Landsat and MODIS data: Effects of site heterogeneity, soil properties and land cover

NASA Astrophysics Data System (ADS)

Guerschman, J. P.; Scarth, P.; McVicar, T.; Malthus, T. J.; Stewart, J.; Rickards, J.; Trevithick, R.; Renzullo, L. J.

2013-12-01

Vegetation fractional cover is a key indicator for land management monitoring, both in pastoral and agricultural settings. Maintaining adequate vegetation cover protects the soil from the effects of water and wind erosion and also ensures that carbon is returned to soil through decomposition. Monitoring vegetation fractional cover across large areas and continuously in time needs good remote sensing techniques underpinned by high quality ground data to calibrate and validate algorithms. In this study we used Landsat and MODIS reflectance data together with field measurements from 1476 observations across Australia to produce estimates of vegetation fractional cover using a linear unmixing technique. Specifically, we aimed at separating fractions of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare soil (B). We used Landsat reflectance averaged over a 3x3 pixel window representing the area actually measured on the ground and also a 'degraded' Landsat reflectance 40x40 pixel window to simulate the effect of a coarser sensor. Using these two Landsat reflectances we quantified the heterogeneity of each site. We used data from two MODIS-derived reflectance products: the Nadir BRDF-Adjusted surface Reflectance product (MCD43A4) and the MODIS 8-day surface reflectance (MOD09A1). We derived endmembers from the data and estimated fractional cover using a linear unmixing technique. Log transforms and band interaction terms were added to account for non-linearities in the spectral mixing. For each reflectance source we investigated if the residuals were correlated with site heterogeneity, soil colour, soil moisture and land cover type. As expected, the best model was obtained when Landsat data for a small region around each site was used. We obtained root mean square error (RMSE) values of 0.134, 0.175 and 0.153 for PV, NPV and B respectively. When we degraded the Landsat data to an area of ~1 km2 around each site the model performance decreased to RMSE of 0.142, 0.181 and 0.166 for PV, NPV and B. Using MODIS reflectance data (from the MCD43A4 and MOD09A1 products) we obtained similar results as when using the 'degraded' Landsat reflectance, with no significant differences between them. Model performance decreased (i.e. RMSE increased) with site heterogeneity when coarse resolution reflectance data was used. We did not find any evidence of soil colour or moisture influence on model performance. We speculate that the unmixing models may be insensitive to soil colour and/or that the soil moisture in the top few millimetres of soil, which influence reflectance in optical sensors, is decoupled from the soil moisture in the top layer (i.e. a few cm) as measured by passive microwave sensors or estimated by models. The models tended to overestimate PV in cropping areas, possibly due to a strong red/ near infrared signal in homogeneous crops which do not have a high green cover. This study sets the basis for an operational Landsat/ MODIS combined product which would benefit users with varying requirements of spatial, temporal resolution and latency and could potentially be applied to other regions in the world.

Global monitoring of atmospheric properties by the EOS MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.

1993-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) being developed for the Earth Observing System (EOS) is well suited to the global monitoring of atmospheric properties from space. Among the atmospheric properties to be examined using MODIS observations, clouds are especially important, since they are a strong modulator of the shortwave and longwave components of the earth's radiation budget. A knowledge of cloud properties (such as optical thickness and effective radius) and their variation in space and time, which are our task objectives, is also crucial to studies of global climate change. In addition, with the use of related airborne instrumentation, such as the Cloud Absorption Radiometer (CAR) and MODIS Airborne Simulator (MAS) in intensive field experiments (both national and international campaigns, see below), various types of surface and cloud properties can be derived from the measured bidirectional reflectances. These missions have provided valuable experimental data to determine the capability of narrow bandpass channels in examining the Earth's atmosphere and to aid in defining algorithms and building an understanding of the ability of MODIS to remotely sense atmospheric conditions for assessing global change. Therefore, the primary task objective is to extend and expand our algorithm for retrieving the optical thickness and effective radius of clouds from radiation measurements to be obtained from MODIS. The secondary objective is to obtain an enhanced knowledge of surface angular and spectral properties that can be inferred from airborne directional radiance measurements.

Combining HJ CCD, GF-1 WFV and MODIS Data to Generate Daily High Spatial Resolution Synthetic Data for Environmental Process Monitoring.

PubMed

Wu, Mingquan; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-08-20

The limitations of satellite data acquisition mean that there is a lack of satellite data with high spatial and temporal resolutions for environmental process monitoring. In this study, we address this problem by applying the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) and the Spatial and Temporal Data Fusion Approach (STDFA) to combine Huanjing satellite charge coupled device (HJ CCD), Gaofen satellite no. 1 wide field of view camera (GF-1 WFV) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to generate daily high spatial resolution synthetic data for land surface process monitoring. Actual HJ CCD and GF-1 WFV data were used to evaluate the precision of the synthetic images using the correlation analysis method. Our method was tested and validated for two study areas in Xinjiang Province, China. The results show that both the ESTARFM and STDFA can be applied to combine HJ CCD and MODIS reflectance data, and GF-1 WFV and MODIS reflectance data, to generate synthetic HJ CCD data and synthetic GF-1 WFV data that closely match actual data with correlation coefficients (r) greater than 0.8989 and 0.8643, respectively. Synthetic red- and near infrared (NIR)-band data generated by ESTARFM are more suitable for the calculation of Normalized Different Vegetation Index (NDVI) than the data generated by STDFA.

Combining HJ CCD, GF-1 WFV and MODIS Data to Generate Daily High Spatial Resolution Synthetic Data for Environmental Process Monitoring

PubMed Central

Wu, Mingquan; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-01-01

The limitations of satellite data acquisition mean that there is a lack of satellite data with high spatial and temporal resolutions for environmental process monitoring. In this study, we address this problem by applying the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) and the Spatial and Temporal Data Fusion Approach (STDFA) to combine Huanjing satellite charge coupled device (HJ CCD), Gaofen satellite no. 1 wide field of view camera (GF-1 WFV) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to generate daily high spatial resolution synthetic data for land surface process monitoring. Actual HJ CCD and GF-1 WFV data were used to evaluate the precision of the synthetic images using the correlation analysis method. Our method was tested and validated for two study areas in Xinjiang Province, China. The results show that both the ESTARFM and STDFA can be applied to combine HJ CCD and MODIS reflectance data, and GF-1 WFV and MODIS reflectance data, to generate synthetic HJ CCD data and synthetic GF-1 WFV data that closely match actual data with correlation coefficients (r) greater than 0.8989 and 0.8643, respectively. Synthetic red- and near infrared (NIR)-band data generated by ESTARFM are more suitable for the calculation of Normalized Different Vegetation Index (NDVI) than the data generated by STDFA. PMID:26308017

Surface BRDF estimation from an aircraft compared to MODIS and ground estimates at the Southern Great Plains site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Knobelspiesse, Kirk D.; Cairns, Brian; Schmid, Beat

2008-10-21

The surface spectral albedo is an important component of climate models since it determines the amount of incident solar radiation that is absorbed by the ground. The albedo can be highly heterogeneous, both in space and time, and thus adequate measurement and modeling is challenging. One source of measurements that constrain the surface albedo are satellite instruments that observe the Earth, such as the Moderate Resolution Imaging Spectroradiometer (MODIS). Satellites estimate the surface bidirectional reflectance distribution function (BRDF) by correcting top of the atmosphere (TOA) radiances for atmospheric effects and accumulating observations at a variety of viewing geometries. The BRDFmore » can then be used to determine the albedo that is required in climate modeling. Other measurements that provide a more direct constraint on surface albedo are those made by upward and downward looking radiometers at the ground. One product in particular, the Best Estimate Radiation Flux (BEFLUX) value added product of the Department of Energy’s Atmospheric Radiation Measurement (ARM) Program at the Southern Great Plains Central Facility (SGP CF) in central Oklahoma, has been used to evaluate the quality of the albedo products derived from MODIS BRDF estimates. These comparisons have highlighted discrepancies between the energy absorbed at the surface that is calculated from the BEFLUX products and that is predicted from the MODIS BRDF product. This paper attempts to investigate these discrepancies by using data from an airborne scanning radiometer, the Research Scanning Polarimeter (RSP) that was flown at low altitude in the vicinity of the SGP CF site during the Aerosol Lidar Validation Experiment (ALIVE) in September of 2005. The RSP is a polarimeter that scans in the direction of the aircraft ground track, and can thus estimate the BRDF in a period of seconds, rather than the days required by MODIS to accumulate enough viewing angles. Atmospheric correction is aided by the Ames Airborne Tracking Sunphotometer (AATS-14), which was operated on the same aircraft as the RSP. The RSP data can therefore be used to validate the MODIS BRDF product and diagnose the reason for the discrepancies with BEFLUX. Our analysis indicates that MODIS and RSP estimates of surface absorption and BEFLUX measurements do agree and that previously noticed differences between MODIS albedo products and BEFLUX were due as much to the analysis techniques used as to any instrumental effects. We conclude that the MODIS BRDF products provide a useful measure of surface albedo that can be used to determine whether the surface radiative heating in climate models has a realistic spatial and seasonal variation.« less

Assessment of the Broadleaf Crops Leaf Area Index Product from the Terra MODIS Instrument

NASA Technical Reports Server (NTRS)

Tan, Bin; Hu, Jiannan; Huang, Dong; Yang, Wenze; Zhang, Ping; Shabanov, Nikolay V.; Knyazikhin, Yuri; Nemani, Ramakrishna R.; Myneni, Ranga B.

2005-01-01

The first significant processing of Terra MODIS data, called Collection 3, covered the period from November 2000 to December 2002. The Collection 3 leaf area index (LAI) and fraction vegetation absorbed photosynthetically active radiation (FPAR) products for broadleaf crops exhibited three anomalies (a) high LAI values during the peak growing season, (b) differences in LAI seasonality between the radiative transfer-based main algorithm and the vegetation index based back-up algorithm, and (c) too few retrievals from the main algorithm during the summer period when the crops are at full flush. The cause of these anomalies is a mismatch between reflectances modeled by the algorithm and MODIS measurements. Therefore, the Look-Up-Tables accompanying the algorithm were revised and implemented in Collection 4 processing. The main algorithm with the revised Look-Up-Tables generated retrievals for over 80% of the pixels with valid data. Retrievals from the back-up algorithm, although few, should be used with caution as they are generated from surface reflectances with high uncertainties.

Retrieval of aerosol optical properties using MERIS observations: Algorithm and some first results.

PubMed

Mei, Linlu; Rozanov, Vladimir; Vountas, Marco; Burrows, John P; Levy, Robert C; Lotz, Wolfhardt

2017-08-01

The MEdium Resolution Imaging Spectrometer (MERIS) instrument on board ESA Envisat made measurements from 2002 to 2012. Although MERIS was limited in spectral coverage, accurate Aerosol Optical Thickness (AOT) from MERIS data are retrieved by using appropriate additional information. We introduce a new AOT retrieval algorithm for MERIS over land surfaces, referred to as eXtensible Bremen AErosol Retrieval (XBAER). XBAER is similar to the "dark-target" (DT) retrieval algorithm used for Moderate-resolution Imaging Spectroradiometer (MODIS), in that it uses a lookup table (LUT) to match to satellite-observed reflectance and derive the AOT. Instead of a global parameterization of surface spectral reflectance, XBAER uses a set of spectral coefficients to prescribe surface properties. In this manner, XBAER is not limited to dark surfaces (vegetation) and retrieves AOT over bright surface (desert, semiarid, and urban areas). Preliminary validation of the MERIS-derived AOT and the ground-based Aerosol Robotic Network (AERONET) measurements yield good agreement, the resulting regression equation is y = (0.92 × ± 0.07) + (0.05 ± 0.01) and Pearson correlation coefficient of R = 0.78. Global monthly means of AOT have been compared from XBAER, MODIS and other satellite-derived datasets.

Impacts of Cross-Platform Vicarious Calibration on the Deep Blue Aerosol Retrievals for Moderate Resolution Imaging Spectroradiometer Aboard Terra

NASA Technical Reports Server (NTRS)

Jeong, Myeong-Jae; Hsu, N. Christina; Kwiatkowska, Ewa J.; Franz, Bryan A.; Meister, Gerhard; Salustro, Clare E.

2012-01-01

The retrieval of aerosol properties from spaceborne sensors requires highly accurate and precise radiometric measurements, thus placing stringent requirements on sensor calibration and characterization. For the Terra/Moderate Resolution Imaging Spedroradiometer (MODIS), the characteristics of the detectors of certain bands, particularly band 8 [(B8); 412 nm], have changed significantly over time, leading to increased calibration uncertainty. In this paper, we explore a possibility of utilizing a cross-calibration method developed for characterizing the Terral MODIS detectors in the ocean bands by the National Aeronautics and Space Administration Ocean Biology Processing Group to improve aerosol retrieval over bright land surfaces. We found that the Terra/MODIS B8 reflectance corrected using the cross calibration method resulted in significant improvements for the retrieved aerosol optical thickness when compared with that from the Multi-angle Imaging Spectroradiometer, Aqua/MODIS, and the Aerosol Robotic Network. The method reported in this paper is implemented for the operational processing of the Terra/MODIS Deep Blue aerosol products.

Developing a Validated Long-Term Satellite-Based Albedo Record in the Central Alaska Range to Improve Regional Hydroclimate Reconstructions

NASA Astrophysics Data System (ADS)

Kreutz, K. J.; Godaire, T. P.; Burakowski, E. A.; Winski, D.; Campbell, S. W.; Wang, Z.; Sun, Q.; Hamilton, G. S.; Birkel, S. D.; Wake, C. P.; Osterberg, E. C.; Schaaf, C.

2015-12-01

Mountain glaciers around the world, particularly in Alaska, are experiencing significant surface mass loss from rapid climatic shifts and constitute a large proportion of the cryosphere's contribution to sea level rise. Surface albedo acts as a primary control on a glacier's mass balance, yet it is difficult to measure and quantify spatially and temporally in steep, mountainous settings. During our 2013 field campaign in Denali National Park to recover two surface to bedrock ice cores, we used an Analytical Spectral Devices (ASD) FieldSpec4 Standard Resolution spectroradiometer to measure incoming solar radiation, outgoing surface reflectance and optical grain size on the Kahiltna Glacier and at the Kahiltna Base Camp. A Campbell Scientific automatic weather station was installed on Mount Hunter (3900m) in June 2013, complementing a longer-term (2008-present) station installed at Kahiltna Base Camp (2100m). Use of our in situ data aids in the validation of surface albedo values derived from Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat satellite imagery. Comparisons are made between ASD FieldSpec4 ground measurements and 500m MODIS imagery to assess the ability of MODIS to capture the variability of surface albedo across the glacier surface. The MODIS MCD43A3 BRDF/Albedo Product performs well at Kahiltna Base Camp (<5% difference from ASD shortwave broadband data), but low biases in MODIS albedo (10-28% relative to ASD data) appear to occur along the Kahiltna Glacier due to the snow-free valley walls being captured in the 500m MODIS footprint. Incorporating Landsat imagery will strengthen our interpretations and has the potential to produce a long-term (1982-present) validated satellite albedo record for steep and mountainous terrain. Once validation is complete, we will compare the satellite-derived albedo record to the Denali ice core accumulation rate, aerosol records (i.e. volcanics and biomass burning), and glacier mass balance data. This research will ultimately contribute to an improved understanding of the relationship between glacier albedo, surface processes, and regional glacier hydroclimate.

Transitioning from MODIS to VIIRS: an analysis of inter-consistency of NDVI data sets for agricultural monitoring.

PubMed

Skakun, Sergii; Justice, Christopher O; Vermote, Eric; Roger, Jean-Claude

2018-01-01

The Visible/Infrared Imager/Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite was launched in 2011, in part to provide continuity with the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard National Aeronautics and Space Administration's (NASA) Terra and Aqua remote sensing satellites. The VIIRS will eventually replace MODIS for both land science and applications and add to the coarse-resolution, long term data record. It is, therefore, important to provide the user community with an assessment of the consistency of equivalent products from the two sensors. For this study, we do this in the context of example agricultural monitoring applications. Surface reflectance that is routinely delivered within the M{O,Y}D09 and VNP09 series of products provide critical input for generating downstream products. Given the range of applications utilizing the normalized difference vegetation index (NDVI) generated from M{O,Y}D09 and VNP09 products and the inherent differences between MODIS and VIIRS sensors in calibration, spatial sampling, and spectral bands, the main objective of this study is to quantify uncertainties related the transitioning from using MODIS to VIIRS-based NDVI's. In particular, we compare NDVI's derived from two sets of Level 3 MYD09 and VNP09 products with various spatial-temporal characteristics, namely 8-day composites at 500 m spatial resolution and daily Climate Modelling Grid (CMG) images at 0.05° spatial resolution. Spectral adjustment of VIIRS I1 (red) and I2 (near infra-red - NIR) bands to match MODIS/Aqua b1 (red) and b2 (NIR) bands is performed to remove a bias between MODIS and VIIRS-based red, NIR, and NDVI estimates. Overall, red reflectance, NIR reflectance, NDVI uncertainties were 0.014, 0.029 and 0.056 respectively for the 500 m product and 0.013, 0.016 and 0.032 for the 0.05° product. The study shows that MODIS and VIIRS NDVI data can be used interchangeably for applications with an uncertainty of less than 0.02 to 0.05, depending on the scale of spatial aggregation, which is typically the uncertainty of the individual dataset.

Spectral Reflectance and Albedo of Snow-Covered Heterogeneous Landscapes in New Hampshire, USA: Comparison of Ground-based, Airborne Hyperspectral, and MODIS Satellite Data

NASA Astrophysics Data System (ADS)

Burakowski, E. A.; Ollinger, S. V.; Martin, M.; Lepine, L. C.; Hollinger, D. Y.; Dibb, J. E.

2013-12-01

This study evaluates the accuracy of hyperspectral imagery (HSI) and MODIS daily 500-m snow albedo over forested, deforested, and mixed land use types under snow-covered conditions in New Hampshire, USA. HSI spectral reflectance generally agrees well with tower-based measurements above a mixed forest canopy. Over cleared pasture, HSI spectral reflectance is lower than ground-based measurements collected using a spectrometer, and greatly underestimates reflectance at wavelengths less than 430 nm. Based on tower-based albedo measurements, HSI shortwave broadband albedo meets the absolute accuracy requirement of ×0.05 recommended for climate modeling. When HSI 5-m fine-resolution imagery is aggregated to MODIS 500-m resolution and integrated to shortwave broadband albedo, MOD10A1 daily snow-covered surface albedo exhibits a negative bias of -0.0033 and root mean square error (RMSE) of 0.067 compared to HSI shortwave broadband albedo, just outside the range of the absolute accuracy requirement of ×0.05 recommended for climate modeling. Spectral albedo collected over a deciduous broadleaf canopy under snow-covered and snow-free conditions will expand the existing spectral library and contribute to future validation efforts of multi-spectral remote sensing products (e.g., HyspIRI).

Validation of MODIS-derived bidirectional reflectivity retrieval algorithm in mid-infrared channel with field measurements.

PubMed

Tang, Bo-Hui; Wu, Hua-; Li, Zhao-Liang; Nerry, Françoise

2012-07-30

This work addressed the validation of the MODIS-derived bidirectional reflectivity retrieval algorithm in mid-infrared (MIR) channel, proposed by Tang and Li [Int. J. Remote Sens. 29, 4907 (2008)], with ground-measured data, which were collected from a field campaign that took place in June 2004 at the ONERA (Office National d'Etudes et de Recherches Aérospatiales) center of Fauga-Mauzac, on the PIRRENE (Programme Interdisciplinaire de Recherche sur la Radiométrie en Environnement Extérieur) experiment site [Opt. Express 15, 12464 (2007)]. The leaving-surface spectral radiances measured by a BOMEM (MR250 Series) Fourier transform interferometer were used to calculate the ground brightness temperatures with the combination of the inversion of the Planck function and the spectral response functions of MODIS channels 22 and 23, and then to estimate the ground brightness temperature without the contribution of the solar direct beam and the bidirectional reflectivity by using Tang and Li's proposed algorithm. On the other hand, the simultaneously measured atmospheric profiles were used to obtain the atmospheric parameters and then to calculate the ground brightness temperature without the contribution of the solar direct beam, based on the atmospheric radiative transfer equation in the MIR region. Comparison of those two kinds of brightness temperature obtained by two different methods indicated that the Root Mean Square Error (RMSE) between the brightness temperatures estimated respectively using Tang and Li's algorithm and the atmospheric radiative transfer equation is 1.94 K. In addition, comparison of the hemispherical-directional reflectances derived by Tang and Li's algorithm with those obtained from the field measurements showed that the RMSE is 0.011, which indicates that Tang and Li's algorithm is feasible to retrieve the bidirectional reflectivity in MIR channel from MODIS data.

Enhanced Deep Blue Aerosol Retrieval Algorithm: The Second Generation

NASA Technical Reports Server (NTRS)

Hsu, N. C.; Jeong, M.-J.; Bettenhausen, C.; Sayer, A. M.; Hansell, R.; Seftor, C. S.; Huang, J.; Tsay, S.-C.

2013-01-01

The aerosol products retrieved using the MODIS collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semi-arid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and non- vegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of pre-calculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semi-arid regions to the entire land areas.

Dust transport model validation using satellite- and ground-based methods in the southwestern United States

NASA Astrophysics Data System (ADS)

Mahler, Anna-Britt; Thome, Kurt; Yin, Dazhong; Sprigg, William A.

2006-08-01

Dust is known to aggravate respiratory diseases. This is an issue in the desert southwestern United States, where windblown dust events are common. The Public Health Applications in Remote Sensing (PHAiRS) project aims to address this problem by using remote-sensing products to assist in public health decision support. As part of PHAiRS, a model for simulating desert dust cycles, the Dust Regional Atmospheric Modeling (DREAM) system is employed to forecast dust events in the southwestern US. Thus far, DREAM has been validated in the southwestern US only in the lower part of the atmosphere by comparison with measurement and analysis products from surface synoptic, surface Meteorological Aerodrome Report (METAR), and upper-air radiosonde. This study examines the validity of the DREAM algorithm dust load prediction in the desert southwestern United States by comparison with satellite-based MODIS level 2 and MODIS Deep Blue aerosol products, and ground-based observations from the AERONET network of sunphotometers. Results indicate that there are difficulties obtaining MODIS L2 aerosol optical thickness (AOT) data in the desert southwest due to low AOT algorithm performance over areas with high surface reflectances. MODIS Deep Blue aerosol products show improvement, but the temporal and vertical resolution of MODIS data limit its utility for DREAM evaluation. AERONET AOT data show low correlation to DREAM dust load predictions. The potential contribution of space- or ground-based lidar to the PHAiRS project is also examined.

Satellite Monitoring of Long-Range Transport of Asian Dust Storms from Sources to Sinks

NASA Astrophysics Data System (ADS)

Hsu, N.; Tsay, S.; Jeong, M.; King, M.; Holben, B.

2007-05-01

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of spring-time cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such popu-lation centers causes flight delays, pushes grit through windows and doors, and forces people indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol optical thickness and single scattering albedo over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been dif-ficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. Deep Blue algorithm has recently been integrated into the MODIS processing stream and began to provide aerosol products over land as part of the opera-tional MYD04 products. In this talk, we will show the comparisons of the MODIS Deep Blue products with data from AERONET sunphotometers on a global ba-sis. The results indicate reasonable agreements between these two. These new satellite products will allow scientists to determine quantitatively the aerosol properties near sources and their evolution along transport pathway using high spatial resolution measurements from SeaWiFS and MODIS-like instruments. We will also utilize the multiyear satellite measurements from MODIS and SeaWiFS to investigate the interannual variability of source strength, pathway, and radia-tive forcing associated with these dust outbreaks in East Asia.

Preliminary Analysis of the Performance of the Landsat 8/OLI Land Surface Reflectance Product

NASA Technical Reports Server (NTRS)

Vermote, Eric; Justice, Chris; Claverie, Martin; Franch, Belen

2016-01-01

The surface reflectance, i.e., satellite derived top of atmosphere (TOA) reflectance corrected for the temporally, spatially and spectrally varying scattering and absorbing effects of atmospheric gases and aerosols, is needed to monitor the land surface reliably. For this reason, the surface reflectance, and not TOA reflectance, is used to generate the greater majority of global land products, for example, from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) sensors. Even if atmospheric effects are minimized by sensor design, atmospheric effects are still challenging to correct. In particular, the strong impact of aerosols in the visible and near infrared spectral range can be difficult to correct, because they can be highly discrete in space and time (e.g., smoke plumes) and because of the complex scattering and absorbing properties of aerosols that vary spectrally and with aerosol size, shape, chemistry and density.

Vegetation Canopy Structure from NASA EOS Multiangle Imaging

NASA Astrophysics Data System (ADS)

Chopping, M.; Martonchik, J. V.; Bull, M.; Rango, A.; Schaaf, C. B.; Zhao, F.; Wang, Z.

2008-12-01

We used red band bidirectional reflectance data from the NASA Multiangle Imaging SpectroRadiometer (MISR) and the MODerate resolution Imaging Spectroradiometer (MODIS) mapped onto a 250 m grid in a multiangle approach to obtain estimates of woody plant fractional cover and crown height through adjustment of the mean radius and mean crown aspect ratio parameters of an hybrid geometric-optical (GO) model. We used a technique to rapidly obtain MISR surface reflectance estimates at 275 m resolution through regression on 1 km MISR land surface estimates previously corrected for atmospheric attenuation using MISR aerosol estimates. MISR data were used to make end of dry season maps from 2000-2007 for parts of southern New Mexico, while MODIS data were used to replicate previous results obtained using MISR for June 2002 over large parts of New Mexico and Arizona. We also examined the applicability of this method in Alaskan tundra and forest by adjusting the GO model against MISR data for winter (March 2000) and summer (August 2008) scenes. We found that the GO model crown aspect ratio from MISR followed dominant shrub species distributions in the USDA, ARS Jornada Experimental Range, enabling differentiation of the more spherical crowns of creosotebush (Larrea tridentata) from the more prolate crowns of honey mesquite (Prosopis glandulosa). The measurement limits determined from 2000-2007 maps for a large part of southern New Mexico are ~0.1 in fractional shrub crown cover and ~3 m in mean canopy height (results obtained using data acquired shortly after precipitation events that radically darkened and altered the structure and angular response of the background). Typical standard deviations over the period for 12 sites covering a range of cover types are on the order of 0.05 in crown cover and 2 m in mean canopy height. We found that the GO model can be inverted to retrieve reasonable distributions of canopy parameters in southwestern environments using MODIS V005 red band surface reflectance estimates at ~250 m spatial resolution accumulated over 16 day periods. The MODIS (N=895) and MISR (N=576) estimates of forest height and cover both showed agreement with USDA, Forest Service estimates, with MODIS mean absolute errors (MAE) of 0.09 and 8.4 m respectively; and MISR MAE of 0.10 and 2.2 m, respectively, noting that a sub-optimal background was used for the MODIS inversions. The MODIS and MISR MAE for estimates of aboveground woody biomass via regression against Forest Service estimates were both 10.1 Mg.ha-1. We found that red band MISR data for central Alaska can be used to obtain first-order estimates of forest cover and height using a snow-free summer scene and shrub cover using a winter scene with full snow cover. The GO model inversion results are often physically unrealistic but spatial distributions correspond to high resolution images and reflect the potential for the multiangle/GO method to retrieve meaningful information that is qualitatively different to that obtained using vegetation indices.

Evaluation of Satellite Remote Sensing Albedo Retrievals over the Ablation Area of the Southwestern Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Moustafa, Samiah E.; Rennermalm, Asa K.; Roman, Miguel O.; Wang, Zhuosen; Schaaf, Crystal B.; Smith, Laurence C.; Koenig, Lora S.; Erb, Angela

2017-01-01

MODerate resolution Imaging Spectroradiometer (MODIS) albedo products have been validated over spatially uniform, snow-covered areas of the Greenland ice sheet (GrIS) using the so-called single 'point-to-pixel' method. This study expands on this methodology by applying a 'multiple-point-to-pixel' method and examination of spatial autocorrelation (here using semivariogram analysis) by using in situ observations, high-resolution World- View-2 (WV-2) surface reflectances, and MODIS Collection V006 daily blue-sky albedo over a spatially heterogeneous surfaces in the lower ablation zone in southwest Greenland. Our results using 232 ground-based samples within two MODIS pixels, one being more spatial heterogeneous than the other, show little difference in accuracy among narrow and broad band albedos (except for Band 2). Within the more homogenous pixel area, in situ and MODIS albedos were very close (error varied from -4% to +7%) and within the range of ASD standard errors. The semivariogram analysis revealed that the minimum observational footprint needed for a spatially representative sample is 30 m. In contrast, over the more spatially heterogeneous surface pixel, a minimum footprint size was not quantifiable due to spatial autocorrelation, and far exceeds the effective resolution of the MODIS retrievals. Over the high spatial heterogeneity surface pixel, MODIS is lower than ground measurements by 4-7%, partly due to a known in situ undersampling of darker surfaces that often are impassable by foot (e.g., meltwater features and shadowing effects over crevasses). Despite the sampling issue, our analysis errors are very close to the stated general accuracy of the MODIS product of 5%. Thus, our study suggests that the MODIS albedo product performs well in a very heterogeneous, low-albedo, area of the ice sheet ablation zone. Furthermore, we demonstrate that single 'point-to-pixel' methods alone are insufficient in characterizing and validating the variation of surface albedo displayed in the lower ablation area. This is true because the distribution of in situ data deviations from MODIS albedo show a substantial range, with the average values for the 10th and 90th percentiles being -0.30 and 0.43 across all bands. Thus, if only single point is taken for ground validation, and is randomly selected from either distribution tails, the error would appear to be considerable. Given the need for multiple in-situ points, concurrent albedo measurements derived from existing AWSs, (low-flying vehicles (airborne or unmanned) and high-resolution imagery (WV-2)) are needed to resolve high sub-pixel variability in the ablation zone, and thus, further improve our characterization of Greenland's surface albedo.

Remote Sensing of Cloud, Aerosol, and Land Properties from MODIS: Applications to the East Asia Region

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Moody, Eric G.

2002-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999 and the Aqua satellite in May 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper we will describe the various methods being used for the remote sensing of cloud, aerosol, and surface properties using MODIS data, focusing primarily on (i) the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, (ii) cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals, (iii) aerosol optical thickness and size characteristics both over land and ocean, and (iv) ecosystem classification and surface spectral reflectance. The physical principles behind the determination of each of these products will be described, together with an example of their application using MODIS observations to the east Asian region. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 min (Level-3 products).

The MODIS Vegetation Canopy Water Content product

NASA Astrophysics Data System (ADS)

Ustin, S. L.; Riano, D.; Trombetti, M.

2008-12-01

Vegetation water stress drives wildfire behavior and risk, having important implications for biogeochemical cycling in natural ecosystems, agriculture, and forestry. Water stress limits plant transpiration and carbon gain. The regulation of photosynthesis creates close linkages between the carbon, water, and energy cycles and through metabolism to the nitrogen cycle. We generated systematic weekly CWC estimated for the USA from 2000-2006. MODIS measures the sunlit reflectance of the vegetation in the visible, near-infrared, and shortwave infrared. Radiative transfer models, such as PROSPECT-SAILH, determine how sunlight interacts with plant and soil materials. These models can be applied over a range of scales and ecosystem types. Artificial Neural Networks (ANN) were used to optimize the inversion of these models to determine vegetation water content. We carried out multi-scale validation of the product using field data, airborne and satellite cross-calibration. An Algorithm Theoretical Basis Document (ATBD) of the product is under evaluation by NASA. The CWC product inputs are 1) The MODIS Terra/Aqua surface reflectance product (MOD09A1/MYD09A1) 2) The MODIS land cover map product (MOD12Q1) reclassified to grassland, shrub-land and forest canopies; 3) An ANN trained with PROSPECT-SAILH; 4) A calibration file for each land cover type. The output is an ENVI file with the CWC values. The code is written in Matlab environment and is being adapted to read not only the 8 day MODIS composites, but also daily surface reflectance data. We plan to incorporate the cloud and snow mask and generate as output a geotiff file. Vegetation water content estimates will help predicting linkages between biogeochemical cycles, which will enable further understanding of feedbacks to atmospheric concentrations of greenhouse gases. It will also serve to estimate primary productivity of the biosphere; monitor/assess natural vegetation health related to drought, pollution or diseases; improve irrigation scheduling by reducing over-watering and under-watering. These estimates will also allow researchers to identify wildfire behavior/risk: drives ignition probability and burning efficiency; to be used as an indicator of soil moisture and Leaf Area Index.

Monitoring the On-Orbit Calibration of Terra MODIS Reflective Solar Bands Using Simultaneous Terra MISR Observations

NASA Technical Reports Server (NTRS)

Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng

2016-01-01

On December 18, 2015, the Terra spacecraft completed 16 years of successful operation in space. Terra has five instruments designed to facilitate scientific measurements of the earths land, ocean, and atmosphere. The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging Spectroradiometer (MISR) instruments provide information for the temporal studies of the globe. After providing over 16 years of complementary measurements, a synergistic use of the measurements obtained from these sensors is beneficial for various science products. The 20 reflective solar bands (RSBs) of MODIS are calibrated using a combination of solar diffuser and lunar measurements, supplemented by measurements from pseudoinvariant desert sites. MODIS views the on-board calibrators and the earth via a two-sided scan mirror at three spatial resolutions: 250 m using 40 detectors in bands 1 and 2, 500 m using 20 detectors in bands 3 and 4, and 1000 m using 10 detectors in bands 819 and 26. Simultaneous measurements of the earths surface are acquired in a push-broom fashion by MISR at nine view angles spreading out in the forward and backward directions along the flight path. While the swath width for MISR acquisitions is 360 km, MODIS scans a wider swath of 2330 km via its two-sided scan mirror. The reflectance of the MODIS scan mirror has an angle dependence characterized by the response versus scan angle (RVS). Its on-orbit change is derived using the gain from a combination of on-board and earth-view measurements. The on-orbit RVS for MODIS has experienced a significant change, especially for the short-wavelength bands. The on-orbit RVS change for the short-wavelength bands (bands 3, 8, and 9) at nadir is observed to be greater than 10 over the mission lifetime. Due to absence of a scanning mechanism, MISR can serve as an effective tool to evaluate and monitor the on-orbit performance of the MODIS RVS. Furthermore, it can also monitor the detector and scan-mirror differences for the MODIS bands using simultaneous measurements from earth-scene targets, e.g., North Atlantic Ocean and North African desert. Simultaneous measurements provide the benefit of minimizing the impact of earth-scene features while comparing the radiometric performance using vicarious techniques. Long-term observations of both instruments using select ground targets also provide an evaluation of the long-term calibration stability. The goal of this paper is to demonstrate the use of MISR to monitor and enhance the on-orbit calibration of the MODIS RSB. The radiometric calibration requirements for the MODIS RSB are +/- 2% in reflectance and +/- 5% in radiance at typical radiance levels within +/- 45 deg. of nadir. The results show that the long-term changes in the MODIS reflectance at nadir frames are generally within 1. The MODIS level 1B calibrated products, generated after correcting for the on-orbit changes in the gain and RVS, do not have any correction for changes in the instruments polarization sensitivity. The mirror-side-dependent polarization sensitivity exhibits an on-orbit change, primarily in the blue bands, that manifests in noticeable mirror side differences in the MODIS calibrated products. The mirror side differences for other RSB are observed to be less than 1%, therefore demonstrating an excellent on-orbit performance. The detector differences in the blue bands of MODIS exhibit divergence in recent years beyond 1%, and a calibration algorithm improvement has been identified to mitigate this effect. Short-term variations in the recent year caused by the forward updates were identified in bands 1 and 2 and are planned to be corrected in the next reprocess.

Greenland ice sheet albedo variability and feedback: 2000-2015

NASA Astrophysics Data System (ADS)

Box, J. E.; van As, D.; Fausto, R. S.; Mottram, R.; Langen, P. P.; Steffen, K.

2015-12-01

Absorbed solar irradiance represents the dominant source of surface melt energy for Greenland ice. Surface melting has increased as part of a positive feedback amplifier due to surface darkening. The 16 most recent summers of observations from the NASA MODIS sensor indicate a darkening exceeding 6% in July when most melting occurs. Without the darkening, the increase in surface melting would be roughly half as large. A minority of the albedo decline signal may be from sensor degradation. So, in this study, MOD10A1 and MCD43 albedo products from MODIS are evaluated for sensor degradation and anisotropic reflectance errors. Errors are minimized through calibration to GC-Net and PROMICE Greenland snow and ice ground control data. The seasonal and spatial variability in Greenland snow and ice albedo over a 16 year period is presented, including quantifying changing absorbed solar irradiance and melt enhancement due to albedo feedback using the DMI HIRHAM5 5 km model.

Characterization of water bodies for mosquito habitat using a multi-sensor approach

NASA Astrophysics Data System (ADS)

Midekisa, A.; Wimberly, M. C.; Senay, G. B.

2012-12-01

Malaria is a major health problem in Ethiopia. Anopheles arabiensis, which inhabits and breeds in a variety of aquatic habitats, is the major mosquito vector for malaria transmission in the region. In the Amhara region of Ethiopia, mosquito breeding sites are heterogeneously distributed. Therefore, accurate characterization of aquatic habitats and potential breeding sites can be used as a proxy to measure the spatial distribution of malaria risk. Satellite remote sensing provides the ability to map the spatial distribution and monitor the temporal dynamics of surface water. The objective of this study is to map the probability of surface water accumulation to identify potential vector breeding sites for Anopheles arabiensis using remote sensing data from sensors at multiple spatial and temporal resolutions. The normalized difference water index (NDWI), which is based on reflectance in the green and the near infrared (NIR) bands were used to estimate fractional cover of surface water. Temporal changes in surface water were mapped using NDWI indices derived from MODIS surface reflectance product (MOD09A1) for the period 2001-2012. Landsat TM and ETM+ imagery were used to train and calibrate model results from MODIS. Results highlighted interannual variation and seasonal changes in surface water that were observed from the MODIS time series. Static topographic indices that estimate the potential for water accumulation were generated from 30 meter Shuttle Radar Topography Mission (SRTM) elevation data. Integrated fractional surface water cover was developed by combining the static topographic indices and dynamic NDWI indices using Geographic Information System (GIS) overlay methods. Accuracy of the results was evaluated based on ground truth data that was collected on presence and absence of surface water immediately after the rainy season. The study provided a multi-sensor approach for mapping areas with a high potential for surface water accumulation that are potential breeding habitats for anopheline mosquitoes. The resulting products are useful for public health decision making towards effective prevention and control of the malaria burden in the Amhara region of Ethiopia.

Assessing Seasonal and Inter-Annual Variations of Lake Surface Areas in Mongolia during 2000-2011 Using Minimum Composite MODIS NDVI

PubMed Central

Kang, Sinkyu; Hong, Suk Young

2016-01-01

A minimum composite method was applied to produce a 15-day interval normalized difference vegetation index (NDVI) dataset from Moderate Resolution Imaging Spectroradiometer (MODIS) daily 250 m reflectance in the red and near-infrared bands. This dataset was applied to determine lake surface areas in Mongolia. A total of 73 lakes greater than 6.25 km2in area were selected, and 28 of these lakes were used to evaluate detection errors. The minimum composite NDVI showed a better detection performance on lake water pixels than did the official MODIS 16-day 250 m NDVI based on a maximum composite method. The overall lake area detection performance based on the 15-day minimum composite NDVI showed -2.5% error relative to the Landsat-derived lake area for the 28 evaluated lakes. The errors increased with increases in the perimeter-to-area ratio but decreased with lake size over 10 km2. The lake area decreased by -9.3% at an annual rate of -53.7 km2 yr-1 during 2000 to 2011 for the 73 lakes. However, considerable spatial variations, such as slight-to-moderate lake area reductions in semi-arid regions and rapid lake area reductions in arid regions, were also detected. This study demonstrated applicability of MODIS 250 m reflectance data for biweekly monitoring of lake area change and diagnosed considerable lake area reduction and its spatial variability in arid and semi-arid regions of Mongolia. Future studies are required for explaining reasons of lake area changes and their spatial variability. PMID:27007233

Principles in Remote Sensing of Aerosol from MODIS Over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Chu, D. A.

1999-01-01

The well-calibrated spectral radiances measured by MODIS will be processed to retrieve daily aerosol properties that include optical thickness and mass loading over land and optical thickness, the mean particle size of the dominant mode and the ratio between aerosol modes over ocean. In addition, after launch, aerosol single scattering albedo will be calculated as an experimental product. The retrieval process over land is based on a dark target method that identifies appropriate targets in the mid-IR channels and uses an empirical relationship found between the mid-ER and the visible channels to estimate surface reflectance in the visible from the mid-HZ reflectance measured by satellite. The method employs new aerosol models for industrial, smoke and dust aerosol. The process for retrieving aerosol over the ocean makes use of the wide spectral band from 0.55-2.13 microns and a look-up table constructed from combinations of five accumulation modes and five coarse modes. Both the over land and over ocean algorithms have been validated with satellite and airborne radiance measurements. We estimate that MODIS will be able to measure aerosol optical thickness (t) to within 0.05 +/- 0.2t over land and to within 0.05 +/- 0.05t over ocean. Much of the earth's surface is located far from aerosol sources and experience very low aerosol optical thickness. Will the accuracy expected from MODIS retrievals be sufficient to measure the global aerosol direct and indirect forcing? We are attempting to answer this question using global model results and cloud climatology.

Assessing Seasonal and Inter-Annual Variations of Lake Surface Areas in Mongolia during 2000-2011 Using Minimum Composite MODIS NDVI.

PubMed

Kang, Sinkyu; Hong, Suk Young

2016-01-01

A minimum composite method was applied to produce a 15-day interval normalized difference vegetation index (NDVI) dataset from Moderate Resolution Imaging Spectroradiometer (MODIS) daily 250 m reflectance in the red and near-infrared bands. This dataset was applied to determine lake surface areas in Mongolia. A total of 73 lakes greater than 6.25 km2in area were selected, and 28 of these lakes were used to evaluate detection errors. The minimum composite NDVI showed a better detection performance on lake water pixels than did the official MODIS 16-day 250 m NDVI based on a maximum composite method. The overall lake area detection performance based on the 15-day minimum composite NDVI showed -2.5% error relative to the Landsat-derived lake area for the 28 evaluated lakes. The errors increased with increases in the perimeter-to-area ratio but decreased with lake size over 10 km(2). The lake area decreased by -9.3% at an annual rate of -53.7 km(2) yr(-1) during 2000 to 2011 for the 73 lakes. However, considerable spatial variations, such as slight-to-moderate lake area reductions in semi-arid regions and rapid lake area reductions in arid regions, were also detected. This study demonstrated applicability of MODIS 250 m reflectance data for biweekly monitoring of lake area change and diagnosed considerable lake area reduction and its spatial variability in arid and semi-arid regions of Mongolia. Future studies are required for explaining reasons of lake area changes and their spatial variability.

Albedo Drop on the Greenland Ice Sheet: Relative Impacts of Wet and Dry Snow Processes

NASA Astrophysics Data System (ADS)

Chen, J.; Polashenski, C.

2014-12-01

The energy balance of the Greenland Ice Sheet (GIS) is strongly impacted by changes in snow albedo. MODIS (Moderate Resolution Imaging Spectroradiometer) observations indicate that the GIS albedo has dropped since the early part of this century. We analyze data from the MODIS products MOD10A1 for broadband snow albedo and MOD09A1 for surface spectral reflectance since 2001 to better explain the physical mechanisms driving these changes. The MODIS products are filtered, and the data is masked using microwave-derived surface melt maps to isolate albedo changes due to dry snow processes from those driven by melt impacts. Results show that the majority of recent changes in the GIS albedo - even at high elevations - are driven by snow wetting rather than dry snow processes such as grain metamorphosis and aerosol impurity deposition. The spectral signature of the smaller changes occurring within dry snow areas suggests that grain metamorphosis dominates the albedo decline in these regions.

Seasonal Surface Spectral Emissivity Derived from Terra MODIS Data

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Chen, Yan; Minnis, Patrick; Young, DavidF.; Smith, William J., Jr.

2004-01-01

The CERES (Clouds and the Earth's Radiant Energy System) Project is measuring broadband shortwave and longwave radiances and deriving cloud properties form various images to produce a combined global radiation and cloud property data set. In this paper, simultaneous data from Terra MODIS (Moderate Resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 11.0, and 12.0 m are used to derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of clear sky temperature in each channel determined by scene classification during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7- m radiances. A set of simultaneous equations is then solved to derive the emissivities. Global monthly emissivity maps are derived from Terra MODIS data while numerical weather analyses provide soundings for correcting the observed radiances for atmospheric absorption. These maps are used by CERES and other cloud retrieval algorithms.

Satellite aerosol retrieval using dark target algorithm by coupling BRDF effect over AERONET site

NASA Astrophysics Data System (ADS)

Yang, Leiku; Xue, Yong; Guang, Jie; Li, Chi

2012-11-01

For most satellite aerosol retrieval algorithms even for multi-angle instrument, the simple forward model (FM) based on Lambertian surface assumption is employed to simulate top of the atmosphere (TOA) spectral reflectance, which does not fully consider the surface bi-directional reflectance functions (BRDF) effect. The approximating forward model largely simplifies the radiative transfer model, reduces the size of the look-up tables, and creates faster algorithm. At the same time, it creates systematic biases in the aerosol optical depth (AOD) retrieval. AOD product from the Moderate Resolution Imaging Spectro-radiometer (MODIS) data based on the dark target algorithm is considered as one of accurate satellite aerosol products at present. Though it performs well at a global scale, uncertainties are still found on regional in a lot of studies. The Lambertian surface assumpiton employed in the retrieving algorithm may be one of the uncertain factors. In this study, we first use radiative transfer simulations over dark target to assess the uncertainty to what extent is introduced from the Lambertian surface assumption. The result shows that the uncertainties of AOD retrieval could reach up to ±0.3. Then the Lambertian FM (L_FM) and the BRDF FM (BRDF_FM) are respectively employed in AOD retrieval using dark target algorithm from MODARNSS (MODIS/Terra and MODIS/Aqua Atmosphere Aeronet Subsetting Product) data over Beijing AERONET site. The validation shows that accuracy in AOD retrieval has been improved by employing the BRDF_FM accounting for the surface BRDF effect, the regression slope of scatter plots with retrieved AOD against AEROENET AOD increases from 0.7163 (for L_FM) to 0.7776 (for BRDF_FM) and the intercept decreases from 0.0778 (for L_FM) to 0.0627 (for BRDF_FM).

Validation of a Climate-Data Record of the "Clear-Kky" Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Box, Jason E.; Koenig, Lora S.; DiGirolamo, Nicolo E.; Comiso, Josefino C.; Shuman, Christopher A.

2011-01-01

Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented since 1981. We extended and refined this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. We developed a daily and monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using an ice-surface temperature (1ST) algorithm developed for use with MODIS data. Validation of this CDR is ongoing. MODIS Terra swath data are projected onto a polar stereographic grid at 6.25-km resolution to develop binary, gridded daily and mean-monthly 1ST maps. Each monthly map also has a color-coded image map that is available to download. Also included with the monthly maps is an accompanying map showing number of days in the month that were used to calculate the mean-monthly 1ST. This is important because no 1ST decision is made by the algorithm for cells that are considered cloudy by the internal cloud mask, so a sufficient number of days must be available to produce a mean 1ST for each grid cell. Validation of the CDR consists of several facets: 1) comparisons between ISTs and in-situ measurements; 2) comparisons between ISTs and AWS data; and 3) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer (ASTER) and Enhanced Thematic Mapper Plus (ETM+). Previous work shows that Terra MODIS ISTs are about 3 C lower than in-situ temperatures measured at Summit Camp, during the winter of 2008-09 under clear skies. In this work we begin to compare surface temperatures derived from AWS data with ISTs from the MODIS CDR. The Greenland Ice Sheet 1ST CDR will be useful for monitoring surface-temperature trends and can be used as input or for validation of climate models. The CDR can be extended into the future using MODIS Terra, Aqua and NPOESS Preparatory Project Visible Infrared Imager Radiometer Suite (VII RS) data.

Application of a new leaf area index algorithm to China's landmass using MODIS data for carbon cycle research.

PubMed

Liu, R; Chen, J M; Liu, J; Deng, F; Sun, R

2007-11-01

An operational system was developed for mapping the leaf area index (LAI) for carbon cycle models from the moderate resolution imaging spectroradiometer (MODIS) data. The LAI retrieval algorithm is based on Deng et al. [2006. Algorithm for global leaf area index retrieval using satellite imagery. IEEE Transactions on Geoscience and Remote Sensing, 44, 2219-2229], which uses the 4-scale radiative transfer model [Chen, J.M., Leblancs, 1997. A 4-scale bidirectional reflection model based on canopy architecture. IEEE Transactions on Geoscience and Remote Sensing, 35, 1316-1337] to simulate the relationship of LAI with vegetated surface reflectance measured from space for various spectral bands and solar and view angles. This algorithm has been integrated to the MODISoft platform, a software system designed for processing MODIS data, to generate 250 m, 500 m and 1 km resolution LAI products covering all of China from MODIS MOD02 or MOD09 products. The multi-temporal interpolation method was implemented to remove the residual cloud and other noise in the final LAI product so that it can be directly used in carbon models without further processing. The retrieval uncertainties from land cover data were evaluated using five different data sets available in China. The results showed that mean LAI discrepancies can reach 27%. The current product was also compared with the NASA MODIS MOD15 LAI product to determine the agreement and disagreement of two different product series. LAI values in the MODIS product were found to be 21% larger than those in the new product. These LAI products were compared against ground TRAC measurements in forests in Qilian Mountain and Changbaishan. On average, the new LAI product agrees with the field measurement in Changbaishan within 2%, but the MODIS product is positively biased by about 20%. In Qilian Mountain, where forests are sparse, the new product is lower than field measurements by about 38%, while the MODIS product is larger by about 65%.

The contribution of brown vegetation to vegetation dynamics

USDA-ARS?s Scientific Manuscript database

Indices of vegetation dynamics that include both green vegetation (GV) and non-photosynthetic vegetation (NPV), that is, brown vegetation, were applied to MODIS surface reflectance data from 2000 to 2006 for the southwestern United States. These indices reveal that the cover of NPV, a measure of veg...

The use of the Sonoran Desert as a pseudo-invariant site for optical sensor cross-calibration and long-term stability monitoring

USGS Publications Warehouse

Angal, A.; Chander, Gyanesh; Choi, Taeyoung; Wu, Aisheng; Xiong, Xiaoxiong

2010-01-01

The Sonoran Desert is a large, flat, pseudo-invariant site near the United States-Mexico border. It is one of the largest and hottest deserts in North America, with an area of 311,000 square km. This site is particularly suitable for calibration purposes because of its high spatial and spectral uniformity and reasonable temporal stability. This study uses measurements from four different sensors, Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+), Aqua MODIS, and Landsat 5 (L5) Thematic Mapper (TM), to assess the suitability of this site for long-term stability monitoring and to evaluate the “radiometric calibration differences” between spectrally matching bands of all four sensors. In general, the drift in the top-of-atmosphere (TOA) reflectance of each sensor over a span of nine years is within the specified calibration uncertainties. Monthly precipitation measurements of the Sonoran Desert region were obtained from the Global Historical Climatology Network (GHCN), and their effects on the retrieved TOA reflectances were evaluated. To account for the combined uncertainties in the TOA reflectance due to the surface and atmospheric Bi-directional Reflectance Distribution Function (BRDF), a semi-empirical BRDF model has been adopted to monitor and reduce the impact of illumination geometry differences on the retrieved TOA reflectances. To evaluate calibration differences between the MODIS and Landsat sensors, correction for spectral response differences using a hyperspectral sensor is also demonstrated.

Remote Sensing of Liquid Water and Ice Cloud Optical Thickness and Effective Radius in the Arctic: Application of Airborne Multispectral MAS Data

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Yang, Ping; Arnold, G. Thomas; Gray, Mark A.; Riedi, Jerome C.; Ackerman, Steven A.; Liou, Kuo-Nan

2003-01-01

A multispectral scanning spectrometer was used to obtain measurements of the reflection function and brightness temperature of clouds, sea ice, snow, and tundra surfaces at 50 discrete wavelengths between 0.47 and 14.0 microns. These observations were obtained from the NASA ER-2 aircraft as part of the FIRE Arctic Clouds Experiment, conducted over a 1600 x 500 km region of the north slope of Alaska and surrounding Beaufort and Chukchi Seas between 18 May and 6 June 1998. Multispectral images of the reflection function and brightness temperature in 11 distinct bands of the MODIS Airborne Simulator (MAS) were used to derive a confidence in clear sky (or alternatively the probability of cloud), shadow, and heavy aerosol over five different ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (water, ice, or undetermined phase). Finally, the cloud optical thickness and effective radius were derived for both water and ice clouds that were detected during one flight line on 4 June. This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS data in Alaska, is quite capable of distinguishing clouds from bright sea ice surfaces during daytime conditions in the high Arctic. Results of individual tests, however, make it difficult to distinguish ice clouds over snow and sea ice surfaces, so additional tests were added to enhance the confidence in the thermodynamic phase of clouds over the Beaufort Sea. The cloud optical thickness and effective radius retrievals used 3 distinct bands of the MAS, with the newly developed 1.62 and 2.13 micron bands being used quite successfully over snow and sea ice surfaces. These results are contrasted with a MODIS-based algorithm that relies on spectral reflectance at 0.87 and 2.13 micron.

Vegetation Continuous Fields--Transitioning from MODIS to VIIRS

NASA Astrophysics Data System (ADS)

DiMiceli, C.; Townshend, J. R.; Sohlberg, R. A.; Kim, D. H.; Kelly, M.

2015-12-01

Measurements of fractional vegetation cover are critical for accurate and consistent monitoring of global deforestation rates. They also provide important parameters for land surface, climate and carbon models and vital background data for research into fire, hydrological and ecosystem processes. MODIS Vegetation Continuous Fields (VCF) products provide four complementary layers of fractional cover: tree cover, non-tree vegetation, bare ground, and surface water. MODIS VCF products are currently produced globally and annually at 250m resolution for 2000 to the present. Additionally, annual VCF products at 1/20° resolution derived from AVHRR and MODIS Long-Term Data Records are in development to provide Earth System Data Records of fractional vegetation cover for 1982 to the present. In order to provide continuity of these valuable products, we are extending the VCF algorithms to create Suomi NPP/VIIRS VCF products. This presentation will highlight the first VIIRS fractional cover product: global percent tree cover at 1 km resolution. To create this product, phenological and physiological metrics were derived from each complete year of VIIRS 8-day surface reflectance products. A supervised regression tree method was applied to the metrics, using training derived from Landsat data supplemented by high-resolution data from Ikonos, RapidEye and QuickBird. The regression tree model was then applied globally to produce fractional tree cover. In our presentation we will detail our methods for creating the VIIRS VCF product. We will compare the new VIIRS VCF product to our current MODIS VCF products and demonstrate continuity between instruments. Finally, we will outline future VIIRS VCF development plans.

Radiometric cross-calibration of EO-1 ALI with L7 ETM+ and Terra MODIS sensors using near-simultaneous desert observations

USGS Publications Warehouse

Chander, Gyanesh; Angal, Amit; Choi, Taeyoung; Xiong, Xiaoxiong

2013-01-01

The Earth Observing-1 (EO-1) satellite was launched on November 21, 2000, as part of a one-year technology demonstration mission. The mission was extended because of the value it continued to add to the scientific community. EO-1 has now been operational for more than a decade, providing both multispectral and hyperspectral measurements. As part of the EO-1 mission, the Advanced Land Imager (ALI) sensor demonstrates a potential technological direction for the next generation of Landsat sensors. To evaluate the ALI sensor capabilities as a precursor to the Operational Land Imager (OLI) onboard the Landsat Data Continuity Mission (LDCM, or Landsat 8 after launch), its measured top-of-atmosphere (TOA) reflectances were compared to the well-calibrated Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors in the reflective solar bands (RSB). These three satellites operate in a near-polar, sun-synchronous orbit 705 km above the Earth's surface. EO-1 was designed to fly one minute behind L7 and approximately 30 minutes in front of Terra. In this configuration, all the three sensors can view near-identical ground targets with similar atmospheric, solar, and viewing conditions. However, because of the differences in the relative spectral response (RSR), the measured physical quantities can be significantly different while observing the same target. The cross-calibration of ALI with ETM+ and MODIS was performed using near-simultaneous surface observations based on image statistics from areas observed by these sensors over four desert sites (Libya 4, Mauritania 2, Arabia 1, and Sudan 1). The differences in the measured TOA reflectances due to RSR mismatches were compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of each sensor. For this study, the spectral profile of the target comes from the near-simultaneous EO-1 Hyperion data over these sites. The results indicate that the TOA reflectance measurements for ALI agree with those of ETM+ and MODIS to within 5% after the application of SBAF.

Cross-calibration of MODIS with ETM+ and ALI sensors for long-term monitoring of land surface processes

USGS Publications Warehouse

Meyer, D.; Chander, G.

2006-01-01

Increasingly, data from multiple sensors are used to gain a more complete understanding of land surface processes at a variety of scales. Although higher-level products (e.g., vegetation cover, albedo, surface temperature) derived from different sensors can be validated independently, the degree to which these sensors and their products can be compared to one another is vastly improved if their relative spectroradiometric responses are known. Most often, sensors are directly calibrated to diffuse solar irradiation or vicariously to ground targets. However, space-based targets are not traceable to metrological standards, and vicarious calibrations are expensive and provide a poor sampling of a sensor's full dynamic range. Crosscalibration of two sensors can augment these methods if certain conditions can be met: (1) the spectral responses are similar, (2) the observations are reasonably concurrent (similar atmospheric & solar illumination conditions), (3) errors due to misregistrations of inhomogeneous surfaces can be minimized (including scale differences), and (4) the viewing geometry is similar (or, some reasonable knowledge of surface bi-directional reflectance distribution functions is available). This study explores the impacts of cross-calibrating sensors when such conditions are met to some degree but not perfectly. In order to constrain the range of conditions at some level, the analysis is limited to sensors where cross-calibration studies have been conducted (Enhanced Thematic Mapper Plus (ETM+) on Landsat-7 (L7), Advance Land Imager (ALI) and Hyperion on Earth Observer-1 (EO-1)) and including systems having somewhat dissimilar geometry, spatial resolution & spectral response characteristics but are still part of the so-called "A.M. constellation" (Moderate Resolution Imaging Spectrometer (MODIS) aboard the Terra platform). Measures for spectral response differences and methods for cross calibrating such sensors are provided in this study. These instruments are cross calibrated using the Railroad Valley playa in Nevada. Best fit linear coefficients (slope and offset) are provided for ALI-to-MODIS and ETM+-to-MODIS cross calibrations, and root-mean-squared errors (RMSEs) and correlation coefficients are provided to quantify the uncertainty in these relationships. In theory, the linear fits and uncertainties can be used to compare radiance and reflectance products derived from each instrument.

Extending the Deep Blue aerosol record from SeaWiFS and MODIS to NPP-VIIRS

NASA Technical Reports Server (NTRS)

Sayer, Andrew M.; Hsu, Nai-Yung Christina; Bettenhausen, Corey; Lee, Jaehwa

2015-01-01

Deep Blue expands AOD coverage to deserts and other bright surfaces. Using multiple similar satellite sensors enables us to obtain a long data record. The Deep Blue family consists of three separate aerosol optical depth (AOD) retrieval algorithms: 1. Bright Land: Surface reflectance database, BRDF correction. AOD retrieved separately at each of 412, 470/490, (650) nm. SSA retrieved for heavy dust events. 2. Dark Land: Spectral/directional surface reflectance relationship. AOD retrieved separately at 470/490 and 650 nm. 3. Water: Surface BRDF including glint, foam, underlight. Multispectral inversion (Not present in MODISdataset) All report the AOD at 550 nm, and Ångström exponent (AE).

A merged surface reflectance product from the Landsat and Sentinel-2 Missions

NASA Astrophysics Data System (ADS)

Vermote, E.; Claverie, M.; Masek, J. G.; Becker-Reshef, I.; Justice, C. O.

2013-12-01

This project is aimed at producing a merged surface product from the Landsat and Sentinel-2 missions to ultimately achieve high temporal coverage (~2 days repeat cycle) at high spatial resolution (20-60m). The goal is to achieve a seamless/consistent stream of surface reflectance data from the different sensors. The first part of this presentation discusses the basic requirements of such a product and the necessary processing steps: mainly calibration, atmospheric corrections, BRDF effect corrections, spectral band pass adjustments and gridding. We demonstrate the performance of those different corrections by using MODIS and VIIRS (Climate Modeling Grid at 0.05deg) data globally as well as Formosat-2 (8m spatial resolution) data (one crop site in South of France where 105 scenes were acquired during 2006-2010). The consistency of the surface reflectance product from MODIS and Formosat-2 ranges from 6 to 8% relative depending on the spectral bands (Green to NIR) with a bias between 2% (NIR) to 5% (green), which is acceptable given the cumulated limitation in cross-calibration, atmospheric correction and BRDF correction. The second part is devoted to the simulation of the merged Landsat and Sentinel-2 mission by using Landsat-7, LDCM (early) and SPOT-4 Take 5 dataset. SPOT-4 Take 5 dataset is a collection of 42 sites distributed globally and systematically acquired by SPOT-4 HRV every 5 days during the decommissioning phase of the SPOT4 mission (February-May 2013). Finally, the benefits of such a merged surface reflectance at high spatial and temporal resolution are discussed within the context of the agricultural monitoring, in particular in the perspective of the GEOGLAM (Global Earth Observation for Global Land Agriculture Monitoring) project.

Validation of the MODIS "Clear-Sky" Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Koenig, L. S.; DiGirolamo, N. E.; Comiso, J.; Shuman, C. A.

2011-01-01

Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and Aqua satellites. We use the MODIS ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and Aqua IST maps; 2) comparisons between ISTs and in-situ measurements; 3) comparisons between ISTs and AWS data; and 4) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer. In this work, we focus on 1) and 2) above. Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and Aqua satellites. We use the MODIS ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and Aqua IST maps; 2) comparisons between ISTs and in-situ measurements; 3) comparisons between ISTs and AWS data; and 4) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer. In this work, we focus on 1) and 2) above. First we provide comparisons between Terra and Aqua swath-based ISTs at approximately 14:00 Local Solar Time, reprojected to 12.5 km polar stereographic cells. Results show good correspondence when Terra and Aqua data were acquired within 2 hrs of each other. For example, for a cell centered over Summit Camp (72.58 N, 38.5 W), the average agreement between Terra and Aqua ISTs is 0.74 K (February 2003), 0.47 K (April 2003), 0.7 K (August 2003) and 0.96 K (October 2003) with the Terra ISTs being generally lower than the Aqua ISTs. More precise comparisons will be calculated using pixel data at the swath level, and correspondence between Terra and Aqua IST is expected to be closer. (Because of cloud cover and other considerations, only a few common cloud-free swaths are typically available for each month for comparison.) Additionally, previous work comparing land-surface temperatures (LSTs) from the standard MODIS LST product and in-situ surface-temperature data at Summit Camp on the Greenland Ice Sheet show that Terra MODIS LSTs are about 3 K lower than in-situ temperatures at Summit Camp, during the winter of 2008-09. This work will be repeated using both Terra and Aqua IST pixel data (in place of LST data). In conclusion, we demonstrate that the uncertainties in the CDR will be well characterized as we work through the various facets of its validation.

Validation and application of MODIS-derived clean snow albedo and dust radiative forcing

NASA Astrophysics Data System (ADS)

Rittger, K. E.; Bryant, A. C.; Seidel, F. C.; Bair, E. H.; Skiles, M.; Goodale, C. E.; Ramirez, P.; Mattmann, C. A.; Dozier, J.; Painter, T.

2012-12-01

Snow albedo is an important control on snowmelt. Though albedo evolution of aging snow can be roughly modeled from grain growth, dust and other light absorbing impurities are extrinsic and therefore must be measured. Estimates of clean snow albedo and surface radiative forcing from impurities, which can be inferred from MODIS 500 m surface reflectance products, can provide this driving data for snowmelt models. Here we use MODSCAG (MODIS snow covered area and grain size) to estimate the clean snow albedo and MODDRFS (MODIS dust radiative forcing of snow) to estimate the additional absorbed solar radiation from dust and black carbon. With its finer spatial (20 m) and spectral (10 nm) resolutions, AVIRIS provides a way to estimate the accuracy of MODIS products and understand variability of snow albedo at a finer scale that we explore though a range of topography. The AVIRIS database includes images from late in the accumulation season through the melt season when we are most interested in changes in snow albedo. In addition to the spatial validation, we employ the best estimate of albedo from MODIS in an energy balance reconstruction model to estimate the maximum snow water equivalent. MODDRFS calculates radiative forcing only in pixels that are completely snow-covered, so we spatially interpolate the product to estimate the forcing in all pixels where MODSCAG has given us estimates of clean snow albedo. Comparisons with snow pillows and courses show better agreement when the radiative forcing from absorbing impurities is included in the energy balance reconstruction.

Evaluation of Operational Albedo Algorithms For AVHRR, MODIS and VIIRS: Case Studies in Southern Africa

NASA Astrophysics Data System (ADS)

Privette, J. L.; Schaaf, C. B.; Saleous, N.; Liang, S.

2004-12-01

Shortwave broadband albedo is the fundamental surface variable that partitions solar irradiance into energy available to the land biophysical system and energy reflected back into the atmosphere. Albedo varies with land cover, vegetation phenological stage, surface wetness, solar angle, and atmospheric condition, among other variables. For these reasons, a consistent and normalized albedo time series is needed to accurately model weather, climate and ecological trends. Although an empirically-derived coarse-scale albedo from the 20-year NOAA AVHRR record (Sellers et al., 1996) is available, an operational moderate resolution global product first became available from NASA's MODIS sensor. The validated MODIS product now provides the benchmark upon which to compare albedo generated through 1) reprocessing of the historic AVHRR record and 2) operational processing of data from the future National Polar-Orbiting Environmental Satellite System's (NPOESS) Visible/Infrared Imager Radiometer Suite (VIIRS). Unfortunately, different instrument characteristics (e.g., spectral bands, spatial resolution), processing approaches (e.g., latency requirements, ancillary data availability) and even product definitions (black sky albedo, white sky albedo, actual or blue sky albedo) complicate the development of the desired multi-mission (AVHRR to MODIS to VIIRS) albedo time series -- a so-called Climate Data Record. This presentation will describe the different albedo algorithms used with AVHRR, MODIS and VIIRS, and compare their results against field measurements collected over two semi-arid sites in southern Africa. We also describe the MODIS-derived VIIRS proxy data we developed to predict NPOESS albedo characteristics. We conclude with a strategy to develop a seamless Climate Data Record from 1982- to 2020.

BRDF Characterization and Calibration Inter-Comparison between Terra MODIS, Aqua MODIS, and S-NPP VIIRS

NASA Technical Reports Server (NTRS)

Chang, Tiejun; Xiong, Xiaoxiong (Jack); Angal, Amit; Wu, Aisheng

2016-01-01

The inter-comparison of reflective solar bands (RSB) between Terra MODIS, Aqua MODIS, and SNPP VIIRS is very important for assessment of each instrument's calibration and to identify calibration improvements. One of the limitations of using their ground observations for the assessment is a lack of the simultaneous nadir overpasses (SNOs) over selected pseudo-invariant targets. In addition, their measurements over a selected Earth view target have significant difference in solar and view angles, and these differences magnify the effects of Bidirectional Reflectance Distribution Function (BRDF). In this work, an inter-comparison technique using a semi-empirical BRDF model is developed for reflectance correction. BRDF characterization requires a broad coverage of solar and view angles in the measurements over selected pseudo-invariant targets. Reflectance measurements over Libya 1, 2, and 4 desert sites from both the Aqua and Terra MODIS are regressed to a BRDF model with an adjustable coefficient accounting for the calibration difference between the two instruments. The BRDF coefficients for three desert sites for MODIS bands 1 to 9 are derived and the wavelength dependencies are presented. The analysis and inter-comparison are for MODIS bands 1 to 9 and VIIRS moderate resolution radiometric bands (M bands) M1, M2, M4, M5, M7, M8, M10 and imaging bands (I bands) I1-I3. Results show that the ratios from different sites are in good agreement. The ratios between Terra and Aqua MODIS from year 2003 to 2014 are presented. The inter-comparison between MODIS and VIIRS are analyzed for year 2014.

Validation of a Climate-Data Record of the "Clear-Sky" Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Box, Jason E.; Koenig, Lora S.; DiGirolamo, Nicolo E.; Comiso, Josefino C.; Shuman, Christopher A.

2011-01-01

Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented since 1981. We extended and refined this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. We developed a daily and monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using an ice-surface temperature (1ST) algorithm developed for use with MODIS data. Validation of this CDR is ongoing. MODIS Terra swath data are projected onto a polar stereographic grid at 6.25-km resolution to develop binary, gridded daily and mean-monthly 1ST maps. Each monthly map also has a color-coded image map that is available to download. Also included with the monthly maps is an accompanying map showing number of days in the month that were used to calculate the mean-monthly 1ST. This is important because no 1ST decision is made by the algorithm for cells that are considered cloudy by the internal cloud mask, so a sufficient number of days must be available to produce a mean 1ST for each grid cell. Validation of the CDR consists of several facets: 1) comparisons between ISTs and in-situ measurements; 2) comparisons between ISTs and AWS data; and 3) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer (ASTER) and Enhanced Thematic Mapper Plus (ETM+). Previous work shows that Terra MODIS ISTs are about 3 C lower than in-situ temperatures measured at Summit Camp, during the winter of 2008-09 under clear skies. In this work we begin to compare surface temperatures derived from AWS data with ISTs from the MODIS CDR.

An efficient approach for pixel decomposition to increase the spatial resolution of land surface temperature images from MODIS thermal infrared band data.

PubMed

Wang, Fei; Qin, Zhihao; Li, Wenjuan; Song, Caiying; Karnieli, Arnon; Zhao, Shuhe

2014-12-25

Land surface temperature (LST) images retrieved from the thermal infrared (TIR) band data of Moderate Resolution Imaging Spectroradiometer (MODIS) have much lower spatial resolution than the MODIS visible and near-infrared (VNIR) band data. The coarse pixel scale of MODIS LST images (1000 m under nadir) have limited their capability in applying to many studies required high spatial resolution in comparison of the MODIS VNIR band data with pixel scale of 250-500 m. In this paper we intend to develop an efficient approach for pixel decomposition to increase the spatial resolution of MODIS LST image using the VNIR band data as assistance. The unique feature of this approach is to maintain the thermal radiance of parent pixels in the MODIS LST image unchanged after they are decomposed into the sub-pixels in the resulted image. There are two important steps in the decomposition: initial temperature estimation and final temperature determination. Therefore the approach can be termed double-step pixel decomposition (DSPD). Both steps involve a series of procedures to achieve the final result of decomposed LST image, including classification of the surface patterns, establishment of LST change with normalized difference of vegetation index (NDVI) and building index (NDBI), reversion of LST into thermal radiance through Planck equation, and computation of weights for the sub-pixels of the resulted image. Since the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with much higher spatial resolution than MODIS data was on-board the same platform (Terra) as MODIS for Earth observation, an experiment had been done in the study to validate the accuracy and efficiency of our approach for pixel decomposition. The ASTER LST image was used as the reference to compare with the decomposed LST image. The result showed that the spatial distribution of the decomposed LST image was very similar to that of the ASTER LST image with a root mean square error (RMSE) of 2.7 K for entire image. Comparison with the evaluation DisTrad (E-DisTrad) and re-sampling methods for pixel decomposition also indicate that our DSPD has the lowest RMSE in all cases, including urban region, water bodies, and natural terrain. The obvious increase in spatial resolution remarkably uplifts the capability of the coarse MODIS LST images in highlighting the details of LST variation. Therefore it can be concluded that, in spite of complicated procedures, the proposed DSPD approach provides an alternative to improve the spatial resolution of MODIS LST image hence expand its applicability to the real world.

Comparability of Red/Near-Infrared Reflectance and NDVI Based on the Spectral Response Function between MODIS and 30 Other Satellite Sensors Using Rice Canopy Spectra

PubMed Central

Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing

2013-01-01

Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The reflectance and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR reflectances and NDVI derived from 31 Earth observation satellite sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy reflectances were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific reflectances in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR reflectances. The results showed that as compared to the Terra MODIS, the mean relative percentage difference (RPD) ranged from −12.67% to 36.30% for the red reflectance, −8.52% to −0.23% for the NIR reflectance, and −9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra MODIS ranged from 1.28% to 36.30% for the red reflectance, 0.84% to 8.71% for the NIR reflectance, and 0.59% to 9.32% for the NDVI. The lowest APD between MODIS and the other 30 satellite sensors was observed for Landsat5 TM for the red reflectance, CBERS02B CCD for the NIR reflectance and Landsat4 TM for the NDVI. In addition, the largest APD between MODIS and the other 30 satellite sensors was observed for IKONOS for the red reflectance, AVHRR1 onboard NOAA8 for the NIR reflectance and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed higher differences than did the other sensors with respect to MODIS. A series of optimum models were presented for remote sensing data assimilation between MODIS and other sensors. PMID:24287529

Comparability of red/near-infrared reflectance and NDVI based on the spectral response function between MODIS and 30 other satellite sensors using rice canopy spectra.

PubMed

Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing

2013-11-26

Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The reflectance and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR reflectances and NDVI derived from 31 Earth observation satellite sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy reflectances were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific reflectances in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR reflectances. The results showed that as compared to the Terra MODIS, the mean relative percentage difference (RPD) ranged from -12.67% to 36.30% for the red reflectance, -8.52% to -0.23% for the NIR reflectance, and -9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra MODIS ranged from 1.28% to 36.30% for the red reflectance, 0.84% to 8.71% for the NIR reflectance, and 0.59% to 9.32% for the NDVI. The lowest APD between MODIS and the other 30 satellite sensors was observed for Landsat5 TM for the red reflectance, CBERS02B CCD for the NIR reflectance and Landsat4 TM for the NDVI. In addition, the largest APD between MODIS and the other 30 satellite sensors was observed for IKONOS for the red reflectance, AVHRR1 onboard NOAA8 for the NIR reflectance and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed higher differences than did the other sensors with respect to MODIS. A series of optimum models were presented for remote sensing data assimilation between MODIS and other sensors.

Land surface temperature measurements from EOS MODIS data

NASA Technical Reports Server (NTRS)

Wan, Zhengming

1995-01-01

A significant progress has been made in TIR instrumentation which is required to establish the spectral BRDF/emissivity knowledge base of land-surface materials and to validate the land-surface temperature (LST) algorithms. The SIBRE (spectral Infrared Bidirectional Reflectance and Emissivity) system and a TIR system for measuring spectral directional-hemispherical emissivity have been completed and tested successfully. Optical properties and performance features of key components (including spectrometer, and TIR source) of these systems have been characterized by integrated use of local standards (blackbody and reference plates). The stabilization of the spectrometer performance was improved by a custom designed and built liquid cooling system. Methods and procedures for measuring spectral TIR BRDF and directional-hemispheric emissivity with these two systems have been verified in sample measurements. These TIR instruments have been used in the laboratory and the field, giving very promising results. The measured spectral emissivities of water surface are very close to the calculated values based on well established water refractive index values in published papers. Preliminary results show that the TIR instruments can be used for validation of the MODIS LST algorithm in homogeneous test sites. The beta-3 version of the MODIS LST software is being prepared for its delivery scheduled in the early second half of this year.

Intercomparison of 30+ years of AVHRR and Landsat-5 TM Surface Reflectance using Multiple Pseudo-Invariant Calibration Sites

NASA Astrophysics Data System (ADS)

Santamaría-Artigas, A. E.; Franch, B.; Vermote, E.; Roger, J. C.; Justice, C. O.

2017-12-01

The 30+ years daily surface reflectance long term data record (LTDR) from the Advanced Very High Resolution Radiometer (AVHRR) is a valuable source of information for long-term studies of the Earth surface. This LTDR was generated by combining observations from multiple AVHRR sensors aboard different NOAA satellites starting from the early 1980s, and due to the lack of on-board calibration its quality should be evaluated. Previous studies have used observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) over pseudo-invariant calibration sites (PICS) as a calibrated reference to assess the performance of AVHRR products. However, this limits the evaluation to the period after MODIS launch. In this work, the AVHRR surface reflectance LTDR was evaluated against Landsat-5 Thematic Mapper (TM) data using observations from 4 well known pseudo-invariant calibration sites (i.e. Sonoran, Saharan, Sudan1, and Libya4) over an extended time period (1984-2011). For the intercomparison, AVHRR and TM observations of each site were extracted and averaged over a 20 km x 20 km area and aggregated to monthly mean values. In order to account for the spectral differences between sensors, Hyperion hyperspectral data from the Sonoran and Libya4 sites were convolved with sensor-specific relative spectral responses, and used to compute spectral band adjustment factors (SBAFs). Results of the intercomparison are reported in terms of the root mean square difference (RMSD) and determination coefficient (r2). In general, there is good agreement between the surface reflectance products from both sensors. The overall RMSD and r2 for all the sites and AVHRR/TM combinations were 0.03 and 0.85 for the red band, and 0.04 and 0.81 for the near-infrared band. These results show the strong performance of the AVHRR surface reflectance LTDR through all of the considered period. Thus, remarking its usefulness and value for long term Earth studies. Figure 1 shows the red (filled markers) and near-infrared (empty markers) surface reflectance from AVHRR and TM for the complete evaluation period over the Saharan (diamond), Libya4 (square), Sudan1 (triangle), and Sonoran (circle) PICS.

Multi-sensor data processing method for improved satellite retrievals

NASA Astrophysics Data System (ADS)

Fan, Xingwang

2017-04-01

Satellite remote sensing has provided massive data that improve the overall accuracy and extend the time series of environmental studies. In reflective solar bands, satellite data are related to land surface properties via radiative transfer (RT) equations. These equations generally include sensor-related (calibration coefficients), atmosphere-related (aerosol optical thickness) and surface-related (surface reflectance) parameters. It is an ill-posed problem to solve three parameters with only one RT equation. Even if there are two RT equations (dual-sensor data), the problem is still unsolvable. However, a robust solution can be obtained when any two parameters are known. If surface and atmosphere are known, sensor intercalibration can be performed. For example, the Advanced Very High Resolution Radiometer (AVHRR) was calibrated to the MODerate-resolution Imaging Spectroradiometer (MODIS) in Fan and Liu (2014) [Fan, X., and Liu, Y. (2014). Quantifying the relationship between intersensor images in solar reflective bands: Implications for intercalibration. IEEE Transactions on Geoscience and Remote Sensing, 52(12), 7727-7737.]. If sensor and surface are known, atmospheric data can be retrieved. For example, aerosol data were retrieved using tandem TERRA and AQUA MODIS images in Fan and Liu (2016a) [Fan, X., and Liu, Y. (2016a). Exploiting TERRA-AQUA MODIS relationship in the reflective solar bands for aerosol retrieval. Remote Sensing, 8(12), 996.]. If sensor and atmosphere are known, data consistency can be obtained. For example, Normalized Difference Vegetation Index (NDVI) data were intercalibrated among coarse-resolution sensors in Fan and Liu (2016b) [Fan, X., and Liu, Y. (2016b). A global study of NDVI difference among moderate-resolution satellite sensors. ISPRS Journal of Photogrammetry and Remote Sensing, 121, 177-191.], and among fine-resolution sensors in Fan and Liu (2017) [Fan, X., and Liu, Y. (2017). A generalized model for intersensor NDVI calibration and its comparison with regression approaches. IEEE Transactions on Geoscience and Remote Sensing, 55(3), doi: 10.1109/TGRS.2016.2635802.]. These studies demonstrate the success of multi-sensor data and novel methods in the research domain of geoscience. These data will benefit remote sensing of terrestrial parameters in decadal timescales, such as soil salinity content in Fan et al. (2016) [Fan, X., Weng, Y., and Tao, J. (2016). Towards decadal soil salinity mapping using Landsat time series data. International Journal of Applied Earth Observation and Geoinformation, 52, 32-41.].

Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

PubMed

Wang, Jiao; Deng, Zhiqiang

2017-06-01

A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

On-Orbit Noise Characterization for MODIS Reflective Solar Bands

NASA Technical Reports Server (NTRS)

Xiong, X.; Xie, X.; Angal, A.

2008-01-01

Since launch, the Moderate Resolution Imaging Spectroradiometer (MODIS) has operated successfully on-board the NASA Earth Observing System (EOS) Terra and EOS Aqua spacecraft. MODIS is a passive cross-track scanning radiometer that makes observations in 36 spectral bands with spectral wavelengths from visible (VIS) to long-wave infrared. MODIS bands 1-19 and 26 are the reflective solar bands (RSB) with wavelengths from 0.41 to 2.2 micrometers. They are calibrated on-orbit using an on-board solar diffuser (SD) and a SD stability monitor (SDSM) system. For MODIS RSB, the level 1B calibration algorithm produces top of the atmosphere reflectance factors and radiances for every pixel of the Earth view. The sensor radiometric calibration accuracy, specified at each spectral band's typical scene radiance, is 2% for the RSB reflectance factors and 5% for the RSB radiances. Also specified at the typical scene radiance is the detector signal-to-noise ratio (SNR), a key sensor performance parameter that directly impacts its radiometric calibration accuracy and stability, as well as the image quality. This paper describes an on-orbit SNR characterization approach developed to evaluate and track MODIS RSB detector performance. In order to perform on-orbit SNR characterization, MODIS RSB detector responses to the solar illumination reflected from the SD panel must be corrected for factors due to variations of the solar angles and the SD bi-directional reflectance factor. This approach enables RSB SNR characterization to be performed at different response levels for each detector. On-orbit results show that both Terra and Aqua MODIS RSB detectors have performed well since launch. Except for a few noisy or inoperable detectors which were identified pre-launch, most RSB detectors continue to meet the SNR design requirements and are able to maintain satisfactory short-term stability. A comparison of on-orbit noise characterization results with results derived from pre-launch calibration and characterization are also provided.

The Retrieval of Aerosol Optical Thickness Using the MERIS Instrument

NASA Astrophysics Data System (ADS)

Mei, L.; Rozanov, V. V.; Vountas, M.; Burrows, J. P.; Levy, R. C.; Lotz, W.

2015-12-01

Retrieval of aerosol properties for satellite instruments without shortwave-IR spectral information, multi-viewing, polarization and/or high-temporal observation ability is a challenging problem for spaceborne aerosol remote sensing. However, space based instruments like the MEdium Resolution Imaging Spectrometer (MERIS) and the successor, Ocean and Land Colour Instrument (OLCI) with high calibration accuracy and high spatial resolution provide unique abilities for obtaining valuable aerosol information for a better understanding of the impact of aerosols on climate, which is still one of the largest uncertainties of global climate change evaluation. In this study, a new Aerosol Optical Thickness (AOT) retrieval algorithm (XBAER: eXtensible Bremen AErosol Retrieval) is presented. XBAER utilizes the global surface spectral library database for the determination of surface properties while the MODIS collection 6 aerosol type treatment is adapted for the aerosol type selection. In order to take the surface Bidirectional Reflectance Distribution Function (BRDF) effect into account for the MERIS reduce resolution (1km) retrieval, a modified Ross-Li mode is used. The AOT is determined in the algorithm using lookup tables including polarization created using Radiative Transfer Model SCIATRAN3.4, by minimizing the difference between atmospheric corrected surface reflectance with given AOT and the surface reflectance calculated from the spectral library. The global comparison with operational MODIS C6 product, Multi-angle Imaging SpectroRadiometer (MISR) product, Advanced Along-Track Scanning Radiometer (AATSR) aerosol product and the validation using AErosol RObotic NETwork (AERONET) show promising results. The current XBAER algorithm is only valid for aerosol remote sensing over land and a similar method will be extended to ocean later.

Characterizing Response Versus Scan-Angle for MODIS Reflective Solar Bands Using Deep Convective Clouds

NASA Technical Reports Server (NTRS)

Bhatt, Rajendra; Doelling, David R.; Angal, Amit; Xiong, Xiaoxiong; Scarino, Benjamin; Gopalan, Arun; Haney, Conor; Wu, Aisheng

2017-01-01

MODIS consists of a cross-track, two-sided scan mirror, whose reflectance is not uniform but is a function of angle of incidence (AOI). This feature, known as response versusscan-angle (RVS), was characterized for all reflective solar bands of both MODIS instruments prior to launch. The RVS characteristic has changed on orbit, which must be tracked precisely over time to ensure the quality of MODIS products. The MODIS characterization support team utilizes the onboard calibrators and the earth view responses from multiple pseudo invariant desert sites to track the RVS changes at different AOIs. The drawback of using deserts is the assumption that these sites are radiometrically stable during the monitoring period. In addition, the 16-day orbit repeat cycle of MODIS allows for only a limited set of AOIs over a given desert. We propose a novel and robust approach of characterizing the MODIS RVS using tropical deep convective clouds (DCC). The method tracks the monthly DCC response at specified sets of AOIs to compute the temporal RVS changes. Initial results have shown that the Aqua-MODIS collection 6 band 1 level 1B radiances show considerable residual RVS dependencies, with long-term drifts up to 2.3 at certain AOIs.

Characterizing response versus scan-angle for MODIS reflective solar bands using deep convective clouds

NASA Astrophysics Data System (ADS)

Bhatt, Rajendra; Doelling, David R.; Angal, Amit; Xiong, Xiaoxiong; Scarino, Benjamin; Gopalan, Arun; Haney, Conor; Wu, Aisheng

2017-01-01

MODIS consists of a cross-track, two-sided scan mirror, whose reflectance is not uniform but is a function of angle of incidence (AOI). This feature, known as response versus scan-angle (RVS), was characterized for all reflective solar bands of both MODIS instruments prior to launch. The RVS characteristic has changed on orbit, which must be tracked precisely over time to ensure the quality of MODIS products. The MODIS characterization support team utilizes the onboard calibrators and the earth view responses from multiple pseudoinvariant desert sites to track the RVS changes at different AOIs. The drawback of using deserts is the assumption that these sites are radiometrically stable during the monitoring period. In addition, the 16-day orbit repeat cycle of MODIS allows for only a limited set of AOIs over a given desert. We propose a novel and robust approach of characterizing the MODIS RVS using tropical deep convective clouds (DCC). The method tracks the monthly DCC response at specified sets of AOIs to compute the temporal RVS changes. Initial results have shown that the Aqua-MODIS collection 6 band 1 level 1B radiances show considerable residual RVS dependencies, with long-term drifts up to 2.3% at certain AOIs.

Development of a MODIS-Derived Surface Albedo Data Set: An Improved Model Input for Processing the NSRDB

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maclaurin, Galen; Sengupta, Manajit; Xie, Yu

A significant source of bias in the transposition of global horizontal irradiance to plane-of-array (POA) irradiance arises from inaccurate estimations of surface albedo. The current physics-based model used to produce the National Solar Radiation Database (NSRDB) relies on model estimations of surface albedo from a reanalysis climatalogy produced at relatively coarse spatial resolution compared to that of the NSRDB. As an input to spectral decomposition and transposition models, more accurate surface albedo data from remotely sensed imagery at finer spatial resolutions would improve accuracy in the final product. The National Renewable Energy Laboratory (NREL) developed an improved white-sky (bi-hemispherical reflectance)more » broadband (0.3-5.0 ..mu..m) surface albedo data set for processing the NSRDB from two existing data sets: a gap-filled albedo product and a daily snow cover product. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellites have provided high-quality measurements of surface albedo at 30 arc-second spatial resolution and 8-day temporal resolution since 2001. The high spatial and temporal resolutions and the temporal coverage of the MODIS sensor will allow for improved modeling of POA irradiance in the NSRDB. However, cloud and snow cover interfere with MODIS observations of ground surface albedo, and thus they require post-processing. The MODIS production team applied a gap-filling methodology to interpolate observations obscured by clouds or ephemeral snow. This approach filled pixels with ephemeral snow cover because the 8-day temporal resolution is too coarse to accurately capture the variability of snow cover and its impact on albedo estimates. However, for this project, accurate representation of daily snow cover change is important in producing the NSRDB. Therefore, NREL also used the Integrated Multisensor Snow and Ice Mapping System data set, which provides daily snow cover observations of the Northern Hemisphere for the temporal extent of the NSRDB (1998-2015). We provide a review of validation studies conducted on these two products and describe the methodology developed by NREL to remap the data products to the NSRDB grid and integrate them into a seamless daily data set.« less

Alternative Method of On-Orbit Response-Versus-Scan-Angle Characterization for MODIS Reflective Solar Bands

NASA Technical Reports Server (NTRS)

Chen, Hongda; Xiong, Xiaoxiong; Angal, Amit; Geng, Xu; Wu, Aisheng

2016-01-01

The moderate resolution imaging spectroradiometer (MODIS) has 20 reflective solar bands (RSB), covering a spectral range from 0.41 to 2.2 microns, which are calibrated on-orbit using its onboard calibrators, which include a solar diffuser, a solar diffuser stability monitor, and a spectroradiometric calibration assembly. A space view (SV) port is used to provide a background reference and also facilitates near-monthly lunar observations through a spacecraft roll. In every scan, the Earth's surface, SV, and onboard calibrators are viewed via a two-sided scan mirror, the reflectance of which depends on the angle of incidence (AOI) as well as the wavelength of the incident light. Response-versus-scan-angle (RVS) is defined as a dependence function of the scan mirror's reflectance over AOI. An initial RVS for each RSB was measured prelaunch for both Terra and Aqua MODIS. Algorithms have been developed to track the on-orbit RVS variation using the measurements from the onboard calibrators, supplemented with the earth view (EV) trends from pseudoinvariant desert targets obtained at different AOI. Since the mission beginning, the MODIS characterization support team (MCST) has dedicated efforts in evaluating approaches of characterizing the on-orbit RVS. A majority of the approaches focused on fitting the data at each AOI over time and then deriving the relative change at different AOI. The current version of the on-orbit RVS algorithm, as implemented in the collection 6 (C6) level-1B (L1B), is also based on the above rationale. It utilizes the EV response trends from the pseudoinvariant Libyan desert targets to supplement the gain derived from the onboard calibrators. The primary limitation of this approach is the assumption of the temporal stability of these desert sites. Consequently, MCST developed an approach that derives the on-orbit RVS change using measurements from a single desert site, combined with the on-orbit lunar measurements. In addition, the EV and onboard responses are fit first as a function of AOI before fitting temporally in order to eliminate the dependence on the stability of the desert site. Comprehensive comparisons are performed with current C6 RVS results for both Terra and Aqua MODIS. Results demonstrate that this alternative method provides a supplemental means to monitor the on-orbit RVS for MODIS RSB.

Alternative method of on-orbit response-versus-scan-angle characterization for MODIS reflective solar bands

NASA Astrophysics Data System (ADS)

Chen, Hongda; Xiong, Xiaoxiong; Angal, Amit; Geng, Xu; Wu, Aisheng

2016-04-01

The moderate resolution imaging spectroradiometer (MODIS) has 20 reflective solar bands (RSB), covering a spectral range from 0.41 to 2.2 μm, which are calibrated on-orbit using its onboard calibrators, which include a solar diffuser, a solar diffuser stability monitor, and a spectroradiometric calibration assembly. A space view (SV) port is used to provide a background reference and also facilitates near-monthly lunar observations through a spacecraft roll. In every scan, the Earth's surface, SV, and onboard calibrators are viewed via a two-sided scan mirror, the reflectance of which depends on the angle of incidence (AOI) as well as the wavelength of the incident light. Response-versus-scan-angle (RVS) is defined as a dependence function of the scan mirror's reflectance over AOI. An initial RVS for each RSB was measured prelaunch for both Terra and Aqua MODIS. Algorithms have been developed to track the on-orbit RVS variation using the measurements from the onboard calibrators, supplemented with the earth view (EV) trends from pseudoinvariant desert targets obtained at different AOI. Since the mission beginning, the MODIS characterization support team (MCST) has dedicated efforts in evaluating approaches of characterizing the on-orbit RVS. A majority of the approaches focused on fitting the data at each AOI over time and then deriving the relative change at different AOI. The current version of the on-orbit RVS algorithm, as implemented in the collection 6 (C6) level-1B (L1B), is also based on the above rationale. It utilizes the EV response trends from the pseudoinvariant Libyan desert targets to supplement the gain derived from the onboard calibrators. The primary limitation of this approach is the assumption of the temporal stability of these desert sites. Consequently, MCST developed an approach that derives the on-orbit RVS change using measurements from a single desert site, combined with the on-orbit lunar measurements. In addition, the EV and onboard responses are fit first as a function of AOI before fitting temporally in order to eliminate the dependence on the stability of the desert site. Comprehensive comparisons are performed with current C6 RVS results for both Terra and Aqua MODIS. Results demonstrate that this alternative method provides a supplemental means to monitor the on-orbit RVS for MODIS RSB.

Optimization of a Deep Convective Cloud Technique in Evaluating the Long-Term Radiometric Stability of MODIS Reflective Solar Bands

NASA Technical Reports Server (NTRS)

Mu, Qiaozhen; Wu, Aisheng; Xiong, Xiaoxiong; Doelling, David R.; Angal, Amit; Chang, Tiejun; Bhatt, Rajendra

2017-01-01

MODIS reflective solar bands are calibrated on-orbit using a solar diffuser and near-monthly lunar observations. To monitor the performance and effectiveness of the on-orbit calibrations, pseudo-invariant targets such as deep convective clouds (DCCs), Libya-4, and Dome-C are used to track the long-term stability of MODIS Level 1B product. However, the current MODIS operational DCC technique (DCCT) simply uses the criteria set for the 0.65- m band. We optimize several critical DCCT parameters including the 11- micrometer IR-band Brightness Temperature (BT11) threshold for DCC identification, DCC core size and uniformity to help locate DCCs at convection centers, data collection time interval, and probability distribution function (PDF) bin increment for each channel. The mode reflectances corresponding to the PDF peaks are utilized as the DCC reflectances. Results show that the BT11 threshold and time interval are most critical for the Short Wave Infrared (SWIR) bands. The Bidirectional Reflectance Distribution Function model is most effective in reducing the DCC anisotropy for the visible channels. The uniformity filters and PDF bin size have minimal impacts on the visible channels and a larger impact on the SWIR bands. The newly optimized DCCT will be used for future evaluation of MODIS on-orbit calibration by MODIS Characterization Support Team.

Compositing MODIS Terra and Aqua 250m daily surface reflectance data sets for vegetation monitoring

USDA-ARS?s Scientific Manuscript database

Remote sensing based vegetation Indices have been proven valuable in providing a spatially complete view of crop’s vegetation condition, which also manifests the impact of the disastrous events such as massive flood and drought. VegScape, a web GIS application for crop vegetation condition monitorin...

Simulating Carbon Flux Dynamics with the Product of PAR Absorbed by Chlorophyll (fAPARchl)

NASA Astrophysics Data System (ADS)

Yao, T.; Zhang, Q.

2016-12-01

A common way to estimate the gross primary production (GPP) is to use the fraction of photosynthetically radiation (PAR) absorbed by vegetation (FPAR). However, only the PAR absorbed by chlorophyll of the canopy, not the PAR absorbed by the foliage or by the entire canopy, is used for photosynthesis. MODIS fAPARchl product, which refers to the fraction of PAR absorbed by chlorophyll of the canopy, is derived from Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance by using an advanced leaf-canopy-soil-water-snow coupled radiative transfer model PROSAIL4. PROSAIL4 can retrieve surface water cover fraction, snow cover fraction, and physiologically active canopy chemistry components (chlorophyll concentration and water content), fraction of photosynthetically active radiation (PAR) absorbed by a canopy (fAPARcanopy), fraction of PAR absorbed by photosynthetic vegetation (PV) component (mainly chlorophyll) throughout the canopy (fAPARPV, i.e., fAPARchl) and fraction of PAR absorbed by non-photosynthetic vegetation (NPV) component of the canopy (fAPARNPV). We have successfully retrieved these vegetation parameters for selected areas with PROSAIL4 and the MODIS images, or simulated spectrally MODIS-like images. In this study, the product of PAR absorbed by chlorophyll (fAPARchl) has been used to simulate carbon flux over different kinds of vegetation types. The results show that MODIS fAPARchl product has the ability to better characterize phenology than current phenology model in the Community Land Model and it also will likely be able to increase the accuracy of carbon fluxes simulations.

Decision Support Tool Evaluation Report for Coral Reef Early Warning System (CREWS) Version 7.0

NASA Technical Reports Server (NTRS)

D'Sa, Eurico; Hall, Callie; Zanoni, Vicki; Holland, Donald; Blonski, Slawomir; Pagnutti, Mary; Spruce, Joseph P.

2004-01-01

The Coral Reef Early Warning System (CREWS) is operated by NOAA's Office of Oceanic and Atmospheric Research as part of its Coral Reef Watch program in response to the deteriorating global state of coral reef and related benthic ecosystems. In addition to sea surface temperatures (SSTs), the two most important parameters used by the CREWS network in generating coral reef bleaching alerts are 1) wind speed and direction and 2) photosynthetically available radiation (PAR). NASA remote sensing products that can enhance CREWS in these areas include SST and PAR products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and wind data from the Quick Scatterometer (QuikSCAT). CREWS researchers are also interested in chlorophyll, chromophoric dissolved organic matter (CDOM), and salinity. Chlorophyll and CDOM are directly available as NASA products, while rainfall (an available NASA product) can be used as a proxy for salinity. Other potential NASA inputs include surface reflectance products from MODIS, the Advanced Spaceborne Thermal Emission and Reflection Radiometer, and Landsat. This report also identifies NASA-supported ocean circulation models and products from future satellite missions that might enchance the CREWS DST.

MODIS Solar Diffuser On-orbit Performance

NASA Technical Reports Server (NTRS)

Xiong, Xiaoxiong; Chen, H.; Choi, T.; Sun, J.; Angal, A.

2008-01-01

MODIS is a key instrument for the NASA Earth Observing System (EOS), currently operated on both the Terra and Aqua missions. Each MODIS instrument has 20 reflective solar bands (RSBs) and 16 thermal emissive bands (TEBs). MODIS RSB on-orbit calibration is reflectance based using an on-board solar diffuser (SD). The SD bi-directional reflectance factors (BRFs) were characterized pre-launch using reference diffuser samples, which are traceable to NIST reflectance standards. The SD BRF on-orbit degradation (or change) is tracked by another onboard device, called the solar diffuser stability monitor (SDSM). The SDSM is operated during each scheduled SD calibration event, making alternate observations of direct sunlight and the diffusely reflected sunlight from the SD. The time series of the ratios of SDSM's SD view to its Sun view provide SD degradation information. This paper presents and compares the Terra and Aqua MODIS SD on-orbit performance. Results show that the SD on-orbit degradation depends on the amount of solar exposure of the SD plate. In addition, it is strongly wavelengthdependent, with a larger degradation rate at shorter wavelengths. For Terra MODIS, an SD door anomaly occurred in May 2003 that led to a decision to fix the door permanently at an "open" position. Since then, the SD degradation rate has significantly increased due to more frequent solar exposure. As expected, the SD on-orbit performance directly impacts the RSB calibration performance. The lessons learned from MODIS on-orbit calibration will provide useful insights into the development and operation of future SD calibration systems.

New capabilities for characterizing smoke and dust aerosol over land using MODIS

NASA Astrophysics Data System (ADS)

Levy, R. C.; Remer, L. A.

2006-12-01

Smoke and dust aerosol have different chemical, optical and physical properties and both types affect many processes within the climate system. As earth's surface and atmosphere are continuously altered by natural and anthropogenic processes, the emission and presumably the effects of these aerosols are also changing. Thus it is necessary to observe and characterize aerosols on a global and climatic scale. While MODIS has been reporting characteristics of smoke and dust aerosol over land and ocean since shortly after Terra launch, the uncertainties in the over-land retrieval have been larger than expected. To better characterize different aerosol types closer to their source regions with greater accuracy, we have developed a new operational algorithm for retrieving aerosol properties over dark land surfaces from MODIS-observed visible (VIS) and infrared (IR) reflectance. Like earlier versions, this algorithm estimates the total loading (aerosol optical depth-τ) and relative weighting of fine (non-dust) and coarse (dust) -dominated aerosol to the total τ (fine weighting-η) over dark land surfaces. However, the fundamental mathematics and major assumptions have been overhauled. The new algorithm performs simultaneous multi-channel inversion that includes information about coarse aerosol in the IR channels, while assuming a fine-tuned relationship between VIS and IR surface reflectances, that is itself a function of scattering angle and vegetation condition. Finally, the suite of expected aerosol optical models described by the lookup table have been revised to closer resemble the AERONET climatology, including for smoke and dust aerosol. Beginning in April 2006, this algorithm has been used for forward processing and backward re- processing of the entire MODIS dataset observed from both Terra and Aqua. "Collection 5" products were completed for Aqua reprocessing by July 2006 and should be complete for Terra by December 2006. In this study, we used the complete Aqua dataset (July 2002-Aug 2006) and two years of Terra (2005-Aug 2006) data to evaluate the products in regions known to be dominated by smoke and/or dust. We compared with sunphotometer data at selected AERONET sites and found improved τ retrievals,within prescribed accuracy.

Pre-Launch Algorithm and Data Format for the Level 1 Calibration Products for the EOS AM-1 Moderate Resolution Imaging Spectroradiometer (MODIS)

NASA Technical Reports Server (NTRS)

Guenther, Bruce W.; Godden, Gerald D.; Xiong, Xiao-Xiong; Knight, Edward J.; Qiu, Shi-Yue; Montgomery, Harry; Hopkins, M. M.; Khayat, Mohammad G.; Hao, Zhi-Dong; Smith, David E. (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) radiometric calibration product is described for the thermal emissive and the reflective solar bands. Specific sensor design characteristics are identified to assist in understanding how the calibration algorithm software product is designed. The reflected solar band software products of radiance and reflectance factor both are described. The product file format is summarized and the MODIS Characterization Support Team (MCST) Homepage location for the current file format is provided.

Spatially Complete Surface Albedo Data Sets: Value-Added Products Derived from Terra MODIS Land Products

NASA Technical Reports Server (NTRS)

Moody, Eric G.; King, Michael D.; Platnick, Steven; Schaaf, Crystal B.; Gao, Feng

2004-01-01

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent observations of diffuse bihemispherical (white-sky) and direct beam directional hemispherical (black-sky ) land surface albedo included in the MOD43B3 product from MODIS instruments aboard NASA's Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal characteristics. Cloud and seasonal snow cover, however, curtail retrievals to approximately half the global land surfaces on an annual equal-angle basis, precluding MOD43B3 albedo products from direct inclusion in some research projects and production environments.

A Technique for Remote Sensing of Suspended Sediments and Shallow Coastal Waters Using MODIS Visible and Near-IR Channels

NASA Technical Reports Server (NTRS)

Li, Rong-Rong; Kaufman, Yoram J.

2002-01-01

We have developed an algorithm to detect suspended sediments and shallow coastal waters using imaging data acquired with the Moderate Resolution Imaging SpectroRadiometer (MODIS). The MODIS instruments on board the NASA Terra and Aqua Spacecrafts are equipped with one set of narrow channels located in a wide 0.4 - 2.5 micron spectral range. These channels were designed primarily for remote sensing of the land surface and atmosphere. We have found that the set of land and cloud channels are also quite useful for remote sensing of the bright coastal waters. We have developed an empirical algorithm, which uses the narrow MODIS channels in this wide spectral range, for identifying areas with suspended sediments in turbid waters and shallow waters with bottom reflections. In our algorithm, we take advantage of the strong water absorption at wavelengths longer than 1 micron that does not allow illumination of sediments in the water or a shallow ocean floor. MODIS data acquired over the east coast of China, west coast of Africa, Arabian Sea, Mississippi Delta, and west coast of Florida are used in this study.

A Technique For Remote Sensing Of Suspended Sediments And Shallow Coastal Waters Using MODIS Visible and Near-IR Channels

NASA Astrophysics Data System (ADS)

Li, R.; Kaufman, Y.

2002-12-01

ABSTRACT We have developed an algorithm to detect suspended sediments and shallow coastal waters using imaging data acquired with the Moderate Resolution Imaging SpectroRadiometer (MODIS). The MODIS instruments on board the NASA Terra and Aqua Spacecrafts are equipped with one set of narrow channels located in a wide 0.4 - 2.5 micron spectral range. These channels were designed primarily for remote sensing of the land surface and atmosphere. We have found that the set of land and cloud channels are also quite useful for remote sensing of the bright coastal waters. We have developed an empirical algorithm, which uses the narrow MODIS channels in this wide spectral range, for identifying areas with suspended sediments in turbid waters and shallow waters with bottom reflections. In our algorithm, we take advantage of the strong water absorption at wavelengths longer than 1 æm that does not allow illumination of sediments in the water or a shallow ocean floor. MODIS data acquired over the east coast of China, west coast of Africa, Arabian Sea, Mississippi Delta, and west coast of Florida are used in this study.

Retrieval of canopy moisture content for dynamic fire risk assessment using simulated MODIS bands

NASA Astrophysics Data System (ADS)

Maffei, Carmine; Leone, Antonio P.; Meoli, Giuseppe; Calabrò, Gaetano; Menenti, Massimo

2007-10-01

Forest fires are one of the major environmental hazards in Mediterranean Europe. Biomass burning reduces carbon fixation in terrestrial vegetation, while soil erosion increases in burned areas. For these reasons, more sophisticated prevention tools are needed by local authorities to forecast fire danger, allowing a sound allocation of intervention resources. Various factors contribute to the quantification of fire hazard, and among them vegetation moisture is the one that dictates vegetation susceptibility to fire ignition and propagation. Many authors have demonstrated the role of remote sensing in the assessment of vegetation equivalent water thickness (EWT), which is defined as the weight of liquid water per unit of leaf surface. However, fire models rely on the fuel moisture content (FMC) as a measure of vegetation moisture. FMC is defined as the ratio of the weight of the liquid water in a leaf over the weight of dry matter, and its retrieval from remote sensing measurements might be problematic, since it is calculated from two biophysical properties that independently affect vegetation reflectance spectrum. The aim of this research is to evaluate the potential of the Moderate Resolution Imaging Spectrometer (MODIS) in retrieving both EWT and FMC from top of the canopy reflectance. The PROSPECT radiative transfer code was used to simulate leaf reflectance and transmittance as a function of leaf properties, and the SAILH model was adopted to simulate the top of the canopy reflectance. A number of moisture spectral indexes have been calculated, based on MODIS bands, and their performance in predicting EWT and FMC has been evaluated. Results showed that traditional moisture spectral indexes can accurately predict EWT but not FMC. However, it has been found that it is possible to take advantage of the multiple MODIS short-wave infrared (SWIR) channels to improve the retrieval accuracy of FMC (r2 = 0.73). The effects of canopy structural properties on MODIS estimates of FMC have been evaluated, and it has been found that the limiting factor is leaf area index (LAI). The best results are recorded for LAI>2 (r2 = 0.83), while acceptable results (r2 = 0.58) can still be achieved for lower vegetation cover density.

Remotely-sensed near real-time monitoring of reservoir storage in India

NASA Astrophysics Data System (ADS)

Tiwari, A. D.; Mishra, V.

2017-12-01

Real-time reservoir storage information at a high temporal resolution is crucial to mitigate the influence of extreme events like floods and droughts. Despite large implications of near real-time reservoir monitoring in India for water resources and irrigation, remotely sensed monitoring systems have been lacking. Here we develop remotely sensed real-time monitoring systems for 91 large reservoirs in India for the period from 2000 to 2017. For the reservoir storage estimation, we combined Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day 250 m Enhanced Vegetation Index (EVI), and Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation Satellite (ICESat) ICESat/GLAS elevation data. Vegetation data with the highest temporal resolution available from the MODIS is at 16 days. To increase the temporal resolution to 8 days, we developed the 8-day composite of near infrared, red, and blue band surface reflectance. Surface reflectance 8-Day L3 Global 250m only have NIR band and Red band, therefore, surface reflectance of 8-Day L3 Global at 500m is used for the blue band, which was regridded to 250m spatial resolution. An area-elevation relationship was derived using area from an unsupervised classification of MODIS image followed by an image enhancement and elevation data from ICESat/GLAS. A trial and error method was used to obtain the area-elevation relationship for those reservoirs for which ICESat/GLAS data is not available. The reservoir storages results were compared with the gauge storage data from 2002 to 2009 (training period), which were then evaluated for the period of 2010 to 2016. Our storage estimates were highly correlated with observations (R2 = 0.6 to 0.96), and the normalized root mean square error (NRMSE) ranged between 10% and 50%. We also developed a relationship between precipitation and reservoir storage that can be used for prediction of storage during the dry season.

Applications of spectral band adjustment factors (SBAF) for cross-calibration

USGS Publications Warehouse

Chander, Gyanesh

2013-01-01

To monitor land surface processes over a wide range of temporal and spatial scales, it is critical to have coordinated observations of the Earth's surface acquired from multiple spaceborne imaging sensors. However, an integrated global observation framework requires an understanding of how land surface processes are seen differently by various sensors. This is particularly true for sensors acquiring data in spectral bands whose relative spectral responses (RSRs) are not similar and thus may produce different results while observing the same target. The intrinsic offsets between two sensors caused by RSR mismatches can be compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of the two sensors. The motivation of this work comes from the need to compensate the spectral response differences of multispectral sensors in order to provide a more accurate cross-calibration between the sensors. In this paper, radiometric cross-calibration of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors was performed using near-simultaneous observations over the Libya 4 pseudoinvariant calibration site in the visible and near-infrared spectral range. The RSR differences of the analogous ETM+ and MODIS spectral bands provide the opportunity to explore, understand, quantify, and compensate for the measurement differences between these two sensors. The cross-calibration was initially performed by comparing the top-of-atmosphere (TOA) reflectances between the two sensors over their lifetimes. The average percent differences in the long-term trends ranged from $-$5% to $+$6%. The RSR compensated ETM+ TOA reflectance (ETM+$^{ast}$) measurements were then found to agree with MODIS TOA reflectance to within 5% for all bands when Earth Observing-1 Hy- erion hyperspectral data were used to produce the SBAFs. These differences were later reduced to within 1% for all bands (except band 2) by using Environmental Satellite Scanning Imaging Absorption Spectrometer for Atmospheric Cartography hyperspectral data to produce the SBAFs.

Intercomparison and validation of MODIS and GLASS leaf area index (LAI) products over mountain areas: A case study in southwestern China

NASA Astrophysics Data System (ADS)

Jin, Huaan; Li, Ainong; Bian, Jinhu; Nan, Xi; Zhao, Wei; Zhang, Zhengjian; Yin, Gaofei

2017-03-01

The validation study of leaf area index (LAI) products over rugged surfaces not only gives additional insights into data quality of LAI products, but deepens understanding of uncertainties regarding land surface process models depended on LAI data over complex terrain. This study evaluated the performance of MODIS and GLASS LAI products using the intercomparison and direct validation methods over southwestern China. The spatio-temporal consistencies, such as the spatial distributions of LAI products and their statistical relationship as a function of topographic indices, time, and vegetation types, respectively, were investigated through intercomparison between MODIS and GLASS products during the period 2011-2013. The accuracies and change ranges of these two products were evaluated against available LAI reference maps over 10 sampling regions which standed for typical vegetation types and topographic gradients in southwestern China. The results show that GLASS LAI exhibits higher percentage of good quality data (i.e. successful retrievals) and smoother temporal profiles than MODIS LAI. The percentage of successful retrievals for MODIS and GLASS is vulnerable to topographic indices, especially to relief amplitude. Besides, the two products do not capture seasonal dynamics of crop, especially in spring over heterogeneously hilly regions. The yearly mean LAI differences between MODIS and GLASS are within ±0.5 for 64.70% of the total retrieval pixels over southwestern China. The spatial distribution of mean differences and temporal profiles of these two products are inclined to be dominated by vegetation types other than topographic indices. The spatial and temporal consistency of these two products is good over most area of grasses/cereal crops; however, it is poor for evergreen broadleaf forest. MODIS presents more reliable change range of LAI than GLASS through comparison with fine resolution reference maps over most of sampling regions. The accuracies of direct validation are obtained for GLASS LAI (r = 0.35, RMSE = 1.72, mean bias = -0.71) and MODIS LAI (r = 0.49, RMSE = 1.75, mean bias = -0.67). GLASS performs similarly to MODIS, but may be marginally inferior to MODIS based on our direct validation results. The validation experience demonstrates the necessity and importance of topographic consideration for LAI estimation over mountain areas. Considerable attention will be paid to the improvements of surface reflectance, retrieval algorithm and land cover types so as to enhance the quality of LAI products in topographically complex terrain.

Annual land cover change mapping using MODIS time series to improve emissions inventories.

NASA Astrophysics Data System (ADS)

López Saldaña, G.; Quaife, T. L.; Clifford, D.

2014-12-01

Understanding and quantifying land surface changes is necessary for estimating greenhouse gas and ammonia emissions, and for meeting air quality limits and targets. More sophisticated inventories methodologies for at least key emission source are needed due to policy-driven air quality directives. Quantifying land cover changes on an annual basis requires greater spatial and temporal disaggregation of input data. The main aim of this study is to develop a methodology for using Earth Observations (EO) to identify annual land surface changes that will improve emissions inventories from agriculture and land use/land use change and forestry (LULUCF) in the UK. First goal is to find the best sets of input features that describe accurately the surface dynamics. In order to identify annual and inter-annual land surface changes, a times series of surface reflectance was used to capture seasonal variability. Daily surface reflectance images from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 500m resolution were used to invert a Bidirectional Reflectance Distribution Function (BRDF) model to create the seamless time series. Given the limited number of cloud-free observations, a BRDF climatology was used to constrain the model inversion and where no high-scientific quality observations were available at all, as a gap filler. The Land Cover Map 2007 (LC2007) produced by the Centre for Ecology & Hydrology (CEH) was used for training and testing purposes. A prototype land cover product was created for 2006 to 2008. Several machine learning classifiers were tested as well as different sets of input features going from the BRDF parameters to spectral Albedo. We will present the results of the time series development and the first exercises when creating the prototype land cover product.

Radiative Properties of Smoke and Aerosol Over Land Surfaces

NASA Technical Reports Server (NTRS)

King, Michael D.

2000-01-01

This talk discusses smoke and aerosol's radiative properties with particular attention to distinguishing the measurement over clear sky from clouds over land, sea, snow, etc. surfaces, using MODIS Airborne Simulator data from (Brazil, arctic sea ice and tundra and southern Africa, west Africa, and other ecosystems. This talk also discusses the surface bidirectional reflectance using Cloud Absorption Radiometer, BRDF measurements of Saudi Arabian desert, Persian Gulf, cerrado and rain forests in Brazil, sea ice, tundra, Atlantic Ocean, Great Dismal Swamp, Kuwait oil fire smoke. Recent upgrades to instrument (new TOMS UVA channels at 340 and 380 planned use in Africa (SAFARI 2000) and possibly for MEIDEX will also be discussed. This talk also plans to discuss the spectral variation of surface reflectance over land and the sensitivity of off-nadir view angles to correlation between visible near-infrared reflectance for use in remote sensing of aerosol over land.

Dynamics of the turbidity maximum zone in a macrotidal estuary (the Gironde, France): Observations from field and MODIS satellite data

NASA Astrophysics Data System (ADS)

Doxaran, David; Froidefond, Jean-Marie; Castaing, Patrice; Babin, Marcel

2009-02-01

Over a 1-year period, field and satellite measurements of surface water turbidity were combined in order to study the dynamics of the turbidity maximum zone (TM) in a macrotidal estuary (the Gironde, France). Four fixed platforms equipped with turbidity sensors calibrated to give the suspended particulate matter (SPM) concentration provided continuous information in the upper estuary. Full resolution data recorded by the moderate resolution imaging spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellite platforms provided information in the central and lower estuary twice a day (depending on cloud cover). Field data were used to validate a recently developed SPM quantification algorithm applied to the MODIS 'surface reflectance' product. The algorithm is based on a relationship between the SPM concentration and a reflectance ratio of MODIS bands 2 (near-infrared) and 1 (red). Based on 62 and 75 match-ups identified in 2005 with MODIS Terra and Aqua data, the relative uncertainty of the algorithm applied to these sensors was found to be 22 and 18%, respectively. Field measurements showed the tidal variations of turbidity in the upper estuary, while monthly-averaged MODIS satellite data complemented by field data allowed observing the monthly movements of the TM in the whole estuary. The trapping of fine sediments occurred in the upper estuary during the period of low river flow. This resulted in the formation of a highly concentrated TM during a 4-month period. With increasing river flow, the TM moved rapidly to the central estuary. A part of the TM detached, moved progressively in the lower estuary and was finally either massively exported to the ocean during peak floods or temporary trapped (settled) on intertidal mudflats. The massive export to the ocean was apparently the result of combined favorable environmental conditions: presence of fluid mud near the mouth, high river flow, high tides and limited wind speeds. The mean SPM concentration within surface waters of the whole estuary showed strong seasonal variations but remained almost unchanged on a 1-year-basis. These observations suggest that the masses of suspended sediments exported toward the ocean and supplied by the rivers were almost equivalent during the year investigated (2005). Results show the usefulness of information extracted from combined field and current ocean color satellite data in order to monitor the transport of suspended particles in coastal and estuarine waters.

Satellite Monitoring of Asian Dust Storms from SeaWiFS and MODIS: Source, Pathway, and Interannual Variability

NASA Astrophysics Data System (ADS)

Hsu, N.; Tsay, S.; Jeong, M.; Holben, B.

2006-12-01

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of spring-time cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such popu-lation centers causes flight delays, pushes grit through windows and doors, and forces people indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol optical thickness and single scattering albedo over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been dif-ficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the satellite retrieved aerosol optical thickness with data from AERONET sunphotometers over desert and semi-desert regions. The compari-sons show reasonable agreements between these two. These new satellite prod-ucts will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments. The multiyear satellite measurements since 1998 from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with these dust outbreaks in East Asia. The monthly av-eraged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Satellite Monitoring of Asian Dust Storms from SeaWiFS and MODIS: Source, pathway and Interannual Variability

NASA Technical Reports Server (NTRS)

Hsu, N. Christina

2007-01-01

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such population centers causes flight delays, pushes grit through windows and doors, and forces people indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol optical thickness and single scattering albedo over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the satellite retrieved aerosol optical thickness with data from AERONET sunphotometers over desert and semi-desert regions. The comparisons show reasonable agreements between these two. These new satellite products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments. The multiyear satellite measurements since 1998 from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with these dust outbreaks in East Asia. The monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Satellite Monitoring of Asian Dust Storms from SeaWiFS and MODIS: Source, Pathway, and Interannual Variability

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Tsay, S.-C.; Bettenhausen, C.; Salustro, C.; Jeong, M. J.

2010-01-01

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochernical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such population centers causes flight delays, pushes grit through windows and doors, and forces people indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol optical thickness and single scattering albedo over bright reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the satellite retrieved aerosol optical thickness with data from AERONET sunphotometers over desert and semi-desert regions. The comparisons show reasonable agreements between these two. These new satellite products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments. The multiyear satellite measurements since 1998 from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with these dust outbreaks in East Asia. The monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Variation of MODIS reflectance and vegetation indices with viewing geometry and soybean development.

PubMed

Breunig, Fábio M; Galvão, Lênio S; Formaggio, Antônio R; Epiphanio, José C N

2012-06-01

Directional effects introduce a variability in reflectance and vegetation index determination, especially when large field-of-view sensors are used (e.g., Moderate Resolution Imaging Spectroradiometer - MODIS). In this study, we evaluated directional effects on MODIS reflectance and four vegetation indices (Normalized Difference Vegetation Index - NDVI; Enhanced Vegetation Index - EVI; Normalized Difference Water Index - NDWI(1640) and NDWI(2120)) with the soybean development in two growing seasons (2004-2005 and 2005-2006). To keep the reproductive stage for a given cultivar as a constant factor while varying viewing geometry, pairs of images obtained in close dates and opposite view angles were analyzed. By using a non-parametric statistics with bootstrapping and by normalizing these indices for angular differences among viewing directions, their sensitivities to directional effects were studied. Results showed that the variation in MODIS reflectance between consecutive phenological stages was generally smaller than that resultant from viewing geometry for closed canopies. The contrary was observed for incomplete canopies. The reflectance of the first seven MODIS bands was higher in the backscattering. Except for the EVI, the other vegetation indices had larger values in the forward scattering direction. Directional effects decreased with canopy closure. The NDVI was lesser affected by directional effects than the other indices, presenting the smallest differences between viewing directions for fixed phenological stages.

An Efficient Approach for Pixel Decomposition to Increase the Spatial Resolution of Land Surface Temperature Images from MODIS Thermal Infrared Band Data

PubMed Central

Wang, Fei; Qin, Zhihao; Li, Wenjuan; Song, Caiying; Karnieli, Arnon; Zhao, Shuhe

2015-01-01

Land surface temperature (LST) images retrieved from the thermal infrared (TIR) band data of Moderate Resolution Imaging Spectroradiometer (MODIS) have much lower spatial resolution than the MODIS visible and near-infrared (VNIR) band data. The coarse pixel scale of MODIS LST images (1000 m under nadir) have limited their capability in applying to many studies required high spatial resolution in comparison of the MODIS VNIR band data with pixel scale of 250–500 m. In this paper we intend to develop an efficient approach for pixel decomposition to increase the spatial resolution of MODIS LST image using the VNIR band data as assistance. The unique feature of this approach is to maintain the thermal radiance of parent pixels in the MODIS LST image unchanged after they are decomposed into the sub-pixels in the resulted image. There are two important steps in the decomposition: initial temperature estimation and final temperature determination. Therefore the approach can be termed double-step pixel decomposition (DSPD). Both steps involve a series of procedures to achieve the final result of decomposed LST image, including classification of the surface patterns, establishment of LST change with normalized difference of vegetation index (NDVI) and building index (NDBI), reversion of LST into thermal radiance through Planck equation, and computation of weights for the sub-pixels of the resulted image. Since the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with much higher spatial resolution than MODIS data was on-board the same platform (Terra) as MODIS for Earth observation, an experiment had been done in the study to validate the accuracy and efficiency of our approach for pixel decomposition. The ASTER LST image was used as the reference to compare with the decomposed LST image. The result showed that the spatial distribution of the decomposed LST image was very similar to that of the ASTER LST image with a root mean square error (RMSE) of 2.7 K for entire image. Comparison with the evaluation DisTrad (E-DisTrad) and re-sampling methods for pixel decomposition also indicate that our DSPD has the lowest RMSE in all cases, including urban region, water bodies, and natural terrain. The obvious increase in spatial resolution remarkably uplifts the capability of the coarse MODIS LST images in highlighting the details of LST variation. Therefore it can be concluded that, in spite of complicated procedures, the proposed DSPD approach provides an alternative to improve the spatial resolution of MODIS LST image hence expand its applicability to the real world. PMID:25609048

On-Orbit Calibration and Performance of Aqua MODIS Reflective Solar Bands

NASA Technical Reports Server (NTRS)

Xiong, Xiaoxiong; Sun, Junqiang; Xie, Xiaobo; Barnes, William; Salomonson, Vincent

2009-01-01

Aqua MODIS has successfully operated on-orbit for more than 6 years since its launch in May 2002, continuously making global observations and improving studies of changes in the Earth's climate and environment. 20 of the 36 MODIS spectral bands, covering wavelengths from 0.41 to 2.2 microns, are the reflective solar bands (RSB). They are calibrated on-orbit using an on-board solar diffuser (SD) and a solar diffuser stability monitor (SDSM). In addition, regularly scheduled lunar observations are made to track the RSB calibration stability. This paper presents Aqua MODIS RSB on-orbit calibration and characterization activities, methodologies, and performance. Included in this study are characterizations of detector signal-to-noise ratio (SNR), short-term stability, and long-term response change. Spectral wavelength dependent degradation of the SD bidirectional reflectance factor (BRF) and scan mirror reflectance, which also varies with angle of incidence (AOI), are examined. On-orbit results show that Aqua MODIS onboard calibrators have performed well, enabling accurate calibration coefficients to be derived and updated for the Level 1B (L1B) production and assuring high quality science data products to be continuously generated and distributed. Since launch, the short-term response, on a scan-by-scan basis, has remained extremely stable for most RSB detectors. With the exception of band 6, there have been no new RSB noisy or inoperable detectors. Like its predecessor, Terra MODIS, launched in December 1999, the Aqua MODIS visible (VIS) spectral bands have experienced relatively large changes, with an annual response decrease (mirror side 1) of 3.6% for band 8 at 0.412 microns, 2.3% for band 9 at 0.443 microns, 1.6% for band 3 at 0.469 microns, and 1.2% for band 10 at 0.488 microns. For other RSB bands with wavelengths greater than 0.5 microns, the annual response changes are typically less than 0.5%. In general, Aqua MODIS optics degradation is smaller than Terra MODIS and the mirror side differences are much smaller. Overall, Aqua MODIS RSB on-orbit performance is better than Terra MODIS.

A climatology of visible surface reflectance spectra

NASA Astrophysics Data System (ADS)

Zoogman, Peter; Liu, Xiong; Chance, Kelly; Sun, Qingsong; Schaaf, Crystal; Mahr, Tobias; Wagner, Thomas

2016-09-01

We present a high spectral resolution climatology of visible surface reflectance as a function of wavelength for use in satellite measurements of ozone and other atmospheric species. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument is planned to measure backscattered solar radiation in the 290-740 nm range, including the ultraviolet and visible Chappuis ozone bands. Observation in the weak Chappuis band takes advantage of the relative transparency of the atmosphere in the visible to achieve sensitivity to near-surface ozone. However, due to the weakness of the ozone absorption features this measurement is more sensitive to errors in visible surface reflectance, which is highly variable. We utilize reflectance measurements of individual plant, man-made, and other surface types to calculate the primary modes of variability of visible surface reflectance at a high spectral resolution, comparable to that of TEMPO (0.6 nm). Using the Moderate-resolution Imaging Spectroradiometer (MODIS) Bidirection Reflectance Distribution Function (BRDF)/albedo product and our derived primary modes we construct a high spatial resolution climatology of wavelength-dependent surface reflectance over all viewing scenes and geometries. The Global Ozone Monitoring Experiment-2 (GOME-2) Lambertian Equivalent Reflectance (LER) product provides complementary information over water and snow scenes. Preliminary results using this approach in multispectral ultraviolet+visible ozone retrievals from the GOME-2 instrument show significant improvement to the fitting residuals over vegetated scenes.

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

NASA Technical Reports Server (NTRS)

King, Michael D.; Moody, Eric G.; Platnick, Steven; Schaaf, Crystal B.

2005-01-01

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent production of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA's Terra and &la satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface's radiative characteristics. Cloud cover, which curtails retrievals, and the presence of ephemeral and seasonal snow limit the snow-free data to approximately half the global land surfaces on an annual equal-angle basis. This precludes the MOD43B3 albedo products from being used in some remote sensing and ground-based applications, &mate models, and global change research projects.

Edge-preserving data assimilation for fire monitoring using optical data

NASA Astrophysics Data System (ADS)

Gomez-Dans, Jose; Lewis, Philip; Disney, Mathias; Roy, David; Quaife, Tristan; Wooster, Martin

2013-04-01

Monitoring fire using optical data from moderate spatial resolution sensors is in essence a change detection process, where changes in reflectance (or a vegetation index) within two dates or periods are interpreted as fires if the change meets a number of spectral rules. A major challenge in any of these algorithms is accounting for angular effects due to different acquistion/illumination geometry. The MODIS Coll5 algorithm for example, uses linear kernel models to forward predict observations, and based on a statistical test, decides whether a change has occurred and labels it as a potential fire. While the algorithm is successful in many regions, it has problems dealing with cloudy periods, and with limitations in the available observations. In this work, we propose a new approach based on (i) a more advanced signal tracking method using edge-preserving data assimilation techniques and (ii) an interpretation of the change signal using a spectral linear model. The signal tracking approach uses linear kernel models, but solves for them using regularisation in time as a prior. This allows for a transfer of information from data rich periods to other periods where data may be more sparse. To minimise information leaking over the actual fire, we implement an edge-preserving mechanism that limits the information transfer over the disturbance. The result of this is a complete time series of surface reflectance acquired with a constant geometry. Note that the system provides complete uncertainty estimates of the parameters, taking into account the initial level of uncertainty in the observations of surface reflectance. A second stage interprets post-fire reflectance as a mixture of a "typical burn signal" and an unburned component, which we assume to be the pre-fire reflectance. We propose a simple spectral model for the burn signal, a constrained quadratic function. This model is appropriate for a number of burned material spectrum. We demonstrate using the MODIS burned area product that the approach provides useful complementary information about fires, describing the spectral nature of the burn signal, as well as providing information on potentially the impact of the fire in the pixel. Both approaches are then combined into a multispectral burned area algorithm with MODIS land surface observations. We test the performance of the proposed method, compare to other well-established products, and show some of the shortcomings of the proposed algorithm.

Verification, improvement and application of aerosol optical depths in China Part 1: Inter-comparison of NPP-VIIRS and Aqua-MODIS

NASA Astrophysics Data System (ADS)

Wei, Jing; Sun, Lin; Huang, Bo; Bilal, Muhammad; Zhang, Zhaoyang; Wang, Lunche

2018-02-01

The objective of this study is to evaluate typical aerosol optical depth (AOD) products in China, which experienced seriously increasing atmospheric particulate pollution. For this, the Aqua-MODerate resolution Imaging Spectroradiometer (MODIS) AOD products (MYD04) at 10 km spatial resolution and Visible Infrared Imaging Radiometer Suite (VIIRS) Environmental Data Record (EDR) AOD product at 6 km resolution for different Quality Flags (QF) are obtained for validation against AErosol RObotic NETwork (AERONET) AOD measurements during 2013-2016. Results show that VIIRS EDR similarly Dark Target (DT) and MODIS DT algorithms perform worse with only 45.36% and 45.59% of the retrievals (QF = 3) falling within the Expected Error (EE, ±(0.05 + 15%)) compared to the Deep Blue (DB) algorithm (69.25%, QF ≥ 2). The DT retrievals perform poorly over the Beijing-Tianjin-Hebei (BTH) and Yangtze-River-Delta (YRD) regions, which significantly overestimate the AOD observations, but the performance is better over the Pearl-River-Delta (PRD) region than DB retrievals, which seriously under-estimate the AOD loadings. It is not surprising that the DT algorithm performs better over vegetated areas, while the DB algorithm performs better over bright areas mainly depends on the accuracy of surface reflectance estimation over different land use types. In general, the sensitivity of aerosol to apparent reflectance reduces by about 34% with an increasing surface reflectance by 0.01. Moreover, VIIRS EDR and MODIS DT algorithms perform overall better in the winter as 64.53% and 72.22% of the retrievals are within the EE but with less retrievals. However, the DB algorithm performs worst (57.17%) in summer mainly affected by the vegetation growth but there are overall high accuracies with more than 62% of the collections falling within the EE in other three seasons. Results suggest that the quality assurance process can help improve the overall data quality for MYD04 DB retrievals, but it is not always true for VIIRS EDR and MYD04 DT AOD retrievals.

Updates on the development of Deep Blue aerosol algorithm for constructing consistent long-term data records from MODIS to VIIRS

NASA Astrophysics Data System (ADS)

Hsu, N. Y. C.; Sayer, A. M.; Lee, J.; Kim, W. V.

2017-12-01

The impacts of natural and anthropogenic sources of air pollution on climate and human health have continued to gain attention from the scientific community. In order to facilitate these effects, high quality consistent long-term global aerosol data records from satellites are essential. Several EOS-era instruments (e.g., SeaWiFS, MODIS, and MISR) are able to provide such information with a high degree of fidelity. However, with the aging MODIS sensors and the launch of the VIIRS instrument on Suomi NPP in late 2011, the continuation of long-term aerosol data records suitable for climate studies from MODIS to VIIRS is needed urgently. Recently, we have successfully modified our MODIS Deep Blue algorithm to process the VIIRS data. Extensive works were performed in refining the surface reflectance determination scheme to account for the wavelength differences between MODIS and VIIRS. Better aerosol models (including non-spherical dust) are also now implemented in our VIIRS algorithm compared to the MODIS C6 algorithm. We will show the global (land and ocean) distributions of various aerosol products from Version 1 of the VIIRS Deep Blue data set. The preliminary validation results of these new VIIRS Deep Blue aerosol products using data from AERONET sunphotometers over land and ocean will be discussed. We will also compare the monthly averaged Deep Blue aerosol optical depth (AOD) from VIIRS with the MODIS C6 products to investigate if any systematic biases may exist between MODIS C6 and VIIRS AOD. The Version 1 VIIRS Deep Blue aerosol products are currently scheduled to be released to the public in 2018.

Mixing weight determination for retrieving optical properties of polluted dust with MODIS and AERONET data

NASA Astrophysics Data System (ADS)

Chang, Kuo-En; Hsiao, Ta-Chih; Hsu, N. Christina; Lin, Neng-Huei; Wang, Sheng-Hsiang; Liu, Gin-Rong; Liu, Chian-Yi; Lin, Tang-Huang

2016-08-01

In this study, an approach in determining effective mixing weight of soot aggregates from dust-soot aerosols is proposed to improve the accuracy of retrieving properties of polluted dusts by means of satellite remote sensing. Based on a pre-computed database containing several variables (such as wavelength, refractive index, soot mixing weight, surface reflectivity, observation geometries and aerosol optical depth (AOD)), the fan-shaped look-up tables can be drawn out accordingly for determining the mixing weights, AOD and single scattering albedo (SSA) of polluted dusts simultaneously with auxiliary regional dust properties and surface reflectivity. To validate the performance of the approach in this study, 6 cases study of polluted dusts (dust-soot aerosols) in Lower Egypt and Israel were examined with the ground-based measurements through AErosol RObotic NETwork (AERONET). The results show that the mean absolute differences could be reduced from 32.95% to 6.56% in AOD and from 2.67% to 0.83% in SSA retrievals for MODIS aerosol products when referenced to AERONET measurements, demonstrating the soundness of the proposed approach under different levels of dust loading, mixing weight and surface reflectivity. Furthermore, the developed algorithm is capable of providing the spatial distribution of the mixing weights and removing the requirement to assume that the dust plume properties are uniform. The case study further shows the spatially variant dust-soot mixing weight would improve the retrieval accuracy in AODmixture and SSAmixture about 10.0% and 1.4% respectively.

Estimation of Melt Ponds over Arctic Sea Ice using MODIS Surface Reflectance Data

NASA Astrophysics Data System (ADS)

Ding, Y.; Cheng, X.; Liu, J.

2017-12-01

Melt ponds over Arctic sea ice is one of the main factors affecting variability of surface albedo, increasing absorption of solar radiation and further melting of snow and ice. In recent years, a large number of melt ponds have been observed during the melt season in Arctic. Moreover, some studies have suggested that late spring to mid summer melt ponds information promises to improve the prediction skill of seasonal Arctic sea ice minimum. In the study, we extract the melt pond fraction over Arctic sea ice since 2000 using three bands MODIS weekly surface reflectance data by considering the difference of spectral reflectance in ponds, ice and open water. The preliminary comparison shows our derived Arctic-wide melt ponds are in good agreement with that derived by the University of Hamburg, especially at the pond distribution. We analyze seasonal evolution, interannual variability and trend of the melt ponds, as well as the changes of onset and re-freezing. The melt pond fraction shows an asymmetrical growth and decay pattern. The observed melt ponds fraction is almost within 25% in early May and increases rapidly in June and July with a high fraction of more than 40% in the east of Greenland and Beaufort Sea. A significant increasing trend in the melt pond fraction is observed for the period of 2000-2017. The relationship between melt pond fraction and sea ice extent will be also discussed. Key Words: melt ponds, sea ice, Arctic

Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land

NASA Astrophysics Data System (ADS)

Lipponen, Antti; Mielonen, Tero; Pitkänen, Mikko R. A.; Levy, Robert C.; Sawyer, Virginia R.; Romakkaniemi, Sami; Kolehmainen, Ville; Arola, Antti

2018-03-01

We have developed a Bayesian aerosol retrieval (BAR) algorithm for the retrieval of aerosol optical depth (AOD) over land from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the BAR algorithm, we simultaneously retrieve all dark land pixels in a granule, utilize spatial correlation models for the unknown aerosol parameters, use a statistical prior model for the surface reflectance, and take into account the uncertainties due to fixed aerosol models. The retrieved parameters are total AOD at 0.55 µm, fine-mode fraction (FMF), and surface reflectances at four different wavelengths (0.47, 0.55, 0.64, and 2.1 µm). The accuracy of the new algorithm is evaluated by comparing the AOD retrievals to Aerosol Robotic Network (AERONET) AOD. The results show that the BAR significantly improves the accuracy of AOD retrievals over the operational Dark Target (DT) algorithm. A reduction of about 29 % in the AOD root mean square error and decrease of about 80 % in the median bias of AOD were found globally when the BAR was used instead of the DT algorithm. Furthermore, the fraction of AOD retrievals inside the ±(0.05+15 %) expected error envelope increased from 55 to 76 %. In addition to retrieving the values of AOD, FMF, and surface reflectance, the BAR also gives pixel-level posterior uncertainty estimates for the retrieved parameters. The BAR algorithm always results in physical, non-negative AOD values, and the average computation time for a single granule was less than a minute on a modern personal computer.

Expanding the Estimation of Surface PM2.5 from Aqua and Terra MODIS Aerosol Optical Depth in the EPA's AirNow Satellite Data Processor to Suomi NPP VIIRS

NASA Astrophysics Data System (ADS)

Szykman, J.; Kondragunta, S.; Zhang, H.; Dickerson, P.; van Donkelaar, A.; Martin, R. V.; Pasch, A. N.; White, J. E.; DeWinter, J. L.; Zahn, P. H.; Dye, T. S.; Haderman, M. D.

2012-12-01

The U.S. Environmental Protection Agency's (EPA) Air Quality Index (AQI) relies on hourly measurements of ground-based surface PM2.5 (particles smaller than 2.5 μm in median diameter) to develop daily AQI index maps. The EPA is improving the accuracy of AQI information and extending its coverage for reporting to the public by incorporating National Aeronautics and Space Administration (NASA) satellite-derived surface PM2.5 concentrations into daily AQI maps. The additional coverage will provide air quality information in regions without dense monitoring networks. The AirNow Satellite Data Processor (ASDP) uses daily PM2.5 estimates and uncertainties derived from average Aqua and Terra MODerate resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) in near real-time over the United States. The algorithm to derive surface PM2.5 from MODIS AOD relies on linear relationships between AOD and PM2.5 generated from multi-year GEOS-Chem model simulations (van Donkelaar et al., 2012). Parameters from the regression equation (slopes and intercepts) are saved in a lookup table (LUT) with 4 km spatial resolution for each day of a given year. To improve data accuracy and continuity, a filter is applied to remove MODIS AOD with low accuracy (e.g., over bright surfaces) and an inverse distance weighted average is applied to fill in gaps created by cloud coverage. Daily surface PM2.5 estimates and their uncertainties are generated at the National Oceanic and Atmospheric Administration (NOAA) using the van Donkelaar et al. algorithm and near real-time MODIS AOD products from Terra and Aqua and are provided to the EPA through its Infusing satellite Data into Environmental Applications (IDEA) website. The Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on October 28, 2011, and similar to MODIS, provides AOD products for real-time applications. NOAA plans to explore the value of VIIRS AOD products to improve AQI. This presentation will focus on a description of ASDP, including an overview of the algorithm used to estimate surface PM2.5 using satellite data and examples of high resolution VIIRS AOD products and their value to the ASDP. Disclaimer: Although this work was reviewed by the U.S. Environmental Protection Agency and approved for publication, it may not necessarily reflect official Agency policy.

Relationship Between Surface Reflectance in the Visible and Mid-IR used in MODIS Aerosol Algorithm-Theory

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Gobron, Nadine; Pinty, Bernard; Widlowski, Jean-Luc; Verstraete, Michel M.; Lau, William K. M. (Technical Monitor)

2002-01-01

Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument that flies in polar orbit on the Terra platform, are used to derive the aerosol optical thickness and properties over land and ocean. The relationships between visible reflectance (at blue, rho(sub blue), and red, rho(sub red)) and mid-infrared (at 2.1 microns, rho(sub 2.1)) are used in the MODIS aerosol retrieval algorithm to derive global distribution of aerosols over the land. These relations have been established from a series of measurements indicating that rho(sub blue) is approximately 0.5 rho(sub red) is approximately 0.25 rho(sub 2.1). Here we use a model to describe the transfer of radiation through a vegetation canopy composed of randomly oriented leaves to assess the theoretical foundations for these relationships. Calculations for a wide range of leaf area indices and vegetation fractions show that rho(sub blue) is consistently about 1/4 of rho(sub 2.1) as used by MODIS for the whole range of analyzed cases, except for very dark soils, such as those found in burn scars. For its part, the ratio rho(sub red)/rho(sub 2.1) varies from less than the empirically derived value of 1/2 for dense and dark vegetation, to more than 1/2 for bright mixture of soil and vegetation. This is in agreement with measurements over uniform dense vegetation, but not with measurements over mixed dark scenes. In the later case the discrepancy is probably mitigated by shadows due to uneven canopy and terrain on a large scale. It is concluded that the value of this ratio should ideally be made dependent on the land cover type in the operational processing of MODIS data, especially over dense forests.

Radiometric cross-calibration of the Terra MODIS and Landsat 7 ETM+ using an invariant desert site

USGS Publications Warehouse

Choi, T.; Angal, A.; Chander, G.; Xiong, X.

2008-01-01

A methodology for long-term radiometric cross-calibration between the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors was developed. The approach involves calibration of near-simultaneous surface observations between 2000 and 2007. Fifty-seven cloud-free image pairs were carefully selected over the Libyan desert for this study. The Libyan desert site (+28.55??, +23.39??), located in northern Africa, is a high reflectance site with high spatial, spectral, and temporal uniformity. Because the test site covers about 12 kmx13 km, accurate geometric preprocessing is required to match the footprint size between the two sensors to avoid uncertainties due to residual image misregistration. MODIS Level IB radiometrically corrected products were reprojected to the corresponding ETM+ image's Universal Transverse Mercator (UTM) grid projection. The 30 m pixels from the ETM+ images were aggregated to match the MODIS spatial resolution (250 m in Bands 1 and 2, or 500 m in Bands 3 to 7). The image data from both sensors were converted to absolute units of at-sensor radiance and top-ofatmosphere (TOA) reflectance for the spectrally matching band pairs. For each band pair, a set of fitted coefficients (slope and offset) is provided to quantify the relationships between the testing sensors. This work focuses on long-term stability and correlation of the Terra MODIS and L7 ETM+ sensors using absolute calibration results over the entire mission of the two sensors. Possible uncertainties are also discussed such as spectral differences in matching band pairs, solar zenith angle change during a collection, and differences in solar irradiance models.

Global Space-Based Inter-Calibration System Reflective Solar Calibration Reference: From Aqua MODIS to S-NPP VIIRS

NASA Technical Reports Server (NTRS)

Xiong, Xiaoxiong; Angal, Amit; Butler, James; Cao, Changyong; Doelling, Daivd; Wu, Aisheng; Wu, Xiangqian

2016-01-01

The MODIS has successfully operated on-board the NASA's EOS Terra and Aqua spacecraft for more than 16 and 14 years, respectively. MODIS instrument was designed with stringent calibration requirements and comprehensive on-board calibration capability. In the reflective solar spectral region, Aqua MODIS has performed better than Terra MODIS and, therefore, has been chosen by the Global Space-based Inter-Calibration System (GSICS) operational community as the calibration reference sensor in cross-sensor calibration and calibration inter-comparisons. For the same reason, it has also been used by a number of earth observing sensors as their calibration reference. Considering that Aqua MODIS has already operated for nearly 14 years, it is essential to transfer its calibration to a follow-on reference sensor with a similar calibration capability and stable performance. The VIIRS is a follow-on instrument to MODIS and has many similar design features as MODIS, including their on-board calibrators (OBC). As a result, VIIRS is an ideal candidate to replace MODIS to serve as the future GSICS reference sensor. Since launch, the S-NPP VIIRS has already operated for more than 4 years and its overall performance has been extensively characterized and demonstrated to meet its overall design requirements. This paper provides an overview of Aqua MODIS and S-NPP VIIRS reflective solar bands (RSB) calibration methodologies and strategies, traceability, and their on-orbit performance. It describes and illustrates different methods and approaches that can be used to facilitate the calibration reference transfer, including the use of desert and Antarctic sites, deep convective clouds (DCC), and the lunar observations.

Preliminary assessment of the GOES-R ABI hourly land surface albedo and reflectance products prototyped with Himawari AHI data

NASA Astrophysics Data System (ADS)

He, T.; Liang, S.; Zhang, Y.; Yu, Y.

2016-12-01

Land surface albedo and reflectance are critical geophysical variables used in climate and environmental applications. The multispectral Advanced Baseline Imager (ABI) onboard the next generation geostationary satellites (GOES-R series, set to launch in late 2016) offers high temporal and medium spatial resolution observations, which can be used for monitoring diurnal variation of surface albedo and reflectance. In the GOES-R data processing chain there is no atmospheric correction to generate surface reflectance product, which is usually required for surface albedo estimation. We propose an optimization method to simultaneously retrieve surface bidirectional reflectance distribution function (BRDF) parameters and aerosol optical depth with GOES-R ABI data on a daily-basis, which are used for estimating surface albedo and reflectance. Before the launch of the GOES-R satellite, our algorithm was prototyped with data from the Advanced Himawari Imager (AHI) onboard the Japanese Himawari-8 satellite, which has spectral bands and spatial resolutions similar to GOES-R ABI. Cal/val activities were carried out against ground measurements at the OzFlux sites in Australia and satellite data including albedo/BRDF products from MODIS and Landsat. The preliminary accuracy assessment showed promising results for both the surface albedo and reflectance estimates. The GOES-R surface albedo and reflectance products will serve as critical inputs for downstream GOES-R satellite products and also help improve climate modeling and weather forecasting with a high temporal resolution.

Land and cryosphere products from Suomi NPP VIIRS: Overview and status

PubMed Central

Justice, Christopher O; Román, Miguel O; Csiszar, Ivan; Vermote, Eric F; Wolfe, Robert E; Hook, Simon J; Friedl, Mark; Wang, Zhuosen; Schaaf, Crystal B; Miura, Tomoaki; Tschudi, Mark; Riggs, George; Hall, Dorothy K; Lyapustin, Alexei I; Devadiga, Sadashiva; Davidson, Carol; Masuoka, Edward J

2013-01-01

[1] The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-Orbiting Partnership (S-NPP). The VIIRS instrument was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA’s Earth Observing System’s Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA- and NOAA-funded scientists have been working to evaluate the instrument performance and generate land and cryosphere products to meet the needs of the NOAA operational users and the NASA science community. NOAA’s focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the National Polar-Orbiting Environmental Satellite System. The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs, and providing MODIS data product continuity. This paper presents to-date findings of the NASA Science Team’s evaluation of the VIIRS land and cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization. The study concludes that, for MODIS data product continuity and earth system science, an enhanced suite of land and cryosphere products and associated data system capabilities are needed beyond the EDRs currently available from the VIIRS. PMID:25821661

Land and cryosphere products from Suomi NPP VIIRS: Overview and status.

PubMed

Justice, Christopher O; Román, Miguel O; Csiszar, Ivan; Vermote, Eric F; Wolfe, Robert E; Hook, Simon J; Friedl, Mark; Wang, Zhuosen; Schaaf, Crystal B; Miura, Tomoaki; Tschudi, Mark; Riggs, George; Hall, Dorothy K; Lyapustin, Alexei I; Devadiga, Sadashiva; Davidson, Carol; Masuoka, Edward J

2013-09-16

[1] The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-Orbiting Partnership (S-NPP). The VIIRS instrument was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA's Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA- and NOAA-funded scientists have been working to evaluate the instrument performance and generate land and cryosphere products to meet the needs of the NOAA operational users and the NASA science community. NOAA's focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the National Polar-Orbiting Environmental Satellite System. The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs, and providing MODIS data product continuity. This paper presents to-date findings of the NASA Science Team's evaluation of the VIIRS land and cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization. The study concludes that, for MODIS data product continuity and earth system science, an enhanced suite of land and cryosphere products and associated data system capabilities are needed beyond the EDRs currently available from the VIIRS.

An assessment of the land surface emissivity in the 8 - 12 micrometer window determined from ASTER and MODIS data

NASA Astrophysics Data System (ADS)

Schmugge, T.; Hulley, G.; Hook, S.

2009-04-01

The land surface emissivity is often overlooked when considering surface properties that effect the energy balance. However, knowledge of the emissivity in the window region is important for determining the longwave radiation balance and its subsequent effect on surface temperature. The net longwave radiation (NLR) is strongly affected by the difference between the temperature of the emitting surface and the sky brightness temperature, this difference will be the greatest in the window region. Outside the window region any changes in the emitted radiation by emissivity variability are mostly compensated for by changes in the reflected sky brightness. The emissivity variability is typically greatest in arid regions where the exposed soil and rock surfaces display the widest range of emissivity. For example, the dune regions of North Africa have emissivities of 0.7 or less in the 8 to 9 micrometer wavelength band due to the quartz sands of the region, which can produce changes in NLR of more than 10 w/m*m compared to assuming a constant emissivity. The errors in retrievals of atmospheric temperature and moisture profiles from hyperspectral infrared radiances, such as those from the Atmospheric Infrared Sounder (AIRS) on the NASA Aqua satellite result from using constant or inaccurate surface emissivities, particularly over arid and semi-arid regions here the variation in emissivity is large, both spatially and spectrally. The multispectral thermal infrared data obtained from the Advanced Spaceborne Thermal Emission and Reflection (ASTER) radiometer and MODerate resolution Imaging Spectrometer (MODIS) sensors on NASA's Terra satellite have been shown to be of good quality and provide a unique new tool for studying the emissivity of the land surface. ASTER has 5 channels in the 8 to 12 micrometer waveband with 90 m spatial resolution, when the data are combined with the Temperature Emissivity Separation (TES) algorithm the surface emissivity over this wavelength region can be determined. The TES algorithm has been validated with field measurements using a multi-spectral radiometer having similar bands to ASTER. The ASTER data have now been used to produce a seasonal gridded database of the emissivity for North America and the results compared to laboratory measured emissivities of in-situ rock/sand samples collected at ten validation sites in the Western USA during 2008. The directional hemispherical reflectance of the in-situ samples are measured in the laboratory using a Nicolet Fourier Transform Interferometer (FTIR), converted to emissivity using Kirchoff's law, and convolving to the appropriate sensor spectral response functions. This ASTER database, termed the North American ASTER Land Surface Emissivity Database (NAALSED), was validated using the laboratory results from these ten sites to within 0.015 (1.5%) in emissivity. MODIS has 3 channels in this waveband with 1km spatial resolution and almost daily global coverage. The MODIS data are composited to 5 km resolution and day night pairs of observations are used to derive the emissivities. These results have been validated using the ASTER emissivities over selected test areas.

Estimation of Surface Air Temperature from MODIS 1km Resolution Land Surface Temperature Over Northern China

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina

2010-01-01

Surface air temperature is a critical variable to describe the energy and water cycle of the Earth-atmosphere system and is a key input element for hydrology and land surface models. It is a very important variable in agricultural applications and climate change studies. This is a preliminary study to examine statistical relationships between ground meteorological station measured surface daily maximum/minimum air temperature and satellite remotely sensed land surface temperature from MODIS over the dry and semiarid regions of northern China. Studies were conducted for both MODIS-Terra and MODIS-Aqua by using year 2009 data. Results indicate that the relationships between surface air temperature and remotely sensed land surface temperature are statistically significant. The relationships between the maximum air temperature and daytime land surface temperature depends significantly on land surface types and vegetation index, but the minimum air temperature and nighttime land surface temperature has little dependence on the surface conditions. Based on linear regression relationship between surface air temperature and MODIS land surface temperature, surface maximum and minimum air temperatures are estimated from 1km MODIS land surface temperature under clear sky conditions. The statistical errors (sigma) of the estimated daily maximum (minimum) air temperature is about 3.8 C(3.7 C).

Satellite observations of turbidity in the Dead Sea

NASA Astrophysics Data System (ADS)

Nehorai, R.; Lensky, I. M.; Hochman, L.; Gertman, I.; Brenner, S.; Muskin, A.; Lensky, N. G.

2013-06-01

A methodology to attain daily variability of turbidity in the Dead Sea by means of remote sensing was developed. 250 m/pixel moderate resolution imaging spectroradiometer (MODIS) surface reflectance data were used to characterize the seasonal cycle of turbidity and plume spreading generated by flood events in the lake. Fifteen minutes interval images from meteosat second generation 1.6 km/pixel high-resolution visible (HRV) channel were used to monitor daily variations of turbidity. The HRV reflectance was normalized throughout the day to correct for the changing geometry and then calibrated against available MODIS surface reflectance. Finally, hourly averaged reflectance maps are presented for summer and winter. The results show that turbidity is concentrated along the silty shores of the lake and the southern embayments, with a gradual decrease of turbidity values from the shoreline toward the center of the lake. This pattern is most pronounced following the nighttime hours of intense winds. A few hours after winds calm the concentric turbidity pattern fades. In situ and remote sensing observations show a clear relation between wind intensity, wave amplitude and water turbidity. In summer and winter similar concentric turbidity patterns are observed but with a much narrower structure in winter. A simple Lagrangain trajectory model suggests that the combined effects of horizontal transport and vertical mixing of suspended particles leads to more effective mixing in winter. The dynamics of suspended matter contributions from winter desert floods are also presented in terms of hourly turbidity maps showing the spreading of the plumes and their decay.

Time-Dependent Response Versus Scan Angle for MODIS Reflective Solar Bands

NASA Technical Reports Server (NTRS)

Sun, Junqiang; Xiong, Xiaoxiong; Angal, Amit; Chen, Hongda; Wu, Aisheng; Geng, Xu

2014-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments currently operate onboard the National Aeronautics and Space Administration (NASA's) Terra and Aqua spacecraft, launched on December 18, 1999 and May 4, 2002, respectively. MODIS has 36 spectral bands, among which 20 are reflective solar bands (RSBs) covering a spectral range from 0.412 to 2.13 µm. The RSBs are calibrated on orbit using a solar diffuser (SD) and an SD stability monitor and with additional measurements from lunar observations via a space view (SV) port. Selected pseudo-invariant desert sites are also used to track the RSB on-orbit gain change, particularly for short-wavelength bands. MODIS views the Earth surface, SV, and the onboard calibrators using a two-sided scan mirror. The response versus scan angle (RVS) of the scan mirror was characterized prior to launch, and its changes are tracked using observations made at different angles of incidence from onboard SD, lunar, and Earth view (EV) measurements. These observations show that the optical properties of the scan mirror have experienced large wavelength-dependent degradation in both the visible and near infrared spectral regions. Algorithms have been developed to track the on-orbit RVS change using the calibrators and the selected desert sites. These algorithms have been applied to both Terra and Aqua MODIS Level 1B (L1B) to improve the EV data accuracy since L1B Collection 4, refined in Collection 5, and further improved in the latest Collection 6 (C6). In C6, two approaches have been used to derive the time-dependent RVS for MODIS RSB. The first approach relies on data collected from sensor onboard calibrators and mirror side ratios from EV observations. The second approach uses onboard calibrators and EV response trending from selected desert sites. This approach is mainly used for the bands with much larger changes in their time-dependent RVS, such as the Terra MODIS bands 1-4, 8, and 9 and the Aqua MODIS bands 8- and 9. In this paper, the algorithms of these approaches are described, their performance is demonstrated, and their impact on L1B products is discussed. In general, the shorter wavelength bands have experienced a larger on-orbit RVS change, which, in general, are mirror side and detector dependent. The on-orbit RVS change due to the degradation of band 8 can be as large as 35 percent for Terra MODIS and 20 percent for Aqua MODIS. Vital to maintaining the accuracy of the MODIS L1B products is an accurate characterization of the on-orbit RVS change. The derived time-independent RVS, implemented in C6, makes an important improvement to the quality of the MODIS L1B products.

MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.

2010-01-01

Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

A Relationship Between Visible and Near-IR Global Spectral Reflectance based on DSCOVR/EPIC

NASA Astrophysics Data System (ADS)

Wen, G.; Marshak, A.; Song, W.; Knyazikhin, Y.

2017-12-01

The launch of Deep Space Climate Observatory (DSCOVR) to the Earth's first Lagrange point (L1) allows us to see a new perspective of the Earth. The Earth Polychromatic Imaging Camera (EPIC) on the DSCOVR measures the back scattered radiation of the entire sunlit side of the Earth at 10 narrow band wavelengths ranging from ultraviolet to visible and near-infrared. We analyzed EPIC global averaged reflectance data. We found that the global averaged visible reflectance has a unique non-linear relationship with near infrared (NIR) reflectance. This non-linear relationship was not observed by any other satellite observations due to a limited spatial and temporal coverage of either low earth orbit (LEO) or geostationary satellite. The non-linear relationship is associated with the changing in the coverages of ocean, cloud, land, and vegetation as the Earth rotates. We used Terra and Aqua MODIS daily global radiance data to simulate EPIC observations. Since MODIS samples the Earth in a limited swath (2330km cross track) at a specific local time (10:30 am for Terra, 1:30 pm for Aqua) with approximately 15 orbits per day, the global average reflectance at a given time may be approximated by averaging the reflectance in the MODIS nearest-time swaths in the sunlit hemisphere. We found that MODIS simulated global visible and NIR spectral reflectance captured the major feature of the EPIC observed non-linear relationship with some errors. The difference between the two is mainly due to the sampling limitation of polar satellite. This suggests that that EPIC observations can be used to reconstruct MODIS global average reflectance time series for studying Earth system change in the past decade.

Multi-sensor analysis of urban ecosystems

USGS Publications Warehouse

Gallo, Kevin P.; Ji, Lei

2004-01-01

This study examines the synthesis of multiple space-based sensors to characterize the urban environment Single scene data (e.g., ASTER visible and near-IR surface reflectance, and land surface temperature data), multi-temporal data (e.g., one year of 16-day MODIS and AVHRR vegetation index data), and DMSP-OLS nighttime light data acquired in the early 1990s and 2000 were evaluated for urban ecosystem analysis. The advantages of a multi-sensor approach for the analysis of urban ecosystem processes are discussed.

Estimating Coastal Turbidity using MODIS 250 m Band Observations

NASA Technical Reports Server (NTRS)

Davies, James E.; Moeller, Christopher C.; Gunshor, Mathew M.; Menzel, W. Paul; Walker, Nan D.

2004-01-01

Terra MODIS 250 m observations are being applied to a Suspended Sediment Concentration (SSC) algorithm that is under development for coastal case 2 waters where reflectance is dominated by sediment entrained in major fluvial outflows. An atmospheric correction based on MODIS observations in the 500 m resolution 1.6 and 2.1 micron bands is used to isolate the remote sensing reflectance in the MODIS 25Om resolution 650 and 865 nanometer bands. SSC estimates from remote sensing reflectance are based on accepted inherent optical properties of sediment types known to be prevalent in the U.S. Gulf of Mexico coastal zone. We present our findings for the Atchafalaya Bay region of the Louisiana Coast, in the form of processed imagery over the annual cycle. We also apply our algorithm to selected sites worldwide with a goal of extending the utility of our approach to the global direct broadcast community.

MODIS tasselled cap: land cover characteristics expressed through transformed MODIS data

Treesearch

S. E. Lobser; W. B. Cohen

2007-01-01

The tasselled cap concept is extended to Moderate Resolution Imaging Spectroradiometer (MODIS) Nadir BRDF-Adjusted Reflectance (NBAR, MOD43) data. The transformation is based on a rigid rotation of principal component axes (PCAs) derived from a global sample spanning one full year of NBAR 16-day composites. To provide a standard for MODIS tasselled cap axes, we...

Development and Testing of the New Surface LER Climatology for OMI UV Aerosol Retrievals

NASA Technical Reports Server (NTRS)

Gupta, Pawan; Torres, Omar; Jethva, Hiren; Ahn, Changwoo

2014-01-01

Ozone Monitoring Instrument (OMI) onboard Aura satellite retrieved aerosols properties using UV part of solar spectrum. The OMI near UV aerosol algorithm (OMAERUV) is a global inversion scheme which retrieves aerosol properties both over ocean and land. The current version of the algorithm makes use of TOMS derived Lambertian Equivalent Reflectance (LER) climatology. A new monthly climatology of surface LER at 354 and 388 nm have been developed. This will replace TOMS LER (380 nm and 354nm) climatology in OMI near UV aerosol retrieval algorithm. The main objectives of this study is to produce high resolution (quarter degree) surface LER sets as compared to existing one degree TOMS surface LERs, to product instrument and wavelength consistent surface climatology. Nine years of OMI observations have been used to derive monthly climatology of surface LER. MODIS derived aerosol optical depth (AOD) have been used to make aerosol corrections on OMI wavelengths. MODIS derived BRDF adjusted reflectance product has been also used to capture seasonal changes in the surface characteristics. Finally spatial and temporal averaging techniques have been used to fill the gaps around the globes, especially in the regions with consistent cloud cover such as Amazon. After implementation of new surface data in the research version of algorithm, comparisons of AOD and single scattering albedo (SSA) have been performed over global AERONET sites for year 2007. Preliminary results shows improvements in AOD retrievals globally but more significance improvement were observed over desert and bright locations. We will present methodology of deriving surface data sets and will discuss the observed changes in retrieved aerosol properties with respect to reference AERONET measurements.

Calibration of the DSCOVR EPIC Visible and NIR Channels using MODIS Terra and Aqua Data and EPIC Lunar Observations

NASA Technical Reports Server (NTRS)

Geogdzhayev, Igor V.; Marshak, Alexander

2018-01-01

The unique position of the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) at the Lagrange 1 point makes an important addition to the data from currently operating low Earth orbit observing instruments. EPIC instrument does not have an onboard calibration facility. One approach to its calibration is to compare EPIC observations to the measurements from polar-orbiting radiometers. Moderate Resolution Imaging Spectroradiometer (MODIS) is a natural choice for such comparison due to its well-established calibration record and wide use in remote sensing. We use MODIS Aqua and Terra L1B 1km reflectances to infer calibration coefficients for four EPIC visible and NIR channels: 443, 551, 680 and 780 nm. MODIS and EPIC measurements made between June 2015 and 2016 are employed for comparison. We first identify favorable MODIS pixels with scattering angle matching temporarily collocated EPIC observations. Each EPIC pixel is then spatially collocated to a subset of the favorable MODIS pixels within 25 km radius. Standard deviation of the selected MODIS pixels as well as of the adjacent EPIC pixels is used to find the most homogeneous scenes. These scenes are then used to determine calibration coefficients using a linear regression between EPIC counts/sec and reflectances in the close MODIS spectral channels. We present thus inferred EPIC calibration coefficients and discuss sources of uncertainties. The lunar EPIC observations are used to calibrate EPIC O2 absorbing channels (688 and 764 nm), assuming that there is a small difference between moon reflectances separated by approx.10 nm in wavelength provided the calibration factors of the red (680 nm) and near-IR (780 nm) are known from comparison between EPIC and MODIS.

An enhanced VIIRS aerosol optical thickness (AOT) retrieval algorithm over land using a global surface reflectance ratio database

NASA Astrophysics Data System (ADS)

Zhang, Hai; Kondragunta, Shobha; Laszlo, Istvan; Liu, Hongqing; Remer, Lorraine A.; Huang, Jingfeng; Superczynski, Stephen; Ciren, Pubu

2016-09-01

The Visible/Infrared Imager Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite has been retrieving aerosol optical thickness (AOT), operationally and globally, over ocean and land since shortly after S-NPP launch in 2011. However, the current operational VIIRS AOT retrieval algorithm over land has two limitations in its assumptions for land surfaces: (1) it only retrieves AOT over the dark surfaces and (2) it assumes that the global surface reflectance ratios between VIIRS bands are constants. In this work, we develop a surface reflectance ratio database over land with a spatial resolution 0.1° × 0.1° using 2 years of VIIRS top of atmosphere reflectances. We enhance the current operational VIIRS AOT retrieval algorithm by applying the surface reflectance ratio database in the algorithm. The enhanced algorithm is able to retrieve AOT over both dark and bright surfaces. Over bright surfaces, the VIIRS AOT retrievals from the enhanced algorithm have a correlation of 0.79, mean bias of -0.008, and standard deviation (STD) of error of 0.139 when compared against the ground-based observations at the global AERONET (Aerosol Robotic Network) sites. Over dark surfaces, the VIIRS AOT retrievals using the surface reflectance ratio database improve the root-mean-square error from 0.150 to 0.123. The use of the surface reflectance ratio database also increases the data coverage of more than 20% over dark surfaces. The AOT retrievals over bright surfaces are comparable to MODIS Deep Blue AOT retrievals.

Global Data for Ecology and Epidemiology: A Novel Algorithm for Temporal Fourier Processing MODIS Data

PubMed Central

Scharlemann, Jörn P. W.; Benz, David; Hay, Simon I.; Purse, Bethan V.; Tatem, Andrew J.; Wint, G. R. William; Rogers, David J.

2008-01-01

Background Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. Methodology/Principal Findings We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Conclusions/Significance Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling. PMID:18183289

Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data.

PubMed

Scharlemann, Jörn P W; Benz, David; Hay, Simon I; Purse, Bethan V; Tatem, Andrew J; Wint, G R William; Rogers, David J

2008-01-09

Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling.

Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS)

NASA Technical Reports Server (NTRS)

Masek, Jeffrey G.

2006-01-01

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project is creating a record of forest disturbance and regrowth for North America from the Landsat satellite record, in support of the carbon modeling activities. LEDAPS relies on the decadal Landsat GeoCover data set supplemented by dense image time series for selected locations. Imagery is first atmospherically corrected to surface reflectance, and then change detection algorithms are used to extract disturbance area, type, and frequency. Reuse of the MODIS Land processing system (MODAPS) architecture allows rapid throughput of over 2200 MSS, TM, and ETM+ scenes. Initial ("Beta") surface reflectance products are currently available for testing, and initial continental disturbance products will be available by the middle of 2006.

Biomass Burning Aerosol Absorption Measurements with MODIS Using the Critical Reflectance Method

NASA Technical Reports Server (NTRS)

Zhu, Li; Martins, Vanderlei J.; Remer, Lorraine A.

2010-01-01

This research uses the critical reflectance technique, a space-based remote sensing method, to measure the spatial distribution of aerosol absorption properties over land. Choosing two regions dominated by biomass burning aerosols, a series of sensitivity studies were undertaken to analyze the potential limitations of this method for the type of aerosol to be encountered in the selected study areas, and to show that the retrieved results are relatively insensitive to uncertainties in the assumptions used in the retrieval of smoke aerosol. The critical reflectance technique is then applied to Moderate Resolution Imaging Spectrometer (MODIS) data to retrieve the spectral aerosol single scattering albedo (SSA) in South African and South American 35 biomass burning events. The retrieved results were validated with collocated Aerosol Robotic Network (AERONET) retrievals. One standard deviation of mean MODIS retrievals match AERONET products to within 0.03, the magnitude of the AERONET uncertainty. The overlap of the two retrievals increases to 88%, allowing for measurement variance in the MODIS retrievals as well. The ensemble average of MODIS-derived SSA for the Amazon forest station is 0.92 at 670 nm, and 0.84-0.89 for the southern African savanna stations. The critical reflectance technique allows evaluation of the spatial variability of SSA, and shows that SSA in South America exhibits higher spatial variation than in South Africa. The accuracy of the retrieved aerosol SSA from MODIS data indicates that this product can help to better understand 44 how aerosols affect the regional and global climate.

Regional Mapping of Coupled Fluxes of Carbon and Water Using Multi-Sensor Fusion Techniques

NASA Astrophysics Data System (ADS)

Schull, M. A.; Anderson, M. C.; Semmens, K. A.; Yang, Y.; Gao, F.; Hain, C.; Houborg, R.

2014-12-01

In an ever-changing climate there is an increasing need to measure the fluxes of water, energy and carbon for decision makers to implement policies that will help mitigate the effects of climate change. In an effort to improve drought monitoring, water resource management and agriculture assessment capabilities, a multi-scale and multi-sensor framework for routine mapping of land-surface fluxes of water and energy at field to regional scales has been established. The framework uses the ALEXI (Atmosphere Land Exchange Inverse)/DisALEXI (Disaggregated ALEXI) suite of land-surface models forced by remotely sensed data from Landsat, MODIS (MODerate resolution Imaging Spectroradiometer), and GOES (Geostationary Operational Environmental Satellite). Land-surface temperature (LST) can be an effective substitute for in-situ surface moisture observations and a valuable metric for constraining land-surface fluxes at sub-field scales. The adopted multi-scale thermal-based land surface modeling framework facilitates regional to local downscaling of water and energy fluxes by using a combination of shortwave reflective and thermal infrared (TIR) imagery from GOES (4-10 km; hourly), MODIS (1 km; daily), and Landsat (30-100 m; bi-weekly). In this research the ALEXI/DisALEXI modeling suite is modified to incorporate carbon fluxes using a stomatal resistance module, which replaces the Priestley-Taylor latent heat approximation. In the module, canopy level nominal light-use-efficiency (βn) is the parameter that modulates the flux of water and carbon in and out of the canopy. Leaf chlorophyll (Chl) is a key parameter for quantifying variability in photosynthetic efficiency to facilitate the spatial distribution of coupled carbon and water retrievals. Spatial distribution of Chl are retrieved from Landsat (30 m) using a surface reflectance dataset as input to the REGularized canopy reFLECtance (REGFLEC) tool. The modified ALEXI/DisALEXI suite is applied to regions of rain fed and irrigated soybean and maize agricultural landscapes within the continental U.S. and flux estimates are compared with flux tower observations.

NASA Blue Marble 2007 West

NASA Image and Video Library

2010-03-12

RELEASE DATE: OCTOBER 9, 2007 Credit: NASA/Goddard Space Flight Center/Reto Stöckli A day’s clouds. The shape and texture of the land. The living ocean. City lights as a beacon of human presence across the globe. This amazingly beautiful view of Earth from space is a fusion of science and art, a showcase for the remote-sensing technology that makes such views possible, and a testament to the passion and creativity of the scientists who devote their careers to understanding how land, ocean, and atmosphere—even life itself—interact to generate Earth’s unique (as far as we know!) life-sustaining environment. Drawing on data from multiple satellite missions (not all collected at the same time), a team of NASA scientists and graphic artists created layers of global data for everything from the land surface, to polar sea ice, to the light reflected by the chlorophyll in the billions of microscopic plants that grow in the ocean. They wrapped these layers around a globe, set it against a black background, and simulated the hazy edge of the Earth’s atmosphere (the limb) that appears in astronaut photography of the Earth. The land surface layer is based on photo-like surface reflectance observations (reflected sunlight) measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite in July 2004. The sea ice layer near the poles comes from Terra MODIS observations of daytime sea ice observed between August 28 and September 6, 2001. The ocean layer is a composite. In shallow water areas, the layer shows surface reflectances observed by Terra MODIS in July 2004. In the open ocean, the photo-like layer is overlaid with observations of the average ocean chlorophyll content for 2004. NASA’s Aqua MODIS collected the chlorophyll data. The cloud layer shows a single-day snapshot of clouds observed by Terra MODIS across the planet on July 29, 2001. City lights on Earth’s night side are visualized from data collected by the Defense Meteorological Satellite Program mission between 1994–1995. The topography layer is based on radar data collected by the Space Shuttle Endeavour during an 11-day mission in February of 2000. Topography over Antarctica comes from the Radarsat Antarctic Mapping Project, version 2. Most of the data layers in this visualization are available as monthly composites as part of NASA’s Blue Marble Next Generation image collection. The images in the collection appear in cylindrical projection (rectangular maps), and they are available at 500-meter resolution. The large images provided above are the full-size versions of these globes. In their hope that these images will inspire people to appreciate the beauty of our home planet and to learn about the Earth system, the developers of these images encourage readers to re-use and re-publish the images freely. NASA images by Reto Stöckli, based on data from NASA and NOAA. To learn the history of the Blue Marble go here: earthobservatory.nasa.gov/Features/BlueMarble/BlueMarble_... To learn more about the Blue Marble go here: earthobservatory.nasa.gov/IOTD/view.php?id=8108 NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe. Follow us on Twitter Join us on Facebook

Evaluation of MODIS columnar aerosol retrievals using AERONET in semi-arid Nevada and California, U.S.A., during the summer of 2012

NASA Astrophysics Data System (ADS)

Loría-Salazar, S. Marcela; Holmes, Heather A.; Patrick Arnott, W.; Barnard, James C.; Moosmüller, Hans

2016-11-01

Satellite characterization of local aerosol pollution is desirable because of the potential for broad spatial coverage, enabling transport studies of pollution from major sources, such as biomass burning events. However, retrieval of quantitative measures of air pollution such as Aerosol Optical Depth (AOD) from satellite measurements is challenging over land because the underlying surface albedo may be heterogeneous in space and time. Ground-based sunphotometer measurements of AOD are unaffected by surface albedo and are crucial in enabling evaluation, testing, and further development of satellite instruments and retrieval algorithms. Columnar aerosol optical properties from ground-based sunphotometers (Cimel CE-318) as part of AERONET and MODIS aerosol retrievals from Aqua and Terra satellites were compared over semi-arid California and Nevada during the summer season of 2012. Sunphotometer measurements were used as a 'ground truth' to evaluate the current state of satellite retrievals in this spatiotemporal domain. Satellite retrieved (MODIS Collection 6) AOD showed the presence of wildfires in northern California during August. During the study period, the dark-target (DT) retrieval algorithm appears to overestimate AERONET AOD by an average factor of 3.85 in the entire study domain. AOD from the deep-blue (DB) algorithm overestimates AERONET AOD by an average factor of 1.64. Low AOD correlation was also found between AERONET, DT, and DB retrievals. Smoke from fires strengthened the aerosol signal, but MODIS versus AERONET AOD correlation hardly increased during fire events (r2∼0.1-0.2 during non-fire periods and r2∼0-0.31 during fire periods). Furthermore, aerosol from fires increased the normalized mean bias (NMB) of MODIS retrievals of AOD (NMB∼23%-154% for non-fire periods and NMB∼77%-196% for fire periods). Ångström Extinction Exponent (AEE) from DB for both Terra and Aqua did not correlate with AERONET observations. High surface reflectance and incorrect aerosol physical parametrizations may still be affecting the DT and DB MODIS AOD retrievals in the semi-arid western U.S.

Testing the Two-Layer Model for Correcting Clear Sky Reflectance near Clouds

NASA Technical Reports Server (NTRS)

Wen, Guoyong; Marshak, Alexander; Evans, Frank; Varnai, Tamas; Levy, Rob

2015-01-01

A two-layer model (2LM) was developed in our earlier studies to estimate the clear sky reflectance enhancement due to cloud-molecular radiative interaction at MODIS at 0.47 micrometers. Recently, we extended the model to include cloud-surface and cloud-aerosol radiative interactions. We use the LES/SHDOM simulated 3D true radiation fields to test the 2LM for reflectance enhancement at 0.47 micrometers. We find: The simple model captures the viewing angle dependence of the reflectance enhancement near cloud, suggesting the physics of this model is correct; the cloud-molecular interaction alone accounts for 70 percent of the enhancement; the cloud-surface interaction accounts for 16 percent of the enhancement; the cloud-aerosol interaction accounts for an additional 13 percent of the enhancement. We conclude that the 2LM is simple to apply and unbiased.

A Geostatistical Data Fusion Technique for Merging Remote Sensing and Ground-Based Observations of Aerosol Optical Thickness

NASA Technical Reports Server (NTRS)

Chatterjee, Abhishek; Michalak, Anna M.; Kahn, Ralph A.; Paradise, Susan R.; Braverman, Amy J.; Miller, Charles E.

2010-01-01

Particles in the atmosphere reflect incoming sunlight, tending to cool the Earth below. Some particles, such as soot, also absorb sunlight, which tens to warm the ambient atmosphere. Aerosol optical depth (AOD) is a measure of the amount of particulate matter in the atmosphere, and is a key input to computer models that simulate and predict Earth's changing climate. The global AOD products from the Multi-angle Imaging SpectroRadiometer (MISR) and the MODerate resolution Imaging Spectroradiometer (MODIS), both of which fly on the NASA Earth Observing System's Terra satellite, provide complementary views of the particles in the atmosphere. Whereas MODIS offers global coverage about four times as frequent as MISR, the multi-angle data makes it possible to separate the surface and atmospheric contributions to the observed top-of-atmosphere radiances, and also to more effectively discriminate particle type. Surface-based AERONET sun photometers retrieve AOD with smaller uncertainties than the satellite instruments, but only at a few fixed locations. So there are clear reasons to combine these data sets in a way that takes advantage of their respective strengths. This paper represents an effort at combining MISR, MODIS and AERONET AOD products over the continental US, using a common spatial statistical technique called kriging. The technique uses the correlation between the satellite data and the "ground-truth" sun photometer observations to assign uncertainty to the satellite data on a region-by-region basis. The larger fraction of the sun photometer variance that is duplicated by the satellite data, the higher the confidence assigned to the satellite data in that region. In the Western and Central US, MISR AOD correlation with AERONET are significantly higher than those with MODIS, likely due to bright surfaces in these regions, which pose greater challenges for the single-view MODIS retrievals. In the east, MODIS correlations are higher, due to more frequent sampling of the varying AOD. These results demonstrate how the MISR and MODIS aerosol products are complementary. The underlying technique also provides one method for combining these products in such a way that takes advantage of the strengths of each, in the places and times when they are maximal, and in addition, yields an estimate of the associated uncertainties in space and time.

Assessment of BRDF effect of Kunlun Mountain glacier on Tibetan Plateau as a potential pseudo-invariant calibration site

NASA Astrophysics Data System (ADS)

Wang, Ling; Hu, Xiuqing; Chen, Lin

2017-09-01

Calibration is a critical step to ensure data quality and to meet the requirement of quantitative remote sensing in a broad range of scientific applications. One of the least expensive and increasingly popular methods of on-orbit calibration is the use of pseudo invariant calibration sites (PICS). A spatial homogenous and temporally stable area of 34 km2 in size around the center of Kunlun Mountain (KLM) over Tibetan Plateau (TP) was identified by our previous study. The spatial and temporal coefficient of variation (CV) this region was better than 4% for the reflective solar bands. In this study, the BRDF impacts of KLM glacier on MODIS observed TOA reflectance in band 1 (659 nm) are examined. The BRDF impact of KLM glacier with respect to the view zenith angle is studied through using the observations at a fixed solar zenith angle, and the effect with respect to the sun zenith angle is studied based on the observations collected at the same view angle. Then, the two widely used BRDF models are applied to our test data to simulate the variations of TOA reflectance due to the changes in viewing geometry. The first one is Ross-Li model, which has been used to produce the MODIS global BRDF albedo data product. The second one is snow surface BRDF model, which has been used to characterize the bidirectional reflectance of Antarctic snow. Finally, the accuracy and effectiveness of these two different BRDF models are tested through comparing the model of simulated TOA reflectance with the observed one. The results show that variations of the reflectances at a fixed solar zenith angle are close to the lambertian pattern, while those at a fixed sensor zenith angle are strongly anisotropic. A decrease in solar zenith angle from 50º to 20º causes an increase in reflectance by the level of approximated 50%. The snow surface BRDF model performs much better than the Ross-Li BRDF model to re-produce the Bi-Directional Reflectance of KLM glacier. The RMSE of snow surface BRDF model is 3.60%, which is only half of the RMSE when using Ross-Li model.

Monitoring Phenology as Indicator for Timing of Nutrient Inputs in Northern Gulf Watersheds

DTIC Science & Technology

2010-06-01

region and compared to nutrient monitoring data. A. Image Data This project uses MODIS normalized difference vegetation index ( NDVI ) to create a time...series of land vegetation canopies. MODIS provides a near-daily repeat time for the elimination of cloud contamination, and NDVI has been widely adopted...steps and NDVI was calculated by the defined formula NDVI = (near-infrared reflectance - red reflectance) / (near-infrared reflectance + red

Retrieval of seasonal dynamics of forest understory reflectance over a set of boreal, sub-boreal and temperate forests using MODIS BRDF data

NASA Astrophysics Data System (ADS)

Pisek, J.; Lang, M.; Kuusk, J.; Kobayashi, H.; Suzuki, R.; Rautiainen, M.; Schaepman, M. E.; Nikopensius, M.; Raabe, K.

2013-12-01

Since ground vegetation (understory) has an essential contribution to the whole-stand reflectance signal in many boreal, sub-boreal and temperate forests, its reflectance spectra are urgently needed in various forest reflectance modelling efforts. However, systematic reflectance data covering different site types are almost missing. Measurement of understory reflectance is a real challenge because of extremely high variability of irradiance at the forest floor, weak signal in some parts of the spectrum and its variable nature. Understory consists of several sub-layers (tree regeneration, shrub, grasses or dwarf shrub, mosses or lichens, litter, bare soil), it has spatially-temporally variable species composition and ground coverage. Additional problems are introduced by patchiness of ground vegetation, ground surface roughness and understory-overstory relations. Due to this variability, remote sensing might be the only technology to provide consistent data at the required spatially extensive scales. Here we follow on our previous effort at mapping understory reflectance dynamics using multi-angle remote sensing observations (Pisek et al. (2012). Retrieval of seasonal dynamics of forest understory reflectance in a Northern European boreal forest from MODIS BRDF data. Remote Sensing of Environment, 117, 464-468). This presentation will focus on the validation of this approach against an extended collection of different types of forest sites with available in-situ understory reflectance measurements distributed along a wide latitudinal gradient: a sparse black spruce forest in Alaska (Poker range; 65.12 N), a northern European boreal forest (Hyytiala; 61.85 N), hemiboreal needleleaf and deciduous stands in Estonia (Jarvselja; 58.27 N), a temperate deciduous forest in Switzerland (Laegeren; 47.48 N), and a dense black spruce forest in Canada (Sudbury; 47.16 N). Our results are pertinent to the ultimate goal of production of circumpolar maps of seasonal dynamics of forest understory over boreal forests using the MODIS BRDF data, starting from 2000. This will allow us to assess the changes in seasonal dynamics of boreal forest understory over the full decade.

Sea Ice Surface Temperature Product from the Moderate Resolution Imaging Spectroradiometer (MODIS)

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Key, Jeffrey R.; Casey, Kimberly A.; Riggs, George A.; Cavalieri, Donald J.

2003-01-01

Global sea ice products are produced from the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) on board both the Terra and Aqua satellites. Daily sea ice extent and ice-surface temperature (IST) products are available at 1- and 4-km resolution. Validation activities have been undertaken to assess the accuracy of the MODIS IST product at the South Pole station in Antarctica and in the Arctic Ocean using near-surface air-temperature data from a meteorological station and drifting buoys. Results from the study areas show that under clear skies, the MODIS ISTs are very close to those of the near-surface air temperatures with a bias of -1.1 and -1.2 K, and an uncertainty of 1.6 and 1.7 K, respectively. It is shown that the uncertainties would be reduced if the actual temperature of the ice surface were reported instead of the near-surface air temperature. It is not possible to get an accurate IST from MODIS in the presence of even very thin clouds or fog, however using both the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and the MODIS on the Aqua satellite, it may be possible to develop a relationship between MODIS-derived IST and ice temperature derived from the AMSR-E. Since the AMSR-E measurements are generally unaffected by cloud cover, they may be used to complement the MODIS IST measurements.

Global Agricultural Monitoring (GLAM) using MODAPS and LANCE Data Products

NASA Astrophysics Data System (ADS)

Anyamba, A.; Pak, E. E.; Majedi, A. H.; Small, J. L.; Tucker, C. J.; Reynolds, C. A.; Pinzon, J. E.; Smith, M. M.

2012-12-01

The Global Inventory Modeling and Mapping Studies / Global Agricultural Monitoring (GIMMS GLAM) system is a web-based geographic application that offers Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and user interface tools to data query and plot MODIS NDVI time series. The system processes near real-time and science quality Terra and Aqua MODIS 8-day composited datasets. These datasets are derived from the MOD09 and MYD09 surface reflectance products which are generated and provided by NASA/GSFC Land and Atmosphere Near Real-time Capability for EOS (LANCE) and NASA/GSFC MODIS Adaptive Processing System (MODAPS). The GIMMS GLAM system is developed and provided by the NASA/GSFC GIMMS group for the U.S. Department of Agriculture / Foreign Agricultural Service / International Production Assessment Division (USDA/FAS/IPAD) Global Agricultural Monitoring project (GLAM). The USDA/FAS/IPAD mission is to provide objective, timely, and regular assessment of the global agricultural production outlook and conditions affecting global food security. This system was developed to improve USDA/FAS/IPAD capabilities for making operational quantitative estimates for crop production and yield estimates based on satellite-derived data. The GIMMS GLAM system offers 1) web map imagery including Terra & Aqua MODIS 8-day composited NDVI, NDVI percent anomaly, and SWIR-NIR-Red band combinations, 2) web map overlays including administrative and 0.25 degree Land Information System (LIS) shape boundaries, and crop land cover masks, and 3) user interface tools to select features, data query, plot, and download MODIS NDVI time series.

MSG SEVIRI Applications for Weather and Climate: Cloud Properties and Calibrations

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Nguyen, Louis; Smith, William L.; Palikonda, Rabindra; Doelling, David R.; Ayers, J. Kirk; Trepte, Qing Z.; Chang, Fu-Lung

2006-01-01

SEVIRI data are cross-calibrated against the corresponding Aqua and Terra MODIS channels. Compared to Terra MODIS, no significant trends are evident in the 0.65, 0.86, and 1.6 micron channel gains between May 2004 and May 2006, indicating excellent stability in the solar-channel sensors. On average, the corresponding Terra reflectances are 12, 14, and 1% greater than the their SEVIRI counterparts. The Terra 3.8- micron channel brightness temperatures T are 7 and 4 K greater than their SEVIRI counterparts during day and night, respectively. The average differences between T for MODIS and SEVIRI 8.6, 10.8, 12.0, and 13.3- micron channels are between 0.5 and 2 K. The cloud properties are being derived hourly over Europe and, in initial comparisons, agree well with surface observations. Errors caused by residual calibration uncertainties, terminator conditions, and inaccurate temperature and humidity profiles are still problematic. Future versions will address those errors and the effects of multilayered clouds.

Estimation of land photosynthetically active radiation in clear sky using MODIS atmosphere and land products

NASA Astrophysics Data System (ADS)

Xie, Xiaoping; Gao, Wei; Gao, Zhiqiang

2008-08-01

Photosynthetically active radiation (PAR) is an essential parameter in vegetation growth model and soil carbon sequestration models. A method is presented with which instantaneous PAR can be calculated with high accuracy from Moderate Resolution Imaging Spectroradiometer (MODIS) atmosphere and land products. The method is based on a simplification of the general radiative transfer equation, which considers five major processes of attenuation of solar radiation: Rayleigh scattering, absorption by ozone and water vapor, aerosol scattering, multiply reflectance between surface and atmosphere. Comparing 108 retrieveled results to filed measured PAR in Yucheng station of Chinese Ecosystem Research Network (CERN) in 2006, and the r-square of 0.855 indicates that the computed results can interpret actual PAR well.

Global, long-term Earth Science Data Records of forest cover, change, and fragmentation from Landsat: the Global Forest Cover Change Project

NASA Astrophysics Data System (ADS)

Sexton, J.; Huang, C.; Channan, S.; Feng, M.; Song, X.; Kim, D.; Song, D.; Vermote, E.; Masek, J.; Townshend, J. R.

2013-12-01

Monitoring, analysis, and management of forests require measurements of forest cover that are both spatio-temporally consistent and resolved globally at sub-hectare resolution. The Global Forest Cover Change project, a cooperation between the University of Maryland Global Land Cover Facility and NASA Goddard Space Flight Center, is providing the first long-term, sub-hectare, globally consistent data records of forest cover, change, and fragmentation in circa-1975, -1990, -2000, and -2005 epochs. These data are derived from the Global Land Survey collection of Landsat images in the respective epochs, atmospherically corrected to surface reflectance in 1990, 2000, and 2005 using the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) implementation of the 6S radiative transfer algorithm, with ancillary information from MODIS Land products, ASTER Global Digital Elevation Model (GDEM), and climatological data layers. Forest cover and change were estimated by a novel continuous-field approach, which produced for the 2000 and 2005 epochs the world's first global, 30-m resolution database of tree cover. Surface reflectance estimates were validated against coincident MODIS measurements, the results of which have been corroborated by subsequent, independent validations against measurements from AERONET sites. Uncertainties in tree- and forest-cover values were estimated in each pixel as a compounding of within-sample uncertainty and accuracy relative to a sample of independent measurements from small-footprint lidar. Accuracy of forest cover and change estimates was further validated relative to expert-interpreted high-resolution imagery, from which unbiased estimates of forest cover and change have been produced at national and eco-regional scales. These first-of-kind Earth Science Data Records--surface reflectance in 1990, 2000, and 2005 and forest cover, change, and fragmentation in and between 1975, 1990, 2000, and 2005--are hosted at native, Landsat resolution for free public access at the Global Land Cover Facility website (www.landcover.org). Global mosaic of circa-2000, Landsat-based estimates of tree cover. Gaps due to clouds and/or snow in each scene were filled first with Landsat-based data from overlapping paths, and the remaining gaps were filled with data from the MODIS VCF Tree Cover layer in 2000.

Using the Moon to Track MODIS Reflective Solar Bands Calibration Stability

NASA Technical Reports Server (NTRS)

Xiong, Xiaoxiong; Geng, Xu; Angal, Amit; Sun, Junqiang; Barnes, William

2011-01-01

MODIS has 20 reflective solar bands (RSB) in the visible (VIS), near infrared (NIR), and short-wave infrared (SWIR) spectral regions. In addition to instrument on-board calibrators (OBC), lunar observations have been used by both Terra and Aqua MODIS to track their reflective solar bands (RSB) on-orbit calibration stability. On a near monthly basis, lunar observations are scheduled and implemented for each instrument at nearly the same lunar phase angles. A time series of normalized detector responses to the Moon is used to monitor its on-orbit calibration stability. The normalization is applied to correct the differences of lunar viewing geometries and the Sun-Moon-Sensor distances among different lunar observations. Initially, the lunar calibration stability monitoring was only applied to MODIS bands (1-4 and 8-12) that do not saturate while viewing the Moon. As the mission continued, we extended the lunar calibration stability monitoring to other RSB bands (bands 13-16) that contain saturated pixels. For these bands, the calibration stability is monitored by referencing their non-saturated pixels to the matched pixels in a non-saturation band. In this paper, we describe this relative approach and apply it to MODIS regularly scheduled lunar observations. We present lunar trending results for both Terra and Aqua MODIS over their entire missions. Also discussed in the paper are the advantages and limitations of this approach and its potential applications to other earth-observing sensors. Keywords: Terra, Aqua, MODIS, sensor, Moon, calibration, stability

Method for validating cloud mask obtained from satellite measurements using ground-based sky camera.

PubMed

Letu, Husi; Nagao, Takashi M; Nakajima, Takashi Y; Matsumae, Yoshiaki

2014-11-01

Error propagation in Earth's atmospheric, oceanic, and land surface parameters of the satellite products caused by misclassification of the cloud mask is a critical issue for improving the accuracy of satellite products. Thus, characterizing the accuracy of the cloud mask is important for investigating the influence of the cloud mask on satellite products. In this study, we proposed a method for validating multiwavelength satellite data derived cloud masks using ground-based sky camera (GSC) data. First, a cloud cover algorithm for GSC data has been developed using sky index and bright index. Then, Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data derived cloud masks by two cloud-screening algorithms (i.e., MOD35 and CLAUDIA) were validated using the GSC cloud mask. The results indicate that MOD35 is likely to classify ambiguous pixels as "cloudy," whereas CLAUDIA is likely to classify them as "clear." Furthermore, the influence of error propagations caused by misclassification of the MOD35 and CLAUDIA cloud masks on MODIS derived reflectance, brightness temperature, and normalized difference vegetation index (NDVI) in clear and cloudy pixels was investigated using sky camera data. It shows that the influence of the error propagation by the MOD35 cloud mask on the MODIS derived monthly mean reflectance, brightness temperature, and NDVI for clear pixels is significantly smaller than for the CLAUDIA cloud mask; the influence of the error propagation by the CLAUDIA cloud mask on MODIS derived monthly mean cloud products for cloudy pixels is significantly smaller than that by the MOD35 cloud mask.

Remote Sensing of Aerosol using MODIS, MODIS+CALIPSO and with the AEROSAT Concept

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.

2002-01-01

In the talk I shall review the MODIS use of spectral information to derive aerosol size distribution, optical thickness and reflected spectral flux. The accuracy and validation of the MODIS products will be discussed. A few applications will be shown: inversion of combined MODIS+lidar data, aerosol Anthropogenic direct forcing, and dust deposition in the Atlantic Ocean. I shall also discuss the aerosol information that MODIS is measuring: real ref index, single scattering albedo, size of fine and coarse modes, and describe the AEROSAT concept that uses bright desert and glint to derive aerosol absorption.

Land cover change mapping using MODIS time series to improve emissions inventories

NASA Astrophysics Data System (ADS)

López-Saldaña, Gerardo; Quaife, Tristan; Clifford, Debbie

2016-04-01

MELODIES is an FP7 funded project to develop innovative and sustainable services, based upon Open Data, for users in research, government, industry and the general public in a broad range of societal and environmental benefit areas. Understanding and quantifying land surface changes is necessary for estimating greenhouse gas and ammonia emissions, and for meeting air quality limits and targets. More sophisticated inventories methodologies for at least key emission source are needed due to policy-driven air quality directives. Quantifying land cover changes on an annual basis requires greater spatial and temporal disaggregation of input data. The main aim of this study is to develop a methodology for using Earth Observations (EO) to identify annual land surface changes that will improve emissions inventories from agriculture and land use/land use change and forestry (LULUCF) in the UK. First goal is to find the best sets of input features that describe accurately the surface dynamics. In order to identify annual and inter-annual land surface changes, a times series of surface reflectance was used to capture seasonal variability. Daily surface reflectance images from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 500m resolution were used to invert a Bidirectional Reflectance Distribution Function (BRDF) model to create the seamless time series. Given the limited number of cloud-free observations, a BRDF climatology was used to constrain the model inversion and where no high-scientific quality observations were available at all, as a gap filler. The Land Cover Map 2007 (LC2007) produced by the Centre for Ecology & Hydrology (CEH) was used for training and testing purposes. A land cover product was created for 2003 to 2015 and a bayesian approach was created to identified land cover changes. We will present the results of the time series development and the first exercises when creating the land cover and land cover changes products.

Comparing MODIS-Terra and GOES surface albedo for New York City NY, Baltimore MD and Washington DC for 2005

NASA Astrophysics Data System (ADS)

Mubenga, K.; Hoff, R.; McCann, K.; Chu, A.; Prados, A.

2006-05-01

The NOAA GOES Aerosol and Smoke Product (GASP) is a product displaying the Aerosol Optical Depth (AOD) over the United States. The GASP retrieval involves discriminating the upwelling radiance from the atmosphere from that of the variable underlying surface. Unlike other sensors with more visible and near- infrared spectral channels such as MODIS, the sensors on GOES 8 through 12 only have one visible and a several far infrared channels. The GASP algorithm uses the detection of the second-darkest pixel from the visible channel over a 28-day period as the reference from which a radiance look-up table gives the corresponding AOD. GASP is reliable in capturing the AOD during large events. As an example, GASP was able to precisely show the Alaska and British Columbia smoke plume advecting from Alaska to the northeastern U.S. during the summer of 2004. Knapp et al. (2005) has shown that the AOD retrieval for GOES- 8 is within +/-0.13 of AERONET ground data with a coefficient of correlation of 0.72. Prados (this meeting) will update that study. However, GASP may not be as reliable when it comes to observing smaller AOD events in the northeast where the surface brightness is relatively high. The presence of large cities, such as New York, increases the surface albedo and produces a bright background against which it may be difficult to deduce the AOD. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on the Earth Observing System Terra and Aqua platforms provides an independent measurement of the surface albedo at a resolution greater than available on GOES. In this research, the MODIS and GOES surface albedo product for New York, Washington and Baltimore are compared in order to see how we can improve the AOD retrieval in urban areas for air quality applications. Ref: K. Knapp et al. 2005. Toward aerosol optical depth retrievals over land from GOES visible radiances: determining surface reflectance. Int.Journal of Remote Sensing 26, 4097-4116

Quantifying the Uncertainty in High Spatial and Temporal Resolution Synthetic Land Surface Reflectance at Pixel Level Using Ground-Based Measurements

NASA Astrophysics Data System (ADS)

Kong, J.; Ryu, Y.

2017-12-01

Algorithms for fusing high temporal frequency and high spatial resolution satellite images are widely used to develop dense time-series land surface observations. While many studies have revealed that the synthesized frequent high spatial resolution images could be successfully applied in vegetation mapping and monitoring, validation and correction of fused images have not been focused than its importance. To evaluate the precision of fused image in pixel level, in-situ reflectance measurements which could account for the pixel-level heterogeneity are necessary. In this study, the synthetic images of land surface reflectance were predicted by the coarse high-frequency images acquired from MODIS and high spatial resolution images from Landsat-8 OLI using the Flexible Spatiotemporal Data Fusion (FSDAF). Ground-based reflectance was measured by JAZ Spectrometer (Ocean Optics, Dunedin, FL, USA) on rice paddy during five main growth stages in Cheorwon-gun, Republic of Korea, where the landscape heterogeneity changes through the growing season. After analyzing the spatial heterogeneity and seasonal variation of land surface reflectance based on the ground measurements, the uncertainties of the fused images were quantified at pixel level. Finally, this relationship was applied to correct the fused reflectance images and build the seasonal time series of rice paddy surface reflectance. This dataset could be significant for rice planting area extraction, phenological stages detection, and variables estimation.

A Wetness Index Using Terrain-Corrected Surface Temperature and Normalized Difference Vegetation Index Derived from Standard MODIS Products: An Evaluation of Its Use in a Humid Forest-Dominated Region of Eastern Canada

PubMed Central

Hassan, Quazi K.; Bourque, Charles P.-A.; Meng, Fan-Rui; Cox, Roger M.

2007-01-01

In this paper we develop a method to estimate land-surface water content in a mostly forest-dominated (humid) and topographically-varied region of eastern Canada. The approach is centered on a temperature-vegetation wetness index (TVWI) that uses standard 8-day MODIS-based image composites of land surface temperature (TS) and surface reflectance as primary input. In an attempt to improve estimates of TVWI in high elevation areas, terrain-induced variations in TS are removed by applying grid, digital elevation model-based calculations of vertical atmospheric pressure to calculations of surface potential temperature (θS). Here, θS corrects TS to the temperature value to what it would be at mean sea level (i.e., ∼101.3 kPa) in a neutral atmosphere. The vegetation component of the TVWI uses 8-day composites of surface reflectance in the calculation of normalized difference vegetation index (NDVI) values. TVWI and corresponding wet and dry edges are based on an interpretation of scatterplots generated by plotting θS as a function of NDVI. A comparison of spatially-averaged field measurements of volumetric soil water content (VSWC) and TVWI for the 2003-2005 period revealed that variation with time to both was similar in magnitudes. Growing season, point mean measurements of VSWC and TVWI were 31.0% and 28.8% for 2003, 28.6% and 29.4% for 2004, and 40.0% and 38.4% for 2005, respectively. An evaluation of the long-term spatial distribution of land-surface wetness generated with the new θS-NDVI function and a process-based model of soil water content showed a strong relationship (i.e., r2 = 95.7%). PMID:28903212

Assessing snow extent data sets over North America to inform and improve trace gas retrievals from solar backscatter

NASA Astrophysics Data System (ADS)

Cooper, Matthew J.; Martin, Randall V.; Lyapustin, Alexei I.; McLinden, Chris A.

2018-05-01

Accurate representation of surface reflectivity is essential to tropospheric trace gas retrievals from solar backscatter observations. Surface snow cover presents a significant challenge due to its variability and thus snow-covered scenes are often omitted from retrieval data sets; however, the high reflectance of snow is potentially advantageous for trace gas retrievals. We first examine the implications of surface snow on retrievals from the upcoming TEMPO geostationary instrument for North America. We use a radiative transfer model to examine how an increase in surface reflectivity due to snow cover changes the sensitivity of satellite retrievals to NO2 in the lower troposphere. We find that a substantial fraction (> 50 %) of the TEMPO field of regard can be snow covered in January and that the average sensitivity to the tropospheric NO2 column substantially increases (doubles) when the surface is snow covered.We then evaluate seven existing satellite-derived or reanalysis snow extent products against ground station observations over North America to assess their capability of informing surface conditions for TEMPO retrievals. The Interactive Multisensor Snow and Ice Mapping System (IMS) had the best agreement with ground observations (accuracy of 93 %, precision of 87 %, recall of 83 %). Multiangle Implementation of Atmospheric Correction (MAIAC) retrievals of MODIS-observed radiances had high precision (90 % for Aqua and Terra), but underestimated the presence of snow (recall of 74 % for Aqua, 75 % for Terra). MAIAC generally outperforms the standard MODIS products (precision of 51 %, recall of 43 % for Aqua; precision of 69 %, recall of 45 % for Terra). The Near-real-time Ice and Snow Extent (NISE) product had good precision (83 %) but missed a significant number of snow-covered pixels (recall of 45 %). The Canadian Meteorological Centre (CMC) Daily Snow Depth Analysis Data set had strong performance metrics (accuracy of 91 %, precision of 79 %, recall of 82 %). We use the Fscore, which balances precision and recall, to determine overall product performance (F = 85 %, 82 (82) %, 81 %, 58 %, 46 (54) % for IMS, MAIAC Aqua (Terra), CMC, NISE, MODIS Aqua (Terra), respectively) for providing snow cover information for TEMPO retrievals from solar backscatter observations. We find that using IMS to identify snow cover and enable inclusion of snow-covered scenes in clear-sky conditions across North America in January can increase both the number of observations by a factor of 2.1 and the average sensitivity to the tropospheric NO2 column by a factor of 2.7.

Snow cover retrieval over Rhone and Po river basins from MODIS optical satellite data (2000-2009).

NASA Astrophysics Data System (ADS)

Dedieu, Jean-Pierre, ,, Dr.; Boos, Alain; Kiage, Wiliam; Pellegrini, Matteo

2010-05-01

Estimation of the Snow Covered Area (SCA) is an important issue for meteorological application and hydrological modeling of runoff. With spectral bands in the visible, near and middle infrared, the MODIS optical satellite sensor can be used to detect snow cover because of large differences between reflectance from snow covered and snow free surfaces. At the same time, it allows separation between snow and clouds. Moreover, the sensor provides a daily coverage of large areas (2,500 km range). However, as the pixel size is 500m x 500m, a MODIS pixel may be partially covered by snow, particularly in Alpine areas, where snow may not be present in valleys lying at lower altitudes. Also, variation of reflectance due to differential sunlit effects as a function of slope and aspect, as well as bidirectional effects may be present in images. Nevertheless, it is possible to estimate snow cover at the Sub-Pixel level with a relatively good accuracy and with very good results if the sub-pixel estimations are integrated for a few pixels relative to an entire watershed. Integrated into the EU-FP7 ACQWA Project (www.acqwa.ch), this approach was first applied over Alpine area of Rhone river basin upper Geneva Lake: Canton du Valais, Switzerland (5 375 km²). In a second step over Alps, rolling hills and plain areas in Po catchment for Val d'Aosta and Piemonte regions, Italy (37 190 km²). Watershed boundaries were provided respectively by GRID (Ch) and ARPA (It) partners. The complete satellite images database was extracted from the U.S. MODIS/NASA website (http://modis.gsfc.nasa.gov/) for MOD09_B1 Reflectance images, and from the MODIS/NSIDC website (http://nsidc.org/index.html) for MOD10_A2 snow cover images. Only the Terra platform was used because images are acquired in the morning and are therefore better correlated with dry snow surface, avoiding cloud coverage of the afternoon (Aqua Platform). The MOD9 Image reflectance and MOD10_A2 products were respectively analyzed to retrieve (i) Fractional Snow cover at sub-pixel scale, and (ii) maximum snow cover. All products were retrieved at 8-days over a complete time period of 10 years (2000-2009), giving 500 images for each river basin. Digital Model Elevation was given by NASA/SRTM database at 90-m resolution and used (i) for illumination versus topography correction on snow cover, (ii) geometric rectification of images. Geographic projection is WGS84, UTM 32. Fractional Snow cover mapping was derived from the NDSI linear regression method (Salomonson et al., 2004). Cloud mask was given by MODIS-NASA library (radiometric threshold) and completed by inverse slope regression to avoid lowlands fog confusing with thin snow cover (Po river basin). Maximum Snow Cover mapping was retrieved from the NSIDC database classification (Hall et al., 2001). Validation step was processed using comparison between MODIS Snow maps outputs and meteorological data provided by network of 87 meteorological stations: temperature, precipitation, snow depth measurement. A 0.92 correlation was observed for snow/non snow cover and can be considered as quite satisfactory, given the radiometric problems encountered in mountainous areas, particularly in snowmelt season. The 10-years time period results indicates a main difference between (i) regular snow accumulation and depletion in Rhone and (ii) the high temporal and spatial variability of snow cover for Po. Then, a high sensitivity to low variation of air temperature, often close to 1° C was observed. This is the case in particular for the beginning and the end of the winter season. The regional snow cover depletion is both influenced by thermal positives anomalies (e.g. 2000 and 2006), and the general trend of rising atmospheric temperatures since the late 1980s, particularly for Po river basin. Results will be combined with two hydrological models: Topkapi and Fest.

Spatially Complete Global Spectral Surface Albedos: Value-Added Datasets Derived from Terra MODIS Land Products

NASA Technical Reports Server (NTRS)

Moody, Eric G.; King, Michael D.; Platnick, Steven; Schaaf, Crystal B.; Gao, Feng

2004-01-01

Land surface albedo is an important parameter in describing the radiative properties of the earth s surface as it represents the amount of incoming solar radiation that is reflected from the surface. The amount and type of vegetation of the surface dramatically alters the amount of radiation that is reflected; for example, croplands that contain leafy vegetation will reflect radiation very differently than blacktop associated with urban areas. In addition, since vegetation goes through a growth, or phenological, cycle, the amount of radiation that is reflected changes over the course of a year. As a result, albedo is both temporally and spatially dependant upon global location as there is a distribution of vegetated surface types and growing conditions. Land surface albedo is critical for a wide variety of earth system research projects including but not restricted to remote sensing of atmospheric aerosol and cloud properties from space, ground-based analysis of aerosol optical properties from surface-based sun/sky radiometers, biophysically-based land surface modeling of the exchange of energy, water, momentum, and carbon for various land use categories, and surface energy balance studies. These projects require proper representation of the surface albedo s spatial, spectral, and temporal variations, however, these representations are often lacking in datasets prior to the latest generation of land surface albedo products.

Computational Short-cutting the Big Data Classification Bottleneck: Using the MODIS Land Cover Product to Derive a Consistent 30 m Landsat Land Cover Product of the Conterminous United States

NASA Astrophysics Data System (ADS)

Zhang, H.; Roy, D. P.

2016-12-01

Classification is a fundamental process in remote sensing used to relate pixel values to land cover classes present on the surface. The state of the practice for large area land cover classification is to classify satellite time series metrics with a supervised (i.e., training data dependent) non-parametric classifier. Classification accuracy generally increases with training set size. However, training data collection is expensive and the optimal training distribution over large areas is unknown. The MODIS 500 m land cover product is available globally on an annual basis and so provides a potentially very large source of land cover training data. A novel methodology to classify large volume Landsat data using high quality training data derived automatically from the MODIS land cover product is demonstrated for all of the Conterminous United States (CONUS). The known misclassification accuracy of the MODIS land cover product and the scale difference between the 500 m MODIS and 30 m Landsat data are accommodated for by a novel MODIS product filtering, Landsat pixel selection, and iterative training approach to balance the proportion of local and CONUS training data used. Three years of global Web-enabled Landsat data (WELD) data for all of the CONUS are classified using a random forest classifier and the results assessed using random forest `out-of-bag' training samples. The global WELD data are corrected to surface nadir BRDF-Adjusted Reflectance and are defined in 158 × 158 km tiles in the same projection and nested to the MODIS land cover products. This reduces the need to pre-process the considerable Landsat data volume (more than 14,000 Landsat 5 and 7 scenes per year over the CONUS covering 11,000 million 30 m pixels). The methodology is implemented in a parallel manner on WELD tile by tile basis but provides a wall-to-wall seamless 30 m land cover product. Detailed tile and CONUS results are presented and the potential for global production using the recently available global WELD products are discussed.

Cross-calibration of A.M. constellation sensors for long term monitoring of land surface processes

USGS Publications Warehouse

Meyer, D.; Chander, G.

2006-01-01

Data from multiple sensors must be used together to gain a more complete understanding of land surface processes at a variety of scales. Although higher-level products derived from different sensors (e.g., vegetation cover, albedo, surface temperature) can be validated independently, the degree to which these sensors and their products can be compared to one another is vastly improved if their relative spectro-radiometric responses are known. Most often, sensors are directly calibrated to diffuse solar irradiation or vicariously to ground targets. However, space-based targets are not traceable to metrological standards, and vicarious calibrations are expensive and provide a poor sampling of a sensor's full dynamic range. Cross-calibration of two sensors can augment these methods if certain conditions can be met: (1) the spectral responses are similar, (2) the observations are reasonably concurrent (similar atmospheric & solar illumination conditions), (3) errors due to misregistrations of inhomogeneous surfaces can be minimized (including scale differences), and (4) the viewing geometry is similar (or, some reasonable knowledge of surface bi-directional reflectance distribution functions is available). This study extends on a previous study of Terra/MODIS and Landsat/ETM+ cross calibration by including the Terra/ASTER and EO-1/ALI sensors, exploring the impacts of cross-calibrating sensors when conditions described above are met to some degree but not perfectly. Measures for spectral response differences and methods for cross calibrating such sensors are provided in this study. These instruments are cross calibrated using the Railroad Valley playa in Nevada. Best fit linear coefficients (slope and offset) are provided for ALI-to-MODIS and ETM+-to-MODIS cross calibrations, and root-mean-squared errors (RMSEs) and correlation coefficients are provided to quantify the uncertainty in these relationships. Due to problems with direct calibration of ASTER data, linear fits were developed between ASTER and ETM+ to assess the impacts of spectral bandpass differences between the two systems. In theory, the linear fits and uncertainties can be used to compare radiance and reflectance products derived from each instrument.

Analysis of Summer 2002 Melt Extent on the Greenland Ice Sheet using MODIS and SSM/I Data

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Williams, Richard S., Jr.; Steffen, Konrad; Chien, Y. L.; Foster, James L.; Robinson, David A.; Riggs, George A.

2004-01-01

Previous work has shown that the summer of 2002 had the greatest area of snow melt extent on the Greenland ice sheet ever recorded using passive-microwave data. In this paper, we compare the 0 degree isotherm derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, with Special Sensor Microwave/Imager (SSM/I)-derived melt, at the time of the maximum melt extent in 2002. To validate the MODIS-derived land-surface temperatures (LSTs), we compared the MODIS LSTs with air temperatures from nine stations (using 11 different data points) and found that they agreed to within 2.3 plus or minus 2.09 C, with station temperatures consistently lower than the MODIS LSTs. According to the MODIS LST, the maximum surface melt extended to approximately 2300 m in southern Greenland; while the SSM/I measurements showed that the maximum melt extended to nearly 2700 m in southeastern Greenland. The MODIS and SSM/I data are complementary in providing detailed information about the progression of surface and near-surface melt on the Greenland ice sheet.

Analysis of Summer 2002 Melt Extent on the Greenland Ice Sheet using MODIS and SSM/I Data

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Williams, Richard S.; Steffen, Konrad; Chien, Janet Y. L.

2004-01-01

Previous work has shown that the summer of 2002 had the greatest area of snow melt extent on the Greenland ice sheet ever recorded using passive-microwave data. In this paper, we compare the 0 deg. isotherm derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, with Special Sensor Microwave/Imager (SSM/I)-derived melt, at the time of the maximum melt extent in 2002. To validate the MODIS derived land-surface temperatures (LSTs), we compared the MODIS LSTs with air temperatures from nine stations (using 11 different data points) and found that they agreed to within 2.3 +/- 2.09 C, with station temperatures consistently lower than the MODIS LSTs. According to the MODIS LST, the maximum surface melt extended to approx. 2300 m in southern Greenland; while the SSM/I measurements showed that the maximum melt extended to nearly 2700 m in southeastern Greenland. The MODIS and SSM/I data are complementary in providing detailed information about the progression of surface and near- surface melt on the Greenland ice sheet.

Analysis of summer 2002 melt extent on the Greenland ice sheet using MODIS and SSM/I data

USGS Publications Warehouse

Hall, D.K.; Williams, R.S.; Steffen, K.; Chien, Janet Y.L.

2004-01-01

Previous work has shown that the summer of 2002 had the greatest area of snow melt extent on the Greenland ice sheet ever recorded using passive-microwave data. In this paper, we compare the 0?? isotherm derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, with Special Sensor Microwave/Imager (SSM/I)-derived melt, at the time of the maximum melt extent in 2002. To validate the MODIS-derived land-surface temperatures (LSTs), we compared the MODIS LSTs with air temperatures from nine stations (using 11 different data points) and found that they agreed to within 2.3??2.09??C, with station temperatures consistently lower than the MODIS LSTs. According to the MODIS LST, the maximum surface melt extended to ???2300 m in southern Greenland; while the SSM/I measurements showed that the maximum melt extended to nearly 2700 m in southeastern Greenland. The MODIS and SSM/I data are complementary in providing detailed information about the progression of surface and near-surface melt on the Greenland ice sheet.

Analysis of summer 2002 melt extent on the Greenland ice sheet using MODIS and SSM/I data

USGS Publications Warehouse

Hall, D. K.; Williams, R.S.; Steffen, K.; Chien, Janet Y.L.

2004-01-01

Previous work has shown that the summer of 2002 had the greatest area of snow melt extent on the Greenland ice sheet ever recorded using passive-microwave data. In this paper, we compare the 0deg isotherm derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument, with Special Sensor Microwave/Imager (SSM/I)-derived melt, at the time of the maximum melt extent in 2002. To validate the MODIS-derived land-surface temperatures (LSTs), we compared the MODIS LSTs with air temperatures from nine stations (using 11 different data points) and found that they agreed to within 2.3 plusmn 2.09 degC, with station temperatures consistently lower than the MODIS LSTs. According to the MODIS LST, the maximum surface melt extended to ~2300 m in southern Greenland; while the SSM/I measurements showed that the maximum melt extended to nearly 2700 m in southeastern Greenland. The MODIS and SSM/I data are complementary in providing detailed information about the progression of surface and near-surface melt on the Greenland ice sheet.

Evaluation of Surface and Near-Surface Melt Characteristics on the Greenland Ice Sheet using MODIS and QuikSCAT Data

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Nghiem, Son V.; Schaaf, Crystal B.; DiGirolamo, Nicolo E.

2009-01-01

The Greenland Ice Sheet has been the focus of much attention recently because of increasing melt in response to regional climate warming. To improve our ability to measure surface melt, we use remote-sensing data products to study surface and near-surface melt characteristics of the Greenland Ice Sheet for the 2007 melt season when record melt extent and runoff occurred. Moderate Resolution Imaging Spectroradiometer (MODIS) daily land-surface temperature (LST), MODIS daily snow albedo, and a special diurnal melt product derived from QuikSCAT (QS) scatterometer data, are all effective in measuring the evolution of melt on the ice sheet. These daily products, produced from different parts of the electromagnetic spectrum, are sensitive to different geophysical features, though QS- and MODIS-derived melt generally show excellent correspondence when surface melt is present on the ice sheet. Values derived from the daily MODIS snow albedo product drop in response to melt, and change with apparent grain-size changes. For the 2007 melt season, the QS and MODIS LST products detect 862,769 square kilometers and 766,184 square kilometers of melt, respectively. The QS product detects about 11% greater melt extent than is detected by the MODIS LST product probably because QS is more sensitive to surface melt, and can detect subsurface melt. The consistency of the response of the different products demonstrates unequivocally that physically-meaningful melt/freeze boundaries can be detected. We have demonstrated that these products, used together, can improve the precision in mapping surface and near-surface melt extent on the Greenland Ice Sheet.

Correcting for trace gas absorption when retrieving aerosol optical depth from satellite observations of reflected shortwave radiation

NASA Astrophysics Data System (ADS)

Patadia, Falguni; Levy, Robert C.; Mattoo, Shana

2018-06-01

Retrieving aerosol optical depth (AOD) from top-of-atmosphere (TOA) satellite-measured radiance requires separating the aerosol signal from the total observed signal. Total TOA radiance includes signal from the underlying surface and from atmospheric constituents such as aerosols, clouds and gases. Multispectral retrieval algorithms, such as the dark-target (DT) algorithm that operates upon the Moderate Resolution Imaging Spectroradiometer (MODIS, on board Terra and Aqua satellites) and Visible Infrared Imaging Radiometer Suite (VIIRS, on board Suomi-NPP) sensors, use wavelength bands in window regions. However, while small, the gas absorptions in these bands are non-negligible and require correction. In this paper, we use the High-resolution TRANsmission (HITRAN) database and Line-By-Line Radiative Transfer Model (LBLRTM) to derive consistent gas corrections for both MODIS and VIIRS wavelength bands. Absorptions from H2O, CO2 and O3 are considered, as well as other trace gases. Even though MODIS and VIIRS bands are similar, they are different enough that applying MODIS-specific gas corrections to VIIRS observations results in an underestimate of global mean AOD (by 0.01), but with much larger regional AOD biases of up to 0.07. As recent studies have been attempting to create a long-term data record by joining multiple satellite data sets, including MODIS and VIIRS, the consistency of gas correction has become even more crucial.

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

NASA Technical Reports Server (NTRS)

King, Michael D.; Moody, Eric G.; Schaaf, Crystal B.; Platnick, Steven

2006-01-01

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. , Over five years of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA s Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface s radiative characteristics. However, roughly 30% of the global land surface, on an annual equal-angle basis, is obscured due to persistent and transient cloud cover, while another 207% is obscured due to ephemeral and seasonal snow effects. This precludes the MOD43B3 albedo products from being directly used in some remote sensing and ground-based applications, climate models, and global change research projects. To provide researchers with the requisite spatially complete global snow-free land surface albedo dataset, an ecosystem-dependent temporal interpolation technique was developed to fill missing or lower quality data and snow covered values from the official MOD43B3 dataset with geophysically realistic values. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the MODIS MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data.

Enhanced clear sky reflectance near clouds: What can be learned from it about aerosol properties?

NASA Astrophysics Data System (ADS)

Marshak, A.; Varnai, T.; Wen, G.; Chiu, J.

2009-12-01

Studies on aerosol direct and indirect effects require a precise separation of cloud-free and cloudy air. However, separation between cloud-free and cloudy areas from remotely-sensed measurements is ambiguous. The transition zone in the regions around clouds often stretches out tens of km, which are neither precisely clear nor precisely cloudy. We study the transition zone between cloud-free and cloudy air using MODerate-resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements. Both instruments show enhanced clear-sky reflectance (MODIS) and clear-sky backscatterer (CALIPSO) near clouds. Analyzing a large dataset of MODIS observations, we examine the effect of three-dimensional radiative interactions between clouds and cloud-free areas, also known as a cloud adjacency effect. The cloud adjacency effect is well observed in MODIS clear-sky data in the vicinity of clouds. Comparing with CALIPSO clear-sky backscatterer measurements, we show that this effect may be responsible for a large portion of the enhanced clear-sky reflectance observed by MODIS. Finally, we describe a simple model that estimates the cloud-induced enhanced reflectances of cloud-free areas in the vicinity of clouds. The model assumes that the enhancement is due entirely to Rayleigh scattering and is therefore bigger at shorter wavelengths, thus creating a so-called apparent “bluing” of aerosols in remote sensing retrievals.

On-Orbit Performance and Calibration Improvements For the Reflective Solar Bands of Terra and Aqua MODIS

NASA Technical Reports Server (NTRS)

Angal, Amit; Xiong, Xiaoxiong; Wu, Aisheng; Chen, Hongda; Geng, Xu; Link, Daniel; Li, Yonghong; Wald, Andrew; Brinkmann, Jake

2016-01-01

Moderate Resolution Imaging Spectroradiometer (MODIS) is the keystone instrument for NASAs EOS Terra and Aqua missions, designed to extend and improve heritage sensor measurements and data records of the land, oceans and atmosphere. The reflective solar bands (RSB) of MODIS covering wavelengths from 0.41 micrometers to 2.2 micrometers, are calibrated on-orbit using a solar diffuser (SD), with its on-orbit bi-directional reflectance factor (BRF) changes tracked using a solar diffuser stability monitor (SDSM). MODIS is a scanning radiometer using a two-sided paddle-wheel mirror to collect earth view (EV) data over a range of (+/-)55 deg. off instrument nadir. In addition to the solar calibration provided by the SD and SDSM system, lunar observations at nearly constant phase angles are regularly scheduled to monitor the RSB calibration stability. For both Terra and Aqua MODIS, the SD and lunar observations are used together to track the on-orbit changes of RSB response versus scan angle (RVS) as the SD and SV port are viewed at different angles of incidence (AOI) on the scan mirror. The MODIS Level 1B (L1B) Collection 6 (C6) algorithm incorporated several enhancements over its predecessor Collection 5 (C5) algorithm. A notable improvement was the use of the earth-view (EV) response trends from pseudo-invariant desert targets to characterize the on-orbit RVS for select RSB (Terra bands 1-4, 8, 9 and Aqua bands 8, 9) and the time, AOI, and wavelength-dependent uncertainty. The MODIS Characterization Support Team (MCST) has been maintaining and enhancing the C6 algorithm since its first update in November, 2011 for Aqua MODIS, and February, 2012 for Terra MODIS. Several calibration improvements have been incorporated that include extending the EV-based RVS approach to other RSB, additional correction for SD degradation at SWIR wavelengths, and alternative approaches for on-orbit RVS characterization. In addition to the on-orbit performance of the MODIS RSB, this paper also discusses in detail the recent calibration improvements implemented in the MODIS L1B C6.

What is the Uncertainty in MODIS Aerosol Optical Depth in the Vicinity of Clouds?

NASA Technical Reports Server (NTRS)

Patadia, Falguni; Levy, Rob; Mattoo, Shana

2017-01-01

MODIS dark-target (DT) algorithm retrieves aerosol optical depth (AOD) using a Look Up Table (LUT) approach. Global comparison of AOD (Collection 6 ) with ground-based sun photometer gives an Estimated Error (EE) of +/-(0.04 + 10%) over ocean. However, EE does not represent per-retrieval uncertainty. For retrievals that are biased high compared to AERONET, here we aim to closely examine the contribution of biases due to presence of clouds and per-pixel retrieval uncertainty. We have characterized AOD uncertainty at 550 nm, due to standard deviation of reflectance in 10 km retrieval region, uncertainty related to gas (H2O, O3) absorption, surface albedo, and aerosol models. The uncertainty in retrieved AOD seems to lie within the estimated over ocean error envelope of +/-(0.03+10%). Regions between broken clouds tend to have higher uncertainty. Compared to C6 AOD, a retrieval omitting observations in the vicinity of clouds (< or = 1 km) is biased by about +/- 0.05. For homogeneous aerosol distribution, clear sky retrievals show near zero bias. Close look at per-pixel reflectance histograms suggests retrieval possibility using median reflectance values.

Abstract Art or Arbiters of Energy?

NASA Technical Reports Server (NTRS)

2002-01-01

More than just the idle stuff of daydreams, clouds help control the flow of radiant energy around our world. Clouds are plentiful and widespread throughout Earth's atmosphere-covering up to 75 percent of our planet at any given time-so they play a dominant role in determining how much sunlight reaches the surface, how much sunlight is reflected back into space, how and where warmth is spread around the globe, and how much heat escapes from the surface and atmosphere back into space. Clouds are also highly variable. Clouds' myriad variations through time and space make them one of the greatest areas of uncertainty in scientists' understanding and predictions of climate change. In short, they play a central role in our world's climate system. The false-color image above shows a one-month composite of cloud optical thickness measured by the Moderate-resolution Imaging Spectroradiometer (MODIS) and averaged globally for April 2001. Optical thickness is a measure of how much solar radiation is not allowed to travel through a column of atmosphere. Areas colored red and yellow indicate very cloudy skies, on average, while areas colored green and light blue show moderately cloudy skies. Dark blue regions show where there is little or no cloud cover. This data product is an important new tool for helping scientists understand the roles clouds play in our global climate system. MODIS gives scientists new capabilities for measuring the structure and composition of clouds. MODIS observes the entire Earth almost every day in 36 spectral bands ranging from visible to thermal infrared wavelengths, enabling it to quantify a wide suite of clouds' physical and radiative properties. Specifically, MODIS can determine whether a cloud is composed of ice or water particles (or some combination of the two), it can measure the effective radius of the particles within a cloud, it can determine the temperature and altitude of cloud tops, and it can observe how much sunlight passes through a cloud. MODIS is one of five sensors flying aboard NASA's Terra satellite, the flagship in NASA's Earth Observing System, launched in December 1999. For more information about this and other new MODIS products, read NASA Unveils Spectacular Suite of New Global Data Products from MODIS. Image courtesy MODIS Atmosphere Group, NASA GSFC

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Transport

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; Van de Water, P. K.; Myers, O. B.; Budge, A. M.;

Enhancement of the MODIS Daily Snow Albedo Product

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Schaaf, Crystal B.; Wang, Zhuosen; Riggs, George A.

2009-01-01

The MODIS daily snow albedo product is a data layer in the MOD10A1 snow-cover product that includes snow-covered area and fractional snow cover as well as quality information and other metadata. It was developed to augment the MODIS BRDF/Albedo algorithm (MCD43) that provides 16-day maps of albedo globally at 500-m resolution. But many modelers require daily snow albedo, especially during the snowmelt season when the snow albedo is changing rapidly. Many models have an unrealistic snow albedo feedback in both estimated albedo and change in albedo over the seasonal cycle context, Rapid changes in snow cover extent or brightness challenge the MCD43 algorithm; over a 16-day period, MCD43 determines whether the majority of clear observations was snow-covered or snow-free then only calculates albedo for the majority condition. Thus changes in snow albedo and snow cover are not portrayed accurately during times of rapid change, therefore the current MCD43 product is not ideal for snow work. The MODIS daily snow albedo from the MOD10 product provides more frequent, though less robust maps for pixels defined as "snow" by the MODIS snow-cover algorithm. Though useful, the daily snow albedo product can be improved using a daily version of the MCD43 product as described in this paper. There are important limitations to the MOD10A1 daily snow albedo product, some of which can be mitigated. Utilizing the appropriate per-pixel Bidirectional Reflectance Distribution Functions (BRDFs) can be problematic, and correction for anisotropic scattering must be included. The BRDF describes how the reflectance varies with view and illumination geometry. Also, narrow-to-broadband conversion specific for snow on different surfaces must be calculated and this can be difficult. In consideration of these limitations of MOD10A1, we are planning to improve the daily snow albedo algorithm by coupling the periodic per-pixel snow albedo from MCD43, with daily surface ref|outanoom, In this paper, we compare a daily version of MCD43B3 with the daily albedo from MOD10A1. and MCD43B3 with a 16-day average of MOD10A1, over Greenland. We also discuss some near-future planned enhancements to MOD10A1.

Use Of MODIS Satellite Images And An Atmospheric Dust Transport Model To Evaluate Juniperus Spp. Pollen Phenology And Transport

NASA Astrophysics Data System (ADS)

Luvall, J. C.; Sprigg, W. A.; Levetin, E.; Huete, A. R.; Nickovic, S.; Crimmins, T. M.; Van De Water, P. K.; Pejanovic, G.; Vukovic, A. J.; Myers, O.; Budge, A.; Zelicoff, A.; Bunderson, L.; Ponce-Campos, G.

2011-12-01

Pollen can be transported great distances. Van de Water et al., 2003 reported Juniperus spp. pollen, a significant aeroallergen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. Direct detection of pollen via satellite is not practical. A practical alternative combines modeling and phenological observations using ground based sampling and satellite data. The DREAM (Dust REgional Atmospheric Model) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust (Nickovic et al. 2001). The use of satellite data products for studying phenology is well documented (White and Nemani 2006). In the current project MODIS data will provide critical input to the PREAM model providing pollen source location, timing of pollen release, and vegetation type. We are modifying the DREAM model (PREAM - Pollen REgional Atmospheric Model) to incorporate pollen transport. The linkages already exist with DREAM through PHAiRS (Public Health Applications in Remote Sensing) to the public health community. This linkage has the potential to fill this data gap so that the potential association of health effects of pollen can better be tracked for possible linkage with health outcome data which may be associated with asthma, respiratory effects, myocardial infarction, and lost workdays. Juniperus spp. pollen phenology may respond to a wide range of environmental factors such as day length, growing degree-days, precipitation patterns and soil moisture. Species differences are also important. These environmental factors vary over both time and spatial scales. Ground based networks such as the USA National Phenology Network have been established to provide national wide observations of vegetation phenology. However, the density of observers is not adequate to sufficiently document the phenology variability over large regions. Hence the use of satellite data is critical to observe Juniperus spp. pollen phenology. MODIS data was used to observe Juniperus spp. pollen phenology. The MODIS surface reflectance product(MOD09) provided information on the Juniper spp. cone formation and cone density. Ground based observational records of pollen release timing and quantities were used as verification. Techniques developed using MOD09 surface reflectance products will be directly applicable to the next generation sensors such as VIIRS.

Impact of MODIS SWIR Band Calibration Improvements on Level-3 Atmospheric Products

NASA Technical Reports Server (NTRS)

Wald, Andrew; Levy, Robert; Angal, Amit; Geng, Xu; Xiong, Jack; Hoffman, Kurt

2016-01-01

The spectral reflectance measured by the MODIS reflective solar bands (RSB) is used for retrieving many atmospheric science products. The accuracy of these products depends on the accuracy of the calibration of the RSB. To this end, the RSB of the MODIS instruments are primarily calibrated on-orbit using regular solar diffuser (SD) observations. For lambda < 0.94 microns the SDs on-orbit bi-directional reflectance factor (BRF) change is tracked using solar diffuser stability monitor (SDSM) observations. For lambda > 0.94 microns, the MODIS Characterization Support Team (MCST) developed, in MODIS Collection 6 (C6), a time-dependent correction using observations from pseudo-invariant earth-scene targets. This correction has been implemented in C6 for the Terra MODIS 1.24 micron band over the entire mission, and for the 1.375 micron band in the forward processing. As the instruments continue to operate beyond their design lifetime of six years, a similar correction is planned for other short-wave infrared (SWIR) bands as well. MODIS SWIR bands are used in deriving atmosphere products, including aerosol optical thickness, atmospheric total column water vapor, cloud fraction and cloud optical depth. The SD degradation correction in Terra bands 5 and 26 impact the spectral radiance and therefore the retrieval of these atmosphere products. Here, we describe the corrections to Bands 5 (1.24 microns) and 26 (1.375 microns), and produce three sets (B5, B26 correction on/on, on/off, and off/off) of Terra-MODIS Level 1B (calibrated radiance product) data. By comparing products derived from these corrected and uncorrected Terra MODIS Level 1B (L1B) calibrations, dozens of L3 atmosphere products are surveyed for changes caused by the corrections, and representative results are presented. Aerosol and water vapor products show only small local changes, while some cloud products can change locally by > 10%, which is a large change.

Evaluation of Detector-to-Detector and Mirror Side Differences for Terra MODIS Reflective Solar Bands Using Simultaneous MISR Observations

NASA Technical Reports Server (NTRS)

Wu, Aisheng; Xiong, Xiaoxiong; Angal, A.; Barnes, W.

2011-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the five Earth-observing instruments on-board the National Aeronautics and Space Administration (NASA) Earth-Observing System(EOS) Terra spacecraft, launched in December 1999. It has 36 spectral bands with wavelengths ranging from 0.41 to 14.4 mm and collects data at three nadir spatial resolutions: 0.25 km for 2 bands with 40 detectors each, 0.5 km for 5 bands with 20 detectors each and 1 km for the remaining 29 bands with 10 detectors each. MODIS bands are located on four separate focal plane assemblies (FPAs) according to their spectral wavelengths and aligned in the cross-track direction. Detectors of each spectral band are aligned in the along-track direction. MODIS makes observations using a two-sided paddle-wheel scan mirror. Its on-board calibrators (OBCs) for the reflective solar bands (RSBs) include a solar diffuser (SD), a solar diffuser stability monitor (SDSM) and a spectral-radiometric calibration assembly (SRCA). Calibration is performed for each band, detector, sub-sample (for sub-kilometer resolution bands) and mirror side. In this study, a ratio approach is applied to MODIS observed Earth scene reflectances to track the detector-to-detector and mirror side differences. Simultaneous observed reflectances from the Multi-angle Imaging Spectroradiometer (MISR), also onboard the Terra spacecraft, are used with MODIS observed reflectances in this ratio approach for four closely matched spectral bands. Results show that the detector-to-detector difference between two adjacent detectors within each spectral band is typically less than 0.2% and, depending on the wavelengths, the maximum difference among all detectors varies from 0.5% to 0.8%. The mirror side differences are found to be very small for all bands except for band 3 at 0.44 mm. This is the band with the shortest wavelength among the selected matching bands, showing a time-dependent increase for the mirror side difference. This study is part of the effort by the MODIS Characterization Support Team (MCST) in order to track the RSB on-orbit performance for MODIS collection 5 data products. To support MCST efforts for future data re-processing, this analysis will be extended to include more spectral bands and temporal coverage.

Spatially Complete Global Surface Albedos Derived from Terra/MODIS Data

NASA Technical Reports Server (NTRS)

King, Michael D.; Moody, Eric G.; Platnick, Steven; Schaaf, Crystal B.

2004-01-01

Spectral land surface albedo is an important parameter for describing the radiative properties of the Earth. Accordingly it reflects the consequences of natural and human interactions, such as anthropogenic, meteorological, and phenological effects, on global and local climatological trends. Consequently, albedos are integral parts in a variety of research areas, such as general circulation models (GCMs), energy balance studies, modeling of land use and land use change, and biophysical, oceanographic, and meteorological studies. Recent production of land surface anisotropy, diffuse bihemispherical (white-sky) albedo and direct beam directional hemispherical (black-sky) albedo from observations acquired by the MODIS instruments aboard NASA s Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface's radiative characteristics. Cloud cover, which cutails retrievals, and the presence of ephemeral and seasonal snow limit the snow-free data to approximately half the global land surfaces on an annual equal-angle basis. This precludes the MOD43B3 albedo products from being used in some remote sensing and ground-based applications, climate models, and global change research projects. An ecosystem-dependent temporal interpolation technique is described that has been developed to fill missing or seasonally snow-covered data in the official MOD43B3 albedo product. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the MODIS MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data. The resulting snow-free value-added products provide the scientific community with spatially and temporally complete global white- and black-sky surface albedo maps and statistics. These products are stored on 1'(approximately 10 km) and coarser resolution equal-angle grids, and are computed for the first seven MODIS wavelengths, ranging from 0.47 through 2.1 microns, and for three broadband wavelengths, 0.3-0.7,0.3-5.0 and 0.7-5.0 microns.

Mapping Daily Evapotranspiration based on Spatiotemporal Fusion of ASTER and MODIS Images over Irrigated Agricultural Areas in the Heihe River Basin, Northwest China

NASA Astrophysics Data System (ADS)

Huang, C.; LI, Y.

2017-12-01

Continuous monitoring of daily evapotranspiration (ET) is crucial for allocating and managing water resources in irrigated agricultural areas in arid regions. In this study, continuous daily ET at a 90-m spatial resolution was estimated using the Surface Energy Balance System (SEBS) by fusing Moderate Resolution Imaging Spectroradiometer (MODIS) images with high temporal resolution and Advanced Space-borne Thermal Emission Reflectance Radiometer (ASTER) images with high spatial resolution. The spatiotemporal characteristics of these sensors were obtained using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The performance of this approach was validated over a heterogeneous oasis-desert region covered by cropland, residential, woodland, water, Gobi desert, sandy desert, desert steppe, and wetland areas using in situ observations from automatic meteorological systems (AMS) and eddy covariance (EC) systems in the middle reaches of the Heihe River Basin in Northwest China. The error introduced during the data fusion process based on STARFM is within an acceptable range for predicted LST at a 90-m spatial resolution. The surface energy fluxes estimated using SEBS based on predicted remotely sensed data that combined the spatiotemporal characteristics of MODIS and ASTER agree well with the surface energy fluxes observed using EC systems for all land cover types, especially for vegetated area with MAP values range from 9% to 15%, which are less than the uncertainty (18%) of the observed in this study area. Time series of daily ET modelled from SEBS were compared to that modelled from PT-JPL (one of Satellite-based Priestley-Taylor ET model) and observations from EC systems. SEBS performed generally better than PT-JPL for vegetated area, especially irrigated cropland with bias, RMSE, and MAP values of 0.29 mm/d, 0.75 mm/d, 13% at maize site, -0.33 mm/d, 0.81 mm/d, and 14% at vegetable sites.

Ocean Observations with EOS/MODIS: Algorithm Development and Post Launch Studies

NASA Technical Reports Server (NTRS)

Gordon, Howard R.

1997-01-01

Significant accomplishments made during the present reporting period are as follows: (1) We developed a new method for identifying the presence of absorbing aerosols and, simultaneously, performing atmospheric correction. The algorithm consists of optimizing the match between the top-of-atmosphere radiance spectrum and the result of models of both the ocean and aerosol optical properties; (2) We developed an algorithm for providing an accurate computation of the diffuse transmittance of the atmosphere given an aerosol model. A module for inclusion into the MODIS atmospheric-correction algorithm was completed; (3) We acquired reflectance data for oceanic whitecaps during a cruise on the RV Ka'imimoana in the Tropical Pacific (Manzanillo, Mexico to Honolulu, Hawaii). The reflectance spectrum of whitecaps was found to be similar to that for breaking waves in the surf zone measured by Frouin, Schwindling and Deschamps, however, the drop in augmented reflectance from 670 to 860 nm was not as great, and the magnitude of the augmented reflectance was significantly less than expected; and (4) We developed a method for the approximate correction for the effects of the MODIS polarization sensitivity. The correction, however, requires adequate characterization of the polarization sensitivity of MODIS prior to launch.

Aerosol Retrievals Over Land and Water using Deep Blue Algorithm from SeaWiFS and MODIS during UAE2 Field Campaign

NASA Astrophysics Data System (ADS)

Hsu, N.

2005-12-01

The environment in Southwest Asia exhibits one of the most complex situations for aerosol remote sensing from space. Several air masses with different aerosol characteristics commonly converge in this region. In particular, there are often fine mode pollution particles generated from oil industry activities in the Persian Gulf colliding with coarse mode dust particles lifted from desert sources in the surrounding areas. During the course of the UAE field campaign (August-October, 2004), we provided near-real time information, calculated using the Deep Blue algorithm, of satellite aerosol optical thickness and Angstrom exponent over the Southwest Asia region, including the Arabian Peninsula, Iran, Afghanistan, Pakistan, and part of north Africa. In this paper, we will present results of aerosol characteristics retrieved from SeaWiFS and MODIS over the Arabian Peninsula, Persian Gulf, and the Arabian Sea during the UAE experiment. The spectral surface reflectance data base constructed using satellite reflectance from MODIS and SeaWiFS employed in our algorithm will be discussed. We will also compare the resulting satellite retrieved aerosol optical thickness and Angstrom exponent with those obtained from the ground based sun photometers from AERONET in the region. Finally, we will discuss the changes in shortwave and longwave fluxes at the top of atmosphere in response to changes in aerosol optical thickness (i.e. aerosol forcing).

Lidar Ratios for Dust Aerosols Derived From Retrievals of CALIPSO Visible Extinction Profiles Constrained by Optical Depths from MODIS-Aqua and CALIPSO/CloudSat Ocean Surface Reflectance Measurements

NASA Technical Reports Server (NTRS)

Young, Stuart A.; Josset, Damien B.; Vaughan, Mark A.

2010-01-01

CALIPSO's (Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations) analysis algorithms generally require the use of tabulated values of the lidar ratio in order to retrieve aerosol extinction and optical depth from measured profiles of attenuated backscatter. However, for any given time or location, the lidar ratio for a given aerosol type can differ from the tabulated value. To gain some insight as to the extent of the variability, we here calculate the lidar ratio for dust aerosols using aerosol optical depth constraints from two sources. Daytime measurements are constrained using Level 2, Collection 5, 550-nm aerosol optical depth measurements made over the ocean by the MODIS (Moderate Resolution Imaging Spectroradiometer) on board the Aqua satellite, which flies in formation with CALIPSO. We also retrieve lidar ratios from night-time profiles constrained by aerosol column optical depths obtained by analysis of CALIPSO and CloudSat backscatter signals from the ocean surface.

A 30+ Year AVHRR LAI and FAPAR Climate Data Record: Algorithm Description, Validation, and Case Study

NASA Technical Reports Server (NTRS)

Claverie, Martin; Matthews, Jessica L.; Vermote, Eric F.; Justice, Christopher O.

2016-01-01

In- land surface models, which are used to evaluate the role of vegetation in the context ofglobal climate change and variability, LAI and FAPAR play a key role, specifically with respect to thecarbon and water cycles. The AVHRR-based LAIFAPAR dataset offers daily temporal resolution,an improvement over previous products. This climate data record is based on a carefully calibratedand corrected land surface reflectance dataset to provide a high-quality, consistent time-series suitablefor climate studies. It spans from mid-1981 to the present. Further, this operational dataset is availablein near real-time allowing use for monitoring purposes. The algorithm relies on artificial neuralnetworks calibrated using the MODIS LAI/FAPAR dataset. Evaluation based on cross-comparisonwith MODIS products and in situ data show the dataset is consistent and reliable with overalluncertainties of 1.03 and 0.15 for LAI and FAPAR, respectively. However, a clear saturation effect isobserved in the broadleaf forest biomes with high LAI (greater than 4.5) and FAPAR (greater than 0.8) values.

Adapting MODIS Dust Mask Algorithm to Suomi NPP VIIRS for Air Quality Applications

NASA Astrophysics Data System (ADS)

Ciren, P.; Liu, H.; Kondragunta, S.; Laszlo, I.

2012-12-01

Despite pollution reduction control strategies enforced by the Environmental Protection Agency (EPA), large regions of the United States are often under exceptional events such as biomass burning and dust outbreaks that lead to non-attainment of particulate matter standards. This has warranted the National Weather Service (NWS) to provide smoke and dust forecast guidance to the general public. The monitoring and forecasting of dust outbreaks relies on satellite data. Currently, Aqua/MODIS (MODerate resolution Imaging Spectrometer) and Terra/MODIS provide measurements needed to derive dust mask and Aerosol Optical Thickness (AOT) products. The newly launched Suomi NPP VIIRS (Visible/Infrared Imaging Radiometer Suite) instrument has a Suspended Matter (SM) product that indicates the presence of dust, smoke, volcanic ash, sea salt, and unknown aerosol types in a given pixel. The algorithm to identify dust is different over land and ocean but for both, the information comes from AOT retrieval algorithm. Over land, the selection of dust aerosol model in the AOT retrieval algorithm indicates the presence of dust and over ocean a fine mode fraction smaller than 20% indicates dust. Preliminary comparisons of VIIRS SM to CALIPSO Vertical Feature Mask (VFM) aerosol type product indicate that the Probability of Detection (POD) is at ~10% and the product is not mature for operational use. As an alternate approach, NESDIS dust mask algorithm developed for NWS dust forecast verification that uses MODIS deep blue, visible, and mid-IR channels using spectral differencing techniques and spatial variability tests was applied to VIIRS radiances. This algorithm relies on the spectral contrast of dust absorption at 412 and 440 nm and an increase in reflectivity at 2.13 μm when dust is present in the atmosphere compared to a clear sky. To avoid detecting bright desert surface as airborne dust, the algorithm uses the reflectances at 1.24 μm and 2.25 μm to flag bright pixels. The algorithm flags pixels that fall into the glint region so sun glint is not picked up as dust. The algorithm also has a spatial variability test that uses reflectances at 0.86 μm to screen for clouds over water. Analysis of one granule for a known dust event on May 2, 2012 shows that the agreement between VIIRS and MODIS is 82% and VIIRS and CALIPSO is 71%. The probability of detection for VIIRS when compared to MODIS and CALIPSO is 53% and 45% respectively whereas the false alarm ratio for VIIRS when compared to MODIS and CALIPSO is 20% and 37% respectively. The algorithm details, results from the test cases, and the use of the dust flag product in NWS applications will be presented.

Collection of LAI and FPAR Data Over The Terra Core Sites

NASA Technical Reports Server (NTRS)

Myneni, Ranga B.; Knjazihhin, J.; Tian, Y.; Wang, Y.

2001-01-01

The objective of our effort was to collect and archive data on LAI (leaf area index) and FPAR (Fraction of Photosynthetically active Radiation absorbed by vegetation) at the EOS Core validation sites as well as to validate and evaluate global fields of LAI and FPAR derived from atmospherically corrected MODIS (Moderate Resolution Imaging Spectrometer) surface reflectance data by comparing these fields with the EOS Core validation data set. The above has been accomplished by: (a) the participation in selected field campaigns within the EOS Validation Program; (b) the processing of the collected data so that suitable comparison between field measurements and the MODIS LAI/FPAR fields can be made; (c) the comparison of the MODAS LAI/FRAM fields with the EOS Terra Core validation data set.

On the Role of Urban and Vegetative Land Cover in the Identification of Tornado Damage Using Dual-Resolution Multispectral Satellite Imagery

NASA Astrophysics Data System (ADS)

Kingfield, D.; de Beurs, K.

2014-12-01

It has been demonstrated through various case studies that multispectral satellite imagery can be utilized in the identification of damage caused by a tornado through the change detection process. This process involves the difference in returned surface reflectance between two images and is often summarized through a variety of ratio-based vegetation indices (VIs). Land cover type plays a large contributing role in the change detection process as the reflectance properties of vegetation can vary based on several factors (e.g. species, greenness, density). Consequently, this provides the possibility for a variable magnitude of loss, making certain land cover regimes less reliable in the damage identification process. Furthermore, the tradeoff between sensor resolution and orbital return period may also play a role in the ability to detect catastrophic loss. Moderate resolution imagery (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS)) provides relatively coarse surface detail with a higher update rate which could hinder the identification of small regions that underwent a dynamic change. Alternatively, imagery with higher spatial resolution (e.g. Landsat) have a longer temporal return period between successive images which could result in natural recovery underestimating the absolute magnitude of damage incurred. This study evaluates the role of land cover type and sensor resolution on four high-end (EF3+) tornado events occurring in four different land cover groups (agriculture, forest, grassland, urban) in the spring season. The closest successive clear images from both Landsat 5 and MODIS are quality controlled for each case. Transacts of surface reflectance across a homogenous land cover type both inside and outside the damage swath are extracted. These metrics are synthesized through the calculation of six different VIs to rank the calculated change metrics by land cover type, sensor resolution and VI.

Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra

NASA Technical Reports Server (NTRS)

Srivastava, Ashok; Oza, Nikunj; Stroeve, Julienne

2004-01-01

Detecting clouds within a satellite image is essential for retrieving surface geophysical parameters, such as albedo and temperature, from optical and thermal imagery because the retrieval methods tend to be valid for clear skies only. Thus, routine satellite data processing requires reliable automated cloud detection algorithms that are applicable to many surface types. Unfortunately, cloud detection over snow and ice is difficult due to the lack of spectral contrast between clouds and snow. Snow and clouds are both highly reflective in the visible wavelen,ats and often show little contrast in the thermal Infrared. However, at 1.6 microns, the spectral signatures of snow and clouds differ enough to allow improved snow/ice/cloud discrimination. The recent Terra and Aqua Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensors have a channel (channel 6) at 1.6 microns. Presently the most comprehensive, long-term information on surface albedo and temperature over snow- and ice-covered surfaces comes from the Advanced Very High Resolution Radiometer ( AVHRR) sensor that has been providing imagery since July 1981. The earlier AVHRR sensors (e.g. AVHRR/2) did not however have a channel designed for discriminating clouds from snow, such as the 1.6 micron channel available on the more recent AVHRR/3 or the MODIS sensors. In the absence of the 1.6 micron channel, the AVHRR Polar Pathfinder (APP) product performs cloud detection using a combination of time-series analysis and multispectral threshold tests based on the satellite's measuring channels to produce a cloud mask. The method has been found to work reasonably well over sea ice, but not so well over the ice sheets. Thus, improving the cloud mask in the APP dataset would be extremely helpful toward increasing the accuracy of the albedo and temperature retrievals, as well as extending the time-series of albedo and temperature retrievals from the more recent sensors to the historical ones. In this work, we use data mining methods to construct a model of MODIS channel 6 as a function of other channels that are common to both MODIS and AVHRR. The idea is to use the model to generate the equivalent of MODIS channel 6 for AVHRR as a function of the AVHRR equivalents to MODIS channels. We call this a Virtual Sensor because it predicts unmeasured spectra. The goal is to use this virtual channel 6. to yield a cloud mask superior to what is currently used in APP . Our results show that several data mining methods such as multilayer perceptrons (MLPs), ensemble methods (e.g., bagging), and kernel methods (e.g., support vector machines) generate channel 6 for unseen MODIS images with high accuracy. Because the true channel 6 is not available for AVHRR images, we qualitatively assess the virtual channel 6 for several AVHRR images.

Development of the atmospheric correction algorithm for the next generation geostationary ocean color sensor data

NASA Astrophysics Data System (ADS)

Lee, Kwon-Ho; Kim, Wonkook

2017-04-01

The geostationary ocean color imager-II (GOCI-II), designed to be focused on the ocean environmental monitoring with better spatial (250m for local and 1km for full disk) and spectral resolution (13 bands) then the current operational mission of the GOCI-I. GOCI-II will be launched in 2018. This study presents currently developing algorithm for atmospheric correction and retrieval of surface reflectance over land to be optimized with the sensor's characteristics. We first derived the top-of-atmosphere radiances as the proxy data derived from the parameterized radiative transfer code in the 13 bands of GOCI-II. Based on the proxy data, the algorithm has been made with cloud masking, gas absorption correction, aerosol inversion, computation of aerosol extinction correction. The retrieved surface reflectances are evaluated by the MODIS level 2 surface reflectance products (MOD09). For the initial test period, the algorithm gave error of within 0.05 compared to MOD09. Further work will be progressed to fully implement the GOCI-II Ground Segment system (G2GS) algorithm development environment. These atmospherically corrected surface reflectance product will be the standard GOCI-II product after launch.

Improvements of top-of-atmosphere and surface irradiance computations with CALIPSO-, CloudSat-, and MODIS-derived cloud and aerosol properties

NASA Astrophysics Data System (ADS)

Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny; Miller, Walter F.; Chen, Yan; Rutan, David A.; Stephens, Graeme L.; Loeb, Norman G.; Minnis, Patrick; Wielicki, Bruce A.; Winker, David M.; Charlock, Thomas P.; Stackhouse, Paul W., Jr.; Xu, Kuan-Man; Collins, William D.

2011-10-01

One year of instantaneous top-of-atmosphere (TOA) and surface shortwave and longwave irradiances are computed using cloud and aerosol properties derived from instruments on the A-Train Constellation: the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, the CloudSat Cloud Profiling Radar (CPR), and the Aqua Moderate Resolution Imaging Spectrometer (MODIS). When modeled irradiances are compared with those computed with cloud properties derived from MODIS radiances by a Clouds and the Earth's Radiant Energy System (CERES) cloud algorithm, the global and annual mean of modeled instantaneous TOA irradiances decreases by 12.5 W m-2 (5.0%) for reflected shortwave and 2.5 W m-2 (1.1%) for longwave irradiances. As a result, the global annual mean of instantaneous TOA irradiances agrees better with CERES-derived irradiances to within 0.5W m-2 (out of 237.8 W m-2) for reflected shortwave and 2.6W m-2 (out of 240.1 W m-2) for longwave irradiances. In addition, the global annual mean of instantaneous surface downward longwave irradiances increases by 3.6 W m-2 (1.0%) when CALIOP- and CPR-derived cloud properties are used. The global annual mean of instantaneous surface downward shortwave irradiances also increases by 8.6 W m-2 (1.6%), indicating that the net surface irradiance increases when CALIOP- and CPR-derived cloud properties are used. Increasing the surface downward longwave irradiance is caused by larger cloud fractions (the global annual mean by 0.11, 0.04 excluding clouds with optical thickness less than 0.3) and lower cloud base heights (the global annual mean by 1.6 km). The increase of the surface downward longwave irradiance in the Arctic exceeds 10 W m-2 (˜4%) in winter because CALIOP and CPR detect more clouds in comparison with the cloud detection by the CERES cloud algorithm during polar night. The global annual mean surface downward longwave irradiance of 345.4 W m-2 is estimated by combining the modeled instantaneous surface longwave irradiance computed with CALIOP and CPR cloud profiles with the global annual mean longwave irradiance from the CERES product (AVG), which includes the diurnal variation of the irradiance. The estimated bias error is -1.5 W m-2 and the uncertainty is 6.9 W m-2. The uncertainty is predominately caused by the near-surface temperature and column water vapor amount uncertainties.

Cloud Statistics and Discrimination in the Polar Regions

NASA Astrophysics Data System (ADS)

Chan, M.; Comiso, J. C.

2012-12-01

Despite their important role in the climate system, cloud cover and their statistics are poorly known, especially in the polar regions, where clouds are difficult to discriminate from snow covered surfaces. The advent of the A-train, which included Aqua/MODIS, CALIPSO/CALIOP and CloudSat/CPR sensors has provided an opportunity to improve our ability to accurately characterize the cloud cover. MODIS provides global coverage at a relatively good temporal and spatial resolution while CALIOP and CPR provide limited nadir sampling but accurate characterization of the vertical structure and phase of the cloud cover. Over the polar regions, cloud detection from a passive sensors like MODIS is challenging because of the presence of cold and highly reflective surfaces such as snow, sea-ice, glaciers, and ice-sheet, which have surface signatures similar to those of clouds. On the other hand, active sensors such as CALIOP and CPR are not only very sensitive to the presence of clouds but can also provide information about its microphysical characteristics. However, these nadir-looking sensors have sparse spatial coverage and their global data can have data spatial gaps of up to 100 km. We developed a polar cloud detection system for MODIS that is trained using collocated data from CALIOP and CPR. In particular, we employ a machine learning system that reads the radiative profile observed by MODIS and determine whether the field of view is cloudy or clear. Results have shown that the improved cloud detection scheme performs better than typical cloud mask algorithms using a validation data set not used for training. A one-year data set was generated and results indicate that daytime cloud detection accuracies improved from 80.1% to 92.6% (over sea-ice) and 71.2% to 87.4% (over ice-sheet) with CALIOP data used as the baseline. Significant improvements are also observed during nighttime, where cloud detection accuracies increase by 19.8% (over sea-ice) and 11.6% (over ice-sheet). The immediate impact of the new algorithm is that it can minimize large biases of MODIS-derived cloud amount over the Polar Regions and thus a more realistic and high quality global cloud statistics. In particular, our results show that cloud fraction in the Arctic is typically 81.2 % during daytime and 84.0% during nighttime. This is significantly higher than the 71.8% and 58.5%, respectively, derived from standard MODIS cloud product.

Spatial distributions ofC3 and C4 grass functional types in the U.S. great plains and their despendency on inter-annual climate variability

USDA-ARS?s Scientific Manuscript database

Grassland ecosystems in North America are primarily composed of C3 and C4 plant functional types (PFTs) with their relative cover varying spatially and temporally. This study used 500-m MODIS surface reflectance products (MOD09A1) from 2000 to 2009 to extract an NDVI time series of C3 and C4 PFTs in...

Aerosol Optical Depth Retrievals from High-Resolution Commercial Satellite Imagery Over Areas of High Surface Reflectance

DTIC Science & Technology

2006-06-01

angle Imaging SpectroRadiometer MODIS Moderate Resolution Imaging Spectroradiometer NGA National Geospatial Intelligence Agency POI Principles of...and µ , the cosine of the viewing zenith angle and the effect of the variation of each of these variables on total optical depth. Extraterrestrial ...Eq. (34). Additionally, solar zenith angle also plays a role in the third term on the RHS of Eq. (34) by modifying extraterrestrial spectral solar

Evaluation of directional normalization methods for Landsat TM/ETM+ over primary Amazonian lowland forests

NASA Astrophysics Data System (ADS)

Van doninck, Jasper; Tuomisto, Hanna

2017-06-01

Biodiversity mapping in extensive tropical forest areas poses a major challenge for the interpretation of Landsat images, because floristically clearly distinct forest types may show little difference in reflectance. In such cases, the effects of the bidirectional reflection distribution function (BRDF) can be sufficiently strong to cause erroneous image interpretation and classification. Since the opening of the Landsat archive in 2008, several BRDF normalization methods for Landsat have been developed. The simplest of these consist of an empirical view angle normalization, whereas more complex approaches apply the semi-empirical Ross-Li BRDF model and the MODIS MCD43-series of products to normalize directional Landsat reflectance to standard view and solar angles. Here we quantify the effect of surface anisotropy on Landsat TM/ETM+ images over old-growth Amazonian forests, and evaluate five angular normalization approaches. Even for the narrow swath of the Landsat sensors, we observed directional effects in all spectral bands. Those normalization methods that are based on removing the surface reflectance gradient as observed in each image were adequate to normalize TM/ETM+ imagery to nadir viewing, but were less suitable for multitemporal analysis when the solar vector varied strongly among images. Approaches based on the MODIS BRDF model parameters successfully reduced directional effects in the visible bands, but removed only half of the systematic errors in the infrared bands. The best results were obtained when the semi-empirical BRDF model was calibrated using pairs of Landsat observation. This method produces a single set of BRDF parameters, which can then be used to operationally normalize Landsat TM/ETM+ imagery over Amazonian forests to nadir viewing and a standard solar configuration.

MODIS land cover and LAI collection 4 product quality across nine states in the western hemisphere.

Treesearch

Warren B. Cohen; Thomas K. Maiersperger; David P. Turner; William D. Ritts; Dirk Pflugmacher; Robert E. Kennedy; Alan Kirschbaum; Steven W. Running; Marcos Costa; Stith T. Gower

2006-01-01

Global maps of land cover and leaf area index (LAI) derived from the Moderate Resolution Imaging Spectrometer (MODIS) reflectance data are an important resource in studies of global change, but errors in these must be characterized and well understood. Product validation requires careful scaling from ground and related measurements to a grain commensurate with MODIS...

Cross-calibration of S-NPP VIIRS moderate-resolution reflective solar bands against MODIS Aqua over dark water scenes

NASA Astrophysics Data System (ADS)

Sayer, Andrew M.; Hsu, N. Christina; Bettenhausen, Corey; Holz, Robert E.; Lee, Jaehwa; Quinn, Greg; Veglio, Paolo

2017-04-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) is being used to continue the record of Earth Science observations and data products produced routinely from National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. However, the absolute calibration of VIIRS's reflected solar bands is thought to be biased, leading to offsets in derived data products such as aerosol optical depth (AOD) as compared to when similar algorithms are applied to different sensors. This study presents a cross-calibration of these VIIRS bands against MODIS Aqua over dark water scenes, finding corrections to the NASA VIIRS Level 1 (version 2) reflectances between approximately +1 and -7 % (dependent on band) are needed to bring the two into alignment (after accounting for expected differences resulting from different band spectral response functions), and indications of relative trending of up to ˜ 0.35 % per year in some bands. The derived calibration gain corrections are also applied to the VIIRS reflectance and then used in an AOD retrieval, and they are shown to decrease the bias and total error in AOD across the mid-visible spectral region compared to the standard VIIRS NASA reflectance calibration. The resulting AOD bias characteristics are similar to those of NASA MODIS AOD data products, which is encouraging in terms of multi-sensor data continuity.

Empirical Corrections for MISR Calibration Temporal Trends, Point-Spread Function, Flat-Fielding, and Ghosting

NASA Astrophysics Data System (ADS)

Limbacher, J.; Kahn, R. A.

2015-12-01

MISR aerosol optical depth retrievals are fairly robust to small radiometric calibration artifacts, due to the multi-angle observations. However, even small errors in the MISR calibration, especially structured artifacts in the imagery, have a disproportionate effect on the retrieval of aerosol properties from these data. Using MODIS, POLDER-3, AERONET, MAN, and MISR lunar images, we diagnose and correct various calibration and radiometric artifacts found in the MISR radiance (Level 1) data, using empirical image analysis. The calibration artifacts include temporal trends in MISR top-of-atmosphere reflectance at relatively stable desert sites and flat-fielding artifacts detected by comparison to MODIS over bright, low-contrast scenes. The radiometric artifacts include ghosting (as compared to MODIS, POLDER-3, and forward model results) and point-spread function mischaracterization (using the MISR lunar data and MODIS). We minimize the artifacts to the extent possible by parametrically modeling the artifacts and then removing them from the radiance (reflectance) data. Validation is performed using non-training scenes (reflectance comparison), and also by using the MISR Research Aerosol retrieval algorithm results compared to MAN and AERONET.

Cross-calibration of the Terra MODIS, Landsat 7 ETM+ and EO-1 ALI sensors using near-simultaneous surface observation over the Railroad Valley Playa, Nevada, test site

USGS Publications Warehouse

Chander, G.; Angal, A.; Choi, T.; Meyer, D.J.; Xiong, X.; Teillet, P.M.

2007-01-01

A cross-calibration methodology has been developed using coincident image pairs from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS), the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Earth Observing EO-1 Advanced Land Imager (ALI) to verify the absolute radiometric calibration accuracy of these sensors with respect to each other. To quantify the effects due to different spectral responses, the Relative Spectral Responses (RSR) of these sensors were studied and compared by developing a set of "figures-of-merit." Seven cloud-free scenes collected over the Railroad Valley Playa, Nevada (RVPN), test site were used to conduct the cross-calibration study. This cross-calibration approach was based on image statistics from near-simultaneous observations made by different satellite sensors. Homogeneous regions of interest (ROI) were selected in the image pairs, and the mean target statistics were converted to absolute units of at-sensor reflectance. Using these reflectances, a set of cross-calibration equations were developed giving a relative gain and bias between the sensor pair.

Spectral assessment of new ASTER SWIR surface reflectance data products for spectroscopic mapping of rocks and minerals

USGS Publications Warehouse

Mars, J.C.; Rowan, L.C.

2010-01-01

ASTER reflectance spectra from Cuprite, Nevada, and Mountain Pass, California, were compared to spectra of field samples and to ASTER-resampled AVIRIS reflectance data to determine spectral accuracy and spectroscopic mapping potential of two new ASTER SWIR reflectance datasets: RefL1b and AST_07XT. RefL1b is a new reflectance dataset produced for this study using ASTER Level 1B data, crosstalk correction, radiance correction factors, and concurrently acquired level 2 MODIS water vapor data. The AST_07XT data product, available from EDC and ERSDAC, incorporates crosstalk correction and non-concurrently acquired MODIS water vapor data for atmospheric correction. Spectral accuracy was determined using difference values which were compiled from ASTER band 5/6 and 9/8 ratios of AST_07XT or RefL1b data subtracted from similar ratios calculated for field sample and AVIRIS reflectance data. In addition, Spectral Analyst, a statistical program that utilizes a Spectral Feature Fitting algorithm, was used to quantitatively assess spectral accuracy of AST_07XT and RefL1b data.Spectral Analyst matched more minerals correctly and had higher scores for the RefL1b data than for AST_07XT data. The radiance correction factors used in the RefL1b data corrected a low band 5 reflectance anomaly observed in the AST_07XT and AST_07 data but also produced anomalously high band 5 reflectance in RefL1b spectra with strong band 5 absorption for minerals, such as alunite. Thus, the band 5 anomaly seen in the RefL1b data cannot be corrected using additional gain adjustments. In addition, the use of concurrent MODIS water vapor data in the atmospheric correction of the RefL1b data produced datasets that had lower band 9 reflectance anomalies than the AST_07XT data. Although assessment of spectral data suggests that RefL1b data are more consistent and spectrally more correct than AST_07XT data, the Spectral Analyst results indicate that spectral discrimination between some minerals, such as alunite and kaolinite, are still not possible unless additional spectral calibration using site specific spectral data are performed. ?? 2010.

Comparison of different methods to retrieve optical-equivalent snow grain size in central Antarctica

NASA Astrophysics Data System (ADS)

Carlsen, Tim; Birnbaum, Gerit; Ehrlich, André; Freitag, Johannes; Heygster, Georg; Istomina, Larysa; Kipfstuhl, Sepp; Orsi, Anaïs; Schäfer, Michael; Wendisch, Manfred

2017-11-01

The optical-equivalent snow grain size affects the reflectivity of snow surfaces and, thus, the local surface energy budget in particular in polar regions. Therefore, the specific surface area (SSA), from which the optical snow grain size is derived, was observed for a 2-month period in central Antarctica (Kohnen research station) during austral summer 2013/14. The data were retrieved on the basis of ground-based spectral surface albedo measurements collected by the COmpact RAdiation measurement System (CORAS) and airborne observations with the Spectral Modular Airborne Radiation measurement sysTem (SMART). The snow grain size and pollution amount (SGSP) algorithm, originally developed to analyze spaceborne reflectance measurements by the MODerate Resolution Imaging Spectroradiometer (MODIS), was modified in order to reduce the impact of the solar zenith angle on the retrieval results and to cover measurements in overcast conditions. Spectral ratios of surface albedo at 1280 and 1100 nm wavelength were used to reduce the retrieval uncertainty. The retrieval was applied to the ground-based and airborne observations and validated against optical in situ observations of SSA utilizing an IceCube device. The SSA retrieved from CORAS observations varied between 27 and 89 m2 kg-1. Snowfall events caused distinct relative maxima of the SSA which were followed by a gradual decrease in SSA due to snow metamorphism and wind-induced transport of freshly fallen ice crystals. The ability of the modified algorithm to include measurements in overcast conditions improved the data coverage, in particular at times when precipitation events occurred and the SSA changed quickly. SSA retrieved from measurements with CORAS and MODIS agree with the in situ observations within the ranges given by the measurement uncertainties. However, SSA retrieved from the airborne SMART data slightly underestimated the ground-based results.

New Features of the Collection 4 MODIS LAI and FPAR Product

NASA Astrophysics Data System (ADS)

Bin, T.; Yang, W.; Dong, H.; Shabanov, N.; Knyazikhin, Y.; Myneni, R.

2003-12-01

An algorithm based on physics of radiative transfer in vegetation canopies for the retrieval of vegetation green leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) from MODIS surface reflectance data was developed, prototyped and is in operational production at NASA computing facilities since June 2000. This poster highlights recent changes in the operational MODIS LAI and FPAR algorithm introduced for collection 4 data reprocessing. The changes to the algorithm are targeted to improve agreement of retrieved LAI and FPAR with corresponding field measurements, improve consistency of Quality Control (QC) definitions and miscellaneous bug fixes as summarized below. * Improvement of LUTs for the main and back-up algorithms for biomes 1 and 3. Benefits: a) increase in quality of retrievals; b) non-physical peaks in the global LAI distribution have been removed; c) improved agreement with field measurements * Improved QA scheme. Benefits: a) consistency between MODLAND and SCF quality flags has been achieved; b)ambiguity in QA has been resolved * New 8-day compositing scheme. Benefits: a) compositing over best quality retrievals, instead of all retrievals; b) lowers LAI values, decreases saturation and number of pixels generated by the back-up * At-launch static IGBP land cover, input to the LAI/FPAR algorithm, was replaced with the MODIS land cover map. Benefits: a) crosswalking of 17 classes IGBP scheme to 6-biome LC has been eliminated; b) uncertainties in the MODIS LAI/FPAR product due to uncertainties in land cover map have been reduced

MODIS-derived EVI, NDVI and WDRVI time series to estimate phenological metrics in French deciduous forests

NASA Astrophysics Data System (ADS)

Testa, S.; Soudani, K.; Boschetti, L.; Borgogno Mondino, E.

2018-02-01

Monitoring forest phenology allows us to study the effects of climate change on vegetated land surfaces. Daily and composite time series (TS) of several vegetation indices (VIs) from MODerate resolution Imaging Spectroradiometer (MODIS) data have been widely used in scientific works for phenological studies since the beginning of the MODIS mission. The objective of this work was to use MODIS data to find the best VI/TS combination to estimate start-of-season (SOS) and end-of-season (EOS) dates across 50 temperate deciduous forests. Our research used as inputs 2001-2012 daily reflectance from MOD09GQ/MOD09GA products and 16-day composite VIs from the MOD13Q1 dataset. The 50 pixels centered on the 50 forest plots were extracted from the above-mentioned MODIS imagery; we then generated 5 different types of TS (1 daily from MOD09 and 4 composite from MOD13Q1) and used all of them to implement 6 VIs, obtaining 30 VI/TS combinations. SOS and EOS estimates were determined for each pixel/year and each VI/TS combination. SOS/EOS estimations were then validated against ground phenological observations. Results showed that, in our test areas, composite TS, if actual acquisition date is considered, performed mostly better than daily TS. EVI, WDRVI0.20 and NDVI were more suitable to SOS estimation, while WDRVI0.05 and EVI were more convenient in estimating early and advanced EOS, respectively.

Retrieval of AOD and PM2.5 Concentrations over Urban Areas of Shenyang City using MODIS Data

NASA Astrophysics Data System (ADS)

Wang, Z.

2016-12-01

Atmospheric aerosols play an important part in the Earth's radiation balance as well as global climate change, aerosols also have very important impact on environment as well as human and other organisms' health, PM2.5 and other small particle aerosols, can enter bronchi directly, thus causing bronchitis, cardiovascular disease, asthma and so on.Detection of AOD by satellite and remote sensing is currently one of the hotest issues , diffierent from the traditional monitoring method, this method has much more advantanges, for emample wide area coverage, fast and convenient etc. So it is possible for people to know the regional changes of AOD real time over large area. Now, detection aerosol by RS technology has reached a high level in marine and dense vegetation land areas, but result is not ideal for urban areas, the higher surface reflectance in urban areas is a bottleneck of AOD retrieval. Focus on the high surface reflectance and low accuracy of the AOD products of urban areas, this paper propose an algorithm coupled with surface reflectance to get red band surface reflectance, based on Dens Dark Vegetation algorithm and geometrical optics model theory, to distinguish urban reflectivity from other targets. Considering the appropriate aerosol model which adapt to season and other proper parameters, this paper uses 6S model to establish look-up table, thus retrieve AOD for urban as well as other high reflectance areas. This paper take Shenyang region as pilot area, then retrieve the AOD and PM2.5 concentration of Shenyang in 2015 based on MODIS data, thus get 1km resolution distribution map, and then analyzed the results in spatial, intensity and temporal. At last, real-time monitoring data from the ground monitor station is used to verify the outcome, the results have good accuracy and the the correlation reached 0.9004 when the weather is sunny. The research shows that this algorithm has relatively higher precision and certain universality. This method has better applicability to retrieve AOD and PM2.5 concentration by remote sensing in Shenyang and Liaoning Provience, and owes guiding and reference significance, and it has a high value in terms of atmospheric environment monitoring.

Monitoring Invasive Aquatic Vegetation in Lake Okeechobee, Florida, using NDVI Derived from MODIS Data

NASA Astrophysics Data System (ADS)

Woods, K. A.; Brozen, M.; Pelkie, A.; Malik, S.

2009-12-01

Lake Okeechobee is the second largest freshwater lake located entirely within the continental United States. The lake encompasses approximately 1,700 km2 in South Florida and is a vital part of the Lake Okeechobee and Everglades ecosystems. Lake Okeechobee has been plagued by invasive aquatic floating vegetation and in-water blooms of blue-green algae (cyanobacteria). Major cyanobacterial blooms have been documented in Lake Okeechobee since the 1970s and have continued to plague the ecosystem. Similarly, invasive hydrilla, water hyacinth, and water lettuce frequently overgrow in the lake and threaten the ecosystem. This study examines invasive aquatic vegetation occurrence through the use of the Normalized Difference Vegetation Index calculated on Moderate Resolution Imaging Spectroradiometer (MODIS) MOD09 surface reflectance imagery. Occurrence during 2008 was analyzed using the Time Series Product Tool developed at John C. Stennis Space Center. This project tracked spatial and temporal variability of cyanobacterial blooms and overgrowth of water lettuce, water hyacinth, and hydrilla. In addition, this study presents an application of MODIS data to assist in water quality management.

The Impacts of Bowtie Effect and View Angle Discontinuity on MODIS Swath Data Gridding

NASA Technical Reports Server (NTRS)

Wang, Yujie; Lyapustin, Alexei

2007-01-01

We have analyzed two effects of the MODIS viewing geometry on the quality of gridded imagery. First, the fact that the MODIS scans a swath of the Earth 10 km wide at nadir, causes abrupt change of the view azimuth angle at the boundary of adjacent scans. This discontinuity appears as striping of the image clearly visible in certain cases with viewing geometry close to principle plane over the snow of the glint area of water. The striping is a true surface Bi-directional Reflectance Factor (BRF) effect and should be preserved during gridding. Second, due to bowtie effect, the observations in adjacent scans overlap each other. Commonly used method of calculating grid cell value by averaging all overlapping observations may result in smearing of the image. This paper describes a refined gridding algorithm that takes the above two effects into account. By calculating the grid cell value by averaging the overlapping observations from a single scan, the new algorithm preserves the measured BRF signal and enhances sharpness of the image.

Geostatistical Analysis of Surface Temperature and In-Situ Soil Moisture Using LST Time-Series from Modis

NASA Astrophysics Data System (ADS)

Sohrabinia, M.; Rack, W.; Zawar-Reza, P.

2012-07-01

The objective of this analysis is to provide a quantitative estimate of the fluctuations of land surface temperature (LST) with varying near surface soil moisture (SM) on different land-cover (LC) types. The study area is located in the Canterbury Plains in the South Island of New Zealand. Time series of LST from the MODerate resolution Imaging Spectro-radiometer (MODIS) have been analysed statistically to study the relationship between the surface skin temperature and near-surface SM. In-situ measurements of the skin temperature and surface SM with a quasi-experimental design over multiple LC types are used for validation. Correlations between MODIS LST and in-situ SM, as well as in-situ surface temperature and SM are calculated. The in-situ measurements and MODIS data are collected from various LC types. Pearson's r correlation coefficient and linear regression are used to fit the MODIS LST and surface skin temperature with near-surface SM. There was no significant correlation between time-series of MODIS LST and near-surface SM from the initial analysis, however, careful analysis of the data showed significant correlation between the two parameters. Night-time series of the in-situ surface temperature and SM from a 12 hour period over Irrigated-Crop, Mixed-Grass, Forest, Barren and Open- Grass showed inverse correlations of -0.47, -0.68, -0.74, -0.88 and -0.93, respectively. These results indicated that the relationship between near-surface SM and LST in short-terms (12 to 24 hours) is strong, however, remotely sensed LST with higher temporal resolution is required to establish this relationship in such time-scales. This method can be used to study near-surface SM using more frequent LST observations from a geostationary satellite over the study area.

Sensitivity of MODIS 2.1 micron Channel for Off-Nadir View Angles for Use in Remote Sensing of Aerosol

NASA Technical Reports Server (NTRS)

Gatebe, C. K.; King, M. D.; Tsay, S.-C.; Ji, Q.

2000-01-01

Remote sensing of aerosol over land, from MODIS will be based on dark targets using mid-IR channels 2.1 and 3.9 micron. This approach was developed by Kaufman et al (1997), who suggested that dark surface reflectance in the red (0.66 micron -- rho(sub 0.66)) channel is half of that at 2.2 micron (rho(sub 2.2)), and the reflectance in the blue (0.49 micron - rho(sub 0.49)) channel is a quarter of that at 2.2 micron. Using this relationship, the surface reflectance in the visible channels can be predicted within Delta.rho(sub 0.49) approximately Delat.rho(sub 0.66) approximately 0.006 from rho(sub 2.2) for rho(sub 2.2) <= 0.10. This was half the error obtained using the 3.75 micron and corresponds to an error in aerosol optical thickness of Delat.tau approximately 0.06. These results, though applicable to several biomes (e.g. forests, and brighter lower canopies), have only been tested at one view angle - the nadir (theta = 0 deg). Considering the importance of the results in remote sensing of aerosols over land surfaces from space, we are validating the relationships for off-nadir view angles using Cloud Absorption Radiometer (CAR) data. The CAR data are available for channels between 0.3 and 2.3 micron and for different surface types and conditions: forest, tundra, ocean, sea-ice, swamp, grassland and over areas covered with smoke. In this study we analyzed data collected during the Smoke, Clouds, and Radiation - Brazil (SCAR-B) experiment to validate Kaufman et al.'s (1997) results for non-nadir view angles. We will show the correlation between rho(sub 0.472), rho(sub 0.675), and rho(sub 2.2) for view angles between nadir (0 deg) and 55 deg off-nadir, and for different viewing directions in the backscatter and forward scatter directions.

Annual Changes of Paddy Rice Planting Areas in Northeastern Asia from MODIS images in 2000-2014

NASA Astrophysics Data System (ADS)

Xiao, X.; Zhang, G.; Dong, J.; Menarguez, M. A.; Kou, W.; Jin, C.; Qin, Y.; Zhou, Y.; Wang, J.; Moore, B., III

2014-12-01

Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, estimation of greenhouse gas (methane) emissions, and understanding avian influenza virus transmission. Over the past two decades, paddy rice cultivation has expanded northward in temperate and cold temperate zones, particularly in Northeastern China. There is a need to quantify and map changes in paddy rice planting areas in Northeastern Asia (Japan, North and South Korea, and northeast China) at annual interval. We developed a pixel- and phenology-based image analysis system, MODIS-RICE, to map the paddy rice in Northeastern Asia by using multi-temporal MODIS thermal and surface reflectance imagery. Paddy rice fields during the flooding and transplanting phases have unique physical and spectral characteristics, which make it possible for the development of an automated and robust algorithm to track flooding and transplanting phases of paddy rice fields over time. In this presentation, we will show the MODIS-based annual maps of paddy rice planting area in the Northeastern Asia from 2000-2014 (500-m spatial resolution). Accuracy assessments using high-resolution images show that the resultant paddy rice map of Northeastern Asia had a comparable accuracy to the existing products, including 2010 Landsat-based National Land Cover Dataset (NLCD) of China, the 2010 RapidEye-based paddy rice map in North Korea, and the 2010 AVNIR-2-based National Land Cover Dataset in Japan in terms of both area and spatial pattern of paddy rice. This study has demonstrated that our novel MODIS-Rice system, which use both thermal and optical MODIS data over a year, are simple and robust tools to identify and map paddy rice fields in temperate and cold temperate zones.

Evaluation of Moderate-Resolution Imaging Spectroradiometer (MODIS) Snow Albedo Product (MCD43A) over Tundra

NASA Technical Reports Server (NTRS)

Wang, Zhuosen; Schaaf, Crystal B.; Chopping, Mark J.; Strahler, Alan H.; Wang, Jindi; Roman, Miguel O.; Rocha, Adrian V.; Woodcock, Curtis E.; Shuai, Yanmin

2012-01-01

This study assesses the MODIS standard Bidirectional Reflectance Distribution Function (BRDF)/Albedo product, and the daily Direct Broadcast BRDF/Albedo algorithm at tundra locations under large solar zenith angles and high anisotropic diffuse illumination and multiple scattering conditions. These products generally agree with ground-based albedo measurements during the snow cover period when the Solar Zenith Angle (SZA) is less than 70deg. An integrated validation strategy, including analysis of the representativeness of the surface heterogeneity, is performed to decide whether direct comparisons between field measurements and 500- m satellite products were appropriate or if the scaling of finer spatial resolution airborne or spaceborne data was necessary. Results indicate that the Root Mean Square Errors (RMSEs) are less than 0.047 during the snow covered periods for all MCD43 albedo products at several Alaskan tundra areas. The MCD43 1- day daily albedo product is particularly well suited to capture the rapidly changing surface conditions during the spring snow melt. Results also show that a full expression of the blue sky albedo is necessary at these large SZA snow covered areas because of the effects of anisotropic diffuse illumination and multiple scattering. In tundra locations with dark residue as a result of fire, the MODIS albedo values are lower than those at the unburned site from the start of snowmelt.

Top-down estimate of dust emissions through integration of MODIS and MISR aerosol retrievals with the GEOS-Chem adjoint model

NASA Astrophysics Data System (ADS)

Wang, Jun; Xu, Xiaoguang; Henze, Daven K.; Zeng, Jing; Ji, Qiang; Tsay, Si-Chee; Huang, Jianping

2012-04-01

Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOS-Chem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10 concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

Clear-Sky Narrowband Albedo Datasets Derived from Modis Data

NASA Astrophysics Data System (ADS)

Chen, Y.; Minnis, P.; Sun-Mack, S.; Arduini, R. F.; Hong, G.

2013-12-01

Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting the clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the near-infrared (NIR; 1.24, 1.6 or 2.13 μm) and visible (VIS; 0.63 μm) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS) to help identify clouds and retrieve their properties. Generally, clear-sky albedo for a given surface type is determined for conditions when the vegetation is either thriving or dormant and free of snow. The clear-sky albedos are derived using a radiative transfer parameterization of the impact of the atmosphere, including aerosols, on the observed reflectances. This paper presents the method of generating monthly clear-sky overhead albedo maps for both snow-free and snow-covered surfaces of these channels using one year of MODIS (Moderate Resolution Imaging Spectroradiometer) CERES products. Maps of 1.24 and 1.6 μm are being used as the background to help retrieve cloud properties (e.g., effective particle size, optical depth) in CERES cloud retrievals in both snow-free and snow-covered conditions.

Top-down Estimate of Dust Emissions Through Integration of MODIS and MISR Aerosol Retrievals With the Geos-chem Adjoint Model

NASA Technical Reports Server (NTRS)

Wang, Jun; Xu, Xiaoguang; Henze, Daven K.; Zeng, Jing; Ji, Qiang; Tsay, Si-Chee; Huang, Jianping

2012-01-01

Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOSChem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10 concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

Testing the Two-Layer Model for Correcting Near Cloud Reflectance Enhancement Using LES SHDOM Simulated Radiances

NASA Technical Reports Server (NTRS)

Wen, Guoyong; Marshak, Alexander; Varnai, Tamas; Levy, Robert

2016-01-01

A transition zone exists between cloudy skies and clear sky; such that, clouds scatter solar radiation into clear-sky regions. From a satellite perspective, it appears that clouds enhance the radiation nearby. We seek a simple method to estimate this enhancement, since it is so computationally expensive to account for all three-dimensional (3-D) scattering processes. In previous studies, we developed a simple two-layer model (2LM) that estimated the radiation scattered via cloud-molecular interactions. Here we have developed a new model to account for cloud-surface interaction (CSI). We test the models by comparing to calculations provided by full 3-D radiative transfer simulations of realistic cloud scenes. For these scenes, the Moderate Resolution Imaging Spectroradiometer (MODIS)-like radiance fields were computed from the Spherical Harmonic Discrete Ordinate Method (SHDOM), based on a large number of cumulus fields simulated by the University of California, Los Angeles (UCLA) large eddy simulation (LES) model. We find that the original 2LM model that estimates cloud-air molecule interactions accounts for 64 of the total reflectance enhancement and the new model (2LM+CSI) that also includes cloud-surface interactions accounts for nearly 80. We discuss the possibility of accounting for cloud-aerosol radiative interactions in 3-D cloud-induced reflectance enhancement, which may explain the remaining 20 of enhancements. Because these are simple models, these corrections can be applied to global satellite observations (e.g., MODIS) and help to reduce biases in aerosol and other clear-sky retrievals.

Using EO-1 Hyperion to Simulate HyspIRI Products for a Coniferous Forest: The Fraction of PAR Absorbed by Chlorophyll (fAPAR(sub chl)) and Leaf Water Content(LWC)

NASA Technical Reports Server (NTRS)

Zhang, Qingyuan; Middleton, Elizabeth M.; Gao, Bo-Cai; Cheng, Yen-Ben

2012-01-01

This paper presents development of prototype products for terrestrial ecosystems in preparation for the future imaging spectrometer planned for the Hyperspectral Infrared Imager (HyspIRI) mission. We present a successful demonstration example in a coniferous forest of two product prototypes: fraction of photosynthetically active radiation (PAR) absorbed by chlorophyll of a canopy (fAPARchl) and leaf water content (LWC), for future HyspIRI implementation at 60-m spatial resolution. For this, we used existing 30-m resolution imaging spectrometer data available from the Earth Observing One (EO-1) Hyperion satellite to simulate and prototype the level one radiometrically corrected radiance (L1R) images expected from the HyspIRI visible through shortwave infrared spectrometer. The HyspIRIlike images were atmospherically corrected to obtain surface reflectance and spectrally resampled to produce 60-m reflectance images for wavelength regions that were comparable to all seven of the MODerate resolution Imaging Spectroradiometer (MODIS) land bands. Thus, we developed MODIS-like surface reflectance in seven spectral bands at the HyspIRI-like spatial scale, which was utilized to derive fAPARchl and LWC with a coupled canopy-leaf radiative transfer model (PROSAIL2) for the coniferous forest. With this paper, we provide additional evidence that the fAPARchl product is more realistic in describing the physiologically active canopy than the traditional fAPAR parameter for the whole canopy (fAPARcanopy), and thus, it should replace it in ecosystem process models to reduce uncertainties in terrestrial carbon cycle and ecosystem studies.

Accuracy Assessment of Aqua-MODIS Aerosol Optical Depth Over Coastal Regions: Importance of Quality Flag and Sea Surface Wind Speed

NASA Technical Reports Server (NTRS)

Anderson, J. C.; Wang, J.; Zeng, J.; Petrenko, M.; Leptoukh, G. G.; Ichoku, C.

2012-01-01

Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from approximately 2002-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard Aqua satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the MODIS Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the MODIS AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R(sup 2) is approximately equal to 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the MODIS AODs from the Land algorithm, Ocean algorithm, and combined Land and Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the MODIS Land and Ocean AOD dataset can be degraded by 30-50% in terms of mean bias. Overall, the MODIS Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD less than 0.25 and underestimates it by 0.029 for AOD greater than 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region 25 (with a mean and median value of 2.94 meters per second and 2.66 meters per second, respectively) are often slower than 6 meters per second assumed in the MODIS Ocean algorithm. As a result of high correlation (R(sup 2) greater than 0.98) between the bias in binned MODIS AOD and the corresponding binned wind speed over the coastal sea surface, an empirical scheme for correcting the bias of AOD retrieved from the MODIS Ocean algorithm is formulated and is shown to be effective over the majority of the coastal AERONET stations, and hence can be used in future analysis of AOD trend and MODIS AOD data assimilation.

Progress in Understanding the Impacts of 3-D Cloud Structure on MODIS Cloud Property Retrievals for Marine Boundary Layer Clouds

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Werner, Frank; Miller, Daniel; Platnick, Steven; Ackerman, Andrew; DiGirolamo, Larry; Meyer, Kerry; Marshak, Alexander; Wind, Galina; Zhao, Guangyu

2016-01-01

Theory: A novel framework based on 2-D Tayler expansion for quantifying the uncertainty in MODIS retrievals caused by sub-pixel reflectance inhomogeneity. (Zhang et al. 2016). How cloud vertical structure influences MODIS LWP retrievals. (Miller et al. 2016). Observation: Analysis of failed MODIS cloud property retrievals. (Cho et al. 2015). Cloud property retrievals from 15m resolution ASTER observations. (Werner et al. 2016). Modeling: LES-Satellite observation simulator (Zhang et al. 2012, Miller et al. 2016).

GOCI Yonsei aerosol retrieval version 2 products: an improved algorithm and error analysis with uncertainty estimation from 5-year validation over East Asia

NASA Astrophysics Data System (ADS)

Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Holben, Brent; Eck, Thomas F.; Li, Zhengqiang; Song, Chul H.

2018-01-01

The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER) version 1 algorithm was developed to retrieve hourly aerosol optical depth at 550 nm (AOD) and other subsidiary aerosol optical properties over East Asia. The GOCI YAER AOD had accuracy comparable to ground-based and other satellite-based observations but still had errors because of uncertainties in surface reflectance and simple cloud masking. In addition, near-real-time (NRT) processing was not possible because a monthly database for each year encompassing the day of retrieval was required for the determination of surface reflectance. This study describes the improved GOCI YAER algorithm version 2 (V2) for NRT processing with improved accuracy based on updates to the cloud-masking and surface-reflectance calculations using a multi-year Rayleigh-corrected reflectance and wind speed database, and inversion channels for surface conditions. The improved GOCI AOD τG is closer to that of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD than was the case for AOD from the YAER V1 algorithm. The V2 τG has a lower median bias and higher ratio within the MODIS expected error range (0.60 for land and 0.71 for ocean) compared with V1 (0.49 for land and 0.62 for ocean) in a validation test against Aerosol Robotic Network (AERONET) AOD τA from 2011 to 2016. A validation using the Sun-Sky Radiometer Observation Network (SONET) over China shows similar results. The bias of error (τG - τA) is within -0.1 and 0.1, and it is a function of AERONET AOD and Ångström exponent (AE), scattering angle, normalized difference vegetation index (NDVI), cloud fraction and homogeneity of retrieved AOD, and observation time, month, and year. In addition, the diagnostic and prognostic expected error (PEE) of τG are estimated. The estimated PEE of GOCI V2 AOD is well correlated with the actual error over East Asia, and the GOCI V2 AOD over South Korea has a higher ratio within PEE than that over China and Japan.

Promise and Capability of NASA's Earth Observing System to Monitor Human-Induced Climate Variations

NASA Technical Reports Server (NTRS)

King, M. D.

2003-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. The Moderate Resolution Imaging Spectroradiometer (MODIS), developed as part of the Earth Observing System (EOS) and launched on Terra in December 1999 and Aqua in May 2002, is designed to meet the scientific needs for satellite remote sensing of clouds, aerosols, water vapor, and land and ocean surface properties. This sensor and multi-platform observing system is especially well suited to observing detailed interdisciplinary components of the Earth s surface and atmosphere in and around urban environments, including aerosol optical properties, cloud optical and microphysical properties of both liquid water and ice clouds, land surface reflectance, fire occurrence, and many other properties that influence the urban environment and are influenced by them. In this presentation I will summarize the current capabilities of MODIS and other EOS sensors currently in orbit to study human-induced climate variations.

Effect of Thin Cirrus Clouds on Dust Optical Depth Retrievals From MODIS Observations

NASA Technical Reports Server (NTRS)

Feng, Qian; Hsu, N. Christina; Yang, Ping; Tsay, Si-Chee

2011-01-01

The effect of thin cirrus clouds in retrieving the dust optical depth from MODIS observations is investigated by using a simplified aerosol retrieval algorithm based on the principles of the Deep Blue aerosol property retrieval method. Specifically, the errors of the retrieved dust optical depth due to thin cirrus contamination are quantified through the comparison of two retrievals by assuming dust-only atmospheres and the counterparts with overlapping mineral dust and thin cirrus clouds. To account for the effect of the polarization state of radiation field on radiance simulation, a vector radiative transfer model is used to generate the lookup tables. In the forward radiative transfer simulations involved in generating the lookup tables, the Rayleigh scattering by atmospheric gaseous molecules and the reflection of the surface assumed to be Lambertian are fully taken into account. Additionally, the spheroid model is utilized to account for the nonsphericity of dust particles In computing their optical properties. For simplicity, the single-scattering albedo, scattering phase matrix, and optical depth are specified a priori for thin cirrus clouds assumed to consist of droxtal ice crystals. The present results indicate that the errors in the retrieved dust optical depths due to the contamination of thin cirrus clouds depend on the scattering angle, underlying surface reflectance, and dust optical depth. Under heavy dusty conditions, the absolute errors are comparable to the predescribed optical depths of thin cirrus clouds.

Evaluation of Long-term Aerosol Data Records from SeaWiFS over Land and Ocean

NASA Astrophysics Data System (ADS)

Bettenhausen, C.; Hsu, C.; Jeong, M.; Huang, J.

2010-12-01

Deserts around the globe produce mineral dust aerosols that may then be transported over cities, across continents, or even oceans. These aerosols affect the Earth’s energy balance through direct and indirect interactions with incoming solar radiation. They also have a biogeochemical effect as they deliver scarce nutrients to remote ecosystems. Large dust storms regularly disrupt air traffic and are a general nuisance to those living in transport regions. In the past, measuring dust aerosols has been incomplete at best. Satellite retrieval algorithms were limited to oceans or vegetated surfaces and typically neglected desert regions due to their high surface reflectivity in the mid-visible and near-infrared wavelengths, which have been typically used for aerosol retrievals. The Deep Blue aerosol retrieval algorithm was developed to resolve these shortcomings by utilizing the blue channels from instruments such as the Sea-Viewing Wide-Field-of-View Sensor (SeaWiFS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) to infer aerosol properties over these highly reflective surfaces. The surface reflectivity of desert regions is much lower in the blue channels and thus it is easier to separate the aerosol and surface signals than at the longer wavelengths used in other algorithms. More recently, the Deep Blue algorithm has been expanded to retrieve over vegetated surfaces and oceans as well. A single algorithm can now follow dust from source to sink. In this work, we introduce the SeaWiFS instrument and the Deep Blue aerosol retrieval algorithm. We have produced global aerosol data records over land and ocean from 1997 through 2009 using the Deep Blue algorithm and SeaWiFS data. We describe these data records and validate them with data from the Aerosol Robotic Network (AERONET). We also show the relative performance compared to the current MODIS Deep Blue operational aerosol data in desert regions. The current results are encouraging and this dataset will be useful to future studies in understanding the effects of dust aerosols on global processes, long-term aerosol trends, quantifying dust emissions, transport, and inter-annual variability.

NASA Blue Marble 2007 East

NASA Image and Video Library

2010-03-12

RELEASE DATE: OCTOBER 9, 2007 Credit: NASA/Goddard Space Flight Center/Reto Stöckli A day’s clouds. The shape and texture of the land. The living ocean. City lights as a beacon of human presence across the globe. This amazingly beautiful view of Earth from space is a fusion of science and art, a showcase for the remote-sensing technology that makes such views possible, and a testament to the passion and creativity of the scientists who devote their careers to understanding how land, ocean, and atmosphere—even life itself—interact to generate Earth’s unique (as far as we know!) life-sustaining environment. Drawing on data from multiple satellite missions (not all collected at the same time), a team of NASA scientists and graphic artists created layers of global data for everything from the land surface, to polar sea ice, to the light reflected by the chlorophyll in the billions of microscopic plants that grow in the ocean. They wrapped these layers around a globe, set it against a black background, and simulated the hazy edge of the Earth’s atmosphere (the limb) that appears in astronaut photography of the Earth. The land surface layer is based on photo-like surface reflectance observations (reflected sunlight) measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite in July 2004. The sea ice layer near the poles comes from Terra MODIS observations of daytime sea ice observed between August 28 and September 6, 2001. The ocean layer is a composite. In shallow water areas, the layer shows surface reflectances observed by Terra MODIS in July 2004. In the open ocean, the photo-like layer is overlaid with observations of the average ocean chlorophyll content for 2004. NASA’s Aqua MODIS collected the chlorophyll data. The cloud layer shows a single-day snapshot of clouds observed by Terra MODIS across the planet on July 29, 2001. City lights on Earth’s night side are visualized from data collected by the Defense Meteorological Satellite Program mission between 1994–1995. The topography layer is based on radar data collected by the Space Shuttle Endeavour during an 11-day mission in February of 2000. Topography over Antarctica comes from the Radarsat Antarctic Mapping Project, version 2. Most of the data layers in this visualization are available as monthly composites as part of NASA’s Blue Marble Next Generation image collection. The images in the collection appear in cylindrical projection (rectangular maps), and they are available at 500-meter resolution. The large images provided above are the full-size versions of these globes. In their hope that these images will inspire people to appreciate the beauty of our home planet and to learn about the Earth system, the developers of these images encourage readers to re-use and re-publish the images freely. NASA images by Reto Stöckli, based on data from NASA and NOAA. To learn the history of the Blue Marble go here: earthobservatory.nasa.gov/Features/BlueMarble/BlueMarble_... To learn more about the Blue Marble go here: earthobservatory.nasa.gov/IOTD/view.php?id=8108 To learn more about NASA's Goddard Space Flight Center go here: www.nasa.gov/centers/goddard/home/index.html NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe. NASA Goddard Space Flight Center is home to the nation's largest organization of combined scientists, engineers and technologists that build spacecraft, instruments and new technology to study the Earth, the sun, our solar system, and the universe. Follow us on Twitter Join us on Facebook

Linking Landsat observations with MODIS derived Land Surface Phenology data to map agricultural expansion and contraction in Russia

NASA Astrophysics Data System (ADS)

Caliskan, S.; de Beurs, K.

2010-12-01

Direct human impacts on the land surface are especially pronounced in agricultural regions that cover a substantial portion of the global land surface: 12% of the terrestrial surface is under active agricultural management. Crops display phenologies distinct from natural vegetation; the growing seasons are often shifted in time, crop establishment is generally fast and the vegetation is rapidly removed at harvest. Previously we have demonstrated that agricultural land abandonment alters land surface phenology sufficiently to be detectable from a time series of coarse resolution imagery. With land surface phenology models based on accumulated growing degree-days (AGDD) and AVHRR NDVI, we demonstrated that abandoned croplands covered with native grasses and weeds typically greened-up and peaked sooner than active croplands. Here we present an expansion of these analyses for the MODIS time period with the ultimate goal to map agricultural abandonment and expansion in European Russia from 2000 to 2010. We used the 8-day, 1km L3 Land Surface Temperature data (MOD11A2) to generate the accumulated growing degree days and the 16-day L3 Nadir BRDF-Adjusted reflectance data at 500m resolution (MCD43A4) to calculate NDVI. We calculated phenological metrics based on three methods: 1) Double-logistic models such as those applied to produce the standard MODIS phenology product (MOD12Q2); 2) A combination of NDII and NDVI; this method has been shown to provide start/end of season measurement closest to field observations in snowy areas; and 3) A quadratic model linking accumulated growing degree days and vegetation indices which we successfully applied in agricultural areas of Kazakhstan and semi-arid Africa. We selected Landsat imagery for two vastly different regions in Russia and present a Landsat-guided probabilistic detection of abandoned and active croplands for all available years of the MODIS image time series (2000-2010). For each region, we selected at least two images during the growing season and calculated the following indices: Normalized Difference Vegetation Index (NDVI), Tasseled Cap indices (Brightness, Greenness, Wetness), as well as the first three principal components for each image. We used the selected images to distinguish between the basic classes of agriculture, water, forest and urban areas, with the primary goal to separate between agricultural and non-agricultural regions. We compared class membership with ancillary regional agricultural statistics and targeted field observations collected in the summer of 2010. In the last part, we linked the Landsat based agricultural estimates and the MODIS phenological measurements using logistic regression and compared the agricultural maps with globally available land cover classifications.

Infrared Algorithm Development for Ocean Observations with EOS/MODIS

NASA Technical Reports Server (NTRS)

Brown, Otis B.

1997-01-01

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared measurements. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, development of experimental instrumentation, and participation in MODIS (project) related activities. Activities in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, undertake field campaigns, analysis of field data, and participation in MODIS meetings.

Sea Surface Temperature and Vegetation Index from MODIS

NASA Technical Reports Server (NTRS)

2002-01-01

This is a composite MODIS image showing the 'green wave' of spring in North America and sea surface temperature in the ocean, collected over an 8-day period during the first week in April 2000. On land, the darker green pixels show where the most green foliage is being produced due to photosynthetic activity. Yellows on land show where there is little or no productivity and red is a boundary zone. In the ocean, orange and yellows show warmer waters and blues show colder values. (MODIS Data Type: MODIS-PFM)

Marine Boundary Layer Cloud Property Retrievals from High-Resolution ASTER Observations: Case Studies and Comparison with Terra MODIS

NASA Technical Reports Server (NTRS)

Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

2016-01-01

A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTERspecific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in Zhao and Di Girolamo (2006). To validate and evaluate the cloud optical thickness (tau) and cloud effective radius (r(sub eff)) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000m resolution as MODIS. Subsequently, tau(sub aA) and r(sub eff, aA) retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R greater than 0.970. However, for partially cloudy pixels there are significant differences between r(sub eff, aA) and the MODIS results which can exceed 10 micrometers. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

Marine boundary layer cloud property retrievals from high-resolution ASTER observations: case studies and comparison with Terra MODIS

NASA Astrophysics Data System (ADS)

Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

2016-12-01

A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTER-specific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in [Zhao and Di Girolamo(2006)]. To validate and evaluate the cloud optical thickness (τ) and cloud effective radius (reff) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000 m resolution as MODIS. Subsequently, τaA and reff, aA retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R > 0.970. However, for partially cloudy pixels there are significant differences between reff, aA and the MODIS results which can exceed 10 µm. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

Comparison of PARASOL Observations with Polarized Reflectances Simulated Using Different Ice Habit Mixtures

NASA Technical Reports Server (NTRS)

Cole, Benjamin H.; Yang, Ping; Baum, Bryan A.; Riedi, Jerome; Labonnote, Laurent C.; Thieuleux, Francois; Platnick, Steven

2012-01-01

Insufficient knowledge of the habit distribution and the degree of surface roughness of ice crystals within ice clouds is a source of uncertainty in the forward light scattering and radiative transfer simulations required in downstream applications involving these clouds. The widely used MODerate Resolution Imaging Spectroradiometer (MODIS) Collection 5 ice microphysical model assumes a mixture of various ice crystal shapes with smooth-facets except aggregates of columns for which a moderately rough condition is assumed. When compared with PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) polarized reflection data, simulations of polarized reflectance using smooth particles show a poor fit to the measurements, whereas very rough-faceted particles provide an improved fit to the polarized reflectance. In this study a new microphysical model based on a mixture of 9 different ice crystal habits with severely roughened facets is developed. Simulated polarized reflectance using the new ice habit distribution is calculated using a vector adding-doubling radiative transfer model, and the simulations closely agree with the polarized reflectance observed by PARASOL. The new general habit mixture is also tested using a spherical albedo differences analysis, and surface roughening is found to improve the consistency of multi-angular observations. It is suggested that an ice model incorporating an ensemble of different habits with severely roughened surfaces would potentially be an adequate choice for global ice cloud retrievals.

MODIS Instrument Operation and Calibration Improvements

NASA Technical Reports Server (NTRS)

Xiong, X.; Angal, A.; Madhavan, S.; Link, D.; Geng, X.; Wenny, B.; Wu, A.; Chen, H.; Salomonson, V.

2014-01-01

Terra and Aqua MODIS have successfully operated for over 14 and 12 years since their respective launches in 1999 and 2002. The MODIS on-orbit calibration is performed using a set of on-board calibrators, which include a solar diffuser for calibrating the reflective solar bands (RSB) and a blackbody for the thermal emissive bands (TEB). On-orbit changes in the sensor responses as well as key performance parameters are monitored using the measurements of these on-board calibrators. This paper provides an overview of MODIS on-orbit operation and calibration activities, and instrument long-term performance. It presents a brief summary of the calibration enhancements made in the latest MODIS data collection 6 (C6). Future improvements in the MODIS calibration and their potential applications to the S-NPP VIIRS are also discussed.

Assessment of MODIS and VIIRS Solar Diffuser On-Orbit Degradation

NASA Technical Reports Server (NTRS)

Xiong, Xiaoxiong; Fulbright, Jon; Angal, Amit; Wang, Zhipeng; Geng, Xu; Butler, Jim

2015-01-01

Both MODIS and VIIRS instruments use a solar diffuser (SD) for their reflective solar bands (RSB) on-orbit calibration. On-orbit changes in SD bi-directional reflectance factor (BRF) are tracked by a solar diffuser stability monitor (SDSM) using its alternate measurements of the sunlight reflected off the SD panel and direct sunlight through a fixed attenuation screen. The SDSM calibration data are collected by a number of filtered detectors, covering wavelengths from 0.41 to 0.94 micrometers. In this paper we describe briefly the Terra and Aqua MODIS and S-NPP VIIRS SDSM on-orbit operation and calibration activities and strategies, provide an overall assessment of their SDSM on-orbit performance, including wavelength-dependent changes in the SDSM detector responses and changes in their SD BRF, and discuss remaining challenging issues and their potential impact on RSB calibration quality. Due to different launch dates, operating configurations, and calibration frequencies, the Terra and Aqua MODIS and S-NPP VIIRS SD have experienced different amount of SD degradation. However, in general the shorter the wavelength, the larger is the SD on-orbit degradation. On the other hand, the larger changes in SDSM detector responses are observed at longer wavelengths in the near infrared (NIR).

Assessment of MODIS and VIIRS solar diffuser on-orbit degradation

NASA Astrophysics Data System (ADS)

Xiong, Xiaoxiong; Fulbright, Jon; Angal, Amit; Wang, Zhipeng; Geng, Xu; Butler, Jim

2015-09-01

Both MODIS and VIIRS instruments use a solar diffuser (SD) for their reflective solar bands (RSB) on-orbit calibration. On-orbit changes in SD bi-directional reflectance factor (BRF) are tracked by a solar diffuser stability monitor (SDSM) using its alternate measurements of the sunlight reflected off the SD panel and direct sunlight through a fixed attenuation screen. The SDSM calibration data are collected by a number of filtered detectors, covering wavelengths from 0.41 to 0.94μm. In this paper we describe briefly the Terra and Aqua MODIS and S-NPP VIIRS SDSM on-orbit operation and calibration activities and strategies, provide an overall assessment of their SDSM on-orbit performance, including wavelength-dependent changes in the SDSM detector responses and changes in their SD BRF, and discuss remaining challenging issues and their potential impact on RSB calibration quality. Due to different launch dates, operating configurations, and calibration frequencies, the Terra and Aqua MODIS and S-NPP VIIRS SD have experienced different amount of SD degradation. However, in general the shorter the wavelength, the larger is the SD on-orbit degradation. On the other hand, the larger changes in SDSM detector responses are observed at longer wavelengths in the near infrared (NIR).

Comparison of in-situ measurements and satellite-derived surface emissivity over Italian volcanic areas

NASA Astrophysics Data System (ADS)

Silvestri, Malvina; Musacchio, Massimo; Cammarano, Diego; Fabrizia Buongiorno, Maria; Amici, Stefania; Piscini, Alessandro

2016-04-01

In this work we compare ground measurements of emissivity collected during dedicated fields campaign on Mt. Etna and Solfatara of Pozzuoli volcanoes and acquired by means of Micro-FTIR (Fourier Thermal Infrared spectrometer) instrument with the emissivity obtained by using single ASTER data (Advanced Spaceborne Thermal Emission and Reflection Radiometer, ASTER 05) and the ASTER emissivity map extract from ASTER Global Emissivity Database (GED), released by LP DAAC on April 2, 2014. The database was developed by the National Aeronautics and Space Administration's (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology. The database includes land surface emissivity derived from ASTER data acquired over the contiguous United States, Africa, Arabian Peninsula, Australia, Europe, and China. Through this analysis we want to investigate the differences existing between the ASTER-GED dataset (average from 2000 to 2008 seasoning independent) and fall in-situ emissivity measurement. Moreover the role of different spatial resolution characterizing ASTER and MODIS, 90mt and 1km respectively, by comparing them with in situ measurements, is analyzed. Possible differences can be due also to the different algorithms used for the emissivity estimation, Temperature and Emissivity Separation algorithm for ASTER TIR band( Gillespie et al, 1998) and the classification-based emissivity method (Snyder and al, 1998) for MODIS. Finally land surface temperature products generated using ASTER-GED and ASTER 05 emissivity are also analyzed. Gillespie, A. R., Matsunaga, T., Rokugawa, S., & Hook, S. J. (1998). Temperature and emissivity separation from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. IEEE Transactions on Geoscience and Remote Sensing, 36, 1113-1125. Snyder, W.C., Wan, Z., Zhang, Y., & Feng, Y.-Z. (1998). Classification-based emissivity for land surface temperature measurement from space. International Journal of Remote Sensing, 19, 2753-2574.

Albedo indicating land degradation around the Badain Jaran Desert for better land resources utilization.

PubMed

Liu, Fengshan; Chen, Ying; Lu, Haiying; Shao, Hongbo

2017-02-01

Surface albedo is an easy access parameter in reflecting the status of both human disturbed soil and indirectly influenced area, whose characteristic is an important indicator in sustainable development under the background of global climate change. In this study, we employed meteorological data, MODIS 8-day BRDF/Albedo and LAI products from 2000 to 2014 to show the amelioration and mechanism around the Badain Jaran Desert. Results showed that the human-dominated afforestation activities significantly increased the leaf area index (LAI) in summer and autumn. Lower reflectance at visible band was sensed inside the desert compared with the ecozone and the lowest albedo at forested area. The contribution of soil and vegetation reflectance to surface albedo determined the linear sensitivity of albedo to LAI variation. Decreased albedo dominated the spatial-temporal pattern of the Badain Jaran Desert. This study suggested that surface albedo can be regarded as a useful index in indicating the change process and evaluating the sustainable development of biological management around the Badain Jaran Desert. Copyright © 2016. Published by Elsevier B.V.

Summary of Terra and Aqua MODIS Long-Term Performance

NASA Technical Reports Server (NTRS)

Xiong, Xiaoxiong (Jack); Wenny, Brian N.; Angal, Amit; Barnes, William; Salomonson, Vincent

2011-01-01

Since launch in December 1999, the MODIS ProtoFlight Model (PFM) onboard the Terra spacecraft has successfully operated for more than 11 years. Its Flight Model (FM) onboard the Aqua spacecraft, launched in May 2002, has also successfully operated for over 9 years. MODIS observations are made in 36 spectral bands at three nadir spatial resolutions and are calibrated and characterized regularly by a set of on-board calibrators (OBC). Nearly 40 science products, supporting a variety of land, ocean, and atmospheric applications, are continuously derived from the calibrated reflectances and radiances of each MODIS instrument and widely distributed to the world-wide user community. Following an overview of MODIS instrument operation and calibration activities, this paper provides a summary of both Terra and Aqua MODIS long-term performance. Special considerations that are critical to maintaining MODIS data quality and beneficial for future missions are also discussed.

Near Real-time Operational Use of eMODIS Expedited NDVI for Monitoring Applications and Famine Early Warning

NASA Astrophysics Data System (ADS)

Rowland, J.; Budde, M. E.

2010-12-01

The Famine Early Warning Systems Network (FEWS NET) has requirements for near real-time monitoring of vegetation conditions for food security applications. Accurate and timely assessments of crop conditions are an important element of food security decision making. FEWS NET scientists at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center are utilizing a new Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) dataset for operational monitoring of crop and pasture conditions in parts of the world where food availability is highly dependent on subsistence agriculture and animal husbandry. The expedited MODIS, or eMODIS, production system processes NDVI data using MODIS surface reflectance provided by the Land Atmosphere Near-real-time Capability for EOS (LANCE). Benefits of this production system include customized compositing schedules, near real-time data availability, and minimized re-sampling. FEWS NET has implemented a 10-day compositing scheme every five days to accommodate the need for timely information on vegetation conditions. The data are currently being processed at 250-meter spatial resolution for Central America, Hispaniola, and Africa. Data are further enhanced by the application of a temporal smoothing filter which helps remove contamination due to clouds and other atmospheric effects. The results of this near real-time monitoring capability have been the timely provision of NDVI and NDVI anomaly maps for each of the FEWS NET monitoring regions and the availability of a consistently processed dataset to aid crop assessment missions and to facilitate customized analyses of crop production, drought, and agro-pastoral conditions.

A cross comparison of spatiotemporally enhanced springtime phenological measurements from satellites and ground in a northern U.S. mixed forest

USGS Publications Warehouse

Liang, Liang; Schwartz, Mark D.; Zhuosen Wang,; Gao, Feng; Schaaf, Crystal B.; Bin Tan,; Morisette, Jeffrey T.; Zhang, Xiaoyang

2014-01-01

Cross comparison of satellite-derived land surface phenology (LSP) and ground measurements is useful to ensure the relevance of detected seasonal vegetation change to the underlying biophysical processes. While standard 16-day and 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI)-based springtime LSP has been evaluated in previous studies, it remains unclear whether LSP with enhanced temporal and spatial resolutions can capture additional details of ground phenology. In this paper, we compared LSP derived from 500-m daily MODIS and 30-m MODIS-Landsat fused VI data with landscape phenology (LP) in a northern U.S. mixed forest. LP was previously developed from intensively observed deciduous and coniferous tree phenology using an upscaling approach. Results showed that daily MODIS-based LSP consistently estimated greenup onset dates at the study area (625 m × 625 m) level with 4.48 days of mean absolute error (MAE), slightly better than that of using 16-day standard VI (4.63 days MAE). For the observed study areas, the time series with increased number of observations confirmed that post-bud burst deciduous tree phenology contributes the most to vegetation reflectance change. Moreover, fused VI time series demonstrated closer correspondences with LP at the community level (0.1-20 ha) than using MODIS alone at the study area level (390 ha). The fused LSP captured greenup onset dates for respective forest communities of varied sizes and compositions with four days of the overall MAE. This study supports further use of spatiotemporally enhanced LSP for more precise phenological monitoring.

Land cover mapping of Greater Mesoamerica using MODIS data

USGS Publications Warehouse

Giri, Chandra; Jenkins, Clinton N.

2005-01-01

A new land cover database of Greater Mesoamerica has been prepared using moderate resolution imaging spectroradiometer (MODIS, 500 m resolution) satellite data. Daily surface reflectance MODIS data and a suite of ancillary data were used in preparing the database by employing a decision tree classification approach. The new land cover data are an improvement over traditional advanced very high resolution radiometer (AVHRR) based land cover data in terms of both spatial and thematic details. The dominant land cover type in Greater Mesoamerica is forest (39%), followed by shrubland (30%) and cropland (22%). Country analysis shows forest as the dominant land cover type in Belize (62%), Cost Rica (52%), Guatemala (53%), Honduras (56%), Nicaragua (53%), and Panama (48%), cropland as the dominant land cover type in El Salvador (60.5%), and shrubland as the dominant land cover type in Mexico (37%). A three-step approach was used to assess the quality of the classified land cover data: (i) qualitative assessment provided good insight in identifying and correcting gross errors; (ii) correlation analysis of MODIS- and Landsat-derived land cover data revealed strong positive association for forest (r2 = 0.88), shrubland (r2 = 0.75), and cropland (r2 = 0.97) but weak positive association for grassland (r2 = 0.26); and (iii) an error matrix generated using unseen training data provided an overall accuracy of 77.3% with a Kappa coefficient of 0.73608. Overall, MODIS 500 m data and the methodology used were found to be quite useful for broad-scale land cover mapping of Greater Mesoamerica.

Estimation of Canopy Clumping Index From MISR and MODIS Sensors Using the Normalized Difference Hotspot and Darkspot (NDHD) Method: The Influence of BRDF Models and Solar Zenith Angle

NASA Astrophysics Data System (ADS)

Wei, S.; Fang, H.

2016-12-01

The Clumping index (CI) describes the spatial distribution pattern of foliage, and is a critical parameter used to characterize the terrestrial ecosystem and model land-surface processes. Global and regional scale CI maps have been generated from POLDER, MODIS, and MISR sensors based on an empirical relationship with the normalized difference between hotspot and darkspot (NDHD) index by previous studies. However, the hotspot and darkspot values and CI values can be considerably different from different bidirectional reflectance distribution function (BRDF) models and solar zenith angles (SZA). In this study, we evaluated the effects of different configurations of BRDF models and SZA values on CI estimation using the NDHD method. CI maps estimated from MISR and MODIS were compared with reference data at the VALERI sites. Results show that for moderate to least clumped vegetation (CI > 0.5), CIs retrieved with the observational SZA agree well with field values, while SZA =0° results in underestimates, and SZA = 60° results in overestimates. For highly clumped (CI < 0.5) and sparsely vegetated areas (FCOVER<25%), the Ross-Li model with 60° SZA is recommended for CI estimation. The suitable NDHD configuration was further used to estimate a 15-year time series CI from MODIS BRDF data. The time series CI shows a reasonable seasonal trajectory, and varies consistently with the MODIS leaf area index (LAI). This study enables better usage of the NDHD method for CI estimation, and can be a useful reference for research on CI validation.

NPP VIIRS and Aqua MODIS RSB Comparison Using Observations from Simultaneous Nadir Overpasses (SNO)

NASA Technical Reports Server (NTRS)

Xiong, X.; Wu, A.

2012-01-01

Suomi NPP (National Polar-orbiting Partnership) satellite (http://npp.gsfc.nasa.gov/viirs.html) began to daily collect global data following its successful launch on October 28, 2011. The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key NPP sensor. Similar to the design of the OLS, SeaWiFS and MODIS instruments, VIIRS has on-board calibration components including a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) for the reflective solar bands (RSB), a V-groove blackbody for the thermal emissive bands (TEB), and a space view (SV) port for background subtraction. Immediately after the VIIRS nadir door s opening on November 21, 2011, anomalously large degradation in the SD response was identified in the near-IR wavelength region, which was unexpected as decreases in the SD reflectance usually occur gradually in the blue (0.4 m) wavelength region based on past experience. In this study, we use a well-calibrated Aqua MODIS as reference to track and evaluate VIIRS RSB stability and performance. Reflectances observed by both sensors from simultaneous nadir overpasses (SNO) are used to determine VIIRS to MODIS reflectance ratios for their spectral matching bands. Results of this study provide an immediate post-launch assessment, independent validation of the anomalous degradation observed in SD measurements at near-IR wavelengths and initial analysis of calibration stability and consistency.

MODIS calibration

NASA Technical Reports Server (NTRS)

Barker, John L.

1992-01-01

The MODIS/MCST (MODIS Characterization Support Team) Status Report contains an outline of the calibration strategy, handbook, and plan. It also contains an outline of the MODIS/MCST action item from the 4th EOS Cal/Val Meeting, for which the objective was to locate potential MODIS calibration targets on the Earth's surface that are radiometrically homogeneous on a scale of 3 by 3 Km. As appendices, draft copies of the handbook table of contents, calibration plan table of contents, and detailed agenda for MODIS calibration working group are included.

Results and lessons learned from MODIS polarization sensitivity characterization

NASA Astrophysics Data System (ADS)

Sun, J.; Xiong, X.; Wang, X.; Qiu, S.; Xiong, S.; Waluschka, E.

2006-08-01

In addition to radiometric, spatial, and spectral calibration requirements, MODIS design specifications include polarization sensitivity requirements of less than 2% for all Reflective Solar Bands (RSB) except for the band centered at 412nm. To the best of our knowledge, MODIS was the first imaging radiometer that went through comprehensive system level (end-to-end) polarization characterization. MODIS polarization sensitivity was measured pre-launch at a number of sensor view angles using a laboratory Polarization Source Assembly (PSA) that consists of a rotatable source, a polarizer (Ahrens prism design), and a collimator. This paper describes MODIS polarization characterization approaches used by MODIS Characterization Support Team (MCST) at NASA/GSFC and addresses issues and concerns in the measurements. Results (polarization factor and phase angle) using different analyzing methods are discussed. Also included in this paper is a polarization characterization comparison between Terra and Aqua MODIS. Our previous and recent analysis of MODIS RSB polarization sensitivity could provide useful information for future Earth-observing sensor design, development, and characterization.

Comparison of Land Skin Temperature from a Land Model, Remote Sensing, and In-situ Measurement

NASA Technical Reports Server (NTRS)

Wang, Aihui; Barlage, Michael; Zeng, Xubin; Draper, Clara Sophie

2014-01-01

Land skin temperature (Ts) is an important parameter in the energy exchange between the land surface and atmosphere. Here hourly Ts from the Community Land Model Version 4.0, MODIS satellite observations, and in-situ observations in 2003 were compared. Compared with the in-situ observations over four semi-arid stations, both MODIS and modeled Ts show negative biases, but MODIS shows an overall better performance. Global distribution of differences between MODIS and modeled Ts shows diurnal, seasonal, and spatial variations. Over sparsely vegetated areas, the model Ts is generally lower than the MODIS observed Ts during the daytime, while the situation is opposite at nighttime. The revision of roughness length for heat and the constraint of minimum friction velocity from Zeng et al. [2012] bring the modeled Ts closer to MODIS during the day, and have little effect on Ts at night. Five factors contributing to the Ts differences between the model and MODIS are identified, including the difficulty in properly accounting for cloud cover information at the appropriate temporal and spatial resolutions, and uncertainties in surface energy balance computation, atmospheric forcing data, surface emissivity, and MODIS Ts data. These findings have implications for the cross-evaluation of modeled and remotely sensed Ts, as well as the data assimilation of Ts observations into Earth system models.

Evaluation of GLI Reflectance and Vegetation Indices With MODIS Products

DTIC Science & Technology

2005-07-25

collective picture of a warming world and other changes in the climate system . Vegetation over land surfaces contains carbon that is re- leased to atmosphere...irradiance based on Thuiller 2002 (Thuiller et al., 2003), Lsat[W/m2/str/µm] is GLI observed radiance, and θs[rad] is solor zenith angle. The GLI Project...longer wavelength than 2500nm, MODTRAN4.0 IR solor irradiance is used. GLI atmospheric correction for land is conducted for Rayleigh scattering and

Land Surface Temperature Measurements form EOS MODIS Data

NASA Technical Reports Server (NTRS)

Wan, Zhengming

1996-01-01

We have developed a physics-based land-surface temperature (LST) algorithm for simultaneously retrieving surface band-averaged emissivities and temperatures from day/night pairs of MODIS (Moderate Resolution Imaging Spectroradiometer) data in seven thermal infrared bands. The set of 14 nonlinear equations in the algorithm is solved with the statistical regression method and the least-squares fit method. This new LST algorithm was tested with simulated MODIS data for 80 sets of band-averaged emissivities calculated from published spectral data of terrestrial materials in wide ranges of atmospheric and surface temperature conditions. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the new LST algorithm and its dependence on variations in surface emissivity and temperature, upon atmospheric conditions, as well as the noise-equivalent temperature difference (NE(Delta)T) and calibration accuracy specifications of the MODIS instrument. In cases with a systematic calibration error of 0.5%, the standard deviations of errors in retrieved surface daytime and nighttime temperatures fall between 0.4-0.5 K over a wide range of surface temperatures for mid-latitude summer conditions. The standard deviations of errors in retrieved emissivities in bands 31 and 32 (in the 10-12.5 micrometer IR spectral window region) are 0.009, and the maximum error in retrieved LST values falls between 2-3 K. Several issues related to the day/night LST algorithm (uncertainties in the day/night registration and in surface emissivity changes caused by dew occurrence, and the cloud cover) have been investigated. The LST algorithms have been validated with MODIS Airborne Simulator (MAS) dada and ground-based measurement data in two field campaigns conducted in Railroad Valley playa, NV in 1995 and 1996. The MODIS LST version 1 software has been delivered.

Monitoring Invasive Aquatic Vegetation in Lake Okeechobee, Florida, Using NDVI Derived from Modis Data

NASA Technical Reports Server (NTRS)

Woods, Kate; Brozen, Madeline; Malik, Sadaf; Maki, Angela

2009-01-01

Lake Okeechobee, located in southern Florida, encompasses approximately 1,700 sq km and is a vital part of the Lake Okeechobee and Everglades ecosystem. Major cyanobacterial blooms have been documented in Lake Okeechobee since the 1970s and have continued to plague the ecosystem. Similarly, hydrilla, water hyacinth, and water lettuce have been documented in the lake and continue to threaten the ecosystem by their rapid growth. This study examines invasive aquatic vegetation occurrence through the use of the Normalized Difference Vegetation Index (NDVI) calculated on MOD09 surface reflectance imagery. Occurrence during 2008 was analyzed using the Time Series Product Tool (TSPT), a MATLAB-based program developed at John C. Stennis Space Center. This project tracked spatial and temporal variability of cyanobacterial blooms, and overgrowth of water lettuce, water hyacinth, and hydrilla. In addition, this study presents an application of Moderate Resolution Imaging Spectroradiometer (MODIS) data to assist in water quality management.

Terra MODIS Band 27 Electronic Crosstalk Effect and Its Removal

NASA Technical Reports Server (NTRS)

Sun, Junqiang; Xiong, Xiaoxiong; Madhavan, Sriharsha; Wenny, Brian

2012-01-01

The MODerate-resolution Imaging Spectroradiometer (MODIS) is one of the primary instruments in the NASA Earth Observing System (EOS). The first MODIS instrument was launched in December, 1999 on-board the Terra spacecraft. MODIS has 36 bands, covering a wavelength range from 0.4 micron to 14.4 micron. MODIS band 27 (6.72 micron) is a water vapor band, which is designed to be insensitive to Earth surface features. In recent Earth View (EV) images of Terra band 27, surface feature contamination is clearly seen and striping has become very pronounced. In this paper, it is shown that band 27 is impacted by electronic crosstalk from bands 28-30. An algorithm using a linear approximation is developed to correct the crosstalk effect. The crosstalk coefficients are derived from Terra MODIS lunar observations. They show that the crosstalk is strongly detector dependent and the crosstalk pattern has changed dramatically since launch. The crosstalk contributions are positive to the instrument response of band 27 early in the mission but became negative and much larger in magnitude at later stages of the mission for most detectors of the band. The algorithm is applied to both Black Body (BB) calibration and MODIS L1B products. With the crosstalk effect removed, the calibration coefficients of Terra MODIS band 27 derived from the BB show that the detector differences become smaller. With the algorithm applied to MODIS L1B products, the Earth surface features are significantly removed and the striping is substantially reduced in the images of the band. The approach developed in this report for removal of the electronic crosstalk effect can be applied to other MODIS bands if similar crosstalk behaviors occur.

Using the Sonoran Desert test site to monitor the long-term radiometric stability of the Landsat TM/ETM+ and Terra MODIS sensors

USGS Publications Warehouse

Angal, A.; Xiong, X.; Choi, T.; Chander, G.; Wu, A.

2009-01-01

Pseudo-invariant ground targets have been extensively used to monitor the long-term radiometric calibration stability of remote sensing instruments. The NASA MODIS Characterization Support Team (MCST), in collaboration with members from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, has previously demonstrated the use of pseudo-invariant ground sites for the long-term stability monitoring of Terra MODIS and Landsat 7 ETM+ sensors. This paper focuses on the results derived from observations made over the Sonoran Desert. Additionally, Landsat 5 TM data over the Sonoran Desert site were used to evaluate the temporal stability of this site. Top-ofatmosphere (TOA) reflectances were computed for the closely matched TM, ETM+, and MODIS spectral bands over selected regions of interest. The impacts due to different viewing geometries, or the effect of test site Bi-directional Reflectance Distribution Function (BRDF), are also presented. ?? 2009 SPIE.

Aerosol Direct Radiative Effect at the Top of the Atmosphere Over Cloud Free Ocean Derived from Four Years of MODIS Data

NASA Technical Reports Server (NTRS)

Remer, L. A.; Kaufman, Y. J.

2006-01-01

A four year record of MODIS spaceborne data provides a new measurement tool to assess the aerosol direct radiative effect at the top of the atmosphere. MODIS derives the aerosol optical thickness and microphysical properties from the scattered sunlight at 0.55-2.1 microns. The monthly MODIS data used here are accumulated measurements across a wide range of view and scattering angles and represent the aerosol s spectrally resolved angular properties. We use these data consistently to compute with estimated accuracy of +/-0.6W/sq m the reflected sunlight by the aerosol over global oceans in cloud free conditions. The MODIS high spatial resolution (0.5 km) allows observation of the aerosol impact between clouds that can be missed by other sensors with larger footprints. We found that over the clear-sky global ocean the aerosol reflected 5.3+/-0.6W/sq m with an average radiative efficiency of 49+/-2W/sq m per unit optical thickness. The seasonal and regional distribution of the aerosol radiative effects are discussed. The analysis adds a new measurement perspective to a climate change problem dominated so far by models.

Cell Adhesion and in Vivo Osseointegration of Sandblasted/Acid Etched/Anodized Dental Implants

PubMed Central

Kim, Mu-Hyon; Park, Kyeongsoon; Choi, Kyung-Hee; Kim, Soo-Hong; Kim, Se Eun; Jeong, Chang-Mo; Huh, Jung-Bo

2015-01-01

The authors describe a new type of titanium (Ti) implant as a Modi-anodized (ANO) Ti implant, the surface of which was treated by sandblasting, acid etching (SLA), and anodized techniques. The aim of the present study was to evaluate the adhesion of MG-63 cells to Modi-ANO surface treated Ti in vitro and to investigate its osseointegration characteristics in vivo. Four different types of Ti implants were examined, that is, machined Ti (control), SLA, anodized, and Modi-ANO Ti. In the cell adhesion study, Modi-ANO Ti showed higher initial MG-63 cell adhesion and induced greater filopodia growth than other groups. In vivo study in a beagle model revealed the bone-to-implant contact (BIC) of Modi-ANO Ti (74.20% ± 10.89%) was much greater than those of machined (33.58% ± 8.63%), SLA (58.47% ± 12.89), or ANO Ti (59.62% ± 18.30%). In conclusion, this study demonstrates that Modi-ANO Ti implants produced by sandblasting, acid etching, and anodizing improve cell adhesion and bone ongrowth as compared with machined, SLA, or ANO Ti implants. These findings suggest that the application of Modi-ANO surface treatment could improve the osseointegration of dental implant. PMID:25955650

Assessment of Provisional MODIS-derived Surfaces Related to the Global Carbon Cycle

NASA Astrophysics Data System (ADS)

Cohen, W. B.; Maiersperger, T. K.; Turner, D. P.; Gower, S. T.; Kennedy, R. E.; Running, S. W.

2002-12-01

The global carbon cycle is one of the most important foci of an emerging global biosphere monitoring system. A key component of such a system is the MODIS sensor, onboard the Terra satellite platform. Biosphere monitoring requires an integrated program of satellite observations, Earth-system models, and in situ data. Related to the carbon cycle, MODIS science teams routinely develop a variety of global surfaces such as land cover, leaf area index, and net primary production using MODIS data and functional algorithms. The quality of these surfaces must be evaluated to determine their effectiveness for global biosphere monitoring. A project called BigFoot (http://www.fsl.orst.edu/larse/bigfoot/) is an organized effort across nine biomes to assess the quality of the abovementioned surfaces: (1) Arctic tundra; (2) boreal evergreen needle-leaved forest; temperate (3) cropland, (4) grassland, (5) evergreen needle-leaved forest, and (6) deciduous broad-leaved forest; desert (7) grassland and (8) shrubland; and (9) tropical evergreen broad-leaved forest. Each biome is represented by a site that has an eddy-covariance flux tower that measures water vapor and CO2 fluxes. Flux tower footprints are relatively small-approximately 1 km2. BigFoot characterizes 25 km2 around each tower, using field data, Landsat ETM+ image data, and ecosystem process models. Our innovative field sampling design incorporates a nested spatial series to facilitate geostatistical analyses, samples the ecological variability at a site, and is logistically efficient. Field data are used both to develop site-specific algorithms for mapping/modeling the variables of interest and to characterize the errors in derived BigFoot surfaces. Direct comparisons of BigFoot- and MODIS-derived surfaces are made to help understand the sources of error in MODIS-derived surfaces and to facilitate improvements to MODIS algorithms. Results from four BigFoot sites will be presented.

a New Algorithm for the Aod Inversion from Noaa/avhrr Data

NASA Astrophysics Data System (ADS)

Sun, L.; Li, R.; Yu, H.

2018-04-01

The advanced very high resolution radiometer (AVHRR) data from the National Oceanic and Atmospheric Administration satellite is one of the earliest data applied in aerosol research. The dense dark vegetation (DDV) algorithm is a popular method for the present land aerosol retrieval. One of the most crucial steps in the DDV algorithm with AVHRR data is estimating the land surface reflectance (LSR). However, LSR cannot be easily estimated because of the lack of a 2.13 μm band. In this article, the moderate resolution imaging spectroradiometer (MODIS) vegetation index product (MYD13) is introduced to support the estimation of AVHRR LSR. The relationship between MODIS NDVI and the AVHRR LSR of the visible band is analysed to retrieve aerosol optical depth (AOD) from AVHRR data. Retrieval experiments are carried out in mid-eastern America. The AOD data from AErosol RObotic NETwork (AERONET) measurements are used to evaluate the aerosol retrieval from AVHRR data, the results indicate that about 74 % of the retrieved AOD are within the expected error range of ±(0.05 + 0.2), and a cross comparison of the AOD retrieval results with the MODIS aerosol product (MYD04) shows that the AOD datasets have a similar spatial distribution.

Global Validation of MODIS Atmospheric Profile-Derived Near-Surface Air Temperature and Dew Point Estimates

NASA Astrophysics Data System (ADS)

Famiglietti, C.; Fisher, J.; Halverson, G. H.

2017-12-01

This study validates a method of remote sensing near-surface meteorology that vertically interpolates MODIS atmospheric profiles to surface pressure level. The extraction of air temperature and dew point observations at a two-meter reference height from 2001 to 2014 yields global moderate- to fine-resolution near-surface temperature distributions that are compared to geographically and temporally corresponding measurements from 114 ground meteorological stations distributed worldwide. This analysis is the first robust, large-scale validation of the MODIS-derived near-surface air temperature and dew point estimates, both of which serve as key inputs in models of energy, water, and carbon exchange between the land surface and the atmosphere. Results show strong linear correlations between remotely sensed and in-situ near-surface air temperature measurements (R2 = 0.89), as well as between dew point observations (R2 = 0.77). Performance is relatively uniform across climate zones. The extension of mean climate-wise percent errors to the entire remote sensing dataset allows for the determination of MODIS air temperature and dew point uncertainties on a global scale.

On the Use of Deep Convective Clouds to Characterize Response versus Scan-angle for MODIS Reflective Solar Bands

NASA Astrophysics Data System (ADS)

Bhatt, R.; Doelling, D. R.; Scarino, B. R.; Gopalan, A.; Haney, C.

2016-12-01

MODIS is a cross-track scanning radiometer with a two-sided scan mirror that images the Earth with an angular field of view of 55° on either side of the nadir. The reflectance of the scan mirror is not uniform and is a function of angle of incidence (AOI), as well as wavelength. This feature of the scan mirror is described by response versus scan-angle (RVS), and was characterized for all reflective solar bands (RSBs), for both MODIS instruments prior to launch. The RVS characteristic of the two MODIS instruments has changed on orbit and, therefore, must be tracked precisely over time to ensure high-quality data in the MODIS products. The MODIS Characterization Support Team (MCST) utilizes the onboard solar diffuser (SD) and lunar measurements to track the RVS changes at two fixed AOIs. The RVS at the remaining AOIs is characterized using the earth view (EV) responses from multiple pseudo-invariant desert sites located in Northern Africa. The drawback of this approach is the assumption that all of the desert sites imaged by the MODIS sensors at different AOIs are radiometrically stable during the same period of time. In addition, the desert samples do not always have continuous AOI coverage as they are limited by the 16-day repeat cycle of the satellite orbit, and by clear-sky conditions over the deserts. This paper proposes a novel and robust approach of characterizing the MODIS RVS using tropical deep convective clouds (DCCs) as an invariant calibration target. The method tracks the monthly DCC response at specified sets of AOIs to compute the temporal RVS changes. Because DCCs are distributed across the entirety of the tropics, they provide a continuum of AOI measurements. Initial results have shown that the Aqua-MODIS Collection 6 band 1 level 1b radiances show considerable residual, or artifact, RVS dependencies, especially on the left side of the cross-track scan. Long-term drifts, up to 2.3%, have been observed at certain AOIs. Temporal correction factors are computed using the DCC trends from 12 scan intervals encompassing all AOIs, and their effectiveness in correcting the observed RVS artifact is evaluated using the Libya-1 pseudo-invariant desert site. The desert and DCC temporal scan dependent trends are reduced to less than 1 standard error after the RVS correction.

Discriminating heavy aerosol, clouds, and fires during SCAR-B: Application of airborne multispectral MAS data

NASA Astrophysics Data System (ADS)

King, Michael D.; Tsay, Si-Chee; Ackerman, Steven A.; Larsen, North F.

1998-12-01

A multispectral scanning spectrometer was used to obtain measurements of the reflection function and brightness temperature of smoke, clouds, and terrestrial surfaces at 50 discrete wavelengths between 0.55 and 14.2 μm. These observations were obtained from the NASA ER-2 aircraft as part of the Smoke, Clouds, and Radiation-Brazil (SCAR-B) campaign, conducted over a 1500×1500 km region of cerrado and rain forest throughout Brazil between August 16 and September 11, 1995. Multispectral images of the reflection function and brightness temperature in 10 distinct bands of the MODIS airborne simulator (MAS) were used to derive a confidence in clear sky (or alternatively the probability of cloud), shadow, fire, and heavy aerosol. In addition to multispectral imagery, monostatic lidar data were obtained along the nadir ground track of the aircraft and used to assess the accuracy of the cloud mask results. This analysis shows that the cloud and aerosol mask being developed for operational use on the moderate-resolution imaging spectroradiometer (MODIS), and tested using MAS data in Brazil, is quite capable of separating cloud, aerosol, shadow, and fires during daytime conditions over land.

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Comiso, Josefino C.; DiGirolamo, Nicolo E.; Shuman, Christopher A.; Key, Jeffrey R.; Koenig, Lora S.

2011-01-01

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly Terra MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid within +/-3 hours of 17:00Z or 2:00 PM Local Solar Time. Preliminary validation of the ISTs at Summit Camp, Greenland, during the 2008-09 winter, shows that there is a cold bias using the MODIS IST which underestimates the measured surface temperature by approximately 3 C when temperatures range from approximately -50 C to approximately -35 C. The ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present. Differences in the APP and MODIS cloud masks have so far precluded the current IST records from spanning both the APP and MODIS IST time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The Greenland IST climate-quality data record is suitable for continuation using future Visible Infrared Imager Radiometer Suite (VIIRS) data and will be elevated in status to a CDR when at least 9 more years of climate-quality data become available either from MODIS Terra or Aqua, or from the VIIRS. The complete MODIS IST data record will be available online in the summer of 2011.

Calibration Challenges and Improvements for Terra and Aqua MODIS Level-1B Data Product Qualit

NASA Astrophysics Data System (ADS)

Xiong, X.; Angal, A.; Chen, H.; Geng, X.; Li, Y.; Link, D.; Salomonson, V.; Twedt, K.; Wang, Z.; Wilson, T.; Wu, A.

2017-12-01

Terra and Aqua MODIS instruments launched in 1999 and 2002, respectively, have provided the remote sensing community and users worldwide a series of high quality long-term data records. They have enabled a broad range of scientific studies of the Earth's system and changes in its key geophysical and environmental parameters. To date, both MODIS instruments continue to operate nominally with all on-board calibrators (OBC) functioning properly. MODIS reflective solar bands (RSB) are currently calibrated by a solar diffuser (SD) and solar diffuser stability monitor (SDSM) system, coupled with regularly scheduled lunar observations and trending results from selected ground reference targets. The thermal emissive bands (TEB) calibration is performed using an on-board blackbody (BB) on a scan-by-scan basis. The sensor's spectral and spatial characteristics are periodically tracked by the on-board spectroradiometric calibration assembly (SRCA). On-orbit changes in sensor responses or performance characteristics, often in non-deterministic ways, underscore the need for dedicated calibration efforts to be made over the course of the sensor's entire mission. For MODIS instruments, this task has been undertaken by the MODIS Characterization Support Team (MCST). In this presentation, we provide an overview of MODIS instrument operation and calibration activities with a focus on recent challenging issues. We describe the efforts made and methodologies developed to address various challenging issues, including on-orbit characterization of sensor response versus scan angle (RVS) and polarization sensitives in the reflective solar spectral region, and electronic crosstalk impact on sensor calibration. Also discussed are the latest improvements made into the MODIS Level-1B data products as well as lessons that could benefit other instruments (e.g. VIIRS) for their on-orbit calibration and characterization.

Sensor On-orbit Calibration and Characterization Using Spacecraft Maneuvers

NASA Technical Reports Server (NTRS)

Xiong, X.; Butler, Jim; Barnes, W. L.; Guenther, B.

2007-01-01

Spacecraft flight operations often require activities that involve different kinds of maneuvers for orbital adjustments (pitch, yaw, and roll). Different maneuvers, when properly planned and scheduled, can also be applied to support and/or to perform on-board sensor calibration and characterization. This paper uses MODIS (Moderate Resolution Imaging Spectroradiometer) as an example to illustrate applications of spacecraft maneuvers for Earth-observing sensors on-orbit calibration and characterization. MODIS is one of the key instruments for NASA's Earth Observing System (EOS) currently operated on-board the EOS Terra and Aqua spacecraft launched in December 1999 and May 2002, respectively. Since their launch, both Terra and Aqua spacecraft have made a number of maneuvers, specially the yaw and roll maneuvers, to support the MODIS on-orbit calibration and characterization. For both Terra and Aqua MODIS, near-monthly spacecraft roll maneuvers are executed for lunar observations. These maneuvers are carefully scheduled so that the lunar phase angles are nearly identical for each sensor's lunar observations. The lunar observations are used to track MODIS reflective solar bands (RSB) calibration stability and to inter-compare Terra and Aqua MODIS RSB calibration consistency. To date, two sets of yaw maneuvers (each consists of two series of 8 consecutive yaws) by the Terra spacecraft and one set by the Aqua spacecraft have been performed to validate MODIS solar diffuser (SD) bi-directional reflectance factor (BRF) and to derive SD screen transmission. Terra spacecraft pitch maneuvers, first made on March 26, 2003 and the second on April 14, 2003 (with the Moon in the spacecraft nadir view), have been applied to characterize MODIS thermal emissive bands (TEB) response versus scan angle (RVS). This is particularly important since the pre-launch TEB RSV measurements made by the sensor vendor were not successful. Terra MODIS TEB RVS obtained from pitch maneuvers have been used in the current LIB calibration algorithm. Lunq observations from pitch maneuvers also provided information to cross-calibrate MODIS with other sensors (MISR and ASTER) on the same platform. We will provide a summary of MODIS maneuver activities and their applications for MODIS calibration and characterization. The results and lessons learned discussed in this paper from MODIS maneuver activities will provide useful insights into future spacecraft and sensor operation.

Cloud Retrieval Information Content Studies with the Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Ocean Color Imager (OCI)

NASA Astrophysics Data System (ADS)

Coddington, Odele; Platnick, Steven; Pilewskie, Peter; Schmidt, Sebastian

2016-04-01

The NASA Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Science Definition Team (SDT) report released in 2012 defined imager stability requirements for the Ocean Color Instrument (OCI) at the sub-percent level. While the instrument suite and measurement requirements are currently being determined, the PACE SDT report provided details on imager options and spectral specifications. The options for a threshold instrument included a hyperspectral imager from 350-800 nm, two near-infrared (NIR) channels, and three short wave infrared (SWIR) channels at 1240, 1640, and 2130 nm. Other instrument options include a variation of the threshold instrument with 3 additional spectral channels at 940, 1378, and 2250 nm and the inclusion of a spectral polarimeter. In this work, we present cloud retrieval information content studies of optical thickness, droplet effective radius, and thermodynamic phase to quantify the potential for continuing the low cloud climate data record established by the MOderate Resolution and Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) missions with the PACE OCI instrument (i.e., non-polarized cloud reflectances and in the absence of midwave and longwave infrared channels). The information content analysis is performed using the GEneralized Nonlinear Retrieval Analysis (GENRA) methodology and the Collection 6 simulated cloud reflectance data for the common MODIS/VIIRS algorithm (MODAWG) for Cloud Mask, Cloud-Top, and Optical Properties. We show that using both channels near 2 microns improves the probability of cloud phase discrimination with shortwave-only cloud reflectance retrievals. Ongoing work will extend the information content analysis, currently performed for dark ocean surfaces, to different land surface types.

Using EO-1 Hyperion to Simulate HyspIRI Products for a Coniferous Forest: The Fraction of PAR Absorbed by Chlorophyll (fAPAR(sub chl)) and Leaf Water Content (LWC)

NASA Technical Reports Server (NTRS)

Zhang, Qingyuan; Middleton, Elizabeth M.; Gao, Bo-Cai; Cheng, Yen-Ben

2011-01-01

This study presents development of prototype products for terrestrial ecosystems in preparation for the future imaging spectrometer planned for the Hyperspectral Infrared Imager (HyspIRI) mission. We present a successful demonstration example in a coniferous forest of two product prototypes: fraction of photosynthetic active radiation (PAR) absorbed by chlorophyll of a canopy (fAPAR(sub chl)) and leaf water content (LWC), for future HyspIRI implementation at 60 m spatial resolution. For this, we used existing 30 m resolution imaging spectrometer data available from the Earth Observing One (EO-1) Hyperion satellite to simulate and prototype the level one radiometrically corrected radiance (L1R) images expected from the HyspIRI visible through shortwave infrared spectrometer. The HyspIRI-like images were atmospherically corrected to obtain surface reflectance, and spectrally resampled to produce 60 m reflectance images for wavelength regions that were comparable to all seven of the MODerate resolution Imaging Spectroradiometer (MODIS) land bands. Thus, we developed MODIS-like surface reflectance in seven spectral bands at the HyspIRI-like spatial scale, which was utilized to derive fAPARchl and LWC with a coupled canopy-leaf radiative transfer model (PROSAIL2) for the coniferous forest[1]. With this study, we provide additional evidence that the fAPARchl product is more realistic for describing the physiologically active canopy than the traditional fAPAR parameter for the whole canopy (fAPAR(sub canopy)), and thus should replace it in ecosystem process models to reduce uncertainties in terrestrial carbon cycle studies and ecosystem studies.

Statistical Studies on Thin Cirrus from MODIS Data

NASA Technical Reports Server (NTRS)

Li, Rong-Rong; Kaufman, Yoram; Remer, Lorraine

2004-01-01

The 1.38 micron channel on the MODerate resolution Imaging Spectroradiomater (MODIS) is an ideal channel to identify and quantify thin cirrus on a global basis. This channel is used to produce the cirrus reflectance product in MOD06 and also used extensively by the MODIS aerosol algorithms to mask clouds for the MOD04 product. The aerosol product uses a lower threshold of the 1.38 micron channel reflectance of 0.01. A cirrus channel reflectance of 0.01 corresponds to approximately an aerosol optical thickness of 0.10. Therefore, the ambiguity due to the minor cirrus contamination may introduce artificial optical thickness in the aerosol products. The questions arise: How prevalent are the thinnest cirrus clouds over the globe? Do they persist over specific regions and seasons? Can we distinguish between the noise of the channel and the actual cloudiness by extrapolating the cloudiness signal to very dark scenes, statistically. We analyze the Terra data, over land and ocean to answer these questions.

Quality assessment of the Harmonized Landsat and Sentinel-2 (HLS) data set

NASA Astrophysics Data System (ADS)

Masek, J. G.; Claverie, M.; Ju, J.; Vermote, E.

2017-12-01

The Harmonized Landsat and Sentinel-2 (HLS) project is a NASA initiative aiming to produce a compatible surface reflectance (SR) data set from a virtual constellation consisting of the US Landsat-8 and the European Sentinel-2 satellites. The creation of such a long-term surface reflectance data record requires the development and implementation of Quality assessment (QA) methods to evaluate the quality of the product. QA is built as an integral part of the HLS production chain. The QA includes three components: (i) the comparison of the HLS data with MODIS data, (ii) an analysis of the geometric accuracy of the Landsat-8 OLI and Sentinel-2 MSI Level-1 products, and (iii) an evaluation of the temporal consistency of the HLS products.The methodology of the cross-comparison of the HLS product with MODIS products was introduced by Claverie et al. (2015, RSE, vol. 169). It consists in comparing HLS SR (L30 products for Landsat-8 and S30 products for Sentinel-2) with MODIS SR (MOD09CMG), after adjustment of sun-view geometry and bandpass differences. The overall uncertainties and biases between MODIS and HLS SR do not exceed, depending on the band (excluding blue bands), 9% and 3%, respectively. No significant spatial or temporal patterns were identified. The most important source of uncertainty comes from the cloud detection omission on the MSI data.The HLS and Level-1 products geometric accuracy was assessed and improved using the automated registration and orthorectification package, AROP (Gao et al., 2009, SPIE JARS, vol. 3). The use of AROP reduces the geometric co-registration error in Level-1 products by about 40% and 60% during HLS processing of OLI and MSI, respectively. The final CE-90 are 6.2 m and 18.8 m, for HLS MSI (computed with 10m pixels) and OLI (30 m pixels), respectively.Finally, the time series (TS) smoothness of the data set was analyzed by computing the time series noise (Vermote et al., 2009, TGRS, vol. 47). We showed that major issue is related to the MSI cloud mask quality. After filtering TS outliers, we demonstrated that the HLS TS noise (i.e., including MSI and OLI data) do not exceed 0.006 for the visible bands and 0.014 for the NIR and SWIR bands.

Correlations of oriented ice and precipitation in marine midlatitude low clouds using collocated CloudSat, CALIOP, and MODIS observations

NASA Astrophysics Data System (ADS)

Ross, Alexa; Holz, Robert E.; Ackerman, Steven A.

2017-08-01

In April 2006, the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) launched aboard the CALIPSO satellite and into the A-Train constellation of satellites with its transmitter pointed near nadir. This proved problematic due to specular reflection from horizontally oriented ice crystals occurring more frequently than expected. Because the specular backscatter from oriented ice crystals has large attenuated backscatter and almost no depolarization, the standard lidar inversions cannot be applied. To mitigate this issue, the CALIOP transmitter was moved to 3° off nadir in November 2007. Though problematic for global CALIOP retrievals, the sensitivity to oriented ice during the first year of observations provides a unique data set to investigate scenes of this ice crystal signature. This study focuses on the CALIOP-oriented signature that occurs in midlatitude ocean regions whose cloud tops are relatively warm and low, existing below 6 km. A significant seasonal dependence is found in the Northern Hemisphere with up to 19% of clouds below 6 km yielding specular reflection by CALIOP during the colder months. In contrast, the Southern Hemisphere lacks such seasonal dependence and sees fewer oriented ice crystals. Using collocated CloudSat observations with both CALIOP and Moderate Resolution Imaging Spectroradiometer (MODIS), we investigate the correlations of the oriented signature with MODIS cloud properties. Comparing with CloudSat precipitation retrievals, we find that the oriented signature is strongly correlated with surface precipitation with 64% of CALIOP-oriented ice crystal cases precipitating compared to 40% for nonoriented cases.

Enhancements to NASA's Land Atmosphere Near real-time Capability for EOS (LANCE)

NASA Astrophysics Data System (ADS)

Michael, K.; Davies, D. K.; Schmaltz, J. E.; Boller, R. A.; Mauoka, E.; Ye, G.; Vermote, E.; Harrison, S.; Rinsland, P. L.; Protack, S.; Durbin, P. B.; Justice, C. O.

2016-12-01

NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) supports application users interested in monitoring a wide variety of natural and man-made phenomena. Near Real-Time (NRT) data and imagery from the AIRS, AMSR2, MISR, MLS, MODIS, OMI and VIIRS instruments are available much quicker than routine processing allows. Most data products are available within 3 hours from satellite observation. NRT imagery are generally available 3-5 hours after observation. This article describes LANCE and enhancements made to LANCE over the last year. These enhancements include: the addition of MISR L1 Georeferenced Radiance and L2 Cloud Motion Vector products, AMSR2 Unified L2B Half-Orbit 25 km EASE-Grid Surface Soil Moisture products and VIIRS VIIRS Day/Night Band, Land Surface Reflectance and Corrected Surface reflectance products. In addition, the selection of LANCE NRT imagery that can be interactively viewed through Worldview and the Global Imagery Browse Services (GIBS) has been expanded. LANCE is also working to ingest and process data from OMPS.

A method for estimating the incident PAR on inclined surfaces

NASA Astrophysics Data System (ADS)

Xie, Xiaoping; Gao, Wei; Gao, Zhiqiang

2008-08-01

A new simple model has been developed that incorporates Digital Elevation Model (DEM) and Moderate Resolution Imaging Spectroradiometer (MODIS) products to produce incident photosynthetically active radiation (PAR) for tilted surface. The method is based on a simplification of the general radiative transfer equation, which considers five major processes of attenuation of solar radiation: 1) Rayleigh scattering, 2) absorption by ozone and water vapor, 3) aerosol scattering, 4) multiple reflectance between surface and atmosphere, and 5) three terrain factors: slope and aspect, isotropic sky view factor, and additional radiation by neighbor reflectance. A comparison of the model results with observational data from the Yucheng and Changbai Mountain sites of the Chinese Ecosystem Research Network (CERN) shows the correlation coefficient as 0.929 and 0.904, respectively. A comparison of the model results with the 2006 filed measured PAR in the Yucheng and Changbai sites shows the correlation coefficient as 0.929 and 0.904, respectively, and the average percent error as 10% and 15%, respectively.

Monitoring NEON terrestrial sites phenology with daily MODIS BRDF/albedo product and landsat data

USDA-ARS?s Scientific Manuscript database

The MODerate resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) and albedo products (MCD43) have already been in production for more than a decade. The standard product makes use of a linear “kernel-driven” RossThick-LiSparse Reciprocal (RTLSR) BRDF m...

BOREAS Level-2 MAS Surface Reflectance and Temperature Images in BSQ Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Newcomer, Jeffrey (Editor); Lobitz, Brad; Spanner, Michael; Strub, Richard; Lobitz, Brad

2000-01-01

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Aircraft Data Acquisition Program focused on providing the research teams with the remotely sensed aircraft data products they needed to compare and spatially extend point results. The MODIS Airborne Simulator (MAS) images, along with other remotely sensed data, were collected to provide spatially extensive information over the primary study areas. This information includes biophysical parameter maps such as surface reflectance and temperature. Collection of the MAS images occurred over the study areas during the 1994 field campaigns. The level-2 MAS data cover the dates of 21-Jul-1994, 24-Jul-1994, 04-Aug-1994, and 08-Aug-1994. The data are not geographically/geometrically corrected; however, files of relative X and Y coordinates for each image pixel were derived by using the C130 navigation data in a MAS scan model. The data are provided in binary image format files.

Land Surface Temperature Measurements from EOS MODIS Data

NASA Technical Reports Server (NTRS)

Wan, Zheng-Ming

2004-01-01

This report summarizes the accomplishments made by the MODIS LST (Land-Surface Temperature) group at University of California, Santa Barbara, under NASA Contract. Version 1 of the MODIS Land-Surface Temperature Algorithm Theoretical Basis Document (ATBD) was reviewed in June 1994, version 2 reviewed in November 1994, version 3.1 in August 1996, and version 3.3 updated in April 1999. Based on the ATBD, two LST algorithms were developed, one is the generalized split-window algorithm and another is the physics-based day/night LST algorithm. These two LST algorithms were implemented into the production generation executive code (PGE 16) for the daily standard MODIS LST products at level-2 (MODII-L2) and level-3 (MODIIA1 at 1 km resolution and MODIIB1 at 5km resolution). PGE codes for 8-day 1 km LST product (MODIIA2) and the daily, 8-day and monthly LST products at 0.05 degree latitude/longitude climate model grids (CMG) were also delivered. Four to six field campaigns were conducted each year since 2000 to validate the daily LST products generated by PGE16 and the calibration accuracies of the MODIS TIR bands used for the LST/emissivity retrieval from versions 2-4 of Terra MODIS data and versions 3-4 of Aqua MODIS data. Validation results from temperature-based and radiance-based methods indicate that the MODIS LST accuracy is better than 1 C in most clear-sky cases in the range from -10 to 58 C. One of the major lessons learn from multi- year temporal analysis of the consistent V4 daily Terra MODIS LST products in 2000-2003 over some selected target areas including lakes, snow/ice fields, and semi-arid sites is that there are variable numbers of cloud-contaminated LSTs in the MODIS LST products depending on surface elevation, land cover types, and atmospheric conditions. A cloud-screen scheme with constraints on spatial and temporal variations in LSTs was developed to remove cloud-contaminated LSTs. The 5km LST product was indirectly validated through comparisons to the 1 km LST product. Twenty three papers related to the LST research work were published in journals over the last decade.

Daytime Land Surface Temperature Extraction from MODIS Thermal Infrared Data under Cirrus Clouds

PubMed Central

Fan, Xiwei; Tang, Bo-Hui; Wu, Hua; Yan, Guangjian; Li, Zhao-Liang

2015-01-01

Simulated data showed that cirrus clouds could lead to a maximum land surface temperature (LST) retrieval error of 11.0 K when using the generalized split-window (GSW) algorithm with a cirrus optical depth (COD) at 0.55 μm of 0.4 and in nadir view. A correction term in the COD linear function was added to the GSW algorithm to extend the GSW algorithm to cirrus cloudy conditions. The COD was acquired by a look up table of the isolated cirrus bidirectional reflectance at 0.55 μm. Additionally, the slope k of the linear function was expressed as a multiple linear model of the top of the atmospheric brightness temperatures of MODIS channels 31–34 and as the difference between split-window channel emissivities. The simulated data showed that the LST error could be reduced from 11.0 to 2.2 K. The sensitivity analysis indicated that the total errors from all the uncertainties of input parameters, extension algorithm accuracy, and GSW algorithm accuracy were less than 2.5 K in nadir view. Finally, the Great Lakes surface water temperatures measured by buoys showed that the retrieval accuracy of the GSW algorithm was improved by at least 1.5 K using the proposed extension algorithm for cirrus skies. PMID:25928059

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Comiso, Josefino C.; DiGirolamo, Nikolo E.; Shuman, Christopher A.; Key, Jeffrey R.; Koenig, Lora S.

2012-01-01

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid. This record will be elevated in status to a CDR when at least nine more years of data become available either from MODIS Terra or Aqua, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Our ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present, and into the VIIRS era. Differences in the APP and MODIS cloud masks have so far precluded the current 1ST records from spanning both the APP and MODIS time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The complete MODIS 1ST daily and monthly data record is available online.

MODIS Global Sea Surface Temperature

NASA Technical Reports Server (NTRS)

2002-01-01

Every day the Moderate-resolution Imaging Spectroradiometer (MODIS) measures sea surface temperature over the entire globe with high accuracy. This false-color image shows a one-month composite for May 2001. Red and yellow indicates warmer temperatures, green is an intermediate value, while blues and then purples are progressively colder values. The new MODIS sea surface temperature product will be particularly useful in studies of temperature anomalies, such as El Nino, as well as research into how air-sea interactions drive changes in weather and climate patterns. In the high resolution image, notice the amazing detail in some of the regional current patterns. For instance, notice the cold water currents that move from Antarctica northward along South America's west coast. These cold, deep waters upwell along an equatorial swath around and to the west of the Galapagos Islands. Note the warm, wide currents of the Gulf Stream moving up the United States' east coast, carrying Caribbean warmth toward Newfoundland and across the Atlantic toward Western Europe. Note the warm tongue of water extending from Africa's east coast to well south of the Cape of Good Hope. MODIS was launched in December 1999 aboard NASA's Terra satellite. For more details on this and other MODIS data products, please see NASA Unveils Spectacular Suite of New Global Data Products from MODIS. Image courtesy MODIS Ocean Group, NASA GSFC, and the University of Miami

Analysis of Rosetta/VIRTIS spectra of earth using observations from ENVISAT/AATSR, TERRA/MODIS and ENVISAT/SCIAMACHY, and radiative-transfer simulations

NASA Astrophysics Data System (ADS)

Hurley, J.; Irwin, P. G. J.; Adriani, A.; Moriconi, M.; Oliva, F.; Capaccioni, F.; Smith, A.; Filacchione, G.; Tosi, F.; Thomas, G.

2014-01-01

Rosetta, the Solar System cornerstone mission of ESA's Horizon 2000 programme, consists of an orbiter and a lander, and is due to arrive at the comet 67P/Churyumov-Gerasimenko in May 2014. Following its 2004 launch, Rosetta carried out a series of planetary fly-bys and gravitational assists. On these close fly-bys of the Earth, measurements were taken by the Visible Infrared Thermal Imaging Spectrometer (VIRTIS). Analysis of these spectra and comparison with spectra acquired by Earth-observing satellites can support the verification of the inflight calibration of Rosetta/VIRTIS. In this paper, measurements taken by VIRTIS in November 2009 are compared with suitable coincident data from Earth-observing instruments (ESA-ENVISAT/AATSR and SCIAMACHY, and EOS-TERRA/MODIS). Radiative transfer simulations using NEMESIS (Irwin et al., 2008) are fit to the fly-by data taken by VIRTIS, using representative atmospheric and surface parameters. VIRTIS measurements correlate 90% with AATSR's, 85-94% with MODIS, and 82-88% with SCIAMACHYs. The VIRTIS spectra are reproducible in the 1-5 μm region, except in the 1.4 μm deep water vapour spectral absorption band in the near-infrared in cases in which the radiance is very low (cloud-free topographies), where VIRTIS consistently registers more radiance than do MODIS and SCIAMACHY. Over these cloud-free regions, VIRTIS registers radiances a factor of 3-10 larger than SCIAMACHY and of 3-8 greater than MODIS. It is speculated that this discrepancy could be due to a spectral light leak originating from reflections from the order-sorting filters above the detector around 1.4 μm.

Analyzing Relationships between Geochemical Composition, Spectral Reflectance, Broad-band Albedo and Thickness of Supra-glacial Tephra Deposits from the Eruptions of Eyafjallajökull and Grímsvötn Volcanoes in 2010 and 2011.

NASA Astrophysics Data System (ADS)

Möller, R.; Möller, M.; Kukla, P. A.; Schneider, C.; Römer, W.; Lehmkuhl, F.; Gudmundsson, M. T.

2016-12-01

On Iceland, explosive subglacial eruptions are common. The two latest eruptions were at Eyjafjallajökull 2010 and at Grímsvötn 2011. Both eruptions produced considerable amounts of tephra fallout that were deposited over large parts of major Icelandic ice caps. These extensive supraglacial tephra deposits are known to considerably alter the energy and mass balance of the ice caps at a strong spatial and temporal variability. We present a statistical evaluation of relationships and links between geochemistry, thermal conductivity, spectral reflectance characteristics, albedo and deposition thickness of the tephra covers and their variability in space and time. Samples of the tephra deposits were gathered in the field and analyzed in the laboratory regarding their chemical and mineralogical composition using X-ray fluorescence and diffraction analyses. Spatial patterns of spectral reflectance over the tephra-covered areas of the three major ice caps Eyjafjallajökull, Myrdalsjökull and Vatnajökull were obtained from multispectral ASTER and MODIS satellite datasets. Spatial patterns of broad-band albedo across the tephra-covered areas and differences to the albedo of unaffected surfaces were obtained from remotely-sensed data and geostatistical modeling. Changes in tephra-cover thickness with time were assessed using a modeling approach that includes thermal conductivity of the tephra cover and surface temperature. The former is derived from laboratory analysis while the latter is based on MODIS observations. We found that there are characteristic patterns of spectral reflectance that could be linked to deposition thickness and geochemical composition of the respective tephra. The temporal variability of the albedo patterns across the ice caps is strongly linked to the evolution of the deposition thicknesses over time.

Long-term Satellite Observations of Asian Dust Storm: Source, Pathway, and Interannual Variability

NASA Technical Reports Server (NTRS)

Hsu, N. Christina

2008-01-01

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. Outbreaks of Asian dust storms occur often in the arid and semi-arid areas of northwestern China -about 1.6x10(exp 6) square kilometers including the Gobi and Taklimakan deserts- with continuous expanding of spatial coverage. These airborne dust particles, originating in desert areas far from polluted regions, interact with anthropogenic sulfate and soot aerosols emitted from Chinese megacities during their transport over the mainland. Adding the intricate effects of clouds and marine aerosols, dust particles reaching the marine environment can have drastically different properties than those from their sources. Furthermore, these aerosols, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol properties (e.g., optical thickness, single scattering albedo) over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. This new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. Reasonable agreements have been achieved between Deep Blue retrievals of aerosol optical thickness and those directly from AERONET sunphotometers over desert and semi-desert regions. New Deep Blue products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments. Long-term satellite measurements (1998 - 2007) from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with the Asian dust storm outbreaks. In addition, monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

A simple estimate of ecosystem respiration across biomes based on MODIS products

NASA Astrophysics Data System (ADS)

Jaegermeyr, J.; Hostert, P.; Lucht, W.

2010-12-01

Beside carbon sequestration by terrestrial photosynthesis, in particular the subsequent carbon release by ecosystem respiration (Reco) is a crucial flux for estimating carbon budgets. Heterotrophic soil decomposition rates (Rh) and autotrophic respiration rates (Ra), which add up to Reco, are highly sensitive to environmental conditions and in some cases they determine net ecosystem productivity. Prior respiration modeling approaches revealed that a precise process-based and bottom-up modeling is important for realistic estimates. On a short timescale, as in the case of satellite environmental monitoring, simplified empirical models are not necessarily less accurate, though. For most major biomes, ecosystem carbon efflux is predominantly driven by air temperature. It can further be limited by water stress, plant activity and substrate quality. Developing simple, empirical and wall-to-wall respiration models from continuous Moderate Resolution Imaging Spectroradiometer (MODIS) land products on a continental scale can enhance our understanding of spatially explicit respiration patterns. We therefore accept model uncertainties by simplifying decay and respiratory processes in that we account for a single static carbon pool and do not include any feedback mechanisms. Preliminary results suggest that the 8-day MODIS 1km land surface temperature product (LST) and the vegetation-water index (NDWI) derived from the 8-day MODIS 500m surface reflectance product are sufficient to largely explain the variability of Reco. Spatial flux variations can be attributed to plant activity variation. We therefore introduce a site-specific, maximum leaf area index (LAI) from the MODIS 1km LAI product as a proxy. A biome-specific model parameterization and validation is performed, based on 8-day composite FLUXNET tower data representing major global biomes. We found that the frequently used temperature model by Loyd and Taylor (1994) does not show superior performance on 8-day ecosystem respiration data. The model by Del Grosso et al. (2005) is more flexible to account for lower Q10 values at high temperatures and thus it is used to describe the temperature dependency here. Although we cannot explain flux variations arising from overall carbon pool variations, results suggest that our approach may contribute to simplified Reco estimates.

Comparison of cloud optical depth and cloud mask applying BRDF model-based background surface reflectance

NASA Astrophysics Data System (ADS)

Kim, H. W.; Yeom, J. M.; Woo, S. H.

2017-12-01

Over the thin cloud region, satellite can simultaneously detect the reflectance from thin clouds and land surface. Since the mixed reflectance is not the exact cloud information, the background surface reflectance should be eliminated to accurately distinguish thin cloud such as cirrus. In the previous research, Kim et al (2017) was developed the cloud masking algorithm using the Geostationary Ocean Color Imager (GOCI), which is one of significant instruments for Communication, Ocean, and Meteorology Satellite (COMS). Although GOCI has 8 spectral channels including visible and near infra-red spectral ranges, the cloud masking has quantitatively reasonable result when comparing with MODIS cloud mask (Collection 6 MYD35). Especially, we noticed that this cloud masking algorithm is more specialized in thin cloud detections through the validation with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data. Because this cloud masking method was concentrated on eliminating background surface effects from the top-of-atmosphere (TOA) reflectance. Applying the difference between TOA reflectance and the bi-directional reflectance distribution function (BRDF) model-based background surface reflectance, cloud areas both thick cloud and thin cloud can be discriminated without infra-red channels which were mostly used for detecting clouds. Moreover, when the cloud mask result was utilized as the input data when simulating BRDF model and the optimized BRDF model-based surface reflectance was used for the optimized cloud masking, the probability of detection (POD) has higher value than POD of the original cloud mask. In this study, we examine the correlation between cloud optical depth (COD) and its cloud mask result. Cloud optical depths mostly depend on the cloud thickness, the characteristic of contents, and the size of cloud contents. COD ranges from less than 0.1 for thin clouds to over 1000 for the huge cumulus due to scattering by droplets. With the cloud optical depth of CALIPSO, the cloud masking result can be more improved since we can figure out how deep cloud is. To validate the cloud mask and the correlation result, the atmospheric retrieval will be computed to compare the difference between TOA reflectance and the simulated surface reflectance.

Producing Global Science Products for the Moderate Resolution Imaging Spectroradiometer (MODIS) in MODAPS

NASA Technical Reports Server (NTRS)

Masuoka, Edward J.; Tilmes, Curt A.; Ye, Gang; Devine, Neal; Smith, David E. (Technical Monitor)

2000-01-01

The MODerate resolution Imaging Spectroradiometer (MODIS) was launched on NASA's EOS-Terra spacecraft December 1999. With 36 spectral bands covering the visible, near wave and short wave infrared. MODIS produces over 40 global science data products, including sea surface temperature, ocean color, cloud properties, vegetation indices land surface temperature and land cover change. The MODIS Data Processing System (MODAPS) produces 400 GB/day of global MODIS science products from calibrated radiances generated in the Earth Observing System Data and Information System (EOSDIS). The science products are shipped to the EOSDIS for archiving and distribution to the public. An additional 200 GB of products are shipped each day to MODIS team members for quality assurance and validation of their products. In the sections that follow, we will describe the architecture of the MODAPS, identify processing bottlenecks encountered in scaling MODAPS from 50 GB/day backup system to a 400 GB/day production system and discuss how these were handled.

Multiple remote sensing data sources to assess spatio-temporal patterns of fire incidence over Campos Amazônicos Savanna Vegetation Enclave (Brazilian Amazon).

PubMed

Alves, Daniel Borini; Pérez-Cabello, Fernando

2017-12-01

Fire activity plays an important role in the past, present and future of Earth system behavior. Monitoring and assessing spatial and temporal fire dynamics have a fundamental relevance in the understanding of ecological processes and the human impacts on different landscapes and multiple spatial scales. This work analyzes the spatio-temporal distribution of burned areas in one of the biggest savanna vegetation enclaves in the southern Brazilian Amazon, from 2000 to 2016, deriving information from multiple remote sensing data sources (Landsat and MODIS surface reflectance, TRMM pluviometry and Vegetation Continuous Field tree cover layers). A fire scars database with 30 m spatial resolution was generated using a Landsat time series. MODIS daily surface reflectance was used for accurate dating of the fire scars. TRMM pluviometry data were analyzed to dynamically establish time limits of the yearly dry season and burning periods. Burned area extent, frequency and recurrence were quantified comparing the results annually/seasonally. Additionally, Vegetation Continuous Field tree cover layers were used to analyze fire incidence over different types of tree cover domains. In the last seventeen years, 1.03millionha were burned within the study area, distributed across 1432 fire occurrences, highlighting 2005, 2010 and 2014 as the most affected years. Middle dry season fires represent 86.21% of the total burned areas and 32.05% of fire occurrences, affecting larger amount of higher density tree surfaces than other burning periods. The results provide new insights into the analysis of burned areas of the neotropical savannas, spatially and statistically reinforcing important aspects linked to the seasonality patterns of fire incidence in this landscape. Copyright © 2017 Elsevier B.V. All rights reserved.

On Orbit Measurement of Response vs. Scan Angle for the Infrared Bands on TRMM/VIRS

NASA Technical Reports Server (NTRS)

Barnes, William L.; Lyu, Cheng-Hsuan; Barnes, Robert A.

1999-01-01

The Visible and Infrared Scanner on the Tropical Rainfall Measuring Mission (TRMM/VIRS) is a whiskbroom imaging radiometer with two reflected solar bands and three emissive infrared bands. All five detectors are on a single cooled focal plane. This configuration necessitated the use of a paddlewheel scan mirror to avoid the effects of focal plane rotation that arise when using a scan mirror that is inclined to its axis of rotation. System radiometric requirements led to the need for protected silver as the mirror surface. Unfortunately, the SiO(x) coatings currently used to protect silver from oxidation introduce a change in reflectance with angle of incidence (AOI). This AOI dependence results in a modulation of system level response with scan angle. Measurement of system response vs. scan angle (RVS) was not difficult for the VIRS reflected solar bands, but attaining the required accuracy for the IR bands in the laboratory was not possible without a large vacuum chamber and a considerable amount of custom designed testing apparatus. Therefore, the decision was made to conduct the measurement on-orbit. On three separate occasions, the TRMM spacecraft was rotated about its pitch axis and, after the nadir view passed over the Earth's limb, the VIRS performed several thousand scans while viewing deep space. The resulting data has been analyzed and the RVS curves generated for the three IR bands are being used in the VIRS radiometric calibration algorithm. This, to our knowledge, the first time this measurement has been made on-orbit. Similar measurements are planned for the EOS-AM and EOS-PM MODIS sensors and are being considered for several systems under development. The VIRS on-orbit results will be compared to VIRS and MODIS system level laboratory measurements, MODIS scan mirror witness sample measurements and modeled data.

An enhanced TIMESAT algorithm for estimating vegetation phenology metrics from MODIS data

USGS Publications Warehouse

Tan, B.; Morisette, J.T.; Wolfe, R.E.; Gao, F.; Ederer, G.A.; Nightingale, J.; Pedelty, J.A.

2011-01-01

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates. ?? 2010 IEEE.

An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data

NASA Technical Reports Server (NTRS)

Tan, Bin; Morisette, Jeffrey T.; Wolfe, Robert E.; Gao, Feng; Ederer, Gregory A.; Nightingale, Joanne; Pedelty, Jeffrey A.

2012-01-01

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.

GOCI Yonsei aerosol retrieval version 2 aerosol products: improved algorithm description and error analysis with uncertainty estimation from 5-year validation over East Asia

NASA Astrophysics Data System (ADS)

Choi, M.; Kim, J.; Lee, J.; KIM, M.; Park, Y. J.; Holben, B. N.; Eck, T. F.; Li, Z.; Song, C. H.

2017-12-01

The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER) version 1 algorithm was developed for retrieving hourly aerosol optical depth at 550 nm (AOD) and other subsidiary aerosol optical properties over East Asia. The GOCI YAER AOD showed comparable accuracy compared to ground-based and other satellite-based observations, but still had errors due to uncertainties in surface reflectance and simple cloud masking. Also, it was not capable of near-real-time (NRT) processing because it required a monthly database of each year encompassing the day of retrieval for the determination of surface reflectance. This study describes the improvement of GOCI YAER algorithm to the version 2 (V2) for NRT processing with improved accuracy from the modification of cloud masking, surface reflectance determination using multi-year Rayleigh corrected reflectance and wind speed database, and inversion channels per surface conditions. Therefore, the improved GOCI AOD ( ) is similar with those of Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD compared to V1 of the YAER algorithm. The shows reduced median bias and increased ratio within range (i.e. absolute expected error range of MODIS AOD) compared to V1 in the validation results using Aerosol Robotic Network (AERONET) AOD ( ) from 2011 to 2016. The validation using the Sun-Sky Radiometer Observation Network (SONET) over China also shows similar results. The bias of error ( is within -0.1 and 0.1 range as a function of AERONET AOD and AE, scattering angle, NDVI, cloud fraction and homogeneity of retrieved AOD, observation time, month, and year. Also, the diagnostic and prognostic expected error (DEE and PEE, respectively) of are estimated. The estimated multiple PEE of GOCI V2 AOD is well matched with actual error over East Asia, and the GOCI V2 AOD over Korea shows higher ratio within PEE compared to over China and Japan. Hourly AOD products based on the improved GOCI YAER AOD could contribute to better understandings of aerosols in terms of long-term climate changes and short-term air quality monitoring and forecasting perspectives over East Asia, especially rapid diurnal variation and transboundary transport.

Comparison of MODIS-derived land surface temperature with air temperature measurements

NASA Astrophysics Data System (ADS)

Georgiou, Andreas; Akçit, Nuhcan

2017-09-01

Air surface temperature is an important parameter for a wide range of applications such as agriculture, hydrology and climate change studies. Air temperature data is usually obtained from measurements made in meteorological stations, providing only limited information about spatial patterns over wide areas. The use of remote sensing data can help overcome this problem, particularly in areas with low station density, having the potential to improve the estimation of air surface temperature at both regional and global scales. Land Surface (skin) Temperatures (LST) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra and Aqua satellite platforms provide spatial estimates of near-surface temperature values. In this study, LST values from MODIS are compared to groundbased near surface air (Tair) measurements obtained from 14 observational stations during 2011 to 2015, covering coastal, mountainous and urban areas over Cyprus. Combining Terra and Aqua LST-8 Day and Night acquisitions into a mean monthly value, provide a large number of LST observations and a better overall agreement with Tair. Comparison between mean monthly LSTs and mean monthly Tair for all sites and all seasons pooled together yields a very high correlation and biases. In addition, the presented high standard deviation can be explained by the influence of surface heterogeneity within MODIS 1km2 grid cells, the presence of undetected clouds and the inherent difference between LST and Tair. However, MODIS LST data proved to be a reliable proxy for surface temperature and mostly for studies requiring temperature reconstruction in areas with lack of observational stations.

An Evaluation of Data Fusion Products for the Analysis of Dryland Forest Phenology

NASA Astrophysics Data System (ADS)

Walker, J. J.; de Beurs, K.; Wynne, R. H.; Gao, F.

2010-12-01

Semi-arid forest areas cover a significant proportion of the world’s land surface; in the interior western U.S. alone, dryland forests extend across more than 56 million hectares. The scarcity of water in these systems makes them acutely sensitive to sustained weather fluctuations, such as the higher temperatures and altered water regimes predicted under most climate change scenarios. To understand, monitor, and predict the anticipated spatial and temporal changes in these areas, it is vital to characterize current phenological patterns. Phenological analysis of western U.S. drylands is complicated by patchy land cover and mosaics of plant phenology states at a variety of spatial scales. Our aim is to use complementary satellite sensors to mitigate these difficulties and gain greater insight into phenological patterns in dryland forests. In this study we applied the spatial and temporal adaptive reflectance model (STARFM; Gao et al. 2006) to fuse Landsat and MODIS imagery to create synthetic images at Landsat spatial resolution and MODIS temporal resolution. To determine which MODIS dataset is most appropriate for the creation of synthetic images intended for the analysis of dryland forest phenology, we examined the effect of temporal compositing and BRDF function adjustment on the accuracy of STARFM imagery. We assembled seven Landsat 5 scenes (path/row 37/36) and temporally-coincident 500m MODIS datasets (seven daily (MOD09GA), seven 8-day composite (MOD09A1), and fourteen 16-day nadir BRDF-adjusted composite (MCD43A4) images) spanning the 2006 April - October growing season in northern Arizona, which is characterized by large tracts of dryland forest. The STARFM algorithm was applied to each MODIS data series to produce four synthetic images (one daily; one 8-day composite; and two 16-day composites) corresponding to each Landsat image. Validation of the accuracy of the synthetic images was achieved by comparing the reflectance values of a random sample of the identified dryland forest pixels in both images. Preliminary data analysis of the effect of the temporal resolution and dataset parameters indicates that the MODIS 8-day composite image may be a suitable and sufficient dataset for phenological analysis in this dryland forest ecosystem. Overall, this work demonstrates the feasibility of using data fusion products to assemble an imagery dataset at sufficiently high temporal and spatial scales to permit a more detailed examination of the underlying phenological processes and trends in dryland forest areas.

Toward Obtaining Reliable Particulate Air Quality Information from Satellites

NASA Astrophysics Data System (ADS)

Strawa, A. W.; Chatfield, R. B.; Legg, M.; Esswein, R.; Justice, E.

2009-12-01

Air quality agencies use ground sites to monitor air quality, providing accurate information at particular points. Using measurements from satellite imagery has the potential to provide air quality information in a timely manner with better spatial resolution and at a lower cost that can also useful for model validation. While previous studies show acceptable correlations between Aerosol Optical Depth (AOD) derived from MODIS and surface Particulate Matter (PM) measurements on the eastern US, the data do not correlate well in the western US (Al-Saadi et al., 2005; Engle-Cox et al., 2004) . This paper seeks to improve the AOD-PM correlations by using advanced statistical analysis techniques. Our study area is the San Joaquin Valley in California because air quality in this region has failed to meet state and federal attainment standards for PM for the past several years. A previous investigation found good correlation of the AOD values between MODIS, MISR and AERONET, but poor correlations (R2 ~ 0.02) between satellite-based AOD and surface PM2.5 measurements. PM2.5 measurements correlated somewhat better (R2 ~ 0.18) with MODIS-derived AOD using the Deep Blue surface reflectance algorithm (Hsu et al., 2006) rather than the standard MODIS algorithm. This level of correlation is not adequate for reliable air quality measurements. Pelletier et al. (2007) used generalized additive models (GAMs) and meteorological data to improve the correlation between PM and AERONET AOD in western Europe. Additive models are more flexible than linear models and the functional relationships can be plotted to give a sense of the relationship between the predictor and the response. In this paper we use GAMs to improve surface PM2.5 to MODIS-AOD correlations. For example, we achieve an R2 ~ 0.44 using a GAM that includes the Deep Blue AOD, and day of year as parameters. Including NOx observations, improves the R2 ~ 0.64. Surprisingly Ångström exponent did not prove to be a significant factor. The relationships between the predictor and the response are discussed. Al-Saadi, J., J. Szykman, R.B. Pierce, C. Kittaka, D. Neil, D.A. Chu, L. Remer, L. Gumley, E. Prins, L. Weinstock, C. MacDonald, R. Wayland, F. Dimmick, and J. Fishman, Imporving national air quality forecasts with satellite aerosol observations, Bull. Amer, Met. Soc. (Sept), 1249-1261, 2005. Engle-Cox, J.A., C.H. Holloman, B.W. Coutant, and R.M. Hoff, Qualitative and quantitative evaluation of MODIS satellite sensor data for regional and urban scale air quality, Atmos. En., 38, 2495-2509, 2004. Hsu, N.C., S.-C. Tsay, M.D. King, and J.R. Herman, Deep blue retrievals of Asian Aerosol properties during ACE-Asia, IEEE Trans. on Geosci.a nd Remote Sensing, 44 (11), 3180, 2006. Pelletier, B., R. Santer, and J. Vidot, Retrieving of particulate matter from optical measurements: A semi-parametric approach, J. Geophys. Res., 112 (D06208), 2007.

Long-term analysis of turbidity patterns in Danube Delta coastal area based on MODIS satellite data

NASA Astrophysics Data System (ADS)

Constantin, Sorin; Constantinescu, Ștefan; Doxaran, David

2017-06-01

The monitoring of coastal areas is becoming an urgent necessity in the context of increased pressure over these ecosystems due to climate change and human activities. Long term evaluation of specific parameters regarding water quality can now be achieved, thanks to the increased number of archived Earth Observation satellite data, now covering decades. Within this study, 12 years of MODIS information were used to compute surface water turbidity products that were further temporal binned into composite datasets (e.g. monthly, annual). A regional algorithm, based on local in situ measurements, was used in order to inverse remote sensing reflectance values into turbidity units. The interpretation of the final maps revealed important characteristics of the processes that play a major role in the regional turbidity dynamics. Observations were made regarding the relation between surface water turbidity and Danube River's discharge rates, winds, currents and also the bottom sedimentary characteristics of the shelf area. We discuss how different regions are affected by various external factors, depending on their geographical location, and we reinforce the idea that the river solid input is not the only parameter controlling water clarity in the Danube Delta coastal area, resuspension processes playing also an important role.

Using VIIRS/NPP and MODIS/Aqua data to provide a continuous record of suspended particulate matter in a highly turbid inland lake

NASA Astrophysics Data System (ADS)

Cao, Zhigang; Duan, Hongtao; Shen, Ming; Ma, Ronghua; Xue, Kun; Liu, Dong; Xiao, Qitao

2018-02-01

Inland lakes are generally an important source of drinking water, and information on their water quality needs to be obtained in real time. To date, Moderate-resolution imaging spectroradiometer (MODIS) data have played a critical, effective and long-term role in fulfilling this function. However, the MODIS instruments on board both the Terra and Aqua satellites have operated beyond their designed five-year mission lifespans (Terra was launched in 1999, whereas Aqua was launched in 2002), and these instruments may stop running at any time in the near future. The Visible Infrared Imager Radiometer Suite (VIIRS) on board the Suomi National Polar-Orbiting Partnership (Suomi NPP, which was launched in Oct 2011) is expected to provide a consistent, long-term data record and continue the series of observations initiated by MODIS. To date, few evaluations of the consistency between VIIRS and MODIS have been conducted for turbid inland waters. In this study, we first used synchronous MODIS/Aqua and VIIRS/NPP data (±1 h) collected during 2012-2015 to evaluate the consistency of Rayleigh-corrected reflectance (Rrc) observations over Lake Hongze (the fourth-largest freshwater lake in China), since accurate remote sensing reflectance (Rrs) values cannot be acquired over turbid inland waters. Second, we used recently developed algorithms based on Rrc in the red band to estimate the concentrations of suspended particulate matter (SPM) from MODIS/Aqua and VIIRS/NPP data. Finally, we assessed the consistency of the SPM products derived from MODIS/Aqua and VIIRS/NPP. The results show the following. (1) The differences in Rrc among the green (VIIRS 551 nm and MODIS 555 nm) and red bands (VIIRS 671 nm and MODIS 645 nm) indicate a satisfactory consistency, and the unbiased percentage difference (UPD) is <12%. Meanwhile, the results for the near infrared (NIR) band (MODIS 859 nm and VIIRS 862 nm) indicate relatively large differences (UPD = 21.84%). (2) The satellite-derived SPM products obtained using MODIS/Aqua and VIIRS/NPP have a satisfactory degree of consistency (0-150 mg/L SPM: R2 = 0.81, UPD < 16% and 0-80 mg/L SPM: R2 = 0.85, UPD < 12%, respectively). These results demonstrate that VIIRS/NPP can continue to record the SPM observations initiated by MODIS/Aqua for turbid inland waters and establish environmental datasets over long time periods to support water quality management endeavors.

The Blue Marble

NASA Technical Reports Server (NTRS)

2002-01-01

This spectacular Moderate Resolution Imaging Spectroradiometer (MODIS) 'blue marble' image is based on the most detailed collection of true-color imagery of the entire Earth to date. Using a collection of satellite-based observations, scientists and visualizers stitched together months of observations of the land surface, oceans, sea ice, and clouds into a seamless, true-color mosaic of every square kilometer (.386 square mile) of our planet. Most of the information contained in this image came from MODIS, illustrating MODIS' outstanding capacity to act as an integrated tool for observing a variety of terrestrial, oceanic, and atmospheric features of the Earth. The land and coastal ocean portions of this image is based on surface observations collected from June through September 2001 and combined, or composited, every eight days to compensate for clouds that might block the satellite's view on any single day. Global ocean color (or chlorophyll) data was used to simulate the ocean surface. MODIS doesn't measure 3-D features of the Earth, so the surface observations were draped over topographic data provided by the U.S. Geological Survey EROS Data Center. MODIS observations of polar sea ice were combined with observations of Antarctica made by the National Oceanic and Atmospheric Administration's AVHRR sensor-the Advanced Very High Resolution Radiometer. The cloud image is a composite of two days of MODIS imagery collected in visible light wavelengths and a third day of thermal infra-red imagery over the poles. A large collection of imagery based on the blue marble in a variety of sizes and formats, including animations and the full (1 km) resolution imagery, is available at the Blue Marble page. Image by Reto Stockli, Render by Robert Simmon. Based on data from the MODIS Science Team

Assessment of MODIS On-Orbit Calibration Using a Deep Convective Cloud Technique

NASA Technical Reports Server (NTRS)

Mu, Qiaozhen; Wu, Aisheng; Chang, Tiejun; Angal, Amit; Link, Daniel; Xiong, Xiaoxiong; Doelling, David R.; Bhatt, Rajendra

2016-01-01

The MODerate Resolution Imaging Spectroradiometer (MODIS) sensors onboard Terra and Aqua satellites are calibrated on-orbit with a solar diffuser (SD) for the reflective solar bands (RSB). The MODIS sensors are operating beyond their designed lifetime and hence present a major challenge to maintain the calibration accuracy. The degradation of the onboard SD is tracked by a solar diffuser stability monitor (SDSM) over a wavelength range from 0.41 to 0.94 micrometers. Therefore, any degradation of the SD beyond 0.94 micrometers cannot be captured by the SDSM. The uncharacterized degradation at wavelengths beyond this limit could adversely affect the Level 1B (L1B) product. To reduce the calibration uncertainties caused by the SD degradation, invariant Earth-scene targets are used to monitor and calibrate the MODIS L1B product. The use of deep convective clouds (DCCs) is one such method and particularly significant for the short-wave infrared (SWIR) bands in assessing their long-term calibration stability. In this study, we use the DCC technique to assess the performance of the Terra and Aqua MODIS Collection-6 L1B for RSB 1 3- 7, and 26, with spectral coverage from 0.47 to 2.13 micrometers. Results show relatively stable trends in Terra and Aqua MODIS reflectance for most bands. Careful attention needs to be paid to Aqua band 1, Terra bands 3 and 26 as their trends are larger than 1% during the study time period. We check the feasibility of using the DCC technique to assess the stability in MODIS bands 17-19. The assessment test on response versus scan angle (RVS) calibration shows substantial trend difference for Aqua band 1between different angles of incidence (AOIs). The DCC technique can be used to improve the RVS calibration in the future.

Application and Evaluation of MODIS LAI, FPAR, and Albedo Products in the WRF/CMAQ System

EPA Science Inventory

MODIS vegetation and albedo products provide a more realistic representation of surface conditions for input to the WRF/CMAQ modeling system. However, the initial evaluation of ingesting MODIS data into the system showed mixed results, with increased bias and error for 2-m temper...

Reconstructing daily clear-sky land surface temperature for cloudy regions from MODIS data

USDA-ARS?s Scientific Manuscript database

Land surface temperature (LST) is a critical parameter in environmental studies and resource management. The MODIS LST data product has been widely used in various studies, such as drought monitoring, evapotranspiration mapping, soil moisture estimation and forest fire detection. However, cloud cont...

Comparison of Satellite-Derived and In-Situ Observations of Ice and Snow Surface Temperatures over Greenland

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Box, Jason E.; Casey, Kimberly A.; Hook, Simon J.; Shuman, Christopher A.; Steffen, Konrad

2008-01-01

The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

Retrieval of the Land Surface Reflectance for Landsat-8 and Sentinel-2 and its validation.

NASA Astrophysics Data System (ADS)

Roger, J. C.; Vermote, E.; Skakun, S.; Franch, B.; Holben, B. N.; Justice, C. O.

2017-12-01

The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and a key parameter in the understanding of the land-surface-climate processes. For 25 years, Vermote and al. develop atmospheric corrections methods to define a land surface reflectance product for various satellites (AVHRR, MODIS, VIIRS…). This presentation highlights the algorithms developed both for Landsant-8 and Sentinel-2. We also emphasize the validation of the "Land surface reflectance" satellite products, which is a very important step to be done. For that purpose, we compared the surface reflectance products to a reference determined by using the accurate radiative transfer code 6S and very detailed measurements of the atmosphere obtained over the AERONET network (which allows to test for a large range of aerosol characteristics); formers being important inputs for atmospheric corrections. However, the application of this method necessitates the definition of a very detailed protocol for the use of AERONET data especially as far as size distribution and absorption are concerned, so that alternative validation methods or protocols could be compared. We describe here the protocol we have been working on based on our experience with the AERONET data and its application to Landsat-8 and Sentinel-2). We also derive a detailed error budget in relation to this approach. For a mean loaded atmosphere, t550 less than 0.25, the maximum uncertainty is 0.0025 corresponding to a relative uncertainty (in the RED channels): U < 1% for rsurf > 0.10, and 1% < U <2% for 0.10 >rsurf > 0.04.

GEONEX: Land Monitoring From a New Generation of Geostationary Satellite Sensors

NASA Technical Reports Server (NTRS)

Nemani, Ramakrishna; Lyapustin, Alexei; Wang, Weile; Wang, Yujie; Hashimoto, Hirofumi; Li, Shuang; Ganguly, Sangram; Michaelis, Andrew; Higuchi, Atsushi; Takaneka, Hideaki;

GEONEX: Land monitoring from a new generation of geostationary satellite sensors

NASA Astrophysics Data System (ADS)

Nemani, R. R.; Lyapustin, A.; Wang, W.; Ganguly, S.; Wang, Y.; Michaelis, A.; Hashimoto, H.; Li, S.; Higuchi, A.; Huete, A. R.; Yeom, J. M.; camacho De Coca, F.; Lee, T. J.; Takenaka, H.

2017-12-01

The latest generation of geostationary satellites carry sensors such as ABI (Advanced Baseline Imager on GOES-16) and the AHI (Advanced Himawari Imager on Himawari) that closely mimic the spatial and spectral characteristics of Earth Observing System flagship MODIS for monitoring land surface conditions. More importantly they provide observations at 5-15 minute intervals. Such high frequency data offer exciting possibilities for producing robust estimates of land surface conditions by overcoming cloud cover, enabling studies of diurnally varying local-to-regional biosphere-atmosphere interactions, and operational decision-making in agriculture, forestry and disaster management. But the data come with challenges that need special attention. For instance, geostationary data feature changing sun angle at constant view for each pixel, which is reciprocal to sun-synchronous observations, and thus require careful adaptation of EOS algorithms. Our goal is to produce a set of land surface products from geostationary sensors by leveraging NASA's investments in EOS algorithms and in the data/compute facility NEX. The land surface variables of interest include atmospherically corrected surface reflectances, snow cover, vegetation indices and leaf area index (LAI)/fraction of photosynthetically absorbed radiation (FPAR), as well as land surface temperature and fires. In order to get ready to produce operational products over the US from GOES-16 starting 2018, we have utilized 18 months of data from Himawari AHI over Australia to test the production pipeline and the performance of various algorithms for our initial tests. The end-to-end processing pipeline consists of a suite of modules to (a) perform calibration and automatic georeference correction of the AHI L1b data, (b) adopt the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to produce surface spectral reflectances along with compositing schemes and QA, and (c) modify relevant EOS retrieval algorithms (e.g., LAI and FPAR, GPP, etc.) for subsequent science product generation. Initial evaluation of Himawari AHI products against standard MODIS products indicate general agreement, suggesting that data from geostationary sensors can augment low earth orbit (LEO) satellite observations.

Recent Progress on Deep Blue Aerosol Algorithm as Applied TO MODIS, SEA WIFS, and VIIRS, and Their Intercomparisons with Ground Based and Other Satellite Measurements

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Bettenhausen, Corey; Sawyer, Andrew; Tsay, Si-Chee

2012-01-01

The impact of natural and anthropogenic sources of aerosols has gained increasing attention from scientific communities in recent years. Indeed, tropospheric aerosols not only perturb radiative energy balance by interacting with solar and terrestrial radiation, but also by changing cloud properties and lifetime. Furthermore, these anthropogenic and natural air particles, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across oceans and continents resulting in important biogeochemical impacts on the ecosystem. With the launch of SeaWiFS in 1997, Terra/MODIS in 1999, and Aqua/MODIS in 2002, high quality comprehensive aerosol climatology is becoming feasible for the first time. As a result of these unprecedented data records, studies of the radiative and biogeochemical effects due to tropospheric aerosols are now possible. In this talk, we will demonstrate how this newly available SeaWiFS/MODIS aerosol climatology can provide an important piece of puzzles in reducing the uncertainty of estimated climatic forcing due to aerosols. We will start with the global distribution of aerosol loading and their variabilities over both land and ocean on short- and long-term temporal scales observed over the last decade. The recent progress made in Deep Blue aerosol algorithm on improving accuracy of these Sea WiFS / MODIS aerosol products in particular over land will be discussed. The impacts on quantifying physical and optical processes of aerosols over source regions of adding the Deep Blue products of aerosol properties over bright-reflecting surfaces into Sea WiFS / MODIS as well as VIIRS data suite will also be addressed. We will also show the intercomparison results of SeaWiFS/MODIS retrieved aerosol optical thickness with data from ground based AERONET sunphotometers over land and ocean as well as with other satellite measurements. The trends observed in global aerosol loadings of both natural and anthropogenic sources based upon more than a decade of combined MODIS/SeaWiFS data (1997-2011) will be discussed. We will also address the importance of various key issues such as differences in spatial-temporal sampling rates and observation time between different satellite measurements could potentially impact these intercomparisons results, especially for using the monthly mean data, and thus on estimates of long-term aerosol trends.

Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic.

PubMed

Kampel, Milton; Lorenzzetti, João A; Bentz, Cristina M; Nunes, Raul A; Paranhos, Rodolfo; Rudorff, Frederico M; Politano, Alexandre T

2009-01-01

Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL) and ocean color remote sensing estimates were conducted during an oceanographic cruise on the Brazilian Southeastern continental shelf and slope, Southwestern South Atlantic. In situ values were based on fluorometry, above-water radiometry and lidar fluorosensor. Three empirical algorithms were used to estimate CHL from radiometric measurements: Ocean Chlorophyll 3 bands (OC3M(RAD)), Ocean Chlorophyll 4 bands (OC4v4(RAD)), and Ocean Chlorophyll 2 bands (OC2v4(RAD)). The satellite estimates of CHL were derived from data collected by the MODerate-resolution Imaging Spectroradiometer (MODIS) with a nominal 1.1 km resolution at nadir. Three algorithms were used to estimate chlorophyll concentrations from MODIS data: one empirical - OC3M(SAT), and two semi-analytical - Garver, Siegel, Maritorena version 01 (GSM01(SAT)), and Carder(SAT). In the present work, MODIS, lidar and in situ above-water radiometry and fluorometry are briefly described and the estimated values of chlorophyll retrieved by these techniques are compared. The chlorophyll concentration in the study area was in the range 0.01 to 0.2 mg/m(3). In general, the empirical algorithms applied to the in situ radiometric and satellite data showed a tendency to overestimate CHL with a mean difference between estimated and measured values of as much as 0.17 mg/m(3) (OC2v4(RAD)). The semi-analytical GSM01 algorithm applied to MODIS data performed better (rmse 0.28, rmse-L 0.08, mean diff. -0.01 mg/m(3)) than the Carder and the empirical OC3M algorithms (rmse 1.14 and 0.36, rmse-L 0.34 and 0.11, mean diff. 0.17 and 0.02 mg/m(3), respectively). We find that rmsd values between MODIS relative to the in situ radiometric measurements are < 26%, i.e., there is a trend towards overestimation of R(RS) by MODIS for the stations considered in this work. Other authors have already reported over and under estimation of MODIS remotely sensed reflectance due to several errors in the bio-optical algorithm performance, in the satellite sensor calibration, and in the atmospheric-correction algorithm.

Characterization of MODIS and SeaWiFS Solar Diffuser On-Orbit Degradation

NASA Technical Reports Server (NTRS)

Xiong, X.; Eplee, R. E., Jr.; Sun, J.; Patt, F. S.; Angal, A.; McClain, C. R.

2009-01-01

MODIS has 20 reflective solar bands (RSB), covering the VIS, NIR, and SWIR spectral regions. They are calibrated on-orbit using a solar diffuser (SD) panel, made of space-grade Spectralon. The SD bi-directional reflectance factor (BRF) was characterized pre-launch by the instrument vendor reference to the NIST reflectance standard. Its on-orbit degradation is tracked by an on-board solar diffuser stability monitor (SDSM). The SeaWifS on-orbit calibration strategy uses monthly lunar observations to monitor the long-term radiometric stability of the instrument and applies daily observations of its solar diffuser (an aluminum plate coated with YB71 paint) to track the short-term changes in the instrument response. This paper provides an overview of MODIS and SeaWiFS SD observations, applications, and approaches used to track their on-orbit degradations. Results from sensors are presented with emphasis on the spectral dependence and temporal trends of the SD degradation. Lessons and challenges from the use of SD for sensor on-orbit calibration are also discussed.

Sub-Pixel Mapping of Tree Canopy, Impervious Surfaces, and Cropland in the Laurentian Great Lakes Basin Using MODIS Time-Series Data

EPA Science Inventory

This research examined sub-pixel land-cover classification performance for tree canopy, impervious surface, and cropland in the Laurentian Great Lakes Basin (GLB) using both timeseries MODIS (MOderate Resolution Imaging Spectroradiometer) NDVI (Normalized Difference Vegetation In...

FLUXNET: A Global Network of Eddy-Covariance Flux Towers

NASA Astrophysics Data System (ADS)

Cook, R. B.; Holladay, S. K.; Margle, S. M.; Olsen, L. M.; Gu, L.; Heinsch, F.; Baldocchi, D.

2003-12-01

The FLUXNET global network was established to aid in understanding the mechanisms controlling the exchanges of carbon dioxide, water vapor, and energy across a variety of terrestrial ecosystems. Flux tower data are also being used to validate ecosystem model outputs and to provide information for validating remote sensing based products, including surface temperature, reflectance, albedo, vegetation indices, leaf area index, photosynthetically active radiation, and photosynthesis derived from MODIS sensors on the Terra and Aqua satellites. The global FLUXNET database provides consistent and complete flux data to support global carbon cycle science. Currently FLUXNET consists of over 210 sites, with most flux towers operating continuously for 4 years or longer. Gap-filled data are available for 53 sites. The FLUXNET database contains carbon, water vapor, sensible heat, momentum, and radiation flux measurements with associated ancillary and value-added data products. Towers are located in temperate conifer and broadleaf forests, tropical and boreal forests, crops, grasslands, chaparral, wetlands, and tundra on five continents. Selected MODIS Land products in the immediate vicinity of the flux tower are subsetted and posted on the FLUXNET Web site for 169 flux-towers. The MODIS subsets are prepared in ASCII format for 8-day periods for an area 7 x 7 km around the tower.

GOME-2 Tropospheric Ozone Profile Retrievals from Joint UV/Visible Measurement

NASA Astrophysics Data System (ADS)

Liu, X.; Zoogman, P.; Chance, K.; Cai, Z.; Nowlan, C. R.; Huang, G.; Gonzalez Abad, G.

2016-12-01

It has been shown from sensitivity studies that adding visible measurements in the Chappuis ozone band to UV measurements in the Hartley/Huggins ozone bands can significantly enhance retrieval sensitivity to lower tropospheric ozone from backscattered solar radiances due to deeper photon penetration in the visible to the surface than in the ultraviolet. The first NASA EVI (Earth Venture Instrument) TEMPO (Tropospheric Emissions: Monitoring of Pollution) instrument is being developed to measure backscattered solar radiation in two channels ( 290-490 and 540-740 nm) and make atmospheric pollution measurements over North America from the Geostationary orbit. However, this retrieval enhancement has yet to be demonstrated from existing measurements due to the weak ozone absorption in the visible and strong interferences from surface reflectance and aerosols and the requirement of accurate radiometric calibration across different spectral channels. We present GOME-2 retrievals from joint UV/visible measurements using the SAO ozone profile retrieval algorithm, to directly explore the retrieval improvement in lower tropospheric ozone from additional visible measurements. To reduce the retrieval interference from surface reflectance, we add characterization of surface spectral reflectance in the visible based on combining EOFs (Empirical Orthogonal Functions) derived from ASTER and other surface reflectance spectra with MODIS BRDF climatology into the ozone profile algorithm. The impacts of various types of aerosols and surface BRDF on the retrievals will be investigated. In addition, we will also perform empirical radiometric calibration of the GOME-2 data based on radiative transfer simulations. We will evaluate the retrieval improvement of joint UV/visible retrieval over the UV retrieval based on fitting quality and validation against ozonesonde observations.

Hydrological Controls on Floodplain Forest Phenology Assessed using Remotely Sensed Vegetation Indices

NASA Astrophysics Data System (ADS)

Lemon, M. G.; Keim, R.

2017-12-01

Although specific controls are not well understood, the phenology of temperate forests is generally thought to be controlled by photoperiod and temperature, although recent research suggests that soil moisture may also be important. The phenological controls of forested wetlands have not been thoroughly studied, and may be more controlled by site hydrology than other forests. For this study, remotely sensed vegetation indices were used to investigate hydrological controls on start-of-season timing, growing season length, and end-of-season timing at five floodplains in Louisiana, Arkansas, and Texas. A simple spring green-up model was used to determine the null spring start of season time for each site as a function of land surface temperature and photoperiod, or two remotely sensed indices: MODIS phenology data product and the MODIS Nadir Bidirectional Reflectance Distribution Function-Adjusted Reflectance (NBAR) product. Preliminary results indicate that topographically lower areas within the floodplain with higher flood frequency experience later start-of-season timing. In addition, start-of-season is delayed in wet years relative to predicted timing based solely on temperature and photoperiod. The consequences for these controls unclear, but results suggest hydrological controls on floodplain ecosystem structure and carbon budgets are likely at least partially expressed by variations in growing season length.

Examination of Regional Trends in Cloud Properties over Surface Sites Derived from MODIS and AVHRR using the CERES Cloud Algorithm

NASA Astrophysics Data System (ADS)

Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.; Sun-Mack, S.; Chen, Y.; Doelling, D. R.; Kato, S.; Rutan, D. A.

2017-12-01

Recent studies analyzing long-term measurements of surface insolation at ground sites suggest that decadal-scale trends of increasing (brightening) and decreasing (dimming) downward solar flux have occurred at various times over the last century. Regional variations have been reported that range from near 0 Wm-2/decade to as large as 9 Wm-2/decade depending on the location and time period analyzed. The more significant trends have been attributed to changes in overhead clouds and aerosols, although quantifying their relative impacts using independent observations has been difficult, owing in part to a lack of consistent long-term measurements of cloud properties. This paper examines new satellite based records of cloud properties derived from MODIS (2000-present) and AVHRR (1981- present) data to infer cloud property trends over a number of surface radiation sites across the globe. The MODIS cloud algorithm was developed for the NASA Clouds and the Earth's Radiant Energy System (CERES) project to provide a consistent record of cloud properties to help improve broadband radiation measurements and to better understand cloud radiative effects. The CERES-MODIS cloud algorithm has been modified to analyze other satellites including the AVHRR on the NOAA satellites. Compared to MODIS, obtaining consistent cloud properties over a long period from AVHRR is a much more significant challenge owing to the number of different satellites, instrument calibration uncertainties, orbital drift and other factors. Nevertheless, both the MODIS and AVHRR cloud properties will be analyzed to determine trends, and their level of consistency and correspondence with surface radiation trends derived from the ground-based radiometer data. It is anticipated that this initial study will contribute to an improved understanding of surface solar radiation trends and their relationship to clouds.

Moderate Resolution Imaging Spectroradiometer (MODIS) MOD21 Land Surface Temperature and Emissivity Algorithm Theoretical Basis Document

NASA Technical Reports Server (NTRS)

Hulley, G.; Malakar, N.; Hughes, T.; Islam, T.; Hook, S.

2016-01-01

This document outlines the theory and methodology for generating the Moderate Resolution Imaging Spectroradiometer (MODIS) Level-2 daily daytime and nighttime 1-km land surface temperature (LST) and emissivity product using the Temperature Emissivity Separation (TES) algorithm. The MODIS-TES (MOD21_L2) product, will include the LST and emissivity for three MODIS thermal infrared (TIR) bands 29, 31, and 32, and will be generated for data from the NASA-EOS AM and PM platforms. This is version 1.0 of the ATBD and the goal is maintain a 'living' version of this document with changes made when necessary. The current standard baseline MODIS LST products (MOD11*) are derived from the generalized split-window (SW) algorithm (Wan and Dozier 1996), which produces a 1-km LST product and two classification-based emissivities for bands 31 and 32; and a physics-based day/night algorithm (Wan and Li 1997), which produces a 5-km (C4) and 6-km (C5) LST product and emissivity for seven MODIS bands: 20, 22, 23, 29, 31-33.

Sun glint requirement for the remote detection of surface oil films

NASA Astrophysics Data System (ADS)

Sun, Shaojie; Hu, Chuanmin

2016-01-01

Natural oil slicks in the western Gulf of Mexico are used to determine the sun glint threshold required for optical remote sensing of oil films. The threshold is determined using the same-day image pairs collected by Moderate Resolution Imaging Spectroradiometer (MODIS) Terra (MODIST), MODIS Aqua (MODISA), and Visible Infrared Imaging Radiometer Suite (VIIRS) (N = 2297 images) over the same oil slick locations where at least one of the sensors captures the oil slicks. For each sensor, statistics of sun glint strengths, represented by the normalized glint reflectance (LGN, sr-1), when oil slicks can and cannot be observed are generated. The LGN threshold for oil film detections is determined to be 10-5-10-6 sr-1 for MODIST and MODISA, and 10-6-10-7 sr-1 for VIIRS. Below these thresholds, no oil films can be detected, while above these thresholds, oil films can always be detected except near the critical-angle zone where oil slicks reverse their contrast against the background water.

Empirical Retrieval of Surface Melt Magnitude from Coupled MODIS Optical and Thermal Measurements over the Greenland Ice Sheet during the 2001 Ablation Season

PubMed Central

Lampkin, Derrick; Peng, Rui

2008-01-01

Accelerated ice flow near the equilibrium line of west-central Greenland Ice Sheet (GIS) has been attributed to an increase in infiltrated surface melt water as a response to climate warming. The assessment of surface melting events must be more than the detection of melt onset or extent. Retrieval of surface melt magnitude is necessary to improve understanding of ice sheet flow and surface melt coupling. In this paper, we report on a new technique to quantify the magnitude of surface melt. Cloud-free dates of June 10, July 5, 7, 9, and 11, 2001 Moderate Resolution Imaging Spectroradiometer (MODIS) daily reflectance Band 5 (1.230-1.250μm) and surface temperature images rescaled to 1km over western Greenland were used in the retrieval algorithm. An optical-thermal feature space partitioned as a function of melt magnitude was derived using a one-dimensional thermal snowmelt model (SNTHERM89). SNTHERM89 was forced by hourly meteorological data from the Greenland Climate Network (GC-Net) at reference sites spanning dry snow, percolation, and wet snow zones in the Jakobshavn drainage basin in western GIS. Melt magnitude or effective melt (E-melt) was derived for satellite composite periods covering May, June, and July displaying low fractions (0-1%) at elevations greater than 2500m and fractions at or greater than 15% at elevations lower than 1000m assessed for only the upper 5 cm of the snow surface. Validation of E-melt involved comparison of intensity to dry and wet zones determined from QSCAT backscatter. Higher intensities (> 8%) were distributed in wet snow zones, while lower intensities were grouped in dry zones at a first order accuracy of ∼ ±2%. PMID:27873793

Empirical Retrieval of Surface Melt Magnitude from Coupled MODIS Optical and Thermal Measurements over the Greenland Ice Sheet during the 2001 Ablation Season.

PubMed

Lampkin, Derrick; Peng, Rui

2008-08-22

Accelerated ice flow near the equilibrium line of west-central Greenland Ice Sheet (GIS) has been attributed to an increase in infiltrated surface melt water as a response to climate warming. The assessment of surface melting events must be more than the detection of melt onset or extent. Retrieval of surface melt magnitude is necessary to improve understanding of ice sheet flow and surface melt coupling. In this paper, we report on a new technique to quantify the magnitude of surface melt. Cloud-free dates of June 10, July 5, 7, 9, and 11, 2001 Moderate Resolution Imaging Spectroradiometer (MODIS) daily reflectance Band 5 (1.230-1.250μm) and surface temperature images rescaled to 1km over western Greenland were used in the retrieval algorithm. An optical-thermal feature space partitioned as a function of melt magnitude was derived using a one-dimensional thermal snowmelt model (SNTHERM89). SNTHERM89 was forced by hourly meteorological data from the Greenland Climate Network (GC-Net) at reference sites spanning dry snow, percolation, and wet snow zones in the Jakobshavn drainage basin in western GIS. Melt magnitude or effective melt (E-melt) was derived for satellite composite periods covering May, June, and July displaying low fractions (0-1%) at elevations greater than 2500m and fractions at or greater than 15% at elevations lower than 1000m assessed for only the upper 5 cm of the snow surface. Validation of E-melt involved comparison of intensity to dry and wet zones determined from QSCAT backscatter. Higher intensities (> 8%) were distributed in wet snow zones, while lower intensities were grouped in dry zones at a first order accuracy of ~ ±2%.

Comparison of Sentinel-2A and Landsat-8 Nadir BRDF Adjusted Reflectance (NBAR) over Southern Africa

NASA Astrophysics Data System (ADS)

Li, J.; Roy, D. P.; Zhang, H.

2016-12-01

The Landsat satellites have been providing moderate resolution imagery of the Earth's surface for over 40 years with continuity provided by the Landsat 8 and planned Landsat 9 missions. The European Space Agency Sentinel-2 satellite was successfully launched into a polar sun-synchronous orbit in 2015 and carries the Multi Spectral Instrument (MSI) that has Landsat-like bands and acquisition coverage. These new sensors acquire images at view angles ± 7.5° (Landsat) and ± 10.3° (Sentinel-2) from nadir that result in small directional effects in the surface reflectance. When data from adjoining paths, or from long time series are used, a model of the surface anisotropy is required to adjust observations to a uniform nadir view (primarily for visual consistency, vegetation monitoring, or detection of subtle surface changes). Recently a generalized approach was published that provides consistent Landsat view angle corrections to provide nadir BRDF-adjusted reflectance (NBAR). Because the BRDF shapes of different terrestrial surfaces are sufficiently similar over the narrow 15° Landsat field of view, a fixed global set of MODIS BRDF spectral model parameters was shown to be adequate for Landsat NBAR derivation with little sensitivity to the land cover type, condition, or surface disturbance. This poster demonstrates the application of this methodology to Sentinel-2 data over a west-east transect across southern Africa. The reflectance differences between adjacent overlapping paths in the forward and backward scatter directions are quantified for both before and after BRDF correction. Sentinel-2 and Landsat-8 reflectance and NBAR inter-comparison results considering different stages of cloud and saturation filtering, and filtering to reduce surface state differences caused by acquisition time differences, demonstrate the utility of the approach. The relevance and limitations of the corrections for providing consistent moderate resolution reflectance are discussed.

Global Aerosol Optical Models and Lookup Tables for the New MODIS Aerosol Retrieval over Land

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Remer, Loraine A.; Dubovik, Oleg

2007-01-01

Since 2000, MODIS has been deriving aerosol properties over land from MODIS observed spectral reflectance, by matching the observed reflectance with that simulated for selected aerosol optical models, aerosol loadings, wavelengths and geometrical conditions (that are contained in a lookup table or 'LUT'). Validation exercises have showed that MODIS tends to under-predict aerosol optical depth (tau) in cases of large tau (tau greater than 1.0), signaling errors in the assumed aerosol optical properties. Using the climatology of almucantur retrievals from the hundreds of global AERONET sunphotometer sites, we found that three spherical-derived models (describing fine-sized dominated aerosol), and one spheroid-derived model (describing coarse-sized dominated aerosol, presumably dust) generally described the range of observed global aerosol properties. The fine dominated models were separated mainly by their single scattering albedo (omega(sub 0)), ranging from non-absorbing aerosol (omega(sub 0) approx. 0.95) in developed urban/industrial regions, to neutrally absorbing aerosol (omega(sub 0) approx.90) in forest fire burning and developing industrial regions, to absorbing aerosol (omega(sub 0) approx. 0.85) in regions of savanna/grassland burning. We determined the dominant model type in each region and season, to create a 1 deg. x 1 deg. grid of assumed aerosol type. We used vector radiative transfer code to create a new LUT, simulating the four aerosol models, in four MODIS channels. Independent AERONET observations of spectral tau agree with the new models, indicating that the new models are suitable for use by the MODIS aerosol retrieval.

Application of MODIS GPP to Forecast Risk of Hantavirus Pulmonary Syndrome Based on Fluctuations in Reservoir Population Density

NASA Astrophysics Data System (ADS)

Loehman, R.; Heinsch, F. A.; Mills, J. N.; Wagoner, K.; Running, S.

2003-12-01

Recent predictive models for hantavirus pulmonary syndrome (HPS) have used remotely sensed spectral reflectance data to characterize risk areas with limited success. We present an alternative method using gross primary production (GPP) from the MODIS sensor to estimate the effects of biomass accumulation on population density of Peromyscus maniculatus (deer mouse), the principal reservoir species for Sin Nombre virus (SNV). The majority of diagnosed HPS cases in North America are attributed to SNV, which is transmitted to humans through inhalation of excretions and secretions from infected rodents. A logistic model framework is used to evaluate MODIS GPP, temperature, and precipitation as predictors of P. maniculatus density at established trapping sites across the western United States. Rodent populations are estimated using monthly minimum number alive (MNA) data for 2000 through 2002. Both local meteorological data from nearby weather stations and 1.25 degree x 1 degree gridded data from the NASA DAO were used in the regression model to determine the spatial sensitivity of the response. MODIS eight-day GPP data (1-km resolution) were acquired and binned to monthly average and monthly sum GPP for 3km x 3km grids surrounding each rodent trapping site. The use of MODIS GPP to forecast HPS risk may result in a marked improvement over past reflectance-based risk area characterizations. The MODIS GPP product provides a vegetation dynamics estimate that is unique to disease models, and targets the fundamental ecological processes responsible for increased rodent density and amplified disease risk.

Using NASA Techniques to Atmospherically Correct AWiFS Data for Carbon Sequestration Studies

NASA Technical Reports Server (NTRS)

Holekamp, Kara L.

2007-01-01

Carbon dioxide is a greenhouse gas emitted in a number of ways, including the burning of fossil fuels and the conversion of forest to agriculture. Research has begun to quantify the ability of vegetative land cover and oceans to absorb and store carbon dioxide. The USDA (U.S. Department of Agriculture) Forest Service is currently evaluating a DSS (decision support system) developed by researchers at the NASA Ames Research Center called CASA-CQUEST (Carnegie-Ames-Stanford Approach-Carbon Query and Evaluation Support Tools). CASA-CQUEST is capable of estimating levels of carbon sequestration based on different land cover types and of predicting the effects of land use change on atmospheric carbon amounts to assist land use management decisions. The CASA-CQUEST DSS currently uses land cover data acquired from MODIS (the Moderate Resolution Imaging Spectroradiometer), and the CASA-CQUEST project team is involved in several projects that use moderate-resolution land cover data derived from Landsat surface reflectance. Landsat offers higher spatial resolution than MODIS, allowing for increased ability to detect land use changes and forest disturbance. However, because of the rate at which changes occur and the fact that disturbances can be hidden by regrowth, updated land cover classifications may be required before the launch of the Landsat Data Continuity Mission, and consistent classifications will be needed after that time. This candidate solution investigates the potential of using NASA atmospheric correction techniques to produce science-quality surface reflectance data from the Indian Remote Sensing Advanced Wide-Field Sensor on the RESOURCESAT-1 mission to produce land cover classification maps for the CASA-CQUEST DSS.

Satellite Monitoring of Asian Dust Storms from SeaWiFS and MODIS: Source, Pathway, and Interannual Variability

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Tsay, S.-C.; Bettenhausen, C.; Sayer, A.

2011-01-01

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. China's capital, Beijing, and other large cities are on the primary pathway of these dust storm plumes, and their passage over such population centers causes flight delays, pushes grit through windows and doors, and forces peop Ie indoors. Furthermore, during the spring these anthropogenic and natural air pollutants, once generated over the source regions, can be tran sported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol optical thickness and single scattering albedo over brightreflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. The new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as Sea WiFS and MODIS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. We have validated the satellite retrieved aerosol optical thickness with data from AERONET sunphotometers over desert and semi-desert regions. The comparisons show reasonable agreements between these two. These new satellite products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from Sea WiFS and MODISlike instruments. The multiyear satellite measurements since 1998 from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with these dust outbreaks in East Asia. The monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Consistency of land surface reflectance data: presentation of a new tool and case study with Formosat-2, SPOT-4 and Landsat-5/7/8 data

NASA Astrophysics Data System (ADS)

Claverie, M.; Vermote, E.; Franch, B.; Huc, M.; Hagolle, O.; Masek, J.

2013-12-01

Maintaining consistent dataset of Surface Reflectance (SR) data derived from the large panel of in-orbit sensors is an important challenge to ensure long term analysis of earth observation data. Continuous validation of such SR products through comparison with a reference dataset is thus an important challenge. Validating with in situ or airborne SR data is not easy since the sensors rarely match completely the same spectral, spatial and directional characteristics of the satellite measurement. Inter-comparison between satellites sensors data appears as a valuable tool to maintain a long term consistency of the data. However, satellite data are acquired at various times of the day (i.e., variation of the atmosphere content) and within a relative large range of geometry (view and sun angles). Also, even if band-to-band spectral characteristics of optical sensors are closed, they rarely have identical spectral responses. As the results, direct comparisons without consideration of these differences are poorly suitable. In this study, we suggest a new systematic method to assess land optical SR data from high to medium resolution sensors. We used MODIS SR products (MO/YD09CMG) which benefit from a long term calibration/validation process, to assess SR from 3 sensors data: Formosat-2 (280 scenes 24x24km - 5 sites), SPOT-4 (62 scenes 120x60km - 1 site) and Landsat-5/7 (104 180x180km scenes - 50 sites). The main issue concerns the difference in term of geometry acquisition between MODIS and compared sensors data. We used the VJB model (Vermote et al. 2009, TGRS) to correct MODIS SR from BRDF effects and to simulate SR at the corresponding geometry (view and sun angles) of each pixel of the compared sensor data. The comparison is done at the CMG spatial resolution (0.05°) which ensures a constant field-of-view and negligible geometrical errors. Figure 1 displays the summary of the NIR results through APU graphs where metrics A, P and U stands for Accuracy, Precision and Uncertainty (metrics explained in Claverie et al., 2013, RSE) and allows comparison with standard Specifications (S in magenta). The results shows relatively good uncertainty taking into account that atmospheric correction differs from MODIS and the sensors data (LEDAPS for Landsat-5/7 and MACC for Formosat-2 and SPOT-4). Biases (referring to the metric A) are in many cases related to the spectral differences which are analyzed using PROSAIL radiative transfer modeling. Finally some images of Landsat-8 OLI SR (computed using the preliminary adaptation of LEDAPS for Landsat-8) are assessed using this method. Figure 1: APU graph of SR comparison between MODIS NIR (from AQUA) and Landsat-5/7, Formosat-2 and SPOT-4. A, P and U metrics are given per bin (red, green and blue line, respectively) and for the whole range (upper left text values). Magenta line refers to the MODIS SR Specification.

Comparison of Near-Surface Air Temperatures and MODIS Ice-Surface Temperatures at Summit, Greenland (2008-2013)

NASA Technical Reports Server (NTRS)

Shuman, Christopher A.; Hall, Dorothy K.; DiGirolamo, Nicolo E.; Mefford, Thomas K.; Schnaubelt, Michael J.

2014-01-01

We have investigated the stability of the MODerate resolution Imaging Spectroradiometer (MODIS) infrared-derived ice surface temperature (IST) data from Terra for use as a climate quality data record. The availability of climate quality air temperature data (TA) from a NOAA Global Monitoring Division observatory at Greenlands Summit station has enabled this high temporal resolution study of MODIS ISTs. During a 5 year period (July 2008 to August 2013), more than 2500 IST values were compared with 3-minute average TA values derived from the 1-minute data from NOAAs primary 2 m air temperature sensor. These data enabled an expected small offset between air and surface temperatures at this the ice sheet location to be investigated over multiple annual cycles.

Aqua and Terra MODIS RSB Calibration Comparison Using BRDF Modeled Reflectance

NASA Technical Reports Server (NTRS)

Chang, Tiejun; Xiong, Xiaoxiong; Angal, Amit; Wu, Aisheng; Geng, Xu

2017-01-01

The inter-comparison of MODIS reflective solar bands onboard Aqua and Terra is very important for assessment of each instrument's calibration. One of the limitations is the lack of simultaneous nadir overpasses. Their measurements over a selected Earth view target have significant differences in solar and view angles, which magnify the effects of atmospheric scattering and Bidirectional Reflectance Distribution Function (BRDF). In this work, an intercomparison technique is formulated after correction for site's BRDF and atmospheric effects. The reflectance measurements over Libya desert sites 1, 2, and 4 from both the Aqua and Terra MODIS are regressed to a BRDF model with an adjustable coefficient accounting for calibration difference. The ratio between Aqua and Terra reflectance measurements are derived for bands 1 to 9 and the results from different sites show good agreement. For year 2003, the ratios are in the range of 0.985 to1.010 for band 1 to 9. Band 3 shows the lowest ratio 0.985 and band 1 shows the highest ratio 1.010. For the year 2014, the ratio ranges from approximately 0.983 for bands 2 and 1.012 for band 8. The BRDF corrected reflectance for the two instruments are also derived for every year from 2003 to 2014 for stability assessment. Bands 1 and 2 show greater than 1 differences between the two instruments. Aqua bands 1 and 2 show downward trends while Terra bands 1 and 2 show upward trends. Bands 8 and 9 of both Aqua and Terra show large variations of reflectance measurement over time.

Improved meteorology from an updated WRF/CMAQ modeling ...

EPA Pesticide Factsheets

Realistic vegetation characteristics and phenology from the Moderate Resolution Imaging Spectroradiometer (MODIS) products improve the simulation for the meteorology and air quality modeling system WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Quality model) that employs the Pleim-Xiu land surface model (PX LSM). Recently, PX LSM WRF/CMAQ has been updated in vegetation, soil, and boundary layer processes resulting in improved 2 m temperature (T) and mixing ratio (Q), 10 m wind speed, and surface ozone simulations across the domain compared to the previous version for a period around August 2006. Yearlong meteorology simulations with the updated system demonstrate that MODIS input helps reduce bias of the 2 m Q estimation during the growing season from April to September. Improvements follow the green-up in the southeast from April and move toward the west and north through August. From October to March, MODIS input does not have much influence on the system because vegetation is not as active. The greatest effects of MODIS input include more accurate phenology, better representation of leaf area index (LAI) for various forest ecosystems and agricultural areas, and realistically sparse vegetation coverage in the western drylands. Despite the improved meteorology, MODIS input causes higher bias for the surface O3 simulation in April, August, and October in areas where MODIS LAI is much less than the base LAI. Thus, improvement

A Prototype MODI- SSM/I Snow Mapping Algorithm

NASA Technical Reports Server (NTRS)

Tait, Andrew B.; Barton, Jonathan S.; Hall, Dorothy K.

1999-01-01

Data in the wavelength range 0.545 - 1.652 microns from the Moderate Resolution Imaging Spectroradiometer (MODIS), to be launched aboard the Earth Observing System (EOS) Terra in the fall of 1999, will be used to map daily global snow cover at 500m resolution. However, during darkness, or when the satellite's view of the surface is obscured by cloud, snow cover cannot be mapped using MODIS data. We show that during these conditions, it is possible to supplement the MODIS product by mapping the snow cover using passive microwave data from the Special Sensor Microwave Imager (SSM/I), albeit with much poorer resolution. For a 7-day time period in March 1999, a prototype MODIS snow-cover product was compared with a prototype MODIS-SSM/I product for the same area in the mid-western United States. The combined MODIS-SSM/I product mapped 9% more snow cover than the MODIS-only product.

Prototype global burnt area algorithm using the AVHRR-LTDR time series

NASA Astrophysics Data System (ADS)

López-Saldaña, Gerardo; Pereira, José Miguel; Aires, Filipe

2013-04-01

One of the main limitations of products derived from remotely-sensed data is the length of the data records available for climate studies. The Advanced Very High Resolution Radiometer (AVHRR) long-term data record (LTDR) comprises a daily global atmospherically-corrected surface reflectance dataset at 0.05° spatial resolution and is available for the 1981-1999 time period. Fire is strong cause of land surface change and emissions of greenhouse gases around the globe. A global long-term identification of areas affected by fire is needed to analyze trends and fire-clime relationships. A burnt area algorithm can be seen as a change point detection problem where there is an abrupt change in the surface reflectance due to the biomass burning. Using the AVHRR-LTDR dataset, a time series of bidirectional reflectance distribution function (BRDF) corrected surface reflectance was generated using the daily observations and constraining the BRDF model inversion using a climatology of BRDF parameters derived from 12 years of MODIS data. The identification of the burnt area was performed using a t-test in the pre- and post-fire reflectance values and a change point detection algorithm, then spectral constraints were applied to flag changes caused by natural land processes like vegetation seasonality or flooding. Additional temporal constraints are applied focusing in the persistence of the affected areas. Initial results for year 1998, which was selected because of a positive fire anomaly, show spatio-temporal coherence but further analysis is required and a formal rigorous validation will be applied using burn scars identified from high-resolution datasets.

Improvement and validation of trace gas retrieval from ACAM aircraft observation

NASA Astrophysics Data System (ADS)

Liu, C.; Liu, X.; Kowalewski, M. G.; Janz, S. J.; Gonzalez Abad, G.; Pickering, K. E.; Chance, K.; Lamsal, L. N.

2014-12-01

The ACAM (Airborne Compact Atmospheric Mapper) instrument, flown on board the NASA UC-12 aircraft during the DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) campaigns, was designed to provide remote sensing observations of tropospheric and boundary layer pollutants and help understand some of the most important pollutants that directly affect the health of the population. In this study, slant column densities (SCD) of trace gases (O3, NO2, HCHO) are retrieved from ACAM measurements during the Baltimore-Washington D.C. 2011 campaign by the Basic Optical Absorption Spectroscopy (BOAS) trace gas fitting algorithm using a nonlinear least-squares (NLLS) inversion technique, and then are converted to vertical column densities (VCDs) using the Air Mass Factors (AMF) calculated with the VLIDORT (Vector Linearized Discrete Ordinate Radiative Transfer) model and CMAQ (Community Multi-scale Air Quality) model simulations of trace gas profiles. For surface treatment in the AMF, we use high-resolution MODIS climatological BRDF product (Bidirectional Reflectance Distribution Function) at 470 nm for NO2, and use high-resolution surface albedo derived by combining MODIS and OMI albedo databases for HCHO and O3. We validate ACAM results with coincident ground-based PANDORA, aircraft (P3B) spiral and satellite (OMI) measurements and find out generally good agreement especially for NO2 and O3

Assessment of the Collection 6 Terra and Aqua MODIS bands 1 and 2 calibration performance

NASA Astrophysics Data System (ADS)

Wu, A.; Chen, X.; Angal, A.; Li, Y.; Xiong, X.

2015-09-01

MODIS (Moderate Resolution Imaging Spectroradiometer) is a key sensor aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. MODIS collects data in 36 spectral bands and generates over 40 data products for land, atmosphere, cryosphere and oceans. MODIS bands 1 and 2 have nadir spatial resolution of 250 m, compared with 500 m for bands 3 to 7 and 1000 m for all the remaining bands, and their measurements are crucial to derive key land surface products. This study evaluates the calibration performance of the Collection-6 L1B for both Terra and Aqua MODIS bands 1 and 2 using three vicarious approaches. The first and second approaches focus on stability assessment using data collected from two pseudo-invariant sites, Libya 4 desert and Antarctic Dome C snow surface. The third approach examines the relative stability between Terra and Aqua in reference to a third sensor from a series of NOAA 15-19 Advanced Very High Resolution Radiometer (AVHRR). The comparison is based on measurements from MODIS and AVHRR Simultaneous Nadir Overpasses (SNO) over a thirteen-year period from 2002 to 2015. Results from this study provide a quantitative assessment of Terra and Aqua MODIS bands 1 and 2 calibration stability and the relative calibration differences between the two sensors.

Coast of the East Siberian Sea, Russia

NASA Technical Reports Server (NTRS)

2002-01-01

Sea ice is pulling away from the coastline of northeastern Siberia in the east Siberia Sea. This true-color Moderate Resolution Imaging Spectroradiometer (MODIS) image from May 26, 2002, also the thinning of ice in bays and coves, and the blue reflection of the water from beneath causes the ice to appear bright blue. Credit: Jacques Descloitres, MODIS Land Rapid Response Team, NASA/GSFC

Development of an Operational Land Water Mask for MODIS Collection 6, and Influence on Downstream Data Products

NASA Technical Reports Server (NTRS)

Carroll, M. L.; DiMiceli, C. M.; Townshend, J. R. G.; Sohlberg, R. A.; Elders, A. I.; Devadiga, S.; Sayer, A. M.; Levy, R. C.

2016-01-01

Data from the Moderate Resolution Imaging Spectro-radiometer (MODIS)on-board the Earth Observing System Terra and Aqua satellites are processed using a land water mask to determine when an algorithm no longer needs to be run or when an algorithm needs to follow a different pathway. Entering the fourth reprocessing (Collection 6 (C6)) the MODIS team replaced the 1 km water mask with a 500 m water mask for improved representation of the continental surfaces. The new water mask represents more small water bodies for an overall increase in water surface from 1 to 2 of the continental surface. While this is still a small fraction of the overall global surface area the increase is more dramatic in certain areas such as the Arctic and Boreal regions where there are dramatic increases in water surface area in the new mask. MODIS products generated by the on-going C6 reprocessing using the new land water mask show significant impact in areas with high concentrations of change in the land water mask. Here differences between the Collection 5 (C5) and C6 water masks and the impact of these differences on the MOD04 aerosol product and the MOD11 land surface temperature product are shown.

Variability in Surface BRDF at Different Spatial Scales (30m-500m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Gatebe, Charles K.; Schaaf, Crystal B.; Poudyal, Rajesh; Wang, Zhuosen; King, Michael D.

2012-01-01

Over the past decade, the role of multiangle 1 remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75deg off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular 18 characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Variability in Surface BRDF at Different Spatial Scales (30 m-500 m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Gatebe, Charles K.; Schaaf, Crystal B.; Poudyal, Rajesh; Wang, Zhousen; King, Michael D.

2011-01-01

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75 off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertain ties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

PERSPECTIVE Working towards a community-wide understanding of satellite skin temperature observations

NASA Astrophysics Data System (ADS)

Shreve, Cheney

2010-12-01

With more than sixty free and publicly available high-quality datasets, including ecosystem variables, radiation budget variables, and land cover products, the MODIS instrument and the MODIS scientific team have contributed significantly to scientific investigations of ecosystems across the globe. The MODIS instrument, launched in December 1999, has 36 spectral bands, a viewing swath of 2330 km, and acquires data at 250 m, 500 m, and 1000 m spatial resolution every one to two days. Radiation budget variables include surface reflectance, skin temperature, emissivity, and albedo, to list a few. Ecosystem variables include several vegetation indices and productivity measures. Land cover characteristics encompass land cover classifications as well as model parameters and vegetation classifications. Many of these products are instrumental in constraining global climate models and climate change studies, as well as monitoring events such as the recent flooding in Pakistan, the unprecedented oil spill in the Gulf of Mexico, or phytoplankton bloom in the Barents Sea. While product validation efforts by the MODIS scientific team are both vigorous and continually improving, validation is unquestionably one of the most difficult tasks when dealing with remotely derived datasets, especially at the global scale. The quality and availability of MODIS data have led to widespread usage in the scientific community that has further contributed to validation and development of the MODIS products. In their recent paper entitled 'Land surface skin temperature climatology: benefitting from the strengths of satellite observations', Jin and Dickinson review the scientific theory behind, and demonstrate application of, a MODIS temperature product: surface skin temperature. Utilizing datasets from the Global Historical Climatological Network (GHCN), daily skin and air temperature from the Atmospheric Radiation Measurement (ARM) program, and MODIS products (skin temperature, albedo, land cover, water vapor, cloud cover), they show that skin temperature is clearly a different physical parameter from air temperature and varies from air temperature in magnitude, response to atmospheric conditions, and diurnal phase. Although the accuracy of skin temperature (Tskin) algorithms has improved to within 0.5-1°C for field measurements and clear-sky satellite observations (Becker and Li 1995, Goetz et al 1995, Wan and Dozier 1996), general confusion regarding the physical definition of 'surface temperature' and how it can be used for climate studies has persisted throughout the scientific community and limited the applications of these data (Jin and Dickinson 2010). For example, satellite sea surface temperature was used as evidence of global climate change instead of skin temperature in the IPCC 2001 and 2007 reports (Jin and Dickinson 2010). This work provides clarity in the theoretical definition of temperature variables, demonstrates the difference between air and skin temperature, and aids the understanding of the MODIS Tskin product, which could be very beneficial for future climate studies. As outlined by Jin and Dickinson, 'surface temperature' is a vague term commonly used in reference to air temperature, aerodynamic temperature, and skin temperature. Air temperature (Tair), or thermodynamic temperature, is measured by an in situ instrument usually 1.5-2 m above the ground. Aerodynamic temperature (Taero) refers to the temperature at the height of the roughness length of heat. Satellite derived skin temperature (Tskin) is the radiometric temperature derived from the inverse of Planck's function. While these different temperature variables are typically correlated, they differ as a result of environmental conditions (e.g. land cover and sky conditions; Jin and Dickinson 2010). With an extensive network of Tair measurements, some have questioned the benefits of using Tskin at all (Peterson et al 1997, 1998). Tskin and Tair can vary depending on land cover or sky conditions and variations may be large, e.g., for sparsely vegetated areas where net radiation is largely balanced by sensible heat flux (Hall et al 1992, Sun and Mahrt 1995, Jin et al 1997). Tskin can be higher than Taero at midday and lower at night (Sun and Mahrt 1995) and some models use Taero to approximate surface radiative temperature (Hubband and Monteith 1986). One of the strengths of the MODIS instrument is the simultaneous collection of surface and atmospheric conditions. By incorporating a range of MODIS variables in their comparison to Tskin, the authors examine the relationship of Tskin to atmospheric and surface conditions. Results from their global evaluation of Tskin highlight its variability on an inter-annual basis, its variation with solar zenith angle, and diurnal variations, which are not achievable with Tair measurements. Comparison with land cover type illustrates the seasonality of Tskin for different land covers. Comparison with the enhanced vegetation index (EVI) suggests more vegetation reduces skin temperature. Using the MODIS albedo, they demonstrate a clear relationship between yearly averaged Tskin and land surface albedo. Lastly, their examination of water vapor and cloud cover in comparison to Tskin suggests similar seasonality between these two variables. The MODIS Tskin product is not without uncertainty; retrieving Tskin requires a calculation of radiative transfer to account for atmospheric emission and molecular absorption, which is time and resource intensive (Jin and Dickinson 2010). Additionally, surface emissivity, instrument noise, and view angle geometry contribute to error in Tskin estimations (Jin and Dickinson 2010). The transparency of the scientific theory underlying this work, and the clear demonstration of the distinction between temperature measures on varying scales, demonstrates the usefulness of Tskin despite the uncertainties. Perhaps equally as important is the tone; in a time when the controversy surrounding climate change is peaking and the very ethics of the scientific community are being questioned, it is more critical than ever to be transparent in one's work and to assist the scientific community in understanding the tools we have available to us for investigating climate change. References Becker F and Li Z-L 1995 Surface temperature and emissivity at different scales: definition, measurement and related problems Remote Sensing Rev. 12 225-53 Goetz S J, Halthore R, Hall F G and Markham B L 1995 Surface temperature retrieval in a temperate grassland with multi-resolution sensors J. Geophys. Res. Atmos. 100 25397-410 Hall F G, Huemmrich K F, Goetz P J, Sellers P J and Nickeson J E 1992 Satellite remote sensing of the surface energy balance: success, failures and unresolved issues in FIFE J. Geophys. Res. Atmos. 97 19061-90 Jin M and Dickinson R E 2010 Land surface skin temperature climatology: benefitting from the strengths of satellite observations Environ. Res. Lett. 5 044004 Jin M, Dickinson R E and Vogelmann A M 1997 A comparison of CCM2/BATS skin temperature and surface-air temperature with satellite and surface observations J. Climate 10 1505-24 Hubband N D S and Monteith J L 1986 Radiative surface temperature and energy balance of a wheat canopy Boundary Layer Meteorol. 36 107-16 Peterson T C and Vose R S 1997 An overview of the Global Historical Climatology Network temperature data base Bull. Am. Meteorol. Soc. 78 2837-49 Peterson T C, Karl T R, Jamason P F, Knight R and Easterling D R 1998 The first difference method: maximizing station density for the calculation of long-term global temperature change J. Geophys. Res. Atmos. 103 25967-74 Sun J and Mahrt L 1995 Determination of surface fluxes from the surface radiative temperature Atmos. Sci. 52 1096-106 Wan Z and Dozier J 1996 A generalized split-window algorithm for retrieving land-surface temperature from space IEEE Trans. Geosci. Remote Sensing 34 892-905

Generating Global Leaf Area Index from Landsat: Algorithm Formulation and Demonstration

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Nemani, Ramakrishna R.; Zhang, Gong; Hashimoto, Hirofumi; Milesi, Cristina; Michaelis, Andrew; Wang, Weile; Votava, Petr; Samanta, Arindam; Melton, Forrest;

Utility of BRDF Models for Estimating Optimal View Angles in Classification of Remotely Sensed Images

NASA Technical Reports Server (NTRS)

Valdez, P. F.; Donohoe, G. W.

1997-01-01

Statistical classification of remotely sensed images attempts to discriminate between surface cover types on the basis of the spectral response recorded by a sensor. It is well known that surfaces reflect incident radiation as a function of wavelength producing a spectral signature specific to the material under investigation. Multispectral and hyperspectral sensors sample the spectral response over tens and even hundreds of wavelength bands to capture the variation of spectral response with wavelength. Classification algorithms then exploit these differences in spectral response to distinguish between materials of interest. Sensors of this type, however, collect detailed spectral information from one direction (usually nadir); consequently, do not consider the directional nature of reflectance potentially detectable at different sensor view angles. Improvements in sensor technology have resulted in remote sensing platforms capable of detecting reflected energy across wavelengths (spectral signatures) and from multiple view angles (angular signatures) in the fore and aft directions. Sensors of this type include: the moderate resolution imaging spectroradiometer (MODIS), the multiangle imaging spectroradiometer (MISR), and the airborne solid-state array spectroradiometer (ASAS). A goal of this paper, then, is to explore the utility of Bidirectional Reflectance Distribution Function (BRDF) models in the selection of optimal view angles for the classification of remotely sensed images by employing a strategy of searching for the maximum difference between surface BRDFs. After a brief discussion of directional reflect ante in Section 2, attention is directed to the Beard-Maxwell BRDF model and its use in predicting the bidirectional reflectance of a surface. The selection of optimal viewing angles is addressed in Section 3, followed by conclusions and future work in Section 4.

Relating a Spectral Index from MODIS and Tower-based Measurements to Ecosystem Light Use Efficiency for a Fluxnet-Canada Coniferous Forest

NASA Technical Reports Server (NTRS)

Middleton, Elizabeth M.; Cheng, Yen-Ben; Hilker, Thomas; Huemmrich, Karl F.; Black, T. Andrew; Krishnan, Praveena; Coops, Nicholas C.

2008-01-01

As part of the North American Carbon Program effort to quantify the terrestrial carbon budget of North America, we have been examining the possibility of retrieving ecosystem light use efficiency (LUE, the carbon sequestered per unit photosynthetically active radiation) directly from satellite observations. Our novel approach has been to compare LUE derived from tower fluxes with LUE estimated using spectral indices computed from MODIS satellite observations over forests in the Fluxnet-Canada Research Network, using the MODIS narrow ocean bands acquired over land. We matched carbon flux data collected around the time of the MODIS mid-day overpass for over one hundred relatively clear days in five years (2001-2006) from a mature Douglas fir forest in British Columbia. We also examined hyperspectral reflectance data collected diurnally from the tower in conjunction with the eddy correlation fluxes and meteorological measurements made throughout the 2006 growing season at this site. The tower-based flux data provided an opportunity to examine diurnal and seasonal LUE processes and their relationship to spectral indices at the scale of the forest stand. We evaluated LUE in conjunction with the Photochemical Reflectance Index (PRI), a normalized difference spectral index that uses 531 nm and a reference band to capture responses to high light induced stress afforded by the xanthophyll cycle. Canopy structure information, retrieved from airborne laser scanning radar (LiDAR) observations, was used to partition the forest canopy into sunlit and shaded fractions throughout the day, on numerous days during 2006. At each observation period throughout a day, the PRI was examined for the sunlit, shaded, and intermediate canopy segments defined by their instantaneous position relative to the solar principal plane (SPP). The sunlit sector was associated with the illumination "hotspot" (the reflectance backscatter maximum), the shaded sector with the "cold or dark spot" (the reflectance forward scatter minimum), while the intermediate, mixed sunlit/shade sector was located in the cross-plane to the SPP. The PRI indices clearly captured the differences in leaf groups, with sunlit foliage exhibiting the lowest values on sunny days throughout the 2006 season. When tower-based canopy-level LUE was recalculated to estimate foliage-based values (LUE(sub foilage) for the three foliage groups under their incident light environments, a strong linear relationship for PRI:LUE(sub foilage) was demonstrated (0.6 less than or equal to r(sup 2) less than or equal to 0.8, n=822, P<0.0001). The MODIS data represent relatively large areas when acquired at nadir (approx.1 sq km) or at variable off-nadir view angles (greater than or equal to 1 sq km) looking forward or aft. Nevertheless, a similar relationship between MODIS PRI and tower-based LUE was obtained from satellite observations (r(sup 2) = 0.76, n=105, P= 0.026) when the azimuth offsets from the SPP for off-nadir observations were considered. At this relatively high latitude of 50 degrees, the MODIS directional observations were offset from the SPP by approximately 50 degrees, but still represented backscatter or forward scatter sectors of the bidirectional reflectance distribution function (BRDF). The backscatter observations sampled the sunlit forest and provided lower PRI values, in general, than the forward scatter observations from the shaded forest. Since the hotspot and darkspot were not typically directly observed, the dynamic range for MODIS PRI was less than that observed in the SPP at the canopy level; therefore, MODIS PRI values were more similar to those observed in sifu in the BRDF cross-plane. While not ideal in terms of spatial resolution or optimal viewing configuration, the MODIS observations nevertheless provide a means to monitor forest under stress using narrow spectral band indices and off-nadir observations. This research has stimulated several spin-off studies for remote sensinf LUE, and demonstrates the importance of the connection between ecosystem structure and physiological function.

Intercalibration of Two Polar Satellite Instruments Without Simultaneous Nadir Observations

NASA Astrophysics Data System (ADS)

Manninen, Terhikki; Riihela, Aku; Schaaf, Crystal; Key, Jeffrey; Lattanzio, Alessio

2016-08-01

A new intercalibration method for two polar satellite instruments is presented. It is based on statistical fitting of two data sets covering the same area during the same period, but not simultaneously. Deming regression with iterative weights is used. The accuracy of the method was better than about 0.5 % for the MODIS vs. MODIS and AVHRR vs. AVHRR test data sets. The intercalibration of AVHRR vs. MODIS red and NIR channels is carried out and showed a difference of reflectance values of 2% (red) and 6 % (NIR). The red channel intercalibration has slightly higher accuracy for all cases studied.

Terrestrial remote sensing science and algorithms planned for EOS/MODIS

USGS Publications Warehouse

Running, S. W.; Justice, C.O.; Salomonson, V.V.; Hall, D.; Barker, J.; Kaufmann, Y. J.; Strahler, Alan H.; Huete, A.R.; Muller, Jan-Peter; Vanderbilt, V.; Wan, Z.; Teillet, P.; Carneggie, David M. Geological Survey (U.S.) Ohlen

1994-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) will be the primary daily global monitoring sensor on the NASA Earth Observing System (EOS) satellites, scheduled for launch on the EOS-AM platform in June 1998 and the EOS-PM platform in December 2000. MODIS is a 36 channel radiometer covering 0·415-14·235 μm wavelengths, with spatial resolution from 250 m to 1 km at nadir. MODIS will be the primary EOS sensor for providing data on terrestrial biospheric dynamics and process activity. This paper presents the suite of global land products currently planned for EOSDIS implementation, to be developed by the authors of this paper, the MODIS land team (MODLAND). These include spectral albedo, land cover, spectral vegetation indices, snow and ice cover, surface temperature and fire, and a number of biophysical variables that will allow computation of global carbon cycles, hydrologic balances and biogeochemistry of critical greenhouse gases. Additionally, the regular global coverage of these variables will allow accurate surface change detection, a fundamental determinant of global change.

Evaluation of the Event Driven Phenology Model Coupled with the VegET Evapotranspiration Model Through Comparisons with Reference Datasets in a Spatially Explicit Manner

NASA Technical Reports Server (NTRS)

Kovalskyy, V.; Henebry, G. M.; Adusei, B.; Hansen, M.; Roy, D. P.; Senay, G.; Mocko, D. M.

2011-01-01

A new model coupling scheme with remote sensing data assimilation was developed for estimation of daily actual evapotranspiration (ET). The scheme represents a mix of the VegET, a physically based model to estimate ET from a water balance, and an event driven phenology model (EDPM), where the EDPM is an empirically derived crop specific model capable of producing seasonal trajectories of canopy attributes. In this experiment, the scheme was deployed in a spatially explicit manner within the croplands of the Northern Great Plains. The evaluation was carried out using 2007-2009 land surface forcing data from the North American Land Data Assimilation System (NLDAS) and crop maps derived from remotely sensed data of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compared the canopy parameters produced by the phenology model with normalized difference vegetation index (NDVI) data derived from the MODIS nadir bi-directional reflectance distribution function (BRDF) adjusted reflectance (NBAR) product. The expectations of the EDPM performance in prognostic mode were met, producing determination coefficient (r2) of 0.8 +/-.0.15. Model estimates of NDVI yielded root mean square error (RMSE) of 0.1 +/-.0.035 for the entire study area. Retrospective correction of canopy dynamics with MODIS NDVI brought the errors down to just below 10% of observed data range. The ET estimates produced by the coupled scheme were compared with ones from the MODIS land product suite. The expected r2=0.7 +/-.15 and RMSE = 11.2 +/-.4 mm per 8 days were met and even exceeded by the coupling scheme0 functioning in both prognostic and retrospective modes. Minor setbacks of the EDPM and VegET performance (r2 about 0.5 and additional 30 % of RMSR) were found on the peripheries of the study area and attributed to the insufficient EDPM training and to spatially varying accuracy of crop maps. Overall the experiment provided sufficient evidence of soundness and robustness of the EDPM and VegET coupling scheme, assuring its potential for spatially explicit applications.

Maturity-onset diabetes of the young (MODY): how many cases are we missing?

PubMed

Shields, B M; Hicks, S; Shepherd, M H; Colclough, K; Hattersley, A T; Ellard, S

2010-12-01

Maturity-onset diabetes of the young is frequently misdiagnosed as type 1 or type 2 diabetes. A correct diagnosis of MODY is important for determining treatment, but can only be confirmed by molecular genetic testing. We aimed to compare the regional distribution of confirmed MODY cases in the UK and to estimate the minimum prevalence. UK referrals for genetic testing in 2,072 probands and 1,280 relatives between 1996 and 2009 were examined by region, country and test result. Referral rate and prevalence were calculated using UK Census 2001 figures. MODY was confirmed in 1,177 (35%) patients, with HNF1A (52%) and GCK mutations (32%) being most frequent in probands confirmed with MODY. There was considerable regional variation in proband referral rates (from <20 per million in Wales and Northern Ireland to >50 per million for South West England and Scotland) and patients diagnosed with MODY (5.3 per million in Northern Ireland, 48.9 per million in South West England). Referral rates and confirmed cases were highly correlated (r = 0.96, p < 0.0001). The minimum prevalence of MODY was estimated to be 108 cases per million. Assuming this minimal prevalence throughout the UK then >80% of MODY is not diagnosed by molecular testing. The marked regional variation in the prevalence of confirmed MODY directly results from differences in referral rates. This could reflect variation in awareness of MODY or unequal access to genetic testing. Increased referral for diagnostic testing is required if the majority of MODY patients are to have the genetic diagnosis necessary for optimal treatment.

Land, Cryosphere, and Nighttime Environmental Products from Suomi NPP VIIRS: Overview and Status

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Justice, Chris; Csiszar, Ivan

2014-01-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-orbiting Partnership (S-NPP: http://npp.gsfc.nasa.gov/). VIIRS was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer (AVHRR) and provide observation continuity with NASA's Earth Observing System's (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA and NOAA funded scientists have been working to evaluate the instrument performance and derived products to meet the needs of the NOAA operational users and the NASA science community. NOAA's focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the former National Polar-orbiting Environmental Satellite System (NPOESS). The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs and providing MODIS data product continuity. This paper will present to-date findings of the NASA Science Team's evaluation of the VIIRS Land and Cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization (http://viirsland.gsfc.nasa.gov/index.html). The paper will also discuss new capabilities being developed at NASA's Land Product Evaluation and Test Element (http://landweb.nascom.nasa.gov/NPP_QA/); including downstream data and products derived from the VIIRS Day/Night Band (DNB).

Heat waves measured with MODIS land surface temperature data predict changes in avian community structure

Treesearch

Thomas P. Albright; Anna M. Pidgeon; Chadwick D. Rittenhouse; Murray K. Clayton; Curtis H. Flather; Patrick D. Culbert; Volker C. Radeloff

2011-01-01

Heat waves are expected to become more frequent and severe as climate changes, with unknown consequences for biodiversity. We sought to identify ecologically-relevant broad-scale indicators of heat waves based on MODIS land surface temperature (LST) and interpolated air temperature data and assess their associations with avian community structure. Specifically, we...

Validation of AIRS V6 Surface Temperature over Greenland with GCN and NOAA Stations

NASA Technical Reports Server (NTRS)

Lee, Jae N.; Hearty, Thomas; Cullather, Richard; Nowicki, Sophie; Susskind, Joel

2016-01-01

This work compares the temporal and spatial characteristics of the AIRSAMSU (Atmospheric Infrared Sounder Advanced Microwave Sounding Unit A) Version 6 and MODIS (Moderate resolution Imaging Spectroradiometer) Collection 5 derived surface temperatures over Greenland. To estimate uncertainties in space-based surface temperature measurements, we re-projected the MODIS Ice Surface Temperature (IST) to 0.5 by 0.5 degree spatial resolution. We also re-gridded AIRS Skin Temperature (Ts) into the same grid but classified with different cloud conditions and surface types. These co-located data sets make intercomparison between the two instruments relatively straightforward. Using this approach, the spatial comparison between the monthly mean AIRS Ts and MODIS IST is in good agreement with RMS 2K for May 2012. This approach also allows the detection of any long-term calibration drift and the careful examination of calibration consistency in the MODIS and AIRS temperature data record. The temporal correlations between temperature data are also compared with those from in-situ measurements from GC-Net (GCN) and NOAA stations. The coherent time series of surface temperature evident in the correlation between AIRS Ts and GCN temperatures suggest that at monthly time scales both observations capture the same climate signal over Greenland. It is also suggested that AIRS surface air temperature (Ta) can be used to estimate the boundary layer inversion.

Characterization of seasonal variation of forest canopy in a temperate deciduous broadleaf forest, using daily MODIS data

Treesearch

Qingyuan Zhang; Xiangming Xiao; Bobby Braswell; Ernst Linder; Scott Ollinger; Marie-Louise Smith; Julian P. Jenkins; Fred Baret; Andrew D. Richardson; Berrien III Moore; Rakesh Minocha

2006-01-01

In this paper, we present an improved procedure for collecting no or little atmosphere- and snow-contaminated observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The resultant time series of daily MODIS data of a temperate deciduous broadleaf forest (the Bartlett Experimental Forest) in 2004 show strong seasonal dynamics of surface...

Improving the MODIS Global Snow-Mapping Algorithm

NASA Technical Reports Server (NTRS)

Klein, Andrew G.; Hall, Dorothy K.; Riggs, George A.

1997-01-01

An algorithm (Snowmap) is under development to produce global snow maps at 500 meter resolution on a daily basis using data from the NASA MODIS instrument. MODIS, the Moderate Resolution Imaging Spectroradiometer, will be launched as part of the first Earth Observing System (EOS) platform in 1998. Snowmap is a fully automated, computationally frugal algorithm that will be ready to implement at launch. Forests represent a major limitation to the global mapping of snow cover as a forest canopy both obscures and shadows the snow underneath. Landsat Thematic Mapper (TM) and MODIS Airborne Simulator (MAS) data are used to investigate the changes in reflectance that occur as a forest stand becomes snow covered and to propose changes to the Snowmap algorithm that will improve snow classification accuracy forested areas.

Retrieval of seasonal dynamics of forest understory reflectance from semiarid to boreal forests using MODIS BRDF data

NASA Astrophysics Data System (ADS)

Pisek, Jan; Chen, Jing M.; Kobayashi, Hideki; Rautiainen, Miina; Schaepman, Michael E.; Karnieli, Arnon; Sprinstin, Michael; Ryu, Youngryel; Nikopensius, Maris; Raabe, Kairi

2016-03-01

Spatial and temporal patterns of forest background (understory) reflectance are crucial for retrieving biophysical parameters of forest canopies (overstory) and subsequently for ecosystem modeling. In this communication, we retrieved seasonal courses of understory normalized difference vegetation index (NDVI) from multiangular Moderate Resolution Imaging Spectroradiometer bidirectional reflectance distribution function (MODIS BRDF)/albedo data. We compared satellite-based seasonal courses of understory NDVI to understory NDVI values measured in different types of forests distributed along a wide latitudinal gradient (65.12°N-31.35°N). Our results indicated that the retrieval method performs well particularly over open forests of different types. We also demonstrated the limitations of the method for closed canopies, where the understory signal retrieval is much attenuated.

XBAER-derived aerosol optical thickness from OLCI/Sentinel-3 observation

NASA Astrophysics Data System (ADS)

Mei, Linlu; Rozanov, Vladimir; Vountas, Marco; Burrows, John P.; Richter, Andreas

2018-02-01

A cloud identification algorithm used for cloud masking, which is based on the spatial variability of reflectances at the top of the atmosphere in visible wavelengths, has been developed for the retrieval of aerosol properties by MODIS. It is shown that the spatial pattern of cloud reflectance, as observed from space, is very different from that of aerosols. Clouds show a high spatial variability in the scale of a hundred metres to a few kilometres, whereas aerosols in general are homogeneous. The concept of spatial variability of reflectances at the top of the atmosphere is mainly applicable over the ocean, where the surface background is sufficiently homogeneous for the separation between aerosols and clouds. Aerosol retrievals require a sufficiently accurate cloud identification to be able to mask these ground scenes. However, a conservative mask will exclude strong aerosol episodes and a less conservative mask could introduce cloud contamination that biases the retrieved aerosol optical properties (e.g. aerosol optical depth and effective radii). A detailed study on the effect of cloud contamination on aerosol retrievals has been performed and parameters are established determining the threshold value for the MODIS aerosol cloud mask (3×3-STD) over the ocean. The 3×3-STD algorithm discussed in this paper is the operational cloud mask used for MODIS aerosol retrievals over the ocean.A prolonged pollution haze event occurred in the northeast part of China during the period 16-21 December 2016. To assess the impact of such events, the amounts and distribution of aerosol particles, formed in such events, need to be quantified. The newly launched Ocean Land Colour Instrument (OLCI) onboard Sentinel-3 is the successor of the MEdium Resolution Imaging Spectrometer (MERIS). It provides measurements of the radiance and reflectance at the top of the atmosphere, which can be used to retrieve the aerosol optical thickness (AOT) from synoptic to global scales. In this study, the recently developed AOT retrieval algorithm eXtensible Bremen AErosol Retrieval (XBAER) has been applied to data from the OLCI instrument for the first time to illustrate the feasibility of applying XBAER to the data from this new instrument. The first global retrieval results show similar patterns of aerosol optical thickness, AOT, to those from MODIS and MISR aerosol products. The AOT retrieved from OLCI is validated by comparison with AERONET observations and a correlation coefficient of 0.819 and bias (root mean square) of 0.115 is obtained. The haze episode is well captured by the OLCI-derived AOT product. XBAER is shown to retrieve AOT well from the observations of MERIS and OLCI.

Harmonized Landsat/Sentinel-2 Reflectance Products for Land Monitoring (Invited)

NASA Technical Reports Server (NTRS)

Masek, Jeffrey G.; Dungan, Jennifer L.; Ju, Junchang; Roger, Jean-Claude; Claverie, Martin P.; Skakun, Sergii; Vermote, Eric; Justice, Christopher Owen

2017-01-01

Many land applications require more frequent observations than can be obtained from a single 'Landsat class'� sensor. Agricultural monitoring, inland water quality assessment, stand-scale phenology, and numerous other applications all require near-daily imagery at better than 1ha resolution. Thus the land science community has begun expressing a desire for a '30-meter MODIS' global monitoring capability. One cost-effective way to achieve this goal is via merging data from multiple, international observatories into a single virtual constellation. The Harmonized Landsat/Sentinel-2 (HLS) project has been working to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2. Harmonization in this context requires a series of radiometric and geometric transforms to create a single surface reflectance time series agnostic to sensor origin. Radiometric corrections include a common atmospheric correction using the Landsat-8 LaSRC/6S approach, a simple BRDF adjustment to constant solar and nadir view angle, and spectral bandpass adjustments to fit the Landsat-8 OLI reference. Data are then resampled to a consistent 30m UTM grid, using the Sentinel-2 global tile system. Cloud and shadow masking are also implemented. Quality assurance (QA) involves comparison of the output 30m HLS products with near-simultaneous MODIS nadir-adjusted observations. Prototoype HLS products have been processed for approximately 7% of the global land area using the NASA Earth Exchange (NEX) compute environment at NASA Ames, and can be downloaded from the HLS web site (https://hls.gsfc.nasa.gov). A wall-to-wall North America data set is being prepared for 2018. This talk will review the objectives and status of the HLS project, and illustrate applications of high-density optical time series data for agriculture and ecology. We also discuss lessons learned from HLS in the general context of implementing virtual constellations.

Harmonized Landsat/Sentinel-2 Reflectance Products for Land Monitoring

NASA Astrophysics Data System (ADS)

Masek, J. G.; Ju, J.; Claverie, M.; Vermote, E.; Dungan, J. L.; Roger, J. C.; Skakun, S.; Justice, C. O.

2017-12-01

Many land applications require more frequent observations than can be obtained from a single "Landsat class" sensor. Agricultural monitoring, inland water quality assessment, stand-scale phenology, and numerous other applications all require near-daily imagery at better than 1ha resolution. Thus the land science community has begun expressing a desire for a "30-meter MODIS" global monitoring capability. One cost-effective way to achieve this goal is via merging data from multiple, international observatories into a single virtual constellation. The Harmonized Landsat/Sentinel-2 (HLS) project has been working to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2. Harmonization in this context requires a series of radiometric and geometric transforms to create a single surface reflectance time series agnostic to sensor origin. Radiometric corrections include a common atmospheric correction using the Landsat-8 LaSRC/6S approach, a simple BRDF adjustment to constant solar and nadir view angle, and spectral bandpass adjustments to fit the Landsat-8 OLI reference. Data are then resampled to a consistent 30m UTM grid, using the Sentinel-2 global tile system. Cloud and shadow masking are also implemented. Quality assurance (QA) involves comparison of the output 30m HLS products with near-simultaneous MODIS nadir-adjusted observations. Prototoype HLS products have been processed for 7% of the global land area using the NASA Earth Exchange (NEX) compute environment at NASA Ames, and can be downloaded from the HLS web site (https://hls.gsfc.nasa.gov). A wall-to-wall North America data set is being prepared for 2018.This talk will review the objectives and status of the HLS project, and illustrate applications of high-density optical time series data for agriculture and ecology. We also discuss lessons learned from HLS in the general context of implementing virtual constellations.

Different combination of MODIS land surface temperature data for daily air surface temperature estimation in North West Vietnam

NASA Astrophysics Data System (ADS)

Noi Phan, Thanh; Kappas, Martin; Degener, Jan

2017-04-01

Land air temperature (Ta) with high spatial and temporal resolution plays an important role in various applications, such as: crop growth monitoring and simulations, environmental risk models, weather forecasting, land use cover change, urban heat islands, etc. Daily Ta (including Ta-max, Ta-min, and Ta-mean) is usually measured by weather stations (often at 2 m above the ground); thus, Ta is limited in spatial coverage. Satellite data, especially MODIS land surface temperature (LST) data at 1 kilometre and high temporal resolution (4 times per day, combining TERRA and AQUA) are free available and easily to access. However, there is a difference between Ta and LST because of the complex surface energy budget and multiple related variables between them. Several researches states that the Ta could be estimated using MODIS LST data with accurate of 2-4oC. However, there are only a handful of studies using dynamically combining of four MODIS LST data for Ta estimation. In this study, we evaluated all 15 - possible - combinations of four MODIS LST using support vector machine (SVM) and random forests (RFs) models. MODIS LST and Ta data was extracted from 4 weather stations in rural area in North West Vietnam from 2010 to 2012 (three years). Our results indicated that the accuracy of Ta estimation was affected by the different combination and the combined data (multiple variables) gave better results than those of single LST (solely variable), the best result was achieved (coefficient of determination (R2) = 0.95, 0.97, 0.97; root mean square error (RMSE) =1.7, 1.4, 1.2 oC for Ta-min, Ta-max, Ta-mean respectively) when all four LSTs were combined and RFs performed better than SVM.

MALIBU: A High Spatial Resolution Multi-Angle Imaging Unmanned Airborne System to Validate Satellite-derived BRDF/Albedo Products

NASA Astrophysics Data System (ADS)

Wang, Z.; Roman, M. O.; Pahlevan, N.; Stachura, M.; McCorkel, J.; Bland, G.; Schaaf, C.

2016-12-01

Albedo is a key climate forcing variable that governs the absorption of incoming solar radiation and its ultimate transfer to the atmosphere. Albedo contributes significant uncertainties in the simulation of climate changes; and as such, it is defined by the Global Climate Observing System (GCOS) as a terrestrial essential climate variable (ECV) required by global and regional climate and biogeochemical models. NASA's Goddard Space Flight Center's Multi AngLe Imaging Bidirectional Reflectance Distribution Function small-UAS (MALIBU) is part of a series of pathfinder missions to develop enhanced multi-angular remote sensing techniques using small Unmanned Aircraft Systems (sUAS). The MALIBU instrument package includes two multispectral imagers oriented at two different viewing geometries (i.e., port and starboard sides) capture vegetation optical properties and structural characteristics. This is achieved by analyzing the surface reflectance anisotropy signal (i.e., BRDF shape) obtained from the combination of surface reflectance from different view-illumination angles and spectral channels. Satellite measures of surface albedo from MODIS, VIIRS, and Landsat have been evaluated by comparison with spatially representative albedometer data from sparsely distributed flux towers at fixed heights. However, the mismatch between the footprint of ground measurements and the satellite footprint challenges efforts at validation, especially for heterogeneous landscapes. The BRDF (Bidirectional Reflectance Distribution Function) models of surface anisotropy have only been evaluated with airborne BRDF data over a very few locations. The MALIBU platform that acquires extremely high resolution sub-meter measures of surface anisotropy and surface albedo, can thus serve as an important source of reference data to enable global land product validation efforts, and resolve the errors and uncertainties in the various existing products generated by NASA and its national and international partners.

Performance of MODIS satellite and mesoscale model based land surface temperature for soil moisture deficit estimation using Neural Network

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K.; Petropoulos, George P.; Gupta, Manika; Islam, Tanvir

2015-04-01

Soil Moisture Deficit (SMD) is a key variable in the water and energy exchanges that occur at the land-surface/atmosphere interface. Monitoring SMD is an alternate method of irrigation scheduling and represents the use of the suitable quantity of water at the proper time by combining measurements of soil moisture deficit. In past it is found that LST has a strong relation to SMD, which can be estimated by MODIS or numerical weather prediction model such as WRF (Weather Research and Forecasting model). By looking into the importance of SMD, this work focused on the application of Artificial Neural Network (ANN) for evaluating its capabilities towards SMD estimation using the LST data estimated from MODIS and WRF mesoscale model. The benchmark SMD estimated from Probability Distribution Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the calibration and validation experiments. The performances between observed and simulated SMD are assessed in terms of the Nash-Sutcliffe Efficiency (NSE), the Root Mean Square Error (RMSE) and the percentage of bias (%Bias). The application of the ANN confirmed a high capability WRF and MODIS LST for prediction of SMD. Performance during the ANN calibration and validation showed a good agreement between benchmark and estimated SMD with MODIS LST information with significantly higher performance than WRF simulated LST. The work presented showed the first comprehensive application of LST from MODIS and WRF mesoscale model for hydrological SMD estimation, particularly for the maritime climate. More studies in this direction are recommended to hydro-meteorological community, so that useful information will be accumulated in the technical literature domain for different geographical locations and climatic conditions. Keyword: WRF, Land Surface Temperature, MODIS satellite, Soil Moisture Deficit, Neural Network

Assimilating leaf area index of three typical types of subtropical forest in China from MODIS time series data based on the integrated ensemble Kalman filter and PROSAIL model

NASA Astrophysics Data System (ADS)

Li, Xuejian; Mao, Fangjie; Du, Huaqiang; Zhou, Guomo; Xu, Xiaojun; Han, Ning; Sun, Shaobo; Gao, Guolong; Chen, Liang

2017-04-01

Subtropical forest ecosystems play essential roles in the global carbon cycle and in carbon sequestration functions, which challenge the traditional understanding of the main functional areas of carbon sequestration in the temperate forests of Europe and America. The leaf area index (LAI) is an important biological parameter in the spatiotemporal simulation of the carbon cycle, and it has considerable significance in carbon cycle research. Dynamic retrieval based on remote sensing data is an important method with which to obtain large-scale high-accuracy assessments of LAI. This study developed an algorithm for assimilating LAI dynamics based on an integrated ensemble Kalman filter using MODIS LAI data, MODIS reflectance data, and canopy reflectance data modeled by PROSAIL, for three typical types of subtropical forest (Moso bamboo forest, Lei bamboo forest, and evergreen and deciduous broadleaf forest) in China during 2014-2015. There were some errors of assimilation in winter, because of the bad data quality of the MODIS product. Overall, the assimilated LAI well matched the observed LAI, with R2 of 0.82, 0.93, and 0.87, RMSE of 0.73, 0.49, and 0.42, and aBIAS of 0.50, 0.23, and 0.03 for Moso bamboo forest, Lei bamboo forest, and evergreen and deciduous broadleaf forest, respectively. The algorithm greatly decreased the uncertainty of the MODIS LAI in the growing season and it improved the accuracy of the MODIS LAI. The advantage of the algorithm is its use of biophysical parameters (e.g., measured LAI) in the LAI assimilation, which makes it possible to assimilate long-term MODIS LAI time series data, and to provide high-accuracy LAI data for the study of carbon cycle characteristics in subtropical forest ecosystems.

Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, MODIS, and MISR

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Wind, Galina; Arnold, G. Thomas; Dominguez, Roseanne T.

2010-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 microns (12.9 microns for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability Of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process MODIS Cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.

The Continuous Monitoring of Desert Dust using an Infrared-based Dust Detection and Retrieval Method

NASA Technical Reports Server (NTRS)

Duda, David P.; Minnis, Patrick; Trepte, Qing; Sun-Mack, Sunny

2006-01-01

Airborne dust and sand are significant aerosol sources that can impact the atmospheric and surface radiation budgets. Because airborne dust affects visibility and air quality, it is desirable to monitor the location and concentrations of this aerosol for transportation and public health. Although aerosol retrievals have been derived for many years using visible and near-infrared reflectance measurements from satellites, the detection and quantification of dust from these channels is problematic over bright surfaces, or when dust concentrations are large. In addition, aerosol retrievals from polar orbiting satellites lack the ability to monitor the progression and sources of dust storms. As a complement to current aerosol dust retrieval algorithms, multi-spectral thermal infrared (8-12 micron) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Meteosat-8 Spinning Enhanced Visible and Infrared Imager (SEVIRI) are used in the development of a prototype dust detection method and dust property retrieval that can monitor the progress of Saharan dust fields continuously, both night and day. The dust detection method is incorporated into the processing of CERES (Clouds and the Earth s Radiant Energy System) aerosol retrievals to produce dust property retrievals. Both MODIS (from Terra and Aqua) and SEVERI data are used to develop the method.

Differences in liquid cloud droplet effective radius and number concentration estimates between MODIS Collections 5.1 and 6 over global oceans.

PubMed

Rausch, John; Meyer, Kerry; Bennartz, Ralf; Platnick, Steven

2017-01-01

Differences in cloud droplet effective radius and cloud droplet number concentration (CDNC) estimates inferred from the Aqua MODIS Collections 5.1 and 6 cloud products (MYD06) are examined for warm clouds over global oceans for the year 2008. Individual pixel level retrievals for both collections are aggregated to 1° × 1° and compared globally and regionally for the three main spectral channel pairs used for MODIS cloud optical property retrievals. Comparisons between both collections are performed for cases in which all three effective radii retrievals are classified by the MODIS Cloud Product as valid. The contribution to the observed differences of several key MYD06 Collection 6 algorithm updates are also explored, with a focus on changes to the surface reflectance model, assumed solar irradiance, above cloud emission, cloud top pressure, and pixel registration. Global results show a neutral to positive (> 50 cm -3 ) change for C6-derived CDNC relative to C5.1 for the 1.6 µm and 2.1 µm channel retrievals, corresponding to a neutral to -2 µm difference in droplet effective radius. For 3.7 µm retrievals, CDNC results show a negative change in the tropics, with differences transitioning toward positive values with increasing latitude spanning -25 to +50 cm -3 related to a +2.5 to -1 µm transition in effective radius. Cloud optical thickness differences were small relative to effective radius, and found to not significantly impact CDNC estimates. Regionally, the magnitude and behavior of the annual CDNC cycle are compared for each effective radius retrieval. Results from this study indicate significant intercollection differences in aggregated values of effective radius due to changes to the pre-computed retrieval lookup tables for ocean scenes, changes to retrieved cloud top pressure, solar irradiance, or above cloud thermal emission, depending upon spectral channel. The observed differences between collections may have implications for existing MODIS derived climatologies and validation studies of effective radius and CDNC.

Synergetic use of Aerosol Robotic Network (AERONET) and Moderate Image Spectrometer (MODIS)

NASA Technical Reports Server (NTRS)

Kaufman, Y.

2004-01-01

I shall describe several distinct modes in which AERONET data are used in conjunction with MODIS data to evaluate the global aerosol system and its impact on climate. These includes: 1) Evaluation of the aerosol diurnal cycle not available from MODIS, and the relationship between the aerosol properties derived from MODIS and the daily average of these properties; 2) Climatology of the aerosol size distribution and single scattering albedo. The climatology is used to formulate the assumptions used in the MODIS look up tables used in the inversion of MODIS data; 3) Measurement of the aerosol effect on irradiation of the surface, this is used in conjunction with the MODIS evaluation of the aerosol effect at the TOA; and 4) Assessment of the aerosol baseline on top off which the satellite data are used to find the amount of dust or anthropogenic aerosol.

Accessing Recent Trend of Land Surface Temperature from Satellite Observations

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Romanov, Peter

2011-01-01

Land surface temperature (Ts) is an important element to measure the state of terrestrial ecosystems and to study surface energy budgets. In support of the land cover/land use change-related international program MAIRS (Monsoon Asia Integrated Regional Study), we have collected global monthly Ts measured by MODIS since the beginning of the missions. The MODIS Ts time series have approximately 11 years of data from Terra since 2000 and approximately 9 years of data from Aqua since 2002, which makes possible to study the recent climate, such as trend. In this study, monthly climatology from two platforms are calculated and compared with that from AIRS. The spatial patterns of Ts trends are accessed, focusing on the Eurasia region. Furthermore, MODIS Ts trends are compared with those from AIRS and NASA's atmospheric assimilation model, MERRA (Modern Era Retrospective-analysis for Research and Applications). The preliminary results indicate that the recent 8-year Ts trend shows an oscillation-type spatial variation over Eurasia. The pattern is consistent for data from MODIS, AIRS, and MERRA, with the positive center over Eastern Europe, and the negative center over Central Siberia. The calculated climatology and anomaly of MODIS Ts will be integrated into the online visualization system, Giovanni, at NASA GES DISC for easy use by scientists and general public.

Near-surface temperature inversion during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

NASA Astrophysics Data System (ADS)

Adolph, Alden C.; Albert, Mary R.; Hall, Dorothy K.

2018-03-01

As rapid warming of the Arctic occurs, it is imperative that climate indicators such as temperature be monitored over large areas to understand and predict the effects of climate changes. Temperatures are traditionally tracked using in situ 2 m air temperatures and can also be assessed using remote sensing techniques. Remote sensing is especially valuable over the Greenland Ice Sheet, where few ground-based air temperature measurements exist. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and the temperature of the actual snow surface (referred to as skin temperature) can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign extending from 8 June to 18 July 2015, near Summit Station in Greenland, to study surface temperature using the following measurements: skin temperature measured by an infrared (IR) sensor, 2 m air temperature measured by a National Oceanic and Atmospheric Administration (NOAA) meteorological station, and a Moderate Resolution Imaging Spectroradiometer (MODIS) surface temperature product. Our data indicate that 2 m air temperature is often significantly higher than snow skin temperature measured in situ, and this finding may account for apparent biases in previous studies of MODIS products that used 2 m air temperature for validation. This inversion is present during our study period when incoming solar radiation and wind speed are both low. As compared to our in situ IR skin temperature measurements, after additional cloud masking, the MOD/MYD11 Collection 6 surface temperature standard product has an RMSE of 1.0 °C and a mean bias of -0.4 °C, spanning a range of temperatures from -35 to -5 °C (RMSE = 1.6 °C and mean bias = -0.7 °C prior to cloud masking). For our study area and time series, MODIS surface temperature products agree with skin surface temperatures better than previous studies indicated, especially at temperatures below -20 °C, where other studies found a significant cold bias. We show that the apparent cold bias present in other comparisons of 2 m air temperature and MODIS surface temperature may be a result of the near-surface temperature inversion. Further investigation of how in situ IR skin temperatures compare to MODIS surface temperature at lower temperatures (below -35 °C) is warranted to determine whether a cold bias exists for those temperatures.

Photosynthetic Efficiency of Northern Forest Ecosystems Using a MODIS-Derived Photochemical Reflectance Index (PRI)

NASA Technical Reports Server (NTRS)

Middleton, E. M.; Huemmrich, K. F.; Landis, D. R.; Black, T. A.; Barr, A. G.; McCaughey, J. H.

2016-01-01

This study evaluates a direct remote sensing approach from space for the determination of ecosystem photosynthetic light use efficiency (LUE), through measurement of vegetation reflectance changes expressed with the Photochemical Reflectance Index (PRI). The PRI is a normalized difference index based on spectral changes at a physiologically active wavelength (approximately 531 nanometers) as compared to a reference waveband, and is only available from a very few satellites. These include the two Moderate-Resolution Imaging Spectroradiometers (MODIS) on the Aqua and Terra satellites each of which have a narrow (10-nanometer) ocean band centered at 531 nanometers. We examined several PRI variations computed with candidate reference bands, since MODIS lacks the traditional 570-nanometer reference band. The PRI computed using MODIS land band 1 (620-670 nanometers) gave the best performance for daily LUE estimation. Through rigorous statistical analyses over a large image collection (n equals 420), the success of relating in situ daily tower-derived LUE to MODIS observations for northern forests was strongly influenced by satellite viewing geometry. LUE was calculated from CO2 fluxes (moles per moles of carbon absorbed quanta) measured at instrumented Canadian Carbon Program flux towers in four Canadian forests: a mature fir site in British Columbia, mature aspen and black spruce sites in Saskatchewan, and a mixed deciduous/coniferous forest site in Ontario. All aspects of the viewing geometry had significant effects on the MODIS-PRI, including the view zenith angle (VZA), the view azimuth angle, and the displacement of the view azimuth relative to the solar principal plane, in addition to illumination related variables.Nevertheless, we show that forward scatter sector views (VZA, 16 degrees-45 degrees) provided the strongest relationships to daily LUE, especially those collected in the early afternoon by Aqua (r squared = 0.83, RMSE (root mean square error) equals 0.003 moles per moles of carbon absorbed quanta). Nadir (VZA, 0 degrees plus or minus 15 degrees) and backscatter views (VZA, -16 degrees to -45 degrees) had lower performance in estimating LUE (nadir: r squared approximately equal to 0.62-0.67; backscatter: r squared approximately equal to 0.54-0.59) and similar estimation error (RMSE equals 0.004-0.005).When directional effects were not considered, only a moderately successful MODIS-PRI vs. LUE relationship (r squared equals 0.34, RMSE equals 0.007) was obtained in the full dataset (all views & sites, both satellites), but site-specific relationships were able to discriminate between coniferous and deciduous forests. Overall, MODIS-PRI values from Terra (late morning) were higher than those from Aqua (early afternoon), before/after the onset of diurnal stress responses expressed spectrally. Therefore, we identified ninety-two Terra-Aqua "same day" pairs, for which the sum of Terra morning and Aqua afternoon MODIS-PRI values (PRI (sub sum) using all available directional observations was linearly correlated with daily tower LUE (r squared equals 0.622, RMSE equals 0.013) and independent of site differences or meteorological information. Our study highlights the value of off-nadir directional reflectance observations, and the value of pairing morning and afternoon satellite observations to monitor stress responses that inhibit carbon uptake in Canadian forest ecosystems. In addition, we show that MODIS-PRI values, when derived from either: (i) forward views only, or (ii) Terra/Aqua same day (any view) combined observations, provided more accurate estimates of tower-measured daily LUE than those derived from either nadir or backscatter views or those calculated by the widely used semi-operational MODIS GPP model (MOD17) which is based on a theoretical maximum LUE and environmental data. Consequently, we demonstrate the importance of diurnal as well as off-nadir satellite observations for detecting vegetation physiological processes.

Remote Sensing of Lake Ice Phenology in Alaska

NASA Astrophysics Data System (ADS)

Zhang, S.; Pavelsky, T.

2017-12-01

Lake ice phenology (e.g. ice break-up and freeze-up timing) in Alaska is potentially sensitive to climate change. However, there are few current lake ice records in this region, which hinders the comprehensive understanding of interactions between climate change and lake processes. To provide a lake ice database with over a comparatively long time period (2000 - 2017) and large spatial coverage (4000+ lakes) in Alaska, we have developed an algorithm to detect the timing of lake ice using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. This approach generally consists of three major steps. First, we use a cloud mask (MOD09GA) to filter out satellite images with heavy cloud contamination. Second, daily MODIS reflectance values (MOD09GQ) of lake surface are used to extract ice pixels from water pixels. The ice status of lakes can be further identified based on the fraction of ice pixels. Third, to improve the accuracy of ice phenology detection, we execute post-processing quality control to reduce false ice events caused by outliers. We validate the proposed algorithm over six lakes by comparing with Landsat-based reference data. Validation results indicate a high correlation between the MODIS results and reference data, with normalized root mean square error (NRMSE) ranging from 1.7% to 4.6%. The time series of this lake ice product is then examined to analyze the spatial and temporal patterns of lake ice phenology.

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation.

Treesearch

David P. Turner; William D. Ritts; Warren B. Cohen; Stith T. Gower; Maosheng Zhao; Steve W. Running; Steven C. Wofsy; Shawn Urbanski; Allison L. Dunn; J.W. Munger

2003-01-01

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using...

Moderate Resolution Imaging Spectroradiometer (MODIS) Overview

USGS Publications Warehouse

,

2008-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is an instrument that collects remotely sensed data used by scientists for monitoring, modeling, and assessing the effects of natural processes and human actions on the Earth's surface. The continual calibration of the MODIS instruments, the refinement of algorithms used to create higher-level products, and the ongoing product validation make MODIS images a valuable time series (2000-present) of geophysical and biophysical land-surface measurements. Carried on two National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) satellites, MODIS acquires morning (EOS-Terra) and afternoon (EOS-Aqua) views almost daily. Terra data acquisitions began in February 2000 and Aqua data acquisitions began in July 2002. Land data are generated only as higher-level products, removing the burden of common types of data processing from the user community. MODIS-based products describing ecological dynamics, radiation budget, and land cover are projected onto a sinusoidal mapping grid and distributed as 10- by 10-degree tiles at 250-, 500-, or 1,000-meter spatial resolution. Some products are also created on a 0.05-degree geographic grid to support climate modeling studies. All MODIS products are distributed in the Hierarchical Data Format-Earth Observing System (HDF-EOS) file format and are available through file transfer protocol (FTP) or on digital video disc (DVD) media. Versions 4 and 5 of MODIS land data products are currently available and represent 'validated' collections defined in stages of accuracy that are based on the number of field sites and time periods for which the products have been validated. Version 5 collections incorporate the longest time series of both Terra and Aqua MODIS data products.

Fine Resolution Air Quality Monitoring from a Small Satellite: CHRIS/PROBA.

PubMed

Nichol, Janet E; Wong, Man Sing; Chan, Yuk Ying

2008-11-27

Current remote sensing techniques fail to address the task of air quality monitoring over complex regions where multiple pollution sources produce high spatial variability. This is due to a lack of suitable satellite-sensor combinations and appropriate aerosol optical thickness (AOT) retrieval algorithms. The new generation of small satellites, with their lower costs and greater flexibility has the potential to address this problem, with customised platform-sensor combinations dedicated to monitoring single complex regions or mega-cities. This paper demonstrates the ability of the European Space Agency's small satellite sensor CHRIS/PROBA to provide reliable AOT estimates at a spatially detailed level over Hong Kong, using a modified version of the dense dark vegetation (DDV) algorithm devised for MODIS. Since CHRIS has no middle-IR band such as the MODIS 2,100 nm band which is transparent to fine aerosols, the longest waveband of CHRIS, the 1,019 nm band was used to approximate surface reflectance, by the subtraction of an offset derived from synchronous field reflectance spectra. Aerosol reflectance in the blue and red bands was then obtained from the strong empirical relationship observed between the CHRIS 1,019 nm, and the blue and red bands respectively. AOT retrievals for three different dates were shown to be reliable, when compared with AERONET and Microtops II sunphotometers, and a Lidar, as well as air quality data at ground stations. The AOT images exhibited considerable spatial variability over the 11 x 11km image area and were able to indicate both local and long distance sources.

Remote Sensing of Aerosol and Aerosol Radiative Forcing of Climate from EOS Terra MODIS Instrument

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Tanre, Didier; Remer, Lorraine; Einaudi, Franco (Technical Monitor)

2000-01-01

The recent launch of EOS-Terra into polar orbit has begun to revolutionize remote sensing of aerosol and their effect on climate. Terra has five instruments, two of them,Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectro-Radiometer (MISR) are designed to monitor global aerosol in two different complementary ways. Here we shall discuss the use of the multispectral measurements of MODIS to derive: (1) the global distribution of aerosol load (and optical thickness) over ocean and land; (2) to measure the impact of aerosol on reflection of sunlight to space; and (3) to measure the ability of aerosol to absorb solar radiation. These measurements have direct applications on the understanding of the effect of aerosol on climate, the ability to predict climate change, and on the monitoring of dust episodes and man-made pollution. Principles of remote sensing of aerosol from MODIS will be discussed and first examples of measurements from MODIS will be provided.

Ground-Truthing Moderate Resolution Satellite Imagery with Near-Surface Canopy Images in Hawai'i's Tropical Cloud Forests

NASA Astrophysics Data System (ADS)

Bergstrom, R.; Miura, T.; Lepczyk, C.; Giambelluca, T. W.; Nullet, M. A.; Nagai, S.

2012-12-01

Phenological studies are gaining importance globally as the onset of climate change is impacting the timing of green up and senescence in forest canopies and agricultural regions. Many studies use and analyze land surface phenology (LSP) derived from satellite vegetation index time series (VI's) such as those from Moderate Resolution Imaging Spectroradiometer (MODIS) to monitor changes in phenological events. Seasonality is expected in deciduous temperate forests, while tropical regions are predicted to show more static reflectance readings given their stable and steady state. Due to persistent cloud cover and atmospheric interference in tropical regions, satellite VI time series are often subject to uncertainties and thus require near surface vegetation monitoring systems for ground-truthing. This study has been designed to assess the precision of MODIS phenological signatures using above-canopy, down-looking digital cameras installed on flux towers on the Island of Hawai'i. The cameras are part of the expanding Phenological Eyes Network (PEN) which has been implementing a global network of above-canopy, hemispherical digital cameras for forest and agricultural phenological monitoring. Cameras have been installed at two locations in Hawaii - one on a flux tower in close proximity to the Thurston Lave Tube (HVT) in Hawai'i Volcanoes National Park and the other on a weather station in a section of the Hawaiian Tropical Experimental Forest in Laupaphoehoe (LEF). HVT consists primarily of a single canopy species, ohi'a lehua (Metrosideros polymorpha), with an understory of hapu'u ferns (Cibotium spp), while LEF is similarly comprised with an additional dominant species, Koa (Acacia Koa), included in the canopy structure. Given these species' characteristics, HVT is expected to show little seasonality, while LEF has the potential to deviate slightly during periods following dry and wet seasons. MODIS VI time series data are being analyzed and will be compared to images from the cameras which will have VI's extracted from their RGB image planes and will be normalized to be comparable with MODIS VI's. Given Hawai'i's susceptibility to invasion and delicacy of its endemic species, results from this study will provide necessary site specific detail in determining the reliability of satellite based inference in similar tropical phenology studies. Should satellite images provide adequate information, results from this study will allow for extrapolation across similar understudied tropical forests.

Evaluation of the MODIS Aerosol Retrievals over Ocean and Land during CLAMS.

NASA Astrophysics Data System (ADS)

Levy, R. C.; Remer, L. A.; Martins, J. V.; Kaufman, Y. J.; Plana-Fattori, A.; Redemann, J.; Wenny, B.

2005-04-01

The Chesapeake Lighthouse Aircraft Measurements for Satellites (CLAMS) experiment took place from 10 July to 2 August 2001 in a combined ocean-land region that included the Chesapeake Lighthouse [Clouds and the Earth's Radiant Energy System (CERES) Ocean Validation Experiment (COVE)] and the Wallops Flight Facility (WFF), both along coastal Virginia. This experiment was designed mainly for validating instruments and algorithms aboard the Terra satellite platform, including the Moderate Resolution Imaging Spectroradiometer (MODIS). Over the ocean, MODIS retrieved aerosol optical depths (AODs) at seven wavelengths and an estimate of the aerosol size distribution. Over the land, MODIS retrieved AOD at three wavelengths plus qualitative estimates of the aerosol size. Temporally coincident measurements of aerosol properties were made with a variety of sun photometers from ground sites and airborne sites just above the surface. The set of sun photometers provided unprecedented spectral coverage from visible (VIS) to the solar near-infrared (NIR) and infrared (IR) wavelengths. In this study, AOD and aerosol size retrieved from MODIS is compared with similar measurements from the sun photometers. Over the nearby ocean, the MODIS AOD in the VIS and NIR correlated well with sun-photometer measurements, nearly fitting a one-to-one line on a scatterplot. As one moves from ocean to land, there is a pronounced discontinuity of the MODIS AOD, where MODIS compares poorly to the sun-photometer measurements. Especially in the blue wavelength, MODIS AOD is too high in clean aerosol conditions and too low under larger aerosol loadings. Using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative code to perform atmospheric correction, the authors find inconsistency in the surface albedo assumptions used by the MODIS lookup tables. It is demonstrated how the high bias at low aerosol loadings can be corrected. By using updated urban/industrial aerosol climatology for the MODIS lookup table over land, it is shown that the low bias for larger aerosol loadings can also be corrected. Understanding and improving MODIS retrievals over the East Coast may point to strategies for correction in other locations, thus improving the global quality of MODIS. Improvements in regional aerosol detection could also lead to the use of MODIS for monitoring air pollution.

Atmospheric Correction of High-Spatial-Resolution Commercial Satellite Imagery Products Using MODIS Atmospheric Products

NASA Technical Reports Server (NTRS)

Pagnutti, Mary; Holekamp, Kara; Ryan, Robert E.; Vaughan, Ronand; Russell, Jeff; Prados, Don; Stanley, Thomas

2005-01-01

Remotely sensed ground reflectance is the foundation of any interoperability or change detection technique. Satellite intercomparisons and accurate vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), require the generation of accurate reflectance maps (NDVI is used to describe or infer a wide variety of biophysical parameters and is defined in terms of near-infrared (NIR) and red band reflectances). Accurate reflectance-map generation from satellite imagery relies on the removal of solar and satellite geometry and of atmospheric effects and is generally referred to as atmospheric correction. Atmospheric correction of remotely sensed imagery to ground reflectance has been widely applied to a few systems only. The ability to obtain atmospherically corrected imagery and products from various satellites is essential to enable widescale use of remotely sensed, multitemporal imagery for a variety of applications. An atmospheric correction approach derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) that can be applied to high-spatial-resolution satellite imagery under many conditions was evaluated to demonstrate a reliable, effective reflectance map generation method. Additional information is included in the original extended abstract.

Advances in remote sensing of forest background reflectance with MODIS BRDF data across Europe

NASA Astrophysics Data System (ADS)

Pisek, Jan; Alikas, Krista; Lukeš, Petr; Lundin, Lars; Kobler, Johannes; Santos-Reis, Margarida; Chen, Jing

2017-04-01

Spatial and temporal patterns of forest background (understory) reflectance are crucial for retrieving biophysical parameters of forest canopies (overstory) and subsequently for ecosystem modeling. However, systematic reflectance data covering different site types are almost missing. This presentation will focus on the validation of background reflectance retrievals using MODIS bidirectional reflectance distribution function (BRDF) data against in-situ understory reflectance measurements covering a diverse set of long-term ecological research (LTER) sites distributed along a wide latitudinal and elevational gradient across Europe: protected coniferous blueberry forest in Sweden, karst forest system in Austria, floodplain broadleaf forest and coniferous forest in the Czech Republic, and Mediterranean agro-sylvo-pastoral woodlands in Portugal. The multi-angle remote sensing data-based methodology was originally developed for the forest background signal retrieval in a boreal region. Here its performance will be tested across diverse forest conditions and moments during the growing season, which is a necessary step before conducting extensive mapping over forested areas. The results can be also used as an input for improved modeling of local carbon and energy fluxes.

Estimate of the Impact of Absorbing Aerosol Over Cloud on the MODIS Retrievals of Cloud Optical Thickness and Effective Radius Using Two Independent Retrievals of Liquid Water Path

NASA Technical Reports Server (NTRS)

Wilcox, Eric M.; Harshvardhan; Platnick, Steven

2009-01-01

Two independent satellite retrievals of cloud liquid water path (LWP) from the NASA Aqua satellite are used to diagnose the impact of absorbing biomass burning aerosol overlaying boundary-layer marine water clouds on the Moderate Resolution Imaging Spectrometer (MODIS) retrievals of cloud optical thickness (tau) and cloud droplet effective radius (r(sub e)). In the MODIS retrieval over oceans, cloud reflectance in the 0.86-micrometer and 2.13-micrometer bands is used to simultaneously retrieve tau and r(sub e). A low bias in the MODIS tau retrieval may result from reductions in the 0.86-micrometer reflectance, which is only very weakly absorbed by clouds, owing to absorption by aerosols in cases where biomass burning aerosols occur above water clouds. MODIS LWP, derived from the product of the retrieved tau and r(sub e), is compared with LWP ocean retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E), determined from cloud microwave emission that is transparent to aerosols. For the coastal Atlantic southern African region investigated in this study, a systematic difference between AMSR-E and MODIS LWP retrievals is found for stratocumulus clouds over three biomass burning months in 2005 and 2006 that is consistent with above-cloud absorbing aerosols. Biomass burning aerosol is detected using the ultraviolet aerosol index from the Ozone Monitoring Instrument (OMI) on the Aura satellite. The LWP difference (AMSR-E minus MODIS) increases both with increasing tau and increasing OMI aerosol index. During the biomass burning season the mean LWP difference is 14 g per square meters, which is within the 15-20 g per square meter range of estimated uncertainties in instantaneous LWP retrievals. For samples with only low amounts of overlaying smoke (OMI AI less than or equal to 1) the difference is 9.4, suggesting that the impact of smoke aerosols on the mean MODIS LWP is 5.6 g per square meter. Only for scenes with OMI aerosol index greater than 2 does the average LWP difference and the estimated bias in MODIS cloud optical thickness attributable to the impact of overlaying biomass burning aerosol exceed the instantaneous uncertainty in the retrievals.

Direct Radiative Effect of Aerosols Based on PARASOL and OMI Satellite Observations

NASA Technical Reports Server (NTRS)

Lacagnina, Carlo; Hasekamp, Otto P.; Torres, Omar

2017-01-01

Accurate portrayal of the aerosol characteristics is crucial to determine aerosol contribution to the Earth's radiation budget. We employ novel satellite retrievals to make a new measurement-based estimate of the shortwave direct radiative effect of aerosols (DREA), both over land and ocean. Global satellite measurements of aerosol optical depth, single-scattering albedo (SSA), and phase function from PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) are used in synergy with OMI (Ozone Monitoring Instrument) SSA. Aerosol information is combined with land-surface bidirectional reflectance distribution function and cloud characteristics from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite products. Eventual gaps in observations are filled with the state-of-the-art global aerosol model ECHAM5-HAM2. It is found that our estimate of DREA is largely insensitive to model choice. Radiative transfer calculations show that DREA at top-of-atmosphere is -4.6 +/- 1.5 W/sq m for cloud-free and -2.1 +/- 0.7 W/sq m for all-sky conditions, during year 2006. These fluxes are consistent with, albeit generally less negative over ocean than, former assessments. Unlike previous studies, our estimate is constrained by retrievals of global coverage SSA, which may justify different DREA values. Remarkable consistency is found in comparison with DREA based on CERES (Clouds and the Earth's Radiant Energy System) and MODIS observations.

Assessment of satellite derived diffuse attenuation coefficients ...

EPA Pesticide Factsheets

Optical data collected in coastal waters off South Florida and in the Caribbean Sea between January 2009 and December 2010 were used to evaluate products derived with three bio-optical inversion algorithms applied to MOIDS/Aqua, MODIS/Terra, and SeaWiFS satellite observations. The products included the diffuse attenuation coefficient at 490 nm (Kd_490) and for the visible range (Kd_PAR), and euphotic depth (Zeu, corresponding to 1% of the surface incident photosynthetically available radiation or PAR). Above-water hyperspectral reflectance data collected over optically shallow waters of the Florida Keys between June 1997 and August 2011 were used to help understand algorithm performance over optically shallow waters. The in situ data covered a variety of water types in South Florida and the Caribbean Sea, ranging from deep clear waters, turbid coastal waters, and optically shallow waters (Kd_490 range of ~0.03 – 1.29m-1). An algorithm based on Inherent Optical Properties (IOPs) showed the best performance (RMSD < 13% and R2 ~1.0 for MODIS/Aqua and SeaWiFS). Two algorithms based on empirical regressions performed well for offshore clear waters, but underestimated Kd_490 and Kd_PAR in coastal waters due to high turbidity or shallow bottom contamination. Similar results were obtained when only in situ data were used to evaluate algorithm performance. The excellent agreement between satellite-derived remote sensing reflectance (Rrs) and in situ Rrs suggested that

3D Cloud Radiative Effects on Aerosol Optical Thickness Retrievals in Cumulus Cloud Fields in the Biomass Burning Region in Brazil

NASA Technical Reports Server (NTRS)

Wen, Guo-Yong; Marshak, Alexander; Cahalan, Robert F.

2004-01-01

Aerosol amount in clear regions of a cloudy atmosphere is a critical parameter in studying the interaction between aerosols and clouds. Since the global cloud cover is about 50%, cloudy scenes are often encountered in any satellite images. Aerosols are more or less transparent, while clouds are extremely reflective in the visible spectrum of solar radiation. The radiative transfer in clear-cloudy condition is highly three- dimensional (3D). This paper focuses on estimating the 3D effects on aerosol optical thickness retrievals using Monte Carlo simulations. An ASTER image of cumulus cloud fields in the biomass burning region in Brazil is simulated in this study. The MODIS products (i-e., cloud optical thickness, particle effective radius, cloud top pressure, surface reflectance, etc.) are used to construct the cloud property and surface reflectance fields. To estimate the cloud 3-D effects, we assume a plane-parallel stratification of aerosol properties in the 60 km x 60 km ASTER image. The simulated solar radiation at the top of the atmosphere is compared with plane-parallel calculations. Furthermore, the 3D cloud radiative effects on aerosol optical thickness retrieval are estimated.

An improved algorithm for small and cool fire detection using MODIS data: A preliminary study in the southeastern United States

Treesearch

Wanting Wang; John J. Qu; Xianjun Hao; Yongqiang Liu; William T. Sommers

2006-01-01

Traditional fire detection algorithms mainly rely on hot spot detection using thermal infrared (TIR) channels with fixed or contextual thresholds. Three solar reflectance channels (0.65 μm, 0.86 μm, and 2.1 μm) were recently adopted into the MODIS version 4 contextual algorithm to improve the active fire detection. In the southeastern United...

[Retrieval of the Optical Thickness and Cloud Top Height of Cirrus Clouds Based on AIRS IR High Spectral Resolution Data].

PubMed

Cao, Ya-nan; Wei, He-li; Dai, Cong-ming; Zhang, Xue-hai

2015-05-01

A study was carried out to retrieve optical thickness and cloud top height of cirrus clouds from the Atmospheric Infrared Sounder (AIRS) high spectral resolution data in 1070~1135 cm-1 IR band using a Combined Atmospheric Radiative Transfer model (CART) by brightness temperature difference between model simulation and AIRS observation. The research is based on AIRS LIB high spectral infrared observation data combined with Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product data. Brightness temperature spectra based, on the retrieved cirrus optical thickness and cloud top height were simulated and compared with brightness temperature spectra of AIRS observation in the 650~1150 cm-1 band. The cirrus optical thickness and cloud top height retrieved were compared with brightness temperature of AIRS for channel 760 (900.56 cm-1, 11. 1 µm) and cirrus reflectance of MODIS cloud product. And cloud top height retrieved was compared with cloud top height from MODIS. Results show that the brightness temperature spectra simulated were basically consistent with AIRS observation under the condition of retrieval in the 650~1150 cm-1 band. It means that CART can be used to simulate AIRS brightness temperature spectra. The retrieved cirrus parameters are consistent with brightness temperature of AIRS for channel 11. 1 µm with low brightness temperature corresponding to large cirrus optical thickness and high cloud top height. And the retrieved cirrus parameters are consistent with cirrus reflectance of MODIS cloud product with high cirrus reflectance corresponding to large cirrus optical thickness and high cloud top height. Correlation coefficient of brightness temperature between retrieved cloud top height and MODIS cloud top height was relatively high. They are mostly located in the range of 8. 5~11.5 km, and their probability distribution trend is approximately identical. CART model is feasible to retrieve cirrus properties, and the retrieval is reliable.

Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans.

PubMed

Cho, Hyoun-Myoung; Zhang, Zhibo; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S; Di Girolamo, Larry; C-Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E

2015-05-16

Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius ( r e ) and optical thickness ( τ ) by projecting observed cloud reflectances onto a precomputed look-up table (LUT). When observations fall outside of the LUT, the retrieval is considered "failed" because no combination of τ and r e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the " r e too large" failure accounting for 60%-85% of all failed retrievals. The rest is mostly due to the " r e too small" or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun-satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study.

Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans

PubMed Central

Cho, Hyoun‐Myoung; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S.; Di Girolamo, Larry; C.‐Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E.

2015-01-01

Abstract Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius (r e) and optical thickness (τ) by projecting observed cloud reflectances onto a precomputed look‐up table (LUT). When observations fall outside of the LUT, the retrieval is considered “failed” because no combination of τ and r e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the “r e too large” failure accounting for 60%–85% of all failed retrievals. The rest is mostly due to the “r e too small” or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun‐satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study. PMID:27656330

Comparison of ASTER Global Emissivity Database (ASTER-GED) With In-Situ Measurement In Italian Vulcanic Areas

NASA Astrophysics Data System (ADS)

Silvestri, M.; Musacchio, M.; Buongiorno, M. F.; Amici, S.; Piscini, A.

2015-12-01

LP DAAC released the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Database (GED) datasets on April 2, 2014. The database was developed by the National Aeronautics and Space Administration's (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology. The database includes land surface emissivities derived from ASTER data acquired over the contiguous United States, Africa, Arabian Peninsula, Australia, Europe, and China. In this work we compare ground measurements of emissivity acquired by means of Micro-FTIR (Fourier Thermal Infrared spectrometer) instrument with the ASTER emissivity map extract from ASTER-GED and the emissivity obtained by using single ASTER data. Through this analysis we want to investigate differences existing between the ASTER-GED dataset (average from 2000 to 2008 seasoning independent) and fall in-situ emissivity measurement. Moreover the role of different spatial resolution characterizing ASTER and MODIS, 90mt and 1km respectively, by comparing them with in situ measurements. Possible differences can be due also to the different algorithms used for the emissivity estimation, Temperature and Emissivity Separation algorithm for ASTER TIR band( Gillespie et al, 1998) and the classification-based emissivity method (Snyder and al, 1998) for MODIS. In-situ emissivity measurements have been collected during dedicated fields campaign on Mt. Etna vulcano and Solfatara of Pozzuoli. Gillespie, A. R., Matsunaga, T., Rokugawa, S., & Hook, S. J. (1998). Temperature and emissivity separation from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. IEEE Transactions on Geoscience and Remote Sensing, 36, 1113-1125. Snyder, W.C., Wan, Z., Zhang, Y., & Feng, Y.-Z. (1998). Classification-based emissivity for land surface temperature measurement from space. International Journal of Remote Sensing, 19, 2753-2574.

Purus River suspended sediment variability and contributions to the Amazon River from satellite data (2000-2015)

NASA Astrophysics Data System (ADS)

Santos, Andre Luis Martinelli Real dos; Martinez, Jean Michel; Filizola, Naziano Pantoja; Armijos, Elisa; Alves, Luna Gripp Simões

2018-01-01

The Purus River is one of the major tributaries of Solimões River in Brazil, draining an area of 370,091 km2 and stretching over 2765 km. Unlike those of the other main tributaries of the Amazon River, the Purus River's sediment discharge is poorly characterized. In this study, as an alternative to the logistic difficulties and considering high monitoring costs, we report an experiment where field measurement data and 2700 satellite (MODIS) images are combined to retrieve both seasonal and interannual dynamics in terms of the Purus river sediment discharge near its confluence with the Solimões River. Field radiometric and hydrologic measurements were acquired during 18 sampling trips, including 115 surface water samples and 61 river discharge measurements. Remote sensing reflectance gave important results in the red and infrared levels. They were very well correlated with suspended sediment concentration. The values of R2 are greater than 0.8 (red band) and 0.9 (NIR band). A retrieval algorithm based on the reflectance in both the red and the infrared was calibrated using the water samples collected for the determination of the surface-suspended sediment concentration (SSS). The algorithm was used to calculate 16 years of SSS time series with MODIS images at the Purus River near its confluence with the Solimões River. Results from satellite data correlated with in situ SSS values validate the use of satellite data to be used as a tool to monitor SSS in the Purus River. We evidenced a very short and intense sediment discharge pulse with 55% of the annual sediment budget discharged during the months of January and February. Using river discharge records, we calculated the mean annual sediment discharge of the Purus River at about of 17 Mt·yr-1.

Monitoring Start of Season in Alaska

NASA Astrophysics Data System (ADS)

Robin, J.; Dubayah, R.; Sparrow, E.; Levine, E.

2006-12-01

In biomes that have distinct winter seasons, start of spring phenological events, specifically timing of budburst and green-up of leaves, coincides with transpiration. Seasons leave annual signatures that reflect the dynamic nature of the hydrologic cycle and link the different spheres of the Earth system. This paper evaluates whether continuity between AVHRR and MODIS normalized difference vegetation index (NDVI) is achievable for monitoring land surface phenology, specifically start of season (SOS), in Alaska. Additionally, two thresholds, one based on NDVI and the other on accumulated growing degree-days (GDD), are compared to determine which most accurately predicts SOS for Fairbanks. Ratio of maximum greenness at SOS was computed from biweekly AVHRR and MODIS composites for 2001 through 2004 for Anchorage and Fairbanks regions. SOS dates were determined from annual green-up observations made by GLOBE students. Results showed that different processing as well as spectral characteristics of each sensor restrict continuity between the two datasets. MODIS values were consistently higher and had less inter-annual variability during the height of the growing season than corresponding AVHRR values. Furthermore, a threshold of 131-175 accumulated GDD was a better predictor of SOS for Fairbanks than a NDVI threshold applied to AVHRR and MODIS datasets. The NDVI threshold was developed from biweekly AVHRR composites from 1982 through 2004 and corresponding annual green-up observations at University of Alaska-Fairbanks (UAF). The GDD threshold was developed from 20+ years of historic daily mean air temperature data and the same green-up observations. SOS dates computed with the GDD threshold most closely resembled actual green-up dates observed by GLOBE students and UAF researchers. Overall, biweekly composites and effects of clouds, snow, and conifers limit the ability of NDVI to monitor phenological changes in Alaska.

Theoretical Basis for the Surface Spectral Reflectance Relationships Used in the MODIS Aerosol Algorithm

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Gobron, Nadine; Pinty, Bernard; Widlowski, Jean-Luc; Verstraete, Michel M.; Lau, William K. M. (Technical Monitor)

2001-01-01

The analysis of data from the MODIS instrument on the Terra platform to derive global distribution of aerosols assumes a set of relationships between the blue, rho (sub blue), the red, rho (sub red), and 2.1 micrometers, rho (sub 2.1), spectral channels. These relations have been established from a series of measurements indicating that rho (sub blue) approximately 0.5 rho (sub red) approximately 0.25 rho (sub 2.1). Here we use a model to describe the transfer of radiation through a vegetation canopy composed of randomly oriented leaves to assess the theoretical foundations for these relationships. The influence of varying fractional vegetation coverage is simulated simply as a linear combination of pure soil and pure vegetation conditions, also known as Independent Pixel Approximation (IPA). Calculations for a wide range of leaf area indices and vegetation fractions show that rho (sub blue) is consistently about 1/4 of rho (sub 2.1) as used by MODIS for the whole range of analyzed cases, except for very dark soils, such as those found in burn scars. For its part, the ratio rho (sub red)/rho (sub 2.1) varies from less than the empirically derived value of 1/2 for dense and dark vegetation (rho (sub 2.1) less than 0.1), to more than 1/2 for bright mixture of soil and vegetation. This is in agreement with measurements over uniform dense vegetation, but not with measurements over mixed dark scenes. In the later case, the discrepancy is probably mitigated by shadows due to uneven canopy and terrain on a large scale. It is concluded that the value of this ratio should ideally be made dependent on the land cover type in the operational processing of MODIS data, especially over dense forests.

An Algorithm for the Retrieval of Droplet Number Concentration and Geometrical Thickness of Stratiform Marine Boundary Layer Clouds Applied to MODIS Radiometric Observations.

NASA Astrophysics Data System (ADS)

Schüller, Lothar; Bennartz, Ralf; Fischer, Jürgen; Brenguier, Jean-Louis

2005-01-01

Algorithms are now currently used for the retrieval of cloud optical thickness and droplet effective radius from multispectral radiance measurements. This paper extends their application to the retrieval of cloud droplet number concentration, cloud geometrical thickness, and liquid water path in shallow convective clouds, using an algorithm that was previously tested with airborne measurements of cloud radiances and validated against in situ measurements of the same clouds. The retrieval is based on a stratified cloud model of liquid water content and droplet spectrum. Radiance measurements in visible and near-infrared channels of the Moderate Resolution Imaging Spectroradiometer (MODIS), which is operated from the NASA platforms Terra and Aqua, are analyzed. Because of uncertainties in the simulation of the continental surface reflectance, the algorithm is presently limited to the monitoring of the microphysical structure of boundary layer clouds over the ocean. Two MODIS scenes of extended cloud fields over the North Atlantic Ocean trade wind region are processed. A transport and dispersion model (the Hybrid Single-Particle Lagrangian Integrated Trajectory Model, HYSPLIT4) is also used to characterize the origin of the air masses and hence their aerosol regimes. One cloud field formed in an air mass that was advected from southern Europe and North Africa. It shows high values of the droplet concentration when compared with the second cloud system, which developed in a more pristine environment. The more pristine case also exhibits a higher geometrical thickness and, thus, liquid water path, which counterbalances the expected cloud albedo increase of the polluted case. Estimates of cloud liquid water path are then compared with retrievals from the Special Sensor Microwave Imager (SSM/I). SSM/I-derived liquid water paths are in good agreement with the MODIS-derived values.

Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

NASA Astrophysics Data System (ADS)

Levy, R. C.; Munchak, L. A.; Mattoo, S.; Patadia, F.; Remer, L. A.; Holz, R. E.

2015-10-01

To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångström Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March-April-May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ~ 0.025), while reducing the differences between AE. We characterize algorithm retrievability through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.

Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

NASA Astrophysics Data System (ADS)

Levy, R. C.; Munchak, L. A.; Mattoo, S.; Patadia, F.; Remer, L. A.; Holz, R. E.

2015-07-01

To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångstrom Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March-April-May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ∼ 0.025), while reducing the differences between AE. We characterize algorithm retrievibility through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.

Environmental changes and microbiological health risks. Satellite-derived turbidity: an indicator of "health hazard" for surface water in West Africa (Bagre lake, Burkina Faso).

NASA Astrophysics Data System (ADS)

Robert, E.; Grippa, M.; Kergoat, L.; Martinez, J.; Pinet, S.; Gal, L.; Soumaguel, N.

2015-12-01

A significant correlation exists between the concentration of parasites, bacteria and some water quality parameters including surface suspended solids (SSS) and turbidity. Suspended particles can carry viruses and pathogenic bacteria affecting human health and foster their development. High SSS, associated with high turbidity, can therefore be considered as a vector of microbiological contaminants, causing diarrheal diseases. Few studies have focused on the turbidity parameter in rural Africa, while many cases of intestinal parasitic infections are due to the consumption of unsafe water from ponds, lakes, and rivers. Monitoring turbidity may therefore contribute to health hazard monitoring. Turbidity refers to the optical properties of water and is known to impact water reflectance in the visible and near-infrared domain. Ideally, its spatial and temporal variability requires the use of high temporal resolution (MODIS) and spatial resolution (Landsat, SPOT, Sentinel-2). Here we investigate turbidity in West-Africa. Various algorithms and indices proposed in the literature for inland waters are applied to MODIS series and to Landsat 7 and 8 CDR images, and SPOT5 images. The data and algorithms are evaluated with field measurements: turbidity, SSS, and hyperspectral ground radiometry. We show that turbidity of the Bagre Lake displays a strong increase over 2000-2015, associated with the corresponding increase of the red and NIR reflectances, as well as a reduction of the seasonal variations. Water level derived from the Jason 2 altimeter does not explain such variations. The most probable hypothesis is a change in land use (increase in bare and degraded soils), that leads to an increase in the particles transported by surface runoff to the lake. Such an increase in turbidity reinforces the health risk. We will discuss the link between turbidity and health in view of data from health centers on diarrheal diseases as well as data on practices and uses of populations.

Evolution of aerosol loading in Santiago de Chile between 1997 and 2014

NASA Astrophysics Data System (ADS)

Pistone, Kristina; Gallardo, Laura

2015-04-01

While aerosols produced by major cities are a significant component of anthropogenic climate forcing as well as an important factor in public health, many South American cities have not been a major focus of aerosol studies due in part to relatively few long-term observations in the region. Here we present a synthesis of the available data for the emerging megacity of Santiago, Chile. We report new results from a recent NASA AERONET (AErosol RObotic NETwork) site in the Santiago basin, combining these with previous AERONET observations in Santiago as well as with a new assessment of the 11-station air quality monitoring network currently administered by the Chilean Environment Ministry (MMA, Ministerio del Medio Ambiente) to assess changes in aerosol composition since 1997. While the average surface concentration of pollution components (specifically PM2.5 and PM10) has decreased, no significant change in total aerosol optical depth was observed. However, changes in aerosol size and composition are suggested by the proxy measurements. Previous studies have revealed limitations in purely satellite-based studies over Santiago due to biases from high surface reflection in the region, particularly in summer months (e.g. Escribano et al 2014). To overcome this difficulty and certain limitations in the air quality data, we next incorporate analysis of aerosol products from the Multi-angle Imaging SpectroRadiometer (MISR) instrument along with those from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, both on NASA's Terra satellite, to better quantify the high bias of MODIS. Thus incorporating these complementary datasets, we characterize the aerosol over Santiago over the period 1997 to 2014, including the evolution of aerosol properties over time and seasonal dependencies in the observed trends. References: Escribano et al (2014), "Satellite Retrievals of Aerosol Optical Depth over a Subtropical Urban Area: The Role of Stratification and Surface Reflectance," Aerosol and Air Quality Research, doi:10.4209/aaqr.2013.03.0082.

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-MODIS_Edition2A)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition2A)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-09-16] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition1B)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Ed2A-NoSW)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-01-01] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-MODIS_Edition2B)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-01-01] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM1-MODIS_Edition2A)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

MODIS Snow and Ice Production

NASA Technical Reports Server (NTRS)

Hall, Dorthoy K.; Hoser, Paul (Technical Monitor)

2002-01-01

Daily, global snow cover maps, and sea ice cover and sea ice surface temperature (IST) maps are derived from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS), are available at no cost through the National Snow and Ice Data Center (NSIDC). Included on this CD-ROM are samples of the MODIS snow and ice products. In addition, an animation, done by the Scientific Visualization studio at Goddard Space Flight Center, is also included.

Satellite Remote Sensing Detection of Coastal Pollution in Southern California: Stormwater Runoff and Wastewater Plumes

NASA Astrophysics Data System (ADS)

Trinh, R. C.; Holt, B.; Gierach, M.

2016-02-01

Coastal pollution poses a major health and environmental hazard, not only for beach goers and coastal communities but for marine organisms as well. Stormwater runoff is the largest source of environmental pollution in coastal waters of the Southern California Bight (SCB) and is of great concern in increasingly urbanized areas. Buoyant wastewater plumes also pose a marine environmental risk. In this study we provide a comprehensive overview of satellite remote sensing capabilities in detecting buoyant coastal pollutants in the form of stormwater runoff and wastewater effluent. The SCB is the final destination of four major urban rivers that act as channels for runoff and pollution during and after rainstorms. We analyzed and compared sea surface roughness data from various Synthetic Aperture Radar (SAR) instruments to ocean color data from the Moderate Imaging System (MODIS) sensor on board the Aqua satellite and correlated the results with existing environmental data in order to create a climatology of naturally occurring stormwater plumes in coastal waters after rain events, from 1992 to 2014 from four major rivers in the area. Heat maps of the primary extent of stormwater plumes were constructed to specify areas that may be subject to the greatest risk of coastal contamination. In conjunction with our efforts to monitor coastal pollution and validate the abilities of satellite remote sensing, a recent Fall 2015 wastewater diversion from the City of Los Angeles Hyperion Treatment Plant (HTP) provided the opportunity to apply these remote sensing methodologies of plume detection to wastewater. During maintenance of their 5-mile long outfall pipe, wastewater is diverted to a shorter outfall pipe that terminates 1-mile offshore and in shallower waters. Sea surface temperature (SST), chlorophyll-a (chl-a) fluorescence, remote sensing reflectance and particulate backscatter signatures were analyzed from MODIS. Terra-ASTER and Landsat-8 thermal infrared data were also obtained to determine SST anomalies associated with surfaced wastewater at a higher resolution than MODIS. SAR data from ALOS-2, and Sentinel-1 were used to identify surfaced wastewater plumes. In situ drifter, chl-a, SST, and hyperspectral water quality measurements from the diversion were also compared with those obtained by satellite sensors.

A fast radiative transfer model for visible through shortwave infrared spectral reflectances in clear and cloudy atmospheres

NASA Astrophysics Data System (ADS)

Wang, Chenxi; Yang, Ping; Nasiri, Shaima L.; Platnick, Steven; Baum, Bryan A.; Heidinger, Andrew K.; Liu, Xu

2013-02-01

A computationally efficient radiative transfer model (RTM) for calculating visible (VIS) through shortwave infrared (SWIR) reflectances is developed for use in satellite and airborne cloud property retrievals. The full radiative transfer equation (RTE) for combinations of cloud, aerosol, and molecular layers is solved approximately by using six independent RTEs that assume the plane-parallel approximation along with a single-scattering approximation for Rayleigh scattering. Each of the six RTEs can be solved analytically if the bidirectional reflectance/transmittance distribution functions (BRDF/BTDF) of the cloud/aerosol layers are known. The adding/doubling (AD) algorithm is employed to account for overlapped cloud/aerosol layers and non-Lambertian surfaces. Two approaches are used to mitigate the significant computational burden of the AD algorithm. First, the BRDF and BTDF of single cloud/aerosol layers are pre-computed using the discrete ordinates radiative transfer program (DISORT) implemented with 128 streams, and second, the required integral in the AD algorithm is numerically implemented on a twisted icosahedral mesh. A concise surface BRDF simulator associated with the MODIS land surface product (MCD43) is merged into a fast RTM to accurately account for non-isotropic surface reflectance. The resulting fast RTM is evaluated with respect to its computational accuracy and efficiency. The simulation bias between DISORT and the fast RTM is large (e.g., relative error >5%) only when both the solar zenith angle (SZA) and the viewing zenith angle (VZA) are large (i.e., SZA>45° and VZA>70°). For general situations, i.e., cloud/aerosol layers above a non-Lambertian surface, the fast RTM calculation rate is faster than that of the 128-stream DISORT by approximately two orders of magnitude.

Clouds and the Earth's Radiant Energy System (CERES) Data Products for Climate Research

NASA Technical Reports Server (NTRS)

Kato, Seiji; Loeb, Norman G.; Rutan, David A.; Rose, Fred G.

2015-01-01

NASA's Clouds and the Earth's Radiant Energy System (CERES) project integrates CERES, Moderate Resolution Imaging Spectroradiometer (MODIS), and geostationary satellite observations to provide top-of-atmosphere (TOA) irradiances derived from broadband radiance observations by CERES instruments. It also uses snow cover and sea ice extent retrieved from microwave instruments as well as thermodynamic variables from reanalysis. In addition, these variables are used for surface and atmospheric irradiance computations. The CERES project provides TOA, surface, and atmospheric irradiances in various spatial and temporal resolutions. These data sets are for climate research and evaluation of climate models. Long-term observations are required to understand how the Earth system responds to radiative forcing. A simple model is used to estimate the time to detect trends in TOA reflected shortwave and emitted longwave irradiances.

Nature's Notebook Provides Phenology Observations for NASA Juniper Phenology and Pollen Transport Project

NASA Technical Reports Server (NTRS)

Luval, J. C.; Crimmins, T. M.; Sprigg, W. A.; Levetin, E.; Huete, A.; Nickovic, S.; Prasad, A.; Vukovic, A.; VandeWater, P. K.; Budge, A. M.;

Cross-Calibration of Earth Observing System Terra Satellite Sensors MODIS and ASTER

NASA Technical Reports Server (NTRS)

McCorkel, J.

2014-01-01

The Advanced Spaceborne Thermal Emissive and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectrometer (MODIS) are two of the five sensors onboard the Earth Observing System's Terra satellite. These sensors share many similar spectral channels while having much different spatial and operational parameters. ASTER is a tasked sensor and sometimes referred to a zoom camera of the MODIS that collects a full-earth image every one to two days. It is important that these sensors have a consistent characterization and calibration for continued development and use of their data products. This work uses a variety of test sites to retrieve and validate intercalibration results. The refined calibration of Collection 6 of the Terra MODIS data set is leveraged to provide the up-to-date reference for trending and validation of ASTER. Special attention is given to spatially matching radiance measurements using prelaunch spatial response characterization of MODIS. Despite differences in spectral band properties and spatial scales, ASTER-MODIS is an ideal case for intercomparison since the sensors have nearly identical views and acquisitions times and therefore can be used as a baseline of intercalibration performance of other satellite sensor pairs.

Global Performance of a Fast Parameterization Scheme for Estimating Surface Solar Radiation from MODIS data

NASA Astrophysics Data System (ADS)

Tang, W.; Yang, K.; Sun, Z.; Qin, J.; Niu, X.

2016-12-01

A fast parameterization scheme named SUNFLUX is used in this study to estimate instantaneous surface solar radiation (SSR) based on products from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard both Terra and Aqua platforms. The scheme mainly takes into account the absorption and scattering processes due to clouds, aerosols and gas in the atmosphere. The estimated instantaneous SSR is evaluated against surface observations obtained from seven stations of the Surface Radiation Budget Network (SURFRAD), four stations in the North China Plain (NCP) and 40 stations of the Baseline Surface Radiation Network (BSRN). The statistical results for evaluation against these three datasets show that the relative root-mean-square error (RMSE) values of SUNFLUX are less than 15%, 16% and 17%, respectively. Daily SSR is derived through temporal upscaling from the MODIS-based instantaneous SSR estimates, and is validated against surface observations. The relative RMSE values for daily SSR estimates are about 16% at the seven SURFRAD stations, four NCP stations, 40 BSRN stations and 90 China Meteorological Administration (CMA) radiation stations.