On-Orbit Lunar Modulation Transfer Function Measurements for the Moderate Resolution Imaging Spectroradiometer

NASA Technical Reports Server (NTRS)

Choi, Taeyong; Xiong, Xiaoxiong; Wang, Zhipeng

2013-01-01

Spatial quality of an imaging sensor can be estimated by evaluating its modulation transfer function (MTF) from many different sources such as a sharp edge, a pulse target, or bar patterns with different spatial frequencies. These well-defined targets are frequently used for prelaunch laboratory tests, providing very reliable and accurate MTF measurements. A laboratory-quality edge input source was included in the spatial-mode operation of the Spectroradiometric Calibration Assembly (SRCA), which is one of the onboard calibrators of the Moderate Resolution Imaging Spectroradiometer (MODIS). Since not all imaging satellites have such an instrument, SRCA MTF estimations can be used as a reference for an on-orbit lunar MTF algorithm and results. In this paper, the prelaunch spatial quality characterization process from the Integrated Alignment Collimator and SRCA is briefly discussed. Based on prelaunch MTF calibration using the SRCA, a lunar MTF algorithm is developed and applied to the lifetime on-orbit Terra and Aqua MODIS lunar collections. In each lunar collection, multiple scan-directionMoon-to-background transition profiles are aligned by the subpixel edge locations from a parametric Fermi function fit. Corresponding accumulated edge profiles are filtered and interpolated to obtain the edge spread function (ESF). The MTF is calculated by applying a Fourier transformation on the line spread function through a simple differentiation of the ESF. The lifetime lunar MTF results are analyzed and filtered by a relationship with the Sun-Earth-MODIS angle. Finally, the filtered lunarMTF values are compared to the SRCA MTF results. This comparison provides the level of accuracy for on-orbit MTF estimations validated through prelaunch SRCA measurements. The lunar MTF values had larger uncertainty than the SRCA MTF results; however, the ratio mean of lunarMTF fit and SRCA MTF values is within 2% in the 250- and 500-m bands. Based on the MTF measurement uncertainty range, the suggested lunar MTF algorithm can be applied to any on-orbit imaging sensor with lunar calibration capability.

MODIS. Volume 1: MODIS level 1A software baseline requirements

NASA Technical Reports Server (NTRS)

Masuoka, Edward; Fleig, Albert; Ardanuy, Philip; Goff, Thomas; Carpenter, Lloyd; Solomon, Carl; Storey, James

1994-01-01

This document describes the level 1A software requirements for the moderate resolution imaging spectroradiometer (MODIS) instrument. This includes internal and external requirements. Internal requirements include functional, operational, and data processing as well as performance, quality, safety, and security engineering requirements. External requirements include those imposed by data archive and distribution systems (DADS); scheduling, control, monitoring, and accounting (SCMA); product management (PM) system; MODIS log; and product generation system (PGS). Implementation constraints and requirements for adapting the software to the physical environment are also included.

Reanalysis of global terrestrial vegetation trends from MODIS products: Browning or greening?

Treesearch

Yulong Zhang; Conghe Song; Lawrence E. Band; Ge Sun; Junxiang Li

2017-01-01

Accurately monitoring global vegetation dynamics with modern remote sensing is critical for understanding the functions and processes of the biosphere and its interactions with the planetary climate. The MODerate resolution Imaging Spectroradiometer (MODIS) vegetation index (VI) product has been a primary data source for this purpose. To date, theMODIS teamhad released...

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.

An Imager Gaussian Process Machine Learning Methodology for Cloud Thermodynamic Phase classification

NASA Astrophysics Data System (ADS)

Marchant, B.; Platnick, S. E.; Meyer, K.

2017-12-01

The determination of cloud thermodynamic phase from MODIS and VIIRS instruments is an important first step in cloud optical retrievals, since ice and liquid clouds have different optical properties. To continue improving the cloud thermodynamic phase classification algorithm, a machine-learning approach, based on Gaussian processes, has been developed. The new proposed methodology provides cloud phase uncertainty quantification and improves the algorithm portability between MODIS and VIIRS. We will present new results, through comparisons between MODIS and CALIOP v4, and for VIIRS as well.

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.

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.

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.

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.

Spatially Varying Spectrally Thresholds for MODIS Cloud Detection

NASA Technical Reports Server (NTRS)

Haines, S. L.; Jedlovec, G. J.; Lafontaine, F.

2004-01-01

The EOS science team has developed an elaborate global MODIS cloud detection procedure, and the resulting MODIS product (MOD35) is used in the retrieval process of several geophysical parameters to mask out clouds. While the global application of the cloud detection approach appears quite robust, the product has some shortcomings on the regional scale, often over determining clouds in a variety of settings, particularly at night. This over-determination of clouds can cause a reduction in the spatial coverage of MODIS derived clear-sky products. To minimize this problem, a new regional cloud detection method for use with MODIS data has been developed at NASA's Global Hydrology and Climate Center (GHCC). The approach is similar to that used by the GHCC for GOES data over the continental United States. Several spatially varying thresholds are applied to MODIS spectral data to produce a set of tests for detecting clouds. The thresholds are valid for each MODIS orbital pass, and are derived from 20-day composites of GOES channels with similar wavelengths to MODIS. This paper and accompanying poster will introduce the GHCC MODIS cloud mask, provide some examples, and present some preliminary validation.

The moderate resolution imaging spectrometer (MODIS) science and data system requirements

NASA Technical Reports Server (NTRS)

Ardanuy, Philip E.; Han, Daesoo; Salomonson, Vincent V.

1991-01-01

The Moderate Resolution Imaging Spectrometer (MODIS) has been designated as a facility instrument on the first NASA polar orbiting platform as part of the Earth Observing System (EOS) and is scheduled for launch in the late 1990s. The near-global daily coverage of MODIS, combined with its continuous operation, broad spectral coverage, and relatively high spatial resolution, makes it central to the objectives of EOS. The development, implementation, production, and validation of the core MODIS data products define a set of functional, performance, and operational requirements on the data system that operate between the sensor measurements and the data products supplied to the user community. The science requirements guiding the processing of MODIS data are reviewed, and the aspects of an operations concept for the production of data products from MODIS for use by the scientific community are discussed.

Characterizing a decade of behavior at Volcán de Colima, Mexico using long term InSAR and thermal remote sensing data

NASA Astrophysics Data System (ADS)

Sorge, J.; Williams-Jones, G.; Wright, R.; Varley, N. R.

2010-12-01

Satellite imagery is playing an increasingly prominent role in volcanology as it allows for consistent monitoring of remote, dangerous, and/or under-monitored volcanoes. One such system is Volcán de Colima (Mexico), a persistently active andesitic stratovolcano. Its characteristic and hazardous activity includes lava dome growth, pyroclastic flows, explosions, and Plinian to Subplinian eruptions, which have historically occurred at the end of Volcán de Colima’s eruptive cycle. Despite the availability of large amounts of historical satellite imagery, methods to process and interpret these images over long time periods are limited. Furthermore, while time-series InSAR data from a previous study (December 2002 to August 2006) detected an overall subsidence between 1 and 3 km from the summit, there is insufficient temporal resolution to unambiguously constrain the source processes. To address this issue, a semi-automated process for time-based characterization of persistent volcanic activity at Volcán de Colima has been developed using a combination of MODIS and GOES satellite imagery to identify thermal anomalies on the volcano edifice. This satellite time-series data is then combined with available geodetic data, a detailed eruption history, and other geophysical time-series data (e.g., seismicity, explosions/day, effusion rate, environmental data, etc.) and examined for possible correlations and recurring patterns in the multiple data sets to investigate potential trigger mechanisms responsible for the changes in volcanic activity. GOES and MODIS images are available from 2000 to present at a temporal resolution of one image every 30 minutes and up to four images per day, respectively, creating a data set of approximately 180,000 images. Thermal anomalies over Volcán de Colima are identified in both night- and day-time images by applying a time-series approach to the analysis of MODIS data. Detection of false anomalies, caused by non-volcanic heat sources such as fires or solar heating (in the daytime images), is mitigated by adjusting the MODIS detection thresholds, through comparison of daytime versus nighttime results, and by observing the spatial distribution of the anomalies on the edifice. Conversely, anomalies may not be detected due to cloud cover; clouds absorb thermal radiation limiting or preventing the ability of the satellite to measure thermal events; therefore, the anomaly data is supplemented with a cloud cover time-series data set. Fast Fourier and Wavelet transforms are then applied to the continuous, uninterrupted intervals of satellite observation to compare and correlate with the multiple time-series data sets. The result is the characterization of the behavior of an individual volcano, based on an extended time period. This volcano specific, comprehensive characterization can then be used as a predictive tool in the real-time monitoring of volcanic activity.

Production and Distribution of Global Products From MODIS

NASA Technical Reports Server (NTRS)

Masuoka, Edward; Smith, David E. (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer was launched on the EOS Terra spacecraft in December 1999 and will also fly on EOS Aqua in December 2000. With 36 spectral bands from the visible through thermal infrared and spatial resolution of 250m to 1 kilometer, each MODIS instrument will image the entire Earth surface in 2 days. This paper traces the flow of MODIS data products from the receipt of Level 0 data at the EDOS facility, through the production and quality assurance process to the Distributed Active Archive Centers (DAACs), which ship products to the user community. It describes where to obtain products and plans for reprocessing MODIS products. As most components of the ground system are severely limited in their capacity to distribute MODIS products, it also describes the key characteristics of MODIS products and their metadata that allow a user to optimize their selection of products given anticipate bottlenecks in distribution.

Operationalizing a Research Sensor: MODIS to VIIRS

NASA Astrophysics Data System (ADS)

Grant, K. D.; Miller, S. W.; Puschell, J.

2012-12-01

The National Oceanic and Atmospheric Administration (NOAA) and NASA are jointly acquiring the next-generation civilian environmental satellite system: the Joint Polar Satellite System (JPSS). JPSS will replace the afternoon orbit component and ground processing system of the current Polar-orbiting Operational Environmental Satellites (POES) managed by NOAA. The JPSS satellite will carry a suite of sensors designed to collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The primary sensor for the JPSS mission is the Visible/Infrared Imager Radiometer Suite (VIIRS) developed by Raytheon Space and Airborne Systems (SAS). The ground processing system for the JPSS mission is known as the Common Ground System (JPSS CGS), and consists of a Command, Control, and Communications Segment (C3S) and the Interface Data Processing Segment (IDPS) which are both developed by Raytheon Intelligence and Information Systems (IIS). The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by Raytheon SAS for the NASA Earth Observing System (EOS) as a research instrument to capture data in 36 spectral bands, ranging in wavelength from 0.4 μm to 14.4 μm and at varying spatial resolutions (2 bands at 250 m, 5 bands at 500 m and 29 bands at 1 km). MODIS data provides unprecedented insight into large-scale Earth system science questions related to cloud and aerosol characteristics, surface emissivity and processes occurring in the oceans, on land, and in the lower atmosphere. MODIS has flown on the EOS Terra satellite since 1999 and on the EOS Aqua satellite since 2002 and provided excellent data for scientific research and operational use for more than a decade. The value of MODIS-derived products for operational environmental monitoring motivated led to the development of an operational counterpart to MODIS for the next-generation polar-orbiting environmental satellites, the Visible/Infrared Imager Radiometer Suite (VIIRS). VIIRS combines the demonstrated high value spectral coverage and radiometric accuracy of MODIS with the legacy spectral bands and radiometric accuracy of the Advanced Very High Resolution Radiometer (AVHRR) and the high spatial resolution (0.75 km) of the Operational Linescan System (OLS). Except for MODIS bands designed for deriving vertical temperature and humidity structure in the atmosphere, VIIRS uses identical or very similar bands from MODIS that have the most interest and usefulness to operational customers in NOAA, the USAF and the USN. The development of VIIRS and JPSS reaps the benefit of investments in MODIS and the NASA EOS and the early development of operational algorithms by NOAA and DoD using MODIS data. This presentation will cover the different aspects of transitioning a research system into an operational system. These aspects include: (1) sensor (hardware & software) operationalization, (2) system performance operational factors, (3) science changes to algorithms reflecting the operational performance factors, and (4) the operationalization and incorporation of the science into a fully 24 x 7 production system, tasked with meeting stringent operational needs. Benefits of early operationalization are discussed along with suggested areas for improvement in this process that could benefit future work such as operationalizing Earth Science Decadal Survey missions.

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.

Improving land surface emissivty parameter for land surface models using portable FTIR and remote sensing observation in Taklimakan Desert

NASA Astrophysics Data System (ADS)

Liu, Yongqiang; Mamtimin, Ali; He, Qing

2014-05-01

Because land surface emissivity (ɛ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply assumption, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, 0.96 for soil and wetland in the Global and Regional Assimilation and Prediction System (GRAPES) Common Land Model (CoLM). This is the so-called emissivity assumption. Accurate broadband emissivity data are needed as model inputs to better simulate the land surface climate. It is demonstrated in this paper that the assumption of the emissivity induces errors in modeling the surface energy budget over Taklimakan Desert where ɛ is far smaller than original value. One feasible solution to this problem is to apply the accurate broadband emissivity into land surface models. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has routinely measured spectral emissivities in six thermal infrared bands. The empirical regression equations have been developed in this study to convert these spectral emissivities to broadband emissivity required by land surface models. In order to calibrate the regression equations, using a portable Fourier Transform infrared (FTIR) spectrometer instrument, crossing Taklimakan Desert along with highway from north to south, to measure the accurate broadband emissivity. The observed emissivity data show broadband ɛ around 0.89-0.92. To examine the impact of improved ɛ to radiative energy redistribution, simulation studies were conducted using offline CoLM. The results illustrate that large impacts of surface ɛ occur over desert, with changes up in surface skin temperature, as well as evident changes in sensible heat fluxes. Keywords: Taklimakan Desert, surface broadband emissivity, Fourier Transform infrared spectrometer, MODIS, CoLM

TERRA/MODIS Data Products and Data Management at the GES-DAAC

NASA Astrophysics Data System (ADS)

Sharma, A. K.; Ahmad, S.; Eaton, P.; Koziana, J.; Leptoukh, G.; Ouzounov, D.; Savtchenko, A.; Serafino, G.; Sikder, M.; Zhou, B.

2001-05-01

Since February 2000, the Earth Sciences Distributed Active Archive Center (GES-DAAC) at the NASA/Goddard Space Flight Center has been successfully ingesting, processing, archiving, and distributing the Moderate Resolution Imaging Spectroradiometer (MODIS) data. MODIS is the key instrument aboard the Terra satellite, viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 channels in the visible and infrared spectral bands (0.4 to 14.4 microns). Higher resolution (250m, 500m, and 1km pixel) data are improving our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere and will play a vital role in the future development of validated, global, interactive Earth-system models. MODIS calibrated and uncalibrated radiances, and geolocation products were released to the public in April 2000, and a suite of oceans products and an entire suite of atmospheric products were released by early January 2001. The suite of ocean products is grouped into three categories Ocean Color, SST and Primary Productivity. The suite of atmospheric products includes Aerosol, Total Precipitable Water, Cloud Optical and Physical properties, Atmospheric Profiles and Cloud Mask. The MODIS Data Support Team (MDST) at the GES-DAAC has been providing support for enabling basic scientific research and assistance in accessing the scientific data and information to the Earth Science User Community. Support is also provided for data formats (HDF-EOS), information on visualization tools, documentation for data products, information on the scientific content of products and metadata. Visit the MDST website at http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/MODIS/index.html The task to process archive and distribute enormous volumes of MODIS data to users (more than 0.5 TB a day) has led to the development of an unique world wide web based GES DAAC Search and Order system http://acdisx.gsfc.nasa.gov/data/, data handling software and tools, as well as a FTP site that contains sample of browse images and MODIS data products. This paper is intended to inform the user community about the data system and services available at the GES-DAAC in support of these information-rich data products. MDST provides support to MODIS data users to access and process data and information for research, applications and educational purposes. This paper will present an overview of the MODIS data products released to public including the suite of atmosphere and oceans data products that can be ordered from the GES-DAAC. Different mechanisms for search and ordering the data, determining data product sizes, data distribution policy, User Assistance System (UAS), and data subscription services will be described.

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.

A Model-based Approach to Scaling GPP and NPP in Support of MODIS Land Product Validation

NASA Astrophysics Data System (ADS)

Turner, D. P.; Cohen, W. B.; Gower, S. T.; Ritts, W. D.

2003-12-01

Global products from the Earth-orbiting MODIS sensor include land cover, leaf area index (LAI), FPAR, 8-day gross primary production (GPP), and annual net primary production (NPP) at the 1 km spatial resolution. The BigFoot Project was designed specifically to validate MODIS land products, and has initiated ground measurements at 9 sites representing a wide array of vegetation types. An ecosystem process model (Biome-BGC) is used to generate estimates of GPP and NPP for each 5 km x 5 km BigFoot site. Model inputs include land cover and LAI (from Landsat ETM+), daily meteorological data (from a centrally located eddy covariance flux tower), and soil characteristics. Model derived outputs are validated against field-measured NPP and flux tower-derived GPP. The resulting GPP and NPP estimates are then aggregated to the 1 km resolution for direct spatial comparison with corresponding MODIS products. At the high latitude sites (tundra and boreal forest), the MODIS GPP phenology closely tracks the BigFoot GPP, but there is a high bias in the MODIS GPP. In the temperate zone sites, problems with the timing and magnitude of the MODIS FPAR introduce differences in MODIS GPP compared to the validation data at some sites. However, the MODIS LAI/FPAR data are currently being reprocessed (=Collection 4) and new comparisons will be made for 2002. The BigFoot scaling approach permits precise overlap in spatial and temporal resolution between the MODIS products and BigFoot products, and thus permits the evaluation of specific components of the MODIS NPP algorithm. These components include meteorological inputs from the NASA Data Assimilation Office, LAI and FPAR from other MODIS algorithms, and biome-specific parameters for base respiration rate and light use efficiency.

Siberian Earth System Science Cluster - A web-based Geoportal to provide user-friendly Earth Observation Products for supporting NEESPI scientists

NASA Astrophysics Data System (ADS)

Eberle, J.; Gerlach, R.; Hese, S.; Schmullius, C.

2012-04-01

To provide earth observation products in the area of Siberia, the Siberian Earth System Science Cluster (SIB-ESS-C) was established as a spatial data infrastructure at the University of Jena (Germany), Department for Earth Observation. This spatial data infrastructure implements standards published by the Open Geospatial Consortium (OGC) and the International Organizsation for Standardization (ISO) for data discovery, data access, data processing and data analysis. The objective of SIB-ESS-C is to faciliate environmental research and Earth system science in Siberia. The region for this project covers the entire Asian part of the Russian Federation approximately between 58°E - 170°W and 48°N - 80°N. To provide discovery, access and analysis services a webportal was published for searching and visualisation of available data. This webportal is based on current web technologies like AJAX, Drupal Content Management System as backend software and a user-friendly surface with Drag-n-Drop and further mouse events. To have a wide range of regular updated earth observation products, some products from sensor MODIS at the satellites Aqua and Terra were processed. A direct connection to NASA archive servers makes it possible to download MODIS Level 3 and 4 products and integrate it in the SIB-ESS-C infrastructure. These data can be downloaded in a file format called Hierarchical Data Format (HDF). For visualisation and further analysis, this data is reprojected, converted to GeoTIFF and global products clipped to the project area. All these steps are implemented as an automatic process chain. If new MODIS data is available within the infrastructure this process chain is executed. With the link to a MODIS catalogue system, the system gets new data daily. With the implemented analysis processes, timeseries data can be analysed, for example to plot a trend or different time series against one another. Scientists working in this area and working with MODIS data can make use of this service over the webportal. Both searching manually the NASA archive for MODIS data, processing these data automatically and then download it for further processing and using the regular updated products.

Comparative Analysis of Aerosol Retrievals from MODIS, OMI and MISR Over Sahara Region

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Hsu, C.; Terres, O.; Leptoukh, G.; Kalashnikova, O.; Korkin, S.

2011-01-01

MODIS is a wide field-of-view sensor providing daily global observations of the Earth. Currently, global MODIS aerosol retrievals over land are performed with the main Dark Target algorithm complimented with the Deep Blue (DB) Algorithm over bright deserts. The Dark Target algorithm relies on surface parameterization which relates reflectance in MODIS visible bands with the 2.1 micrometer region, whereas the Deep Blue algorithm uses an ancillary angular distribution model of surface reflectance developed from the time series of clear-sky MODIS observations. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm has been developed for MODIS. MAIAC uses a time series and an image based processing to perform simultaneous retrievals of aerosol properties and surface bidirectional reflectance. It is a generic algorithm which works over both dark vegetative surfaces and bright deserts and performs retrievals at 1 km resolution. In this work, we will provide a comparative analysis of DB, MAIAC, MISR and OMI aerosol products over bright deserts of northern Africa.

Modis, SeaWIFS, and Pathfinder funded activities

NASA Technical Reports Server (NTRS)

Evans, Robert H.

1995-01-01

MODIS (Moderate Resolution Imaging Spectrometer), SeaWIFS (Sea-viewing Wide Field Sensor), Pathfinder, and DSP (Digital Signal Processor) objectives are summarized. An overview of current progress is given for the automatic processing database, client/server status, matchup database, and DSP support.

Synergistic Use of MODIS and AIRS in a Variational Retrieval of Cloud Parameters.

NASA Astrophysics Data System (ADS)

Li, Jun; Menzel, W. Paul; Zhang, Wenjian; Sun, Fengying; Schmit, Timothy J.; Gurka, James J.; Weisz, Elisabeth

2004-11-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS's) Aqua satellite enable global monitoring of the distribution of clouds. MODIS is able to provide a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size, and cloud optical thickness at high spatial resolution (1 5 km). The combined MODIS AIRS system offers the opportunity for improved cloud products, better than from either system alone; this improvement is demonstrated in this paper with both simulated and real radiances. A one-dimensional variational (1DVAR) methodology is used to retrieve the CTP and ECA from AIRS longwave (650 790 cm-1 or 15.38 12.65 μm) cloudy radiance measurements (hereinafter referred to as MODIS AIRS 1DVAR). The MODIS AIRS 1DVAR cloud properties show significant improvement over the MODIS-alone cloud properties and slight improvement over AIRS-alone cloud properties in a simulation study, while MODIS AIRS 1DVAR is much more computationally efficient than the AIRS-alone 1DVAR; comparisons with radiosonde observations show that CTPs improve by 10 40 hPa for MODIS AIRS CTPs over those from MODIS alone. The 1DVAR approach is applied to process the AIRS longwave cloudy radiance measurements; results are compared with MODIS and Geostationary Operational Environmental Satellite sounder cloud products. Data from ground-based instrumentation at the Atmospheric Radiation Measurement Program Cloud and Radiation Test Bed in Oklahoma are used for validation; results show that MODIS AIRS improves the MODIS CTP, especially in low-level clouds. The operational use of a high-spatial-resolution imager, along with information from a high-spectral-resolution sounder will be possible with instruments planned for the next-generation geostationary operational instruments.

Extending MODIS Deep Blue Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: First Results

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Shinozuka, Y.; Schmid, B.

2015-01-01

Absorbing smoke or mineral dust aerosols above clouds (AAC) are a frequent occurrence in certain regions and seasons. Operational aerosol retrievals from sensors like MODIS omit AAC because they are designed to work only over cloud-free scenes. However, AAC can in principle be quantified by these sensors in some situations (e.g. Jethva et al., 2013; Meyer et al., 2013). We present a summary of some analyses of the potential of MODIS-like instruments for this purpose, along with two case studies using airborne observations from the Ames Airborne Tracking Sunphotometer (AATS; http://geo.arc.nasa.gov/sgg/AATS-website/) as a validation data source for a preliminary AAC algorithm applied to MODIS measurements. AAC retrievals will eventually be added to the MODIS Deep Blue (Hsu et al., 2013) processing chain.

MODIS Snow and Ice Products from the NSIDC DAAC

NASA Technical Reports Server (NTRS)

Scharfen, Greg R.; Hall, Dorothy K.; Riggs, George A.

1997-01-01

The National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) provides data and information on snow and ice processes, especially pertaining to interactions among snow, ice, atmosphere and ocean, in support of research on global change detection and model validation, and provides general data and information services to cryospheric and polar processes research community. The NSIDC DAAC is an integral part of the multi-agency-funded support for snow and ice data management services at NSIDC. The Moderate Resolution Imaging Spectroradiometer (MODIS) will be flown on the first Earth Observation System (EOS) platform (AM-1) in 1998. The MODIS Instrument Science Team is developing geophysical products from data collected by the MODIS instrument, including snow and ice products which will be archived and distributed by NSIDC DAAC. The MODIS snow and ice mapping algorithms will generate global snow, lake ice, and sea ice cover products on a daily basis. These products will augment the existing record of satellite-derived snow cover and sea ice products that began about 30 years ago. The characteristics of these products, their utility, and comparisons to other data set are discussed. Current developments and issues are summarized.

Continental-Scale Validation of Modis-Based and LEDAPS Landsat ETM + Atmospheric Correction Methods

NASA Technical Reports Server (NTRS)

Ju, Junchang; Roy, David P.; Vermote, Eric; Masek, Jeffrey; Kovalskyy, Valeriy

2012-01-01

The potential of Landsat data processing to provide systematic continental scale products has been demonstratedby several projects including the NASA Web-enabled Landsat Data (WELD) project. The recent freeavailability of Landsat data increases the need for robust and efficient atmospheric correction algorithms applicableto large volume Landsat data sets. This paper compares the accuracy of two Landsat atmospheric correctionmethods: a MODIS-based method and the Landsat Ecosystem Disturbance Adaptive ProcessingSystem (LEDAPS) method. Both methods are based on the 6SV radiative transfer code but have different atmosphericcharacterization approaches. The MODIS-based method uses the MODIS Terra derived dynamicaerosol type, aerosol optical thickness, and water vapor to atmospherically correct ETM+ acquisitions ineach coincident orbit. The LEDAPS method uses aerosol characterizations derived independently from eachLandsat acquisition and assumes a fixed continental aerosol type and uses ancillary water vapor. Validationresults are presented comparing ETM+ atmospherically corrected data generated using these two methodswith AERONET corrected ETM+ data for 95 10 km10 km 30 m subsets, a total of nearly 8 million 30 mpixels, located across the conterminous United States. The results indicate that the MODIS-based methodhas better accuracy than the LEDAPS method for the ETM+ red and longer wavelength bands.

MODIS Data from the GES DISC DAAC: Moderate-Resolution Imaging Spectroradiometer (MODIS)

NASA Technical Reports Server (NTRS)

2002-01-01

The Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) is responsible for the distribution of the Level 1 data, and the higher levels of all Ocean and Atmosphere products (Land products are distributed through the Land Processes (LP) DAAC DAAC, and the Snow and Ice products are distributed though the National Snow and Ice Data Center (NSIDC) DAAC). Ocean products include sea surface temperature (SST), concentrations of chlorophyll, pigment and coccolithophores, fluorescence, absorptions, and primary productivity. Atmosphere products include aerosols, atmospheric water vapor, clouds and cloud masks, and atmospheric profiles from 20 layers. While most MODIS data products are archived in the Hierarchical Data Format-Earth Observing System (HDF-EOS 2.7) format, the ocean binned products and primary productivity products (Level 4) are in the native HDF4 format. MODIS Level 1 and 2 data are of the Swath type and are packaged in files representing five minutes of Files for Level 3 and 4 are global products at daily, weekly, monthly or yearly resolutions. Apart from the ocean binned and Level 4 products, these are in Grid type, and the maps are in the Cylindrical Equidistant projection with rectangular grid. Terra viewing (scenes of approximately 2000 by 2330 km). MODIS data have several levels of maturity. Most products are released with a provisional level of maturity and only announced as validated after rigorous testing by the MODIS Science Teams. MODIS/Terra Level 1, and all MODIS/Terra 11 micron SST products are announced as validated. At the time of this publication, the MODIS Data Support Team (MDST) is working with the Ocean Science Team toward announcing the validated status of the remainder of MODIS/Terra Ocean products. MODIS/Aqua Level 1 and cloud mask products are released with provisional maturity.

Predicting Treatment Windows for Invasive Buffelgrass in Southern Arizona using MODIS and Climate Data

NASA Astrophysics Data System (ADS)

Wallace, C.; Weltzin, J. F.; Skirvin, S. M.; Patrick-Birdwell, C.; Raichle, H.

2014-12-01

The increasing spread and abundance of an invasive perennial grass, buffelgrass (Pennisetum ciliare), represents an important shift in the vegetation composition of the Sonoran Desert in southern Arizona. Buffelgrass out-competes native species and alters fire regimes, and its control and management is a high-priority issue for resource managers who seek to preserve the unique and iconic Sonoran Desert flora. Herbicidal treatment of buffelgrass is most effective when the vegetation is actively growing; however, the erratic timing and length of active buffelgrass growth periods in southern Arizona confound effective management decision-making. The goal of our research is to enable the strategic application of buffelgrass herbicide by using remote sensing data to detect when and where buffelgrass is photosynthetically active. We integrated ground-based observations of buffelgrass phenology (green-up and senescence) in the Tucson, Arizona area with climate information and Moderate-resolution Imaging Spectroradiometer (MODIS) satellite imagery at 250m spatial and both 8-day and 16-day composite temporal resolution to understand dynamics, relationships and resonance between these disparate datasets during 2011 to 2013. Fourier harmonics analysis was used to derive land surface phenology (LSP) metrics from MODIS Enhanced Vegetation Index (EVI) greenness data and to quantify the temporal patterns of the climate and phenophase abundance datasets. Regression analyses and statistical tests were used to identify correlations between temporal patterns of the data sets. Our results reveal strong correlations between the observed greenness of in-situ buffelgrass and satellite LSP metrics, confirming that MODIS-EVI data can be a useful indicator of active buffelgrass growth at multiple scales. The analysis also reveals strong harmonics between precipitation and greenness, but with a lagged response, suggesting that precipitation can be a predictor of the location and intensity of buffelgrass green-up at landscape scales. This information can be used by resource managers to treat buffelgrass during optimal conditions.

Characterising volcanic cycles at Soufriere Hills Volcano, Montserrat: Time series analysis of multi-parameter satellite data

NASA Astrophysics Data System (ADS)

Flower, Verity J. B.; Carn, Simon A.

2015-10-01

The identification of cyclic volcanic activity can elucidate underlying eruption dynamics and aid volcanic hazard mitigation. Whilst satellite datasets are often analysed individually, here we exploit the multi-platform NASA A-Train satellite constellation to cross-correlate cyclical signals identified using complementary measurement techniques at Soufriere Hills Volcano (SHV), Montserrat. In this paper we present a Multi-taper (MTM) Fast Fourier Transform (FFT) analysis of coincident SO2 and thermal infrared (TIR) satellite measurements at SHV facilitating the identification of cyclical volcanic behaviour. These measurements were collected by the Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) (respectively) in the A-Train. We identify a correlating cycle in both the OMI and MODIS data (54-58 days), with this multi-week feature attributable to episodes of dome growth. The 50 day cycles were also identified in ground-based SO2 data at SHV, confirming the validity of our analysis and further corroborating the presence of this cycle at the volcano. In addition a 12 day cycle was identified in the OMI data, previously attributed to variable lava effusion rates on shorter timescales. OMI data also display a one week (7-8 days) cycle attributable to cyclical variations in viewing angle resulting from the orbital characteristics of the Aura satellite. Longer period cycles possibly relating to magma intrusion were identified in the OMI record (102-, 121-, and 159 days); in addition to a 238-day cycle identified in the MODIS data corresponding to periodic destabilisation of the lava dome. Through the analysis of reconstructions generated from cycles identified in the OMI and MODIS data, periods of unrest were identified, including the major dome collapse of 20th May 2006 and significant explosive event of 3rd January 2009. Our analysis confirms the potential for identification of cyclical volcanic activity through combined analysis of satellite data, which would be of particular value at poorly monitored volcanic systems.

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.

A Disk-Based System for Producing and Distributing Science Products from MODIS

NASA Technical Reports Server (NTRS)

Masuoka, Edward; Wolfe, Robert; Sinno, Scott; Ye Gang; Teague, Michael

2007-01-01

Since beginning operations in 1999, the MODIS Adaptive Processing System (MODAPS) has evolved to take advantage of trends in information technology, such as the falling cost of computing cycles and disk storage and the availability of high quality open-source software (Linux, Apache and Perl), to achieve substantial gains in processing and distribution capacity and throughput while driving down the cost of system operations.

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%.

Mapping Snow Grain Size over Greenland from MODIS

NASA Technical Reports Server (NTRS)

Lyapustin, Alexei; Tedesco, Marco; Wang, Yujie; Kokhanovsky, Alexander

2008-01-01

This paper presents a new automatic algorithm to derive optical snow grain size (SGS) at 1 km resolution using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Differently from previous approaches, snow grains are not assumed to be spherical but a fractal approach is used to account for their irregular shape. The retrieval is conceptually based on an analytical asymptotic radiative transfer model which predicts spectral bidirectional snow reflectance as a function of the grain size and ice absorption. The analytical form of solution leads to an explicit and fast retrieval algorithm. The time series analysis of derived SGS shows a good sensitivity to snow metamorphism, including melting and snow precipitation events. Preprocessing is performed by a Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, which includes gridding MODIS data to 1 km resolution, water vapor retrieval, cloud masking and an atmospheric correction. MAIAC cloud mask (CM) is a new algorithm based on a time series of gridded MODIS measurements and an image-based rather than pixel-based processing. Extensive processing of MODIS TERRA data over Greenland shows a robust performance of CM algorithm in discrimination of clouds over bright snow and ice. As part of the validation analysis, SGS derived from MODIS over selected sites in 2004 was compared to the microwave brightness temperature measurements of SSM\\I radiometer, which is sensitive to the amount of liquid water in the snowpack. The comparison showed a good qualitative agreement, with both datasets detecting two main periods of snowmelt. Additionally, MODIS SGS was compared with predictions of the snow model CROCUS driven by measurements of the automatic whether stations of the Greenland Climate Network. We found that CROCUS grain size is on average a factor of two larger than MODIS-derived SGS. Overall, the agreement between CROCUS and MODIS results was satisfactory, in particular before and during the first melting period in mid-June. Following detailed time series analysis of SGS for four permanent sites, the paper presents SGS maps over the Greenland ice sheet for the March-September period of 2004.

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.

System for Continuous Delivery of MODIS Imagery to Internet Mapping Applications

NASA Technical Reports Server (NTRS)

Plesea, Lucian

2008-01-01

This software represents a complete, unsupervised processing chain that generates a continuously updating global image of the Earth from the most recent available MODIS Level 1B scenes. The software constantly updates a global image of the Earth at 250 m per pixel.

A review of maturity onset diabetes of the young (MODY) and challenges in the management of glucokinase-MODY.

PubMed

Bishay, Ramy H; Greenfield, Jerry R

2016-11-21

Maturity onset diabetes of the young (MODY), the most common monogenic form of diabetes, accounts for 1-2% of all diabetes diagnoses. Glucokinase (GCK)-MODY (also referred to as MODY2) constitutes 10-60% of all MODY cases and is inherited as an autosomal dominant heterozygous mutation, resulting in loss of function of the GCK gene. Patients with GCK-MODY generally have mild, fasting hyperglycaemia that is present from birth, are commonly leaner and diagnosed at a younger age than patients with type 2 diabetes, and rarely develop complications from diabetes. Hence, treatment is usually unnecessary and may be ceased. Therefore, genetic screening is recommended in all young patients (< 40 years) with an autosomal dominant family history of diabetes and who lack features of the metabolic syndrome and type 1 diabetes. Further, treatment discontinuation should be discussed with the patient as part of the informed consent process, as the realisation that prior treatment may have not been necessary - or that it could have been less burdensome - may have psychological implications for the patient. This is true for other forms of MODY, such as hepatocyte nuclear factor 1A mutations (MODY3) where hyperglycaemia is managed with low dose sulfonylurea rather than insulin. Patients with GCK-MODY, in line with trends in the general population, are becoming older and more overweight and obese, and are concomitantly developing features of insulin resistance and glucose intolerance. Therefore, controversy exists as to whether such "treatment-exempt" patients should be reassessed for treatment later in life. As testing becomes more accessible, clinicians and patients are likely to embrace genetic screening earlier in the course of diabetes, which may avert the consequences of delayed testing years after diagnosis and treatment initiation.

Improvements to the MODIS Land Products in Collection Version 6

NASA Astrophysics Data System (ADS)

Wolfe, R. E.; Devadiga, S.; Masuoka, E. J.; Running, S. W.; Vermote, E.; Giglio, L.; Wan, Z.; Riggs, G. A.; Schaaf, C.; Myneni, R. B.; Friedl, M. A.; Wang, Z.; Sulla-menashe, D. J.; Zhao, M.

2013-12-01

The MODIS (Moderate Resolution Imaging Spectroradiometer) Adaptive Processing System (MODAPS), housed at the NASA Goddard Space Flight Center (GSFC), has been processing the earth view data acquired by the MODIS instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites to generate suite of land and atmosphere data products using the science algorithms developed by the MODIS Science Team. These data products are used by diverse set of users in research and other applications from both government and non-government agencies around the world. These validated global products are also being used in interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment. Hence an increased emphasis is being placed on generation of high quality consistent data records from the MODIS data through reprocessing of the records using improved science algorithms. Since the launch of Terra in December 1999, MODIS land data records have been reprocessed four times. The Collection Version 6 (C6) reprocessing of MODIS Land and Atmosphere products is scheduled to start in Fall 2013 and is expected to complete in Spring 2014. This presentation will describe changes made to the C6 science algorithms to correct issues in the C5 products, additional improvements made to the products as deemed necessary by the data users and science teams, and new products introduced in this reprocessing. In addition to the improvements from product specific changes to algorithms, the C6 products will also see significant improvement in the calibration by the MODIS Calibration Science Team (MCST) of the C6 L1B Top of the Atmosphere (TOA) reflectance and radiance product, more accurate geolocation, and an improved Land Water mask. For the a priori land cover input, this reprocessing will use the multi-year land cover product generated with three years of MODIS data as input as opposed to one single land cover product used for the entire mission in the C5 reprocessing. The C6 products are expected to be released from the Distributed Active Archive Center (DAAC) soon after the reprocessing begins. To facilitate user acquaintance with products from the new version and independent evaluation of C6 by comparison of two versions, MODAPS plans to continue generation of products from both versions for at least a year after completion of the C6 reprocessing after which C5 processing will be discontinued.

Continental-scale Validation of MODIS-based and LEDAPS Landsat ETM+ Atmospheric Correction Methods

NASA Technical Reports Server (NTRS)

Ju, Junchang; Roy, David P.; Vermote, Eric; Masek, Jeffrey; Kovalskyy, Valeriy

2012-01-01

The potential of Landsat data processing to provide systematic continental scale products has been demonstrated by several projects including the NASA Web-enabled Landsat Data (WELD) project. The recent free availability of Landsat data increases the need for robust and efficient atmospheric correction algorithms applicable to large volume Landsat data sets. This paper compares the accuracy of two Landsat atmospheric correction methods: a MODIS-based method and the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) method. Both methods are based on the 6SV radiative transfer code but have different atmospheric characterization approaches. The MODIS-based method uses the MODIS Terra derived dynamic aerosol type, aerosol optical thickness, and water vapor to atmospherically correct ETM+ acquisitions in each coincident orbit. The LEDAPS method uses aerosol characterizations derived independently from each Landsat acquisition and assumes a fixed continental aerosol type and uses ancillary water vapor. Validation results are presented comparing ETM+ atmospherically corrected data generated using these two methods with AERONET corrected ETM+ data for 95 10 km×10 km 30 m subsets, a total of nearly 8 million 30 m pixels, located across the conterminous United States. The results indicate that the MODIS-based method has better accuracy than the LEDAPS method for the ETM+ red and longer wavelength bands.

Consistency of two global MODIS aerosol products over ocean on Terra and Aqua CERES SSF datasets

NASA Astrophysics Data System (ADS)

Ignatov, Alexander; Minnis, Patrick; Wielicki, Bruce; Loeb, Norman G.; Remer, Lorraine A.; Kaufman, Yoram J.; Miller, Walter F.; Sun-Mack, Sunny; Laszlo, Istvan; Geier, Erika B.

2004-12-01

MODIS aerosol retrievals over ocean from Terra and Aqua platforms are available from the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint (SSF) datasets generated at NASA Langley Research Center (LaRC). Two aerosol products are reported side by side. The primary M product is generated by subsetting and remapping the multi-spectral (0.44 - 2.1 μm) MOD04 aerosols onto CERES footprints. MOD04 processing uses cloud screening and aerosol algorithms developed by the MODIS science team. The secondary (AVHRR-like) A product is generated in only two MODIS bands: 1 and 6 on Terra, and ` and 7 on Aqua. The A processing uses NASA/LaRC cloud-screening and NOAA/NESDIS single channel aerosol algorthm. The M and A products have been documented elsewhere and preliminarily compared using two weeks of global Terra CERES SSF (Edition 1A) data in December 2000 and June 2001. In this study, the M and A aerosol optical depths (AOD) in MODIS band 1 and (0.64 μm), τ1M and τ1A, are further checked for cross-platform consistency using 9 days of global Terra CERES SSF (Edition 2A) and Aqua CERES SSF (Edition 1A) data from 13 - 21 October 2002.

Investigation of cloud properties and atmospheric stability with MODIS

NASA Technical Reports Server (NTRS)

Menzel, Paul

1995-01-01

In the past six months several milestones were accomplished. The MODIS Airborne Simulator (MAS) was flown in a 50 channel configuration for the first time in January 1995 and the data were calibrated and validated; in the same field campaign the approach for validating MODIS radiances using the MAS and High resolution Interferometer Sounder (HIS) instruments was successfully tested on GOES-8. Cloud masks for two scenes (one winter and the other summer) of AVHRR local area coverage from the Gulf of Mexico to Canada were processed and forwarded to the SDST for MODIS Science Team investigation; a variety of surface and cloud scenes were evident. Beta software preparations continued with incorporation of the EOS SDP Toolkit. SCAR-C data was processed and presented at the biomass burning conference. Preparations for SCAR-B accelerated with generation of a home page for access to real time satellite data related to biomass burning; this will be available to the scientists in Brazil via internet on the World Wide Web. The CO2 cloud algorithm was compared to other algorithms that differ in their construction of clear radiance fields. The HIRS global cloud climatology was completed for six years. The MODIS science team meeting was attended by five of the UW scientists.

Synergistic use of MODIS cloud products and AIRS radiance measurements for retrieval of cloud parameters

NASA Astrophysics Data System (ADS)

Li, J.; Menzel, W.; Sun, F.; Schmit, T.

2003-12-01

The Moderate-Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS) Aqua satellite will enable global monitoring of the distribution of clouds. MODIS is able to provide at high spatial resolution (1 ~ 5km) the cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud water path (CWP). AIRS is able to provide CTP, ECA, CPS, and CWP within the AIRS footprint with much better accuracy using its greatly enhanced hyperspectral remote sensing capability. The combined MODIS / AIRS system offers the opportunity for cloud products improved over those possible from either system alone. The algorithm developed was applied to process the AIRS longwave cloudy radiance measurements; results are compared with MODIS cloud products, as well as with the Geostationary Operational Environmental Satellite (GOES) sounder cloud products, to demonstrate the advantage of synergistic use of high spatial resolution MODIS cloud products and high spectral resolution AIRS sounder radiance measurements for optimal cloud retrieval. Data from ground-based instrumentation at the Atmospheric Radiation Measurement (ARM) Program Cloud and Radiation Test Bed (CART) in Oklahoma were used for the validation; results show that AIRS improves the MODIS cloud products in certain cases such as low-level clouds.

Quality Assessment of Collection 6 MODIS Atmospheric Science Products

NASA Astrophysics Data System (ADS)

Manoharan, V. S.; Ridgway, B.; Platnick, S. E.; Devadiga, S.; Mauoka, E.

2015-12-01

Since the launch of the NASA Terra and Aqua satellites in December 1999 and May 2002, respectively, atmosphere and land data acquired by the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor on-board these satellites have been reprocessed five times at the MODAPS (MODIS Adaptive Processing System) located at NASA GSFC. The global land and atmosphere products use science algorithms developed by the NASA MODIS science team investigators. MODAPS completed Collection 6 reprocessing of MODIS Atmosphere science data products in April 2015 and is currently generating the Collection 6 products using the latest version of the science algorithms. This reprocessing has generated one of the longest time series of consistent data records for understanding cloud, aerosol, and other constituents in the earth's atmosphere. It is important to carefully evaluate and assess the quality of this data and remove any artifacts to maintain a useful climate data record. Quality Assessment (QA) is an integral part of the processing chain at MODAPS. This presentation will describe the QA approaches and tools adopted by the MODIS Land/Atmosphere Operational Product Evaluation (LDOPE) team to assess the quality of MODIS operational Atmospheric products produced at MODAPS. Some of the tools include global high resolution images, time series analysis and statistical QA metrics. The new high resolution global browse images with pan and zoom have provided the ability to perform QA of products in real time through synoptic QA on the web. This global browse generation has been useful in identifying production error, data loss, and data quality issues from calibration error, geolocation error and algorithm performance. A time series analysis for various science datasets in the Level-3 monthly product was recently developed for assessing any long term drifts in the data arising from instrument errors or other artifacts. This presentation will describe and discuss some test cases from the recently processed C6 products. We will also describe the various tools and approaches developed to verify and assess the algorithm changes implemented by the science team to address known issues in the products and improve the quality of the products.

Occurrence of weak, sub-micron, tropospheric aerosol events at high Arctic latitudes

NASA Astrophysics Data System (ADS)

O'Neill, N. T.; Pancrati, O.; Baibakov, K.; Eloranta, E.; Batchelor, R. L.; Freemantle, J.; McArthur, L. J. B.; Strong, K.; Lindenmaier, R.

2008-07-01

Numerous fine mode (sub-micron) aerosol optical events were observed during the summer of 2007 at the High Arctic atmospheric observatory (PEARL) located at Eureka, Nunavut, Canada. Half of these events could be traced to forest fires in southern and eastern Russia and the Northwest Territories of Canada. The most notable findings were that (a) a combination of ground-based measurements (passive sunphotometry, high spectral resolution lidar) could be employed to determine that weak (near sub-visual) fine mode events had occurred, and (b) this data combined with remote sensing imagery products (MODIS, OMI-AI, FLAMBE fire sources), Fourier transform spectroscopy and back trajectories could be employed to identify the smoke events.

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.

Evaluation of Shortwave Infrared Atmospheric Correction for Ocean Color Remote Sensing of Chesapeake Bay

NASA Technical Reports Server (NTRS)

Werdell, P. Jeremy; Franz, Bryan A.; Bailey, Sean W.

2010-01-01

The NASA Moderate Resolution Imaging Spectroradiometer onboard the Aqua platform (MODIS-Aqua) provides a viable data stream for operational water quality monitoring of Chesapeake Bay. Marine geophysical products from MODIS-Aqua depend on the efficacy of the atmospheric correction process, which can be problematic in coastal environments. The operational atmospheric correction algorithm for MODIS-Aqua requires an assumption of negligible near-infrared water-leaving radiance, nL(sub w)(NIR). This assumption progressively degrades with increasing turbidity and, as such, methods exist to account for non-negligible nL(sub w)(NIR) within the atmospheric correction process or to use alternate radiometric bands where the assumption is satisfied, such as those positioned within shortwave infrared (SWIR) region of the spectrum. We evaluated a decade-long time-series of nL(sub w)(lambda) from MODIS-Aqua in Chesapeake Bay derived using NIR and SWIR bands for atmospheric correction. Low signal-to-noise ratios (SNR) for the SWIR bands of MODIS-Aqua added noise errors to the derived radiances, which produced broad, flat frequency distributions of nL(sub w)(lambda) relative to those produced using the NIR bands. The SWIR approach produced an increased number of negative nL(sub w)(lambda) and decreased sample size relative to the NIR approach. Revised vicarious calibration and regional tuning of the scheme to switch between the NIR and SWIR approaches may improve retrievals in Chesapeake Bay, however, poor SNR values for the MODIS-Aqua SWIR bands remain the primary deficiency of the SWIR-based atmospheric correction approach.

Fourier analysis and signal processing by use of the Moebius inversion formula

NASA Technical Reports Server (NTRS)

Reed, Irving S.; Yu, Xiaoli; Shih, Ming-Tang; Tufts, Donald W.; Truong, T. K.

1990-01-01

A novel Fourier technique for digital signal processing is developed. This approach to Fourier analysis is based on the number-theoretic method of the Moebius inversion of series. The Fourier transform method developed is shown also to yield the convolution of two signals. A computer simulation shows that this method for finding Fourier coefficients is quite suitable for digital signal processing. It competes with the classical FFT (fast Fourier transform) approach in terms of accuracy, complexity, and speed.

ACCOUNTING FOR ERROR PROPAGATION IN THE DEVELOPMENT OF A LEAF AREA INDEX (LAI) REFERENCE MAP TO ASSESS THE MODIS LAI MODI5A LAI PRODUCT

EPA Science Inventory

The ability to effectively use remotely sensed data for environmental spatial analysis is dependent on understanding the underlying procedures and associated variances attributed to the data processing and image analysis technique. Equally important, also, is understanding the er...

Assessing the Accuracy of MODIS-NDVI Derived Land-Cover Across the Great Lakes Basin

EPA Science Inventory

This research describes the accuracy assessment process for a land-cover dataset developed for the Great Lakes Basin (GLB). This land-cover dataset was developed from the 2007 MODIS Normalized Difference Vegetation Index (NDVI) 16-day composite (MOD13Q) 250 m time-series data. Tr...

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.

Progress towards MODIS and VIIRS Cloud Fraction Data Record Continuity

NASA Astrophysics Data System (ADS)

Ackerman, S. A.; Frey, R.; Holz, R.; Platnick, S. E.; Heidinger, A. K.

2016-12-01

Satellite-derived clear-sky vs. cloudy-sky discrimination at the pixel scale is an important input parameter used in many real-time applications. Cloud fractions, resulting from integrating over time and space, are also critical to the study of recent decadal climate changes. The NASA NPOESS Preparatory Project (NPP) has funded a science team to develop and study the ability to make continuous climate records from MODIS (2000-2020) and VIIRS (2012-2030). The MODAWG project, led by Dr. Steve Platnick of NASA/GSFC, combines elements of the MODIS processing system and the NOAA Algorithm Working Group (AWG) to achieve this goal. This presentation will focus on the cloud masking aspects of MODAWG, derived primarily from the MODIS cloud mask (MOD35). Challenges to continuity of cloud detection due to differences in instrument characteristics will be discussed. Cloud mask results from use of the same (continuity) algorithm will be shown for both MODIS and VIIRS, including comparisons to collocated CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) cloud data.

Corrections to MODIS Terra Calibration and Polarization Trending Derived from Ocean Color Products

NASA Technical Reports Server (NTRS)

Meister, Gerhard; Eplee, Robert E.; Franz, Bryan A.

2014-01-01

Remotely sensed ocean color products require highly accurate top-of-atmosphere (TOA) radiances, on the order of 0.5% or better. Due to incidents both prelaunch and on-orbit, meeting this requirement has been a consistent problem for the MODIS instrument on the Terra satellite, especially in the later part of the mission. The NASA Ocean Biology Processing Group (OBPG) has developed an approach to correct the TOA radiances of MODIS Terra using spatially and temporally averaged ocean color products from other ocean color sensors (such as the SeaWiFS instrument on Orbview-2 or the MODIS instrument on the Aqua satellite). The latest results suggest that for MODIS Terra, both linear polarization parameters of the Mueller matrix are temporally evolving. A change to the functional form of the scan angle dependence improved the quality of the derived coefficients. Additionally, this paper demonstrates that simultaneously retrieving polarization and gain parameters improves the gain retrieval (versus retrieving the gain parameter only).

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.

Calculations of Aerosol Radiative Forcing in the SAFARI Region from MODIS Data

NASA Technical Reports Server (NTRS)

Remer, L. A.; Ichoku, C.; Kaufman, Y. J.; Chu, D. A.

2003-01-01

SAFARI 2000 provided the opportunity to validate MODIS aerosol retrievals and to correct any assumptions in the retrieval process. By comparing MODIS retrievals with ground-based sunphotometer data, we quantified the degree to which the MODIS algorithm underestimated the aerosol optical thickness. This discrepancy was attributed to underestimating the degree of light absorption by the southern African smoke aerosol. Correcting for this underestimation of absorption, produces more realistic aerosol retrievals that allow various applications of the MODIS aerosol products. One such application is the calculation of the aerosol radiative forcing at the top and bottom of the atmosphere. The combination of MODIS accuracy, coverage, resolution and the ability to separate fine and coarse mode make this calculation substantially advanced over previous attempts with other satellites. We focus on the oceans adjacent to southern Africa and use a solar radiative transfer model to perform the flux calculations. The forcing at the top of atmosphere is calculated to be 10 W/sq m, while the forcing at the surface is -26 W/sq m. These results resemble those calculated from INDOEX data, and are most sensitive to assumptions of aerosol absorption, the same parameter that initially interfered with our 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.

Remote Sensing Time Series Product Tool

NASA Technical Reports Server (NTRS)

Predos, Don; Ryan, Robert E.; Ross, Kenton W.

2006-01-01

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

Assessments and Applications of Terra and Aqua MODIS On-Orbit Electronic Calibration

NASA Technical Reports Server (NTRS)

Xiong, Xiaoxiong; Chen, Na; Li, Yonghong; Wilson, Truman

2016-01-01

MODIS has 36 spectral bands located on four focal plane assemblies (FPAs), covering wavelengths from 0.41 to 14.4 micrometers. MODIS bands 1-30 collect data using photovoltaic (PV) detectors and, therefore, are referred to as the PV bands. Similarly, bands 31-36 using photoconductive (PC) detectors are referred to as the PC bands.The MODIS instrument was built with a set of on-board calibrators (OBCs) in order to track on-orbit changes of its radiometric, spatial, and spectral characteristics. In addition, an electronic calibration (ECAL) function can be used to monitor on-orbit changes of its electronic responses (gains). This is accomplished via a series of stair step signals generated by the ECAL function. These signals, in place of the FPA detector signals, are amplified and digitized just like the detector signals. Over the entire mission of both Terra and Aqua MODIS,the ECAL has been performed for the PV bands and used to assess their on-orbit performance. This paper provides an overview of MODIS on-orbit calibration activities with a focus on the PV ECAL, including its calibration process and approaches used to monitor the electronic performance. It presents the results derived and lessons learned from Terra and Aqua MODIS on-orbit ECAL. Also discussed are some of the applications performed with the information provided by the ECAL data.

Downscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.

2015-01-01

The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have been used for terrestrial ecosystem modeling and monitoring. High temporal resolution with a wide range of wavelengths make the MODIS land surface products robust and reliable. The long-term 30-m Landsat data provide spatial detailed information for characterizing human-scale processes and have been used for land cover and land change studies. The main goal of this study is to combine 250-m MODIS GSN and 30-m Landsat observations to generate a quality-improved high spatial resolution (30-m) GSN database. A rule-based piecewise regression GSN model based on MODIS and Landsat data was developed. Results show a strong correlation between predicted GSN and actual GSN (r = 0.97, average error = 0.026). The most important Landsat variables in the GSN model are Normalized Difference Vegetation Indices (NDVIs) in May and August. The derived MODIS-Landsat-based 30-m GSN map provides biophysical information for moderate-scale ecological features. This multiple sensor study retains the detailed seasonal dynamic information captured by MODIS and leverages the high-resolution information from Landsat, which will be useful for regional ecosystem studies.

Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands, USA

USGS Publications Warehouse

Boyte, Stephen; Wylie, Bruce K.; Rigge, Matthew B.; Dahal, Devendra

2018-01-01

Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R2 values ranging from 0.74 to 0.85. The correlation coefficients (r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.

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.

Antarctic Temperature Extremes from MODIS Land Surface Temperatures: New Processing Methods Reveal Data Quality Puzzles

NASA Astrophysics Data System (ADS)

Grant, G.; Gallaher, D. W.

2017-12-01

New methods for processing massive remotely sensed datasets are used to evaluate Antarctic land surface temperature (LST) extremes. Data from the MODIS/Terra sensor (Collection 6) provides a twice-daily look at Antarctic LSTs over a 17 year period, at a higher spatiotemporal resolution than past studies. Using a data condensation process that creates databases of anomalous values, our processes create statistical images of Antarctic LSTs. In general, the results find few significant trends in extremes; however, they do reveal a puzzling picture of inconsistent cloud detection and possible systemic errors, perhaps due to viewing geometry. Cloud discrimination shows a distinct jump in clear-sky detections starting in 2011, and LSTs around the South Pole exhibit a circular cooling pattern, which may also be related to cloud contamination. Possible root causes are discussed. Ongoing investigations seek to determine whether the results are a natural phenomenon or, as seems likely, the results of sensor degradation or processing artefacts. If the unusual LST patterns or cloud detection discontinuities are natural, they point to new, interesting processes on the Antarctic continent. If the data artefacts are artificial, MODIS LST users should be alerted to the potential issues.

Sixteen Years of Terra MODIS On-Orbit Operation, Calibration, and Performance

NASA Technical Reports Server (NTRS)

Xiong, X.; Angal, A.; Wu, A.; Link, D.; Geng, X.; Barnes, W.; Solomonson, V.

2016-01-01

Terra MODIS has successfully operated for more than 16 years since its launch in December 1999. From its observations, many science data products have been generated in support of a broad range of research activities and remote sensing applications. Terra MODIS has operated in a number of configurations and experienced a few anomalies, including spacecraft and instrument related events. MODIS collects data in 36 spectral bands that are calibrated regularly by a set of on-board calibrators for their radiometric, spectral, and spatial performance. Periodic lunar observations and long-term radiometric trending over well-characterized ground targets are also used to support sensor on-orbit calibration. Dedicated efforts made by the MODIS Characterization Support Team (MCST) and continuing support from the MODIS Science Team have contributed to the mission success, enabling well-calibrated data products to be continuously generated and routinely delivered to users worldwide. This paper presents an overview of Terra MODIS mission operations, calibration activities, and instrument performance of the past 16 years. It illustrates and describes the results of key sensor performance parameters derived from on-orbit calibration and characterization, such as signal-to-noise ratio (SNR), noise equivalent temperature difference (NEdT), solar diffuser (SD) degradation, changes in sensor responses, center wavelengths, and band-to-band registration (BBR). Also discussed in this paper are the calibration approaches and strategies developed and implemented in support of MODIS Level 1B data production and re-processing, major challenging issues, and lessons learned. (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Remote sensing of cloud, aerosol and water vapor properties from the Moderate Resolution Imaging Spectrometer (MODIS)

NASA Technical Reports Server (NTRS)

King, M. D.

1992-01-01

The Moderate Resolution Imaging Spectrometer (MODIS) is an Earth-viewing sensor being developed as a facility instrument for the Earth Observing System (EOS) to be launched in the late 1990s. MODIS consists of two separate instruments that scan 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. Of primary interest for studies of atmospheric physics is the MODIS-N (nadir) instrument which will provide images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resoulutions 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 atmosperhic processes. The intent of this lecture is to describe the current status of MODIS-N and its companion instrument MODIS-T (tilt), a tiltable cross-track scanning radiometer with 32 uniformly spaced channels between 0.410 and 0.875 micrometers, and to describe the physical principles behind the development of MODIS for the remote sensing of atmospheric properties. Primary emphasis will be placed on the main atmospheric applications of determining the optical, microphysical and physical properties of clouds and aerosol particles form spectral-reflection and thermal-emission measurements. In addition to cloud and aerosol properties, MODIS-N will be utilized for the determination of the total precipitable water vapor over land and atmospheric stability. The physical principles behind the determination of each of these atmospheric products will be described herein.

Harmonic regression of Landsat time series for modeling attributes from national forest inventory data

NASA Astrophysics Data System (ADS)

Wilson, Barry T.; Knight, Joseph F.; McRoberts, Ronald E.

2018-03-01

Imagery from the Landsat Program has been used frequently as a source of auxiliary data for modeling land cover, as well as a variety of attributes associated with tree cover. With ready access to all scenes in the archive since 2008 due to the USGS Landsat Data Policy, new approaches to deriving such auxiliary data from dense Landsat time series are required. Several methods have previously been developed for use with finer temporal resolution imagery (e.g. AVHRR and MODIS), including image compositing and harmonic regression using Fourier series. The manuscript presents a study, using Minnesota, USA during the years 2009-2013 as the study area and timeframe. The study examined the relative predictive power of land cover models, in particular those related to tree cover, using predictor variables based solely on composite imagery versus those using estimated harmonic regression coefficients. The study used two common non-parametric modeling approaches (i.e. k-nearest neighbors and random forests) for fitting classification and regression models of multiple attributes measured on USFS Forest Inventory and Analysis plots using all available Landsat imagery for the study area and timeframe. The estimated Fourier coefficients developed by harmonic regression of tasseled cap transformation time series data were shown to be correlated with land cover, including tree cover. Regression models using estimated Fourier coefficients as predictor variables showed a two- to threefold increase in explained variance for a small set of continuous response variables, relative to comparable models using monthly image composites. Similarly, the overall accuracies of classification models using the estimated Fourier coefficients were approximately 10-20 percentage points higher than the models using the image composites, with corresponding individual class accuracies between six and 45 percentage points higher.

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.

Evaluation and comparison of gross primary production estimates for the Northern Great Plains grasslands

USGS Publications Warehouse

Zhang, Li; Wylie, Bruce K.; Loveland, Thomas R.; Fosnight, Eugene A.; Tieszen, Larry L.; Ji, Lei; Gilmanov, Tagir

2007-01-01

Two spatially-explicit estimates of gross primary production (GPP) are available for the Northern Great Plains. An empirical piecewise regression (PWR) GPP model was developed from flux tower measurements to map carbon flux across the region. The Moderate Resolution Imaging Spectrometer (MODIS) GPP model is a process-based model that uses flux tower data to calibrate its parameters. Verification and comparison of the regional PWR GPP and the global MODIS GPP are important for the modeling of grassland carbon flux. This study compared GPP estimates from PWR and MODIS models with five towers in the grasslands. Among them, PWR GPP and MODIS GPP showed a good agreement with tower-based GPP at three towers. The global MODIS GPP, however, did not agree well with tower-based GPP at two other towers, probably because of the insensitivity of MODIS model to regional ecosystem and climate change and extreme soil moisture conditions. Cross-validation indicated that the PWR model is relatively robust for predicting regional grassland GPP. However, the PWR model should include a wide variety of flux tower data as the training data sets to obtain more accurate results.In addition, GPP maps based on the PWR and MODIS models were compared for the entire region. In the northwest and south, PWR GPP was much higher than MODIS GPP. These areas were characterized by the higher water holding capacity with a lower proportion of C4 grasses in the northwest and a higher proportion of C4 grasses in the south. In the central and southeastern regions, PWR GPP was much lower than MODIS GPP under complicated conditions with generally mixed C3/C4 grasses. The analysis indicated that the global MODIS GPP model has some limitations on detecting moisture stress, which may have been caused by the facts that C3 and C4 grasses are not distinguished, water stress is driven by vapor pressure deficit (VPD) from coarse meteorological data, and MODIS land cover data are unable to differentiate the sub-pixel cropland components.

New Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. T.; King, Michael D. (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. 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 micrometers 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 I will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of cloud drops and ice crystals. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

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.

Calibration Improvements in the Detector-to-Detector Differences for the MODIS Ocean Color Bands

NASA Technical Reports Server (NTRS)

Li, Yonghong; Angal, Amit; Wu, Aisheng; Geng, Xu; Link, Daniel; Xiong, Xiaoxiong

2016-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major instrument within NASAs Earth Observation System missions, has operated for over 16 and 14 years onboard the Terra and Aqua satellites, respectively. Its reflective solar bands (RSB) covering a spectral range from 0.4 to 2.1 micrometers are primarily calibrated using the on-board solar diffuser(SD), with its on-orbit degradation monitored using the Solar Diffuser Stability Monitor. RSB calibrations are supplemented by near-monthly lunar measurements acquired from the instruments space-view port. Nine bands (bands 8-16) in the visible to near infrared spectral range from 0.412 to 0.866 micrometers are primarily used for ocean color observations.During a recent reprocessing of ocean color products, performed by the NASA Ocean Biology Processing Group, detector-to-detector differences of up to 1.5% were observed in bands 13-16 of Terra MODIS. This paper provides an overview of the current approach to characterize the MODIS detector-to-detector differences. An alternative methodology was developed to mitigate the observed impacts for bands 13-16. The results indicated an improvement in the detector residuals and in turn are expected to improve the MODIS ocean color products. This paper also discusses the limitations,subsequent enhancements, and the improvements planned for future MODIS calibration collections.

Adjustments to the MODIS Terra Radiometric Calibration and Polarization Sensitivity in the 2010 Reprocessing

NASA Technical Reports Server (NTRS)

Meister, Gerhard; Franz, Bryan A.

2011-01-01

The Moderate-Resolution Imaging Spectroradiometer (MODIS) on NASA s Earth Observing System (EOS) satellite Terra provides global coverage of top-of-atmosphere (TOA) radiances that have been successfully used for terrestrial and atmospheric research. The MODIS Terra ocean color products, however, have been compromised by an inadequate radiometric calibration at the short wavelengths. The Ocean Biology Processing Group (OBPG) at NASA has derived radiometric corrections using ocean color products from the SeaWiFS sensor as truth fields. In the R2010.0 reprocessing, these corrections have been applied to the whole mission life span of 10 years. This paper presents the corrections to the radiometric gains and to the instrument polarization sensitivity, demonstrates the improvement to the Terra ocean color products, and discusses issues that need further investigation. Although the global averages of MODIS Terra ocean color products are now in excellent agreement with those of SeaWiFS and MODIS Aqua, and image quality has been significantly improved, the large corrections applied to the radiometric calibration and polarization sensitivity require additional caution when using the data.

MOD06 Optical and Microphysical Retrievals

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Arnold, G. T.; Dinsick, J.; Gatebe, C. K.; Gray, M. A.; Hubanks, P. A.; Moody, E. G.; Wind, B.; Wind, G.

2003-01-01

Major efforts over the past six months included: (1) submission of MOD06 Optical and Microphysical Retrieval recompetition proposal, (2) delivery of a MODIS Atmosphere Level-3 update, (3) delivery of the MODIS Atmosphere s new combined Level-2 product, (4) development of an above-cloud precipitable water research algorithm and a multi-layer cloud detection algorithm, (5) continued development of a Fortran 90 version of the retrieval code for use with MAS as well as operational MODIS processing, (6) preliminary analysis of CRYSTAL-FACE field experiment in July 2002, (7) continued analysis of data obtained during the SAFARI 2000 dry season campaign in southern Africa, and the Arctic FIRE-ACE experiment.

Impact of MODIS Sensor Calibration Updates on Greenland Ice Sheet Surface Reflectance and Albedo Trends

NASA Technical Reports Server (NTRS)

Casey, Kimberly A.; Polashenski, Chris M.; Chen, Justin; Tedesco, Marco

2017-01-01

We evaluate Greenland Ice Sheet (GrIS) surface reflectance and albedo trends using the newly released Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) products over the period 2001-2016. We find that the correction of MODIS sensor degradation provided in the new C6 data products reduces the magnitude of the surface reflectance and albedo decline trends obtained from previous MODIS data (i.e., Collection 5, C5). Collection 5 and 6 data product analysis over GrIS is characterized by surface (i.e., wet vs. dry) and elevation (i.e., 500-2000 m, 2000 m and greater) conditions over the summer season from 1 June to 31 August. Notably, the visible-wavelength declining reflectance trends identified in several bands of MODIS C5 data from previous studies are only slightly detected at reduced magnitude in the C6 versions over the dry snow area. Declining albedo in the wet snow and ice area remains over the MODIS record in the C6 product, albeit at a lower magnitude than obtained using C5 data. Further analyses of C6 spectral reflectance trends show both reflectance increases and decreases in select bands and regions, suggesting that several competing processes are contributing to Greenland Ice Sheet albedo change. Investigators using MODIS data for other ocean, atmosphere and/or land analyses are urged to consider similar re-examinations of trends previously established using C5 data.

A web-based subsetting service for regional scale MODIS land products

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

SanthanaVannan, Suresh K; Cook, Robert B; Holladay, Susan K

2009-12-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor has provided valuable information on various aspects of the Earth System since March 2000. The spectral, spatial, and temporal characteristics of MODIS products have made them an important data source for analyzing key science questions relating to Earth System processes at regional, continental, and global scales. The size of the MODIS product and native HDF-EOS format are not optimal for use in field investigations at individual sites (100 - 100 km or smaller). In order to make MODIS data readily accessible for field investigations, the NASA-funded Distributed Active Archive Center (DAAC) for Biogeochemicalmore » Dynamics at Oak Ridge National Laboratory (ORNL) has developed an online system that provides MODIS land products in an easy-to-use format and in file sizes more appropriate to field research. This system provides MODIS land products data in a nonproprietary comma delimited ASCII format and in GIS compatible formats (GeoTIFF and ASCII grid). Web-based visualization tools are also available as part of this system and these tools provide a quick snapshot of the data. Quality control tools and a multitude of data delivery options are available to meet the demands of various user communities. This paper describes the important features and design goals for the system, particularly in the context of data archive and distribution for regional scale analysis. The paper also discusses the ways in which data from this system can be used for validation, data intercomparison, and modeling efforts.« less

MODIS Direct Broadcast and Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee

2004-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard both Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 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). Equipped with direct broadcast capability, the MODIS measurements can be received worldwide real time. There are 82 ingest sites (over 900 users, listed on the Direct Readout Portal) around the world for Terra/Aqua-MODIS Direct Broadcast DB) downlink. This represents 27 (6 from EOS science team members) science research organizations for DB land, ocean and atmospheric processing, and 53 companies that base their application algorithms and value added products on DB data. In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of aerosol/cloud optical properties, especially optical thickness and effective particle size. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Preliminary results will be presented and discussed their implications in regional-to-global climatic effects.

Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

NASA Technical Reports Server (NTRS)

Platnick, Steven E.

2011-01-01

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

NASA Technical Reports Server (NTRS)

McKellip, Rodney; Prados, Donald; Ryan, Robert; Ross, Kenton; Spruce, Joseph; Gasser, Gerald; Greer, Randall

2008-01-01

The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify a variety of plant phenomena and improve monitoring capabilities.

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

Comparison of C5 and C6 Aqua-MODIS Dark Target Aerosol Validation

NASA Technical Reports Server (NTRS)

Munchak, Leigh A.; Levy, Robert C.; Mattoo, Shana

2014-01-01

We compare C5 and C6 validation to compare the C6 10 km aerosol product against the well validated and trusted aerosol product on global and regional scales. Only the 10 km aerosol product is evaluated in this study, validation of the new C6 3 km aerosol product still needs to be performed. Not all of the time series has processed yet for C5 or C6, and the years processed for the 2 products is not exactly the same (this work is preliminary!). To reduce the impact of outlier observations, MODIS is spatially averaged within 27.5 km of the AERONET site, and AERONET is temporatally averaged within 30 minutes of the MODIS overpass time. Only high quality (QA = 3 over land, QA greater than 0 over ocean) pixels are included in the mean.

Daily MODIS Data Trends of Hurricane-Induced Forest Impact and Early Recovery

NASA Technical Reports Server (NTRS)

Ramsey, Elijah, III; Spruce, Joseph; Rangoonwala, Amina; Suzuoki, Yukihiro; Smoot, James; Gasser, Jerry; Bannister, Terri

2011-01-01

We studied the use of daily satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors to assess wetland forest damage and recovery from Hurricane Katrina (29 August 2005 landfall). Processed MODIS daily vegetation index (VI) trends were consistent with previously determined impact and recovery patterns provided by the "snapshot" 25 m Landsat Thematic Mapper optical and RADARSAT-1 synthetic aperture radar satellite data. Phenological trends showed high 2004 and 2005 pre-hurricane temporal correspondence within bottomland hardwood forest communities, except during spring green-up, and temporal dissimilarity between these hardwoods and nearby cypress-tupelo swamp forests (Taxodium distichum [baldcypress] and Nyssa aquatica [water tupelo]). MODIS VI trend analyses established that one year after impact, cypress-tupelo and lightly impacted hardwood forests had recovered to near prehurricane conditions. In contrast, canopy recovery lagged in the moderately and severely damaged hardwood forests, possibly reflecting regeneration of pre-hurricane species and stand-level replacement by invasive trees.

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.

Improved Snow Mapping Accuracy with Revised MODIS Snow Algorithm

NASA Technical Reports Server (NTRS)

Riggs, George; Hall, Dorothy K.

2012-01-01

The MODIS snow cover products have been used in over 225 published studies. From those reports, and our ongoing analysis, we have learned about the accuracy and errors in the snow products. Revisions have been made in the algorithms to improve the accuracy of snow cover detection in Collection 6 (C6), the next processing/reprocessing of the MODIS data archive planned to start in September 2012. Our objective in the C6 revision of the MODIS snow-cover algorithms and products is to maximize the capability to detect snow cover while minimizing snow detection errors of commission and omission. While the basic snow detection algorithm will not change, new screens will be applied to alleviate snow detection commission and omission errors, and only the fractional snow cover (FSC) will be output (the binary snow cover area (SCA) map will no longer be included).

Multi-Angle Implementation of Atmospheric Correction for MODIS (MAIAC). Part 3: Atmospheric Correction

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Laszlo, I.; Hilker, T.; Hall, F.; Sellers, P.; Tucker, J.; Korkin, S.

2012-01-01

This paper describes the atmospheric correction (AC) component of the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) which introduces a new way to compute parameters of the Ross-Thick Li-Sparse (RTLS) Bi-directional reflectance distribution function (BRDF), spectral surface albedo and bidirectional reflectance factors (BRF) from satellite measurements obtained by the Moderate Resolution Imaging Spectroradiometer (MODIS). MAIAC uses a time series and spatial analysis for cloud detection, aerosol retrievals and atmospheric correction. It implements a moving window of up to 16 days of MODIS data gridded to 1 km resolution in a selected projection. The RTLS parameters are computed directly by fitting the cloud-free MODIS top of atmosphere (TOA) reflectance data stored in the processing queue. The RTLS retrieval is applied when the land surface is stable or changes slowly. In case of rapid or large magnitude change (as for instance caused by disturbance), MAIAC follows the MODIS operational BRDF/albedo algorithm and uses a scaling approach where the BRDF shape is assumed stable but its magnitude is adjusted based on the latest single measurement. To assess the stability of the surface, MAIAC features a change detection algorithm which analyzes relative change of reflectance in the Red and NIR bands during the accumulation period. To adjust for the reflectance variability with the sun-observer geometry and allow comparison among different days (view geometries), the BRFs are normalized to the fixed view geometry using the RTLS model. An empirical analysis of MODIS data suggests that the RTLS inversion remains robust when the relative change of geometry-normalized reflectance stays below 15%. This first of two papers introduces the algorithm, a second, companion paper illustrates its potential by analyzing MODIS data over a tropical rainforest and assessing errors and uncertainties of MAIAC compared to conventional MODIS products.

Contribution of National near Real Time MODIS Forest Maximum Percentage NDVI Change Products to the U.S. ForWarn System

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hargrove, William; Gasser, Gerald; Smoot, James; Kuper, Philip D.

2012-01-01

This presentation reviews the development, integration, and testing of Near Real Time (NRT) MODIS forest % maximum NDVI change products resident to the USDA Forest Service (USFS) ForWarn System. ForWarn is an Early Warning System (EWS) tool for detection and tracking of regionally evident forest change, which includes the U.S. Forest Change Assessment Viewer (FCAV) (a publically available on-line geospatial data viewer for visualizing and assessing the context of this apparent forest change). NASA Stennis Space Center (SSC) is working collaboratively with the USFS, ORNL, and USGS to contribute MODIS forest change products to ForWarn. These change products compare current NDVI derived from expedited eMODIS data, to historical NDVI products derived from MODIS MOD13 data. A new suite of forest change products are computed every 8 days and posted to the ForWarn system; this includes three different forest change products computed using three different historical baselines: 1) previous year; 2) previous three years; and 3) all previous years in the MODIS record going back to 2000. The change product inputs are maximum value NDVI that are composited across a 24 day interval and refreshed every 8 days so that resulting images for the conterminous U.S. are predominantly cloud-free yet still retain temporally relevant fresh information on changes in forest canopy greenness. These forest change products are computed at the native nominal resolution of the input reflectance bands at 231.66 meters, which equates to approx 5.4 hectares or 13.3 acres per pixel. The Time Series Product Tool, a MATLAB-based software package developed at NASA SSC, is used to temporally process, fuse, reduce noise, interpolate data voids, and re-aggregate the historical NDVI into 24 day composites, and then custom MATLAB scripts are used to temporally process the eMODIS NDVIs so that they are in synch with the historical NDVI products. Prior to posting, an in-house snow mask classification product is computed for the current compositing period and integrated into the change images to account for snow related NDVI drops. The supplemental snow classification product was needed because other available QA cloud/snow mask typically underestimates snow cover. MODIS true and false color composites were also computed from eMODIS reflectance data and the true color RGBs are also posted on ForWarn?s FCAV; this data is used for assessing apparent occasional quality issues on the change products due to residual unmasked cloud cover. New forest change products are posted with typical latencies of 1-2 days after the last input eMODIS data collection date for a given 24 day compositing period.

Monitoring 2009 Forest Disturbance across the Conterminous United States, Based on Near-Real Time and Historical MODIS 250 Meter NDVI Products

NASA Astrophysics Data System (ADS)

Spruce, J.; Hargrove, W. W.; Gasser, G.; Smoot, J. C.; Kuper, P.

2009-12-01

This presentation discusses a study on the use of MODIS NDVI data for viewing regional patterns of forest disturbance across the conterminous United States. This capability is a part of a national forest threat early warning system (EWS) being developed by the USDA Forest Service’s Eastern and Western Environmental Threat Centers with help from NASA Stennis Space Center and the Oak Ridge National Laboratory. The viewing capability of the EWS was recently demonstrated for 2009, using near-real time (NRT) MODIS NDVI data from the USGS eMODIS Web site and historical NDVI data from standard MOD13 products. For this study, a historical maximum NDVI baseline for CONUS was computed from fused Aqua and Terra MOD13 data for June 10-July 27 of each year during 2000-2006. Comparable 2009 MODIS NDVI imagery was computed from fusion and re-compositing of eMODIS NRT Aqua and Terra 7-day products. For the historical data, time series data processing software was used to remove poor quality data and to mitigate data gaps mainly due to clouds. Although the NRT component was not as rigorously processed to mitigate noise, the processing still yielded largely cloud-free clean, coherent CONUS NDVI imagery initially with only 21-days of compositing. The principal end product of the study was a forest disturbance visualization product based on an NDVI RGB image that combines data from 2 dates (i.e. time frames). For this RGB, the historical maximum NDVI for the observed temporal window was assigned to the red color gun and the 2009 NRT product for the same time frame was assigned to the blue and green guns. The resulting image was masked with a USFS FIA 250-m type map to include only forested areas. The forest disturbance areas on the forest-masked 2-date NDVI RGB are shown in red tones with non-disturbed closed canopy forest generally shown in medium to bright gray tones. This product highlighted several broad-scaled forest canopy disturbances for the observed time in 2009, including damage from caterpillars, bark beetles, ice storms, hail and wind storms, and wildfire. The MODIS forest disturbance products compared well with reference data (e.g., Landsat, aerial sketch maps, and news accounts). These products have been useful in aiding development of the forest threat EWS. Information on location and extent of regional forest disturbance is important to Federal, State, and private sector forest managers. The 2-date RGB product for 2009 was also processed into a classification of forest disturbance for the Colorado Front Range. Validation of this classification is underway. Regional forest disturbance classifications in conjunction with available CONUS forest biomass products could be useful for assessing carbon impacts from biotic threats such as mountain pine beetle and from abiotic threats related to climate change. The latency of the NRT eMODIS products addresses an important need of the USFS EWS.

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.

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.

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

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.

Extending MODIS Cloud Top and Infrared Phase Climate Records with VIIRS and CrIS

NASA Astrophysics Data System (ADS)

Heidinger, A. K.; Platnick, S. E.; Ackerman, S. A.; Holz, R.; Meyer, K.; Frey, R.; Wind, G.; Li, Y.; Botambekov, D.

2015-12-01

The MODIS imagers on the NASA EOS Terra and Aqua satellites have generated accurate and well-used cloud climate data records for 15 years. Both missions are expected to continue until the end of this decade and perhaps beyond. The Visible and Infrared Imaging Radiometer Suite (VIIRS) imagers on the Suomi-NPP (SNPP) mission (launched in October 2011) and future NOAA Joint Polar Satellite System (JPSS) platforms are the successors for imager-based cloud climate records from polar orbiting satellites after MODIS. To ensure product continuity across a broad suite of EOS products, NASA has funded a SNPP science team to develop EOS-like algorithms that can be use with SNPP and JPSS observations, including two teams to work on cloud products. Cloud data record continuity between MODIS and VIIRS is particularly challenging due to the lack of VIIRS CO2-slicing channels, which reduces information content for cloud detection and cloud-top property products, as well as down-stream cloud optical products that rely on both. Here we report on our approach to providing continuity specifically for the MODIS/VIIRS cloud-top and infrared-derived thermodynamic phase products by combining elements of the NASA MODIS science team (MOD) and the NOAA Algorithm Working Group (AWG) algorithms. The combined approach is referred to as the MODAWG processing package. In collaboration with the NASA Atmospheric SIPS located at the University of Wisconsin Space Science and Engineering Center, the MODAWG code has been exercised on one year of SNPP VIIRS data. In addition to cloud-top and phase, MODAWG provides a full suite of cloud products that are physically consistent with MODIS and have a similar data format. Further, the SIPS has developed tools to allow use of Cross-track Infrared Sounder (CrIS) observations in the MODAWG processing that can ameliorate the loss of the CO2 absorption channels on VIIRS. Examples will be given that demonstrate the positive impact that the CrIS data can provide when combined with VIIRS for cloud height and IR-phase retrievals.

Calipso's Mission Design: Sun-Glint Avoidance Strategies

NASA Technical Reports Server (NTRS)

Mailhe, Laurie M.; Schiff, Conrad; Stadler, John H.

2004-01-01

CALIPSO will fly in formation with the Aqua spacecraft to obtain a coincident image of a portion of the Aqua/MODIS swath. Since MODIS pixels suffering sun-glint degradation are not processed, it is essential that CALIPSO only co- image the glint h e portion of the MODIS instrument swath. This paper presents sun-glint avoidance strategies for the CALIPSO mission. First, we introduce the Aqua sun-glint geometry and its relation to the CALIPSO-Aqua formation flying parameters. Then, we detail our implementation of the computation and perform a cross-track trade-space analysis. Finally, we analyze the impact of the sun-glint avoidance strategy on the spacecraft power and delta-V budget over the mission lifetime.

Rice Crop Monitoring and Yield Assessment with MODIS 250m Gridded Vegetation Products: A Case Study of Sa Kaeo Province, Thailand

NASA Astrophysics Data System (ADS)

Wijesingha, J. S. J.; Deshapriya, N. L.; Samarakoon, L.

2015-04-01

Billions of people in the world depend on rice as a staple food and as an income-generating crop. Asia is the leader in rice cultivation and it is necessary to maintain an up-to-date rice-related database to ensure food security as well as economic development. This study investigates general applicability of high temporal resolution Moderate Resolution Imaging Spectroradiometer (MODIS) 250m gridded vegetation product for monitoring rice crop growth, mapping rice crop acreage and analyzing crop yield, at the province-level. The MODIS 250m Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) time series data, field data and crop calendar information were utilized in this research in Sa Kaeo Province, Thailand. The following methodology was used: (1) data pre-processing and rice plant growth analysis using Vegetation Indices (VI) (2) extraction of rice acreage and start-of-season dates from VI time series data (3) accuracy assessment, and (4) yield analysis with MODIS VI. The results show a direct relationship between rice plant height and MODIS VI. The crop calendar information and the smoothed NDVI time series with Whittaker Smoother gave high rice acreage estimation (with 86% area accuracy and 75% classification accuracy). Point level yield analysis showed that the MODIS EVI is highly correlated with rice yield and yield prediction using maximum EVI in the rice cycle predicted yield with an average prediction error 4.2%. This study shows the immense potential of MODIS gridded vegetation product for keeping an up-to-date Geographic Information System of rice cultivation.

Application and Evaluation of MODIS LAI, FPAR, and Albedo ...

EPA Pesticide Factsheets

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 temperature and reduced bias and error for 2-m mixing ratio. Recently, the WRF/CMAQ land surface and boundary laywer processes have been updated. In this study, MODIS vegetation and albedo data are input to the updated WRF/CMAQ meteorology and air quality simulations for 2006 over a North American (NA) 12-km domain. The evaluation of the simulation results shows that the updated WRF/CMAQ system improves 2-m temperature estimates over the pre-update base modeling system estimates. The MODIS vegetation input produces a realistic spring green-up that progresses through time from the south to north. Overall, MODIS input reduces 2-m mixing ration bias during the growing season. The NA west shows larger positive O3 bias during the growing season because of reduced gas phase deposition resulting from lower O3 deposition velocities driven by reduced vegetation cover. The O3 bias increase associated with the realistic vegetation representation indicates that further improvement may be needed in the WRF/CMAQ system. The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment. AMAD’s rese

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

MODIS. Volume 2: MODIS level 1 geolocation, characterization and calibration algorithm theoretical basis document, version 1

NASA Technical Reports Server (NTRS)

Barker, John L.; Harnden, Joann M. K.; Montgomery, Harry; Anuta, Paul; Kvaran, Geir; Knight, ED; Bryant, Tom; Mckay, AL; Smid, Jon; Knowles, Dan, Jr.

1994-01-01

The EOS Moderate Resolution Imaging Spectrometer (MODIS) is being developed by NASA for flight on the Earth Observing System (EOS) series of satellites, the first of which (EOS-AM-1) is scheduled for launch in 1998. This document describes the algorithms and their theoretical basis for the MODIS Level 1B characterization, calibration, and geolocation algorithms which must produce radiometrically, spectrally, and spatially calibrated data with sufficient accuracy so that Global change research programs can detect minute changes in biogeophysical parameters. The document first describes the geolocation algorithm which determines geodetic latitude, longitude, and elevation of each MODIS pixel and the determination of geometric parameters for each observation (satellite zenith angle, satellite azimuth, range to the satellite, solar zenith angle, and solar azimuth). Next, the utilization of the MODIS onboard calibration sources, which consist of the Spectroradiometric Calibration Assembly (SRCA), Solar Diffuser (SD), Solar Diffuser Stability Monitor (SDSM), and the Blackbody (BB), is treated. Characterization of these sources and integration of measurements into the calibration process is described. Finally, the use of external sources, including the Moon, instrumented sites on the Earth (called vicarious calibration), and unsupervised normalization sites having invariant reflectance and emissive properties is treated. Finally, algorithms for generating utility masks needed for scene-based calibration are discussed. Eight appendices are provided, covering instrument design and additional algorithm details.

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.;

Hyperbolic Cross Truncations for Stochastic Fourier Cosine Series

PubMed Central

Zhang, Zhihua

2014-01-01

Based on our decomposition of stochastic processes and our asymptotic representations of Fourier cosine coefficients, we deduce an asymptotic formula of approximation errors of hyperbolic cross truncations for bivariate stochastic Fourier cosine series. Moreover we propose a kind of Fourier cosine expansions with polynomials factors such that the corresponding Fourier cosine coefficients decay very fast. Although our research is in the setting of stochastic processes, our results are also new for deterministic functions. PMID:25147842

Measurement Comparisons Towards Improving the Understanding of Aerosol-Cloud Processing

NASA Astrophysics Data System (ADS)

Noble, Stephen R.

Cloud processing of aerosol is an aerosol-cloud interaction that is not heavily researched but could have implications on climate. The three types of cloud processing are chemical processing, collision and coalescence processing, and Brownian capture of interstitial particles. All types improve cloud condensation nuclei (CCN) in size or hygroscopicity (kappa). These improved CCN affect subsequent clouds. This dissertation focuses on measurement comparisons to improve our observations and understanding of aerosol-cloud processing. Particle size distributions measured at the continental Southern Great Plains (SGP) site were compared with ground based measurements of cloud fraction (CF) and cloud base altitude (CBA). Particle size distributions were described by a new objective shape parameter to define bimodality rather than an old subjective one. Cloudy conditions at SGP were found to be correlated with lagged shape parameter. Horizontal wind speed and regional CF explained 42%+ of this lag time. Many of these surface particle size distributions were influenced by aerosol-cloud processing. Thus, cloud processing may be more widespread with more implications than previously thought. Particle size distributions measured during two aircraft field campaigns (MArine Stratus/stratocumulus Experiment; MASE; and Ice in Cloud Experiment-Tropical; ICE-T) were compared to CCN distributions. Tuning particle size to critical supersaturation revealed hygroscopicity expressed as ? when the distributions were overlain. Distributions near cumulus clouds (ICE-T) had a higher frequency of the same ?s (48% in ICE-T to 42% in MASE) between the accumulation (processed) and Aitken (unprocessed) modes. This suggested physical processing domination in ICE-T. More MASE (stratus cloud) kappa differences between modes pointed to chemical cloud processing. Chemistry measurements made in MASE showed increases in sulfates and nitrates with distributions that were more processed. This supported chemical cloud processing in MASE. This new method to determine kappa provides the needed information without interrupting ambient measurements. MODIS derived cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (re) were compared to the same in situ derived variables from cloud probe measurements of two stratus/stratocumulus cloud campaigns (MASE and Physics Of Stratocumulus Tops; POST). In situ data were from complete vertical cloud penetrations, while MODIS data were from pixels along the aircraft penetration path. Comparisons were well correlated except that MODIS LWP (14-36%) and re (20-30%) were biased high. The LWP bias was from re bias and was not improved by using the vertically stratified assumption. MODIS re bias was almost removed when compared to cloud top maximum in situ re, but, that does not describe re for the full depth of the cloud. COT is validated by in situ COT. High correlations suggest that MODIS variables are useful in self-comparisons such as gradient changes in stratus cloud re during aerosol-cloud processing.

Operational Observation of Australian Bioregions with Bands 8-19 of Modis

NASA Astrophysics Data System (ADS)

McAtee, B. K.; Gray, M.; Broomhall, M.; Lynch, M.; Fearns, P.

2012-07-01

Data from bands 1-7 are the most common bands of the MODIS instrument used for near-real time terrestrial earth observation operations in Australia. However, many of Australia's bioregions present unique scenarios which constitute a challenge for quantitative environmental remote sensing. We believe that data from MODIS bands 8-19 may provide significant benefit to Earth observation over particular bioregions of the Australian continent. Examples here include the use of band 8 in characterising aerosol optical depth over typically bright land surfaces and accounting for anomalous retrievals of atmospheric water vapour obtained using MOD05 based on the abundance of Australia's 'red dirt', which exhibits absorption features in the near infrared bands 17-19 of MODIS. Bioregion-focused applications such as those mentioned above have driven the development of automated processing, infrastructure for the atmospheric and BRDF correction of the first 19 bands of MODIS rather than only the first 7, which is more often the case. This work has been facilitated by the AusCover project which is the remote sensing component of the Terrestrial Ecosystem Research Network (TERN), itself a program designed to create a new generation of infrastructure for ecological study of the Australian landscape.

Improved estimates of net primary productivity from MODIS satellite data at regional and local scales

Treesearch

Yude Pan; Richard Birdsey; John Hom; Kevin McCullough; Kenneth Clark

2006-01-01

We compared estimates of net primary production (NPP) from the MODIS satellite with estimates from a forest ecosystem process model (PnET-CN) and forest inventory and analysis (FIA) data for forest types of the mid-Atlantic region of the United States. The regional means were similar for the three methods and for the dominant oak? hickory forests in the region. However...

MODIS NDVI Change Detection Techniques and Products Used in the Near Real Time ForWarn System for Detecting, Monitoring, and Analyzing Regional Forest Disturbances

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hargrove, William; Gasser, Jerry; Smoot, James; Kuper, Philip D.

2014-01-01

This presentation discusses MODIS NDVI change detection methods and products used in the ForWarn Early Warning System (EWS) for near real time (NRT) recognition and tracking of regionally evident forest disturbances throughout the conterminous US (CONUS). The latter has provided NRT forest change products to the forest health protection community since 2010, using temporally processed MODIS Aqua and Terra NDVI time series data to currently compute and post 6 different forest change products for CONUS every 8 days. Multiple change products are required to improve detectability and to more fully assess the nature of apparent disturbances. Each type of forest change product reports per pixel percent change in NDVI for a given 24 day interval, comparing current versus a given historical baseline NDVI. EMODIS 7 day expedited MODIS MOD13 data are used to obtain current and historical NDVIs, respectively. Historical NDVI data is processed with Time Series Product Tool (TSPT); and 2) the Phenological Parameters Estimation Tool (PPET) software. While each change products employ maximum value compositing (MVC) of NDVI, the design of specific products primarily differs in terms of the historical baseline. The three main change products use either 1, 3, or all previous years of MVC NDVI as a baseline. Another product uses an Adaptive Length Compositing (ALC) version of MVC to derive an alternative current NDVI that is the freshest quality NDVI as opposed to merely the MVC NDVI across a 24 day time frame. The ALC approach can improve detection speed by 8 to 16 days. ForWarn also includes 2 change products that improve detectability of forest disturbances in lieu of climatic fluctuations, especially in the spring and fall. One compares current MVC NDVI to the zonal maximum under the curve NDVI per pheno-region cluster class, considering all previous years in the MODIS record. The other compares current maximum NDVI to the mean of maximum NDVI for all previous MODIS years.

Potential of VIIRS Data for Regional Monitoring of Gypsy Moth Defoliation: Implications for Forest Threat Early Warning System

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Ryan, Robert E.; Smoot, James C.; Prados, Donald; McKellip, Rodney; Sader. Steven A.; Gasser, Jerry; May, George; Hargrove, William

2007-01-01

A NASA RPC (Rapid Prototyping Capability) experiment was conducted to assess the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) data for monitoring non-native gypsy moth (Lymantria dispar) defoliation of forests. This experiment compares defoliation detection products computed from simulated VIIRS and from MODIS (Moderate Resolution Imaging Spectroradiometer) time series products as potential inputs to a forest threat EWS (Early Warning System) being developed for the USFS (USDA Forest Service). Gypsy moth causes extensive defoliation of broadleaved forests in the United States and is specifically identified in the Healthy Forest Restoration Act (HFRA) of 2003. The HFRA mandates development of a national forest threat EWS. This system is being built by the USFS and NASA is aiding integration of needed satellite data products into this system, including MODIS products. This RPC experiment enabled the MODIS follow-on, VIIRS, to be evaluated as a data source for EWS forest monitoring products. The experiment included 1) assessment of MODIS-simulated VIIRS NDVI products, and 2) evaluation of gypsy moth defoliation mapping products from MODIS-simulated VIIRS and from MODIS NDVI time series data. This experiment employed MODIS data collected over the approximately 15 million acre mid-Appalachian Highlands during the annual peak defoliation time frame (approximately June 10 through July 27) during 2000-2006. NASA Stennis Application Research Toolbox software was used to produce MODIS-simulated VIIRS data and NASA Stennis Time Series Product Tool software was employed to process MODIS and MODIS-simulated VIIRS time series data scaled to planetary reflectance. MODIS-simulated VIIRS data was assessed through comparison to Hyperion-simulated VIIRS data using data collected during gypsy moth defoliation. Hyperion-simulated MODIS data showed a high correlation with actual MODIS data (NDVI R2 of 0.877 and RMSE of 0.023). MODIS-simulated VIIRS data for the same date showed moderately high correlation with Hyperion-simulated VIIRS data (NDVI R2 of 0.62 and RMSE of 0.035), even though the datasets were collected about a half an hour apart during changing weather conditions. MODIS products (MOD02, MOD09, and MOD13) and MOD02-simulated VIIRS time series data were used to generate defoliation mapping products based on image classification and image differencing change detection techniques. Accuracy of final defoliation mapping products was assessed by image interpreting over 170 randomly sampled locations found on Landsat and ASTER data in conjunction with defoliation map data from the USFS. The MOD02-simulated VIIRS 400-meter NDVI classification produced a similar overall accuracy (87.28 percent with 0.72 Kappa) to the MOD02 250-meter NDVI classification (86.71 percent with 0.71 Kappa). In addition, the VIIRS 400-meter NDVI, MOD02 250-meter NDVI, and MOD02 500-meter NDVI showed good user and producer accuracies for the defoliated forest class (70 percent) and acceptable Kappa values (0.66). MOD02 and MOD02-simulated VIIRS data both showed promise as data sources for regional monitoring of forest disturbance due to insect defoliation.

Daily MODIS data trends of hurricane-induced forest impact and early recovery

USGS Publications Warehouse

Ramsey, Elijah W.; Spruce, Joseph; Rangoonwala, Amina; Suzuoki, Yukihiro; Smoot, James; Gasser, Jerry; Bannister, Terri

2011-01-01

We studied the use of daily satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors to assess wetland forest damage and recovery from Hurricane Katrina (29 August 2005 landfall). Processed MODIS daily vegetation index (VI) trends were consistent with previously determined impact and recovery patterns provided by the "snapshot" 25 m Landsat Thematic Mapper optical and RADARSAT-1 synthetic aperture radar satellite data. Phenological trends showed high 2004 and 2005 pre-hurricane temporal correspondence within bottomland hardwood forest communities, except during spring green-up, and temporal dissimilarity between these hardwoods and nearby cypress-tupelo swamp forests (Taxodium distichum [baldcypress] and Nyssa aquatica [water tupelo]). MODIS VI trend analyses established that one year after impact, cypress-tupelo and lightly impacted hardwood forests had recovered to near pre-hurricane conditions. In contrast, canopy recovery lagged in the moderately and severely damaged hardwood forests, possibly reflecting regeneration of pre-hurricane species and stand-level replacement by invasive trees.

Comparison of the MODIS Collection 5 Multilayer Cloud Detection Product with CALIPSO

NASA Technical Reports Server (NTRS)

Platnick, Steven; Wind, Gala; King, Michael D.; Holz, Robert E.; Ackerman, Steven A.; Nagle, Fred W.

2010-01-01

CALIPSO, launched in June 2006, provides global active remote sensing measurements of clouds and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the Aqua spacecraft and other A-Train platforms. The most recent processing effort for the MODIS Atmosphere Team, referred to as the Collection 5 scream, includes a research-level multilayer cloud detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D cloud models used in the MODIS cloud optical and microphysical product retrieval, which are generated at a 1 km resolution. Using pixel-level collocations of MODIS Aqua, CALIOP, we investigate the global performance of multilayer cloud detection algorithms (and thermodynamic phase).

Contribution of Modis Satellite Image to Estimate the Daily Air Temperature in the Casablanca City, Morocco

NASA Astrophysics Data System (ADS)

Bahi, Hicham; Rhinane, Hassan; Bensalmia, Ahmed

2016-10-01

Air temperature is considered to be an essential variable for the study and analysis of meteorological regimes and chronics. However, the implementation of a daily monitoring of this variable is very difficult to achieve. It requires sufficient of measurements stations density, meteorological parks and favourable logistics. The present work aims to establish relationship between day and night land surface temperatures from MODIS data and the daily measurements of air temperature acquired between [2011-20112] and provided by the Department of National Meteorology [DMN] of Casablanca, Morocco. The results of the statistical analysis show significant interdependence during night observations with correlation coefficient of R2=0.921 and Root Mean Square Error RMSE=1.503 for Tmin while the physical magnitude estimated from daytime MODIS observation shows a relatively coarse error with R2=0.775 and RMSE=2.037 for Tmax. A method based on Gaussian process regression was applied to compute the spatial distribution of air temperature from MODIS throughout the city of Casablanca.

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.

A Comparison of MODIS and DOAS Sulfur Dioxide Measurements of the April 24, 2004 Eruption of Anatahan Volcano, Mariana Islands

NASA Astrophysics Data System (ADS)

Meier, V. L.; Scuderi, L.; Fischer, T.; Realmuto, V.; Hilton, D.

2006-12-01

Measurements of volcanic SO2 emissions provide insight into the processes working below a volcano, which can presage volcanic events. Being able to measure SO2 in near real-time is invaluable for the planning and response of hazard mitigation teams. Currently, there are several methods used to quantify the SO2 output of degassing volcanoes. Ground and aerial-based measurements using the differential optical absorption spectrometer (mini-DOAS) provide real-time estimates of SO2 output. Satellite-based measurements, which can provide similar estimates in near real-time, have increasingly been used as a tool for volcanic monitoring. Direct Broadcast (DB) real-time processing of remotely sensed data from NASA's Earth Observing System (EOS) satellites (MODIS Terra and Aqua) presents volcanologists with a range of spectral bands and processing options for the study of volcanic emissions. While the spatial resolution of MODIS is 1 km in the Very Near Infrared (VNIR) and Thermal Infrared (TIR), a high temporal resolution and a wide range of radiance measurements in 32 channels between VNIR and TIR combine to provide a versatile space borne platform to monitor SO2 emissions from volcanoes. An important question remaining to be answered is how well do MODIS SO2 estimates compare with DOAS estimates? In 2004 ground-based plume measurements were collected on April 24th and 25th at Anatahan volcano in the Mariana Islands using a mini-DOAS (Fischer and Hilton). SO2 measurements for these same dates have also been calculated using MODIS images and SO2 mapping software (Realmuto). A comparison of these different approaches to the measurement of SO2 for the same plume is presented. Differences in these observations are used to better quantify SO2 emissions, to assess the current mismatch between ground based and remotely sensed retrievals, and to develop an approach to continuously and accurately monitor volcanic activity from space in near real-time.

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.

Effect of MODIS Terra Radiometric Calibration Improvements on Collection 6 Deep Blue Aerosol Products: Validation and Terra/Aqua Consistency

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Jeong, M.-J.; Meister, G.

2015-01-01

The Deep Blue (DB) algorithm's primary data product is midvisible aerosol optical depth (AOD). DB applied to Moderate Resolution Imaging Spectroradiometer (MODIS) measurements provides a data record since early 2000 for MODIS Terra and mid-2002 for MODIS Aqua. In the previous data version (Collection 5, C5), DB production from Terra was halted in 2007 due to sensor degradation; the new Collection 6 (C6) has both improved science algorithms and sensor radiometric calibration. This includes additional calibration corrections developed by the Ocean Biology Processing Group to address MODIS Terra's gain, polarization sensitivity, and detector response versus scan angle, meaning DB can now be applied to the whole Terra record. Through validation with Aerosol Robotic Network (AERONET) data, it is shown that the C6 DB Terra AOD quality is stable throughout the mission to date. Compared to the C5 calibration, in recent years the RMS error compared to AERONET is smaller by approximately 0.04 over bright (e.g., desert) and approximately 0.01-0.02 over darker (e.g., vegetated) land surfaces, and the fraction of points in agreement with AERONET within expected retrieval uncertainty higher by approximately 10% and approximately 5%, respectively. Comparisons to the Aqua C6 time series reveal a high level of correspondence between the two MODIS DB data records, with a small positive (Terra-Aqua) average AOD offset <0.01. The analysis demonstrates both the efficacy of the new radiometric calibration efforts and that the C6 MODIS Terra DB AOD data remain stable (to better than 0.01 AOD) throughout the mission to date, suitable for quantitative scientific analyses.

Remote Sensing of the Radiative and Microphysical Properties of Clouds during TC4: Results from MAS, MASTER, MODIS, and MISR

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Wind, Galina; Arnold, George T.; Ackerman, Steven A.; Frey, Richard

2007-01-01

The MODIS Airborne Simulator (MAS) and MODIS/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 14.3 (12.9 m for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Clouds and Climate Coupling Experiment (TC4) conducted over Central America and surrounding Pacific and Atlantic Oceans between July 17 and August 8, 2007. Multispectral images in eight 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 this cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). Finally, 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 as 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 date in TC4, 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 used three distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to MISR data to infer the cloud optical thickness of liquid water clouds from MISR. Results of this analysis will be presented and discussed.

Investigation of cloud properties and atmospheric stability with MODIS

NASA Technical Reports Server (NTRS)

Menzel, P.; Ackerman, S.; Moeller, C.; Gumley, L.; Strabala, K.; Frey, R.; Prins, E.; LaPorte, D.; Lynch, M.

1996-01-01

The last half year was spent in preparing Version 1 software for delivery, and culminated in transfer of the Level 2 cloud mask production software to the SDST in April. A simulated MODIS test data set with good radiometric integrity was produced using MAS data for a clear ocean scene. ER-2 flight support and MAS data processing were provided by CIMSS personnel during the Apr-May 96 SUCCESS field campaign in Salina, Kansas. Improvements have been made in the absolute calibration of the MAS, including better characterization of the spectral response for all 50 channels. Plans were laid out for validating and testing the MODIS calibration techniques; these plans were further refined during a UW calibration meeting with MCST.

Unified Aerosol Microphysics for NWP

DTIC Science & Technology

2013-09-30

it may be treated as a generic variable such as when it is processed by advection, or it may be used specifically like dust in ice nucleation...interactions. We shifted instead to a winter-time passage of a low pressure system across North Africa and the Mediterranean Sea (Figure 1). The strong...MODIS multispectral albedo data, MODIS land surface data, and the NRL DSD for SW Asia and E Asia a multi-variate, non-linear classification was

MODIS Cloud Microphysics Product (MOD_PR06OD) Data Collection 6 Updates

NASA Technical Reports Server (NTRS)

Wind, Gala; Platnick, Steven; King, Michael D.

2014-01-01

The MODIS Cloud Optical and Microphysical Product (MOD_PR060D) for Data Collection 6 has entered full scale production. Aqua reprocessing is almost completed and Terra reprocessing will begin shortly. Unlike previous collections, the CHIMAERA code base allows for simultaneous processing for multiple sensors and the operational CHIMAERA 6.0.76 stream is also available for VIIRS and SEVIRI sensors and for our E-MAS airborne platform.

Extending 'Deep Blue' aerosol retrieval coverage to cases of absorbing aerosols above clouds: sensitivity analysis and first case studies

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

Sayer, Andrew M.; Hsu, C.; Bettenhausen, Corey

Cases of absorbing aerosols above clouds (AAC), such as smoke or mineral dust, are omitted from most routinely-processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar

Improvement of Operational Streamflow Prediction with MODIS-derived Fractional Snow Covered Area Observations

NASA Astrophysics Data System (ADS)

Bender, S.; Burgess, A.; Goodale, C. E.; Mattmann, C. A.; Miller, W. P.; Painter, T. H.; Rittger, K. E.; Stokes, M.; Werner, K.

2013-12-01

Water managers in the western United States depend heavily on the timing and magnitude of snowmelt-driven runoff for municipal supply, irrigation, maintenance of environmental flows, and power generation. The Colorado Basin River Forecast Center (CBRFC) of the National Weather Service issues operational forecasts of snowmelt-driven streamflow for watersheds within the Colorado River Basin (CRB) and eastern Great Basin (EGB), across a wide variety of scales. Therefore, the CBRFC and its stakeholders consider snowpack observations to be highly valuable. Observations of fractional snow covered area (fSCA) from satellite-borne instrumentation can better inform both forecasters and water users with respect to subsequent snowmelt runoff, particularly when combined with observations from ground-based station networks and/or airborne platforms. As part of a multi-year collaborative effort, CBRFC has partnered with the Jet Propulsion Laboratory (JPL) under funding from NASA to incorporate observations of fSCA from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) into the operational CBRFC hydrologic forecasting and modeling process. In the first year of the collaboration, CBRFC and NASA/JPL integrated snow products into the forecasting and decision making processes of the CBRFC and showed preliminary improvement in operational streamflow forecasts. In late 2012, CBRFC and NASA/JPL began retrospective analysis of relationships between the MODIS Snow Covered Area and Grain size (MODSCAG) fSCA and streamflow patterns for several watersheds within the CRB and the EGB. During the 2013 snowmelt runoff season, CBRFC forecasters used MODIS-derived fSCA semi-quantitatively as a binary indicator of the presence or lack of snow. Indication of the presence or lack of snow by MODIS assisted CBRFC forecasters in determining the cause of divergence between modeled and recently observed streamflow. Several examples of improved forecasts from across the CRB and EGB, informed by MODIS-derived fSCA, are described. Our analysis shows the value of MODIS fSCA to CBRFC and to users of CBRFC's streamflow forecasts. The relationships between the MODIS fSCA and the melt season streamflow vary with the magnitude of runoff, which is important to resource managers. The analysis also emphasizes the importance of the invaluable collaboration between an operational forecasting agency (CBRFC) and a research-oriented agency (NASA/JPL) specializing in remote sensing science. The collaboration is expected to continue over the next several years as CBRFC and JPL work to further improve modeling of snowmelt and prediction of snowmelt-driven streamflow in the CRB and EGB.

Cloud vertical profiles derived from CALIPSO and CloudSat and a comparison with MODIS derived clouds

NASA Astrophysics Data System (ADS)

Kato, S.; Sun-Mack, S.; Miller, W. F.; Rose, F. G.; Minnis, P.; Wielicki, B. A.; Winker, D. M.; Stephens, G. L.; Charlock, T. P.; Collins, W. D.; Loeb, N. G.; Stackhouse, P. W.; Xu, K.

2008-05-01

CALIPSO and CloudSat from the a-train provide detailed information of vertical distribution of clouds and aerosols. The vertical distribution of cloud occurrence is derived from one month of CALIPSO and CloudSat data as a part of the effort of merging CALIPSO, CloudSat and MODIS with CERES data. This newly derived cloud profile is compared with the distribution of cloud top height derived from MODIS on Aqua from cloud algorithms used in the CERES project. The cloud base from MODIS is also estimated using an empirical formula based on the cloud top height and optical thickness, which is used in CERES processes. While MODIS detects mid and low level clouds over the Arctic in April fairly well when they are the topmost cloud layer, it underestimates high- level clouds. In addition, because the CERES-MODIS cloud algorithm is not able to detect multi-layer clouds and the empirical formula significantly underestimates the depth of high clouds, the occurrence of mid and low-level clouds is underestimated. This comparison does not consider sensitivity difference to thin clouds but we will impose an optical thickness threshold to CALIPSO derived clouds for a further comparison. The effect of such differences in the cloud profile to flux computations will also be discussed. In addition, the effect of cloud cover to the top-of-atmosphere flux over the Arctic using CERES SSF and FLASHFLUX products will be discussed.

Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band

NASA Technical Reports Server (NTRS)

Wind, Galina; Platnick, Steven; King, Michael D.; Hubanks, Paul A,; Pavolonis, Michael J.; Heidinger, Andrew K.; Yang, Ping; Baum, Bryan A.

2009-01-01

Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Earth Observing System EOS Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that presents difficulties for retrieving cloud effective radius using single layer plane-parallel cloud models. The algorithm uses the MODIS 0.94 micron water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94 micron methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases

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).

Applications of Near Real-Time Image and Fire Products from MODIS

NASA Astrophysics Data System (ADS)

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

2010-12-01

NASA’s MODIS Rapid Response Project (http://rapidfire.sci.gsfc.nasa.gov/) has been providing MODIS fire detections and imagery in near real-time since 2001. The Rapid Response system is part of the Land and Atmospheres Near-real time Capability for EOS (LANCE-MODIS) system. Current capabilities include providing MODIS imagery in true color and false color band combinations, a vegetation index, and temperature - in both uncorrected swath format and geographically corrected subset regions. The geographically-corrected subsets images cover the world's land areas and adjoining waters, as well as the entire Arctic and Antarctic. These data are available within a few hours of data acquisition. The images are accessed by large number of user communities to obtain a rapid, 250 meter-resolution overview of ground conditions for fire management, crop and famine monitoring and forecasting, disaster response (fires, oil spills, floods, storms), dust and aerosol monitoring, aviation (tracking volcanic ash), monitoring sea ice conditions, environmental monitoring, and more. In addition, the scientific community uses imagery to locate phenomena of interest prior to ordering and processing data and to support the day-to-day planning of field campaigns. The MODIS Rapid Response project has also been providing a near real-time data feed on fire locations and MODIS imagery subsets to the Fire Information for Resource Management System (FIRMS) project (http://maps.geog.umd.edu/firms). FIRMS provides timely availability of fire location information, which is essential in preventing and fighting large forest/wild fires. Products are available through a WebGIS for visualizing MODIS hotspots and MCD45 Burned Area images, an email alerting tool to deliver fire data on daily/weekly/near real-time basis, active data downloads in formats such as shape, KML, CSV, WMS, etc., along with MODIS imagery subsets. FIRMS’ user base covers more than 100 countries and territories. A recent user survey showed that a majority of people use FIRMS for the purposes of conservation, fire-fighting, natural hazard monitoring, land cover change monitoring, and climate change. FIRMS has also developed a cellphone-based text (SMS) alerting of MODIS and MSG-detected fires in near real-time in South Africa, in partnership with the South African power company ESKOM and Council of Scientific and Industrial Research, South Africa. FIRMS was transitioned to the United Nations Food and Agricultural Organization (UN-FAO) in Rome, Italy in Spring 2010 and is scheduled to become a part of the LANCE-MODIS data system (http://lance.nasa.gov/) in Spring 2011.

Earth-Atmospheric Coupling During Strong Earthquakes by Analyzing MODIS Data

NASA Technical Reports Server (NTRS)

Ouzounov, Dimitar; Williams, Robin G.; Freund, Friedemann

2001-01-01

Interactions between the Earth and the atmosphere during major earthquakes (M greater than 5) are the subject of this investigation. Recently a mechanism has been proposed predicting the build-up of positive ground potentials prior to strong earthquake activity. Connected phenomena include: transient conductivity of rocks, injection of currents, possibly also electromagnetic emission and light emission from high points at the surface of the Earth. To understand this process we analyze vertical atmospheric profiles, land surface and brightness (temperature) data, using the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellite launched in December 1999. MODIS covers the entire Earth every 1-2 days in 36 wavelength bands (20 visible and 16 infrared) at different spatial resolutions (250 m, 500 m, and 1 km). Using MODIS data we look for correlations between the atmospheric dynamics and solid Earth processes for the January 2001 strong earthquakes in San Salvador and India. As part of the build-up of positive grounds potential, an IR luminescence is predicted to occur in the 8-12 micrometer band. We use the MODIS data to differentiate between true "thermal" signals and IR luminescence. Indeed, on the basis of a temporal and spatial distribution analysis, a thermal anomaly pattern is found that appears to be related to the seismic activity. Aerosol content and atmospheric instability parameters also change when ground charges build up causing ion emission and leading to a thin aerosol layer over land. We analyze the aerosol content, atmospheric pressure, moisture profile and lifted index. Anomalous trends have been identified in few days prior to the main shocks. The significance of this observation should be explored further using other data sets.

Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from MODIS Collection 6

NASA Technical Reports Server (NTRS)

Platnick, Steven; Wind, Galina; Zhang, Zhibo; Ackerman, Steven A.; Maddux, Brent

2012-01-01

The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the l.6, 2.1, and 3.7 m spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "notclear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud'edges as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the ID cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.

Consistency of Global Modis Aerosol Optical Depths over Ocean on Terra and Aqua Ceres SSF Datasets

NASA Technical Reports Server (NTRS)

Ignatov, Alexander; Minnis, Patrick; Miller, Walter F.; Wielicki, Bruce A.; Remer, Lorraine

2006-01-01

Aerosol retrievals over ocean from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua platforms are available from the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint (SSF) datasets generated at NASA Langley Research Center (LaRC). Two aerosol products are reported side-by-side. The primary M product is generated by sub-setting and remapping the multi-spectral (0.47-2.1 micrometer) MODIS produced oceanic aerosol (MOD04/MYD04 for Terra/Aqua) onto CERES footprints. M*D04 processing uses cloud screening and aerosol algorithms developed by the MODIS science team. The secondary AVHRR-like A product is generated in only two MODIS bands 1 and 6 (on Aqua, bands 1 and 7). The A processing uses the CERES cloud screening algorithm, and NOAA/NESDIS glint identification, and single-channel aerosol retrieval algorithms. The M and A products have been documented elsewhere and preliminarily compared using 2 weeks of global Terra CERES SSF Edition 1A data in which the M product was based on MOD04 collection 3. In this study, the comparisons between the M and A aerosol optical depths (AOD) in MODIS band 1 (0.64 micrometers), tau(sub 1M) and tau(sub 1A) are re-examined using 9 days of global CERES SSF Terra Edition 2A and Aqua Edition 1B data from 13 - 21 October 2002, and extended to include cross-platform comparisons. The M and A products on the new CERES SSF release are generated using the same aerosol algorithms as before, but with different preprocessing and sampling procedures, lending themselves to a simple sensitivity check to non-aerosol factors. Both tau(sub 1M) and tau(sub 1A) generally compare well across platforms. However, the M product shows some differences, which increase with ambient cloud amount and towards the solar side of the orbit. Three types of comparisons conducted in this study - cross-platform, cross-product, and cross-release confirm the previously made observation that the major area for improvement in the current aerosol processing lies in a more formalized and standardized sampling (and most importantly, cloud screening) whereas optimization of the aerosol algorithm is deemed to be an important yet less critical element.

The MODIS reprojection tool

USGS Publications Warehouse

Dwyer, John L.; Schmidt, Gail L.; Qu, J.J.; Gao, W.; Kafatos, M.; Murphy , R.E.; Salomonson, V.V.

2006-01-01

The MODIS Reprojection Tool (MRT) is designed to help individuals work with MODIS Level-2G, Level-3, and Level-4 land data products. These products are referenced to a global tiling scheme in which each tile is approximately 10° latitude by 10° longitude and non-overlapping (Fig. 9.1). If desired, the user may reproject only selected portions of the product (spatial or parameter subsetting). The software may also be used to convert MODIS products to file formats (generic binary and GeoTIFF) that are more readily compatible with existing software packages. The MODIS land products distributed by the Land Processes Distributed Active Archive Center (LP DAAC) are in the Hierarchical Data Format - Earth Observing System (HDF-EOS), developed by the National Center for Supercomputing Applications at the University of Illinois at Urbana Champaign for the NASA EOS Program. Each HDF-EOS file is comprised of one or more science data sets (SDSs) corresponding to geophysical or biophysical parameters. Metadata are embedded in the HDF file as well as contained in a .met file that is associated with each HDF-EOS file. The MRT supports 8-bit, 16-bit, and 32-bit integer data (both signed and unsigned), as well as 32-bit float data. The data type of the output is the same as the data type of each corresponding input SDS.

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.

The Transition of High-Resolution NASA MODIS Sea Surface Temperatures into the WRF Environmental Modeling System

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Jedlove, Gary J.; Santos, Pablo; Medlin, Jeffrey M.; Rozumalski, Robert A.

2009-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composite at 2-km resolution that has been implemented in version 3 of the National Weather Service (NWS) Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). The WRF EMS is a complete, full physics numerical weather prediction package that incorporates dynamical cores from both the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). The installation, configuration, and execution of either the ARW or NMM models is greatly simplified by the WRF EMS to encourage its use by NWS Weather Forecast Offices (WFOs) and the university community. The WRF EMS is easy to run on most Linux workstations and clusters without the need for compilers. Version 3 of the WRF EMS contains the most recent public release of the WRF-NMM and ARW modeling system (version 3 of the ARW is described in Skamarock et al. 2008), the WRF Pre-processing System (WPS) utilities, and the WRF Post-Processing program. The system is developed and maintained by the NWS National Science Operations Officer Science and Training Resource Coordinator. To initialize the WRF EMS with high-resolution MODIS SSTs, SPoRT developed the composite product consisting of MODIS SSTs over oceans and large lakes with the NCEP Real-Time Global (RTG) filling data over land points. Filling the land points is required due to minor inconsistencies between the WRF land-sea mask and that used to generate the MODIS SST composites. This methodology ensures a continuous field that adequately initializes all appropriate arrays in WRF. MODIS composites covering the Gulf of Mexico, western Atlantic Ocean and the Caribbean are generated daily at 0400, 0700, 1600, and 1900 UTC corresponding to overpass times of the NASA Aqua and Terra polar orbiting satellites. The MODIS SST product is output in gridded binary-1 (GRIB-1) data format for a seamless incorporation into WRF via the WPS utilities. The full-resolution, 1-km MODIS product is sub-sampled to 2-km grid spacing due to limitations in handling very large dimensions in the GRIB-1 data format. The GRIB-1 files are posted online at ftp://ftp.nsstc.org/sstcomp/WRF/, which is directly accessed by the WRF EMS scripts. The MODIS SST composites are also downloaded to the EMS data server, which is accessible by the WRF EMS users and NWS WFOs. The SPoRT MODIS SST composite provides the model with superior detail of the ocean gradients around Florida and surrounding waters, whereas the operational RTG SST typically depicts a relatively smooth field and is not able to capture sharp horizontal gradients in SST. Differences of 2-3 C are common over small horizontal distances, leading to enhanced SST gradients on either side of the Gulf Stream and along the edges of the cooler shelf waters. These sharper gradients can in turn produce atmospheric responses in simulated temperature and wind fields as depicted in LaCasse et al. Differences in atmospheric verification statistics over a several month study were generally small in the vicinity of south Florida; however, the validation of SSTs at specific buoy locations revealed important improvements in the biases and RMS errors, especially in the vicinity of the cooler shelf waters off the east-central Florida coast. A current weakness in the MODIS SST product is the occurrence of occasional discontinuities caused by high latency in SST coverage due to persistent cloud cover. An enhanced method developed by Jedlovec et al. (2009, GHRSST User Symposium) reduces the occurrence of these problems by adding Advanced Microwave Scanning Radiometer -- EOS (AMSR-E) SST data to the compositing process. Enhanced SST composites are produced over the ocean regions surrounding the Continental U.S. at four times each day corresponding to Terra and Aqua equator crossing times. For a given day and overpass time, both MODInd AMSR-E data from the previous seven days form a collection used in the compositing. At each MODIS pixel, cloud-free SST values from the collection are used to form a weighted average based on their latency (number of days from the current day). In this way, recent SST data are given more weight than older data. One of the primary issues involved in incorporating the AMSR-E microwave data in the composites is the tradeoff between the decreased spatial resolution of the AMSR-E data (25 km) and the increased coverage due to its near all-weather capability. Currently, the AMSR-E is given a weight of 20% compared to MODIS data, thereby preserving the spatial structure observed in the MODIS data. Day-time (night-time) AMSR-E SST data from Aqua are used with both Terra and Aqua MODIS day-time (night-time) SST data sets.

Extending Single-Molecule Microscopy Using Optical Fourier Processing

PubMed Central

2015-01-01

This article surveys the recent application of optical Fourier processing to the long-established but still expanding field of single-molecule imaging and microscopy. A variety of single-molecule studies can benefit from the additional image information that can be obtained by modulating the Fourier, or pupil, plane of a widefield microscope. After briefly reviewing several current applications, we present a comprehensive and computationally efficient theoretical model for simulating single-molecule fluorescence as it propagates through an imaging system. Furthermore, we describe how phase/amplitude-modulating optics inserted in the imaging pathway may be modeled, especially at the Fourier plane. Finally, we discuss selected recent applications of Fourier processing methods to measure the orientation, depth, and rotational mobility of single fluorescent molecules. PMID:24745862

Extending single-molecule microscopy using optical Fourier processing.

PubMed

Backer, Adam S; Moerner, W E

2014-07-17

This article surveys the recent application of optical Fourier processing to the long-established but still expanding field of single-molecule imaging and microscopy. A variety of single-molecule studies can benefit from the additional image information that can be obtained by modulating the Fourier, or pupil, plane of a widefield microscope. After briefly reviewing several current applications, we present a comprehensive and computationally efficient theoretical model for simulating single-molecule fluorescence as it propagates through an imaging system. Furthermore, we describe how phase/amplitude-modulating optics inserted in the imaging pathway may be modeled, especially at the Fourier plane. Finally, we discuss selected recent applications of Fourier processing methods to measure the orientation, depth, and rotational mobility of single fluorescent molecules.

Data systems trade studies for a next generation sensor

NASA Astrophysics Data System (ADS)

Masuoka, Edward J.; Fleig, Albert J.

1997-01-01

Processing system designers must make substantial changes to accommodate current and anticipated improvements in remote sensing instruments.Increases in the spectral, radiometric and geometric resolution lead to data rates, processing loads and storage volumes which far exceed the ability of most current computer systems. To accommodate user expectations, the data must be processed and made available quickly in a convenient and easy to use form. This paper describes design trade-offs made in developing the processing system for the moderate resolution imaging spectroradiometer, MODIS, which will fly on the Earth Observing System's, AM-1 spacecraft to be launched in 1998. MODIS will have an average continuous date rate of 6.2 Mbps and require processing at 6.5 GFLOPS to produce 600GB of output products per day. Specific trade-offs occur in the areas of science software portability and usability of science products versus overall system performance and throughput.

Comprehensive genomic analysis identifies pathogenic variants in maturity-onset diabetes of the young (MODY) patients in South India.

PubMed

Mohan, Viswanathan; Radha, Venkatesan; Nguyen, Thong T; Stawiski, Eric W; Pahuja, Kanika Bajaj; Goldstein, Leonard D; Tom, Jennifer; Anjana, Ranjit Mohan; Kong-Beltran, Monica; Bhangale, Tushar; Jahnavi, Suresh; Chandni, Radhakrishnan; Gayathri, Vijay; George, Paul; Zhang, Na; Murugan, Sakthivel; Phalke, Sameer; Chaudhuri, Subhra; Gupta, Ravi; Zhang, Jingli; Santhosh, Sam; Stinson, Jeremy; Modrusan, Zora; Ramprasad, V L; Seshagiri, Somasekar; Peterson, Andrew S

2018-02-13

Maturity-onset diabetes of the young (MODY) is an early-onset, autosomal dominant form of non-insulin dependent diabetes. Genetic diagnosis of MODY can transform patient management. Earlier data on the genetic predisposition to MODY have come primarily from familial studies in populations of European origin. In this study, we carried out a comprehensive genomic analysis of 289 individuals from India that included 152 clinically diagnosed MODY cases to identify variants in known MODY genes. Further, we have analyzed exome data to identify putative MODY relevant variants in genes previously not implicated in MODY. Functional validation of MODY relevant variants was also performed. We found MODY 3 (HNF1A; 7.2%) to be most frequently mutated followed by MODY 12 (ABCC8; 3.3%). They together account for ~ 11% of the cases. In addition to known MODY genes, we report the identification of variants in RFX6, WFS1, AKT2, NKX6-1 that may contribute to development of MODY. Functional assessment of the NKX6-1 variants showed that they are functionally impaired. Our findings showed HNF1A and ABCC8 to be the most frequently mutated MODY genes in south India. Further we provide evidence for additional MODY relevant genes, such as NKX6-1, and these require further validation.

Use of MODIS Satellite Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts

NASA Technical Reports Server (NTRS)

Luvall, J. C.; Sprigg, W.; Levetin, E.; Huete, A.; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P.; Budge, A.; Hudspeth, W.;

Evaluation and Windspeed Dependence of MODIS Aerosol Retrievals Over Open Ocean

NASA Technical Reports Server (NTRS)

Kleidman, Richard G.; Smirnov, Alexander; Levy, Robert C.; Mattoo, Shana; Tanre, Didier

2011-01-01

The Maritime Aerosol Network (MAN) data set provides high quality ground-truth to validate the MODIS aerosol product over open ocean. Prior validation of the ocean aerosol product has been limited to coastal and island sites. Comparing MODIS Collection 5 ocean aerosol retrieval products with collocated MAN measurements from ships shows that MODIS is meeting the pre-launch uncertainty estimates for aerosol optical depth (AOD) with 64% and 67% of retrievals at 550 nm, and 74% and 78% of retrievals at 870 nm, falling within expected uncertainty for Terra and Aqua, respectively. Angstrom Exponent comparisons show a high correlation between MODIS retrievals and shipboard measurements (R= 0.85 Terra, 0.83 Aqua), although the MODIS aerosol algorithm tends to underestimate particle size for large particles and overestimate size for small particles, as seen in earlier Collections. Prior analysis noted an offset between Terra and Aqua ocean AOD, without concluding which sensor was more accurate. The simple linear regression reported here, is consistent with other anecdotal evidence that Aqua agreement with AERONET is marginally better. However we cannot claim based on the current study that the better Aqua comparison is statistically significant. Systematic increase of error as a function of wind speed is noted in both Terra and Aqua retrievals. This wind speed dependency enters the retrieval when winds deviate from the 6 m/s value assumed in the rough ocean surface and white cap parameterizations. Wind speed dependency in the results can be mitigated by using auxiliary NCEP wind speed information in the retrieval process.

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.

The performance of DC restoration function for MODIS thermal emissive bands

NASA Astrophysics Data System (ADS)

Wang, Zhipeng; Xiong, Xiaoxiong Jack; Shrestha, Ashish

2017-09-01

The DC restore (DCR) process of MODIS instrument maintains the output of a detector at focal plane assembly (FPA) within the dynamic range of subsequent analog-to-digital converter, by adding a specific offset voltage to the output. The DCR offset value is adjusted per scan, based on the comparison of the detector response in digital number (DN) collected from the blackbody (BB) view with target DN saved as an on-board look-up table. In this work, the MODIS DCR mechanism is revisited, with the trends of DCR offset being provided for thermal emissive bands (TEB). Noticeable changes have been occasionally found which coincide with significant detector gain change due to various instrumental events such as safe-mode anomaly or FPA temperature fluctuation. In general, MODIS DCR functionality has been effective and the change of DCR offset has no impact to the quality of MODIS data. One exception is the Earth view (EV) data saturation of Aqua MODIS LWIR bands 33, 35 ad 36 during BB warm-up cool-down (WUCD) cycle which has been observed since 2008. The BB view of their detectors saturate when the BB temperature is above certain threshold so the DCR cannot work as designed. Therefore, the dark signal DN fluctuates with the cold FPA (CFPA) temperature and saturate for a few hours per WUCD cycle, which also saturate the EV data sector within the scan. The CFPA temperature fluctuation peaked in 2012 and has been reduced in recent years and the saturation phenomenon has been easing accordingly. This study demonstrates the importance of DCR to data generation.

Comparison of the MODIS Multilayer Cloud Detection and Thermodynamic Phase Products with CALIPSO and CloudSat

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Gala; Holz, Robert E.; Ackerman, Steven A.; Nagle, Fred W.

2008-01-01

CALIPSO and CloudSat, launched in June 2006, provide global active remote sensing measurements of clouds and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the Aqua spacecraft and other A-Train platforms. The most recent processing effort for the MODIS Atmosphere Team, referred to as the "Collection 5" stream, includes a research-level multilayer cloud detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D cloud models used in the MODIS cloud optical and microphysical product retrieval, which are generated at a 1 h resolution. Using pixel-level collocations of MODIS Aqua, CALIOP, and CloudSat radar measurements, we investigate the global performance of the thermodynamic phase and multilayer cloud detection algorithms.

Fan beam image reconstruction with generalized Fourier slice theorem.

PubMed

Zhao, Shuangren; Yang, Kang; Yang, Kevin

2014-01-01

For parallel beam geometry the Fourier reconstruction works via the Fourier slice theorem (or central slice theorem, projection slice theorem). For fan beam situation, Fourier slice can be extended to a generalized Fourier slice theorem (GFST) for fan-beam image reconstruction. We have briefly introduced this method in a conference. This paper reintroduces the GFST method for fan beam geometry in details. The GFST method can be described as following: the Fourier plane is filled by adding up the contributions from all fanbeam projections individually; thereby the values in the Fourier plane are directly calculated for Cartesian coordinates such avoiding the interpolation from polar to Cartesian coordinates in the Fourier domain; inverse fast Fourier transform is applied to the image in Fourier plane and leads to a reconstructed image in spacial domain. The reconstructed image is compared between the result of the GFST method and the result from the filtered backprojection (FBP) method. The major differences of the GFST and the FBP methods are: (1) The interpolation process are at different data sets. The interpolation of the GFST method is at projection data. The interpolation of the FBP method is at filtered projection data. (2) The filtering process are done in different places. The filtering process of the GFST is at Fourier domain. The filtering process of the FBP method is the ramp filter which is done at projections. The resolution of ramp filter is variable with different location but the filter in the Fourier domain lead to resolution invariable with location. One advantage of the GFST method over the FBP method is in short scan situation, an exact solution can be obtained with the GFST method, but it can not be obtained with the FBP method. The calculation of both the GFST and the FBP methods are at O(N^3), where N is the number of pixel in one dimension.

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.

Practical Sub-Nyquist Sampling via Array-Based Compressed Sensing Receiver Architecture

DTIC Science & Technology

2016-07-10

different array ele- ments at different sub-Nyquist sampling rates. Signal processing inspired by the sparse fast Fourier transform allows for signal...reconstruction algorithms can be computationally demanding (REF). The related sparse Fourier transform algorithms aim to reduce the processing time nec- essary to...compute the DFT of frequency-sparse signals [7]. In particular, the sparse fast Fourier transform (sFFT) achieves processing time better than the

Quality Assessment of Landsat Surface Reflectance Products Using MODIS Data

NASA Technical Reports Server (NTRS)

Feng, Min; Huang, Chengquan; Channan, Saurabh; Vermote, Eric; Masek, Jeffrey G.; Townshend, John R.

2012-01-01

Surface reflectance adjusted for atmospheric effects is a primary input for land cover change detection and for developing many higher level surface geophysical parameters. With the development of automated atmospheric correction algorithms, it is now feasible to produce large quantities of surface reflectance products using Landsat images. Validation of these products requires in situ measurements, which either do not exist or are difficult to obtain for most Landsat images. The surface reflectance products derived using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), however, have been validated more comprehensively. Because the MODIS on the Terra platform and the Landsat 7 are only half an hour apart following the same orbit, and each of the 6 Landsat spectral bands overlaps with a MODIS band, good agreements between MODIS and Landsat surface reflectance values can be considered indicators of the reliability of the Landsat products, while disagreements may suggest potential quality problems that need to be further investigated. Here we develop a system called Landsat-MODIS Consistency Checking System (LMCCS). This system automatically matches Landsat data with MODIS observations acquired on the same date over the same locations and uses them to calculate a set of agreement metrics. To maximize its portability, Java and open-source libraries were used in developing this system, and object-oriented programming (OOP) principles were followed to make it more flexible for future expansion. As a highly automated system designed to run as a stand-alone package or as a component of other Landsat data processing systems, this system can be used to assess the quality of essentially every Landsat surface reflectance image where spatially and temporally matching MODIS data are available. The effectiveness of this system was demonstrated using it to assess preliminary surface reflectance products derived using the Global Land Survey (GLS) Landsat images for the 2000 epoch. As surface reflectance likely will be a standard product for future Landsat missions, the approach developed in this study can be adapted as an operational quality assessment system for those missions.

Online Time Series Analysis of Land Products over Asia Monsoon Region via Giovanni

NASA Technical Reports Server (NTRS)

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

2011-01-01

Time series analysis is critical to the study of land cover/land use changes and climate. Time series studies at local-to-regional scales require higher spatial resolution, such as 1km or less, data. MODIS land products of 250m to 1km resolution enable such studies. However, such MODIS land data files are distributed in 10ox10o tiles, due to large data volumes. Conducting a time series study requires downloading all tiles that include the study area for the time period of interest, and mosaicking the tiles spatially. This can be an extremely time-consuming process. In support of the Monsoon Asia Integrated Regional Study (MAIRS) program, NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has processed MODIS land products at 1 km resolution over the Asia monsoon region (0o-60oN, 60o-150oE) with a common data structure and format. The processed data have been integrated into the Giovanni system (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) that enables users to explore, analyze, and download data over an area and time period of interest easily. Currently, the following regional MODIS land products are available in Giovanni: 8-day 1km land surface temperature and active fire, monthly 1km vegetation index, and yearly 0.05o, 500m land cover types. More data will be added in the near future. By combining atmospheric and oceanic data products in the Giovanni system, it is possible to do further analyses of environmental and climate changes associated with the land, ocean, and atmosphere. This presentation demonstrates exploring land products in the Giovanni system with sample case scenarios.

Evaluation of the MODIS Albedo Product over a Heterogeneous Agricultural Area

NASA Technical Reports Server (NTRS)

Sobrino, Jose Antonio; Franch, B.; Oltra-Carrio, R.; Vermote, E. F.; Fedele, E.

2013-01-01

In this article, the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF)/Albedo product (MCD43) is evaluated over a heterogeneous agricultural area in the framework of the Earth Observation: Optical Data Calibration and Information Extraction (EODIX) project campaign, which was developed in Barrax (Spain) in June 2011. In this method, two models, the RossThick-LiSparse-Reciprocal (RTLSR) (which corresponds to the MODIS BRDF algorithm) and the RossThick-Maignan-LiSparse-Reciprocal (RTLSR-HS), were tested over airborne data by processing high-resolution images acquired with the Airborne Hyperspectral Scanner (AHS) sensor. During the campaign, airborne images were retrieved with different view zenith angles along the principal and orthogonal planes. Comparing the results of applying the models to the airborne data with ground measurements, we obtained a root mean square error (RMSE) of 0.018 with both RTLSR and RTLSR-HS models. The evaluation of the MODIS BRDF/Albedo product (MCD43) was performed by comparing satellite images with AHS estimations. The results reported an RMSE of 0.04 with both models. Additionally, taking advantage of a homogeneous barley pixel, we compared in situ albedo data to satellite albedo data. In this case, the MODIS albedo estimation was (0.210 +/- 0.003), while the in situ measurement was (0.204 +/- 0.003). This result shows good agreement in regard to a homogeneous pixel.

Real-time processing for full-range Fourier-domain optical-coherence tomography with zero-filling interpolation using multiple graphic processing units.

PubMed

Watanabe, Yuuki; Maeno, Seiya; Aoshima, Kenji; Hasegawa, Haruyuki; Koseki, Hitoshi

2010-09-01

The real-time display of full-range, 2048?axial pixelx1024?lateral pixel, Fourier-domain optical-coherence tomography (FD-OCT) images is demonstrated. The required speed was achieved by using dual graphic processing units (GPUs) with many stream processors to realize highly parallel processing. We used a zero-filling technique, including a forward Fourier transform, a zero padding to increase the axial data-array size to 8192, an inverse-Fourier transform back to the spectral domain, a linear interpolation from wavelength to wavenumber, a lateral Hilbert transform to obtain the complex spectrum, a Fourier transform to obtain the axial profiles, and a log scaling. The data-transfer time of the frame grabber was 15.73?ms, and the processing time, which includes the data transfer between the GPU memory and the host computer, was 14.75?ms, for a total time shorter than the 36.70?ms frame-interval time using a line-scan CCD camera operated at 27.9?kHz. That is, our OCT system achieved a processed-image display rate of 27.23 frames/s.

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.

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.

Monitoring ice break-up on the Mackenzie River using MODIS data

NASA Astrophysics Data System (ADS)

Muhammad, P.; Duguay, C.; Kang, K.-K.

2016-03-01

The aim of this study was to develop an approach for estimating ice break-up dates on the Mackenzie River (MR) using more than a decade of MODIS Level 3 500 m snow products (MOD/MYD10A1), complemented with 250 m Level 1B radiance products (MOD/MYD02QKM) from the Terra and Aqua satellite platforms. The analysis showed break-up began on average between days of year (DOYs) 115 and 125 and ended between DOYs 145 and 155 over 13 ice seasons (2001-2013), resulting in an average melt duration of ca. 30-40 days. Thermal processes were more important in driving ice break-up south of the MR confluence with the Liard River, while dynamically driven break-up was more important north of the Liard. A comparison of the timing of ice disappearance with snow disappearance from surrounding land areas of the MR with MODIS Level 3 snow products showed varying relationships along the river. Ice-off and snow-off timing were in sync north of the MR-Liard River confluence and over sections of the MR before it enters the Mackenzie Delta, but ice disappeared much later than snow on land in regions where thermal ice break-up processes dominated. MODIS observations revealed that channel morphology is a more important control of ice break-up patterns than previously believed with ice runs on the MR strongly influenced by channel morphology (islands and bars, confluences and channel constriction). Ice velocity estimates from feature tracking were able to be made in 2008 and 2010 and yielded 3-4-day average ice velocities of 1.21 and 1.84 m s-1 respectively, which is in agreement with estimates from previous studies. These preliminary results confirm the utility of daily MODIS data for monitoring ice break-up processes along the Mackenzie River. The addition of optical and synthetic aperture radar data from recent and upcoming satellite missions (e.g. Sentinel-1/2/3 and RADARSAT Constellation) would improve the monitoring of ice break-up in narrower sections of the MR.

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

MODIS NDVI Response Following Fires in Siberia

NASA Technical Reports Server (NTRS)

Ranson, K. Jon; Sun, G.; Kovacs, K.; Kharuk, V. I.

2003-01-01

The Siberian boreal forest is considered a carbon sink but may become an important source of carbon dioxide if climatic warming predictions are correct. The forest is continually changing through various disturbance mechanisms such as insects, logging, mineral exploitation, and especially fires. Patterns of disturbance and forest recovery processes are important factors regulating carbon flux in this area. NASA's Terra MODIS provides useful information for assessing location of fires and post fire changes in forests. MODIS fire (MOD14), and NDVI (MOD13) products were used to examine fire occurrence and post fire variability in vegetation cover as indicated by NDVI. Results were interpreted for various post fire outcomes, such as decreased NDVI after fire, no change in NDVI after fire and positive NDVI change after fire. The fire frequency data were also evaluated in terms of proximity to population centers, and transportation networks.

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.

Ocean observations with EOS/MODIS: Algorithm development and post launch studies

NASA Technical Reports Server (NTRS)

Gordon, Howard R.

1995-01-01

Several significant accomplishments were made during the present reporting period. (1) Initial simulations to understand the applicability of the MODerate Resolution Imaging Spectrometer (MODIS) 1380 nm band for removing the effects of stratospheric aerosols and thin cirrus clouds were completed using a model for an aged volcanic aerosol. The results suggest that very simple procedures requiring no a priori knowledge of the optical properties of the stratospheric aerosol may be as effective as complex procedures requiring full knowledge of the aerosol properties, except the concentration which is estimated from the reflectance at 1380 nm. The limitations of this conclusion will be examined in the next reporting period; (2) The lookup tables employed in the implementation of the atmospheric correction algorithm have been modified in several ways intended to improve the accuracy and/or speed of processing. These have been delivered to R. Evans for implementation into the MODIS prototype processing algorithm for testing; (3) A method was developed for removal of the effects of the O2 'A' absorption band from SeaWiFS band 7 (745-785 nm). This is important in that SeaWiFS imagery will be used as a test data set for the MODIS atmospheric correction algorithm over the oceans; and (4) Construction of a radiometer, and associated deployment boom, for studying the spectral reflectance of oceanic whitecaps at sea was completed. The system was successfully tested on a cruise off Hawaii on which whitecaps were plentiful during October-November. This data set is now under analysis.

[Temporal and spatial variation of MODIS vegetation indices in Hunan Province].

PubMed

Lin, Hui; Xiong, Yu-Jiu; Wan, Ling-Feng; Mo, Deng-Kui; Sun, Hua

2007-03-01

Based on MODIS images and by using the algorithm of maximum value composite (MVC), the monthly vegetation indices (VIs) in 2005 in Hunan Province were obtained. Through the analysis of the MODIS VIs, Hunan Province was divided into six districts to describe the spatial distribution of the VIs, and by using the monthly mean temperature and rainfall data collected from 5 climatic monitoring stations in this province, the temporal variation of the VIs was analyzed. The results showed that the spatial distribution of MODIS VIs was positively correlated with vegetation cover, and appeared regional characteristics. The MODIS VIs varied with season, and the curves of their monthly mean values were downwards opening quadratic parabolas, with the maximum appeared in July. The value of MODIS EVI was smaller than that of MODIS NDVI. MODIS VI was mainly affected by monthly mean temperature, but this effect was decreased with decreasing latitude. The variation pattern of MODIS EVI was more apparent than that of MODIS NDVI, i. e. , the quadratic parabola of MODIS EVI was smoother, going gradually from minimum to maximum and then going down, while that of MODIS NDVI had tiny fluctuations on both sides of the maximum point.

Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project

NASA Astrophysics Data System (ADS)

Stengel, Martin; Stapelberg, Stefan; Sus, Oliver; Schlundt, Cornelia; Poulsen, Caroline; Thomas, Gareth; Christensen, Matthew; Carbajal Henken, Cintia; Preusker, Rene; Fischer, Jürgen; Devasthale, Abhay; Willén, Ulrika; Karlsson, Karl-Göran; McGarragh, Gregory R.; Proud, Simon; Povey, Adam C.; Grainger, Roy G.; Fokke Meirink, Jan; Feofilov, Artem; Bennartz, Ralf; Bojanowski, Jedrzej S.; Hollmann, Rainer

2017-11-01

New cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for cloud detection and cloud typing followed by cloud property retrievals based on the optimal estimation (OE) technique. The OE-based retrievals are applied to simultaneously retrieve cloud-top pressure, cloud particle effective radius and cloud optical thickness using measurements at visible, near-infrared and thermal infrared wavelengths, which ensures spectral consistency. The retrieved cloud properties are further processed to derive cloud-top height, cloud-top temperature, cloud liquid water path, cloud ice water path and spectral cloud albedo. The Cloud_cci products are pixel-based retrievals, daily composites of those on a global equal-angle latitude-longitude grid, and monthly cloud properties such as averages, standard deviations and histograms, also on a global grid. All products include rigorous propagation of the retrieval and sampling uncertainties. Grouping the orbital properties of the sensor families, six datasets have been defined, which are named AVHRR-AM, AVHRR-PM, MODIS-Terra, MODIS-Aqua, ATSR2-AATSR and MERIS+AATSR, each comprising a specific subset of all available sensors. The individual characteristics of the datasets are presented together with a summary of the retrieval systems and measurement records on which the dataset generation were based. Example validation results are given, based on comparisons to well-established reference observations, which demonstrate the good quality of the data. In particular the ensured spectral consistency and the rigorous uncertainty propagation through all processing levels can be considered as new features of the Cloud_cci datasets compared to existing datasets. In addition, the consistency among the individual datasets allows for a potential combination of them as well as facilitates studies on the impact of temporal sampling and spatial resolution on cloud climatologies.

For each dataset a digital object identifier has been issued:

Cloud_cci AVHRR-AM: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-AM/V002

Cloud_cci AVHRR-PM: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V002

Cloud_cci MODIS-Terra: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Terra/V002

Cloud_cci MODIS-Aqua: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Aqua/V002

Cloud_cci ATSR2-AATSR: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V002

Cloud_cci MERIS+AATSR: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MERIS+AATSR/V002

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.

Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.

2015-01-01

Accurately estimating aboveground vegetation biomass productivity is essential for local ecosystem assessment and best land management practice. Satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. A 250-m grassland biomass productivity map for the Greater Platte River Basin had been developed based on the relationship between Moderate Resolution Imaging Spectroradiometer (MODIS) GSN and Soil Survey Geographic (SSURGO) annual grassland productivity. However, the 250-m MODIS grassland biomass productivity map does not capture detailed ecological features (or patterns) and may result in only generalized estimation of the regional total productivity. Developing a high or moderate spatial resolution (e.g., 30-m) productivity map to better understand the regional detailed vegetation condition and ecosystem services is preferred. The 30-m Landsat data provide spatial detail for characterizing human-scale processes and have been successfully used for land cover and land change studies. The main goal of this study is to develop a 30-m grassland biomass productivity estimation map for central Nebraska, leveraging 250-m MODIS GSN and 30-m Landsat data. A rule-based piecewise regression GSN model based on MODIS and Landsat (r = 0.91) was developed, and a 30-m MODIS equivalent GSN map was generated. Finally, a 30-m grassland biomass productivity estimation map, which provides spatially detailed ecological features and conditions for central Nebraska, was produced. The resulting 30-m grassland productivity map was generally supported by the SSURGO biomass production map and will be useful for regional ecosystem study and local land management practices.

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; Chu, D. Allen; Moody, Eric G.

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 between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five 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 we 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 (i) developing a cloud mask for distinguishing clear sky from clouds, (ii) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (iii) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (iv) determining atmospheric profiles of moisture and temperature, and (v) 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 to the east Asian region in Spring 2001. 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 degree (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.

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.

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

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Menzel, W. Paul; Kaufman, Yoram J.; Ackerman, Steven A.; Tanre, Didier; Gao, Bo-Cai

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 kilometers, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 meters (2 bands), 500 meters (5 bands) and 1000 meters (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation we 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 (i) developing a cloud mask for distinguishing clear sky from clouds, (ii) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (iii) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (iv) determining atmospheric profiles of moisture and temperature, and (v) 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 degree (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.

Characterization of beta cell and incretin function in patients with MODY1 (HNF4A MODY) and MODY3 (HNF1A MODY) in a Swedish patient collection.

PubMed

Ekholm, E; Shaat, N; Holst, J J

2012-10-01

The aim of this study was to evaluate the beta cell and incretin function in patients with HNF4A and HNF1A MODY during a test meal. Clinical characteristics and biochemical data (glucose, proinsulin, insulin, C-peptide, GLP-1 and GIP) during a test meal were compared between MODY patients from eight different families. BMI-matched T2D and healthy subjects were used as two separate control groups. The early phase of insulin secretion was attenuated in HNF4A, HNF1A MODY and T2D (AUC0-30 controls: 558.2 ± 101.2, HNF4A MODY: 93.8 ± 57.0, HNF1A MODY: 170.2 ± 64.5, T2D: 211.2 ± 65.3, P < 0.01). Markedly reduced levels of proinsulin were found in HNF4A MODY compared to T2D and that tended to be so also in HNF1A MODY (HNF4A MODY: 3.7 ± 1.2, HNF1A MODY: 8.3 ± 3.8 vs. T2D: 26.6 ± 14.3). Patients with HNF4A MODY had similar total GLP-1 and GIP responses as controls (GLP-1 AUC: (control: 823.9 ± 703.8, T2D: 556.4 ± 698.2, HNF4A MODY: 1,257.0 ± 999.3, HNF1A MODY: 697.1 ± 818.4) but with a different secretion pattern. The AUC insulin during the test meal was strongly correlated with the GIP secretion (Correlation coefficient 1.0, P < 0.001). No such correlation was seen for insulin and GLP-1. Patients with HNF4A and HNF1A MODY showed an attenuated early phase of insulin secretion similar to T2Ds. AUC insulin during the test meal was strongly correlated with GIP secretion, whereas no such correlation was seen for insulin and GLP-1. Thus, GIP may be a more important factor for insulin secretion than GLP-1 in MODY patients.

Viirs Land Science Investigator-Led Processing System

NASA Astrophysics Data System (ADS)

Devadiga, S.; Mauoka, E.; Roman, M. O.; Wolfe, R. E.; Kalb, V.; Davidson, C. C.; Ye, G.

2015-12-01

The objective of the NASA's Suomi National Polar Orbiting Partnership (S-NPP) Land Science Investigator-led Processing System (Land SIPS), housed at the NASA Goddard Space Flight Center (GSFC), is to produce high quality land products from the Visible Infrared Imaging Radiometer Suite (VIIRS) to extend the Earth System Data Records (ESDRs) developed from NASA's heritage Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the EOS Terra and Aqua satellites. In this paper we will present the functional description and capabilities of the S-NPP Land SIPS, including system development phases and production schedules, timeline for processing, and delivery of land science products based on coordination with the S-NPP Land science team members. The Land SIPS processing stream is expected to be operational by December 2016, generating land products either using the NASA science team delivered algorithms, or the "best-of" science algorithms currently in operation at NASA's Land Product Evaluation and Algorithm Testing Element (PEATE). In addition to generating the standard land science products through processing of the NASA's VIIRS Level 0 data record, the Land SIPS processing system is also used to produce a suite of near-real time products for NASA's application community. Land SIPS will also deliver the standard products, ancillary data sets, software and supporting documentation (ATBDs) to the assigned Distributed Active Archive Centers (DAACs) for archival and distribution. Quality assessment and validation will be an integral part of the Land SIPS processing system; the former being performed at Land Data Operational Product Evaluation (LDOPE) facility, while the latter under the auspices of the CEOS Working Group on Calibration & Validation (WGCV) Land Product Validation (LPV) Subgroup; adopting the best-practices and tools used to assess the quality of heritage EOS-MODIS products generated at the MODIS Adaptive Processing System (MODAPS).

MODIS Land Data Products: Generation, Quality Assurance and Validation

NASA Technical Reports Server (NTRS)

Masuoka, Edward; Wolfe, Robert; Morisette, Jeffery; Sinno, Scott; Teague, Michael; Saleous, Nazmi; Devadiga, Sadashiva; Justice, Christopher; Nickeson, Jaime

2008-01-01

The Moderate Resolution Imaging Spectrometer (MODIS) on-board NASA's Earth Observing System (EOS) Terra and Aqua Satellites are key instruments for providing data on global land, atmosphere, and ocean dynamics. Derived MODIS land, atmosphere and ocean products are central to NASA's mission to monitor and understand the Earth system. NASA has developed and generated on a systematic basis a suite of MODIS products starting with the first Terra MODIS data sensed February 22, 2000 and continuing with the first MODIS-Aqua data sensed July 2, 2002. The MODIS Land products are divided into three product suites: radiation budget products, ecosystem products, and land cover characterization products. The production and distribution of the MODIS Land products are described, from initial software delivery by the MODIS Land Science Team, to operational product generation and quality assurance, delivery to EOS archival and distribution centers, and product accuracy assessment and validation. Progress and lessons learned since the first MODIS data were in early 2000 are described.

Remote Sensing of Fires and Smoke from the Earth Observing System MODIS Instrument

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Hao, W. M.; Justice, C.; Giglio, L.; Herring, D.; Einaudi, Franco (Technical Monitor)

2001-01-01

The talk will include review of the MODIS (Moderate Resolution Imaging Spectrometer) algorithms and performance e.g. the MODIS algorithm and the changes in the algorithm since launch. Comparison of MODIS and ASTER fire observations. Summary of the fall activity with the Forest Service in use of MODIS data for the fires in the North-West. Validation on the ground of the MODIS fire product.

Phenotypical aspects of maturity-onset diabetes of the young (MODY diabetes) in comparison with Type 2 diabetes mellitus (T2DM) in children and adolescents: experience from a large multicentre database.

PubMed

Schober, E; Rami, B; Grabert, M; Thon, A; Kapellen, Th; Reinehr, Th; Holl, R W

2009-05-01

To analyse and compare clinical characteristics in young patients with maturity-onset diabetes of the young (MODY) and Type 2 diabetes mellitus (T2DM). We conducted an observational investigation using the DPV-Wiss database containing clinical data on 40 757 diabetic patients < 20 years of age from Germany and Austria. Three hundred and thirty-nine cases were clinically categorized as MODY (0.83%); 562 patients were diagnosed as T2DM (1.4%). In 20% of cases, the diagnosis of MODY was based on clinical findings only. Of the 272 subjects where genetic testing was available, 3% did not carry mutations in the three examined MODY genes. Glucokinase-MODY was commoner than HNF1A-MODY and HNF4A-MODY. Age at diagnosis was younger in MODY patients. The body mass index of T2DM was significantly higher compared with all MODY subgroups. Macrovascular risk factors such as dyslipidaemia and hypertension were commoner in T2DM, but 23% of MODY patients had dyslipidaemia and 10% hypertension. Glycaemic control was within the therapeutic target (HbA(1c) < 7.5%) in 86% of MODY and 70% of T2DM patients. The prevalence of MODY in children and adolescents in Germany and Austria is lower than that of T2DM in this age group. Dyslipidaemia and hypertension are less frequent in MODY compared with T2DM patients, but do occur.

Level 1 Processing of MODIS Direct Broadcast Data at the GSFC DAAC

NASA Technical Reports Server (NTRS)

Lynnes, Christopher; Kempler, Steven J. (Technical Monitor)

2001-01-01

The GSFC DAAC is working to test and package the MODIS Level 1 Processing software for Aqua Direct Broadcast data. This entails the same code base, but different lookup tables for Aqua and Terra. However, the most significant change is the use of ancillary attitude and ephemeris files instead of orbit/attitude information within the science data stream (as with Terra). In addition, we are working on Linux: ports of the algorithms, which could eventually enable processing on PC clusters. Finally, the GSFC DAAC is also working with the GSFC Direct Readout laboratory to ingest Level 0 data from the GSFC DB antenna into the main DAAC, enabling level 1 production in near real time in support of applications users, such as the Synergy project. The mechanism developed for this could conceivably be extended to other participating stations.

Cystatin C is not a good candidate biomarker for HNF1A-MODY.

PubMed

Nowak, Natalia; Szopa, Magdalena; Thanabalasingham, Gaya; McDonald, Tim J; Colclough, Kevin; Skupien, Jan; James, Timothy J; Kiec-Wilk, Beata; Kozek, Elzbieta; Mlynarski, Wojciech; Hattersley, Andrew T; Owen, Katharine R; Malecki, Maciej T

2013-10-01

Cystatin C is a marker of glomerular filtration rate (GFR). Its level is influenced, among the others, by CRP whose concentration is decreased in HNF1A-MODY. We hypothesized that cystatin C level might be altered in HNF1A-MODY. We aimed to evaluate cystatin C in HNF1A-MODY both as a diagnostic marker and as a method of assessing GFR. We initially examined 51 HNF1A-MODY patients, 56 subjects with type 1 diabetes (T1DM), 39 with type 2 diabetes (T2DM) and 43 non-diabetic individuals (ND) from Poland. Subjects from two UK centres were used as replication panels: including 215 HNF1A-MODY, 203 T2DM, 39 HNF4A-MODY, 170 GCK-MODY, 17 HNF1B-MODY and 58 T1DM patients. The data were analysed with additive models, adjusting for gender, age, BMI and estimated GFR (creatinine). In the Polish subjects, adjusted cystatin C level in HNF1A-MODY was lower compared with T1DM, T2DM and ND (p < 0.05). Additionally, cystatin C-based GFR was higher than that calculated from creatinine level (p < 0.0001) in HNF1A-MODY, while the two GFR estimates were similar or cystatin C-based lower in the other groups. In the UK subjects, there were no differences in cystatin C between HNF1A-MODY and the other diabetic subgroups, except HNF1B-MODY. In UK HNF1A-MODY, cystatin C-based GFR estimate was higher than the creatinine-based one (p < 0.0001). Concluding, we could not confirm our hypothesis (supported by the Polish results) that cystatin C level is altered by HNF1A mutations; thus, it cannot be used as a biomarker for HNF1A-MODY. In HNF1A-MODY, the cystatin C-based GFR estimate is higher than the creatinine-based one.

NASA Satellite Data for Seagrass Health Modeling and Monitoring

NASA Technical Reports Server (NTRS)

Spiering, Bruce A.; Underwood, Lauren; Ross, Kenton

2011-01-01

Time series derived information for coastal waters will be used to provide input data for the Fong and Harwell model. The current MODIS land mask limits where the model can be applied; this project will: a) Apply MODIS data with resolution higher than the standard products (250-m vs. 1-km). b) Seek to refine the land mask. c) Explore nearby areas to use as proxies for time series directly over the beds. Novel processing approaches will be leveraged from other NASA projects and customized as inputs for seagrass productivity modeling

Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from MODIS Collection 6

NASA Astrophysics Data System (ADS)

Platnick, S.; Wind, G.; Zhang, Z.; Ackerman, S. A.; Maddux, B. C.

2012-12-01

The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the 1.6, 2.1, and 3.7 μm spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "not-clear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud edges (defined by immediate adjacency to "clear" MOD/MYD35 pixels) as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the 1D cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.

GEONEX: algorithm development and validation of Gross Primary Production from geostationary satellites

NASA Astrophysics Data System (ADS)

Hashimoto, H.; Wang, W.; Ganguly, S.; Li, S.; Michaelis, A.; Higuchi, A.; Takenaka, H.; Nemani, R. R.

2017-12-01

New geostationary sensors such as the AHI (Advanced Himawari Imager on Himawari-8) and the ABI (Advanced Baseline Imager on GOES-16) have the potential to advance ecosystem modeling particularly of diurnally varying phenomenon through frequent observations. These sensors have similar channels as in MODIS (MODerate resolution Imaging Spectroradiometer), and allow us to utilize the knowledge and experience in MODIS data processing. Here, we developed sub-hourly Gross Primary Production (GPP) algorithm, leverating the MODIS 17 GPP algorithm. We run the model at 1-km resolution over Japan and Australia using geo-corrected AHI data. Solar radiation was directly calculated from AHI using a neural network technique. The other necessary climate data were derived from weather stations and other satellite data. The sub-hourly estimates of GPP were first compared with ground-measured GPP at various Fluxnet sites. We also compared the AHI GPP with MODIS 17 GPP, and analyzed the differences in spatial patterns and the effect of diurnal changes in climate forcing. The sub-hourly GPP products require massive storage and strong computational power. We use NEX (NASA Earth Exchange) facility to produce the GPP products. This GPP algorithm can be applied to other geostationary satellites including GOES-16 in future.

[Maturity onset diabetes of the young (MODY) - screening, diagnostic and therapy].

PubMed

Kaser, Susanne; Resl, Michael

2016-04-01

Maturity onset diabetes of the young (MODY) is a group of monogenetic diabetes types affecting up to 2% all known diabetics. Transcription factor MODY (HNF1α, HNF4α), the most frequent forms of MODY, allow treatment with sulfonylureas, mutations of glucokinase (GCK-MODY) usually do not require any therapy. Especially in younger patients correct diagnosis of MODY often results in discontinuation of insulin therapy and initiation of a sulfonylurea. Accordingly, in patients with diabetes onset below age of 25 years, with a positive family history for diabetes and negative autoantibodies screening for MODY is recommended.

Sensitivity of Aerosol Multi-Sensor Daily Data Intercomparison to the Level 3 Dataday Definition

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Lary, David; Shen, Suhung; Lynnes, Christopher

2010-01-01

Topics include: why people use Level 3 products, why someone might go wrong with Level 3 products, differences in L3 from different sensors, Level 3 data day definition, MODIS vs. MODIS, AOD MODIS Terra vs. Aqua in Pacific, AOD Aqua MODIS vs. MISR correlation map, MODIS vs MISR on Terra, MODIS atmospheric data day definition, orbit time difference for Terra and Aqua 2009-01-06, maximum time difference for Terra (Calendar day), artifact explains, data day definitions, local time distribution, spatial (local time) data day definition, maximum time difference between Terra and Aqua, Removing the artifact in 16-day AOD correlation, MODIS cloud top pressure, and MODIS Terra and Aqua vs. AIRS cloud top pressure.

[Diagnosis of MODY - brief overview for clinical practice].

PubMed

Urbanová, Jana; Brunerová, Ludmila; Brož, Jan

2018-01-01

Maturity Onset Diabetes of the Young (MODY) comprises inherited forms of diabetes mellitus caused by the mutations in the genes involved in the development, differentiation and function of beta-cells. The majority of patients with MODY remains misdiagnosed and erroneously classified as type 1 or type 2 diabetic patients. Correct MODY diagnosis is, however, essential since it enables individualization of treatment, assessment of the prognosis and identification of diabetes among patient´s relatives. Clinical presentation of MODY is highly variable and it could resemble other types of diabetes, thus identification of MODY patients might be difficult. In this review, we describe typical clinical presentation of the most common MODY subtypes, we summarize current diagnostic guidelines in confirmation of MODY and we raise the question of possible need for extension of current clinical criteria indicating a patient for molecular-genetic testing.Key words: clinical course - diagnosis - differential diagnosis - glucokinase - hepatocyte nuclear factors - MODY.

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

NASA Technical Reports Server (NTRS)

Gordon, Howard R.; Conboy, B. (Technical Monitor)

1999-01-01

Significant accomplishments made during the present reporting period include: 1) Installed spectral optimization algorithm in the SeaDas image processing environment and successfully processed SeaWiFS imagery. The results were superior to the standard SeaWiFS algorithm (the MODIS prototype) in a turbid atmosphere off the US East Coast, but similar in a clear (typical) oceanic atmosphere; 2) Inverted ACE-2 LIDAR measurements coupled with sun photometer-derived aerosol optical thickness to obtain the vertical profile of aerosol optical thickness. The profile was validated with simultaneous aircraft measurements; and 3) Obtained LIDAR and CIMEL measurements of typical maritime and mineral dust-dominated marine atmosphere in the U.S. Virgin Islands. Contemporaneous SeaWiFS imagery were also acquired.

MODIS Validation, Data Merger and Other Activities Accomplished by the SIMBIOS Project: 2002-2003

NASA Technical Reports Server (NTRS)

Fargion, Giulietta S.; McClain, Charles R.

2003-01-01

The purpose of this technical report is to provide current documentation of the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities, satellite data processing, and data product validation. This documentation is necessary to ensure that critical information is related to the scientific community and NASA management. This critical information includes the technical difficulties and challenges of validating and combining ocean color data from an array of independent satellite systems to form consistent and accurate global bio-optical time series products. This technical report focuses on the SIMBIOS Project s efforts in support of the Moderate-Resolution Imaging Spectroradiometer (MODIS) on the Earth Observing System (EOS) Terra platform (similar evaluations of MODIS/Aqua are underway). This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational project.

Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

NASA Astrophysics Data System (ADS)

Riggs, George A.; Hall, Dorothy K.; Román, Miguel O.

2017-10-01

Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6; https://nsidc.org/data/modis/data_summaries) and VIIRS Collection 1 (C1; https://doi.org/10.5067/VIIRS/VNP10.001) represent the state-of-the-art global snow-cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow-cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map. The increased data content allows flexibility in using the datasets for specific regions and end-user applications. Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375 m native resolution compared to MODIS 500 m), the snow detection algorithms and data products are designed to be as similar as possible so that the 16+ year MODIS ESDR of global SCE can be extended into the future with the S-NPP VIIRS snow products and with products from future Joint Polar Satellite System (JPSS) platforms. These NASA datasets are archived and accessible through the NASA Distributed Active Archive Center at the National Snow and Ice Data Center in Boulder, Colorado.

Monitoring start of season in Alaska with GLOBE, AVHRR, and MODIS data

NASA Astrophysics Data System (ADS)

Robin, Jessica; Dubayah, Ralph; Sparrow, Elena; Levine, Elissa

2008-03-01

This work evaluates whether continuity between Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) is achievable for monitoring phenological changes in Alaska. This work also evaluates whether NDVI can detect changes in start of the growing season (SOS) in this region. Six quadratic regression models with NDVI as a function of accumulated growing degree days (AGDD) were developed from 2001 through 2004 AVHRR and MODIS NDVI data sets for urban, mixed, and forested land covers. Model parameters determined NDVI values for start of the observational period as well as peak and length of the growing season. NDVI values for start of the growing season were determined from the model equations and field observations of SOS made by GLOBE students and researchers at University of Alaska Fairbanks. AGDD was computed from daily air temperature. AVHRR and MODIS models were significantly different from one another with differences in the start of the observational season as well as start, peak, and length of the growing season. Furthermore, AGDD for SOS was significantly lower during the 1990s than the 1980s. NDVI values at SOS did not detect this change. There are limitations with using NDVI to monitor phenological changes in these regions because of snow, the large extent of conifers, and clouds, which restrict the composite period. In addition, differing processing and spectral characteristics restrict continuity between AVHRR and MODIS NDVI data sets.

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.

Sensitivity Study for Sensor Optical and Electric Crosstalk Based on Spectral Measurements: An Application to Developmental Sensors Using Heritage Sensors Such As MODIS

NASA Technical Reports Server (NTRS)

Butler, James J.; Oudrari, Hassan; Xiong, Sanxiong; Che, Nianzeng; Xiong, Xiaoxiong

2007-01-01

The process of developing new sensors for space flight frequently builds upon the designs and experience of existing heritage space flight sensors. Frequently in the development and testing of new sensors, problems are encountered that pose the risk of serious impact on successful retrieval of geophysical products. This paper describes an approach to assess the importance of optical and electronic cross-talk on retrieval of geophysical products using new MODIS-like sensors through the use of MODIS data sets. These approaches may be extended to any sensor characteristic and any sensor where that characteristic may impact the Level 1 products so long as validated geophysical products are being developed from the heritage sensor. In this study, a set of electronic and/or optical cross-talk coefficients are postulated. These coefficients are sender-receiver influence coefficients and represent a sensor signal contamination on any detector on a focal plane when another band's detectors on that focal plane are stimulated with a monochromatic light. The approach involves using the postulated cross-talk coefficients on an actual set of MODIS data granules. The original MODIS data granules and the cross-talk impacted granules are used with validated geophysical algorithms to create the derived products. Comparison of the products produced with the original and cross-talk impacted granules indicates potential problems, if any, with the characteristics of the developmental sensor that are being studied.

Quantitative Evaluation of Serum Proteins Uncovers a Protein Signature Related to Maturity-Onset Diabetes of the Young (MODY).

PubMed

Tuerxunyiming, Muhadasi; Xian, Feng; Zi, Jin; Yimamu, Yilihamujiang; Abuduwayite, Reshalaiti; Ren, Yan; Li, Qidan; Abudula, Abulizi; Liu, SiQi; Mohemaiti, Patamu

2018-01-05

Maturity-onset diabetes of the young (MODY) is an inherited monogenic type of diabetes. Genetic mutations in MODY often cause nonsynonymous changes that directly lead to the functional distortion of proteins and the pathological consequences. Herein, we proposed that the inherited mutations found in a MODY family could cause a disturbance of protein abundance, specifically in serum. The serum samples were collected from a Uyghur MODY family through three generations, and the serum proteins after depletion treatment were examined by quantitative proteomics to characterize the MODY-related serum proteins followed by verification using target quantification of proteomics. A total of 32 serum proteins were preliminarily identified as the MODY-related. Further verification test toward the individual samples demonstrated the 12 candidates with the significantly different abundance in the MODY patients. A comparison of the 12 proteins among the sera of type 1 diabetes, type 2 diabetes, MODY, and healthy subjects was conducted and revealed a protein signature related with MODY composed of the serum proteins such as SERPINA7, APOC4, LPA, C6, and F5.

Analysis of land degradation processes on a tiger bush plateau in South West Niger using MODIS and LANDSAT TM/ETM+ data

NASA Astrophysics Data System (ADS)

Fiorillo, Edoardo; Maselli, Fabio; Tarchiani, Vieri; Vignaroli, Patrizio

2017-10-01

Remote sensing digital image analysis has been applied to monitor land clearing and degradation processes on a plateau covered by tiger bush near Niamey in South West Niger, where signs of severe landscape degradation due to fuelwood supply have been observed in the last decades. A MODIS NDVI dataset (2000-2015) and five LANDSAT images (1986-2012) were used to identify spatial and temporal dynamics and to emphasize areas of greater degradation. The study indicates that the land clearing found by previous investigations in the second part of the 20th century is still ongoing, with a decreasing trend of MODIS NDVI values recorded in the period 2000-2015. This trend appeared to be linked to an increase in bare soil areas that was demonstrated by analysis of LANDSAT SAVI images. The investigation also indicated that rates of degradation are stronger in more deteriorated areas like those located nearer Niamey; degradation patterns also tend to increase from the inner areas to the edges of the plateau. These results attest to the urgency to develop effective environmental preservation policies and find alternative solutions for domestic energy supply.

Progress towards NASA MODIS and Suomi NPP Cloud Property Data Record Continuity

NASA Astrophysics Data System (ADS)

Platnick, S.; Meyer, K.; Holz, R.; Ackerman, S. A.; Heidinger, A.; Wind, G.; Platnick, S. E.; Wang, C.; Marchant, B.; Frey, R.

2017-12-01

The Suomi NPP VIIRS imager provides an opportunity to extend the 17+ year EOS MODIS climate data record into the next generation operational era. Similar to MODIS, VIIRS provides visible through IR observations at moderate spatial resolution with a 1330 LT equatorial crossing consistent with the MODIS on the Aqua platform. However, unlike MODIS, VIIRS lacks key water vapor and CO2 absorbing channels used for high cloud detection and cloud-top property retrievals. In addition, there is a significant mismatch in the spectral location of the 2.2 μm shortwave-infrared channels used for cloud optical/microphysical retrievals and cloud thermodynamic phase. Given these instrument differences between MODIS EOS and VIIRS S-NPP/JPSS, a merged MODIS-VIIRS cloud record to serve the science community in the coming decades requires different algorithm approaches than those used for MODIS alone. This new approach includes two parallel efforts: (1) Imager-only algorithms with only spectral channels common to VIIRS and MODIS (i.e., eliminate use of MODIS CO2 and NIR/IR water vapor channels). Since the algorithms are run with similar spectral observations, they provide a basis for establishing a continuous cloud data record across the two imagers. (2) Merged imager and sounder measurements (i.e.., MODIS-AIRS, VIIRS-CrIS) in lieu of higher-spatial resolution MODIS absorption channels absent on VIIRS. The MODIS-VIIRS continuity algorithm for cloud optical property retrievals leverages heritage algorithms that produce the existing MODIS cloud mask (MOD35), optical and microphysical properties product (MOD06), and the NOAA AWG Cloud Height Algorithm (ACHA). We discuss our progress towards merging the MODIS observational record with VIIRS in order to generate cloud optical property climate data record continuity across the observing systems. In addition, we summarize efforts to reconcile apparent radiometric biases between analogous imager channels, a critical consideration for obtaining inter-sensor climate data record continuity.

Toward Unified Satellite Climatology of Aerosol Properties. 3. MODIS Versus MISR Versus AERONET

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Liu, Li; Geogdzhayev, Igor V.; Travis, Larry D.; Cairns, Brian; Lacis, Andrew A.

2010-01-01

We use the full duration of collocated pixel-level MODIS-Terra and MISR aerosol optical thickness (AOT) retrievals and level 2 cloud-screened quality-assured AERONET measurements to evaluate the likely individual MODIS and MISR retrieval accuracies globally over oceans and land. We show that the use of quality-assured MODIS AOTs as opposed to the use of all MODIS AOTs has little effect on the resulting accuracy. The MODIS and MISR relative standard deviations (RSTDs) with respect to AERONET are remarkably stable over the entire measurement record and reveal nearly identical overall AOT performances of MODIS and MISR over the entire suite of AERONET sites. This result is used to evaluate the likely pixel-level MODIS and MISR performances on the global basis with respect to the (unknown) actual AOTs. For this purpose, we use only fully compatible MISR and MODIS aerosol pixels. We conclude that the likely RSTDs for this subset of MODIS and MISR AOTs are 73% over land and 30% over oceans. The average RSTDs for the combined [AOT(MODIS)+AOT(MISR)]/2 pixel-level product are close to 66% and 27%, respectively, which allows us to recommend this simple blend as a better alternative to the original MODIS and MISR data. These accuracy estimates still do not represent the totality of MISR and quality-assured MODIS pixel-level AOTs since an unaccounted for and potentially significant source of errors is imperfect cloud screening. Furthermore, many collocated pixels for which one of the datasets reports a retrieval, whereas the other one does not may also be problematic.

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

MODIS comparisons with northeastern Pacific in situ stratocumulus microphysics

NASA Astrophysics Data System (ADS)

Noble, Stephen R.; Hudson, James G.

2015-08-01

Vertical sounding measurements within stratocumuli during two aircraft field campaigns, Marine Stratus/stratocumulus Experiment (MASE) and Physics of Stratocumulus Top (POST), are used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (re). In situ COT, LWP, and re were calculated using 5 m vertically averaged droplet probe measurements of complete vertical cloud penetrations. MODIS COT, LWP, and re 1 km pixels were averaged along these penetrations. COT comparisons in POST showed strong correlations and a near 1:1 relationship. In MASE, comparisons showed strong correlations; however, MODIS COT exceeded in situ COT, likely due to larger temporal differences between MODIS and in situ measurements. LWP comparisons between two cloud probes show good agreement for POST but not MASE, giving confidence to POST data. Both projects provided strong LWP correlations but MODIS exceeded in situ by 14-36%. MODIS in situ re correlations were strong, but MODIS 2.1 µm re exceeded in situ re, which contributed to LWP bias; in POST, MODIS re was 20-30% greater than in situ re. Maximum in situ re near cloud top showed comparisons nearer 1:1. Other MODIS re bands (3.7 µm and 1.6 µm) showed similar comparisons. Temporal differences between MODIS and in situ measurements, airplane speed differences, and cloud probe artifacts were likely causes of weaker MASE correlations. POST COT comparison was best for temporal differences under 20 min. POST data validate MODIS COT but it also implies a positive MODIS re bias that propagates to LWP while still capturing variability.

Effect of Cloud Fraction on Near-Cloud Aerosol Behavior Based on MODIS and CALIPSO Observations

NASA Technical Reports Server (NTRS)

Marshak, A.; Varnai, T.; Yang, W.

2015-01-01

Organizers of the MODIS-VIIRS Science Team Meeting, held May 18-22, 2015 in Silver Spring, MD plan to post the presentations and posters to the NASA MODIS website: http:modis.gsfc.nasa.govsci_teammeetings201505index.php. The MODIS Science Team Meeting is held twice a year, so that the members of the science team may assemble and discuss data they have collected, ideas they have formed, and future issues that apply to the MODIS Mission.

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.

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.

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.

No novel, high penetrant gene might remain to be found in Japanese patients with unknown MODY.

PubMed

Horikawa, Yukio; Hosomichi, Kazuyoshi; Enya, Mayumi; Ishiura, Hiroyuki; Suzuki, Yutaka; Tsuji, Shoji; Sugano, Sumio; Inoue, Ituro; Takeda, Jun

2018-07-01

MODY 5 and 6 have been shown to be low-penetrant MODYs. As the genetic background of unknown MODY is assumed to be similar, a new analytical strategy is applied here to elucidate genetic predispositions to unknown MODY. We examined to find whether there are major MODY gene loci remaining to be identified using SNP linkage analysis in Japanese. Whole-exome sequencing was performed with seven families with typical MODY. Candidates for novel MODY genes were examined combined with in silico network analysis. Some peaks were found only in either parametric or non-parametric analysis; however, none of these peaks showed a LOD score greater than 3.7, which is approved to be the significance threshold of evidence for linkage. Exome sequencing revealed that three mutated genes were common among 3 families and 42 mutated genes were common in two families. Only one of these genes, MYO5A, having rare amino acid mutations p.R849Q and p.V1601G, was involved in the biological network of known MODY genes through the intermediary of the INS. Although only one promising candidate gene, MYO5A, was identified, no novel, high penetrant MODY genes might remain to be found in Japanese MODY.

Precise and fast spatial-frequency analysis using the iterative local Fourier transform.

PubMed

Lee, Sukmock; Choi, Heejoo; Kim, Dae Wook

2016-09-19

The use of the discrete Fourier transform has decreased since the introduction of the fast Fourier transform (fFT), which is a numerically efficient computing process. This paper presents the iterative local Fourier transform (ilFT), a set of new processing algorithms that iteratively apply the discrete Fourier transform within a local and optimal frequency domain. The new technique achieves 2¹⁰ times higher frequency resolution than the fFT within a comparable computation time. The method's superb computing efficiency, high resolution, spectrum zoom-in capability, and overall performance are evaluated and compared to other advanced high-resolution Fourier transform techniques, such as the fFT combined with several fitting methods. The effectiveness of the ilFT is demonstrated through the data analysis of a set of Talbot self-images (1280 × 1024 pixels) obtained with an experimental setup using grating in a diverging beam produced by a coherent point source.

Improving Access to MODIS Biophysical Science Products for NACP Investigators

NASA Technical Reports Server (NTRS)

Wolfe, Robert E.; Gao, Feng; Morisette, Jeffrey T.; Ederer, Gregory A.; Pedelty, Jeffrey A.

2007-01-01

MODIS 4 NACP is a NASA-funded project supporting the North American Carbon Program (NACP). The purpose of this Advancing Collaborative Connections for Earth-Sun System Science (ACCESS) project is to provide researchers with Moderate Resolution Imaging Spectroradiometer (MODIS) biophysical data products that are custom tailored for use in NACP model studies. Standard MODIS biophysical products provide used to improve our understanding on the climate and ecosystem changes. However, direct uses of the MODIS biophysical parameters are constrained by retrieval quality and cloud contamination. Another challenge that NACP users face is acquiring MODIS data in formats and at spatial-temporal resolutions consistent with other data sets they use. We have been working closely with key NACP users to tailor the MODIS products to fit their needs. First, we provide new temporally smoothed and spatially continuous MODIS biophysical data sets. Second, we are distributing MODIS data at suitable spatial-temporal resolutions and in formats consistent with other data integration into model studies.

GES DAAC HDF Data Processing and Visualization Tools

NASA Astrophysics Data System (ADS)

Ouzounov, D.; Cho, S.; Johnson, J.; Li, J.; Liu, Z.; Lu, L.; Pollack, N.; Qin, J.; Savtchenko, A.; Teng, B.

2002-12-01

The Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) plays a major role in enabling basic scientific research and providing access to scientific data to the general user community. Several GES DAAC Data Support Teams provide expert assistance to users in accessing data, including information on visualization tools and documentation for data products. To provide easy access to the science data, the data support teams have additionally developed many online and desktop tools for data processing and visualization. This presentation is an overview of major HDF tools implemented at the GES DAAC and aimed at optimizing access to EOS data for the Earth Sciences community. GES DAAC ONLINE TOOLS: MODIS and AIRS on-demand Channel/Variable Subsetter are web-based, on-the-fly/on-demand subsetters that perform channel/variable subsetting and restructuring for Level1B and Level 2 data products. Users can specify criteria to subset data files with desired channels and variables and then download the subsetted file. AIRS QuickLook is a CGI/IDL combo package that allows users to view AIRS/HSB/AMSU Level-1B data online by specifying a channel prior to obtaining data. A global map is also provided along with the image to show geographic coverage of the granule and flight direction of the spacecraft. OASIS (Online data AnalySIS) is an IDL-based HTML/CGI interface for search, selection, and simple analysis of earth science data. It supports binary and GRIB formatted data, such as TOVS, Data Assimilation products, and some NCEP operational products. TRMM Online Analysis System is designed for quick exploration, analyses, and visualization of TRMM Level-3 and other precipitation products. The products consist of the daily (3B42), monthly(3B43), near-real-time (3B42RT), and Willmott's climate data. The system is also designed to be simple and easy to use - users can plot the average or accumulated rainfall over their region of interest for a given time period, or plot the time series of regional rainfall average. WebGIS is an online web software that implements the Open GIS Consortium (OGC) standards for mapping requests and rendering. It allows users access to TRMM, MODIS, SeaWiFS, and AVHRR data from several DAAC map servers, as well as externally served data such as political boundaries, population centers, lakes, rivers, and elevation. GES DAAC DESKTOP TOOLS: HDFLook-MODIS is a new, multifunctional, data processing and visualization tool for Radiometric and Geolocation, Atmosphere, Ocean, and Land MODIS HDF-EOS data. Features include (1) accessing and visualization of all swath (Levels l and 2) MODIS and AIRS products, and gridded (Levels 3 and 4) MODIS products; (2) re-mapping of swath data to world map; (3) geo-projection conversion; (4) interactive and batch mode capabilities; (5) subsetting and multi-granule processing; and (6) data conversion. SIMAP is an IDL-based script that is designed to read and map MODIS Level 1B (L1B) and Level 2 (L2) Ocean and Atmosphere products. It is a non-interactive, command line executed tool. The resulting maps are scaled to physical units (e.g., radiances, concentrations, brightness temperatures) and saved in binary files. TRMM HDF (in C and Fortran), reads in TRMM HDF data files and writes out user-selected SDS arrays and Vdata tables as separate flat binary files.

An optical Fourier transform coprocessor with direct phase determination.

PubMed

Macfaden, Alexander J; Gordon, George S D; Wilkinson, Timothy D

2017-10-20

The Fourier transform is a ubiquitous mathematical operation which arises naturally in optics. We propose and demonstrate a practical method to optically evaluate a complex-to-complex discrete Fourier transform. By implementing the Fourier transform optically we can overcome the limiting O(nlogn) complexity of fast Fourier transform algorithms. Efficiently extracting the phase from the well-known optical Fourier transform is challenging. By appropriately decomposing the input and exploiting symmetries of the Fourier transform we are able to determine the phase directly from straightforward intensity measurements, creating an optical Fourier transform with O(n) apparent complexity. Performing larger optical Fourier transforms requires higher resolution spatial light modulators, but the execution time remains unchanged. This method could unlock the potential of the optical Fourier transform to permit 2D complex-to-complex discrete Fourier transforms with a performance that is currently untenable, with applications across information processing and computational physics.

MODIS comparisons with northeastern Pacific in situ stratocumulus microphysics

PubMed Central

Noble, Stephen R.

2015-01-01

Abstract Vertical sounding measurements within stratocumuli during two aircraft field campaigns, Marine Stratus/stratocumulus Experiment (MASE) and Physics of Stratocumulus Top (POST), are used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (r e). In situ COT, LWP, and r e were calculated using 5 m vertically averaged droplet probe measurements of complete vertical cloud penetrations. MODIS COT, LWP, and r e 1 km pixels were averaged along these penetrations. COT comparisons in POST showed strong correlations and a near 1:1 relationship. In MASE, comparisons showed strong correlations; however, MODIS COT exceeded in situ COT, likely due to larger temporal differences between MODIS and in situ measurements. LWP comparisons between two cloud probes show good agreement for POST but not MASE, giving confidence to POST data. Both projects provided strong LWP correlations but MODIS exceeded in situ by 14–36%. MODIS in situ r e correlations were strong, but MODIS 2.1 µm r e exceeded in situ r e, which contributed to LWP bias; in POST, MODIS r e was 20–30% greater than in situ r e. Maximum in situ r e near cloud top showed comparisons nearer 1:1. Other MODIS r e bands (3.7 µm and 1.6 µm) showed similar comparisons. Temporal differences between MODIS and in situ measurements, airplane speed differences, and cloud probe artifacts were likely causes of weaker MASE correlations. POST COT comparison was best for temporal differences under 20 min. POST data validate MODIS COT but it also implies a positive MODIS r e bias that propagates to LWP while still capturing variability. PMID:27708990

MODIS comparisons with northeastern Pacific in situ stratocumulus microphysics

DOE PAGES

Noble, Stephen R.; Hudson, James G.

2015-07-22

Here, vertical sounding measurements within stratocumuli during two aircraft field campaigns, Marine Stratus/stratocumulus Experiment (MASE) and Physics of Stratocumulus Top (POST), are used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (r e). In situ COT, LWP, and r e were calculated using 5 m vertically averaged droplet probe measurements of complete vertical cloud penetrations. MODIS COT, LWP, and r e 1 km pixels were averaged along these penetrations. COT comparisons in POST showed strong correlations and a near 1:1 relationship. In MASE, comparisons showed strong correlations; however,more » MODIS COT exceeded in situ COT, likely due to larger temporal differences between MODIS and in situ measurements. LWP comparisons between two cloud probes show good agreement for POST but not MASE, giving confidence to POST data. Both projects provided strong LWP correlations but MODIS exceeded in situ by 14–36%. MODIS in situ r e correlations were strong, but MODIS 2.1 µm r e exceeded in situ r e, which contributed to LWP bias; in POST, MODIS r e was 20–30% greater than in situ r e. Maximum in situ r e near cloud top showed comparisons nearer 1:1. Other MODIS r e bands (3.7 µm and 1.6 µm) showed similar comparisons. Temporal differences between MODIS and in situ measurements, airplane speed differences, and cloud probe artifacts were likely causes of weaker MASE correlations. POST COT comparison was best for temporal differences under 20 min. POST data validate MODIS COT but it also implies a positive MODIS r e bias that propagates to LWP while still capturing variability.« less

A Real-Time MODIS Vegetation Composite for Land Surface Models and Short-Term Forecasting

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.; Jedlovec, Gary J.

2011-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center is producing real-time, 1- km resolution Normalized Difference Vegetation Index (NDVI) gridded composites over a Continental U.S. domain. These composites are updated daily based on swath data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the polar orbiting NASA Aqua and Terra satellites, with a product time lag of about one day. A simple time-weighting algorithm is applied to the NDVI swath data that queries the previous 20 days of data to ensure a continuous grid of data populated at all pixels. The daily composites exhibited good continuity both spatially and temporally during June and July 2010. The composites also nicely depicted high greenness anomalies that resulted from significant rainfall over southwestern Texas, Mexico, and New Mexico during July due to early-season tropical cyclone activity. The SPoRT Center is in the process of computing greenness vegetation fraction (GVF) composites from the MODIS NDVI data at the same spatial and temporal resolution for use in the NASA Land Information System (LIS). The new daily GVF dataset would replace the monthly climatological GVF database (based on Advanced Very High Resolution Radiometer [AVHRR] observations from 1992-93) currently available to the Noah land surface model (LSM) in both LIS and the public version of the Weather Research and Forecasting (WRF) model. The much higher spatial resolution (1 km versus 0.15 degree) and daily updates based on real-time satellite observations have the capability to greatly improve the simulation of the surface energy budget in the Noah LSM within LIS and WRF. Once code is developed in LIS to incorporate the daily updated GVFs, the SPoRT Center will conduct simulation sensitivity experiments to quantify the impacts and improvements realized by the MODIS real-time GVF data. This presentation will describe the methodology used to develop the 1-km MODIS NDVI composites and show sample output from summer 2010, compare the MODIS GVF data to the AVHRR monthly climatology, and illustrate the sensitivity of the Noah LSM within LIS and/or the coupled LIS/WRF system to the new MODIS GVF dataset.

Detecting Soil Moisture Related Impacts on Gross Primary Productivity using the MODIS-based Photochemical Reflectance Index

NASA Astrophysics Data System (ADS)

He, M.; Kimball, J. S.; Running, S. W.; Ballantyne, A.; Guan, K.; Huemmrich, K. F.

2016-12-01

Satellite remote sensing provides continuous observations of vegetation properties that can be used to estimate ecosystem gross primary production (GPP). The Photochemical Reflectance Index (PRI) has been shown to be sensitive to photosynthetic light use efficiency (LUE), GPP and canopy water-stress. The NASA EOS MODIS (Moderate Resolution Imaging Spectroradiometer) sensor provides potential PRI estimation globally at daily time step and 1-km spatial resolution for more than 10 years. Here, we use the MODIS based PRI with eddy covariance CO2 flux measurements and meteorological observations from 20 tower sites representing 5 major plant functional types (PFT) within the continental USA (CONUS) to assess GPP sensitivity to seasonal water supply variability. The sPRI (scaled PRI) derived using MODIS band 13 as a reference band (sPRI13) generally shows higher correspondence with tower GPP observations than other potential MODIS reference bands (MODIS band 1, 4, 10 and 12). The sPRI13 was used to represent soil moisture related water supply constraints to LUE within a terrestrial carbon flux model to estimate GPP (GPPPRI). The GPPPRI calculations show generally strong relationships with tower GPP observations (0.457 ≤ R2 ≤ 0.818), except for lower GPPPRI performance over evergreen needleleaf forest (ENF) sites. A regional model sensitivity analysis using the sPRI13 as a proxy for soil moisture related water supply limits indicated that water restrictions limit GPP over more than 21% of the CONUS domain, particularly in northwest and southwest CONUS subregions, and drier climate areas where atmospheric moisture deficits (VPD) alone are insufficient to represent both atmosphere demand and soil water supply controls affecting productivity. Our results indicate strong potential of the MODIS sPRI13 to represent GPP sensitivity to seasonal soil moisture related water supply variability, with enhanced (1-km resolution) delineation of these processes closer to the scale of in situ tower observations, providing an effective tool to characterize sub-grid spatial heterogeneity in soil moisture related water supply controls that inform coarser scale observations and estimates determined from other satellite observations and global carbon, and climate models.

Generalized Fourier slice theorem for cone-beam image reconstruction.

PubMed

Zhao, Shuang-Ren; Jiang, Dazong; Yang, Kevin; Yang, Kang

2015-01-01

The cone-beam reconstruction theory has been proposed by Kirillov in 1961, Tuy in 1983, Feldkamp in 1984, Smith in 1985, Pierre Grangeat in 1990. The Fourier slice theorem is proposed by Bracewell 1956, which leads to the Fourier image reconstruction method for parallel-beam geometry. The Fourier slice theorem is extended to fan-beam geometry by Zhao in 1993 and 1995. By combining the above mentioned cone-beam image reconstruction theory and the above mentioned Fourier slice theory of fan-beam geometry, the Fourier slice theorem in cone-beam geometry is proposed by Zhao 1995 in short conference publication. This article offers the details of the derivation and implementation of this Fourier slice theorem for cone-beam geometry. Especially the problem of the reconstruction from Fourier domain has been overcome, which is that the value of in the origin of Fourier space is 0/0. The 0/0 type of limit is proper handled. As examples, the implementation results for the single circle and two perpendicular circle source orbits are shown. In the cone-beam reconstruction if a interpolation process is considered, the number of the calculations for the generalized Fourier slice theorem algorithm is O(N^4), which is close to the filtered back-projection method, here N is the image size of 1-dimension. However the interpolation process can be avoid, in that case the number of the calculations is O(N5).

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.

Role of MODIS Vegetation Phenology Products in the ForWarn System for Monitoring of Forest Disturbances in the Conterminous United States

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hargrove, William; Norman, Steve; Gasser, Jerry; Smoot, James; Kuper, Philip D,

2012-01-01

This presentation discusses MODIS vegetation phenology products used in the ForWarn Early Warning System (EWS) tool for near real time regional forest disturbance detection and surveillance at regional to national scales. The ForWarn EWS is being developed by the USDA Forest Service NASA, ORNL, and USGS to aid federal and state forest health management activities. ForWarn employs multiple historical land surface phenology products that are derived from MODIS MOD13 Normalized Difference Vegetation Index (NDVI) data. The latter is temporally processed into phenology products with the Time Series Product Tool (TSPT) and the Phenological Parameter Estimation Tool (PPET) software produced at NASA Stennis Space Center. TSPT is used to effectively noise reduce, fuse, and void interpolate MODIS NDVI data. PPET employs TSPT-processed NDVI time series data as an input, outputting multiple vegetation phenology products at a 232 meter resolution for 2000 to 2011, including NDVI magnitude and day of year products for seven key points along the growing season (peak of growing season and the minima, 20%, and 80% of the peak NDVI for both the left and right side of growing season), cumulative NDVI integral products for the most active part of the growing season and sequentially across the growing season at 8 day intervals, and maximum value NDVI products composited at 24 day intervals in which each product date has 8 days of overlap between the previous and following product dates. MODIS NDVI phenology products are also used to compute nationwide NRT forest change products refreshed every 8 days. These include percent change in forest NDVI products that compare the current NDVI from USGS eMODIS products to historical MODIS MOD13 NDVI. For each date, three forest change products are produced using three different maximum value NDVI baselines (from the previous year, three previous years, and all previous years). All change products are output with a rainbow color table in which forests with the most severe NDVI decreases are assigned hot colors (yellow to red) and forests with prominent NDVI increases are assigned cold colors (blue tones). All mentioned products have been integrated as data layers into ForWarn s geospatial data viewer known as the U.S. Forest Change Assessment Viewer (FCAV). The latter is used to view and assess the context of the mentioned forest change products with respect to ancillary data layers, such as land cover, elevation, hydrologic features, climatic data, storm data, aerial disturbance surveys, fire data, and land ownership. The FCAV also includes a temporal NDVI profiler for viewing phenological change in multi-year NDVI associated with known or suspected regionally apparent forest disturbances (e.g., from fire and insects). ForWarn forest change products have been used to detect, track, and assess several biotic and abiotic regional forest disturbance events across the country, including ephemeral and longer lasting damage from storms, drought, and insects. Such change products are most effective for viewing severe disturbances affecting multiple MODIS pixels. MODIS vegetation phenology products contribute vital current information on forest conditions to the ForWarn system and this role is expected to grow as these products are refined and derivative products are added.

Update of NASA's ocean colour activities

NASA Technical Reports Server (NTRS)

Yoder, J. A.

1987-01-01

The NIMBUS-7 Coastal Zone Color Scanner (CZCS) status and processing are reviewed, and future American ocean color instruments are introduced. The CZCS is probably dead, but an attempt to restart it is planned. A wide field instrument for LANDSAT-6 and 7 (WIFS) and a wiskbroom imaging spectrometer (MODIS-T) for Columbus Polar Platforms are outlined. The WIFS and MODIS-T specifications are similar: 64 bands in the range 400 to 1030 nm, with 15 to 30 nm bandwidth; 1 km resolution from 850 km altitude; 64 km footprint along track; 1500 km scan across track; and 10 yr continuous operation life.

Validating data analysis of broadband laser ranging

NASA Astrophysics Data System (ADS)

Rhodes, M.; Catenacci, J.; Howard, M.; La Lone, B.; Kostinski, N.; Perry, D.; Bennett, C.; Patterson, J.

2018-03-01

Broadband laser ranging combines spectral interferometry and a dispersive Fourier transform to achieve high-repetition-rate measurements of the position of a moving surface. Telecommunications fiber is a convenient tool for generating the large linear dispersions required for a dispersive Fourier transform, but standard fiber also has higher-order dispersion that distorts the Fourier transform. Imperfections in the dispersive Fourier transform significantly complicate the ranging signal and must be dealt with to make high-precision measurements. We describe in detail an analysis process for interpreting ranging data when standard telecommunications fiber is used to perform an imperfect dispersive Fourier transform. This analysis process is experimentally validated over a 27-cm scan of static positions, showing an accuracy of 50 μm and a root-mean-square precision of 4.7 μm.

15 CFR Supplement No. 6 to Part 774 - Sensitive List

Code of Federal Regulations, 2014 CFR

2014-01-01

... filtering and beamforming using Fast Fourier or other transforms or processes. (vi) 6A001.a.2.d. (vii) 6A001... processing and correlation, including spectral analysis, digital filtering and beamforming using Fast Fourier...

Near-real-time Estimation and Forecast of Total Precipitable Water in Europe

NASA Astrophysics Data System (ADS)

Bartholy, J.; Kern, A.; Barcza, Z.; Pongracz, R.; Ihasz, I.; Kovacs, R.; Ferencz, C.

2013-12-01

Information about the amount and spatial distribution of atmospheric water vapor (or total precipitable water) is essential for understanding weather and the environment including the greenhouse effect, the climate system with its feedbacks and the hydrological cycle. Numerical weather prediction (NWP) models need accurate estimations of water vapor content to provide realistic forecasts including representation of clouds and precipitation. In the present study we introduce our research activity for the estimation and forecast of atmospheric water vapor in Central Europe using both observations and models. The Eötvös Loránd University (Hungary) operates a polar orbiting satellite receiving station in Budapest since 2002. This station receives Earth observation data from polar orbiting satellites including MODerate resolution Imaging Spectroradiometer (MODIS) Direct Broadcast (DB) data stream from satellites Terra and Aqua. The received DB MODIS data are automatically processed using freely distributed software packages. Using the IMAPP Level2 software total precipitable water is calculated operationally using two different methods. Quality of the TPW estimations is a crucial question for further application of the results, thus validation of the remotely sensed total precipitable water fields is presented using radiosonde data. In a current research project in Hungary we aim to compare different estimations of atmospheric water vapor content. Within the frame of the project we use a NWP model (DBCRAS; Direct Broadcast CIMSS Regional Assimilation System numerical weather prediction software developed by the University of Wisconsin, Madison) to forecast TPW. DBCRAS uses near real time Level2 products from the MODIS data processing chain. From the wide range of the derived Level2 products the MODIS TPW parameter found within the so-called mod07 results (Atmospheric Profiles Product) and the cloud top pressure and cloud effective emissivity parameters from the so-called mod06 results (Cloud Product) are assimilated twice a day (at 00 and 12 UTC) by DBCRAS. DBCRAS creates 72 hours long weather forecasts with 48 km horizontal resolution. DBCRAS is operational at the University since 2009 which means that by now sufficient data is available for the verification of the model. In the present study verification results for the DBCRAS total precipitable water forecasts are presented based on analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Numerical indices are calculated to quantify the performance of DBCRAS. During a limited time period DBCRAS was also ran without assimilating MODIS products which means that there is possibility to quantify the effect of assimilating MODIS physical products on the quality of the forecasts. For this limited time period verification indices are compared to decide whether MODIS data improves forecast quality or not.

Simple and Efficient Technique for Spatial/Temporal Composite Imagery

DTIC Science & Technology

2007-08-01

visible spectrum between 412nm and 869nm, three bands at 500m and two bands at 250m. The MODIS data was processed using the Automated Processing System2...Version 3.6 developed by the Naval Research Labo- ratory (NRL). The Automated Processing System (APS) is a collection of software programs assembled

Validation of MODIS aerosol optical depth over the Mediterranean Coast

NASA Astrophysics Data System (ADS)

Díaz-Martínez, J. Vicente; Segura, Sara; Estellés, Víctor; Utrillas, M. Pilar; Martínez-Lozano, J. Antonio

2013-04-01

Atmospheric aerosols, due to their high spatial and temporal variability, are considered one of the largest sources of uncertainty in different processes affecting visibility, air quality, human health, and climate. Among their effects on climate, they play an important role in the energy balance of the Earth. On one hand they have a direct effect by scattering and absorbing solar radiation; on the other, they also have an impact in precipitation, modifying clouds, or affecting air quality. The application of remote sensing techniques to investigate aerosol effects on climate has advanced significatively over last years. In this work, the products employed have been obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). MODIS is a sensor located onboard both Earth Observing Systems (EOS) Terra and Aqua satellites, which provide almost complete global coverage every day. These satellites have been acquiring data since early 2000 (Terra) and mid 2002 (Aqua) and offer different products for land, ocean and atmosphere. Atmospheric aerosol products are presented as level 2 products with a pixel size of 10 x 10 km2 in nadir. MODIS aerosol optical depth (AOD) is retrieved by different algorithms depending on the pixel surface, distinguishing between land and ocean. For its validation, ground based sunphotometer data from AERONET (Aerosol Robotic Network) has been employed. AERONET is an international operative network of Cimel CE318 sky-sunphotometers that provides the most extensive aerosol data base globally available of ground-based measurements. The ground sunphotometric technique is considered the most accurate for the retrieval of radiative properties of aerosols in the atmospheric column. In this study we present a validation of MODIS C051 AOD employing AERONET measurements over different Mediterranean coastal sites centered over an area of 50 x 50 km2, which includes both pixels over land and ocean. The validation is done comparing spatial statistics from MODIS with corresponding temporal statistics from AERONET, as proposed by Ichoku et al. (2002). Eight Mediterranean coastal sites (in Spain, France, Italy, Crete, Turkey and Israel) with available AERONET and MODIS data have been used. These stations have been selected following QA criteria (minimum 1000 days of level 2.0 data) and a maximum distance of 8 km from the coast line. Results of the validation over each site show analogous behaviour, giving similar results regarding to the accuracy of the algorithms. Greatest differences are found for the AOD obtained over land, especially for drier regions, where the surface tends to be brighter. In general, the MODIS AOD has better a agreement with AERONET retrievals for the ocean algorithm than the land algorithm when validated over coastal sites, and the agreement is within the expected uncertainty estimated for MODIS data. References: - C. Ichoku et al., "A spatio-temporal approach for global validation and analysis of MODIS aerosol products", Geophysical Research Letters, 219, 12, 10.1029/2001GL013206, 2002.

Analysis of MODIS snow cover time series over the alpine regions as input for hydrological modeling

NASA Astrophysics Data System (ADS)

Notarnicola, Claudia; Rastner, Philipp; Irsara, Luca; Moelg, Nico; Bertoldi, Giacomo; Dalla Chiesa, Stefano; Endrizzi, Stefano; Zebisch, Marc

2010-05-01

Snow extent and relative physical properties are key parameters in hydrology, weather forecast and hazard warning as well as in climatological models. Satellite sensors offer a unique advantage in monitoring snow cover due to their temporal and spatial synoptic view. The Moderate Resolution Imaging Spectrometer (MODIS) from NASA is especially useful for this purpose due to its high frequency. However, in order to evaluate the role of snow on the water cycle of a catchment such as runoff generation due to snowmelt, remote sensing data need to be assimilated in hydrological models. This study presents a comparison on a multi-temporal basis between snow cover data derived from (1) MODIS images, (2) LANDSAT images, and (3) predictions by the hydrological model GEOtop [1,3]. The test area is located in the catchment of the Matscher Valley (South Tyrol, Northern Italy). The snow cover maps derived from MODIS-images are obtained using a newly developed algorithm taking into account the specific requirements of mountain regions with a focus on the Alps [2]. This algorithm requires the standard MODIS-products MOD09 and MOD02 as input data and generates snow cover maps at a spatial resolution of 250 m. The final output is a combination of MODIS AQUA and MODIS TERRA snow cover maps, thus reducing the presence of cloudy pixels and no-data-values due to topography. By using these maps, daily time series starting from the winter season (November - May) 2002 till 2008/2009 have been created. Along with snow maps from MODIS images, also some snow cover maps derived from LANDSAT images have been used. Due to their high resolution (< 30 m) they have been considered as an evaluation tool. The snow cover maps are then compared with the hydrological GEOtop model outputs. The main objectives of this work are: 1. Evaluation of the MODIS snow cover algorithm using LANDSAT data 2. Investigation of snow cover, and snow cover duration for the area of interest for South Tyrol 3. Derivation and interpretation of the snow line for the seven winter seasons 4. An evaluation of the model outputs in order to determine the situations in which the remotely sensed data can be used to improve the model prediction of snow coverage and related variables References [1] Rigon R., Bertoldi G. and Over T.M. 2006. GEOtop: A Distributed Hydrological Model with Coupled Water and Energy Budgets, Journal of Hydrometeorology, 7: 371-388. [2] Rastner P., Irsara L., Schellenberger T., Della Chiesa S., Bertoldi G., Endrizzi S., Notarnicola C., Steurer C., Zebisch M. 2009. Monitoraggio del manto nevoso in aree alpine con dati MODIS multi-temporali e modelli idrologici, 13th ASITA National Conference, 1-4.12.2009, Bari, Italy. [3] Zanotti F., Endrizzi S., Bertoldi G. and Rigon R. 2004. The GEOtop snow module. Hydrological Processes, 18: 3667-3679. DOI:10.1002/hyp.5794.

Suomi NPP VIIRS active fire product status

NASA Astrophysics Data System (ADS)

Ellicott, E. A.; Csiszar, I. A.; Schroeder, W.; Giglio, L.; Wind, B.; Justice, C. O.

2012-12-01

We provide an overview of the evaluation and development of the Active Fires product derived from the Visible Infrared Imager Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (SNPP) satellite during the first year of on-orbit data. Results from the initial evaluation of the standard SNPP Active Fires product, generated by the SNPP Interface Data Processing System (IDPS), supported the stabilization of the VIIRS Sensor Data Record (SDR) product. This activity focused in particular on the processing of the dual-gain 4 micron VIIRS M13 radiometric measurements into 750m aggregated data, which are fundamental for active fire detection. Following the VIIRS SDR product's Beta maturity status in April 2012, correlative analysis between VIIRS and near-simultaneous fire detections from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System Aqua satellite confirmed the expected relative detection rates driven primarily by sensor differences. The VIIRS Active Fires Product Development and Validation Team also developed a science code that is based on the latest MODIS Collection 6 algorithm and provides a full spatially explicit fire mask to replace the sparse array output of fire locations from a MODIS Collection 4 equivalent algorithm in the current IDPS product. The Algorithm Development Library (ADL) was used to support the planning for the transition of the science code into IDPS operations in the future. Product evaluation and user outreach was facilitated by a product website that provided end user access to fire data in user-friendly format over North America as well as examples of VIIRS-MODIS comparisons. The VIIRS fire team also developed an experimental product based on 375m VIIRS Imagery band measurements and provided high quality imagery of major fire events in US. By August 2012 the IDPS product achieved Beta maturity, with some known and documented shortfalls related to the processing of incorrect SDR input data and to apparent algorithm deficiencies in select observing and environmental conditions.

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.

Systematic errors in temperature estimates from MODIS data covering the western Palearctic and their impact on a parasite development model.

PubMed

Alonso-Carné, Jorge; García-Martín, Alberto; Estrada-Peña, Agustin

2013-11-01

The modelling of habitat suitability for parasites is a growing area of research due to its association with climate change and ensuing shifts in the distribution of infectious diseases. Such models depend on remote sensing data and require accurate, high-resolution temperature measurements. The temperature is critical for accurate estimation of development rates and potential habitat ranges for a given parasite. The MODIS sensors aboard the Aqua and Terra satellites provide high-resolution temperature data for remote sensing applications. This paper describes comparative analysis of MODIS-derived temperatures relative to ground records of surface temperature in the western Palaearctic. The results show that MODIS overestimated maximum temperature values and underestimated minimum temperatures by up to 5-6 °C. The combined use of both Aqua and Terra datasets provided the most accurate temperature estimates around latitude 35-44° N, with an overestimation during spring-summer months and an underestimation in autumn-winter. Errors in temperature estimation were associated with specific ecological regions within the target area as well as technical limitations in the temporal and orbital coverage of the satellites (e.g. sensor limitations and satellite transit times). We estimated error propagation of temperature uncertainties in parasite habitat suitability models by comparing outcomes of published models. Error estimates reached 36% of annual respective measurements depending on the model used. Our analysis demonstrates the importance of adequate image processing and points out the limitations of MODIS temperature data as inputs into predictive models concerning parasite lifecycles.

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.

Remote sensing of cirrus cloud vertical size profile using MODIS data

NASA Astrophysics Data System (ADS)

Wang, Xingjuan; Liou, K. N.; Ou, Steve S. C.; Mace, G. G.; Deng, M.

2009-05-01

This paper describes an algorithm for inferring cirrus cloud top and cloud base effective particle sizes and cloud optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS) 0.645, 1.64 and 2.13, and 3.75 μm band reflectances/radiances. This approach uses a successive minimization method based on a look-up library of precomputed reflectances/radiances from an adding-doubling radiative transfer program, subject to corrections for Rayleigh scattering at the 0.645 μm band, above-cloud water vapor absorption, and 3.75 μm thermal emission. The algorithmic accuracy and limitation of the retrieval method were investigated by synthetic retrievals subject to the instrument noise and the perturbation of input parameters. The retrieval algorithm was applied to three MODIS cirrus scenes over the Atmospheric Radiation Measurement Program's southern Great Plain site, north central China, and northeast Asia. The reliability of retrieved cloud optical thicknesses and mean effective particle sizes was evaluated by comparison with MODIS cloud products and qualitatively good correlations were obtained for all three cases, indicating that the performance of the vertical sizing algorithm is comparable with the MODIS retrieval program. Retrieved cloud top and cloud base ice crystal effective sizes were also compared with those derived from the collocated ground-based millimeter wavelength cloud radar for the first case and from the Cloud Profiling Radar onboard CloudSat for the other two cases. Differences between retrieved and radar-derived cloud properties are discussed in light of assumptions made in the collocation process and limitations in radar remote sensing characteristics.

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.

Anopheles atroparvus density modeling using MODIS NDVI in a former malarious area in Portugal.

PubMed

Lourenço, Pedro M; Sousa, Carla A; Seixas, Júlia; Lopes, Pedro; Novo, Maria T; Almeida, A Paulo G

2011-12-01

Malaria is dependent on environmental factors and considered as potentially re-emerging in temperate regions. Remote sensing data have been used successfully for monitoring environmental conditions that influence the patterns of such arthropod vector-borne diseases. Anopheles atroparvus density data were collected from 2002 to 2005, on a bimonthly basis, at three sites in a former malarial area in Southern Portugal. The development of the Remote Vector Model (RVM) was based upon two main variables: temperature and the Normalized Differential Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite. Temperature influences the mosquito life cycle and affects its intra-annual prevalence, and MODIS NDVI was used as a proxy for suitable habitat conditions. Mosquito data were used for calibration and validation of the model. For areas with high mosquito density, the model validation demonstrated a Pearson correlation of 0.68 (p<0.05) and a modelling efficiency/Nash-Sutcliffe of 0.44 representing the model's ability to predict intra- and inter-annual vector density trends. RVM estimates the density of the former malarial vector An. atroparvus as a function of temperature and of MODIS NDVI. RVM is a satellite data-based assimilation algorithm that uses temperature fields to predict the intra- and inter-annual densities of this mosquito species using MODIS NDVI. RVM is a relevant tool for vector density estimation, contributing to the risk assessment of transmission of mosquito-borne diseases and can be part of the early warning system and contingency plans providing support to the decision making process of relevant authorities. © 2011 The Society for Vector Ecology.

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.

Maturity-onset diabetes of the young as a model for elucidating the multifactorial origin of type 2 diabetes mellitus.

PubMed

Horikawa, Yukio

2018-02-06

Maturity-onset diabetes of the young (MODY) is a form of diabetes classically characterized as having autosomal dominant inheritance, onset before the age of 25 years in at least one family member and partly preserved pancreatic β-cell function. The 14 responsible genes are reported to be MODY type 1~14, of which MODY 2 and 3 might be the most common forms. Although MODY is currently classified as diabetes of a single gene defect, it has become clear that mutations in rare MODYs, such as MODY 5 and MODY 6, have small mutagenic effects and low penetrance. In addition, as there are differences in the clinical phenotypes caused by the same mutation even in the same family, other phenotypic modifying factors are thought to exist; MODY could well have characteristics of type 2 diabetes mellitus, which is of multifactorial origin. Here, we outline the effects of genetic and environmental factors on the known phenotypes of MODY, focusing mainly on the examples of MODY 5 and 6, which have low penetrance, as suggestive models for elucidating the multifactorial origin of type 2 diabetes mellitus. © 2018 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.

Beyond Fourier

NASA Astrophysics Data System (ADS)

Hoch, Jeffrey C.

2017-10-01

Non-Fourier methods of spectrum analysis are gaining traction in NMR spectroscopy, driven by their utility for processing nonuniformly sampled data. These methods afford new opportunities for optimizing experiment time, resolution, and sensitivity of multidimensional NMR experiments, but they also pose significant challenges not encountered with the discrete Fourier transform. A brief history of non-Fourier methods in NMR serves to place different approaches in context. Non-Fourier methods reflect broader trends in the growing importance of computation in NMR, and offer insights for future software development.

Quantitative assessment of AOD from 17 CMIP5 models based on satellite-derived AOD over India

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

Misra, Amit; Kanawade, Vijay P.; Tripathi, Sachchida Nand

Aerosol optical depth (AOD) values from 17 CMIP5 models are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) derived AODs over India. The objective is to identify the cases of successful AOD simulation by CMIP5 models, considering satellite-derived AOD as a benchmark. Six years of AOD data (2000–2005) from MISR and MODIS are processed to create quality-assured gridded AOD maps over India, which are compared with corresponding maps of 17 CMIP5 models at the same grid resolution. Intercomparison of model and satellite data shows that model-AOD is better correlated with MISR-derived AOD than MODIS. The correlation between model-AOD andmore » MISR-AOD is used to segregate the models into three categories identifying their performance in simulating the AOD over India. Maps of correlation between model-AOD and MISR-/MODIS-AOD are generated to provide quantitative information about the intercomparison. The two sets of data are examined for different seasons and years to examine the seasonal and interannual variation in the correlation coefficients. In conclusion, latitudinal and longitudinal variations in AOD as simulated by models are also examined and compared with corresponding variations observed by satellites.« less

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.

Quantitative assessment of AOD from 17 CMIP5 models based on satellite-derived AOD over India

DOE PAGES

Misra, Amit; Kanawade, Vijay P.; Tripathi, Sachchida Nand

2016-08-03

Aerosol optical depth (AOD) values from 17 CMIP5 models are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) derived AODs over India. The objective is to identify the cases of successful AOD simulation by CMIP5 models, considering satellite-derived AOD as a benchmark. Six years of AOD data (2000–2005) from MISR and MODIS are processed to create quality-assured gridded AOD maps over India, which are compared with corresponding maps of 17 CMIP5 models at the same grid resolution. Intercomparison of model and satellite data shows that model-AOD is better correlated with MISR-derived AOD than MODIS. The correlation between model-AOD andmore » MISR-AOD is used to segregate the models into three categories identifying their performance in simulating the AOD over India. Maps of correlation between model-AOD and MISR-/MODIS-AOD are generated to provide quantitative information about the intercomparison. The two sets of data are examined for different seasons and years to examine the seasonal and interannual variation in the correlation coefficients. In conclusion, latitudinal and longitudinal variations in AOD as simulated by models are also examined and compared with corresponding variations observed by satellites.« less

Optical properties of aerosol contaminated cloud derived from MODIS instrument

NASA Astrophysics Data System (ADS)

Mei, Linlu; Rozanov, Vladimir; Lelli, Luca; Vountas, Marco; Burrows, John P.

2016-04-01

The presence of absorbing aerosols above/within cloud can reduce the amount of up-welling radiation in visible (VIS) and short-wave infrared and darken the spectral reflectance when compared with a spectrum of a clean cloud observed by satellite instruments (Jethva et al., 2013). Cloud properties retrieval for aerosol contaminated cases is a great challenge. Even small additional injection of aerosol particles into clouds in the cleanest regions of Earth's atmosphere will cause significant effect on those clouds and on climate forcing (Koren et al., 2014; Rosenfeld et al., 2014) because the micro-physical cloud process are non-linear with respect to the aerosol loading. The current cloud products like Moderate Resolution Imaging Spectroradiometer (MODIS) ignoring the aerosol effect for the retrieval, which may cause significant error in the satellite-derived cloud properties. In this paper, a new cloud properties retrieval method, considering aerosol effect, based on the weighting-function (WF) method, is presented. The retrieval results shows that the WF retrieved cloud properties (e.g COT) agrees quite well with MODIS COT product for relative clear atmosphere (AOT ≤ 0.4) while there is a large difference for large aerosol loading. The MODIS COT product is underestimated for at least 2 - 3 times for AOT>0.4, and this underestimation increases with the increase of AOT.

MODIS Views North Pole

NASA Technical Reports Server (NTRS)

2002-01-01

This true-color image over the North Pole was acquired by the MODerate-resolution Imaging Spectroradiometer (MODIS), flying aboard the Terra spacecraft, on May 5, 2000. The scene was received and processed by Norway's MODIS Direct Broadcast data receiving station, located in Svalbard, within seconds of photons hitting the sensor's detectors. (Click for more details about MODIS Direct Broadcast data.) In this image, the sea ice appears white and areas of open water, or recently refrozen sea surface, appear black. The irregular whitish shapes toward the bottom of the image are clouds, which are often difficult to distinguish from the white Arctic surface. Notice the considerable number of cracks, or 'leads,' in the ice that appear as dark networks of lines. Throughout the region within the Arctic Circle leads are continually opening and closing due to the direction and intensity of shifting wind and ocean currents. Leads are particularly common during the summer, when temperatures are higher and the ice is thinner. In this image, each pixel is one square kilometer. Such true-color views of the North Pole are quite rare, as most of the time much of the region within the Arctic Circle is cloaked in clouds. Image by Allen Lunsford, NASA GSFC Direct Readout Laboratory; Data courtesy Tromso receiving station, Svalbard, Norway

The vector radiative transfer numerical model of coupled ocean-atmosphere system using the matrix-operator method

NASA Astrophysics Data System (ADS)

Xianqiang, He; Delu, Pan; Yan, Bai; Qiankun, Zhu

2005-10-01

The numerical model of the vector radiative transfer of the coupled ocean-atmosphere system is developed based on the matrix-operator method, which is named PCOART. In PCOART, using the Fourier analysis, the vector radiative transfer equation (VRTE) splits up into a set of independent equations with zenith angle as only angular coordinate. Using the Gaussian-Quadrature method, VRTE is finally transferred into the matrix equation, which is calculated by using the adding-doubling method. According to the reflective and refractive properties of the ocean-atmosphere interface, the vector radiative transfer numerical model of ocean and atmosphere is coupled in PCOART. By comparing with the exact Rayleigh scattering look-up-table of MODIS(Moderate-resolution Imaging Spectroradiometer), it is shown that PCOART is an exact numerical calculation model, and the processing methods of the multi-scattering and polarization are correct in PCOART. Also, by validating with the standard problems of the radiative transfer in water, it is shown that PCOART could be used to calculate the underwater radiative transfer problems. Therefore, PCOART is a useful tool to exactly calculate the vector radiative transfer of the coupled ocean-atmosphere system, which can be used to study the polarization properties of the radiance in the whole ocean-atmosphere system and the remote sensing of the atmosphere and ocean.

Maturity-onset diabetes of the young (MODY): an update.

PubMed

Anık, Ahmet; Çatlı, Gönül; Abacı, Ayhan; Böber, Ece

2015-03-01

Maturity-onset diabetes of the young (MODY) is a group of monogenic disorders characterized by autosomal dominantly inherited non-insulin dependent form of diabetes classically presenting in adolescence or young adults before the age of 25 years. MODY is a rare cause of diabetes (1% of all cases) and is frequently misdiagnosed as Type 1 diabetes (T1DM) or Type 2 diabetes (T2DM). A precise molecular diagnosis is essential because it leads to optimal treatment of the patients and allows early diagnosis for their asymptomatic family members. Mutations in the glucokinase (GCK) (MODY 2) and hepatocyte nuclear factor (HNF)1A/4A (MODY 3 and MODY 1) genes are the most common causes of MODY. GCK mutations cause a mild, asymptomatic, and stable fasting hyperglycemia usually requiring no specific treatment. However, mutations in the HNF1A and HNF4A cause a progressive pancreatic β-cell dysfunction and hyperglycemia that can result in microvascular complications. Sulfonylureas are effective in these patients by acting on adenosine triphosphate (ATP)-sensitive potassium channels, although insulin therapy may be required later in life. Mutations in the HNF1B (MODY 5) is associated with pancreatic agenesis, renal abnormalities, genital tract malformations, and liver dysfunction. Compared to MODY 1, 2, 3, and 5, the remaining subtypes of MODY have a much lower prevalence. In this review, we summarize the main clinical and laboratory characteristics of the common and rarer causes of MODY.

A Blended Global Snow Product using Visible, Passive Microwave and Scatterometer Satellite Data

NASA Technical Reports Server (NTRS)

Foster, James L.; Hall, Dorothy K.; Eylander, John B.; Riggs, George A.; Nghiem, Son V.; Tedesco, Marco; Kim, Edward; Montesano, Paul M.; Kelly, Richard E. J.; Casey, Kimberly A.;

Remote sensing evaluation of CLM4 GPP for the period 2000 to 2009

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

Mao, Jiafu; Thornton, Peter E; Shi, Xiaoying

2012-01-01

The ability of a process-based ecosystem model like Version 4 of the Community Land Model (CLM4) to provide accurate estimates of CO2 flux is a top priority for researchers, modelers and policy makers. Remote sensing can provide long-term and large scale products suitable for ecosystem model evaluation. Global estimations of gross primary production (GPP) at the 1 km spatial resolution from years 2000 to 2009 from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor offer a unique opportunity for evaluating the temporal and spatial patterns of global GPP and its relationship with climate for CLM4. We compare monthly GPP simulated bymore » CLM4 at half-degree resolution with satellite estimates of GPP from the MODIS GPP (MOD17) dataset for the 10-yr period, January 2000 December 2009. The assessment is presented in terms of long-term mean carbon assimilation, seasonal mean distributions, amplitude and phase of the annual cycle, and intra-annual and inter-annual GPP variability and their responses to climate variables. For the long-term annual and seasonal means, major GPP patterns are clearly demonstrated by both products. Compared to the MODIS product, CLM4 overestimates the magnitude of GPP for tropical evergreen forests. CLM4 has longer carbon uptake period than MODIS for most plant functional types (PFTs) with an earlier onset of GPP in spring and later decline of GPP in autumn. Empirical Orthogonal Function (EOF) analysis of the monthly GPP changes indicates that on the intra-annual scale, both CLM4 and MODIS display similar spatial representations and temporal patterns for most terrestrial ecosystems except in northeast Russia and the very dry region in central Australia. For 2000-2009, CLM4 simulates increases in annual averaged GPP over both hemispheres, however estimates from MODIS suggest a reduction in the Southern Hemisphere (-0.2173 PgC/year) balancing the significant increase over the Northern Hemisphere (0.2157 PgC/year).« less

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.

Pipeline oil fire detection with MODIS active fire products

NASA Astrophysics Data System (ADS)

Ogungbuyi, M. G.; Martinez, P.; Eckardt, F. D.

2017-12-01

We investigate 85 129 MODIS satellite active fire events from 2007 to 2015 in the Niger Delta of Nigeria. The region is the oil base for Nigerian economy and the hub of oil exploration where oil facilities (i.e. flowlines, flow stations, trunklines, oil wells and oil fields) are domiciled, and from where crude oil and refined products are transported to different Nigerian locations through a network of pipeline systems. Pipeline and other oil facilities are consistently susceptible to oil leaks due to operational or maintenance error, and by acts of deliberate sabotage of the pipeline equipment which often result in explosions and fire outbreaks. We used ground oil spill reports obtained from the National Oil Spill Detection and Response Agency (NOSDRA) database (see www.oilspillmonitor.ng) to validate MODIS satellite data. NOSDRA database shows an estimate of 10 000 spill events from 2007 - 2015. The spill events were filtered to include largest spills by volume and events occurring only in the Niger Delta (i.e. 386 spills). By projecting both MODIS fire and spill as `input vector' layers with `Points' geometry, and the Nigerian pipeline networks as `from vector' layers with `LineString' geometry in a geographical information system, we extracted the nearest MODIS events (i.e. 2192) closed to the pipelines by 1000m distance in spatial vector analysis. The extraction process that defined the nearest distance to the pipelines is based on the global practices of the Right of Way (ROW) in pipeline management that earmarked 30m strip of land to the pipeline. The KML files of the extracted fires in a Google map validated their source origin to be from oil facilities. Land cover mapping confirmed fire anomalies. The aim of the study is to propose a near-real-time monitoring of spill events along pipeline routes using 250 m spatial resolution of MODIS active fire detection sensor when such spills are accompanied by fire events in the study location.

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

Observations of Ocean Primary Productivity Using MODIS

NASA Technical Reports Server (NTRS)

Esaias, Wayne E.; Abbott, Mark R.; Koblinsky, Chester J. (Technical Monitor)

2001-01-01

Measuring the magnitude and variability of oceanic net primary productivity (NPP) represents a key advancement toward our understanding of the dynamics of marine ecosystems and the role of the ocean in the global carbon cycle. MODIS observations make two new contributions in addition to continuing the bio-optical time series begun with Orbview-2's SeaWiFS sensor. First, MODIS provides weekly estimates of global ocean net primary productivity on weekly and annual time periods, and annual empirical estimates of carbon export production. Second, MODIS provides additional insight into the spatial and temporal variations in photosynthetic efficiency through the direct measurements of solar-stimulated chlorophyll fluorescence. The two different weekly productivity indexes (first developed by Behrenfeld & Falkowski and by Yoder, Ryan and Howard) are used to derive daily productivity as a function of chlorophyll biomass, incident daily surface irradiance, temperature, euphotic depth, and mixed layer depth. Comparisons between these two estimates using both SeaWiFS and MODIS data show significant model differences in spatial distribution after allowance for the different integration depths. Both estimates are strongly dependence on the accuracy of the chlorophyll determination. In addition, an empirical approach is taken on annual scales to estimate global NPP and export production. Estimates of solar stimulated fluorescence efficiency from chlorophyll have been shown to be inversely related to photosynthetic efficiency by Abbott and co-workers. MODIS provides the first global estimates of oceanic chlorophyll fluorescence, providing an important proof of concept. MODIS observations are revealing spatial patterns of fluorescence efficiency which show expected variations with phytoplankton photo-physiological parameters as measured during in-situ surveys. This has opened the way for research into utilizing this information to improve our understanding of oceanic NPP variability. Deriving the ocean bio-optical properties places severe demands on instrument performance (especially band to band precision) and atmospheric correction. Improvements in MODIS instrument characterization and calibration over the first 16 mission months have greatly improved the accuracy of the chlorophyll input fields and FLH, and therefore the estimates of NPP and fluorescence efficiency. Annual estimates now show the oceanic NPP accounts for 40-50% of the global total NPP, with significant interannual variations related to large scale ocean processes. Spatial variations in ocean NPP, and exported production, have significant effects on exchange of CO2 between the ocean and atmosphere. Further work is underway to improve both the primary productivity model functions, and to refine our understanding of the relationships between fluorescence efficiency and NPP estimates. We expect that the MODIS instruments will prove extremely useful in assessing the time dependencies of oceanic carbon uptake and effects of iron enrichment, within the global carbon cycle.

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

Noble, Stephen R.; Hudson, James G.

Here, vertical sounding measurements within stratocumuli during two aircraft field campaigns, Marine Stratus/stratocumulus Experiment (MASE) and Physics of Stratocumulus Top (POST), are used to validate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical thickness (COT), cloud liquid water path (LWP), and cloud effective radius (r e). In situ COT, LWP, and r e were calculated using 5 m vertically averaged droplet probe measurements of complete vertical cloud penetrations. MODIS COT, LWP, and r e 1 km pixels were averaged along these penetrations. COT comparisons in POST showed strong correlations and a near 1:1 relationship. In MASE, comparisons showed strong correlations; however,more » MODIS COT exceeded in situ COT, likely due to larger temporal differences between MODIS and in situ measurements. LWP comparisons between two cloud probes show good agreement for POST but not MASE, giving confidence to POST data. Both projects provided strong LWP correlations but MODIS exceeded in situ by 14–36%. MODIS in situ r e correlations were strong, but MODIS 2.1 µm r e exceeded in situ r e, which contributed to LWP bias; in POST, MODIS r e was 20–30% greater than in situ r e. Maximum in situ r e near cloud top showed comparisons nearer 1:1. Other MODIS r e bands (3.7 µm and 1.6 µm) showed similar comparisons. Temporal differences between MODIS and in situ measurements, airplane speed differences, and cloud probe artifacts were likely causes of weaker MASE correlations. POST COT comparison was best for temporal differences under 20 min. POST data validate MODIS COT but it also implies a positive MODIS r e bias that propagates to LWP while still capturing variability.« less

Validation of MODIS aerosol optical depth product over China using CARSNET measurements

NASA Astrophysics Data System (ADS)

Xie, Yong; Zhang, Yan; Xiong, Xiaoxiong; Qu, John J.; Che, Huizheng

2011-10-01

This study evaluates Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) retrievals with ground measurements collected by the China Aerosol Remote Sensing NETwork (CARSNET). In current stage, the MODIS Collection 5 (C5) AODs are retrieved by two distinct algorithms: the Dark Target (DT) and the Deep Blue (DB). The CARSNET AODs are derived with measurements of Cimel Electronique CE-318, the same instrument deployed by the AEROsol Robotic Network (AEROENT). The collocation is performed by matching each MODIS AOD pixel (10 × 10 km 2) to CARSNET AOD mean within 7.5 min of satellite overpass. Four-year comparisons (2005-2008) of MODIS/CARSNET at ten sites show the performance of MODIS AOD retrieval is highly dependent on the underlying land surface. The MODIS DT AODs are on average lower than the CARSNET AODs by 6-30% over forest and grassland areas, but can be higher by up to 54% over urban area and 95% over desert-like area. More than 50% of the MODIS DT AODs fall within the expected error envelope over forest and grassland areas. The MODIS DT tends to overestimate for small AOD at urban area. At high vegetated area it underestimates for small AOD and overestimates for large AOD. Generally, its quality reduces with the decreasing AOD value. The MODIS DB is capable of retrieving AOD over desert but with a significant underestimation at CARSNET sites. The best retrieval of the MODIS DB is over grassland area with about 70% retrievals within the expected error. The uncertainties of MODIS AOD retrieval from spatial-temporal collocation and instrument calibration are discussed briefly.

Clinical differences between patients with MODY-3, MODY-2 and type 2 diabetes mellitus with I27L polymorphism in the HNF1alpha gene.

PubMed

Pinés Corrales, Pedro José; López Garrido, María P; Aznar Rodríguez, Silvia; Louhibi Rubio, Lynda; López Jiménez, Luz M; Lamas Oliveira, Cristina; Alfaro Martínez, Jose J; Lozano García, Jose J; Hernández López, Antonio; Requejo Castillo, Ramón; Escribano Martínez, Julio; Botella Romero, Francisco

2010-01-01

The aim of our study was to describe and evaluate the clinical and metabolic characteristics of patients with MODY-3, MODY-2 or type 2 diabetes who presented I27L polymorphism in the HNF1alpha gene. The study included 31 previously diagnosed subjects under follow-up for MODY-3 (10 subjects from 5 families), MODY-2 (15 subjects from 9 families), or type 2 diabetes (6 subjects) with I27L polymorphism in the HNF1alpha gene. The demographic, clinical, metabolic, and genetic characteristics of all patients were analyzed. No differences were observed in distribution according to sex, age of onset, or form of diagnosis. All patients with MODY-2 or MODY-3 had a family history of diabetes. In contrast, 33.3% of patients with type 2 diabetes mellitus and I27L polymorphism in the HNF1alpha gene had no family history of diabetes (p < 0.05). No differences were observed in body mass index, prevalence of hypertension, or microvascular or macrovascular complications. Drug therapy was required by 100% of MODY-3 patients, but not required by 100% of MODY-2 patients or 16.7% of patients with type 2 diabetes mellitus and I27L polymorphism in the HNF1alpha gene (p < 0.05). Occasional difficulties may be encountered when classifying patients with MODY-2, MODY-3 or type 2 diabetes of atypical characteristics, in this case patients who present I27L polymorphism in the HNF1alpha gene. Copyright 2010 Sociedad Española de Endocrinología y Nutrición. Published by Elsevier Espana. All rights reserved.

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.

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Semiconductor-laser Fourier processors of electric signals

NASA Astrophysics Data System (ADS)

Blok, A. S.; Bukhenskii, A. F.; Krupitskii, É. I.; Morozov, S. V.; Pelevin, V. Yu; Sergeenko, T. N.; Yakovlev, V. I.

1995-10-01

An investigation is reported of acousto-optical and fibre-optic Fourier processors of electric signals, based on semiconductor lasers. A description is given of practical acousto-optical processors with an analysis band 120 MHz wide, a resolution of 200 kHz, and 7 cm × 8 cm × 18 cm dimensions. Fibre-optic Fourier processors are considered: they represent a new class of devices which are promising for the processing of gigahertz signals.

An Evaluation of MODIS-Retrieved Aerosol Optical Depth over a Mountainous AERONET Site in the Southeastern US

NASA Technical Reports Server (NTRS)

Sherman, James P.; Gupta, Pawan; Levy, Robert C.; Sherman, Peter J.

2016-01-01

The literature shows that aerosol optical depth (AOD) derived from the MODIS Collection 5 (C5) dark target algorithm has been extensively validated by spatiotemporal collocation with AERONET sites on both global and regional scales.Although generally comparing well over the eastern US region, poor performance over mountains in other regions indicate the need to evaluate the MODIS product over a mountain site. This study compares MODIS C5 AOD at 550nm to AOD measured at the Appalachian State University AERONET site in Boone, NC over 30 months between August 2010 and September 2013. For the combined Aqua and Terra datasets, although more than 70% of the 500 MODIS AOD measurements agree with collocated AERONET AOD to within error envelope of +/- (0.05 + 15%), MODIS tends to have a low bias (0.02-0.03). The agreement between MODIS and AERONET AOD does not depend on MODIS quality assurance confidence (QAC) value. However, when stratified by satellite, MODIS-Terra data does not perform as well as Aqua, with especially poor correlation (r = 0.39) for low aerosol loading conditions (AERONET AOD less than 0.15).Linear regressions between Terra and AERONET possess statistically-different slopes for AOD < 0.15 and AOD > or = 0.15. AERONET AOD measured only during MODIS overpass hours is highly correlated with daily-averaged AERONET AOD. MODIS monthly-averaged AOD also tracks that of AERONET over the study period. These results indicate that MODIS is sensitive to the day-to-day variability, as well as the annual cycle of AOD over the Appalachian State AERONET site. The complex topography and high seasonality in AOD and vegetation indices allow us to specifically evaluate MODIS dark target algorithm surface albedo and aerosol model assumptions at a regionally-representative SE US mountain site.

[Clinical parameters for molecular testing of Maturity Onset Diabetes of the Young (MODY)].

PubMed

Datz, N; Nestoris, C; von Schütz, W; Danne, T; Driesel, A J; Maringa, M; Kordonouri, O

2011-05-01

Monogenic forms of diabetes are often diagnosed by chance, due to the variety of clinical presentation and limited experience of the diabetologists with this kind of diabetes. Aim of this study was to evaluate clinical parameters for an efficient screening. Clinical parameters were: negative diabetes-specific antibodies at onset of diabetes, positive family history of diabetes, and low to moderate insulin requirements after one year of diabetes treatment. Molecular testing was performed through sequencing of the programming regions of HNF-4alpha (MODY 1), glucokinase (MODY 2) and HNF-1alpha/TCF1 (MODY 3) and in one patient the HNF-1beta/TCF2 region (MODY 5). 39 of 292 patients treated with insulin were negative for GADA and IA2A, and 8 (20.5%) patients fulfilled both other criteria. Positive molecular results were found in five (63%) patients (two with MODY 2, two with MODY 3, one with MODY 5). At diabetes onset, the mean age of the 5 patients with MODY was 10.6 ± 5.3 yrs (range 2.6-15 yrs), HbA(1c) was 8.4 ± 3.1 % (6.5-13.9%), mean diabetes duration until diagnosis of MODY was 3.3 ± 3.6 yrs (0.8-9.6 yrs) with insulin requirements of 0.44 ± 0.17 U/kg/d (0.2-0.6 U/kg/d). Patients with MODY 3 were changed from insulin to repaglinide, those with MODY 2 were recommended discontinuing insulin treatment. In patients with negative diabetes-specific antibodies at onset of diabetes, with a positive family history, and low to moderate insulin needs a genetic screening for MODY is indicated. Watchful consideration of these clinical parameters may lead to an early genetic testing, and to an adequate treatment. © Georg Thieme Verlag KG Stuttgart · New York.

HDL cholesterol as a diagnostic tool for clinical differentiation of GCK-MODY from HNF1A-MODY and type 1 diabetes in children and young adults.

PubMed

Fendler, Wojciech; Borowiec, Maciej; Antosik, Karolina; Szadkowska, Agnieszka; Deja, Grazyna; Jarosz-Chobot, Przemyslawa; Mysliwiec, Malgorzata; Wyka, Krystyna; Pietrzak, Iwona; Skupien, Jan; Malecki, Maciej T; Mlynarski, Wojciech

2011-09-01

Confirmation of monogenic diabetes caused by glucokinase mutations (GCK-MODY) allows pharmacogenetic intervention in the form of insulin discontinuation. This is especially important among paediatric and young adult populations where GCK-MODY is most prevalent. The study evaluated the utility of lipid parameters in screening for patients with GCK-MODY. Eighty-nine children with type 1 diabetes and 68 with GCK-MODY were screened for triglyceride (TG), total and HDL cholesterol levels. Standardization against a control group of 171 healthy children was applied to eliminate the effect of development. Clinical applicability and cut-off value were evaluated in all available patients with GCK-MODY (n = 148), hepatocyte nuclear factor 1-alpha-MODY (HNF1A MODY) (n = 37) or type 1 diabetes (n = 221). Lower lipid parameter values were observed in GCK-MODY than in patients with type 1 diabetes. Standard deviation scores were -0·22 ± 2·24 vs 1·31 ± 2·17 for HDL cholesterol (P < 0·001), -0·16 ± 2·14 vs 0·60 ± 1·77 for total cholesterol (P = 0·03) and -0·57 ± 0·97 vs-0·22 ± 0·97 for TG (P = 0·05). Validation analysis confirmed that HDL cholesterol was the best parameter for GCK-MODY selection [sensitivity 87%, specificity 54%, negative predictive value (NPV) 86%, positive PV 56%]. A threshold HDL concentration of 1·56 mm offered significantly better diagnostic efficiency than total cholesterol (cut-off value 4·51 mm; NPV 80%; PPV 38%; P < 0·001). TG did not offer a meaningful cut-off value. HDL cholesterol levels measured in individuals with likely monogenic diabetes may be useful in screening for GCK-MODY and differentiation from T1DM and HNF1A-MODY, regardless of treatment or metabolic control. © 2011 Blackwell Publishing Ltd.

MODIS GPP/NPP for complex land use area: a case study of comparison between MODIS GPP/NPP and ground-based measurements over Korea

NASA Astrophysics Data System (ADS)

Shim, C.

2013-12-01

The Moderate Resolution Imaging Radiometer (MODIS) Gross Primary Productivity (GPP)/Net Primary Productivity (NPP) has been widely used for the study on global terrestrial ecosystem and carbon cycle. The current MODIS product with ~ 1 km spatial resolution, however, has limitation on the information on local scale environment (< 1km), particularly on the regions with complex land-use types. Here we try to test the performance of MODIS annual GPP/NPP for a case of Korea, where the vegetation types are mostly heterogeneous within a size of MODIS products (~1km). We selected the sites where the ground/tower flux measurements and MODIS retrievals were simultaneously available and the land classification of sites agreed the forest type map (~71m) (1 site over Gwangneung flux tower (GDK) for 2006-2008 and 2 sites of ground measurements over Cheongju (CJ1 and CJ2) for 2011). The MODIS GPP are comparable to that of GDK (largely deciduous forest) within -6.3 ~ +2.3% of bias (-104.5 - 37.9 gCm-2yr-1). While the MODIS NPP of CJ1 at Cheongju (largely Larix leptolepis) underestimated NPP by 34% (-224.5 gCm-2yr-1), the MODIS NPP of CJ2 (largely Pinus densiflora) agreed well with -0.2% of bias (1.6 gCm-2yr-1). The fairly comparable values of the MODIS here however, cannot assure the quality of the MOD17 over the complex vegetation area of Korea since the ground measurements except the eddy covariance tower flux measurements are highly inconsistent. Therefore, the comprehensive experiments to represents GPP/NPP over diverse vegetation types for a comparable scale of MODIS with a consistent measurement technique are necessary in order to evaluate the MODIS vegetation productivity data over Korea, which contains a large portion of highly heterogeneous vegetation area.

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.

Cloud Retrieval Intercomparisons Between SEVIRI, MODIS and VIIRS with CHIMAERA PGE06 Data Collection 6 Products

NASA Technical Reports Server (NTRS)

Wind, Galina; Riedi, Jerome; Platnick, Steven; Heidinger, Andrew

2014-01-01

The Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system allows us to perform MODIS-like cloud top, optical and microphysical properties retrievals on any sensor that possesses a minimum set of common spectral channels. The CHIMAERA system uses a shared-core architecture that takes retrieval method out of the equation when intercomparisons are made. Here we show an example of such retrieval and a comparison of simultaneous retrievals done using SEVIRI, MODIS and VIIRS sensors. All sensor retrievals are performed using CLAVR-x (or CLAVR-x based) cloud top properties algorithm. SEVIRI uses the SAF_NWC cloud mask. MODIS and VIIRS use the IFF-based cloud mask that is a shared algorithm between MODIS and VIIRS. The MODIS and VIIRS retrievals are performed using a VIIRS branch of CHIMAERA that limits available MODIS channel set. Even though in that mode certain MODIS products such as multilayer cloud map are not available, the cloud retrieval remains fully equivalent to operational Data Collection 6.

[MODY type diabetes: overview and recent findings].

PubMed

Ben Khelifa, Souhaïra; Barboura, Ilhem; Dandana, Azza; Ferchichi, Selima; Miled, Abdelhedi

2011-01-01

We present an update of knowledge on diabetes MODY (maturity onset diabetes of the young), including the recent molecular discoveries, and new diagnostic strategies. Considerable progress has been made in understanding the different molecular abnormalities that cause MODY and the phenotypic consequences resulting therefrom. MODY diabetes is very heterogeneous and is the most common form of monogenic diabetes. Its distribution is worldwide. MODY is an autosomal dominant diabetes mellitus, nonketotic and occurs at an early age (usually before 25 years). To date, at least seven genes are associated with MODY, with frequencies that differ from one population to another. Both 2 and 3 subtypes predominate, while other subtypes (1, 4, 5, 6 and 7) concern only a few families. Since its discovery in the sixties, studies have succeeded to fully clarify the epidemiological, molecular and clinical diagnosis of each subtype, to provide better care for patients. However, the subject of MODY has not yet revealed all its secrets. Indeed, it remains to identify other genes that are associated with MODY X.

Decadal monitoring of rice farming practices from MODIS data in Myanmar

NASA Astrophysics Data System (ADS)

Thanh Son, Nguyen; Farn Chen, Chi; Chen, Cheng Ru

2015-04-01

Rice agriculture was the most important sector in Myanmar's economy because it provided employments and livelihoods for at least 75% of the country's population, accounting for more than 48% of the national gross domestic product. Prior to the World War II, this country was the largest rice-producing nation in the world. However, it is currently a relatively minor rice exporter, ranking seventh after Thailand and Vietnam. The country's rice export potential remains high due to abundant land and water resources along with recent indications of progressive policy reforms to improve rice productivity. This study aimed at investigating decadal changes in rice farming practices in Myanmar during 2001 to 2014 using Moderate Resolution Imaging Spectroradiometer (MODIS) data. We processed the data though three main steps: (1) data pre-processing to construct the smooth time-series MODIS enhanced vegetation index (EVI) data, (2) mapping rice farming practices using phenological information of crop phenology, and (3) accuracy assessment. The mapping results were compared with the ground reference data indicated satisfactory results, with the overall accuracies and Kappa coefficients generally higher than 90% and 0.8, respectively. These results were reaffirmed by comparisons between MODIS-derived rice area and the government's rice area statistics, with a close correlation between the two datasets (R2 > 0.8) and the relative error in area smaller than 15%. From 2001 to 2014, rice farming practices in Myanmar had remarkably changed from single-cropped rice to double-cropped rice, especially in Ayeyarwady river basin. This study demonstrates the validity of the phenology-based approach for national-wide monitoring of decadal changes in rice farming practices in Myanmar. Such a quantitative information might be useful for agronomic managers to devise better plans for long-term rice crop management of in the country.

MODIS-based spatiotemporal patterns of soil moisture and evapotranspiration interactions in Tampa Bay urban watershed

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Xuan, Zhemin; Wimberly, Brent

2011-09-01

Soil moisture and evapotranspiration (ET) is affected by both water and energy balances in the soilvegetation- atmosphere system, it involves many complex processes in the nexus of water and thermal cycles at the surface of the Earth. These impacts may affect the recharge of the upper Floridian aquifer. The advent of urban hydrology and remote sensing technologies opens new and innovative means to undertake eventbased assessment of ecohydrological effects in urban regions. For assessing these landfalls, the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing images can be used for the estimation of such soil moisture change in connection with two other MODIS products - Enhanced Vegetation Index (EVI), Land Surface Temperature (LST). Supervised classification for soil moisture retrieval was performed for Tampa Bay area on the 2 kmx2km grid with MODIS images. Machine learning with genetic programming model for soil moisture estimation shows advances in image processing, feature extraction, and change detection of soil moisture. ET data that were derived by Geostationary Operational Environmental Satellite (GOES) data and hydrologic models can be retrieved from the USGS web site directly. Overall, the derived soil moisture in comparison with ET time series changes on a seasonal basis shows that spatial and temporal variations of soil moisture and ET that are confined within a defined region for each type of surfaces, showing clustered patterns and featuring space scatter plot in association with the land use and cover map. These concomitant soil moisture patterns and ET fluctuations vary among patches, plant species, and, especially, location on the urban gradient. Time series plots of LST in association with ET, soil moisture and EVI reveals unique ecohydrological trends. Such ecohydrological assessment can be applied for supporting the urban landscape management in hurricane-stricken regions.

Real-Time and Memory Correlation via Acousto-Optic Processing,

DTIC Science & Technology

1978-06-01

acousto - optic technology as an answer to these requirements appears very attractive. Three fundamental signal-processing schemes using the acousto ... optic interaction have been investigated: (i) real-time correlation and convolution, (ii) Fourier and discrete Fourier transformation, and (iii

[Research on spatially modulated Fourier transform imaging spectrometer data processing method].

PubMed

Huang, Min; Xiangli, Bin; Lü, Qun-Bo; Zhou, Jin-Song; Jing, Juan-Juan; Cui, Yan

2010-03-01

Fourier transform imaging spectrometer is a new technic, and has been developed very rapidly in nearly ten years. The data catched by Fourier transform imaging spectrometer is indirect data, can not be used by user, and need to be processed by various approaches, including data pretreatment, apodization, phase correction, FFT, and spectral radicalization calibration. No paper so far has been found roundly to introduce this method. In the present paper, the author will give an effective method to process the interfering data to spectral data, and with this method we can obtain good result.

Moderate Resolution Imaging Spectrometer (MODIS) design evolution and associated development and verification of data product efforts

NASA Technical Reports Server (NTRS)

Salomonson, Vincent V.

1991-01-01

The Moderate Resolution Imaging Spectrometer (MODIS) is a key observing facility to be flown on the Earth Observing System (EOS). The facility is composed of two instruments called MODIS-N (nadir) and MODIS-T (tilt). The MODIS-N is being built under contract to NASA by the Santa Barbara Research Center. The MODIS-T is being fabricated by the Engineering Directorate at the Goddard Space Flight Center. The MODIS Science Team has defined nearly 40 biogeophysical data products for studies of the ocean and land surface and properties of the atmosphere including clouds that can be expected to be produced from the MODIS instruments shortly after the launch of EOS. The ocean, land, atmosphere, and calibration groups of the MODIS Science Team are now proceeding to plan and implement the operations and facilities involving the analysis of data from existing spaceborne, airborne, and in-situ sensors required to develop and validate the algorithms that will produce the geophysical data products. These algorithm development and validation efforts will be accomplished wherever possible within the context of existing or planned national and international experiments or programs such as those in the World Climate Research Program.

A Comparison Between SST and AOT Derived from AVHRR and MODIS Data in the Frame of the CREPAD Program

NASA Astrophysics Data System (ADS)

Robles-Gonzalez, Cristina; Fernandez-Renau, Alix; Lopez Gordillo, Noelia; Sevilla, Angel Garcia; Suarez, Juana Santana

2010-12-01

Since 1997, the INTA-CREPAD (Centre for REception, Processing, Archiving and Dissemination of Earth Observation Data) program distributes freely some of the most demanded low-resolution remote sensing products: SST, Ocean Chl-a, NDVI, AOD... The data input for such products are captured at the Canary Space Station (Centro Espacial de Canarias, CEC). The data sensors received at the station and used in the CREPAD program are AVHRR, SEAWIFS and MODIS. In this study SST and AOD retrieved by CREPAD algorithms from AVHRR and the SEADAS derived SST and AOD from MODIS have compared. SST values agree very well within 0.1±0.5oC and the coefficient of correlation of the images is 0.9. AOD validation gives good results taking into account the differences in the algorithms used. Mean AOD difference at 0.630 μm is 0.01±0.05 and the correlation coefficient is 0.6.

Radiometric Quality of the MODIS Bands at 667 and 678nm

NASA Technical Reports Server (NTRS)

Meister, Gerhard; Franz, Bryan A.

2010-01-01

The MODIS instruments on Terra and Aqua were designed to allow the measurement of chlorophyll fluorescence effects over ocean. The retrieval algorithm is based on the difference between the water-leaving radiances at 667nm and 678nm. The water-leaving radiances at these wavelengths are usually very low relative to the top- of-atmosphere radiances. The high radiometric accuracy needed to retrieve the small fluorescence signal lead to a dual gain design for the 667 and 678nm bands. This paper discusses the benefits obtained from this design choice and provides justification for the use of only one set of gains for global processing of ocean color products. Noise characteristics of the two bands and their related products are compared to other products of bands from 412nm to 2130nm. The impact of polarization on the two bands is discussed. In addition, the impact of stray light on the two bands is compared to other MODIS bands.

Radiometric Quality of the MODIS Bands at 667 and 678nm

NASA Technical Reports Server (NTRS)

Meister, Gerhard; Franz, Bryan A.

2011-01-01

The MODIS instruments on Terra and Aqua were designed to allow the measurement of chlorophyll fluorescence effects over ocean. The retrieval algorithm is based on the difference between the water-leaving radiances at 667nm and 678nm. The water-leaving radiances at these wavelengths are usually very low relative to the top-of-atmosphere radiances. The high radiometric accuracy needed to retrieve the small fluorescence signal lead to a dual gain design for the 667 and 678nm bands. This paper discusses the benefits obtained from this design choice and provides justification for the use of only one set of gains for global processing of ocean color products. Noise characteristics of the two bands and their related products are compared to other products of bands from 412nm to 2130nm. The impact of polarization on the two bands is discussed. In addition, the impact of stray light on the two bands is compared to other MODIS bands.

Estimating atmospheric visibility using synergy of MODIS data and ground-based observations

NASA Astrophysics Data System (ADS)

Komeilian, H.; Mohyeddin Bateni, S.; Xu, T.; Nielson, J.

2015-05-01

Dust events are intricate climatic processes, which can have adverse effects on human health, safety, and the environment. In this study, two data mining approaches, namely, back-propagation artificial neural network (BP ANN) and supporting vector regression (SVR), were used to estimate atmospheric visibility through the synergistic use of Moderate Resolution Imaging Spectroradiometer (MODIS) Level 1B (L1B) data and ground-based observations at fourteen stations in the province of Khuzestan (southwestern Iran), during 2009-2010. Reflectance and brightness temperature in different bands (from MODIS) along with in situ meteorological data were input to the models to estimate atmospheric visibility. The results show that both models can accurately estimate atmospheric visibility. The visibility estimates from the BP ANN network had a root-mean-square error (RMSE) and Pearson's correlation coefficient (R) of 0.67 and 0.69, respectively. The corresponding RMSE and R from the SVR model were 0.59 and 0.71, implying that the SVR approach outperforms the BP ANN.

Evaluation of the Harmful Algal Bloom Mapping System (HABMapS) and Bulletin

NASA Technical Reports Server (NTRS)

Hall, Callie; Zanoni, Vicki; Estep, Leland; Terrie, Gregory; D'Sa, Eurico; Pagnutti, Mary

2004-01-01

The National Oceanic and Atmospheric Administration (NOAA) Harmful Algal Bloom (HAB) Mapping System and Bulletin provide a Web-based geographic information system (GIS) and an e-mail alert system that allow the detection, monitoring, and tracking of HABs in the Gulf of Mexico. NASA Earth Science data that potentially support HABMapS/Bulletin requirements include ocean color, sea surface temperature (SST), salinity, wind fields, precipitation, water surface elevation, and ocean currents. Modeling contributions include ocean circulation, wave/currents, along-shore current regimes, and chlorophyll modeling (coupled to imagery). The most immediately useful NASA contributions appear to be the 1-km Moderate Resolution Imaging Spectrometer (MODIS) chlorophyll and SST products and the (presently used) SeaWinds wind vector data. MODIS pigment concentration and SST data are sufficiently mature to replace imagery currently used in NOAA HAB applications. The large file size of MODIS data is an impediment to NOAA use and modified processing schemes would aid in NOAA adoption of these products for operational HAB forecasting.

Evaluation of NCAR CAM5 Simulated Marine Boundary Layer Cloud Properties Using a Combination of Satellite and Surface Observations

NASA Astrophysics Data System (ADS)

Zhang, Z.; Song, H.; Wang, M.; Ghan, S. J.; Dong, X.

2016-12-01

he main objective of this study is to systematically evaluate the MBL cloud properties simulated in CAM5 family models using a combination of satellite-based CloudSat/MODIS observations and ground-based observations from the ARM Azores site, with a special focus on MBL cloud microphysics and warm rain process. First, we will present a global evaluation based on satellite observations and retrievals. We will compare global cloud properties (e.g., cloud fraction, cloud vertical structure, cloud CER, COT, and LWP, as well as drizzle frequency and intensity diagnosed using the CAM5-COSP instrumental simulators) simulated in the CAM5 models with the collocated CloudSat and MODIS observations. We will also present some preliminary results from a regional evaluation based mainly on ground observations from ARM Azores site. We will compare MBL cloud properties simulated in CAM5 models over the ARM Azores site with collocated satellite (MODIS and CloudSat) and ground-based observations from the ARM site.

Pre-Launch Tasks Proposed in our Contract of December 1991

NASA Technical Reports Server (NTRS)

1998-01-01

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data; (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC; (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

Pre-Launch Tasks Proposed in our Contract of December 1991

NASA Technical Reports Server (NTRS)

Running, Steven W.; Nemani, Ramakrishna R.; Glassy, Joseph

1997-01-01

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data. (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

MODIS Information, Data, and Control System (MIDACS) system specifications and conceptual design

NASA Technical Reports Server (NTRS)

Han, D.; Salomonson, V.; Ormsby, J.; Ardanuy, P.; Mckay, A.; Hoyt, D.; Jaffin, S.; Vallette, B.; Sharts, B.; Folta, D.

1988-01-01

The MODIS Information, Data, and Control System (MIDACS) Specifications and Conceptual Design Document discusses system level requirements, the overall operating environment in which requirements must be met, and a breakdown of MIDACS into component subsystems, which include the Instrument Support Terminal, the Instrument Control Center, the Team Member Computing Facility, the Central Data Handling Facility, and the Data Archive and Distribution System. The specifications include sizing estimates for the processing and storage capacities of each data system element, as well as traffic analyses of data flows between the elements internally, and also externally across the data system interfaces. The specifications for the data system, as well as for the individual planning and scheduling, control and monitoring, data acquisition and processing, calibration and validation, and data archive and distribution components, do not yet fully specify the data system in the complete manner needed to achieve the scientific objectives of the MODIS instruments and science teams. The teams have not yet been formed; however, it was possible to develop the specifications and conceptual design based on the present concept of EosDIS, the Level-1 and Level-2 Functional Requirements Documents, the Operations Concept, and through interviews and meetings with key members of the scientific community.

CHIMAERA System for Cloud Retrievals v 6.0.85

NASA Technical Reports Server (NTRS)

Wind, Galina; Platnick, Steven; Meyer, Kerry; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, Tom; King, Michael D.

2015-01-01

Organizers of the MODIS-VIIRS Science Team Meeting, held May 18-22, 2015 in Silver Spring, MD plan to post the presentations and posters to the NASA MODIS website: http:modis.gsfc.nasa.govsci_teammeetings201505index.php. The MODIS Science Team Meeting is held twice a year, so that the members of the science team may assemble and discuss data they have collected, ideas they have formed, and future issues that apply to the MODIS Mission.

Farm Management Support on Cloud Computing Platform: A System for Cropland Monitoring Using Multi-Source Remotely Sensed Data

NASA Astrophysics Data System (ADS)

Coburn, C. A.; Qin, Y.; Zhang, J.; Staenz, K.

2015-12-01

Food security is one of the most pressing issues facing humankind. Recent estimates predict that over one billion people don't have enough food to meet their basic nutritional needs. The ability of remote sensing tools to monitor and model crop production and predict crop yield is essential for providing governments and farmers with vital information to ensure food security. Google Earth Engine (GEE) is a cloud computing platform, which integrates storage and processing algorithms for massive remotely sensed imagery and vector data sets. By providing the capabilities of storing and analyzing the data sets, it provides an ideal platform for the development of advanced analytic tools for extracting key variables used in regional and national food security systems. With the high performance computing and storing capabilities of GEE, a cloud-computing based system for near real-time crop land monitoring was developed using multi-source remotely sensed data over large areas. The system is able to process and visualize the MODIS time series NDVI profile in conjunction with Landsat 8 image segmentation for crop monitoring. With multi-temporal Landsat 8 imagery, the crop fields are extracted using the image segmentation algorithm developed by Baatz et al.[1]. The MODIS time series NDVI data are modeled by TIMESAT [2], a software package developed for analyzing time series of satellite data. The seasonality of MODIS time series data, for example, the start date of the growing season, length of growing season, and NDVI peak at a field-level are obtained for evaluating the crop-growth conditions. The system fuses MODIS time series NDVI data and Landsat 8 imagery to provide information of near real-time crop-growth conditions through the visualization of MODIS NDVI time series and comparison of multi-year NDVI profiles. Stakeholders, i.e., farmers and government officers, are able to obtain crop-growth information at crop-field level online. This unique utilization of GEE in combination with advanced analytic and extraction techniques provides a vital remote sensing tool for decision makers and scientists with a high-degree of flexibility to adapt to different uses.

Evaluating the Usefulness of High-Temporal Resolution Vegetation Indices to Identify Crop Types

NASA Astrophysics Data System (ADS)

Hilbert, K.; Lewis, D.; O'Hara, C. G.

2006-12-01

The National Aeronautical and Space Agency (NASA) and the United States Department of Agriculture (USDA) jointly sponsored research covering the 2004 to 2006 South American crop seasons that focused on developing methods for the USDA's Foreign Agricultural Service's (FAS) Production Estimates and Crop Assessment Division (PECAD) to identify crop types using MODIS-derived, hyper-temporal Normalized Difference Vegetation Index (NDVI) images. NDVI images were composited in 8 day intervals from daily NDVI images and aggregated to create a hyper-termporal NDVI layerstack. This NDVI layerstack was used as input to image classification algorithms. Research results indicated that creating high-temporal resolution Normalized Difference Vegetation Index (NDVI) composites from NASA's MODerate Resolution Imaging Spectroradiometer (MODIS) data products provides useful input to crop type classifications as well as potential useful input for regional crop productivity modeling efforts. A current NASA-sponsored Rapid Prototyping Capability (RPC) experiment will assess the utility of simulated future Visible Infrared Imager / Radiometer Suite (VIIRS) imagery for conducting NDVI-derived land cover and specific crop type classifications. In the experiment, methods will be considered to refine current MODIS data streams, reduce the noise content of the MODIS, and utilize the MODIS data as an input to the VIIRS simulation process. The effort also is being conducted in concert with an ISS project that will further evaluate, verify and validate the usefulness of specific data products to provide remote sensing-derived input for the Sinclair Model a semi-mechanistic model for estimating crop yield. The study area encompasses a large portion of the Pampas region of Argentina--a major world producer of crops such as corn, soybeans, and wheat which makes it a competitor to the US. ITD partnered with researchers at the Center for Surveying Agricultural and Natural Resources (CREAN) of the National University of Cordoba, Argentina, and CREAN personnel collected and continue to collect field-level, GIS-based in situ information. Current efforts involve both developing and optimizing software tools for the necessary data processing. The software includes the Time Series Product Tool (TSPT), Leica's ERDAS Imagine, and Mississippi State University's Temporal Map Algebra computational tools.

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.

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.

Influence of enzymatic hydrolysis on the allergenic reactivity of processed cashew and pistachio

USDA-ARS?s Scientific Manuscript database

Tree nuts constitute one of the main cause of fatal anaphylactic reactions due to food allergy upon direct ingestion and as ingredients (hidden allergens), and cashew and pistachio allergies are considered a serious health problem. Several previous studies have shown that thermal processing may modi...

Using MODIS Terra 250 m Imagery to Map Concentrations of Total Suspended Matter in Coastal Waters

NASA Technical Reports Server (NTRS)

Miller, Richard L.; McKee, Brent A.

2004-01-01

High concentrations of suspended particulate matter in coastal waters directly effect or govern numerous water column and benthic processes. The concentration of suspended sediments derived from bottom sediment resuspension or discharge of sediment-laden rivers is highly variable over a wide range of time and space scales. Although there has been considerable effort to use remotely sensed images to provide synoptic maps of suspended particulate matter, there are limited routine applications of this technology due in-part to the low spatial resolution, long revisit period, or cost of most remotely sensed data. In contrast, near daily coverage of medium-resolution data is available from the MODIS Terra instrument without charge from several data distribution gateways. Equally important, several display and processing programs are available that operate on low cost computers.

International MODIS and AIRS Processing Package (IMAPP) Implementation of Infusion of Satellite Data into Environmental Applications-International (IDEA-I) for Air Quality Forecasts using Suomi-NPP, Terra and Aqua Aerosol Retrievals

NASA Astrophysics Data System (ADS)

Davies, J. E.; Strabala, K.; Pierce, R. B.; Huang, A.

2016-12-01

Fine mode aerosols play a significant role in public health through their impact on respiratory and cardiovascular disease. IDEA-I (Infusion of Satellite Data into Environmental Applications-International) is a real-time system for trajectory-based forecasts of aerosol dispersion that can assist in the prediction of poor air quality events. We released a direct broadcast version of IDEA-I for aerosol trajectory forecasts in June 2012 under the International MODIS and AIRS Processing Package (IMAPP). In January 2014 we updated this application with website software to display multi-satellite products. Now we have added VIIRS aerosols from Suomi National Polar-orbiting Partnership (S-NPP). IMAPP is a NASA-funded and freely-distributed software package developed at Space Science and Engineering Center of University of Wisconsin-Madison that has over 2,300 registered users worldwide. With IMAPP, any ground station capable of receiving direct broadcast from Terra or Aqua can produce calibrated and geolocated radiances and a suite of environmental products. These products include MODIS AOD required for IDEA-I. VIIRS AOD for IDEA-I can be generated by Community Satellite Processing Package (CSPP) VIIRS EDR Version 2.0 Software for Suomi NPP. CSPP is also developed and distributed by Space Science & Engineering Center. This presentation describes our updated IMAPP implementation of IDEA-I through an example of its operation in a region known for episodic poor air quality events.

Beyond Fourier.

PubMed

Hoch, Jeffrey C

2017-10-01

Non-Fourier methods of spectrum analysis are gaining traction in NMR spectroscopy, driven by their utility for processing nonuniformly sampled data. These methods afford new opportunities for optimizing experiment time, resolution, and sensitivity of multidimensional NMR experiments, but they also pose significant challenges not encountered with the discrete Fourier transform. A brief history of non-Fourier methods in NMR serves to place different approaches in context. Non-Fourier methods reflect broader trends in the growing importance of computation in NMR, and offer insights for future software development. Copyright © 2017 Elsevier Inc. All rights reserved.

Validation of MODIS Aerosol Retrieval Over Ocean

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Tanre, Didier; Kaufman, Yoram J.; Ichoku, Charles; Mattoo, Shana; Levy, Robert; Chu, D. Allen; Holben, Brent N.; Dubovik, Oleg; Ahmad, Ziauddin;

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.

Undiagnosed MODY: Time for Action

PubMed Central

Kleinberger, Jeffrey W.; Pollin, Toni I.

2016-01-01

Maturity-Onset Diabetes of the Young (MODY) is a monogenic form of diabetes that accounts for at least 1% of all cases of diabetes mellitus. MODY classically presents as non-insulin requiring diabetes in lean individuals younger than 25 with evidence of autosomal dominant inheritance, but these criteria do not capture all cases and can also overlap with other diabetes types. Genetic diagnosis of MODY is important for selecting the right treatment, yet ~95% of MODY cases in the U.S. are misdiagnosed. MODY prevalence and characteristics have been well-studied in some populations, such as the UK and Norway, while other ethnicities, like African and Latino, need much more study. Emerging next-generation sequencing methods are making more widespread study and clinical diagnosis increasingly feasible. This review will cover the current epidemiological studies of MODY and barriers and opportunities for moving toward a goal of access to an appropriate diagnosis for all affected individuals. PMID:26458381

Snow and Ice Mask for the MODIS Aerosol Products

NASA Technical Reports Server (NTRS)

Li, Rong-Rong; Remer, Lorraine; Kaufman, Yoram J.; Mattoo, Shana; Gao, Bo-Cai; Vermote, Eric

2005-01-01

The atmospheric products have been derived operationally from multichannel imaging data collected with the Moderate Resolution Imaging SpectroRadiometers (MODIS) on board the NASA Terra and Aqua spacecrafts. Preliminary validations of the products were previously reported. Through analysis of more extensive time-series of MODIS aerosol products (Collection 4), we have found that the aerosol products over land areas are slightly contaminated by snow and ice during the springtime snow-melting season. We have developed an empirical technique using MODIS near-IR channels centered near 0.86 and 1.24 pm and a thermal emission channel near 11 pm to mask out these snow-contaminated pixels over land. Improved aerosol retrievals over land have been obtained. Sample results from application of the technique to MODIS data acquired over North America, northern Europe, and northeastern Asia are presented. The technique has been implemented into the MODIS Collection 5 operational algorithm for retrieving aerosols over land from MODIS data.

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.

HNF1 alpha gene coding regions mutations screening, in a Caucasian population clinically characterized as MODY from Argentina.

PubMed

Lopez, Ariel Pablo; Foscaldi, Sabrina Andrea; Perez, Maria Silvia; Rodriguez, Martín; Traversa, Mercedes; Puchulu, Félix Miguel; Bergada, Ignacio; Frechtel, Gustavo Daniel

2011-02-01

There are at least six subtypes of Maturity Onset Diabetes of the Young (MODY) with distinctive genetic causes. MODY 3 is caused by mutations in HNF1A gene, an insulin transcription factor, so mutations in this gene are associated with impaired insulin secretion. MODY 3 prevalence differs according to the population analyzed, but it is one of the most frequent subtypes. Therefore, our aims in this work were to find mutations present in the HNF1A gene and provide information on their prevalence. Mutations screening was done in a group of 80 unrelated patients (average age 17.1 years) selected by clinical characterization of MODY, by SSCP electrophoresis followed by sequenciation. We found eight mutations, of which six were novel and four sequence variants, which were all novel. Therefore the prevalence of MODY 3 in this group was 10%. Compared clinical data between the non-MODY 3 patients and the MODY 3 diagnosed patients did not show any significant difference. Eight patients were diagnosed as MODY 3 and new data about the prevalence of that subtype is provided. Our results contribute to reveal novel mutations, providing new data about the prevalence of that subtype. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Beyond MODIS: Developing an aerosol climate data record

NASA Astrophysics Data System (ADS)

Levy, R. C.; Mattoo, S.; Munchak, L. A.; Patadia, F.; Laszlo, I.; Holz, R.

2013-12-01

As defined by the National Research Council, a climate data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. As one of our most pressing research questions concerns changes in global direct aerosol radiative forcing (DARF), creating an aerosol CDR is of high importance. To reduce our uncertainties in DARF, we need uncertainty in global aerosol optical depth (AOD) reduced to ×0.02 or better, or about 10% of global mean AOD (~0.15-0.20). To quantify aerosol trends with significance, we also need a stable time series at least 20-30 years. By this Fall-2013 AGU meeting, the Moderate Resolution Imaging Spectrometer (MODIS) has been flying on NASA's Terra and Aqua satellites for 14 years and 11.5 years, respectively. During this time, we have fine-tuned the aerosol retrieval algorithms and data processing protocols, resulting in a well characterized product of aerosol optical depth (AOD). MODIS AOD has been extensively compared to ground-based sunphotometer data, showing per-retrieval expected error (EE) of ×(0.03 + 5%) over ocean, and has been generally adopted as a robust and stable environmental data record (EDR). With the 2011 launch of the Visible and Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP, we have begun a new aerosol time series. The VIIRS AOD product has stabilized to the point where, compared to ground-based AERONET sunphotometer, the VIIRS AOD is within similar EE envelope as MODIS. Thus, if VIIRS continues to perform as expected, it too can provide a robust and stable aerosol EDR. What will it take to stitch MODIS and VIIRS into a robust aerosol CDR? Based on the recent experience of MODIS 'Collection 6' development, there are many details of aerosol retrieval that each lead to ×0.01 uncertainties in global AOD. These include 'radiative transfer' assumptions such as calculations for gas absorption and sea-level Rayleigh optical depth, 'decision making' assumptions such as cloud masking and pixel selection, as well as 'retrieval' assumptions such as aerosol type, and surface reflectance model. Also there are instrument issues such as calibration and geo-location, which even on the level of 1-2%, will lead to 10% error in retrieved AOD. At this point, however, many of these issues have been solved, or are being quantified for MODIS and VIIRS. In the past year, we created a generic dark-target aerosol retrieval algorithm, which can be applied to MODIS, VIIRS, or any other sensor with a similar set of wavelength bands. We applied the same radiative transfer codes for creating lookup tables, the same protocols for deriving non-aerosol assumptions, and the same criteria for cloud masking. Although there are still inconsistencies to work out, this generic algorithm is being applied to selected months having VIIRS/MODIS overlap. Comparing to AERONET, and with each other, we quantify the statistical agreement between MODIS and VIIRS, both for the official algorithms run on each sensor, as well as for our generic algorithm run on both.

Progress towards MODIS and VIIRS Cloud Optical Property Data Record Continuity

NASA Astrophysics Data System (ADS)

Meyer, K.; Platnick, S. E.; Wind, G.; Amarasinghe, N.; Holz, R.; Ackerman, S. A.; Heidinger, A. K.

2016-12-01

The launch of Suomi NPP in the fall of 2011 began the next generation of U.S. operational polar orbiting Earth observations, and its VIIRS imager provides an opportunity to extend the 15+ year climate data record of MODIS EOS. Similar to MODIS, VIIRS provides visible through IR observations at moderate spatial resolution with a 1330 LT equatorial crossing consistent with the MODIS on the Aqua platform. However, unlike MODIS, VIIRS lacks key water vapor and CO2 absorbing channels used for high cloud detection and cloud-top property retrievals, and there is a significant change in the spectral location of the 2.1μm shortwave-infrared channel used for cloud optical/microphysical retrievals and cloud thermodynamic phase. Given these instrument differences between MODIS EOS and VIIRS S-NPP/JPSS, we discuss our progress towards merging the MODIS observational record with VIIRS in order to generate cloud optical property climate data record continuity across the observing systems. The MODIS-VIIRS continuity algorithm for cloud optical property retrievals leverages heritage algorithms that produce the existing MODIS cloud optical and microphysical properties product (MOD06); the NOAA AWG/CLAVR-x cloud-top property algorithm and a common MODIS-VIIRS cloud mask feed into the optical property algorithm. To account for the different channel sets of MODIS and VIIRS, each algorithm nominally uses a subset of channels common to both imagers. Data granule and aggregated examples for the current version of the continuity algorithm (MODAWG) will be shown. In addition, efforts to reconcile apparent radiometric biases between analogous channels of the two imagers, a critical consideration for obtaining inter-sensor climate data record continuity, will be discussed.

Cost-effectiveness of MODY genetic testing: translating genomic advances into practical health applications.

PubMed

Naylor, Rochelle N; John, Priya M; Winn, Aaron N; Carmody, David; Greeley, Siri Atma W; Philipson, Louis H; Bell, Graeme I; Huang, Elbert S

2014-01-01

OBJECTIVE To evaluate the cost-effectiveness of a genetic testing policy for HNF1A-, HNF4A-, and GCK-MODY in a hypothetical cohort of type 2 diabetic patients 25-40 years old with a MODY prevalence of 2%. RESEARCH DESIGN AND METHODS We used a simulation model of type 2 diabetes complications based on UK Prospective Diabetes Study data, modified to account for the natural history of disease by genetic subtype to compare a policy of genetic testing at diabetes diagnosis versus a policy of no testing. Under the screening policy, successful sulfonylurea treatment of HNF1A-MODY and HNF4A-MODY was modeled to produce a glycosylated hemoglobin reduction of -1.5% compared with usual care. GCK-MODY received no therapy. Main outcome measures were costs and quality-adjusted life years (QALYs) based on lifetime risk of complications and treatments, expressed as the incremental cost-effectiveness ratio (ICER) (USD/QALY). RESULTS The testing policy yielded an average gain of 0.012 QALYs and resulted in an ICER of 205,000 USD. Sensitivity analysis showed that if the MODY prevalence was 6%, the ICER would be ~50,000 USD. If MODY prevalence was >30%, the testing policy was cost saving. Reducing genetic testing costs to 700 USD also resulted in an ICER of ~50,000 USD. CONCLUSIONS Our simulated model suggests that a policy of testing for MODY in selected populations is cost-effective for the U.S. based on contemporary ICER thresholds. Higher prevalence of MODY in the tested population or decreased testing costs would enhance cost-effectiveness. Our results make a compelling argument for routine coverage of genetic testing in patients with high clinical suspicion of MODY.

High-sensitivity CRP discriminates HNF1A-MODY from other subtypes of diabetes.

PubMed

McDonald, Tim J; Shields, Beverley M; Lawry, Jane; Owen, Katharine R; Gloyn, Anna L; Ellard, Sian; Hattersley, Andrew T

2011-08-01

Maturity-onset diabetes of the young (MODY) as a result of mutations in hepatocyte nuclear factor 1-α (HNF1A) is often misdiagnosed as type 1 diabetes or type 2 diabetes. Recent work has shown that high-sensitivity C-reactive protein (hs-CRP) levels are lower in HNF1A-MODY than type 1 diabetes, type 2 diabetes, or glucokinase (GCK)-MODY. We aim to replicate these findings in larger numbers and other MODY subtypes. hs-CRP levels were assessed in 750 patients (220 HNF1A, 245 GCK, 54 HNF4-α [HNF4A], 21 HNF1-β (HNF1B), 53 type 1 diabetes, and 157 type 2 diabetes). hs-CRP was lower in HNF1A-MODY (median [IQR] 0.3 [0.1-0.6] mg/L) than type 2 diabetes (1.40 [0.60-3.45] mg/L; P < 0.001) and type 1 diabetes (1.10 [0.50-1.85] mg/L; P < 0.001), HNF4A-MODY (1.45 [0.46-2.88] mg/L; P < 0.001), GCK-MODY (0.60 [0.30-1.80] mg/L; P < 0.001), and HNF1B-MODY (0.60 [0.10-2.8] mg/L; P = 0.07). hs-CRP discriminated HNF1A-MODY from type 2 diabetes with hs-CRP <0.75 mg/L showing 79% sensitivity and 70% specificity (receiver operating characteristic area under the curve = 0.84). hs-CRP levels are lower in HNF1A-MODY than other forms of diabetes and may be used as a biomarker to select patients for diagnostic HNF1A genetic testing.

Whole-exome sequencing and high throughput genotyping identified KCNJ11 as the thirteenth MODY gene.

PubMed

Bonnefond, Amélie; Philippe, Julien; Durand, Emmanuelle; Dechaume, Aurélie; Huyvaert, Marlène; Montagne, Louise; Marre, Michel; Balkau, Beverley; Fajardy, Isabelle; Vambergue, Anne; Vatin, Vincent; Delplanque, Jérôme; Le Guilcher, David; De Graeve, Franck; Lecoeur, Cécile; Sand, Olivier; Vaxillaire, Martine; Froguel, Philippe

2012-01-01

Maturity-onset of the young (MODY) is a clinically heterogeneous form of diabetes characterized by an autosomal-dominant mode of inheritance, an onset before the age of 25 years, and a primary defect in the pancreatic beta-cell function. Approximately 30% of MODY families remain genetically unexplained (MODY-X). Here, we aimed to use whole-exome sequencing (WES) in a four-generation MODY-X family to identify a new susceptibility gene for MODY. WES (Agilent-SureSelect capture/Illumina-GAIIx sequencing) was performed in three affected and one non-affected relatives in the MODY-X family. We then performed a high-throughput multiplex genotyping (Illumina-GoldenGate assay) of the putative causal mutations in the whole family and in 406 controls. A linkage analysis was also carried out. By focusing on variants of interest (i.e. gains of stop codon, frameshift, non-synonymous and splice-site variants not reported in dbSNP130) present in the three affected relatives and not present in the control, we found 69 mutations. However, as WES was not uniform between samples, a total of 324 mutations had to be assessed in the whole family and in controls. Only one mutation (p.Glu227Lys in KCNJ11) co-segregated with diabetes in the family (with a LOD-score of 3.68). No KCNJ11 mutation was found in 25 other MODY-X unrelated subjects. Beyond neonatal diabetes mellitus (NDM), KCNJ11 is also a MODY gene ('MODY13'), confirming the wide spectrum of diabetes related phenotypes due to mutations in NDM genes (i.e. KCNJ11, ABCC8 and INS). Therefore, the molecular diagnosis of MODY should include KCNJ11 as affected carriers can be ideally treated with oral sulfonylureas.

Identification of circulating microRNAs in HNF1A-MODY carriers.

PubMed

Bonner, C; Nyhan, K C; Bacon, S; Kyithar, M P; Schmid, J; Concannon, C G; Bray, I M; Stallings, R L; Prehn, J H M; Byrne, M M

2013-08-01

HNF1A-MODY is a monogenic form of diabetes caused by mutations in the HNF1A gene. Here we identify, for the first time, HNF1A-MODY-associated microRNAs (miRNAs) that can be detected in the serum of HNF1A-MODY carriers. An miRNA array was carried out in rat INS-1 insulinoma cells inducibly expressing the common human Pro291fsinsC-HNF1A frame shift mutation. Differentially expressed miRNAs were validated by quantitative real-time PCR. Expression of miRNAs in the serum of HNF1A-MODY carriers (n = 31), MODY-negative family members (n = 10) and individuals with type 2 diabetes mellitus (n = 17) was quantified by absolute real-time PCR analysis. Inducible expression of Pro291fsinsC-HNF1A in INS-1 cells caused a significant upregulation of three miRNAs (miR-103, miR-224, miR-292-3p). The differential expression of two miRNAs (miR-103 and miR-224) was validated in vitro. Strongly elevated levels of miR-103 and miR-224 could be detected in the serum of HNF1A-MODY carriers compared with MODY-negative family controls. Serum levels of miR-103 distinguished HNF1A-MODY carriers from HbA1c-matched individuals with type 2 diabetes mellitus. Our study demonstrates that the pathophysiology of HNF1A-MODY is associated with the overexpression of miR-103 and miR-224. Furthermore, our study demonstrates that these miRNAs can be readily detected in the serum of HNF1A-MODY carriers.

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.;

Co-variability of smoke and fire in the Amazon basin

NASA Astrophysics Data System (ADS)

Mishra, Amit Kumar; Lehahn, Yoav; Rudich, Yinon; Koren, Ilan

2015-05-01

The Amazon basin is a hot spot of anthropogenically-driven biomass burning, accounting for approximately 15% of total global fire emissions. It is essential to accurately measure these fires for robust regional and global modeling of key environmental processes. Here we have explored the link between spatio-temporal variability patterns in the Amazon basin's fires and the resulting smoke loading using 11 years (2002-2012) of data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Aerosol Robotic Network (AERONET) observations. Focusing on the peak burning season (July-October), our analysis shows strong inter-annual correlation between aerosol optical depth (AOD) and two MODIS fire products: fire radiative power (FRP) and fire pixel counts (FC). Among these two fire products, the FC better indicates the amount of smoke in the basin, as represented in remotely sensed AOD data. This fire product is significantly correlated both with regional AOD retrievals from MODIS and with point AOD measurements from the AERONET stations, pointing to spatial homogenization of the smoke over the basin on a seasonal time scale. However, MODIS AODs are found better than AERONET AODs observation for linking between smoke and fire. Furthermore, MODIS AOD measurements are strongly correlated with number of fires ∼10-20 to the east, most likely due to westward advection of smoke by the wind. These results can be rationalized by the regional topography and the wind regimes. Our analysis can improve data assimilation of satellite and ground-based observations into regional and global model studies, thus improving the assessment of the environmental and climatic impacts of frequency and distribution variability of the Amazon basin's fires. We also provide the optimal spatial and temporal scales for ground-based observations, which could be used for such applications.

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.

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.

An Operational Assessment of the MODIS False Color Composite with the Great Falls, Montana National Weather Service

NASA Technical Reports Server (NTRS)

Loss, GIna; Mercer, Michael; Fuell, Kevin K.; Stano, Geoffrey T.

2009-01-01

The close and productive collaborations between the NWS Warning and Forecast Office (WFO) in Great Falls, MT and the Short Term Prediction and Research Transition (SPORT) Center at NASA/Marshall Space Flight Center have provided a unique opportunity for science sharing and technology transfer. In particular, SPoRT has provided a false color composite product derived from MODIS data, which is part of NASA's Earth Observing System. This product is designed to delineate snow and ice covered ground, bare ground and clouds. The Great Falls WFO has been a test bed of the MODIS false color composite as a tool in operations to monitor the development and dissipation of snow cover In particular, preliminary applications have shown that the product can be used to monitor snow cover in remote locations as well as ice in rivers. This information can lead to improved assessments of flooding potential during post event conditions where rapid melting and runoff are anticipated. The potential of this product on future geostationary satellites may substantially contribute to the NWS mission by providing enhanced situational awareness. The operational use of this product has been transitioned at WFO Great Falls through a process of product implementation, discussions with the service hydrologist and forecasters, and post event analysis. A concentrated assessment period from January to March, 2008 was initiated to investigate the impact of the MODIS false color product on WFO Great Falls' operations. This presentation will emphasize the impact the MODIS false color product had in the WFO's situational awareness and how best this information can be used to influence operational decisions.

Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

NASA Technical Reports Server (NTRS)

Ulsig, Laura; Nichol, Caroline J.; Huemmrich, Karl F.; Landis, David R.; Middleton, Elizabeth M.; Lyapustin, Alexei I.; Mammarella, Ivan; Levula, Janne; Porcar-Castell, Albert

2017-01-01

Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI). This study investigates the potential of a Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS) were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction) processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R (sup 2) equals 0.36-0.8), which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R (sup 2) is greater than 0.6 in all cases). The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology.

Comparison of MODIS and VIIRS Snow Cover Products for the 2016 Hydrological Year

NASA Astrophysics Data System (ADS)

Klein, A. G.; Thapa, S.

2017-12-01

The VIIRS (Visible Infrared Imaging Radiometer Suite) instrument on board the Suomi-NPP satellite aims to provide long-term continuity of several environmental data series including snow cover initiated with MODIS. While it is speculated that MODIS and VIIRS snow cover products may differ because of their differing spatial resolutions and spectral coverage quantitative comparisons between their snow products are currently limited. Therefore this study intercompares MODIS and VIIRS snow products for the 2016 Hydrological Year over the Midwestern United States and southern Canada. Two hundred and forty-four swath snow products from MODIS/Aqua (MYD10L2) and the VIIRS EDR (VSCMO/binary) were intercompared using confusion matrices, comparison maps and false color imagery. Thresholding the MODIS NDSI Snow Cover product at a snow cover fraction of 30% generated binary snow maps most comparable to the NOAA VIIRS binary snow product. Overall agreement between MODIS and VIIRS was found to be approximately 98%. This exceeds the VIIRS accuracy requirements of 90% probability of correct typing. Agreement was highest during the winter but lower during late fall and spring. Comparability was lowest over forest. MODIS and VIIRS often mapped snow/no-snow transition zones as cloud. The assessment of total snow and cloud pixels and comparison snow maps of MODIS and VIIRS indicates that VIIRS is mapping more snow cover and less cloud cover compared to MODIS. This is evidenced by the average area of snow in MYD10L2 and VSCMO being 5.72% and 11.43%, no-snow 26.65% and 28.67%, and cloud 65.02% and 59.91%, respectively. Visual comparisons depict good qualitative agreement between snow cover area visible in MODIS and VIIRS false color imagery and mapped in their respective snow cover products. While VIIRS and MODIS have similar capacity to map snow cover, VIIRS has the potential to more accurately map snow cover area for the successive development of climate data records.

Synergism of MODIS Aerosol Remote Sensing from Terra and Aqua

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Kaufman, Yoram J.; Remer, Lorraine A.

2003-01-01

The MODerate-resolution Imaging Spectro-radiometer (MODIS) sensors, aboard the Earth Observing System (EOS) Terra and Aqua satellites, are showing excellent competence at measuring the global distribution and properties of aerosols. Terra and Aqua were launched on December 18, 1999 and May 4, 2002 respectively, with daytime equator crossing times of approximately 10:30 am and 1:30 pm respectively. Several aerosol parameters are retrieved at 10-km spatial resolution from MODIS daytime data over land and ocean surfaces. The parameters retrieved include: aerosol optical thickness (AOT) at 0.47, 0.55 and 0.66 micron wavelengths over land, and at 0.47, 0.55, 0.66, 0.87, 1.2, 1.6, and 2.1 microns over ocean; Angstrom exponent over land and ocean; and effective radii, and the proportion of AOT contributed by the small mode aerosols over ocean. Since the beginning of its operation, the quality of Terra-MODIS aerosol products (especially AOT) have been evaluated periodically by cross-correlation with equivalent data sets acquired by ground-based (and occasionally also airborne) sunphotometers, particularly those coordinated within the framework of the AErosol Robotic NETwork (AERONET). Terra-MODIS AOT data have been found to meet or exceed pre-launch accuracy expectations, and have been applied to various studies dealing with local, regional, and global aerosol monitoring. The results of these Terra-MODIS aerosol data validation efforts and studies have been reported in several scientific papers and conferences. Although Aqua-MODIS is still young, it is already yielding formidable aerosol data products, which are also subjected to careful periodic evaluation similar to that implemented for the Terra-MODIS products. This paper presents results of validation of Aqua-MODIS aerosol products with AERONET, as well as comparative evaluation against corresponding Terra-MODIS data. In addition, we show interesting independent and synergistic applications of MODIS aerosol data from both Terra and Aqua. In certain situations, this combined analysis of Terra- and Aqua-MODIS data offers an insight into the diurnal cycle of aerosol loading.

Prevalence of Retinopathy in Adult Patients with GCK-MODY and HNF1A-MODY.

PubMed

Szopa, M; Wolkow, J; Matejko, B; Skupien, J; Klupa, T; Wybrańska, I; Trznadel-Morawska, I; Kiec-Wilk, B; Borowiec, M; Malecki, M T

2015-10-01

We aimed to assess the prevalence of diabetic retinopathy (DR) in adult patients with GCK-MODY and HNF1A-MODY in Poland and to identify biochemical and clinical risk factors associated with its occurrence.We examined 74 GCK mutation carriers, 51 with diabetes and 23 with prediabetes, respectively, and 63 patients with HNF1A-MODY. Retinal photographs, 12 for each patient, were done by a fundus camera. Signs of DR were graded according to the DR disease severity scale. Statistical tests were performed to assess differences between the groups and logistic regression was done for the association with DR.The mean age at examination was 34.5±14.8 and 39.9±15.2 in the GCK-MODY and HNF1A-MODY groups, respectively. Mild nonproliferative DR (NPDR) was found in one patient with the GCK mutation and likely concomitant type 1 diabetes, whereas DR was diagnosed in 15 HNF1A-MODY patients: 9 with proliferative, 3 with moderate NPDR and 2 with mild NPDR. In univariate logistic regression analysis in the HNF1A-MODY group, significant results were found for diabetes duration, fasting glycemia, HbA1c, arterial hypertension, age at the examination, and eGFR. The strongest independent predictors of DR in HNF1A-MODY were markers of glucose control: HbA1c (OR: 2.05, CL%95: 1.2-3.83, p=0.01) and glucose (p=0.006, OR: 1.40, CL%95: 1.12-1.83) analyzed in 2 separated models. Additionally, arterial hypertension independently predicted DR (OR: 9.06, CL%95: 1.19-98.99, p=0.04) in the model with HbA1c as glycaemic control marker.In conclusion, DR of any degree was not present in our GCK-MODY group, while in spite of young age almost every fourth subject with HNF1A-MODY showed signs of this complication. © Georg Thieme Verlag KG Stuttgart · New York.

Validation of ET maps derived from MODIS imagery

NASA Astrophysics Data System (ADS)

Hong, S.; Hendrickx, J. M.; Borchers, B.

2005-12-01

In previous work we have used the New Mexico Tech implementation of the Surface Energy Balance Algorithm for Land (SEBAL-NMT) for the generation of ET maps from LandSat imagery. Comparison of these SEBAL ET estimates versus ET ground measurements using eddy covariance showed satisfactory agreement between the two methods in the heterogeneous arid landscape of the Middle Rio Grande Basin. The objective of this study is to validate SEBAL ET estimates obtained from MODIS imagery. The use of MODIS imagery is attractive since MODIS images are available at a much higher frequency than LandSat images at no cost to the user. MODIS images have a pixel size in the thermal band of 1000x1000 m which is much coarser than the 60x60 m pixel size of LandSat 7. This large pixel size precludes the use of eddy covariance measurements for validation of ET maps derived from MODIS imagery since the eddy covariance measurement is not representative of a 1000x1000 m MODIS pixel. In our experience, a typical foot print of an ET rate measured by eddy covariance on a clear day in New Mexico around 11 am is less than then thousand square meters or two orders of magnitude smaller than a MODIS thermal pixel. Therefore, we have validated ET maps derived from MODIS imagery by comparison with up-scaled ET maps derived from LandSat imagery. The results of our study demonstrate: (1) There is good agreement between ET maps derived from LandSat and MODIS images; (2) Up-scaling of LandSat ET maps over the Middle Rio Grande Basin produces ET maps that are very similar to ET maps directly derived from MODIS images; (3) ET maps derived from free MODIS imagery using SEBAL-NMT can provide reliable regional ET information for water resource managers.

Continuity of MODIS and VIIRS Snow-Cover Maps during Snowmelt in the Catskill Mountains in New York

NASA Astrophysics Data System (ADS)

Hall, D. K.; Riggs, G. A., Jr.; Roman, M. O.; DiGirolamo, N. E.

2015-12-01

We investigate the local and regional differences and possible biases between the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible-Infrared Imager Radiometer Suite (VIIRS) snow-cover maps in the winter of 2012 during snowmelt conditions in the Catskill Mountains in New York using a time series of cloud-gap filled daily snow-cover maps. The MODIS Terra instrument has been providing daily global snow-cover maps since February 2000 (Riggs and Hall, 2015). Using the VIIRS instrument, launched in 2011, NASA snow products are being developed based on the heritage MODIS snow-mapping algorithms, and will soon be available to the science community. Continuity of the standard NASA MODIS and VIIRS snow-cover maps is essential to enable environmental-data records (EDR) to be developed for analysis of snow-cover trends using a consistent data record. For this work, we compare daily MODIS and VIIRS snow-cover maps of the Catskill Mountains from 29 February through 14 March 2012. The entire region was snow covered on 29 February and by 14 March the snow had melted; we therefore have a daily time series available to compare normalized difference snow index (NDSI), as an indicator of snow-cover fraction. The MODIS and VIIRS snow-cover maps have different spatial resolutions (500 m for MODIS and 375 m for VIIRS) and different nominal overpass times (10:30 AM for MODIS Terra and 2:30 PM for VIIRS) as well as different cloud masks. The results of this work will provide a quantitative assessment of the continuity of the snow-cover data records for use in development of an EDR of snow cover.http://modis-snow-ice.gsfc.nasa.gov/Riggs, G.A. and D.K. Hall, 2015: MODIS Snow Products User Guide to Collection 6, http://modis-snow-ice.gsfc.nasa.gov/?c=userguides

Rapid update of discrete Fourier transform for real-time signal processing

NASA Astrophysics Data System (ADS)

Sherlock, Barry G.; Kakad, Yogendra P.

2001-10-01

In many identification and target recognition applications, the incoming signal will have properties that render it amenable to analysis or processing in the Fourier domain. In such applications, however, it is usually essential that the identification or target recognition be performed in real time. An important constraint upon real-time processing in the Fourier domain is the time taken to perform the Discrete Fourier Transform (DFT). Ideally, a new Fourier transform should be obtained after the arrival of every new data point. However, the Fast Fourier Transform (FFT) algorithm requires on the order of N log2 N operations, where N is the length of the transform, and this usually makes calculation of the transform for every new data point computationally prohibitive. In this paper, we develop an algorithm to update the existing DFT to represent the new data series that results when a new signal point is received. Updating the DFT in this way uses less computational order by a factor of log2 N. The algorithm can be modified to work in the presence of data window functions. This is a considerable advantage, because windowing is often necessary to reduce edge effects that occur because the implicit periodicity of the Fourier transform is not exhibited by the real-world signal. Versions are developed in this paper for use with the boxcar window, the split triangular, Hanning, Hamming, and Blackman windows. Generalization of these results to 2D is also presented.

Circulating CD36 is reduced in HNF1A-MODY carriers.

PubMed

Bacon, Siobhan; Kyithar, Ma P; Schmid, Jasmin; Costa Pozza, Andre; Handberg, Aase; Byrne, Maria M

2013-01-01

Premature atherosclerosis is a significant cause of morbidity and mortality in type 2 diabetes mellitus. Maturity onset diabetes of the young (MODY) accounts for approximately 2% of all diabetes, with mutations in the transcription factor; hepatocyte nuclear factor 1 alpha (HNF1A) accounting for the majority of MODY cases. There is somewhat limited data available on the prevalence of macrovascular disease in HNF1A-MODY carriers with diabetes. Marked insulin resistance and the associated dyslipidaemia are not clinical features of HNF1A-MODY carriers. The scavenger protein CD36 has been shown to play a substantial role in the pathogenesis of atherosclerosis, largely through its interaction with oxidised LDL. Higher levels of monocyte CD36 and plasma CD36(sCD36) are seen to cluster with insulin resistance and diabetes. The aim of this study was to determine levels of sCD36 in participants with HNF1A-MODY diabetes and to compare them with unaffected normoglycaemic family members and participants with type 2 diabetes mellitus. We recruited 37 participants with HNF1A-MODY diabetes and compared levels of sCD36 with BMI-matched participants with type 2 diabetes mellitus and normoglycaemic HNF1A-MODY negative family controls. Levels of sCD36 were correlated with phenotypic and biochemical parameters. HNF1A-MODY participants were lean, normotensive, with higher HDL and lower triglyceride levels when compared to controls and participants with type 2 diabetes mellitus. sCD36 was also significantly lower in HNF1A-MODY participants when compared to both the normoglycaemic family controls and to lean participants with type 2 diabetes mellitus. In conclusion, sCD36 is significantly lower in lean participants with HNF1A-MODY diabetes when compared to weight-matched normoglycaemic familial HNF1A-MODY negative controls and to lean participants with type 2 diabetes mellitus. Lower levels of this pro-atherogenic marker may result from the higher HDL component in the lipid profile of HNF1A-MODY participants.

Lipoprotein composition in HNF1A-MODY: differentiating between HNF1A-MODY and type 2 diabetes.

PubMed

McDonald, Tim J; McEneny, Jane; Pearson, Ewan R; Thanabalasingham, Gaya; Szopa, Magdalena; Shields, Beverley M; Ellard, Sian; Owen, Katharine R; Malecki, Maciej T; Hattersley, Andrew T; Young, Ian S

2012-05-18

The young-onset diabetes seen in HNF1A-MODY is often misdiagnosed as Type 2 diabetes. Type 2 diabetes, unlike HNF1A-MODY, is associated with insulin resistance and a characteristic dyslipidaemia. We aimed to compare the lipid profiles in HNF1A-MODY, Type 2 diabetes and control subjects and to determine if lipids can be used to aid the differential diagnosis of diabetes sub-type. 1) 14 subjects in each group (HNF1A-MODY, Type 2 diabetes and controls) were matched for gender and BMI. Fasting lipid profiles and HDL lipid constituents were compared in the 3 groups. 2) HDL-cholesterol was assessed in a further 267 patients with HNF1A-MODY and 297 patients with a diagnosis of Type 2 diabetes to determine its discriminative value. 1) In HNF1A-MODY subjects, plasma-triglycerides were lower (1.36 vs. 1.93 mmol/l, p = 0.07) and plasma-HDL-cholesterol was higher than in subjects with Type 2 diabetes (1.47 vs. 1.15 mmol/l, p = 0.0008), but was similar to controls. Furthermore, in the isolated HDL; HDL-phospholipid and HDL-cholesterol ester content were higher in HNF1A-MODY, than in Type 2 diabetes (1.59 vs. 1.33 mmol/L, p = 0.04 and 1.10 vs. 0.83 mmol/L, p = 0.019, respectively), but were similar to controls (1.59 vs. 1.45 mmol/L, p = 0.35 and 1.10 vs. 1.21 mmol/L, p = 0.19, respectively). 2) A plasma-HDL-cholesterol > 1.12 mmol/L was 75% sensitive and 64% specific (ROC AUC = 0.76) at discriminating HNF1A-MODY from Type 2 diabetes. The plasma-lipid profiles of HNF1A-MODY and the lipid constituents of HDL are similar to non-diabetic controls. However, HDL-cholesterol was higher in HNF1A-MODY than in Type 2 diabetes and could be used as a biomarker to aid in the identification of patients with HNF1A-MODY. Copyright © 2012 Elsevier B.V. All rights reserved.

Satellite Remote Sensing for Developing Time and Space Resolved Estimates of Ambient Particulate in Cleveland, OH.

PubMed

Kumar, Naresh; Chu, Allen D; Foster, Andrew D; Peters, Thomas; Willis, Robert

2011-09-01

This article empirically demonstrates the use of fine resolution satellite-based aerosol optical depth (AOD) to develop time and space resolved estimates of ambient particulate matter (PM) ≤2.5 µm and ≤10 µm in aerodynamic diameters (PM(2.5) and PM(10), respectively). AOD was computed at three different spatial resolutions, i.e., 2 km (means 2 km × 2 km area at nadir), 5 km, and 10 km, by using the data from MODerate Resolution Imaging Spectroradiometer (MODIS), aboard the Terra and Aqua satellites. Multiresolution AOD from MODIS (AOD(MODIS)) was compared with the in situ measurements of AOD by NASA's AErosol RObotic NETwork (AERONET) sunphotometer (AOD(AERONET)) at Bondville, IL, to demonstrate the advantages of the fine resolution AOD(MODIS) over the 10-km AOD(MODIS), especially for air quality prediction. An instrumental regression that corrects AOD(MODIS) for meteorological conditions was used for developing a PM predictive model.The 2-km AOD(MODIS) aggregated within 0.025° and 15-min intervals shows the best association with the in situ measurements of AOD(AERONET). The 2-km AOD(MODIS) seems more promising to estimate time and space resolved estimates of ambient PM than the 10-km AOD(MODIS), because of better location precision and a significantly greater number of data points across geographic space and time. Utilizing the collocated AOD(MODIS) and PM data in Cleveland, OH, a regression model was developed for predicting PM for all AOD(MODIS) data points. Our analysis suggests that the slope of the 2-km AOD(MODIS) (instrumented on meteorological conditions) is close to unity with the PM monitored on the ground. These results should be interpreted with caution, because the slope of AOD(MODIS) ranges from 0.52 to 1.72 in the site-specific models. In the cross validation of the overall model, the root mean square error (RMSE) of PM(10) was smaller (2.04 µg/m(3) in overall model) than that of PM(2.5) (2.5 µg/m(3)). The predicted PM in the AOD(MODIS) data (∼2.34 million data points) was utilized to develop a systematic grid of daily PM at 5-km spatial resolution with the aid of spatiotemporal Kriging.

A single dose of dapagliflozin, an SGLT-2 inhibitor, induces higher glycosuria in GCK- and HNF1A-MODY than in type 2 diabetes mellitus.

PubMed

Hohendorff, J; Szopa, M; Skupien, J; Kapusta, M; Zapala, B; Platek, T; Mrozinska, S; Parpan, T; Glodzik, W; Ludwig-Galezowska, A; Kiec-Wilk, B; Klupa, T; Malecki, M T

2017-08-01

SGLT2 inhibitors are a new class of oral hypoglycemic agents used in type 2 diabetes (T2DM). Their effectiveness in maturity onset diabetes of the young (MODY) is unknown. We aimed to assess the response to a single dose of 10 mg dapagliflozin in patients with Hepatocyte Nuclear Factor 1 Alpha (HNF1A)-MODY, Glucokinase (GCK)-MODY, and type 2 diabetes. We examined 14 HNF1A-MODY, 19 GCK-MODY, and 12 type 2 diabetes patients. All studied individuals received a single morning dose of 10 mg of dapagliflozin added to their current therapy of diabetes. To assess the response to dapagliflozin we analyzed change in urinary glucose to creatinine ratio and serum 1,5-Anhydroglucitol (1,5-AG) level. There were only four patients with positive urine glucose before dapagliflozin administration (one with HNF1A-MODY, two with GCK-MODY, and one with T2DM), whereas after SGLT-2 inhibitor use, glycosuria occurred in all studied participants. Considerable changes in mean glucose to creatinine ratio after dapagliflozin administration were observed in all three groups (20.51 ± 12.08, 23.19 ± 8.10, and 9.84 ± 6.68 mmol/mmol for HNF1A-MODY, GCK-MODY, and T2DM, respectively, p < 0.001 for all comparisons). Post-hoc analysis revealed significant differences in mean glucose to creatinine ratio change between type 2 diabetes and each monogenic diabetes in response to dapagliflozin (p = 0.02, p = 0.003 for HNF1-A and GCK MODY, respectively), but not between the two MODY forms (p = 0.7231). Significant change in serum 1,5-AG was noticed only in T2DM and it was -6.57 ± 7.34 mg/ml (p = 0.04). A single dose of dapagliflozin, an SGLT-2 inhibitor, induces higher glycosuria in GCK- and HNF1A-MODY than in T2DM. Whether flozins are a valid therapeutic option in these forms of MODY requires long-term clinical studies.

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.

Terra and Aqua MODIS Design, Radiometry, and Geometry in Support of Land Remote Sensing

NASA Technical Reports Server (NTRS)

Xiong, Xiaoxiong; Wolfe, Robert; Barnes, William; Guenther, Bruce; Vermote, Eric; Saleous, Nazmi; Salomonson, Vincent

2011-01-01

The NASA Earth Observing System (EOS) mission includes the construction and launch of two nearly identical Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. The MODIS proto-flight model (PFM) is onboard the EOS Terra satellite (formerly EOS AM-1) launched on December 18, 1999 and hereafter referred to as Terra MODIS. Flight model-1 (FM1) is onboard the EOS Aqua satellite (formerly EOS PM-1) launched on May 04, 2002 and referred to as Aqua MODIS. MODIS was developed based on the science community s desire to collect multiyear continuous datasets for monitoring changes in the Earth s land, oceans and atmosphere, and the human contributions to these changes. It was designed to measure discrete spectral bands, which includes many used by a number of heritage sensors, and thus extends the heritage datasets to better understand both long- and short-term changes in the global environment (Barnes and Salomonson 1993; Salomonson et al. 2002; Barnes et al. 2002). The MODIS development, launch, and operation were managed by NASA/Goddard Space Flight Center (GSFC), Greenbelt, Maryland. The sensors were designed, built, and tested by Raytheon/ Santa Barbara Remote Sensing (SBRS), Goleta, California. Each MODIS instrument offers 36 spectral bands, which span the spectral region from the visible (0.41 m) to long-wave infrared (14.4 m). MODIS collects data at three different nadir spatial resolutions: 0.25, 0.5, and 1 km. Key design specifications, such as spectral bandwidths, typical scene radiances, required signal-to-noise ratios (SNR) or noise equivalent temperature differences (NEDT), and primary applications of each MODIS spectral band are summarized in Table 7.1. These parameters were the basis for the MODIS design. More details on the evolution of the NASA EOS and development of the MODIS instruments are provided in Chap. 1. This chapter focuses on the MODIS sensor design, radiometry, and geometry as they apply to land remote sensing. With near-daily coverage of the Earth's surface, MODIS provides comprehensive measurements that enable scientists and policy makers to better understand and effectively manage the natural resources on both regional and global scales. Terra, the first large multisensor EOS satellite, is operated in a 10:30 am (local equatorial crossing time, descending southwards) polar orbit. Aqua, the second multisensor EOS satellite is operated in a 1:30 pm (local equatorial crossing time, ascending northwards) polar orbit. With complementing morning and afternoon observations, the Terra and Aqua MODIS, together with other sensors housed on both satellites, have greatly improved our understanding of the dynamics of the global environmental system.

Evaluation of MODIS Land Surface Temperature with In Situ Snow Surface Temperature from CREST-SAFE

NASA Astrophysics Data System (ADS)

Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Munoz, J.; Khanbilvardi, R.; Yu, Y.

2016-12-01

This paper presents the procedure and results of a temperature-based validation approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) product provided by the National Aeronautics and Space Administration (NASA) Terra and Aqua Earth Observing System satellites using in situ LST observations recorded at the Cooperative Remote Sensing Science and Technology Center - Snow Analysis and Field Experiment (CREST-SAFE) during the years of 2013 (January-April) and 2014 (February-April). A total of 314 day and night clear-sky thermal images, acquired by the Terra and Aqua satellites, were processed and compared to ground-truth data from CREST-SAFE with a frequency of one measurement every 3 min. Additionally, this investigation incorporated supplementary analyses using meteorological CREST-SAFE in situ variables (i.e. wind speed, cloud cover, incoming solar radiation) to study their effects on in situ snow surface temperature (T-skin) and T-air. Furthermore, a single pixel (1km2) and several spatially averaged pixels were used for satellite LST validation by increasing the MODIS window size to 5x5, 9x9, and 25x25 windows for comparison. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and nighttime values. Results indicate that, although all the data sets (Terra and Aqua, diurnal and nocturnal) showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C), both suggesting that MODIS LST retrievals are reliable for similar land cover classes and atmospheric conditions. Results from the CREST-SAFE in situ variables' analyses indicate that T-air is commonly higher than T-skin, and that a lack of cloud cover results in: lower T-skin and higher T-air minus T-skin difference (T-diff). Additionally, the study revealed that T-diff is inversely proportional to cloud cover, wind speed, and incoming solar radiation. Increasing the MODIS window size showed an overestimation of in situ LST and some improvement in the daytime Terra and nighttime Aqua biases, with the highest accuracy achieved with the 5x5 window. A comparison between MODIS emmisivity from bands 31, 32, and in situ emissivity showed that emissivity errors (Relative error = -.003) were insignificant.

Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.; Roman, Miguel O.

2017-01-01

Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6) and VIIRS Collection 1 (C1) represent the state-of-the-art global snow cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map.The increased data content allows flexibility in using the datasets for specific regions and end-user applications.Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375m native resolution compared to MODIS 500 m), the snow detection algorithms and data products are designed to be as similar as possible so that the 16C year MODIS ESDR of global SCE can be extended into the future with the S-NPP VIIRS snow products and with products from future Joint Polar Satellite System (JPSS) platforms.These NASA datasets are archived and accessible through the NASA Distributed Active Archive Center at the National Snow and Ice Data Center in Boulder, Colorado.

High-speed spectral domain optical coherence tomography using non-uniform fast Fourier transform

PubMed Central

Chan, Kenny K. H.; Tang, Shuo

2010-01-01

The useful imaging range in spectral domain optical coherence tomography (SD-OCT) is often limited by the depth dependent sensitivity fall-off. Processing SD-OCT data with the non-uniform fast Fourier transform (NFFT) can improve the sensitivity fall-off at maximum depth by greater than 5dB concurrently with a 30 fold decrease in processing time compared to the fast Fourier transform with cubic spline interpolation method. NFFT can also improve local signal to noise ratio (SNR) and reduce image artifacts introduced in post-processing. Combined with parallel processing, NFFT is shown to have the ability to process up to 90k A-lines per second. High-speed SD-OCT imaging is demonstrated at camera-limited 100 frames per second on an ex-vivo squid eye. PMID:21258551

A Simple, Scalable, Script-based Science Processor

NASA Technical Reports Server (NTRS)

Lynnes, Christopher

2004-01-01

The production of Earth Science data from orbiting spacecraft is an activity that takes place 24 hours a day, 7 days a week. At the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC), this results in as many as 16,000 program executions each day, far too many to be run by human operators. In fact, when the Moderate Resolution Imaging Spectroradiometer (MODIS) was launched aboard the Terra spacecraft in 1999, the automated commercial system for running science processing was able to manage no more than 4,000 executions per day. Consequently, the GES DAAC developed a lightweight system based on the popular Per1 scripting language, named the Simple, Scalable, Script-based Science Processor (S4P). S4P automates science processing, allowing operators to focus on the rare problems occurring from anomalies in data or algorithms. S4P has been reused in several systems ranging from routine processing of MODIS data to data mining and is publicly available from NASA.

A hybrid color mapping approach to fusing MODIS and Landsat images for forward prediction

USDA-ARS?s Scientific Manuscript database

We present a new, simple, and efficient approach to fusing MODIS and Landsat images. It is well known that MODIS images have high temporal resolution and low spatial resolution whereas Landsat images are just the opposite. Similar to earlier approaches, our goal is to fuse MODIS and Landsat images t...

Zonal Aerosol Direct and Indirect Radiative Forcing using Combined CALIOP, CERES, CloudSat, and CERES Data

NASA Astrophysics Data System (ADS)

Miller, W. F.; Kato, S.; Rose, F. G.; Sun-Mack, S.

2009-12-01

Under the NASA Energy and Water Cycle System (NEWS) program, cloud and aerosol properties derived from CALIPSO, CloudSat, and MODIS data then matched to the CERES footprint are used for irradiance profile computations. Irradiance profiles are included in the publicly available product, CCCM. In addition to the MODIS and CALIPSO generated aerosol, aerosol optical thickness is calculated over ocean by processing MODIS radiance through the Stowe-Ignatov algorithm. The CERES cloud mask and properties algorithm are use with MODIS radiance to provide additional cloud information to accompany the actively sensed data. The passively sensed data is the only input to the standard CERES radiative flux products. The combined information is used as input to the NASA Langley Fu-Liou radiative transfer model to determine vertical profiles and Top of Atmosphere shortwave and longwave flux for pristine, all-sky, and aerosol conditions for the special data product. In this study, the three sources of aerosol optical thickness will be compared directly and their influence on the calculated and measured TOA fluxes. Earlier studies indicate that the largest uncertainty in estimating direct aerosol forcing using aerosol optical thickness derived from passive sensors is caused by cloud contamination. With collocated CALIPSO data, we are able to estimate frequency of occurrence of cloud contamination, effect on the aerosol optical thickness and direct radiative effect estimates.

Fourier domain asymmetric cryptosystem for privacy protected multimodal biometric security

NASA Astrophysics Data System (ADS)

Choudhury, Debesh

2016-04-01

We propose a Fourier domain asymmetric cryptosystem for multimodal biometric security. One modality of biometrics (such as face) is used as the plaintext, which is encrypted by another modality of biometrics (such as fingerprint). A private key is synthesized from the encrypted biometric signature by complex spatial Fourier processing. The encrypted biometric signature is further encrypted by other biometric modalities, and the corresponding private keys are synthesized. The resulting biometric signature is privacy protected since the encryption keys are provided by the human, and hence those are private keys. Moreover, the decryption keys are synthesized using those private encryption keys. The encrypted signatures are decrypted using the synthesized private keys and inverse complex spatial Fourier processing. Computer simulations demonstrate the feasibility of the technique proposed.

Capability of MODIS radiance to analyze Iberian turbid plumes

NASA Astrophysics Data System (ADS)

Fernandez-Novoa, Diego; deCastro, Maite; Des, Marisela; Costoya, Xurxo; Mendes, Renato; Gomez-Gesteira, Moncho

2017-04-01

River plumes are formed near river mouths by freshwater and riverine materials. Therefore, the area influenced by freshwater (salinity plume) is usually negatively correlated with the area occupied by suspension and dissolved material (turbid plume). Suspended material results in a strong signal detected by satellite sensors whereas ocean clear waters have negligible contributions. Thus, remote sensing data, such as radiance obtained from Moderate Resolution Imaging Spectroradiometer (MODIS), are a very useful tool to analyze turbid plumes due to the high spatial and time resolution provided. Here, MODIS capability for characterizing similarities and differences among the most important Iberian plumes was assessed under the influence of their main forcing. Daily radiance data from MODIS-Aqua and MODIS-Terra satellite sensors were processed obtaining a resolution of 500 m. Two approaches are usually used for atmospheric correction treatments: Near-Infrared (NIR) bands and a combined algorithm using NIR and Short Wave Infrared (SWIR) bands. In the particular case of Iberian Peninsula plumes both methods offered similar results, although NIR bands present a lower associated error. MODIS allows working with several bands of normalized water-leaving radiances (nLw). Focusing in the resolution provided, nLw555 and 645 were the most appropriate because both provide the best coverage and correlation with river discharge. The nLw645 band was chosen because has a lower water penetration avoiding overestimations of turbidity caused by shallow seafloor areas and/or upwelling blooms. Daily data from both satellites were merged to enhance the robustness and precision of the study by increasing the number of available pixels. Results indicate that differences between radiance data from both satellites are negligible for Iberian plumes, justifying the merging. By last, each turbid limit, to delimit the respective plume from adjacent seawater, was obtained using two alternative methods. The first method evaluates the maximum correlation between river discharge and plume extension and the second one analyzes a histogram of radiance distribution for days characterized by a negligible plume and days showing a well-developed plume. The capability of MODIS radiance to delimit each river plume was tested by means of salinity data from Atlantic-Iberian Biscay Irish-Ocean Physics Reanalysis (IBI) database. Significant and negative correlations were found in the Atlantic Iberian plumes, showing the capability of MODIS to adequately track them. However, no correlation was found for Ebro River. This discrepancy is due to the presence of fresh water associated to other external sources (Rhone River), promoting low salinity values when Ebro discharge is low. In this particular case, the MODIS methodology is better to determine the river plume. In general, Atlantic Iberian plumes show a moderate or high dependence on river discharge, being wind a secondary forcing and tide the third one, although each plume presents particular features. On the other hand, Ebro plume has low dependence on river discharge and wind, and a negligible one on tide, being mainly driven for the Liguro-Provençal current.

Mutations of maturity-onset diabetes of the young (MODY) genes in Thais with early-onset type 2 diabetes mellitus.

PubMed

Plengvidhya, Nattachet; Boonyasrisawat, Watip; Chongjaroen, Nalinee; Jungtrakoon, Prapaporn; Sriussadaporn, Sutin; Vannaseang, Sathit; Banchuin, Napatawn; Yenchitsomanus, Pa-thai

2009-06-01

Six known genes responsible for maturity-onset diabetes of the young (MODY) were analysed to evaluate the prevalence of their mutations in Thai patients with MODY and early-onset type 2 diabetes. Fifty-one unrelated probands with early-onset type 2 diabetes, 21 of them fitted into classic MODY criteria, were analysed for nucleotide variations in promoters, exons, and exon-intron boundaries of six known MODY genes, including HNF-4alpha, GCK, HNF-1alpha, IPF-1, HNF-1beta, and NeuroD1/beta2, by the polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) method followed by direct DNA sequencing. Missense mutations or mutations located in regulatory region, which were absent in 130 chromosomes of non-diabetic controls, were classified as potentially pathogenic mutations. We found that mutations of the six known MODY genes account for a small proportion of classic MODY (19%) and early-onset type 2 diabetes (10%) in Thais. Five of these mutations are novel including GCK R327H, HNF-1alpha P475L, HNF-1alphaG554fsX556, NeuroD1-1972 G > A and NeuroD1 A322N. Mutations of IPF-1 and HNF-1beta were not identified in the studied probands. Mutations of the six known MODY genes may not be a major cause of MODY and early-onset type 2 diabetes in Thais. Therefore, unidentified genes await discovery in a majority of Thai patients with MODY and early-onset type 2 diabetes.

Searching for Maturity-Onset Diabetes of the Young (MODY): When and What for?

PubMed

Timsit, José; Saint-Martin, Cécile; Dubois-Laforgue, Danièle; Bellanné-Chantelot, Christine

2016-10-01

Maturity-onset diabetes of the young (MODY) is a group of monogenic diseases that results in primary defects in insulin secretion and dominantly inherited forms of nonautoimmune diabetes. Although many genes may be associated with monogenic diabetes, heterozygous mutations in 6 of them are responsible for the majority of cases of MODY. Glucokinase (GCK)-MODY is due to mutations in the glucokinase gene, 3 MODY subtypes are associated with mutations in the hepatocyte nuclear factor (HNF) transcription factors, and 2 others with mutations in ABCC8 and KCNJ11, which encode the subunits of the ATP-dependent potassium channel in pancreatic beta cells. GCK-MODY and HNF1A-MODY are the most common subtypes. The clinical presentation of MODY subtypes has been reported to differ according to the gene involved, and the diagnosis of MODY may be considered in various clinical circumstances. However, except in patients with GCK-MODY whose phenotype is very homogeneous, in most cases the penetrance and expressivity of a given molecular abnormality vary greatly among patients and, conversely, alterations in various genes may lead to similar phenotypes. Moreover, differential diagnosis among more common forms of diabetes may be difficult, particularly with type 2 diabetes. Thus, careful assessment of the personal and family histories of patients with diabetes is mandatory to select those in whom genetic screening is worthwhile. The diagnosis of monogenic diabetes has many consequences in terms of prognosis, therapeutics and family screening. Copyright © 2015 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

Preliminary validation of the military low back pain questionnaire.

PubMed

Roy, Tanja C; Fish, Karen L; Lopez, Heather P; Piva, Sara R

2014-02-01

Soldiers must perform a variety of physical tasks that the civilian population does not. The Modified Oswestry Disability Index (M-ODI) is the most widely used measure of function in patients with low back pain but does not include military tasks. The Military Low Back Pain Questionnaire (MBQ) was developed by military Physical Therapists to include tasks such as wearing body armor. The purpose of this study was to provide preliminary evidence for the reliability, responsiveness, and validity of the MBQ in nondeployed Soldiers. The MBQ had good reliability compared to the M-ODI. The inter-rater correlation coefficient for the M-ODI was 0.79 and 0.75 for the MBQ. Cronbach's alpha was 0.75 and 0.85 for the M-ODI and MBQ, respectively. The minimal detectable change for the M-ODI was 21.03 and 22.97 for the MBQ. Responsiveness was assessed using a global rating of change; area under the curve for the M-ODI was 0.82 and 0.90 for the MBQ. The correlation between the M-ODI and the MBQ was r = 0.80 indicating good concurrent validity. The MBQ was as reliable as the M-ODI in an Army population. There were trends in the psychometrics suggesting the MBQ may be more sensitive to change than the M-ODI in this population. Reprint & Copyright © 2014 Association of Military Surgeons of the U.S.

Level 1 Processing of MODIS Direct Broadcast Data From Terra

NASA Technical Reports Server (NTRS)

Lynnes, Christopher; Smith, Peter; Shotland, Larry; El-Ghazawi, Tarek; Zhu, Ming

2000-01-01

In February 2000, an effort was begun to adapt the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 1 production software to process direct broadcast data. Three Level 1 algorithms have been adapted and packaged for release: Level 1A converts raw (level 0) data into Hierarchical Data Format (HDF), unpacking packets into scans; Geolocation computes geographic information for the data points in the Level 1A; and the Level 1B computes geolocated, calibrated radiances from the Level 1A and Geolocation products. One useful aspect of adapting the production software is the ability to incorporate enhancements contributed by the MODIS Science Team. We have therefore tried to limit changes to the software. However, in order to process the data immediately on receipt, we have taken advantage of a branch in the geolocation software that reads orbit and altitude information from the packets themselves, rather than external ancillary files used in standard production. We have also verified that the algorithms can be run with smaller time increments (2.5 minutes) than the five-minute increments used in production. To make the code easier to build and run, we have simplified directories and build scripts. Also, dependencies on a commercial numerics library have been replaced by public domain software. A version of the adapted code has been released for Silicon Graphics machines running lrix. Perhaps owing to its origin in production, the software is rather CPU-intensive. Consequently, a port to Linux is underway, followed by a version to run on PC clusters, with an eventual goal of running in near-real-time (i.e., process a ten-minute pass in ten minutes).

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...

View Angle Effects on MODIS Snow Mapping in Forests

NASA Technical Reports Server (NTRS)

Xin, Qinchuan; Woodcock, Curtis E.; Liu, Jicheng; Tan, Bin; Melloh, Rae A.; Davis, Robert E.

2012-01-01

Binary snow maps and fractional snow cover data are provided routinely from MODIS (Moderate Resolution Imaging Spectroradiometer). This paper investigates how the wide observation angles of MODIS influence the current snow mapping algorithm in forested areas. Theoretical modeling results indicate that large view zenith angles (VZA) can lead to underestimation of fractional snow cover (FSC) by reducing the amount of the ground surface that is viewable through forest canopies, and by increasing uncertainties during the gridding of MODIS data. At the end of the MODIS scan line, the total modeled error can be as much as 50% for FSC. Empirical analysis of MODIS/Terra snow products in four forest sites shows high fluctuation in FSC estimates on consecutive days. In addition, the normalized difference snow index (NDSI) values, which are the primary input to the MODIS snow mapping algorithms, decrease as VZA increases at the site level. At the pixel level, NDSI values have higher variances, and are correlated with the normalized difference vegetation index (NDVI) in snow covered forests. These findings are consistent with our modeled results, and imply that consideration of view angle effects could improve MODIS snow monitoring in forested areas.

Space environment's effect on MODIS calibration

NASA Astrophysics Data System (ADS)

Dodd, J. L.; Wenny, B. N.; Chiang, K.; Xiong, X.

2010-09-01

The MODerate resolution Imaging Spectroradiometer flies on board the Earth Observing System (EOS) satellites Terra and Aqua in a sun-synchronous orbit that crosses the equator at 10:30 AM and 2:30 PM, respectively, at a low earth orbit (LEO) altitude of 705 km. Terra was launched on December 18,1999 and Aqua was launched on May 4, 2002. As the MODIS instruments on board these satellites continue to operate beyond the design lifetime of six years, the cumulative effect of the space environment on MODIS and its calibration is of increasing importance. There are several aspects of the space environment that impact both the top of atmosphere (TOA) calibration and, therefore, the final science products of MODIS. The south Atlantic anomaly (SAA), spacecraft drag, extreme radiative and thermal environment, and the presence of orbital debris have the potential to significantly impact both MODIS and the spacecraft, either directly or indirectly, possibly resulting in data loss. Efforts from the Terra and Aqua Flight Operations Teams (FOT), the MODIS Instrument Operations Team (IOT), and the MODIS Characterization Support Team (MCST) prevent or minimize external impact on the TOA calibrated data. This paper discusses specific effects of the space environment on MODIS and how they are minimized.

MODY in Ukraine: genes, clinical phenotypes and treatment.

PubMed

Globa, Evgenia; Zelinska, Nataliya; Elblova, Lenka; Dusatkova, Petra; Cinek, Ondrej; Lebl, Jan; Colclough, Kevin; Ellard, Sian; Pruhova, Stepanka

2017-10-26

Maturity-onset diabetes of the young (MODY) has not been previously studied in Ukraine. We investigated the genetic etiology in a selected cohort of patients with diabetes diagnosed before 18 years of age, and in their family members. Genetic testing of the most prevalent MODY genes (GCK, HNF1A, HNF4A, HNF1B and INS) was undertaken for 36 families (39 affected individuals) by Sanger or targeted next generation sequencing. A genetic diagnosis of MODY was made in 15/39 affected individuals from 12/36 families (33%). HNF1A and HNF4A MODY were the most common subtypes, accounting for 9/15 of MODY cases. Eight patients with HNF1A or HNF4A MODY and inadequate glycemic control were successfully transferred to sulfonylureas. Median HbA1c decreased from 67 mmol/mol (range 58-69) to 47 mmol/mol (range 43-50) (8.3% [7.5-8.5] to 6.4% [6.1-6.7]) 3 months after transfer (p=0.006). Genetic testing identified pathogenic HNF1A and HNF4A variants as the most common cause of MODY in Ukraine. Transfer to sulfonylureas substantially improved the glycemic control of these patients.

To test, or not to test: time for a MODY calculator?

PubMed

Njølstad, P R; Molven, A

2012-05-01

To test, or not to test, that is often the question in diabetes genetics. This is why the paper of Shields et al in the current issue of Diabetologia is so warmly welcomed. MODY is the most common form of monogenic diabetes. Nevertheless, the optimal way of identifying MODY families still poses a challenge both for researchers and clinicians. Hattersley's group in Exeter, UK, have developed an easy-to-use MODY prediction model that can help to identify cases appropriate for genetic testing. By answering eight simple questions on the internet ( www.diabetesgenes.org/content/mody-probability-calculator ), the doctor receives a positive predictive value in return: the probability that the patient has MODY. Thus, the classical binary (yes/no) assessment provided by clinical diagnostic criteria has been substituted by a more rational, quantitative estimate. The model appears to discriminate well between MODY and type 1 and type 2 diabetes when diabetes is diagnosed before the age of 35 years. However, the performance of the MODY probability calculator should now be validated in other settings than where it was developed-and, as always, there is room for some improvements and modifications.

MODi: a powerful and convenient web server for identifying multiple post-translational peptide modifications from tandem mass spectra.

PubMed

Kim, Sangtae; Na, Seungjin; Sim, Ji Woong; Park, Heejin; Jeong, Jaeho; Kim, Hokeun; Seo, Younghwan; Seo, Jawon; Lee, Kong-Joo; Paek, Eunok

2006-07-01

MOD(i) (http://modi.uos.ac.kr/modi/) is a powerful and convenient web service that facilitates the interpretation of tandem mass spectra for identifying post-translational modifications (PTMs) in a peptide. It is powerful in that it can interpret a tandem mass spectrum even when hundreds of modification types are considered and the number of potential PTMs in a peptide is large, in contrast to most of the methods currently available for spectra interpretation that limit the number of PTM sites and types being used for PTM analysis. For example, using MOD(i), one can consider for analysis both the entire PTM list published on the unimod webpage (http://www.unimod.org) and user-defined PTMs simultaneously, and one can also identify multiple PTM sites in a spectrum. MOD(i) is convenient in that it can take various input file formats such as .mzXML, .dta, .pkl and .mgf files, and it is equipped with a graphical tool called MassPective developed to display MOD(i)'s output in a user-friendly manner and helps users understand MOD(i)'s output quickly. In addition, one can perform manual de novo sequencing using MassPective.

History and Future for the Happy Marriage between the MODIS Land team and Fluxnet

NASA Astrophysics Data System (ADS)

Running, S. W.

2015-12-01

When I wrote the proposal to NASA in 1988 for daily global evapotranspiration and gross primary production algorithms for the MODIS sensor, I had no validation plan. Fluxnet probably saved my MODIS career by developing a global network of rigorously calibrated towers measuring water and carbon fluxes over a wide variety of ecosystems that I could not even envision at the time that first proposal was written. However my enthusiasm for Fluxnet was not reciprocated by the Fluxnet community until we began providing 7 x 7 pixel MODIS Land datasets exactly over each of their towers every 8 days, without them having to crawl thru the global datasets and make individual orders. This system, known informally as the MODIS ASCII cutouts, began in 2002 and operates at the Oak Ridge DAAC to this day, cementing a mutually beneficial data interchange between the Fluxnet and remote sensing communities. This talk will briefly discuss the history of MODIS validation with flux towers, and flux spatial scaling with MODIS data. More importantly I will detail the future continuity of global biophysical datasets in the post-MODIS era, and what next generation sensors will provide.

Role of MODIS Vegetation Phenology Products in the ForWarn System for Monitoring of Forest Disturbances in the Conterminous United States

NASA Astrophysics Data System (ADS)

Spruce, J.; Hargrove, W. W.; Norman, S.; Gasser, J.; Smoot, J.; Kuper, P.

2012-12-01

This presentation discusses MODIS vegetation phenology products used in the ForWarn Early Warning System (EWS) tool for near real time regional forest disturbance detection and surveillance at regional to national scales. The ForWarn EWS is being developed by the USDA Forest Service NASA, ORNL, and USGS to aid federal and state forest health management activities. ForWarn employs multiple historical land surface phenology products that are derived from MODIS MOD13 Normalized Difference Vegetation Index (NDVI) data. The latter is temporally processed into phenology products with the Time Series Product Tool (TSPT) and the Phenological Parameter Estimation Tool (PPET) software produced at NASA Stennis Space Center. TSPT is used to effectively noise reduce, fuse, and void interpolate MODIS NDVI data. PPET employs TSPT-processed NDVI time series data as an input, outputting multiple vegetation phenology products at a 232 meter resolution for 2000 to 2011, including NDVI magnitude and day of year products for seven key points along the growing season (peak of growing season and the minima, 20%, and 80% of the peak NDVI for both the left and right side of growing season), cumulative NDVI integral products for the most active part of the growing season and sequentially across the growing season at 8 day intervals, and maximum value NDVI products composited at 24 day intervals in which each product date has 8 days of overlap between the previous and following product dates. MODIS NDVI phenology products are also used to compute nationwide near real time forest change products every 8 days. These include percent change in forest NDVI products that compare the current NDVI from USGS eMODIS products to historical MODIS MOD13 NDVI. For each date, three forest change products are produced using three different maximum value NDVI baselines (from the previous year, three previous years, and all previous years). All change products are output with a rainbow color table in which forests with the most severe NDVI decreases are assigned hot colors (yellow to red) and forests with prominent NDVI increases are assigned cold colors (blue tones). All mentioned products have been integrated as data layers into ForWarn's geospatial data viewer known as the U.S. Forest Change Assessment Viewer (FCAV). The latter is used to view and assess the context of the mentioned forest change products with respect to ancillary data layers, such as land cover, elevation, hydrologic features, climatic data, storm data, aerial disturbance surveys, fire data, and land ownership. The FCAV also includes a temporal NDVI profiler for viewing phenological change in multi-year NDVI associated with known or suspected regionally apparent forest disturbances (e.g., from fire and insects). ForWarn forest change products have been used to detect, track, and assess several biotic and abiotic regional forest disturbance events across the country, including ephemeral and longer lasting damage from storms, drought, and insects. Such change products are most effective for viewing severe disturbance patches of multiple pixels. MODIS vegetation phenology products contribute vital current information on forest conditions to the ForWarn system and this role is expected to grow as these products are refined and derivative products are added.

Improvements in Night-Time Low Cloud Detection and MODIS-Style Cloud Optical Properties from MSG SEVIRI

NASA Technical Reports Server (NTRS)

Wind, Galina (Gala); Platnick, Steven; Riedi, Jerome

2011-01-01

The MODIS cloud optical properties algorithm (MOD06IMYD06 for Terra and Aqua MODIS, respectively) slated for production in Data Collection 6 has been adapted to execute using available channels on MSG SEVIRI. Available MODIS-style retrievals include IR Window-derived cloud top properties, using the new Collection 6 cloud top properties algorithm, cloud optical thickness from VISINIR bands, cloud effective radius from 1.6 and 3.7Jlm and cloud ice/water path. We also provide pixel-level uncertainty estimate for successful retrievals. It was found that at nighttime the SEVIRI cloud mask tends to report unnaturally low cloud fraction for marine stratocumulus clouds. A correction algorithm that improves detection of such clouds has been developed. We will discuss the improvements to nighttime low cloud detection for SEVIRI and show examples and comparisons with MODIS and CALIPSO. We will also show examples of MODIS-style pixel-level (Level-2) cloud retrievals for SEVIRI with comparisons to MODIS.

Undiagnosed MODY: Time for Action.

PubMed

Kleinberger, Jeffrey W; Pollin, Toni I

2015-12-01

Maturity-onset diabetes of the young (MODY) is a monogenic form of diabetes that accounts for at least 1 % of all cases of diabetes mellitus. MODY classically presents as non-insulin-requiring diabetes in lean individuals typically younger than 25 with evidence of autosomal dominant inheritance, but these criteria do not capture all cases and can also overlap with other diabetes types. Genetic diagnosis of MODY is important for selecting the right treatment, yet ~95 % of MODY cases in the USA are misdiagnosed. MODY prevalence and characteristics have been well-studied in some populations, such as the UK and Norway, while other ethnicities, like African and Latino, need much more study. Emerging next-generation sequencing methods are making more widespread study and clinical diagnosis increasingly feasible; at the same time, they are detecting other mutations in the same genes of unknown clinical significance. This review will cover the current epidemiological studies of MODY and barriers and opportunities for moving toward a goal of access to an appropriate diagnosis for all affected individuals.

Monitoring Farmland Loss Caused by Urbanization in Beijing from Modis Time Series Using Hierarchical Hidden Markov Model

NASA Astrophysics Data System (ADS)

Yuan, Y.; Meng, Y.; Chen, Y. X.; Jiang, C.; Yue, A. Z.

2018-04-01

In this study, we proposed a method to map urban encroachment onto farmland using satellite image time series (SITS) based on the hierarchical hidden Markov model (HHMM). In this method, the farmland change process is decomposed into three hierarchical levels, i.e., the land cover level, the vegetation phenology level, and the SITS level. Then a three-level HHMM is constructed to model the multi-level semantic structure of farmland change process. Once the HHMM is established, a change from farmland to built-up could be detected by inferring the underlying state sequence that is most likely to generate the input time series. The performance of the method is evaluated on MODIS time series in Beijing. Results on both simulated and real datasets demonstrate that our method improves the change detection accuracy compared with the HMM-based method.

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.

Resolution Enhancement of MODIS-derived Water Indices for Studying Persistent Flooding

NASA Astrophysics Data System (ADS)

Underwood, L. W.; Kalcic, M. T.; Fletcher, R. M.

2012-12-01

Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250-m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.

Resolution Enhancement of MODIS-Derived Water Indices for Studying Persistent Flooding

NASA Technical Reports Server (NTRS)

Underwood, L. W.; Kalcic, Maria; Fletcher, Rose

2012-01-01

Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250-m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.

Fractional Snowcover Estimates from Earth Observing System (EOS) Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS)

NASA Technical Reports Server (NTRS)

Salomonson, Vincent V.

2002-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System (EOS) Terra and Aqua missions has shown considerable capability for mapping snowcover. The typical approach that has used, along with other criteria, the Normalized Snow Difference Index (NDSI) that takes the difference between 500 meter observations at 1.64 micrometers (MODIS band 6) and 0.555 micrometers (MODIS band 4) over the sum of these observations to determine whether MODIS pixels are snowcovered or not in mapping the extent of snowcover. For many hydrological and climate studies using remote sensing of snowcover, it is desirable to assess if the MODIS snowcover observations could not be enhanced by providing the fraction of snowcover in each MODIS observation (pixel). Pursuant to this objective studies have been conducted to assess whether there is sufficient "signal%o in the NDSI parameter to provide useful estimates of fractional snowcover in each MODIS 500 meter pixel. To accomplish this objective high spatial resolution (30 meter) Landsat snowcover observations were used and co-registered with MODIS 500 meter pixels. The NDSI approach was used to assess whether a Landsat pixel was or was not snowcovered. Then the number of snowcovered Landsat pixels within a MODIS pixel was used to determine the fraction of snowcover within each MODIS pixel. The e results were then used to develop statistical relationships between the NDSI value for each 500 meter MODIS pixel and the fraction of snowcover in the MODIS pixel. Such studies were conducted for three widely different areas covered by Landsat scenes in Alaska, Russia, and the Quebec Province in Canada. The statistical relationships indicate that a 10 percent accuracy can be attained. The variability in the statistical relationship for the three areas was found to be remarkably similar (-0.02 for mean error and less than 0.01 for mean absolute error and standard deviation). Independent tests of the relationships were accomplished by taking the relationship of fractional snow-cover to NDSI from one area (e.g., Alaska) and testing it on the other two areas (e.g. Russia and Quebec). Again the results showed that fractional snow-cover can be estimated to 10 percent. The results have been shown to have advantages over other published fractional snowcover algorithms applied to MODIS data. Most recently the fractional snow-cover algorithm has been applied using 500-meter observations over the state of Colorado for a period spanning 25 days. The results exhibit good behavior in mapping the spatial and temporal variability in snowcover over that 25-day period. Overall these studies indicate that robust estimates of fractional snow-cover can be attained using the NDSI parameter over areas extending in size from watersheds relatively large compared to MODIS pixels to global land cover. Other refinements to this approach as well as different approaches are being examined for mapping fractional snow-cover using MODIS observations.

Monogenic Diabetes

MedlinePlus

... monogenic diabetes? Maturity-onset Diabetes of the Young (MODY) MODY is the most common form of monogenic diabetes. ... teenagers but sometimes is not found until adulthood. MODY can be mild or severe, depending on which ...

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.

The application of digital signal processing techniques to a teleoperator radar system

NASA Technical Reports Server (NTRS)

Pujol, A.

1982-01-01

A digital signal processing system was studied for the determination of the spectral frequency distribution of echo signals from a teleoperator radar system. The system consisted of a sample and hold circuit, an analog to digital converter, a digital filter, and a Fast Fourier Transform. The system is interfaced to a 16 bit microprocessor. The microprocessor is programmed to control the complete digital signal processing. The digital filtering and Fast Fourier Transform functions are implemented by a S2815 digital filter/utility peripheral chip and a S2814A Fast Fourier Transform chip. The S2815 initially simulates a low-pass Butterworth filter with later expansion to complete filter circuit (bandpass and highpass) synthesizing.

Statistical Inter-comparison Analysis of MODIS, MISR, and AERONET Over the Middle East and North Africa

NASA Astrophysics Data System (ADS)

Farahat, A.; El-Askary, H. M.; Kalashnikova, O. V.; Garay, M. J.

2016-12-01

Several space-borne and ground based sensors can provide long-standing monitoring of aerosols characteristics, but inconsistencies among different sensors reduce data reliability and lead to uncertainty in analysing long-term data. In this study, we perform statistical inter-comparison of the Aerosol Optical Depth (AOD) among MISR, MODIS/Terra, MODIS/Aqua and Aerosol Robotic Network (AERONET) over seven sites located in the Middle East and North Africa during the period (1995 -2015). The sites are categorized into two regions based on their geographic location and possible dominate particles composition. Compared to MISR, MODIS and AERONET AOD data retrievals indicate larger uncertainty over all sites with a larger daily variability in MODIS measurements. In general, MISR and MODIS AOD matches during high dust seasons but MODIS tends to under estimate the AOD values on low dust seasons. While Terra measurements give a negative trend over the time series at the dust-dominated sites, Aqua, MISR and AERONET show a positive trend. In general, MODIS/Aqua displays stable measurements over the time line at the dust dominated sites. MODIS/Terra, MODIS/Aqua and MISR display a positive trend over Cairo_EMA site while AERONET shows a negative trend over the time line. Terra was found to overestimate AOD during 2002 - 2004 and underestimates it after 2004. We also observe a deviation between Aqua and Terra regardless of the region and data sampling. Excluding Bahrain and Cairo_EMA for low data retrievals the performance of MODIS tends to be similar over all region with 68 % of the retrieved AOD values fall within the confidence range of the AERONET matched data, within global averaged level (> 66 %). MISR indicated better data performance with 72 % falls within the same confidence range. Complimentary MISR and MODIS data was found to provide a better picture of dust storms evolution over Arabian Peninsula and the Middle East. Acknowledgement The authors would like to acknowledge the support provided by the Deanship of Scientific Research (DSR) at the King Fahd University of Petroleum and Minerals (KFUPM) for funding this work through project No. IN141051.

Intima-media thickness and endothelial dysfunction in GCK and HNF1A-MODY patients.

PubMed

Szopa, Magdalena; Osmenda, Grzegorz; Wilk, Grzegorz; Matejko, Bartłomiej; Skupien, Jan; Zapala, Barbara; Młynarski, Wojciech; Guzik, Tomasz; Malecki, Maciej T

2015-03-01

Mutations in the glucokinase (GCK) gene, along with hepatocyte nuclear factor 1A (HNF1A) gene mutations, are the most frequent cause of maturity-onset diabetes of the young (MODY). GCK-MODY patients are typically characterized by a moderate fasting hyperglycemia; however, little is known about atherosclerosis and intermediate-related phenotypes in these subjects. To examine carotid artery intima-media thickness (IMT) and endothelial function assessed by brachial artery flow-mediated dilatation (FMD) in GCK gene mutations carriers and HNF1A-MODY. A total of 64 subjects with GCK gene mutations, and 52 HNF1A gene mutation carriers as well as 53 nondiabetic controls were examined. IMT and FMD were assessed by ultrasonography. Appropriate statistical tests were performed to assess differences between the groups, and multivariate linear regression was done for the association with IMT and FMD. The clinical characteristics of all groups were similar with the mean age at examination of 35.1, 41.1, and 39.5 years for GCK, HNF1A and the control group respectively. The highest mean IMT value was in the HNF1A-MODY group: 7.0±1.4 mm, whereas it reached 6.3±1.4 mm in GCK mutation carriers and 6.3±1.3 mm in controls (P=0.008). After adjustment for possible clinical and biochemical cofounders, IMT remained higher in HNF1A-MODY patients as compared with GCK-MODY patients (P=0.02) and controls (P=0.0003). FMD was significantly lower in HNF1A (9.9±4.6%) and GCK-MODY (11.1±4.6%) patients in comparison with controls (13.9±4.7%; P=0.0001). After adjustment, FMD remained lower in HNF1A-MODY (P=0.0005) and GCK-MODY patients (P=0.01) as compared with controls. Both examined MODY groups demonstrated evidence of endothelial dysfunction. In addition, HNF1-MODY patients seem to be more prone to an early atherosclerotic phenotype. © 2015 European Society of Endocrinology.

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.

Spatial and Temporal Distribution of Cloud Properties Observed by MODIS: Preliminary Level-3 Results from the Collection 5 Reprocessing

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Hubanks, Paul; Pincus, Robert

2006-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of operational algorithms for the retrieval of cloud physical and optical properties (optical thickness, effective particle radius, water path, thermodynamic phase) have recently been updated and are being used in the new "Collection 5" processing stream being produced by the MODIS Adaptive Processing System (MODAPS) at NASA GSFC. All Terra and Aqua data are undergoing Collection 5 reprocessing with an expected completion date by the end of 2006. The archived products from these algorithms include 1 km pixel-level (Level-2) and global gridded Level-3 products. The cloud products have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In this talk, we will summarize the available Level-3 cloud properties and their associated statistical data sets, and show preliminary Terra and Aqua results from the available Collection 5 reprocessing effort. Anticipated results include the latitudinal distribution of cloud optical and radiative properties for both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

Trend analysis of the aerosol optical depth from fusion of MISR and MODIS retrievals over China

NASA Astrophysics Data System (ADS)

Guo, Jing; Gu, Xingfa; Yu, Tao; Cheng, Tianhai; Chen, Hao

2014-03-01

Atmospheric aerosol plays an important role in the climate change though direct and indirect processes. In order to evaluate the effects of aerosols on climate, it is necessary to have a research on their spatial and temporal distributions. Satellite aerosol remote sensing is a developing technology that may provide good temporal sampling and superior spatial coverage to study aerosols. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) have provided aerosol observations since 2000, with large coverage and high accuracy. However, due to the complex surface, cloud contamination, and aerosol models used in the retrieving process, the uncertainties still exist in current satellite aerosol products. There are several observed differences in comparing the MISR and MODIS AOD data with the AERONET AOD. Combing multiple sensors could reduce uncertainties and improve observational accuracy. The validation results reveal that a better agreement between fusion AOD and AERONET AOD. The results confirm that the fusion AOD values are more accurate than single sensor. We have researched the trend analysis of the aerosol properties over China based on nine-year (2002-2010) fusion data. Compared with trend analysis in Jingjintang and Yangtze River Delta, the accuracy has increased by 5% and 3%, respectively. It is obvious that the increasing trend of the AOD occurred in Yangtze River Delta, where human activities may be the main source of the increasing AOD.

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.

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.

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.

A Discussion of the Discrete Fourier Transform Execution on a Typical Desktop PC

NASA Technical Reports Server (NTRS)

White, Michael J.

2006-01-01

This paper will discuss and compare the execution times of three examples of the Discrete Fourier Transform (DFT). The first two examples will demonstrate the direct implementation of the algorithm. In the first example, the Fourier coefficients are generated at the execution of the DFT. In the second example, the coefficients are generated prior to execution and the DFT coefficients are indexed at execution. The last example will demonstrate the Cooley- Tukey algorithm, better known as the Fast Fourier Transform. All examples were written in C executed on a PC using a Pentium 4 running at 1.7 Ghz. As a function of N, the total complex data size, the direct implementation DFT executes, as expected at order of N2 and the FFT executes at order of N log2 N. At N=16K, there is an increase in processing time beyond what is expected. This is not caused by implementation but is a consequence of the effect that machine architecture and memory hierarchy has on implementation. This paper will include a brief overview of digital signal processing, along with a discussion of contemporary work with discrete Fourier processing.

Creating a consistent dark-target aerosol optical depth record from MODIS and VIIRS

NASA Astrophysics Data System (ADS)

Levy, R. C.; Mattoo, S.; Munchak, L. A.; Patadia, F.; Holz, R.

2014-12-01

To answer fundamental questions about our changing climate, we must quantify how aerosols are changing over time. This is a global question that requires regional characterization, because in some places aerosols are increasing and in others they are decreasing. Although NASA's Moderate resolution Imaging Spectrometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, the creation of an aerosol climate data record (CDR) requires consistent multi-decadal data. With the Visible and Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP, there is potential to continue the MODIS aerosol time series. Yet, since the operational VIIRS aerosol product is produced by a different algorithm, it is not suitable to continue MODIS to create an aerosol CDR. Therefore, we have applied the MODIS Dark-target (DT) algorithm to VIIRS observations, taking into account the slight differences in wavelengths, resolutions and geometries between the two sensors. More specifically, we applied the MODIS DT algorithm to a dataset known as the Intermediate File Format (IFF), created by the University of Wisconsin. The IFF is produced for both MODIS and VIIRS, with the idea that a single (MODIS-like or ML) algorithm can be run either dataset, which can in turn be compared to the MODIS Collection 6 (M6) retrieval that is run on standard MODIS data. After minimizing or characterizing remaining differences between ML on MODIS-IFF (or ML-M) and M6, we have performed apples-to-apples comparison between ML-M and ML on VIIRS IFF (ML-V). Examples of these comparisons include time series of monthly global mean, monthly and seasonal global maps at 1° resolution, and collocations as compared to AERONET. We concentrate on the overlapping period January 2012 through June 2014, and discuss some of the remaining discrepancies between the ML-V and ML-M datasets.

Exploring the Genomic Roadmap and Molecular Phylogenetics Associated with MODY Cascades Using Computational Biology.

PubMed

Chakraborty, Chiranjib; Bandyopadhyay, Sanghamitra; Doss, C George Priya; Agoramoorthy, Govindasamy

2015-04-01

Maturity onset diabetes of the young (MODY) is a metabolic and genetic disorder. It is different from type 1 and type 2 diabetes with low occurrence level (1-2%) among all diabetes. This disorder is a consequence of β-cell dysfunction. Till date, 11 subtypes of MODY have been identified, and all of them can cause gene mutations. However, very little is known about the gene mapping, molecular phylogenetics, and co-expression among MODY genes and networking between cascades. This study has used latest servers and software such as VarioWatch, ClustalW, MUSCLE, G Blocks, Phylogeny.fr, iTOL, WebLogo, STRING, and KEGG PATHWAY to perform comprehensive analyses of gene mapping, multiple sequences alignment, molecular phylogenetics, protein-protein network design, co-expression analysis of MODY genes, and pathway development. The MODY genes are located in chromosomes-2, 7, 8, 9, 11, 12, 13, 17, and 20. Highly aligned block shows Pro, Gly, Leu, Arg, and Pro residues are highly aligned in the positions of 296, 386, 437, 455, 456 and 598, respectively. Alignment scores inform us that HNF1A and HNF1B proteins have shown high sequence similarity among MODY proteins. Protein-protein network design shows that HNF1A, HNF1B, HNF4A, NEUROD1, PDX1, PAX4, INS, and GCK are strongly connected, and the co-expression analyses between MODY genes also show distinct association between HNF1A and HNF4A genes. This study has used latest tools of bioinformatics to develop a rapid method to assess the evolutionary relationship, the network development, and the associations among eleven MODY genes and cascades. The prediction of sequence conservation, molecular phylogenetics, protein-protein network and the association between the MODY cascades enhances opportunities to get more insights into the less-known MODY disease.

Circulating ghrelin level is higher in HNF1A-MODY and GCK-MODY than in polygenic forms of diabetes mellitus.

PubMed

Nowak, Natalia; Hohendorff, Jerzy; Solecka, Iwona; Szopa, Magdalena; Skupien, Jan; Kiec-Wilk, Beata; Mlynarski, Wojciech; Malecki, Maciej T

2015-12-01

Ghrelin is a hormone that regulates appetite. It is likely to be involved in the pathophysiology of varying forms of diabetes. In animal studies, the ghrelin expression was regulated by the hepatocyte nuclear factor 1 alpha (HNF1A). Mutations of the HNF1A gene cause maturity onset diabetes of the young (MODY). We aimed to assess the circulating ghrelin levels in HNF1A-MODY and in other types of diabetes and to evaluate its association with HNF1A mutation status. Our cohort included 46 diabetic HNF1A gene mutation carriers, 55 type 2 diabetes (T2DM) subjects, 42 type 1 diabetes (T1DM) patients, and 31 glucokinase (GCK) gene mutation carriers with diabetes as well as 51 healthy controls. Plasma ghrelin concentration was measured using the immunoenzymatic assay with polyclonal antibody against the C-terminal fragment of its acylated and desacylated forms. Ghrelin concentrations were 0.75 ± 0.32, 0.70 ± 0.21, 0.50 ± 0.20, and 0.40 ± 0.16 ng/ml in patients with HNF1A-MODY, GCK-MODY, T1DM, and T2DM, respectively. The ghrelin levels were higher in HNF1A-MODY and GCK-MODY than in T1DM and T2DM (p < 0.001 for all comparisons) but lower than in non-diabetic controls (1.02 ± 0.29 ng/ml, p < 0.001 for both comparisons). In the multivariate linear model, the differences between both MODY groups and common diabetes types remained significant. Analysis by a HNF1A mutation type indicated that ghrelin concentration is similar in patients with different types of sequence differences. Plasma ghrelin level is higher in HNF1A-MODY and GCK-MODY than in the common polygenic forms of diabetes.

Successful maintenance on sulphonylurea therapy and low diabetes complication rates in a HNF1A-MODY cohort.

PubMed

Bacon, S; Kyithar, M P; Rizvi, S R; Donnelly, E; McCarthy, A; Burke, M; Colclough, K; Ellard, S; Byrne, M M

2016-07-01

HNF1A gene mutations are the most common cause of maturity-onset diabetes of the young (MODY) in the UK. Persons with HNF1A-MODY display sensitivity to sulphonylurea therapy; however, the long-term efficacy is not established. There is limited literature as to the prevalence of micro- and macrovascular complications in this unique cohort. The aim of this study was to determine the natural progression and clinical management of HNF1A-MODY diabetes in a dedicated MODY clinic. Sixty patients with HNF1A-MODY and a cohort of 60 BMI-, age-, ethnicity- and diabetes duration-matched patients with Type 1 diabetes mellitus participated in the study. All patients were phenotyped in detail. Clinical follow-up of the HNF1A-MODY cohort occurred on a bi-annual basis. Following a genetic diagnosis of MODY, the majority of the cohort treated with sulphonylurea therapy remained insulin independent at 84-month follow-up (80%). The HbA1c in the HNF1A-MODY group treated with sulphonylurea therapy alone improved significantly over the study period [from 49 (44-63) mmol/mol, 6.6 (6.2-7.9)% to 41 (31-50) mmol/mol, 5.9 (5-6.7)%; P = 0.003]. The rate of retinopathy was significantly lower than that noted in the Type 1 diabetes mellitus group (13.6 vs. 50%; P = 0.0001).There was also a lower rate of microalbuminuria and cardiovascular disease in the HNF1A-MODY group compared with the Type 1 diabetes mellitus group. This study demonstrates that the majority of patients with HNF1A-MODY can be maintained successfully on sulphonylurea therapy with good glycaemic control. We note a significantly lower rate of micro- and macrovascular complications than reported previously. The use of appropriate therapy at early stages of the disorder may decrease the incidence of complications. © 2015 Diabetes UK.

Comparing Stream Discharge, Dissolved Organic Carbon, and Selected MODIS Indices in Freshwater Basins

NASA Astrophysics Data System (ADS)

Shaver, W. T.; Wollheim, W. M.

2009-12-01

In a preliminary study of the Ipswich Basin in Massachusetts, a good correlation was found to exist between the MODIS (Moderate Resolution Imaging Spectroradiometer) Enhanced Vegetation Index and stream dissolved organic carbon (DOC). Further study was warranted to determine the utility of MODIS indices in predicting temporal stream DOC. Stream discharge rates and DOC data were obtained from the USGS National Water Quality Assessment Program (NAWQA) database. Twelve NAWQA monitoring sites were selected for evaluation based on the criteria of having drainage basin sizes less than 600 km2 with relatively continuous, long-term DOC and discharge data. MODIS indices were selected based on their connections with terrestrial DOC and were obtained for each site's catchment area. These included the Normalized Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the Daily Photosynthesis (PSN) and the Leaf Area Index (LAI). Regression analysis was used to evaluate the relationships between DOC, discharge and MODIS products. Data analysis revealed several important trends. Sites with strong positive correlation coefficients (r values ranging from 0.462 to 0.831) between DOC and discharge displayed weak correlations with all of the MODIS indices (r values ranging from 0 to 0.322). For sites where the DOC/discharge correlation was weak or negative, MODIS indices were moderately correlated, with r values ranging from 0.35 to 0.647, all of which were significant at less than 1 percent. Some sites that had weak positive correlations with MODIS indices displayed a lag time, that is, the MODIS index rose and fell shortly before the DOC concentration rose and fell. Shifting the MODIS data forward in time by roughly one month significantly increased the DOC/MODIS r values by about 10%. NDVI and EVI displayed the strongest correlations with temporal DOC variability (r values ranging from 0.471 to 0.647), and therefore these indices are the most promising for being incorporated into a model for remotely sensing terrestrial DOC.

Double Fourier analysis for Emotion Identification in Voiced Speech

NASA Astrophysics Data System (ADS)

Sierra-Sosa, D.; Bastidas, M.; Ortiz P., D.; Quintero, O. L.

2016-04-01

We propose a novel analysis alternative, based on two Fourier Transforms for emotion recognition from speech. Fourier analysis allows for display and synthesizes different signals, in terms of power spectral density distributions. A spectrogram of the voice signal is obtained performing a short time Fourier Transform with Gaussian windows, this spectrogram portraits frequency related features, such as vocal tract resonances and quasi-periodic excitations during voiced sounds. Emotions induce such characteristics in speech, which become apparent in spectrogram time-frequency distributions. Later, the signal time-frequency representation from spectrogram is considered an image, and processed through a 2-dimensional Fourier Transform in order to perform the spatial Fourier analysis from it. Finally features related with emotions in voiced speech are extracted and presented.

Developing Land Use Land Cover Maps for the Lower Mekong Basin to Aid SWAT Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Spruce, J.; Bolten, J. D.; Srinivasan, R.

2017-12-01

This presentation discusses research to develop Land Use Land Cover (LULC) maps for the Lower Mekong Basin (LMB). Funded by a NASA ROSES Disasters grant, the main objective was to produce updated LULC maps to aid the Mekong River Commission's (MRC's) Soil and Water Assessment Tool (SWAT) hydrologic model. In producing needed LULC maps, temporally processed MODIS monthly NDVI data for 2010 were used as the primary data source for classifying regionally prominent forest and agricultural types. The MODIS NDVI data was derived from processing MOD09 and MYD09 8-day reflectance data with the Time Series Product Tool, a custom software package. Circa 2010 Landsat multispectral data from the dry season were processed into top of atmosphere reflectance mosaics and then classified to derive certain locally common LULC types, such as urban areas and industrial forest plantations. Unsupervised ISODATA clustering was used to derive most LULC classifications. GIS techniques were used to merge MODIS and Landsat classifications into final LULC maps for Sub-Basins (SBs) 1-8 of the LMB. The final LULC maps were produced at 250-meter resolution and delivered to the MRC for use in SWAT modeling for the LMB. A map accuracy assessment was performed for the SB 7 LULC map with 14 classes. This assessment was performed by comparing random locations for sampled LULC types to geospatial reference data such as Landsat RGBs, MODIS NDVI phenologic profiles, high resolution satellite data from Google Map/Earth, and other reference data from the MRC (e.g., crop calendars). LULC accuracy assessment results for SB 7 indicated an overall agreement to reference data of 81% at full scheme specificity. However, by grouping 3 deciduous forest classes into 1 class, the overall agreement improved to 87%. The project enabled updated LULC maps, plus more specific rice types were classified compared to the previous LULC maps. The LULC maps from this project should improve the use of SWAT for modeling hydrology in the LMB, plus improve water and disaster management in a region vulnerable to flooding, droughts, and anthropogenic change (e.g., from dam building and other LULC change).

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.

Modeling Gross Primary Production of Agro-Forestry Ecosystems by Assimilation of Satellite-Derived Information in a Process-Based Model

PubMed Central

Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

2009-01-01

In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale. PMID:22399948

Modeling gross primary production of agro-forestry ecosystems by assimilation of satellite-derived information in a process-based model.

PubMed

Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

2009-01-01

In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

New Statistical Model for Variability of Aerosol Optical Thickness: Theory and Application to MODIS Data over Ocean

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail Dmitrievic; Geogdzhayev, Igor V.; Tsigaridis, Konstantinos; Marshak, Alexander; Levy, Robert; Cairns, Brian

2016-01-01

A novel model for the variability in aerosol optical thickness (AOT) is presented. This model is based on the consideration of AOT fields as realizations of a stochastic process, that is the exponent of an underlying Gaussian process with a specific autocorrelation function. In this approach AOT fields have lognormal PDFs and structure functions having the correct asymptotic behavior at large scales. The latter is an advantage compared with fractal (scale-invariant) approaches. The simple analytical form of the structure function in the proposed model facilitates its use for the parameterization of AOT statistics derived from remote sensing data. The new approach is illustrated using a month-long global MODIS AOT dataset (over ocean) with 10 km resolution. It was used to compute AOT statistics for sample cells forming a grid with 5deg spacing. The observed shapes of the structure functions indicated that in a large number of cases the AOT variability is split into two regimes that exhibit different patterns of behavior: small-scale stationary processes and trends reflecting variations at larger scales. The small-scale patterns are suggested to be generated by local aerosols within the marine boundary layer, while the large-scale trends are indicative of elevated aerosols transported from remote continental sources. This assumption is evaluated by comparison of the geographical distributions of these patterns derived from MODIS data with those obtained from the GISS GCM. This study shows considerable potential to enhance comparisons between remote sensing datasets and climate models beyond regional mean AOTs.

MODIS On-Board Blackbody Function and Performance

NASA Technical Reports Server (NTRS)

Xiaoxiong, Xiong; Wenny, Brian N.; Wu, Aisheng; Barnes, William

2009-01-01

Two MODIS instruments are currently in orbit, making continuous global observations in visible to long-wave infrared wavelengths. Compared to heritage sensors, MODIS was built with an advanced set of on-board calibrators, providing sensor radiometric, spectral, and spatial calibration and characterization during on-orbit operation. For the thermal emissive bands (TEB) with wavelengths from 3.7 m to 14.4 m, a v-grooved blackbody (BB) is used as the primary calibration source. The BB temperature is accurately measured each scan (1.47s) using a set of 12 temperature sensors traceable to NIST temperature standards. The onboard BB is nominally operated at a fixed temperature, 290K for Terra MODIS and 285K for Aqua MODIS, to compute the TEB linear calibration coefficients. Periodically, its temperature is varied from 270K (instrument ambient) to 315K in order to evaluate and update the nonlinear calibration coefficients. This paper describes MODIS on-board BB functions with emphasis on on-orbit operation and performance. It examines the BB temperature uncertainties under different operational conditions and their impact on TEB calibration and data product quality. The temperature uniformity of the BB is also evaluated using TEB detector responses at different operating temperatures. On-orbit results demonstrate excellent short-term and long-term stability for both the Terra and Aqua MODIS on-board BB. The on-orbit BB temperature uncertainty is estimated to be 10mK for Terra MODIS at 290K and 5mK for Aqua MODIS at 285K, thus meeting the TEB design specifications. In addition, there has been no measurable BB temperature drift over the entire mission of both Terra and Aqua MODIS.

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.

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.

[Humoral response markers in GCK MODY].

PubMed

Skała-Zamorowska, Eliza; Deja, Grażyna; Borowiec, Maciej; Fendler, Wojciech; Małachowska, Beata; Kamińska, Halla; Wyka, Krystyna; Młynarski, Wojciech; Jarosz-Chobot, Przemysława

2016-01-01

The prevalence of antibodies to pancreatic islets in monogenic diabetes remains unknown and the incidence estimation is difficult as the occurrence of autoantibodies in patient is one of the well-known exclusion criteria for further genetic diagnostics. They has been found not only among patients with type 1 diabetes, but also in other types of diabetes: Type 2 diabetes, Latent Autoimmune Diabetes in Adults (LADA) (16) and monogenic diabetes (MD). Immunological characteristic of GCK MODY patients. The study group included families of 27 adolescent patients with GCK MODY (39 parents and 19 siblings) monitored in the Department of Pediatrics, Endocrinology and Diabetes and in the Diabetes Clinic of John Paul II Upper Silesian Child Health Centre in Katowice in the years 2007-2012. All patients and family members with GCK MODY underwent a blood sample drawing for immunological (classic humoral response markers: ICA, GAD, IA-2, IAA) and biochemical diagnostics. Pediatric, diabetes and family medical history was collected from the subjects and parents. Immunological diagnostics was performed in all patients except 1 (96.3%). Immunological diagnostics included 17 (89.5%) parents and 7 (87.5%) siblings with diagnosed GCK MODY. 8 (30.8%) adolescent patients with GCK MODY, 3 subjects (17.64%) among parents (with GCK MODY), as well as 2 subjects (28.57%) among siblings (with GCK MODY) showed a positive antibodies screen. The results of our study in children with GCK MODY and their family members suggest that the occurrence of classic antibodies directed against pancreatic islets antigens is fairly common in patients with GCK MODY. Despite various observations and many legitimate discussions, it is difficult to clarify the pathogenesis of the occurrence of autoantibodies in monogenic diabetes. © Polish Society for Pediatric Endocrinology and Diabetology.

The development and validation of a clinical prediction model to determine the probability of MODY in patients with young-onset diabetes.

PubMed

Shields, B M; McDonald, T J; Ellard, S; Campbell, M J; Hyde, C; Hattersley, A T

2012-05-01

Diagnosing MODY is difficult. To date, selection for molecular genetic testing for MODY has used discrete cut-offs of limited clinical characteristics with varying sensitivity and specificity. We aimed to use multiple, weighted, clinical criteria to determine an individual's probability of having MODY, as a crucial tool for rational genetic testing. We developed prediction models using logistic regression on data from 1,191 patients with MODY (n = 594), type 1 diabetes (n = 278) and type 2 diabetes (n = 319). Model performance was assessed by receiver operating characteristic (ROC) curves, cross-validation and validation in a further 350 patients. The models defined an overall probability of MODY using a weighted combination of the most discriminative characteristics. For MODY, compared with type 1 diabetes, these were: lower HbA(1c), parent with diabetes, female sex and older age at diagnosis. MODY was discriminated from type 2 diabetes by: lower BMI, younger age at diagnosis, female sex, lower HbA(1c), parent with diabetes, and not being treated with oral hypoglycaemic agents or insulin. Both models showed excellent discrimination (c-statistic = 0.95 and 0.98, respectively), low rates of cross-validated misclassification (9.2% and 5.3%), and good performance on the external test dataset (c-statistic = 0.95 and 0.94). Using the optimal cut-offs, the probability models improved the sensitivity (91% vs 72%) and specificity (94% vs 91%) for identifying MODY compared with standard criteria of diagnosis <25 years and an affected parent. The models are now available online at www.diabetesgenes.org . We have developed clinical prediction models that calculate an individual's probability of having MODY. This allows an improved and more rational approach to determine who should have molecular genetic testing.

Substantial proportion of MODY among multiplex families participating in a Type 1 diabetes prediction programme.

PubMed

Petruzelkova, L; Dusatkova, P; Cinek, O; Sumnik, Z; Pruhova, S; Hradsky, O; Vcelakova, J; Lebl, J; Kolouskova, S

2016-12-01

Patients with maturity-onset diabetes of the young (MODY) might be over-represented in families with histories of Type 1 diabetes. Our aim was to re-evaluate families participating in the Czech T1D Prediction Programme (PREDIA.CZ) with at least two members affected with diabetes to assess the proportion of MODY among these families and determine its most significant clinical predictors. Of the 557 families followed up by the PREDIA.CZ, 53 (9.5%) had two or more family members with diabetes. One proband with diabetes from these families was chosen for direct sequencing of the GCK, HNF1A, HNF4A and INS genes. Non-parametric tests and a linear logistic regression model were used to evaluate differences between MODY and non-MODY families. MODY was genetically diagnosed in 24 of the 53 families with multiple occurrences of diabetes (45%). Mutations were detected most frequently in GCK (58%), followed by HNF1A (38%) and INS (4%). MODY families were more likely to have a parent with diabetes and had a higher proportion of females with diabetes than non-MODY families. Higher age (P < 0.001), a lower level of HbA 1c (P < 0.001) at clinical onset and at least two generations affected by diabetes were the variables most predictive for probands of MODY families already presenting with diabetes. A prediction programme for Type 1 diabetes would provide a useful new source of patients with MODY most likely to benefit from an accurate diagnosis. This identification has implications for patient treatment and disease prognosis. © 2015 Diabetes UK.

Detector Noise Characterization and Performance of MODIS Thermal Emissive Bands

NASA Technical Reports Server (NTRS)

Xiong, X.; Wu, A.; Chen, N.; Chiang, K.; Xiong, S.; Wenny, B.; Barnes, W. L.

2007-01-01

MODIS has 16 thermal emissive bands, a total of 160 individual detectors (10 for each spectral bands), located on the two cold focal plane assemblies (CFPA). MODIS TEB detectors were fully characterized pre-launch in a thermal vacuum (TV) environment using a NIST traceable blackbody calibration source (BCS) with temperatures ranging from 170 to 340K. On-orbit the TEB detectors are calibrated using an on-board blackbody (BB) on a scan-by-scan basis. For nominal on-orbit operation, the on-board BB temperature is typically controlled at 285K for Aqua MODIS and 290K for Terra MODIS. For the MODIS TEB calibration, each detector's noise equivalent temperature difference (NEdT) is often used to assess its performance and this parameter is a major contributor to the calibration uncertainty. Because of its impact on sensor calibration and data product quality, each MODIS TEB detector's NEdT is monitored on a daily basis at a fixed BB temperature and completely characterized on a regular basis at a number of BB temperatures. In this paper, we describe MODIS on-orbit TEB NEdT characterization activities, approaches, and results. We compare both pre-launch and on-orbit performance with sensor design specification and examine detector noise characterization impact on the calibration uncertainty. To date, 135 TEB detectors (out of a total of 160 detectors) in Terra MODIS (launched in December 1999) and 158 in Aqua MODIS (launched in May 2002) continue to perform with their NEdT below (or better than) their design specifications. A complete summary of all TEB noisy detectors, identified both pre-launch and on-orbit, is provided.

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.

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.

Evaluation and Validation of Updated MODIS C6 and VIIRS LAI/FPAR

NASA Astrophysics Data System (ADS)

Yan, K.; Park, T.; Chen, C.; Yang, B.; Yan, G.; Knyazikhin, Y.; Myneni, R. B.; CHOI, S.

2015-12-01

Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (0.4-0.7 μm) absorbed by vegetation (FPAR) play a key role in characterizing vegetation canopy functioning and energy absorption capacity. With radiative transfer realization, MODIS onboard NASA EOS Terra and Aqua satellites has provided globally continuous LAI/FPAR since 2000 and continuously updated the products with better quality. And NPP VIIRS shows the measurement capability to extend high-quality LAI/FPAR time series data records as a successor of MODIS. The primary objectives of this study are 1) to evaluate and validate newly updated MODIS Collection 6 (C6) LAI/FPAR product which has finer resolution (500m) and improved biome type input, and 2) to examine and adjust VIIRS LAI/FPAR algorithm for continuity with MODIS'. For MODIS C6 investigation, we basically measure the spatial coverage (i.e., main radiative transfer algorithm execution), continuity and consistency with Collection 5 (C5), and accuracy with field measured LAI/FPAR. And we also validate C6 LAI/FPAR via comparing other possible global LAI/FPAR products (e.g., GLASS and CYCLOPES) and capturing co-varying seasonal signatures with climatic variables (e.g., temperature and precipitation). For VIIRS evaluation and adjustment, we first quantify possible difference between C5 and MODIS heritage based VIIRS LAI/FPAR. Then based on the radiative transfer theory of canopy spectral invariants, we find VIIRS- and biome-specific configurable parameters (single scattering albedo and uncertainty). These two practices for MODIS C6 and VIIRS LAI/FPAR products clearly suggest that (a) MODIS C6 has better coverage and accuracy than C5, (b) C6 shows consistent spatiotemporal pattern with C5, (c) VIIRS has the potential for producing MODIS-like global LAI/FPAR Earth System Data Records.

MODIS information, data and control system (MIDACS) operations concepts

NASA Technical Reports Server (NTRS)

Han, D.; Salomonson, V.; Ormsby, J.; Ardanuy, P.; Mckay, A.; Hoyt, D.; Jaffin, S.; Vallette, B.; Sharts, B.; Folta, D.

1988-01-01

The MODIS Information, Data, and Control System (MIDACS) Operations Concepts Document provides a basis for the mutual understanding between the users and the designers of the MIDACS, including the requirements, operating environment, external interfaces, and development plan. In defining the concepts and scope of the system, how the MIDACS will operate as an element of the Earth Observing System (EOS) within the EosDIS environment is described. This version follows an earlier release of a preliminary draft version. The individual operations concepts for planning and scheduling, control and monitoring, data acquisition and processing, calibration and validation, data archive and distribution, and user access do not yet fully represent the requirements of the data system needed to achieve the scientific objectives of the MODIS instruments and science teams. The teams are not yet formed; however, it is possible to develop the operations concepts based on the present concept of EosDIS, the level 1 and level 2 Functional Requirements Documents, and through interviews and meetings with key members of the scientific community. The operations concepts were exercised through the application of representative scenarios.

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.

Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

NASA Astrophysics Data System (ADS)

Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

2007-12-01

Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

Remote sensing change detection methods to track deforestation and growth in threatened rainforests in Madre de Dios, Peru

USGS Publications Warehouse

Shermeyer, Jacob S.; Haack, Barry N.

2015-01-01

Two forestry-change detection methods are described, compared, and contrasted for estimating deforestation and growth in threatened forests in southern Peru from 2000 to 2010. The methods used in this study rely on freely available data, including atmospherically corrected Landsat 5 Thematic Mapper and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF). The two methods include a conventional supervised signature extraction method and a unique self-calibrating method called MODIS VCF guided forest/nonforest (FNF) masking. The process chain for each of these methods includes a threshold classification of MODIS VCF, training data or signature extraction, signature evaluation, k-nearest neighbor classification, analyst-guided reclassification, and postclassification image differencing to generate forest change maps. Comparisons of all methods were based on an accuracy assessment using 500 validation pixels. Results of this accuracy assessment indicate that FNF masking had a 5% higher overall accuracy and was superior to conventional supervised classification when estimating forest change. Both methods succeeded in classifying persistently forested and nonforested areas, and both had limitations when classifying forest change.

Near Real Time Processing Chain for Suomi NPP Satellite Data

NASA Astrophysics Data System (ADS)

Monsorno, Roberto; Cuozzo, Giovanni; Costa, Armin; Mateescu, Gabriel; Ventura, Bartolomeo; Zebisch, Marc

2014-05-01

Since 2009, the EURAC satellite receiving station, located at Corno del Renon, in a free obstacle site at 2260 m a.s.l., has been acquiring data from Aqua and Terra NASA satellites equipped with Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. The experience gained with this local ground segmenthas given the opportunity of adapting and modifying the processing chain for MODIS data to the Suomi NPP, the natural successor to Terra and Aqua satellites. The processing chain, initially implemented by mean of a proprietary system supplied by Seaspace and Advanced Computer System, was further developed by EURAC's Institute for Applied Remote Sensing engineers. Several algorithms have been developed using MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) data to produce Snow Cover, Particulate Matter estimation and Meteo maps. These products are implemented on a common processor structure based on the use of configuration files and a generic processor. Data and products have then automatically delivered to the customers such as the Autonomous Province of Bolzano-Civil Protection office. For the processing phase we defined two goals: i) the adaptation and implementation of the products already available for MODIS (and possibly new ones) to VIIRS, that is one of the sensors onboard Suomi NPP; ii) the use of an open source processing chain in order to process NPP data in Near Real Time, exploiting the knowledge we acquired on parallel computing. In order to achieve the second goal, the S-NPP data received and ingested are sent as input to RT-STPS (Real-time Software Telemetry Processing System) software developed by the NASA Direct Readout Laboratory 1 (DRL) that gives as output RDR files (Raw Data Record) for VIIRS, ATMS (Advanced Technology Micorwave Sounder) and CrIS (Cross-track Infrared Sounder)sensors. RDR are then transferred to a server equipped with CSPP2 (Community Satellite Processing Package) software developed by the University of Wisconsin. CSPP subdivides the input file in granules, making possible the use of parallel computing, and produces SDR (Science Data Record) and some EDR (Environmental Data Record) products. The integration with the EDRs not yet available with CSPP is realized with the use of SPAs (Science Processing Algorithm) stand-alone version by DRL. The important result of this system consists in the possibility of processing data acquired by the EURAC antenna with open source software and delivering the SDRs, EDRs and higher level products developed internally by EURAC in near real time using a Data Exchange Server. By means of the parallelized CSPP, SDR data are currently available after about 7 minutes since the production of RDR, while we are currently implementing a strategy to get the best possible processing time for the EDRs products that are in principle not parallelizable. 1. http://directreadout.sci.gsfc.nasa.gov/ 2. http://cimss.ssec.wisc.edu/cspp/

Observations on the effects of image processing functions on fingermark data in the Fourier domain

NASA Astrophysics Data System (ADS)

Bramble, Simon K.; Fabrizi, Paola M.

1995-09-01

One of the image processing functions used for the enhancement of laten fingermark images is the Fourier transform. This paper describes some effects of spatial resolution, zero-filling and windowing on fingermark data in the Fourier domain. It is shown that with an understanding of the fingermark structure it is possible to determine the approximate prosition of the frequency data in the Fourier domain corresponding to the fingermark image detail. The effect of attenuation of frequency data on a zero-filled image is shown to be different to the same attenuation on a non-zero-filled image. The effects of windowing spatial data on the frequency data are also highlighted and compared with the same data after the application of a Hanning window.

Heterozygous RFX6 protein truncating variants are associated with MODY with reduced penetrance.

PubMed

Patel, Kashyap A; Kettunen, Jarno; Laakso, Markku; Stančáková, Alena; Laver, Thomas W; Colclough, Kevin; Johnson, Matthew B; Abramowicz, Marc; Groop, Leif; Miettinen, Päivi J; Shepherd, Maggie H; Flanagan, Sarah E; Ellard, Sian; Inagaki, Nobuya; Hattersley, Andrew T; Tuomi, Tiinamaija; Cnop, Miriam; Weedon, Michael N

2017-10-12

Finding new causes of monogenic diabetes helps understand glycaemic regulation in humans. To find novel genetic causes of maturity-onset diabetes of the young (MODY), we sequenced MODY cases with unknown aetiology and compared variant frequencies to large public databases. From 36 European patients, we identify two probands with novel RFX6 heterozygous nonsense variants. RFX6 protein truncating variants are enriched in the MODY discovery cohort compared to the European control population within ExAC (odds ratio = 131, P = 1 × 10 -4 ). We find similar results in non-Finnish European (n = 348, odds ratio = 43, P = 5 × 10 -5 ) and Finnish (n = 80, odds ratio = 22, P = 1 × 10 -6 ) replication cohorts. RFX6 heterozygotes have reduced penetrance of diabetes compared to common HNF1A and HNF4A-MODY mutations (27, 70 and 55% at 25 years of age, respectively). The hyperglycaemia results from beta-cell dysfunction and is associated with lower fasting and stimulated gastric inhibitory polypeptide (GIP) levels. Our study demonstrates that heterozygous RFX6 protein truncating variants are associated with MODY with reduced penetrance.Maturity-onset diabetes of the young (MODY) is the most common subtype of familial diabetes. Here, Patel et al. use targeted DNA sequencing of MODY patients and large-scale publically available data to show that RFX6 heterozygous protein truncating variants cause reduced penetrance MODY.

The impact of the use of different satellite data as training data against GOSAT-2 CAI-2 L2 cloud discrimination

NASA Astrophysics Data System (ADS)

Oishi, Y.; Ishida, H.; Nakajima, T. Y.

2016-12-01

Greenhouse gases Observing SATellite-2 (GOSAT-2) will be launched in fiscal 2017 to determine atmospheric concentrations of greenhouse gases, such as CO2, CH4, and CO. GOSAT-2 will be equipped with two sensors: the Thermal and Near-infrared Sensor for Carbon Observation (TANSO)-Fourier Transform Spectrometer-2 (FTS-2) and TANSO-Cloud and Aerosol Imager-2 (CAI-2). CAI-2 is a push-broom imaging sensor that has forward- and backward-looking bands for observing the optical properties of aerosols and clouds, and for monitoring the status of urban air pollution and transboundary air pollution over oceans. An important role of CAI-2 is to perform cloud discrimination in each direction. The Cloud and Aerosol Unbiased Decision Intellectual Algorithm (CLAUDIA1), which applies sequential threshold tests to features, has been used in GOSAT CAI L2 cloud flag processing. If CLAUDIA1 used with CAI-2, it is necessary to optimize the thresholds in accordance with CAI-2. Meanwhile, CLAUDIA3 using support vector machines (SVM), which is a supervised pattern recognition method, was developed for GOSAT-2 CAI-2 L2 cloud discrimination processing. Thus, CLAUDIA3 can automatically find the optimized boundary between clear and cloudy. Improvement of the CLAUDIA3 used with CAI (CLAUDIA3-CAI) has carried out and is still continuing. In this study we compared results of CLAUDIA3-CAI using Terra MODIS data and GOSAT CAI data as training data to clarify the impact of the use of different satellite data as training data against GOSAT-2 CAI-2 L2 cloud discrimination. We will present our latest results.

Detection of the long-range transport of wildfire pollution to the Arctic using a network of ground-based FTIR spectrometers, satellite observations and model result

NASA Astrophysics Data System (ADS)

Lutsch, E.; Conway, S. A.; Strong, K.; Jones, D. B. A.; Drummond, J. R.; Ortega, I.; Hannigan, J. W.; Makarova, M.; Notholt, J.; Blumenstock, T.; Sussmann, R.; Mahieu, E.; Kasai, Y.; Clerbaux, C.

2017-12-01

We present a multi-year time series of the total columns of carbon monoxide (CO), hydrogen cyanide (HCN) and ethane (C2H6) obtained by Fourier Transform Infrared (FTIR) spectrometer measurements at nine sites. Six are high-latitude sites: Eureka, Nunavut; Ny Alesund, Norway; Thule, Greenland; Kiruna, Sweden; Poker Flat, Alaska and St. Petersburg, Russia and three are mid-latitude sites; Zugspitze, Germany; Jungfraujoch, Switzerland and Toronto, Ontario. For each site, the inter-annual trends and seasonal variabilities of the CO total column time series are accounted for, allowing ambient concentrations to be determined. Enhancements above ambient levels are then used to identify possible wildfire pollution events. Since the abundance of each trace gas species emitted in a wildfire event is specific to the type of vegetation burned and the burning phase, correlations of CO to the other long-lived wildfire tracers HCN and C2H6 allow for further confirmation of the detection of wildfire pollution. Back-trajectories from HYSPLIT and FLEXPART as well as fire detections from the Moderate Resolution Spectroradiometer (MODIS) allow the source regions of the detected enhancements to be determined while satellite observations of CO from the Measurement of Pollution in the Troposphere (MOPITT) and Infrared Atmospheric Sounding Interferometer (IASI) instruments can be used to track the transport of the smoke plume. Differences in travel times between sites allows ageing of biomass burning plumes to be determined, providing a means to infer the physical and chemical processes affecting the loss of each species during transport. Comparisons of ground-based FTIR measurements to GEOS-Chem chemical transport model results are used to investigate these processes, evaluate wildfire emission inventories and infer the influence of wildfire emissions on the Arctic.

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.

Inter-Comparison of S-NPP VIIRS and Aqua MODIS Thermal Emissive Bands Using Hyperspectral Infrared Sounder Measurements as a Transfer Reference

NASA Technical Reports Server (NTRS)

Li, Yonghong; Wu, Aisheng; Xiong, Xiaoxiong

2016-01-01

This paper compares the calibration consistency of the spectrally-matched thermal emissive bands (TEB) between the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) and the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), using observations from their simultaneous nadir overpasses (SNO). Nearly-simultaneous hyperspectral measurements from the Aqua Atmospheric Infrared Sounder(AIRS) and the S-NPP Cross-track Infrared Sounder (CrIS) are used to account for existing spectral response differences between MODIS and VIIRS TEB. The comparison uses VIIRS Sensor Data Records (SDR) in MODIS five-minute granule format provided by the NASA Land Product and Evaluation and Test Element (PEATE) and Aqua MODIS Collection 6 Level 1 B (L1B) products. Each AIRS footprint of 13.5 km (or CrIS field of view of 14 km) is co-located with multiple MODIS (or VIIRS) pixels. The corresponding AIRS- and CrIS-simulated MODIS and VIIRS radiances are derived by convolutions based on sensor-dependent relative spectral response (RSR) functions. The VIIRS and MODIS TEB calibration consistency is evaluated and the two sensors agreed within 0.2 K in brightness temperature.Additional factors affecting the comparison such as geolocation and atmospheric water vapor content are also discussed in this paper.

Maturity-Onset Diabetes of the Young (MODY): Making the Right Diagnosis to Optimize Treatment.

PubMed

Amed, Shazhan; Oram, Richard

2016-10-01

Maturity onset diabetes of the young (MODY) is a rare but increasingly recognized cause of diabetes in young people. It is a monogenic disorder that typically presents at <25 years of age, is non-insulin dependent and is familial, with an autosomal dominant pattern of inheritance. The most common forms of MODY are caused by mutations in glucokinase and hepatic nuclear factor 1 alpha or 4 alpha genes and account for almost 80% of cases of MODY. MODY is commonly misdiagnosed as type 1 or type 2 diabetes and, as a result, patients are often inappropriately managed with insulin when they can be more effectively managed with oral sulfonylureas. Therefore, making the right diagnosis is critical for effective treatment as well as for genetic counselling and, more important, for patients' quality of life. In this review, we aim to raise awareness about MODY among diabetes clinicians by describing key clinical and laboratory features of the most common forms of MODY, outlining features that might help to differentiate MODY from type 1 and type 2 diabetes and providing information about clinical tests and tools that might assist in identifying patients who are most likely to benefit from molecular genetic testing. Copyright © 2016 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

Maturity onset diabetes of youth (MODY) in Turkish children: sequence analysis of 11 causative genes by next generation sequencing.

PubMed

Ağladıoğlu, Sebahat Yılmaz; Aycan, Zehra; Çetinkaya, Semra; Baş, Veysel Nijat; Önder, Aşan; Peltek Kendirci, Havva Nur; Doğan, Haldun; Ceylaner, Serdar

2016-04-01

Maturity-onset diabetes of the youth (MODY), is a genetically and clinically heterogeneous group of diseasesand is often misdiagnosed as type 1 or type 2 diabetes. The aim of this study is to investigate both novel and proven mutations of 11 MODY genes in Turkish children by using targeted next generation sequencing. A panel of 11 MODY genes were screened in 43 children with MODY diagnosed by clinical criterias. Studies of index cases was done with MISEQ-ILLUMINA, and family screenings and confirmation studies of mutations was done by Sanger sequencing. We identified 28 (65%) point mutations among 43 patients. Eighteen patients have GCK mutations, four have HNF1A, one has HNF4A, one has HNF1B, two have NEUROD1, one has PDX1 gene variations and one patient has both HNF1A and HNF4A heterozygote mutations. This is the first study including molecular studies of 11 MODY genes in Turkish children. GCK is the most frequent type of MODY in our study population. Very high frequency of novel mutations (42%) in our study population, supports that in heterogenous disorders like MODY sequence analysis provides rapid, cost effective and accurate genetic diagnosis.

First Moderate Resolution Imaging Spectroradiometer (MODIS) Snow and Ice Workshop

NASA Technical Reports Server (NTRS)

Hall, Dorothy K. (Editor)

1995-01-01

This document is a compilation of summaries of talks presented at a 2-day workshop on Moderate Resolution maging Spectroradiometer (MODIS) snow and ice products. The objectives of the workshop were to: inform the snow and ce community of potential MODIS products, seek advice from the participants regarding the utility of the products, and letermine the needs for future post-launch MODIS snow and ice products. Four working groups were formed to discuss at-launch snow products, at-launch ice products, post-launch snow and ice products and utility of MODIS snow and ice products, respectively. Each working group presented recommendations at the conclusion of the workshop.

Faster processing of multiple spatially-heterodyned direct to digital holograms

DOEpatents

Hanson, Gregory R.; Bingham, Philip R.

2006-10-03

Systems and methods are described for faster processing of multiple spatially-heterodyned direct to digital holograms. A method includes of obtaining multiple spatially-heterodyned holograms, includes: digitally recording a first spatially-heterodyned hologram including spatial heterodyne fringes for Fourier analysis; digitally recording a second spatially-heterodyned hologram including spatial heterodyne fringes for Fourier analysis; Fourier analyzing the recorded first spatially-heterodyned hologram by shifting a first original origin of the recorded first spatially-heterodyned hologram including spatial heterodyne fringes in Fourier space to sit on top of a spatial-heterodyne carrier frequency defined as a first angle between a first reference beam and a first, object beam; applying a first digital filter to cut off signals around the first original origin and performing an inverse Fourier transform on the result; Fourier analyzing the recorded second spatially-heterodyned hologram by shifting a second original origin of the recorded second spatially-heterodyned hologram including spatial heterodyne fringes in Fourier space to sit on top of a spatial-heterodyne carrier frequency defined as a second angle between a second reference beam and a second object beam; and applying a second digital filter to cut off signals around the second original origin and performing an inverse Fourier transform on the result, wherein digitally recording the first spatially-heterodyned hologram is completed before digitally recording the second spatially-heterodyned hologram and a single digital image includes both the first spatially-heterodyned hologram and the second spatially-heterodyned hologram.

Faster processing of multiple spatially-heterodyned direct to digital holograms

DOEpatents

Hanson, Gregory R [Clinton, TN; Bingham, Philip R [Knoxville, TN

2008-09-09

Systems and methods are described for faster processing of multiple spatially-heterodyned direct to digital holograms. A method includes of obtaining multiple spatially-heterodyned holograms, includes: digitally recording a first spatially-heterodyned hologram including spatial heterodyne fringes for Fourier analysis; digitally recording a second spatially-heterodyned hologram including spatial heterodyne fringes for Fourier analysis; Fourier analyzing the recorded first spatially-heterodyned hologram by shifting a first original origin of the recorded first spatially-heterodyned hologram including spatial heterodyne fringes in Fourier space to sit on top of a spatial-heterodyne carrier frequency defined as a first angle between a first reference beam and a first object beam; applying a first digital filter to cut off signals around the first original origin and performing an inverse Fourier transform on the result; Fourier analyzing the recorded second spatially-heterodyned hologram by shifting a second original origin of the recorded second spatially-heterodyned hologram including spatial heterodyne fringes in Fourier space to sit on top of a spatial-heterodyne carrier frequency defined as a second angle between a second reference beam and a second object beam; and applying a second digital filter to cut off signals around the second original origin and performing an inverse Fourier transform on the result, wherein digitally recording the first spatially-heterodyned hologram is completed before digitally recording the second spatially-heterodyned hologram and a single digital image includes both the first spatially-heterodyned hologram and the second spatially-heterodyned hologram.

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.

Achieving sub-pixel geolocation accuracy in support of MODIS land science

USGS Publications Warehouse

Wolfe, R.E.; Nishihama, M.; Fleig, A.J.; Kuyper, J.A.; Roy, David P.; Storey, James C.; Patt, F.S.

2002-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was launched in December 1999 on the polar orbiting Terra spacecraft and since February 2000 has been acquiring daily global data in 36 spectral bands—29 with 1 km, five with 500 m, and two with 250 m nadir pixel dimensions. The Terra satellite has on-board exterior orientation (position and attitude) measurement systems designed to enable geolocation of MODIS data to approximately 150 m (1σ) at nadir. A global network of ground control points is being used to determine biases and trends in the sensor orientation. Biases have been removed by updating models of the spacecraft and instrument orientation in the MODIS geolocation software several times since launch and have improved the MODIS geolocation to approximately 50 m (1σ) at nadir. This paper overviews the geolocation approach, summarizes the first year of geolocation analysis, and overviews future work. The approach allows an operational characterization of the MODIS geolocation errors and enables individual MODIS observations to be geolocated to the sub-pixel accuracies required for terrestrial global change applications.

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.

Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR

PubMed Central

Mobli, Mehdi; Hoch, Jeffrey C.

2017-01-01

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR. PMID:25456315

Spring floods prediction with the use of optical satellite data in Québec

NASA Astrophysics Data System (ADS)

Roy, A.; Royer, A.; Turcotte, R.

2009-04-01

The Centre d'expertise hydrique du Québec (CEHQ) operates a distributed hydrological model, which integrates a snow model, for the management of dams in the south of Québec. It appears that the estimation of the water quantity of snowmelt in spring remains a variable with a large uncertainty and induces generally to an important error in stream flow simulation. Therefore, the National snow and ice center (NSIDC) produces, from MODIS (Moderate Resolution Imaging Spectroradiometer) data, continuous and homogeneous spatial snow cover (snow/swow-free) data on the whole territory, but with a cloud contamination. This research aims to improve the prediction of spring floods and the estimation of the rate of discharge by integrating snow cover data in the CEHQ's snow model. The study is done on two watersheds: du Nord river watershed (45,8°N) and Aux Écorces river watershed (47,9°N). The snow model used in the study (SPH-AV) is an implementation developed by the CEHQ of the snowmelt model of HYDROLTEL in is hydrological forecast system to simulate the melted water. The melted water estimated is then used as input in the empirical hydrological model MOHYSE to simulate stream flow. MODIS data are considered valid only when the cloud cover on each pixel of the watersheds is less then 30%. A pixel by pixel correction is applied to the snow pack when there is a difference between satellite snow cover and modeled snow cover. In the case of model shows to much snow, a factor is applied on temperatures by iterative process (starting from the last valid MODIS data) to melt the snow. In the opposite case, the snow quantity added to the last valid MODIS data is found by iterative process so that the pixel's snow water equivalent is equal to the nonzero neighbor minimum value. The study shows, through the simulations done on the two watersheds, the interest of the use of snow/snow-free product for the operational update of snow water equivalent with the objective to improve spring snowmelt stream flow simulations. The binary aspect (snow/snowfree) of the data is however a limit. Alternatives are discussed (passive microwave data). Keywords : satellite snow cover data, MODIS, satellite data integration, snow model, hydrological model, stream flow simulation, flood.

Synthesis, Analysis, and Processing of Fractal Signals

DTIC Science & Technology

1991-10-01

coordinator in hockey, squash, volleyball, and softball, but also for reminding me periodically that 1/f noise can exist outside a computer. More...similar signals as Fourier-based representations are for stationary and periodic signals. Furthermore, because wave- let transformations can be...and periodic signals. Furthermore, just as the discovery of fast Fourier transform (FFT) algorithms dramatically increased the viability the Fourier

Model development for MODIS thermal band electronic cross-talk

NASA Astrophysics Data System (ADS)

Chang, Tiejun; Wu, Aisheng; Geng, Xu; Li, Yonghong; Brinkmann, Jake; Keller, Graziela; Xiong, Xiaoxiong (Jack)

2016-10-01

MODerate-resolution Imaging Spectroradiometer (MODIS) has 36 bands. Among them, 16 thermal emissive bands covering a wavelength range from 3.8 to 14.4 μm. After 16 years on-orbit operation, the electronic crosstalk of a few Terra MODIS thermal emissive bands develop substantial issues which cause biases in the EV brightness temperature measurements and surface feature contamination. The crosstalk effects on band 27 with center wavelength at 6.7 μm and band 29 at 8.5 μm increased significantly in recent years, affecting downstream products such as water vapor and cloud mask. The crosstalk issue can be observed from nearly monthly scheduled lunar measurements, from which the crosstalk coefficients can be derived. Most of MODIS thermal bands are saturated at moon surface temperatures and the development of an alternative approach is very helpful for verification. In this work, a physical model was developed to assess the crosstalk impact on calibration as well as in Earth view brightness temperature retrieval. This model was applied to Terra MODIS band 29 empirically for correction of Earth brightness temperature measurements. In the model development, the detector nonlinear response is considered. The impacts of the electronic crosstalk are assessed in two steps. The first step consists of determining the impact on calibration using the on-board blackbody (BB). Due to the detector nonlinear response and large background signal, both linear and nonlinear coefficients are affected by the crosstalk from sending bands. The crosstalk impact on calibration coefficients was calculated. The second step is to calculate the effects on the Earth view brightness temperature retrieval. The effects include those from affected calibration coefficients and the contamination of Earth view measurements. This model links the measurement bias with crosstalk coefficients, detector nonlinearity, and the ratio of Earth measurements between the sending and receiving bands. The correction of the electronic crosstalk can be implemented empirically from the processed bias at different brightness temperature. The implementation can be done through two approaches. As routine calibration assessment for thermal infrared bands, the trending over select Earth scenes is processed for all the detectors in a band and the band averaged bias is derived for certain time. In this case, the correction of an affected band can be made using the regression of the model with band averaged bias and then corrections of detector differences are applied. The second approach requires the trending for individual detectors and the bias for each detector is used for regression with the model. A test using the first approach was made for Terra MODIS band 29 with the biases derived from long-term trending of sea surface temperature and Dome-C surface temperature.

Validation of MODIS Dust Aerosol Retrieval and Development Ambient Dust Phase Function using PRIDE Data

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Lau, William (Technical Monitor)

2002-01-01

The PRIDE data set of MODIS aerosol retrievals co-located with sunphotometer measurements provides the basis of MODIS validation in a dust environment. The sunphotometer measurements include AERONET automatic instruments, land-based Microtops instruments, ship-board Microtops instruments and the AATS-6 aboard the Navajo aircraft. Analysis of these data indicate that the MODIS retrieval is within pre-launch estimates of uncertainty within the spectral range of 600-900 nm. However, the MODIS algorithm consistently retrieves smaller particles than reality thus leading to incorrect spectral response outside of the 600-900 nm range and improper size information. Further analysis of MODIS retrievals in other dust environments shows the inconsistencies are due to nonspherical effects in the phase function. These data are used to develop an ambient phase function for dust aerosol to be used for remote sensing purposes.

Calibration Adjustments to the MODIS Aqua Ocean Color Bands

NASA Technical Reports Server (NTRS)

Meister, Gerhard

2012-01-01

After the end of the SeaWiFS mission in 2010 and the MERIS mission in 2012, the ocean color products of the MODIS on Aqua are the only remaining source to continue the ocean color climate data record until the VIIRS ocean color products become operational (expected for summer 2013). The MODIS on Aqua is well beyond its expected lifetime, and the calibration accuracy of the short wavelengths (412nm and 443nm) has deteriorated in recent years_ Initially, SeaWiFS data were used to improve the MODIS Aqua calibration, but this solution was not applicable after the end of the SeaWiFS mission_ In 2012, a new calibration methodology was applied by the MODIS calibration and support team using desert sites to improve the degradation trending_ This presentation presents further improvements to this new approach. The 2012 reprocessing of the MODIS Aqua ocean color products is based on the new methodology.

Trends in MODIS Geolocation Error Analysis

NASA Technical Reports Server (NTRS)

Wolfe, R. E.; Nishihama, Masahiro

2009-01-01

Data from the two MODIS instruments have been accurately geolocated (Earth located) to enable retrieval of global geophysical parameters. The authors describe the approach used to geolocate with sub-pixel accuracy over nine years of data from M0DIS on NASA's E0S Terra spacecraft and seven years of data from MODIS on the Aqua spacecraft. The approach uses a geometric model of the MODIS instruments, accurate navigation (orbit and attitude) data and an accurate Earth terrain model to compute the location of each MODIS pixel. The error analysis approach automatically matches MODIS imagery with a global set of over 1,000 ground control points from the finer-resolution Landsat satellite to measure static biases and trends in the MO0lS geometric model parameters. Both within orbit and yearly thermally induced cyclic variations in the pointing have been found as well as a general long-term trend.

A Critical Examination of Spatial Biases Between MODIS and MISR Aerosol Products - Application for Potential AERONET Deployment

NASA Technical Reports Server (NTRS)

Shi, Y.; Zhang, J.; Reid, J. S.; Hyer, E. J.; Eck, T. F.; Holben, B. N.; Kahn, R. A.

2011-01-01

AErosol RObotic NETwork (AERONET) data are the primary benchmark for evaluating satellite-retrieved aerosol properties. However, despite its extensive coverage, the representativeness of the AERONET data is rarely discussed. Indeed, many studies have shown that satellite retrieval biases have a significant degree of spatial correlation that may be problematic for higher-level processes or inverse-emissions-modeling studies. To consider these issues and evaluate relative performance in regions of few surface observations, cross-comparisons between the Aerosol Optical Depth (AOD) products of operational MODIS Collection 5.1 Dark Target (DT) and operational MODIS Collection 5.1 Deep Blue (DB) with MISR version 22 were conducted. Through such comparisons, we can observe coherent spatial features of the AOD bias while side-stepping the full analysis required for determining when or where either retrieval is more correct. We identify regions where MODIS to MISR AOD ratios were found to be above 1.4 and below 0.7. Regions where lower boundary condition uncertainty is likely to be a dominant factor include portions of Western North America, the Andes mountains, Saharan Africa, the Arabian Peninsula, and Central Asia. Similarly, microphysical biases may be an issue in South America, and specific parts of Southern Africa, India Asia, East Asia, and Indonesia. These results help identify high-priority locations for possible future deployments of both in situ and ground based remote sensing measurements. The Supplement includes a km1 file.

Improving correlations between MODIS aerosol optical thickness and ground-based PM 2.5 observations through 3D spatial analyses

NASA Astrophysics Data System (ADS)

Hutchison, Keith D.; Faruqui, Shazia J.; Smith, Solar

The Center for Space Research (CSR) continues to focus on developing methods to improve correlations between satellite-based aerosol optical thickness (AOT) values and ground-based, air pollution observations made at continuous ambient monitoring sites (CAMS) operated by the Texas commission on environmental quality (TCEQ). Strong correlations and improved understanding of the relationships between satellite and ground observations are needed to formulate reliable real-time predictions of air quality using data accessed from the moderate resolution imaging spectroradiometer (MODIS) at the CSR direct-broadcast ground station. In this paper, improvements in these correlations are demonstrated first as a result of the evolution in the MODIS retrieval algorithms. Further improvement is then shown using procedures that compensate for differences in horizontal spatial scales between the nominal 10-km MODIS AOT products and CAMS point measurements. Finally, airborne light detection and ranging (lidar) observations, collected during the Texas Air Quality Study of 2000, are used to examine aerosol profile concentrations, which may vary greatly between aerosol classes as a result of the sources, chemical composition, and meteorological conditions that govern transport processes. Further improvement in correlations is demonstrated with this limited dataset using insights into aerosol profile information inferred from the vertical motion vectors in a trajectory-based forecast model. Analyses are ongoing to verify these procedures on a variety of aerosol classes using data collected by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (Calipso) lidar.

Alerts of forest disturbance from MODIS imagery

NASA Astrophysics Data System (ADS)

Hammer, Dan; Kraft, Robin; Wheeler, David

2014-12-01

This paper reports the methodology and computational strategy for a forest cover disturbance alerting system. Analytical techniques from time series econometrics are applied to imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to detect temporal instability in vegetation indices. The characteristics from each MODIS pixel's spectral history are extracted and compared against historical data on forest cover loss to develop a geographically localized classification rule that can be applied across the humid tropical biome. The final output is a probability of forest disturbance for each 500 m pixel that is updated every 16 days. The primary objective is to provide high-confidence alerts of forest disturbance, while minimizing false positives. We find that the alerts serve this purpose exceedingly well in Pará, Brazil, with high probability alerts garnering a user accuracy of 98 percent over the training period and 93 percent after the training period (2000-2005) when compared against the PRODES deforestation data set, which is used to assess spatial accuracy. Implemented in Clojure and Java on the Hadoop distributed data processing platform, the algorithm is a fast, automated, and open source system for detecting forest disturbance. It is intended to be used in conjunction with higher-resolution imagery and data products that cannot be updated as quickly as MODIS-based data products. By highlighting hotspots of change, the algorithm and associated output can focus high-resolution data acquisition and aid in efforts to enforce local forest conservation efforts.

The MODIS Aerosol Algorithm: Critical Evaluation and Plans for Collection 6

NASA Technical Reports Server (NTRS)

Remer, Lorraine

2010-01-01

For ten years the MODIS aerosol algorithm has been applied to measured MODIS radiances to produce a continuous set of aerosol products, over land and ocean. The MODIS aerosol products are widely used by the scientific and applied science communities for variety of purposes that span operational air quality forecasting in estimates o[ clear-sky direct radiative effects over ocean and aerosol-cloud interactions. The products undergo continual evaluation, including self-consistency checks and comparisons with highly accurate ground-based instruments. The result of these evaluation exercises is a quantitative understanding of the strengths and weaknesses of the retrieval, where and when the products are accurate and the situations where and when accuracy degrades. We intend 10 present results of the most recent critical evaluations including the first comparison of the over ocean products against the shipboard aerosol optical depth measurements of the Marine Aerosol Network (MAN), the demonstration of the lack of sensitivity to size parameter in the over land products and identification of residual problems and regional issues. While the current data set is undergoing evaluation, we are preparing for the next data processing, labeled Collection 6. Collection 6 will include transparent Quality Flags, a 3 km aerosol product and the 500m resolution cloud mask used within the aerosol n:bicvu|. These new products and adjustments to algorithm assumptions should provide users with more options and greater control, as they adapt the product for their own purposes.

Satellite and Surface Perspectives of Snow Extent in the Southern Appalachian Mountains

NASA Technical Reports Server (NTRS)

Sugg, Johnathan W.; Perry, Baker L.; Hall, Dorothy K.

2012-01-01

Assessing snow cover patterns in mountain regions remains a challenge for a variety of reasons. Topography (e.g., elevation, exposure, aspect, and slope) strongly influences snowfall accumulation and subsequent ablation processes, leading to pronounced spatial variability of snow cover. In-situ observations are typically limited to open areas at lower elevations (<1000 m). In this paper, we use several products from the Moderate Resolution Imaging Spectroradiometer (MODIS) to assess snow cover extent in the Southern Appalachian Mountains (SAM). MODIS daily snow cover maps and true color imagery are analyzed after selected snow events (e.g., Gulf/Atlantic Lows, Alberta Clippers, and Northwest Upslope Flow) from 2006 to 2012 to assess the spatial patterns of snowfall across the SAM. For each event, we calculate snow cover area across the SAM using MODIS data and compare with the Interactive Multi-sensor Snow and ice mapping system (IMS) and available in-situ observations. Results indicate that Gulf/Atlantic Lows are typically responsible for greater snow extent across the entire SAM region due to intensified cyclogenesis associated with these events. Northwest Upslope Flow events result in snow cover extent that is limited to higher elevations (>1000 m) across the SAM, but also more pronounced along NW aspects. Despite some limitations related to the presence of ephemeral snow or cloud cover immediately after each event, we conclude that MODIS products are useful for assessing the spatial variability of snow cover in heavily forested mountain regions such as the SAM.

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.

Improving AIRS Radiance Spectra in High Contrast Scenes Using MODIS

NASA Technical Reports Server (NTRS)

Pagano, Thomas S.; Aumann, Hartmut H.; Manning, Evan M.; Elliott, Denis A.; Broberg, Steven E.

2015-01-01

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002. AIRS acquires hyperspectral infrared radiances in 2378 channels ranging in wavelength from 3.7-15.4 microns with spectral resolution of better than 1200, and spatial resolution of 13.5 km with global daily coverage. The AIRS is designed to measure temperature and water vapor profiles for improvement in weather forecast accuracy and improved understanding of climate processes. As with most instruments, the AIRS Point Spread Functions (PSFs) are not the same for all detectors. When viewing a non-uniform scene, this causes a significant radiometric error in some channels that is scene dependent and cannot be removed without knowledge of the underlying scene. The magnitude of the error depends on the combination of non-uniformity of the AIRS spatial response for a given channel and the non-uniformity of the scene, but is typically only noticeable in about 1% of the scenes and about 10% of the channels. The current solution is to avoid those channels when performing geophysical retrievals. In this effort we use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument to provide information on the scene uniformity that is used to correct the AIRS data. For the vast majority of channels and footprints the technique works extremely well when compared to a Principal Component (PC) reconstruction of the AIRS channels. In some cases where the scene has high inhomogeneity in an irregular pattern, and in some channels, the method can actually degrade the spectrum. Most of the degraded channels appear to be slightly affected by random noise introduced in the process, but those with larger degradation may be affected by alignment errors in the AIRS relative to MODIS or uncertainties in the PSF. Despite these errors, the methodology shows the ability to correct AIRS radiances in non-uniform scenes under some of the worst case conditions and improves the ability to match AIRS and MODIS radiances in non-uniform scenes.

The morphing of geographical features by Fourier transformation.

PubMed

Li, Jingzhong; Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features' continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable.

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.

Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters - Part 2: Aerosols

NASA Astrophysics Data System (ADS)

Wind, Galina; da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-07-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a "simulated radiance" product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land-ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers.This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled.In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model subgrid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms.Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (M{O/Y}D04). The M{O/Y}D04 product is of course normally produced from M{O/Y}D021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a M{O/Y}D021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source.We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters . Part 2; Aerosols

NASA Technical Reports Server (NTRS)

Wind, Galina; Da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-01-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

Metasurface Enabled Wide-Angle Fourier Lens.

PubMed

Liu, Wenwei; Li, Zhancheng; Cheng, Hua; Tang, Chengchun; Li, Junjie; Zhang, Shuang; Chen, Shuqi; Tian, Jianguo

2018-06-01

Fourier optics, the principle of using Fourier transformation to understand the functionalities of optical elements, lies at the heart of modern optics, and it has been widely applied to optical information processing, imaging, holography, etc. While a simple thin lens is capable of resolving Fourier components of an arbitrary optical wavefront, its operation is limited to near normal light incidence, i.e., the paraxial approximation, which puts a severe constraint on the resolvable Fourier domain. As a result, high-order Fourier components are lost, resulting in extinction of high-resolution information of an image. Other high numerical aperture Fourier lenses usually suffer from the bulky size and costly designs. Here, a dielectric metasurface consisting of high-aspect-ratio silicon waveguide array is demonstrated experimentally, which is capable of performing 1D Fourier transform for a large incident angle range and a broad operating bandwidth. Thus, the device significantly expands the operational Fourier space, benefitting from the large numerical aperture and negligible angular dispersion at large incident angles. The Fourier metasurface will not only facilitate efficient manipulation of spatial spectrum of free-space optical wavefront, but also be readily integrated into micro-optical platforms due to its compact size. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Comparison between MODIS-derived day and night cloud cover and surface observations over the North China Plain

NASA Astrophysics Data System (ADS)

Zhang, Xiao; Tan, Saichun; Shi, Guangyu

2018-02-01

Satellite and human visual observation are two of the most important observation approaches for cloud cover. In this study, the total cloud cover (TCC) observed by MODIS onboard the Terra and Aqua satellites was compared with Synop meteorological station observations over the North China Plain and its surrounding regions for 11 years during daytime and 7 years during nighttime. The Synop data were recorded eight times a day at 3-h intervals. Linear interpolation was used to interpolate the Synop data to the MODIS overpass time in order to reduce the temporal deviation between the satellite and Synop observations. Results showed that MODIS-derived TCC had good consistency with the Synop observations; the correlation coefficients ranged from 0.56 in winter to 0.73 in summer for Terra MODIS, and from 0.55 in winter to 0.71 in summer for Aqua MODIS. However, they also had certain differences. On average, the MODIS-derived TCC was 15.16% higher than the Synop data, and this value was higher at nighttime (15.58%-16.64%) than daytime (12.74%-14.14%). The deviation between the MODIS and Synop TCC had large seasonal variation, being largest in winter (29.53%-31.07%) and smallest in summer (4.46%-6.07%). Analysis indicated that cloud with low cloud-top height and small cloud optical thickness was more likely to cause observation bias. Besides, an increase in the satellite view zenith angle, aerosol optical depth, or snow cover could lead to positively biased MODIS results, and this affect differed among different cloud types.

MODIS Retrieval of Dust Aerosol

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Kaufman, Yoram J.; Tanre, Didier

2003-01-01

The MODerate resolution Imaging Spectroradiometer (MODIS) currently aboard both the Terra and Aqua satellites produces a suite of products designed to characterize global aerosol distribution, optical thickness and particle size. Never before has a space-borne instrument been able to provide such detailed information, operationally, on a nearly global basis every day. The three years of Terra-MODIS data have been validated by comparing with co-located AERONET observations of aerosol optical thickness and derivations of aerosol size parameters. Some 8000 comparison points located at 133 AERONET sites around the globe show that the MODIS aerosol optical thickness retrievals are accurate to within the pre-launch expectations. However, the validation in regions dominated by desert dust is less accurate than in regions dominated by fine mode aerosol or background marine sea salt. The discrepancy is most apparent in retrievals of aerosol size parameters over ocean. In dust situations, the MODIS algorithm tends to under predict particle size because the reflectances at top of atmosphere measured by MODIS exhibit the stronger spectral signature expected by smaller particles. This pattern is consistent with the angular and spectral signature of non-spherical particles. All possible aerosol models in the MODIS Look-Up Tables were constructed from Mie theory, assuming a spherical shape. Using a combination of MODIS and AERONET observations, in regimes dominated by desert dust, we construct phase functions, empirically, with no assumption of particle shape. These new phase functions are introduced into the MODIS algorithm, in lieu of the original options for large dust-like particles. The results will be analyzed and examined.

The Observed Behavior of the Bias in MODIS-retrieved Cloud Droplet Effective Radius through MISR-MODIS Data Fusion

NASA Astrophysics Data System (ADS)

Fu, D.; Di Girolamo, L.; Liang, L.; Zhao, G.

2017-12-01

Listed as one of the Essential Climate Variables by the Global Climate Observing System, the effective radius (Re) of the cloud drop size distribution plays an important role in the energy and water cycles of the Earth system. Re is retrieved from several passive sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), based on a visible and near-infrared bi-spectral technique that had its foundation more than a quarter century ago. This technique makes a wide range of assumptions, including 1-D radiative transfer, assumed single-mode drop size distribution, and cloud horizontal and vertical homogeneity. It is well known that deviations from these assumptions lead to bias in the retrieved Re. Recently, an effort to characterize the bias in MODIS-retrieved Re through MISR-MODIS data fusion revealed biases in the zonal-mean values of MODIS-retrieved Re that varied from 2 to 11 µm, depending on latitude (Liang et al., 2015). Here, in a push towards bias-correction of MODIS-retrieved Re, we further examine the bias with MISR-MODIS data fusion as it relates to other observed cloud properties, such as cloud-top height and the spatial variability of the radiance field, sun-view geometry, and the driving meteorology had from reanalysis data. Our results show interesting relationships in Re bias behavior with these observed properties, revealing that while Re bias do show a certain degree of dependence on some properties, no single property dominates the behavior in MODIS-retrieved Re bias.

Evaluation of VIIRS and MODIS Thermal Emissive Band Calibration Stability Using Ground Target

NASA Technical Reports Server (NTRS)

Madhavan, Sriharsha; Brinkmann, Jake; Wenny, Brian N.; Wu, Aisheng; Xiong, Xiaoxiong

2017-01-01

The S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, a polar orbiting Earth remote sensing instrument built using a strong MODIS background, employs a similarly designed on-board calibrating source - a V-grooved blackbody for the thermal emissive bands (TEB). The central wavelengths of most VIIRS TEBs are very close to those of MODIS with the exception of the 10.7 micron channel. To ensure the long term continuity of climate data records derived using VIIRS and MODIS TEB, it is necessary to assess any systematic differences between the two instruments, including scenes with temperatures significantly lower than blackbody operating temperatures at approximately 290 K. Previous work performed by the MODIS Characterization Support Team (MCST) at NASAGSFC used the frequent observations of the Dome Concordia site located in Antarctica to evaluate the calibration stability and consistency of Terra and Aqua MODIS over the mission lifetime. The near-surface temperature measurements from an automatic weather station (AWS) provide a direct reference useful for tracking the stability and determining the relative bias between the two MODIS instruments. In this study, the same technique is applied to the VIIRS TEB and the results are compared with those from the matched MODIS TEB. The results of this study show a small negative bias when comparing the matching VIIRS and Aqua MODIS TEB, implying a higher scene temperature retrieval for S-VIIRS at the cold end. Statistically no significant drift is observed for VIIRS TEB performance over the first 3.5 years of the mission.

Mutations in HNF1A Result in Marked Alterations of Plasma Glycan Profile

PubMed Central

Thanabalasingham, Gaya; Huffman, Jennifer E.; Kattla, Jayesh J.; Novokmet, Mislav; Rudan, Igor; Gloyn, Anna L.; Hayward, Caroline; Adamczyk, Barbara; Reynolds, Rebecca M.; Muzinic, Ana; Hassanali, Neelam; Pucic, Maja; Bennett, Amanda J.; Essafi, Abdelkader; Polasek, Ozren; Mughal, Saima A.; Redzic, Irma; Primorac, Dragan; Zgaga, Lina; Kolcic, Ivana; Hansen, Torben; Gasperikova, Daniela; Tjora, Erling; Strachan, Mark W.J.; Nielsen, Trine; Stanik, Juraj; Klimes, Iwar; Pedersen, Oluf B.; Njølstad, Pål R.; Wild, Sarah H.; Gyllensten, Ulf; Gornik, Olga; Wilson, James F.; Hastie, Nicholas D.; Campbell, Harry; McCarthy, Mark I.; Rudd, Pauline M.; Owen, Katharine R.; Lauc, Gordan; Wright, Alan F.

2013-01-01

A recent genome-wide association study identified hepatocyte nuclear factor 1-α (HNF1A) as a key regulator of fucosylation. We hypothesized that loss-of-function HNF1A mutations causal for maturity-onset diabetes of the young (MODY) would display altered fucosylation of N-linked glycans on plasma proteins and that glycan biomarkers could improve the efficiency of a diagnosis of HNF1A-MODY. In a pilot comparison of 33 subjects with HNF1A-MODY and 41 subjects with type 2 diabetes, 15 of 29 glycan measurements differed between the two groups. The DG9-glycan index, which is the ratio of fucosylated to nonfucosylated triantennary glycans, provided optimum discrimination in the pilot study and was examined further among additional subjects with HNF1A-MODY (n = 188), glucokinase (GCK)-MODY (n = 118), hepatocyte nuclear factor 4-α (HNF4A)-MODY (n = 40), type 1 diabetes (n = 98), type 2 diabetes (n = 167), and nondiabetic controls (n = 98). The DG9-glycan index was markedly lower in HNF1A-MODY than in controls or other diabetes subtypes, offered good discrimination between HNF1A-MODY and both type 1 and type 2 diabetes (C statistic ≥0.90), and enabled us to detect three previously undetected HNF1A mutations in patients with diabetes. In conclusion, glycan profiles are altered substantially in HNF1A-MODY, and the DG9-glycan index has potential clinical value as a diagnostic biomarker of HNF1A dysfunction. PMID:23274891

Unveiling aerosol-cloud interactions - Part 2: Minimising the effects of aerosol swelling and wet scavenging in ECHAM6-HAM2 for comparison to satellite data

NASA Astrophysics Data System (ADS)

Neubauer, David; Christensen, Matthew W.; Poulsen, Caroline A.; Lohmann, Ulrike

2017-11-01

Aerosol-cloud interactions (ACIs) are uncertain and the estimates of the ACI effective radiative forcing (ERFaci) magnitude show a large variability. Within the Aerosol_cci project the susceptibility of cloud properties to changes in aerosol properties is derived from the high-resolution AATSR (Advanced Along-Track Scanning Radiometer) data set using the Cloud-Aerosol Pairing Algorithm (CAPA) (as described in our companion paper) and compared to susceptibilities from the global aerosol climate model ECHAM6-HAM2 and MODIS-CERES (Moderate Resolution Imaging Spectroradiometer - Clouds and the Earth's Radiant Energy System) data. For ECHAM6-HAM2 the dry aerosol is analysed to mimic the effect of CAPA. Furthermore the analysis is done for different environmental regimes. The aerosol-liquid water path relationship in ECHAM6-HAM2 is systematically stronger than in AATSR-CAPA data and cannot be explained by an overestimation of autoconversion when using diagnostic precipitation but rather by aerosol swelling in regions where humidity is high and clouds are present. When aerosol water is removed from the analysis in ECHAM6-HAM2 the strength of the susceptibilities of liquid water path, cloud droplet number concentration and cloud albedo as well as ERFaci agree much better with those of AATSR-CAPA or MODIS-CERES. When comparing satellite-derived to model-derived susceptibilities, this study finds it more appropriate to use dry aerosol in the computation of model susceptibilities. We further find that the statistical relationships inferred from different satellite sensors (AATSR-CAPA vs. MODIS-CERES) as well as from ECHAM6-HAM2 are not always of the same sign for the tested environmental conditions. In particular the susceptibility of the liquid water path is negative in non-raining scenes for MODIS-CERES but positive for AATSR-CAPA and ECHAM6-HAM2. Feedback processes like cloud-top entrainment that are missing or not well represented in the model are therefore not well constrained by satellite observations. In addition to aerosol swelling, wet scavenging and aerosol processing have an impact on liquid water path, cloud albedo and cloud droplet number susceptibilities. Aerosol processing leads to negative liquid water path susceptibilities to changes in aerosol index (AI) in ECHAM6-HAM2, likely due to aerosol-size changes by aerosol processing. Our results indicate that for statistical analysis of aerosol-cloud interactions the unwanted effects of aerosol swelling, wet scavenging and aerosol processing need to be minimised when computing susceptibilities of cloud variables to changes in aerosol.

Apolipoprotein M can discriminate HNF1A-MODY from Type 1 diabetes.

PubMed

Mughal, S A; Park, R; Nowak, N; Gloyn, A L; Karpe, F; Matile, H; Malecki, M T; McCarthy, M I; Stoffel, M; Owen, K R

2013-02-01

Missed diagnosis of maturity-onset diabetes of the young (MODY) has led to an interest in biomarkers that enable efficient prioritization of patients for definitive molecular testing. Apolipoprotein M (apoM) was suggested as a biomarker for hepatocyte nuclear factor 1 alpha (HNF1A)-MODY because of its reduced expression in Hnf1a(-/-) mice. However, subsequent human studies examining apoM as a biomarker have yielded conflicting results. We aimed to evaluate apoM as a biomarker for HNF1A-MODY using a highly specific and sensitive ELISA. ApoM concentration was measured in subjects with HNF1A-MODY (n = 69), Type 1 diabetes (n = 50), Type 2 diabetes (n = 120) and healthy control subjects (n = 100). The discriminative accuracy of apoM and of the apoM/HDL ratio for diabetes aetiology was evaluated. Mean (standard deviation) serum apoM concentration (μmol/l) was significantly lower for subjects with HNF1A-MODY [0.86 (0.29)], than for those with Type 1 diabetes [1.37 (0.26), P = 3.1 × 10(-18) ) and control subjects [1.34 (0.22), P = 7.2 × 10(-19) ). There was no significant difference in apoM concentration between subjects with HNF1A-MODY and Type 2 diabetes [0.89 (0.28), P = 0.13]. The C-statistic measure of discriminative accuracy for apoM was 0.91 for HNF1A-MODY vs. Type 1 diabetes, indicating high discriminative accuracy. The apoM/HDL ratio was significantly lower in HNF1A-MODY than other study groups. However, this ratio did not perform well in discriminating HNF1A-MODY from either Type 1 diabetes (C-statistic = 0.79) or Type 2 diabetes (C-statistic = 0.68). We confirm an earlier report that serum apoM levels are lower in HNF1A-MODY than in controls. Serum apoM provides good discrimination between HNF1A-MODY and Type 1 diabetes and warrants further investigation for clinical utility in diabetes diagnostics. © 2012 The Authors. Diabetic Medicine © 2012 Diabetes UK.

Building a symbolic computer algebra toolbox to compute 2D Fourier transforms in polar coordinates.

PubMed

Dovlo, Edem; Baddour, Natalie

2015-01-01

The development of a symbolic computer algebra toolbox for the computation of two dimensional (2D) Fourier transforms in polar coordinates is presented. Multidimensional Fourier transforms are widely used in image processing, tomographic reconstructions and in fact any application that requires a multidimensional convolution. By examining a function in the frequency domain, additional information and insights may be obtained. The advantages of our method include: •The implementation of the 2D Fourier transform in polar coordinates within the toolbox via the combination of two significantly simpler transforms.•The modular approach along with the idea of lookup tables implemented help avoid the issue of indeterminate results which may occur when attempting to directly evaluate the transform.•The concept also helps prevent unnecessary computation of already known transforms thereby saving memory and processing time.

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.

Cross comparison of the Collection 6 and Collection 6.1 Terra and Aqua MODIS Bands 1 and 2 using AVHRR N15 and N19

NASA Astrophysics Data System (ADS)

Chen, Xuexia; Wu, Aisheng; Xiong, Xiaoxiong J.; Chen, Na

2017-09-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key scientific instrument that was launched into Earth orbit by NASA in 1999 on board the Terra (EOS AM) satellite and in 2002 on board the Aqua (EOS PM) satellite. Terra and Aqua MODIS collect the entire Earth's images every 1 to 2 days in 36 spectral bands. MODIS band 1 (0.620- 0.670 μm) and band 2 (0.841-0.876 μm) have nadir spatial resolution of 250 m and their measurements are crucial to derive key land surface products. This study evaluates the performance of the Collection 6 (C6, and C6.1) L1B of both Terra and Aqua MODIS bands 1 and 2 using Simultaneous Nadir Overpass (SNO) data to compare with AVHRR/3 sensors. We examine the relative stability between Terra and Aqua MODIS in reference to NOAA N15 and N19 the Advanced Very High Resolution Radiometer (AVHRR/3). The comparisons for MODIS to AVHRR/3 are over a fifteenyear period from 2002 to 2017. Results from this study provide a quantitative assessment of Terra and Aqua MODIS band 1 and band 2 calibration stability and the relative differences through the NOAA N15 and N19 AVHRR/3 sensors.

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.

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.

Results and Lessons from a Decade of Terra MODIS On-Orbit Spectral Characterization

NASA Technical Reports Server (NTRS)

Xiong, X.; Choi, T.; Che, N.; Wang, Z.; Dodd, J.

2010-01-01

Since its launch in December 1999, the NASA EOS Terra MODIS has successfully operated for more than a decade. MODIS makes observations in 36 spectral bands from visible (VIS) to longwave infrared (LWIR) and at three nadir spatial resolutions: 250m (2 bands), 500m (5 bands), and 1km (29 bands). In addition to its on-board calibrators designed for the radiometric calibration, MODIS was built with a unique device, called the spectro-radiometric calibration assembly (SRCA). It can be configured in three different modes: radiometric, spatial, and spectral. When it is operated in the spectral modes, the SRCA can monitor changes in Sensor spectral performance for the VIS and near-infrared (NIR) spectral bands. For more than 10 years, the SRCA operation has continued to provide valuable information for MODIS on-orbit spectral performance. This paper briefly describes SRCA on-orbit operation and calibration activities; it presents decade-long spectral characterization results for Terra MODIS VIS and NIR spectral bands in terms of chances in their center wavelengths (CW) and bandwidths (BW). It is shown that the SRCA on-orbit wavelength calibration capability remains satisfactory. For most spectral bands, the changes in CW and BW are less than 0.5 and 1 nm, respectively. Results and lessons from Terra MODIS on-orbit spectral characterization have and will continue to benefit its successor, Aqua MODIS, and other future missions.

An Assessment of SeaWiFS and MODIS Ocean Coverage

NASA Technical Reports Server (NTRS)

Woodward, Robert H.; Gregg, Watson W.

1998-01-01

Ocean coverages of SeaWiFS and MODIS were assessed for three seasons by considering monthly mean values of surface winds speeds and cloud cover. Mean and maximum coverages combined SeaWiFS and MODIS by considering combined coverages for ten-degree increments of the MODIS orbital mean anomaly. From this analysis the mean and maximum combined coverages for SeaWiFS and MODIS were determined for one and four-day periods for spring, summer, and winter seasons. Loss of coverage due to Sun glint and cloud cover were identified for both the individual and combined cases. Our analyses indicate that MODIS will enhance ocean coverage for all three seasons examined. ne combined SeaWiFS/MODIS show an increase of coverage of 42.2% to 48.7% over SeaWiFS alone for the three seasons studied; the increase in maximum one day coverage ranges from 47.5% to 52.0%. The increase in four-day coverage for the combined case ranged from 31.0% to 35.8% for mean coverage and 33.1 % to 39.2% for maximum coverage. We computed meridional distributions of coverages by binning the data into five-degree latitude bands. Our analysis shows a strong seasonal dependence of coverage. In general the meridional analysis indicates that increase in coverages for SeaWiFS/MODIS over SeaWiFS alone are greatest near the solar declination.

Identification of HNF1A-MODY and HNF4A-MODY in Irish families: phenotypic characteristics and therapeutic implications.

PubMed

Kyithar, M P; Bacon, S; Pannu, K K; Rizvi, S R; Colclough, K; Ellard, S; Byrne, M M

2011-12-01

The prevalence of hepatocyte nuclear factor (HNF)-1A and HNF4A mutations, and the clinical implications following the genetic diagnosis of maturity-onset diabetes of the young (MODY) in the Irish population, remain unknown. The aim of this study was to establish the occurrence of HNF1A and HNF4A mutations in subjects classified clinically as MODY to identify novel mutations, and to determine the phenotypic features and response to therapy. A total of 36 unrelated index cases with a clinical diagnosis of MODY were analyzed for HNF1A/HNF4A mutations. OGTT was performed to determine the degree of glucose tolerance and insulin secretory response. Also, 38 relatives underwent OGTT and were tested for the relevant known mutations. HNF1A-/HNF4A-MODY subjects were compared with nine HNF1A mutation-negative relatives and 20 type 2 diabetic (T2DM) patients. Seven different HNF1A mutations were identified in 11/36 (30.5%) index cases, two of which were novel (S352fsdelG and F426X), as well as two novel HNF4A mutations (M1? and R290C; 6%). Family screening revealed 20 subjects with HNF1A and seven with HNF4A mutations. Only 51.6% of HNF1A mutation carriers were diagnosed with diabetes by age 25 years; 11 of the mutation carriers were overweight and four were obese. Insulin secretory response to glucose was significantly lower in HNF1A-MODY subjects than in T2DM patients and HNF1A mutation-negative relatives (P=0.01). Therapeutic changes occurred in 48% of mutation carriers following genetic diagnosis. There was an HNF1A-MODY pick-up rate of 30.5% and an HNF4A-MODY pick-up rate of 6% in Irish MODY families. Genetically confirmed MODY has significant therapeutic implications. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

High-sensitivity C-reactive protein does not improve the differential diagnosis of HNF1A-MODY and familial young-onset type 2 diabetes: A grey zone analysis.

PubMed

Bellanné-Chantelot, C; Coste, J; Ciangura, C; Fonfrède, M; Saint-Martin, C; Bouché, C; Sonnet, E; Valéro, R; Lévy, D-J; Dubois-Laforgue, D; Timsit, J

2016-02-01

Low plasma levels of high-sensitivity C-reactive protein (hs-CRP) have been suggested to differentiate hepatocyte nuclear factor 1 alpha-maturity-onset diabetes of the young (HNF1A-MODY) from type 2 diabetes (T2D). Yet, differential diagnosis of HNF1A-MODY and familial young-onset type 2 diabetes (F-YT2D) remains a difficult challenge. Thus, this study assessed the added value of hs-CRP to distinguish between the two conditions. This prospective multicentre study included 143 HNF1A-MODY patients, 310 patients with a clinical history suggestive of HNF1A-MODY, but not confirmed genetically (F-YT2D), and 215 patients with T2D. The ability of models, including clinical characteristics and hs-CRP to predict HNF1A-MODY was analyzed, using the area of the receiver operating characteristic (AUROC) curve, and a grey zone approach was used to evaluate these models in clinical practice. Median hs-CRP values were lower in HNF1A-MODY (0.25mg/L) than in F-YT2D (1.14mg/L) and T2D (1.70mg/L) patients. Clinical parameters were sufficient to differentiate HNF1A-MODY from classical T2D (AUROC: 0.99). AUROC analyses to distinguish HNF1A-MODY from F-YT2D were 0.82 for clinical features and 0.87 after including hs-CRP. For the grey zone analysis, the lower boundary was set to miss<1.5% of true positives in non-tested subjects, while the upper boundary was set to perform 50% of genetic tests in individuals with no HNF1A mutation. On comparing HNF1A-MODY with F-YT2D, 65% of patients were classified in between these categories - in the zone of diagnostic uncertainty - even after adding hs-CRP to clinical parameters. hs-CRP does not improve the differential diagnosis of HNF1A-MODY and F-YT2D. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

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.

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.

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.

Hypercomplex Fourier transforms of color images.

PubMed

Ell, Todd A; Sangwine, Stephen J

2007-01-01

Fourier transforms are a fundamental tool in signal and image processing, yet, until recently, there was no definition of a Fourier transform applicable to color images in a holistic manner. In this paper, hypercomplex numbers, specifically quaternions, are used to define a Fourier transform applicable to color images. The properties of the transform are developed, and it is shown that the transform may be computed using two standard complex fast Fourier transforms. The resulting spectrum is explained in terms of familiar phase and modulus concepts, and a new concept of hypercomplex axis. A method for visualizing the spectrum using color graphics is also presented. Finally, a convolution operational formula in the spectral domain is discussed.

The scale of the Fourier transform: a point of view of the fractional Fourier transform

NASA Astrophysics Data System (ADS)

Jimenez, C. J.; Vilardy, J. M.; Salinas, S.; Mattos, L.; Torres, C. O.

2017-01-01

In this paper using the Fourier transform of order fractional, the ray transfer matrix for the symmetrical optical systems type ABCD and the formulae by Collins for the diffraction, we obtain explicitly the expression for scaled Fourier transform conventional; this result is the great importance in optical signal processing because it offers the possibility of scaling the size of output the Fourier distribution of the system, only by manipulating the distance of the diffraction object toward the thin lens, this research also emphasizes on practical limits when a finite spherical converging lens aperture is used. Digital simulation was carried out using the numerical platform of Matlab 7.1.

Physical Modeling for Processing Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Hyperspectral Data

DTIC Science & Technology

2003-09-30

Physical Modeling for Processing Geosynchronous Imaging Fourier Transform Spectrometer ( GIFTS ) Hyperspectral Data Dr. Allen H.-L. Huang...ssec.wisc.edu Award Number: N000140110850 Grant Number: 144KE70 http://www.ssec.wisc.edu/ gifts /navy/ LONG-TERM GOALS This Office of Naval...objective of this DoD research effort is to develop and demonstrate a fully functional GIFTS hyperspectral data processing system with the potential for a

Can Biomarkers Help Target Maturity-Onset Diabetes of the Young Genetic Testing in Antibody-Negative Diabetes?

PubMed

Majidi, Shideh; Fouts, Alexandra; Pyle, Laura; Chambers, Christina; Armstrong, Taylor; Wang, Zhenyuan; Batish, Sat Dev; Klingensmith, Georgeanna; Steck, Andrea K

2018-02-01

Maturity-onset diabetes of the young (MODY) is an antibody-negative, autosomal dominant form of diabetes. With the increasing prevalence of diabetes and the expense of MODY testing, markers to identify those who need further genetic testing would be beneficial. We investigated whether HLA genotypes, random C-peptide, and/or high-sensitivity C-reactive protein (hsCRP) levels could be helpful biomarkers for identifying MODY in antibody-negative diabetes. Subjects (N = 97) with diabetes onset ≤age 25, measurable C-peptide (≥0.1 ng/mL), and negative for all four diabetes autoantibodies were enrolled at a large academic center and tested for MODY 1-5 through Athena Diagnostics. A total of 22 subjects had a positive or very likely pathogenic mutation for MODY. Random C-peptide levels were significantly different between MODY-positive and MODY-negative subjects (0.16 nmol/L vs. 0.02 nmol/L; P = 0.02). After adjusting for age and diabetes duration, hsCRP levels were significantly lower in MODY-positive subjects (0.37 mg/L vs. 0.87 mg/L; P = 0.02). Random C-peptide level ≥0.15 nmol/L obtained at ≥6 months after diagnosis had 83% sensitivity for diagnosis of MODY with a negative predictive value of 96%. Receiver operating characteristic curves showed that area under the curve for random C-peptide (0.75) was significantly better than hsCRP (0.54), high-risk HLA DR3/4-DQB1*0302 (0.59), and high-risk HLA/random C-peptide combined (0.54; P = 0.03). Random C-peptide obtained at ≥6 months after diagnosis can be a useful biomarker to identify antibody-negative individuals who need further genetic testing for MODY, whereas hsCRP and HLA do not appear to improve this antibody/C-peptide-based approach.

Intercomparisons of Marine Boundary Layer Cloud Properties from the ARM CAP-MBL Campaign and Two MODIS Cloud Products

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick

2017-01-01

From April 2009 to December 2010, the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an inter-comparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT) and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility (AMF) and two Moderate Resolution Spectroradiometer (MODIS) cloud products (GSFC-MODIS and CERES-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for inter-comparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R greater than 0.95 despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 micrometers band (CER(sub 2.1)) is significantly smaller than that based on the 3.7 micrometers band (CER(sub 3.7)). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER(sub 3.7) and CER(sub 2.1) retrievals have a lower correlation (R is approximately 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 micrometers and 3.0 micrometers, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 micrometers.

Should the negativity for islet cell autoantibodies be used in a prescreening for genetic testing in maturity-onset diabetes of the young? The case of autoimmunity-associated destruction of pancreatic β-cells in a family of HNF1A-MODY subjects.

PubMed

Urbanová, Jana; Rypáčková, Blanka; Kučera, Petr; Anděl, Michal; Heneberg, Petr

2013-01-01

It was recently suggested that routine islet cell autoantibody testing should be performed to discriminate maturity-onset diabetes of the young (MODY) from type 1 diabetes mellitus (T1DM). This is the first report ever to describe the familial manifestation of T1DM autoimmunity in nonobese HNF1A-MODY subjects and the presence of islet antigen-2 (IA-2) antibodies in MODY subjects. Three nonobese subjects in an age range of 14-35 years were diagnosed with HNF1A-MODY (p. Arg159Gln mutation). All the tested subjects had detectable (but varying) levels of islet cell autoantibodies (i.e., antibodies against glutamate decarboxylase or IA-2) in the absence of other T1DM characteristics. They displayed long-term expression of intermediate fasting C-peptide levels, ketoacidosis was absent even in periods of spontaneous insulin withdrawal, and full dependence on externally administered insulin was not detected in any of them although better glycemic control was achieved when insulin was supplemented. The course of the disease was similar to that of the autoantibody-negative HNF1A-MODY subjects. The case questions the selectivity of autoantibodies as a marker of T1DM or late-onset autoimmune diabetes of adulthood (LADA) over MODY and challenges the use of autoantibodies as a universal negative marker of MODY in an effort to decrease the cost of health care, as it may eventually lead to the wrong diagnosis and thus to the incorrect treatment. Further research should involve examination of the autoantibody titers and prevalence in large and geographically diverse cohorts of MODY subjects selected for genetic testing (regardless of their autoantibody titers) as well as determination of the islet cell autoantibody kinetics in the course of MODY onset and progression. Copyright © 2013 S. Karger AG, Basel.

Half-Life of Sulfonylureas in HNF1A and HNF4A Human MODY Patients is not Prolonged as Suggested by the Mouse Hnf1a(-/-) Model.

PubMed

Urbanova, Jana; Andel, Michal; Potockova, Jana; Klima, Josef; Macek, Jan; Ptacek, Pavel; Mat'oska, Vaclav; Kumstyrova, Tereza; Heneberg, Petr

2015-01-01

Sulfonylurea derivatives are widely used for clinical treatment of human subjects with Maturity Onset Diabetes of the Young (MODY) caused by mutations in HNF-1α or HNF-4α despite the mechanism leading to their hypersensitivity is incompletely understood. In Hnf1a(-/-) mice, serum concentrations and half-life of sulfonylurea derivatives are strongly increased. We thus hypothesized that reduced sulfonylurea derivatives clearance stands behind their therapeutic potential in human HNF1A/HNF4A MODY subjects. Single doses of 3 mg glipizide and 5 mg glibenclamide/glyburide were administered sequentially to seven HNF1A/HNF4A MODY subjects and six control individuals matched for their age, BMI and CYP2C9 genotype. Pharmacokinetic (plasma concentration levels, Cmax, tmax, t1/2, AUC) and pharmacodynamic parameters (glycemia, C-peptide and insulin plasma levels) were followed for 24 hours after drug administration. We provide the first evidence on the pharmacokinetics and pharmacodynamics of sulfonylurea derivatives in human MODY subjects. The half-life of glipizide did not change, and reached 3.8±0.7 and 3.7±1.8 h in the MODY and control subjects, respectively. The half-life of glibenclamide was increased only in some MODY subjects (t1/2 9.5±6.7 and 5.0±1.4 h, respectively). Importantly, the intra- individual responses of MODY (but control) subjects to glipizide and glibenclamide treatment were highly correlated. With regards to pharmacodynamics, we observed a differential response of control but not MODY subjects to the doses of glipizide and glibenclamide applied. We rejected the hypothesis that all human MODY-associated mutations in HNF1A / HNF4A induce changes in the pharmacokinetics of sulfonylureas in humans analogically to the Hnf1a(-/-) mouse model.

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.

A browser-based 3D Visualization Tool designed for comparing CERES/CALIOP/CloudSAT level-2 data sets.

NASA Astrophysics Data System (ADS)

Chu, C.; Sun-Mack, S.; Chen, Y.; Heckert, E.; Doelling, D. R.

2017-12-01

In Langley NASA, Clouds and the Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) are merged with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat Cloud Profiling Radar (CPR). The CERES merged product (C3M) matches up to three CALIPSO footprints with each MODIS pixel along its ground track. It then assigns the nearest CloudSat footprint to each of those MODIS pixels. The cloud properties from MODIS, retrieved using the CERES algorithms, are included in C3M with the matched CALIPSO and CloudSat products along with radiances from 18 MODIS channels. The dataset is used to validate the CERES retrieved MODIS cloud properties and the computed TOA and surface flux difference using MODIS or CALIOP/CloudSAT retrieved clouds. This information is then used to tune the computed fluxes to match the CERES observed TOA flux. A visualization tool will be invaluable to determine the cause of these large cloud and flux differences in order to improve the methodology. This effort is part of larger effort to allow users to order the CERES C3M product sub-setted by time and parameter as well as the previously mentioned visualization capabilities. This presentation will show a new graphical 3D-interface, 3D-CERESVis, that allows users to view both passive remote sensing satellites (MODIS and CERES) and active satellites (CALIPSO and CloudSat), such that the detailed vertical structures of cloud properties from CALIPSO and CloudSat are displayed side by side with horizontally retrieved cloud properties from MODIS and CERES. Similarly, the CERES computed profile fluxes whether using MODIS or CALIPSO and CloudSat clouds can also be compared. 3D-CERESVis is a browser-based visualization tool that makes uses of techniques such as multiple synchronized cursors, COLLADA format data and Cesium.

Intercomparisons of marine boundary layer cloud properties from the ARM CAP-MBL campaign and two MODIS cloud products

NASA Astrophysics Data System (ADS)

Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick

2017-02-01

From April 2009 to December 2010, the Department of Energy Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an intercomparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT), and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility and two Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products (Goddard Space Flight Center (GSFC)-MODIS and Clouds and Earth's Radiant Energy System-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for intercomparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R > 0.95, despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 µm band (CER2.1) are significantly larger than those based on the 3.7 µm band (CER3.7). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal-spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER3.7 and CER2.1 retrievals have a lower correlation (R 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 µm and 3.0 µm, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 µm.

Comparisons of Satellite-Deduced Overlapping Cloud Properties and CALIPSO CloudSat Data

NASA Technical Reports Server (NTRS)

Chang, Fu-Lung; Minnis, Patrick; Lin, Bing; Sun-Mack, Sunny

2010-01-01

Introduction to the overlapped cloud properties derived from polar-orbiting (MODIS) and geostationary (GOES-12, -13, Meteosat-8, -9, etc.) meteorological satellites, which are produced at the NASA Langley Research Center (LaRC) cloud research & development team (NASA lead scientist: Dr. Patrick Minnis). Comparison of the LaRC CERES MODIS Edition-3 overlapped cloud properties to the CALIPSO and the CloudSat active sensing data. High clouds and overlapped clouds occur frequently as deduced by CALIPSO (44 & 25%), CloudSat (25 & 4%), and MODIS (37 & 6%). Large fractions of optically-thin cirrus and overlapped clouds are deduced from CALIPSO, but much smaller fractions are from CloudSat and MODIS. For overlapped clouds, the averaged upper-layer CTHs are about 12.8 (CALIPSO), 10.9 (CloudSat) and 10 km (MODIS), and the averaged lower-layer CTHs are about 3.6 (CALIPSO), 3.2 (CloudSat) and 3.9 km (MODIS). Based on comparisons of upper and lower-layer cloud properties as deduced from the MODIS, CALIPSO and CloudSat data, more enhanced passive satellite methods for retrieving thin cirrus and overlapped cloud properties are needed and are under development.

Evaluation of the MODIS Retrievals of Dust Aerosol over the Ocean during PRIDE

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Remer, Lorraine A.; Tanre, Didier; Kaufman, Yoram J.; Ichoku, Charles; Holben, Brent N.; Livingston, John M.; Russell, Philip B.; Maring, Hal

2002-01-01

The Puerto Rico Dust Experiment (PRIDE) took place in Roosevelt Roads, Puerto Rico from June 26 to July 24,2000 to study the radiative and physical properties of African dust aerosol transported into the region. PRIDE had the unique distinction of being the first major field experiment to allow direct comparison of aerosol retrievals from the MODerate Imaging Spectro-radiometer (MODIS) with sunphotometer and in-situ aerosol measurements. Over the ocean, the MODIS algorithm retrieves aerosol optical depth (AOD) as well as information about the aerosols size distribution. During PRIDE, MODIS derived AODs in the red wavelengths (0.66 micrometers) compare closely with AODs measured from sunphotometers, but, are too large at blue and green wavelengths (0.47 and 0.55 micrometers) and too small in the infrared (0.87 micrometers). This discrepancy of spectral slope results in particle size distributions retrieved by MODIS that are small compared to in-situ measurements, and smaller still when compared to sunphotometer sky radiance inversions. The differences in size distributions are, at least in part, associated with MODIS simplification of dust as spherical particles. Analysis of this PRIDE data set is a first step towards derivation of realistic non-spherical models for future MODIS retrievals.

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Ryan, Robert E.; Smoot, James; Kuper, Phillip; Prados, Donald; Russell, Jeffrey; Ross, Kenton; Gasser, Gerald; Sader, Steven; McKellip, Rodney

2007-01-01

This report details one of three experiments performed during FY 2007 for the NASA RPC (Rapid Prototyping Capability) at Stennis Space Center. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria dispar). The intent of the RPC experiment was to assess the degree to which VIIRS data can provide forest disturbance monitoring information as an input to a forest threat EWS (Early Warning System) as compared to the level of information that can be obtained from MODIS data. The USDA Forest Service (USFS) plans to use MODIS products for generating broad-scaled, regional monitoring products as input to an EWS for forest health threat assessment. NASA SSC is helping the USFS to evaluate and integrate currently available satellite remote sensing technologies and data products for the EWS, including the use of MODIS products for regional monitoring of forest disturbance. Gypsy moth defoliation of the mid-Appalachian highland region was selected as a case study. Gypsy moth is one of eight major forest insect threats listed in the Healthy Forest Restoration Act (HFRA) of 2003; the gypsy moth threatens eastern U.S. hardwood forests, which are also a concern highlighted in the HFRA of 2003. This region was selected for the project because extensive gypsy moth defoliation occurred there over multiple years during the MODIS operational period. This RPC experiment is relevant to several nationally important mapping applications, including agricultural efficiency, coastal management, ecological forecasting, disaster management, and carbon management. In this experiment, MODIS data and VIIRS data simulated from MODIS were assessed for their ability to contribute broad, regional geospatial information on gypsy moth defoliation. Landsat and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data were used to assess the quality of gypsy moth defoliation mapping products derived from MODIS data and from simulated VIIRS data. The project focused on use of data from MODIS Terra as opposed to MODIS Aqua mainly because only MODIS Terra data was collected during 2000 and 2001-years with comparatively high amounts of gypsy moth defoliation within the study area. The project assessed the quality of VIIRS data simulation products. Hyperion data was employed to assess the quality of MODIS-based VIIRS simulation datasets using image correlation analysis techniques. The ART (Application Research Toolbox) software was used for data simulation. Correlation analysis between MODIS-simulated VIIRS data and Hyperion-simulated VIIRS data for red, NIR (near-infrared), and NDVI (Normalized Difference Vegetation Index) image data products collectively indicate that useful, effective VIIRS simulations can be produced using Hyperion and MODIS data sources. The r(exp 2) for red, NIR, and NDVI products were 0.56, 0.63, and 0.62, respectively, indicating a moderately high correlation between the 2 data sources. Temporal decorrelation from different data acquisition times and image misregistration may have lowered correlation results. The RPC experiment also generated MODIS-based time series data products using the TSPT (Time Series Product Tool) software. Time series of simulated VIIRS NDVI products were produced at approximately 400-meter resolution GSD (Ground Sampling Distance) at nadir for comparison to MODIS NDVI products at either 250- or 500-meter GSD. The project also computed MODIS (MOD02) NDMI (Normalized Difference Moisture Index) products at 500-meter GSD for comparison to NDVI-based products. For each year during 2000-2006, MODIS and VIIRS (simulated from MOD02) time series were computed during the peak gypsy moth defoliation time frame in the study area (approximately June 10 through July 27). Gypsy moth defoliation mapping products from simated VIIRS and MOD02 time series were produced using multiple methods, including image classification and change detection via image differencing. The latter enabled an automated defoliation detection product computed using percent change in maximum NDVI for a peak defoliation period during 2001 compared to maximum NDVI across the entire 2000-2006 time frame. Final gypsy moth defoliation mapping products were assessed for accuracy using randomly sampled locations found on available geospatial reference data (Landsat and ASTER data in conjunction with defoliation map data from the USFS). Extensive gypsy moth defoliation patches were evident on screen displays of multitemporal color composites derived from MODIS data and from simulated VIIRS vegetation index data. Such defoliation was particularly evident for 2001, although widespread denuded forests were also seen for 2000 and 2003. These visualizations were validated using aforementioned reference data. Defoliation patches were visible on displays of MODIS-based NDVI and NDMI data. The viewing of apparent defoliation patches on all of these products necessitated adoption of a specialized temporal data processing method (e.g., maximum NDVI during the peak defoliation time frame). The frequency of cloud cover necessitated this approach. Multitemporal simulated VIIRS and MODIS Terra data both produced effective general classifications of defoliated forest versus other land cover. For 2001, the MOD02-simulated VIIRS 400-meter NDVI classification produced a similar yet slightly lower overall accuracy (87.28 percent with 0.72 Kappa) than the MOD02 250-meter NDVI classification (88.44 percent with 0.75 Kappa). The MOD13 250-meter NDVI classification had a lower overall accuracy (79.13 percent) and a much lower Kappa (0.46). The report discusses accuracy assessment results in much more detail, comparing overall classification and individual class accuracy statistics for simulated VIIRS 400-meter NDVI, MOD02 250-meter NDVI, MOD02-500 meter NDVI, MOD13 250-meter NDVI, and MOD02 500-meter NDMI classifications. Automated defoliation detection products from simulated VIIRS and MOD02 data for 2001 also yielded similar, relatively high overall classification accuracy (85.55 percent for the VIIRS 400-meter NDVI versus 87.28 percent for the MOD02 250-meter NDVI). In contrast, the USFS aerial sketch map of gypsy moth defoliation showed a lower overall classification accuracy at 73.64 percent. The overall classification Kappa values were also similar for the VIIRS (approximately 0.67 Kappa) versus the MOD02 (approximately 0.72 Kappa) automated defoliation detection product, which were much higher than the values exhibited by the USFS sketch map product (overall Kappa of approximately 0.47). The report provides additional details on the accuracy of automated gypsy moth defoliation detection products compared with USFS sketch maps. The results suggest that VIIRS data can be effectively simulated from MODIS data and that VIIRS data will produce gypsy moth defoliation mapping products that are similar to MODIS-based products. The results of the RPC experiment indicate that VIIRS and MODIS data products have good potential for integration into the forest threat EWS. The accuracy assessment was performed only for 2001 because of time constraints and a relative scarcity of cloud-free Landsat and ASTER data for the peak defoliation period of the other years in the 2000-2006 time series. Additional work should be performed to assess the accuracy of gypsy moth defoliation detection products for additional years.The study area (mid-Appalachian highlands) and application (gypsy moth forest defoliation) are not necessarily representative of all forested regions and of all forest threat disturbance agents. Additional work should be performed on other inland and coastal regions as well as for other major forest threats.

A MODIS-based begetation index climatology

USDA-ARS?s Scientific Manuscript database

Passive microwave soil moisture algorithms must account for vegetation attenuation of the signal in the retrieval process. One approach to accounting for vegetation is to use vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to estimate the vegetation optical depth. The pa...

Estimation of Carbon Flux of Forest Ecosystem over Qilian Mountains by BIOME-BGC Model

NASA Astrophysics Data System (ADS)

Yan, Min; Tian, Xin; Li, Zengyuan; Chen, Erxue; Li, Chunmei

2014-11-01

The gross primary production (GPP) and net ecosystem exchange (NEE) are important indicators for carbon fluxes. This study aims at evaluating the forest GPP and NEE over the Qilian Mountains using meteorological, remotely sensed and other ancillary data at large scale. To realize this, the widely used ecological-process-based model, Biome-BGC, and remote-sensing-based model, MODIS GPP algorithm, were selected for the simulation of the forest carbon fluxes. The combination of these two models was based on calibrating the Biome-BGC by the optimized MODIS GPP algorithm. The simulated GPP and NEE values were evaluated against the eddy covariance observed GPPs and NEEs, and the well agreements have been reached, with R2=0.76, 0.67 respectively.

Estimation of Carbon Flux of Forest Ecosystem over Qilian Mountains by BIOME-BGC Model

NASA Astrophysics Data System (ADS)

Yan, Min; Tian, Xin; Li, Zengyuan; Chen, Erxue; Li, Chunmei

2014-11-01

The gross primary production (GPP) and net ecosystem exchange (NEE) are important indicators for carbon fluxes. This study aims at evaluating the forest GPP and NEE over the Qilian Mountains using meteorological, remotely sensed and other ancillary data at large scale. To realize this, the widely used ecological-process- based model, Biome-BGC, and remote-sensing-based model, MODIS GPP algorithm, were selected for the simulation of the forest carbon fluxes. The combination of these two models was based on calibrating the Biome-BGC by the optimized MODIS GPP algorithm. The simulated GPP and NEE values were evaluated against the eddy covariance observed GPPs and NEEs, and the well agreements have been reached, with R2=0.76, 0.67 respectively.

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.

Exploring the nutrient inputs and cycles in Tampa Bay and coastal watersheds using MODIS images and data mining

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Xuan, Zhemin

2011-09-01

Excessive nutrients, which may be represented as Total Nitrogen (TN) and Total Phosphorus (TP) levels, in natural water systems have proven to cause high levels of algae production. The process of phytoplankton growth which consumes the excess TN and TP in a water body can also be related to the changing water quality levels, such as Dissolved Oxygen (DO), chlorophyll-a, and turbidity, associated with their changes in absorbance of natural radiation. This paper explores spatiotemporal nutrient patterns in Tampa Bay, Florida with the aid of Moderate Resolution Imaging Spectroradiometer or MODIS images and Genetic Programming (GP) models that are deigned to link those relevant water quality parameters in aquatic environments.

Recent Update on MODIS/VIIRS Deep Blue Data Continuity and New Aerosol Products

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Sayer, Andrew M.; Lee, Jaehwa; Bettenhausen, Corey; Carletta, N.; Tsay, Si-Chee

2016-01-01

The MODIS VIIRS 2016 Science Team Meeting was held June 6-10, 2016 at the Sheraton in Silver Spring, MD. The organizers plan to post the presentations and posters here: http:modis.gsfc.nasa.govsci_teammeetings201606.

The Use of MODIS NDVI Data for Characterizing Cropland Across the Great Lakes Basin

EPA Science Inventory

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides new opportunities for characterizing land-cover (LC) to support monitoring and assessment studies at watershed, regional and global scales. This research evaluated the potential for using the MODIS Normalized Diff...

Is It Possible to Distinguish Between Dust and Salt Aerosol Over Waters with Unknown Chlorophyll Concentrations Using Spectral Remote Sensing?

NASA Technical Reports Server (NTRS)

Levy, R. C.; Kaufman, Y. J.

1999-01-01

Atmospheric aerosol has uncertain impacts on the global climate system, as well as on atmospheric and bio-geo-chemical processes of regional and local scales. EOS-MODIS is one example of a satellite sensor designed to improve understanding of the aerosols' type, size and distribution at all temporal and spatial scales. Ocean scientists also plan to use data from EOS-MODIS to assess the temporal and spatial coverage of in-water chlorophyll. MODIS is the first sensor planned to observe the combined ocean-atmosphere system with a wide spectral range (from 410 to 2200 nm). Dust aerosol and salt aerosol have similar spectral signals for wavelengths longer than 550 nm, but because dust selectively absorbs blue light, they have divergent signals in the blue wavelength regions (412 to 490 nm). Chlorophyll also selectively absorbs blue radiation, so that varying chlorophyll concentrations produces a highly varying signal in the blue regions, but less variability in the green, and almost no signal in the red to mid-infrared regions. Thus, theoretically, it may be difficult to differentiate dust and salt in the presence of unknown chlorophyll in the ocean. This study attempts to address the cases in which aerosol and chlorophyll signals can and cannot be separated. For the aerosol spectra, we use the aerosol lookup table from the operational MODIS aerosol-over-ocean algorithm, and for chlorophyll spectra, we use the SeaBAM data set (created for SeaWiFS). We compare the signals using Principal Component Analysis and attempt to retrieve both chlorophyll and aerosol properties using a variant of the operational MODIS aerosol-over-ocean algorithm. Results show that for small optical depths, less than 0.5, it is not possible to differentiate between dust and salt and to determine the chlorophyll concentration at the same time. For larger aerosol optical depths, the chlorophyll signals are comparatively insignificant, and we can hope to distinguish between dust and salt.

Initial Verification of GEOS-4 Aerosols Using CALIPSO and MODIS: Scene Classification

NASA Technical Reports Server (NTRS)

Welton, Ellsworth J.; Colarco, Peter R.; Hlavka, Dennis; Levy, Robert C.; Vaughan, Mark A.; daSilva, Arlindo

2007-01-01

A-train sensors such as MODIS and MISR provide column aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important because retrievals are often dependent upon selection of the right aerosol model. In addition, aerosol scene classification helps place the retrieved products in context for comparisons and analysis with aerosol transport models. The recent addition of CALIPSO to the A-train now provides a means of classifying aerosol distribution with altitude. CALIPSO level 1 products include profiles of attenuated backscatter at 532 and 1064 nm, and depolarization at 532 nm. Backscatter intensity, wavelength ratio, and depolarization provide information on the vertical profile of aerosol concentration, size, and shape. Thus similar estimates of aerosol type using MODIS or MISR are possible with CALIPSO, and the combination of data from all sensors provides a means of 3D aerosol scene classification. The NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-4) provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS-4 aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures along the flight track for NASA's Geoscience Laser Altimeter System (GLAS) satellite lidar. GLAS launched in 2003 and did not have the benefit of depolarization measurements or other sensors from the A-train. Aerosol typing from GLAS data alone was not possible, and the GEOS-4 aerosol classifier has been used to identify aerosol type and improve the retrieval of GLAS products. Here we compare 3D aerosol scene classification using CALIPSO and MODIS with the GEOS-4 aerosol classifier. Dust, smoke, and pollution examples will be discussed in the context of providing an initial verification of the 3D GEOS-4 aerosol products. Prior model verification has only been attempted with surface mass comparisons and column optical depth from AERONET and MODIS.

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;

Application of Remote Sensing to Assess the Impact of Short Term Climate Variability on Coastal Sedimentation

NASA Technical Reports Server (NTRS)

Moeller, Christopher C.; Gunshor, Mathew M.; Menzel, W. Paul; Huh, Oscar K.; Walker, Nan D.; Rouse, Lawrence J.; Frey, Herbert V. (Technical Monitor)

2001-01-01

The University of Wisconsin and Louisiana State University have teamed to study the forcing of winter season cold frontal wind systems on sediment distribution patterns and geomorphology in the Louisiana coastal zone. Wind systems associated with cold fronts have been shown to modify coastal circulation and resuspend sediments along the microtidal Louisiana coast. The assessment includes quantifying the influence of cumulative winter season atmospheric forcing (through surface wind observations) from year to year in response to short term climate variability, such as El Nino events. A correlation between winter cyclone frequency and the strength of El Nino events has been suggested. The atmospheric forcing data are being correlated to geomorphic measurements along western Louisiana's prograding muddy coast. Remote sensing data is being used to map and track sediment distribution patterns for various wind conditions. Transferring a suspended sediment concentration (SSC) algorithm to EOS MODIS observations will enable estimates of SSC in case 2 waters over the global domain. Progress in Year 1 of this study has included data collection and analysis of wind observations for atmospheric forcing characterization, a field activity (TX-2001) to collect in situ water samples with co-incident remote sensing measurements from the NASA ER-2 based MODIS Airborne Simulator (MAS) and the EOS Terra based MODerate resolution Imaging Spectroradiometer (MODIS) instruments, aerial photography and of sediment burial pipe field measurements along the prograding muddy Chenier Plain coast of western Louisiana for documenting coastal change in that dynamic region, and routine collection of MODIS 250 in resolution data for monitoring coastal sediment patterns. The data sets are being used in a process to transfer an SSC estimation algorithm to the MODIS platform. Work is underway on assessing coastal transport for the winter 2000-01 season. Water level data for use in a Geomorphic Impact Index, which relates wind energy, water level conditions, and geomorphic change along the microtidal western Louisiana coastline is being assembled.

The morphing of geographical features by Fourier transformation

PubMed Central

Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features’ continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable. PMID:29351344

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.

Validation of MODIS 3 km land aerosol optical depth from NASA's EOS Terra and Aqua missions

NASA Astrophysics Data System (ADS)

Gupta, Pawan; Remer, Lorraine A.; Levy, Robert C.; Mattoo, Shana

2018-05-01

In addition to the standard resolution product (10 km), the MODerate resolution Imaging Spectroradiometer (MODIS) Collection 6 (C006) data release included a higher resolution (3 km). Other than accommodations for the two different resolutions, the 10 and 3 km Dark Target (DT) algorithms are basically the same. In this study, we perform global validation of the higher-resolution aerosol optical depth (AOD) over global land by comparing against AErosol RObotic NETwork (AERONET) measurements. The MODIS-AERONET collocated data sets consist of 161 410 high-confidence AOD pairs from 2000 to 2015 for Terra MODIS and 2003 to 2015 for Aqua MODIS. We find that 62.5 and 68.4 % of AODs retrieved from Terra MODIS and Aqua MODIS, respectively, fall within previously published expected error bounds of ±(0.05 + 0.2 × AOD), with a high correlation (R = 0.87). The scatter is not random, but exhibits a mean positive bias of ˜ 0.06 for Terra and ˜ 0.03 for Aqua. These biases for the 3 km product are approximately 0.03 larger than the biases found in similar validations of the 10 km product. The validation results for the 3 km product did not have a relationship to aerosol loading (i.e., true AOD), but did exhibit dependence on quality flags, region, viewing geometry, and aerosol spatial variability. Time series of global MODIS-AERONET differences show that validation is not static, but has changed over the course of both sensors' lifetimes, with Terra MODIS showing more change over time. The likely cause of the change of validation over time is sensor degradation, but changes in the distribution of AERONET stations and differences in the global aerosol system itself could be contributing to the temporal variability of validation.

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.

Detection rates of the MODIS active fire product in the United States

USGS Publications Warehouse

Hawbaker, T.J.; Radeloff, V.C.; Syphard, A.D.; Zhu, Z.; Stewart, S.I.

2008-01-01

MODIS active fire data offer new information about global fire patterns. However, uncertainties in detection rates can render satellite-derived fire statistics difficult to interpret. We evaluated the MODIS 1??km daily active fire product to quantify detection rates for both Terra and Aqua MODIS sensors, examined how cloud cover and fire size affected detection rates, and estimated how detection rates varied across the United States. MODIS active fire detections were compared to 361 reference fires (??? 18??ha) that had been delineated using pre- and post-fire Landsat imagery. Reference fires were considered detected if at least one MODIS active fire pixel occurred within 1??km of the edge of the fire. When active fire data from both Aqua and Terra were combined, 82% of all reference fires were found, but detection rates were less for Aqua and Terra individually (73% and 66% respectively). Fires not detected generally had more cloudy days, but not when the Aqua data were considered exclusively. MODIS detection rates decreased with fire size, and the size at which 50% of all fires were detected was 105??ha when combining Aqua and Terra (195??ha for Aqua and 334??ha for Terra alone). Across the United States, detection rates were greatest in the West, lower in the Great Plains, and lowest in the East. The MODIS active fire product captures large fires in the U.S. well, but may under-represent fires in areas with frequent cloud cover or rapidly burning, small, and low-intensity fires. We recommend that users of the MODIS active fire data perform individual validations to ensure that all relevant fires are included. ?? 2008 Elsevier Inc. All rights reserved.

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.

De novo mutations of GCK, HNF1A and HNF4A may be more frequent in MODY than previously assumed.

PubMed

Stanik, Juraj; Dusatkova, Petra; Cinek, Ondrej; Valentinova, Lucia; Huckova, Miroslava; Skopkova, Martina; Dusatkova, Lenka; Stanikova, Daniela; Pura, Mikulas; Klimes, Iwar; Lebl, Jan; Gasperikova, Daniela; Pruhova, Stepanka

2014-03-01

MODY is mainly characterised by an early onset of diabetes and a positive family history of diabetes with an autosomal dominant mode of inheritance. However, de novo mutations have been reported anecdotally. The aim of this study was to systematically revisit a large collection of MODY patients to determine the minimum prevalence of de novo mutations in the most prevalent MODY genes (i.e. GCK, HNF1A, HNF4A). Analysis of 922 patients from two national MODY centres (Slovakia and the Czech Republic) identified 150 probands (16%) who came from pedigrees that did not fulfil the criterion of two generations with diabetes but did fulfil the remaining criteria. The GCK, HNF1A and HNF4A genes were analysed by direct sequencing. Mutations in GCK, HNF1A or HNF4A genes were detected in 58 of 150 individuals. Parents of 28 probands were unavailable for further analysis, and in 19 probands the mutation was inherited from an asymptomatic parent. In 11 probands the mutations arose de novo. In our cohort of MODY patients from two national centres the de novo mutations in GCK, HNF1A and HNF4A were present in 7.3% of the 150 families without a history of diabetes and 1.2% of all of the referrals for MODY testing. This is the largest collection of de novo MODY mutations to date, and our findings indicate a much higher frequency of de novo mutations than previously assumed. Therefore, genetic testing of MODY could be considered for carefully selected individuals without a family history of diabetes.

A decade of molecular genetic testing for MODY: a retrospective study of utilization in The Netherlands.

PubMed

Weinreich, Stephanie S; Bosma, Astrid; Henneman, Lidewij; Rigter, Tessel; Spruijt, Carla M J; Grimbergen, Anneliese J E M A; Breuning, Martijn H; de Koning, Eelco J P; Losekoot, Monique; Cornel, Martina C

2015-01-01

Genetic testing for maturity-onset diabetes of the young (MODY) may be relevant for treatment and prognosis in patients with usually early-onset, non-ketotic, insulin-sensitive diabetes and for monitoring strategies in non-diabetic mutation carriers. This study describes the first 10 years of genetic testing for MODY in The Netherlands in terms of volume and test positive rate, medical setting, purpose of the test and age of patients tested. Some analyses focus on the most prevalent subtype, HNF1A MODY. Data were retrospectively extracted from a laboratory database. In total, 502 individuals were identified with a pathogenic mutation in HNF4A, GCK or HNF1A between 2001 and 2010. Although mutation scanning for MODY was used at an increasing rate, cascade testing was only used for one relative, on average, per positive index patient. Testing for HNF1A MODY was mostly requested by internists and paediatricians, often from regional hospitals. Primary care physicians and clinical geneticists rarely requested genetic testing for HNF1A MODY. Clinical geneticists requested cascade testing relatively more often than other health professionals. A substantial proportion (currently 29%) of HNF1A MODY probands was at least 40 years old at the time of testing. In conclusion, the number of individuals genetically tested for MODY so far in The Netherlands is low compared with previously predicted numbers of patients. Doctors' valuation of the test and patients' and family members' response to (an offer of) genetic testing on the other hand need to be investigated. Efforts may be needed to develop and implement translational guidelines.

A multi-scale assessment of forest primary production across the eastern USA using Forest Inventory and Analysis (FIA) and MODIS data

NASA Astrophysics Data System (ADS)

Kwon, Youngsang

As evidence of global warming continues to increase, being able to predict the relationship between forest growth rate and climate factors will be vital to maintain the sustainability and productivity of forests. Comprehensive analyses of forest primary production across the eastern US were conducted using remotely sensed MODIS and field-based FIA datasets. This dissertation primarily explored spatial patterns of gross and net carbon uptake in the eastern USA, and addressed three objectives. 1) Examine the use of pixel- and plot-scale screening variables to validate MODIS GPP predictions with Forest Inventory and Analysis (FIA) NPP measures. 2) Assess the net primary production (NPP) from MODIS and FIA at increasing levels of spatial aggregation using a hexagonal tiling system. 3) Assess the carbon use efficiency (CUE) calculated using a direct ratio of MODIS NPP to MODIS GPP and a standardized ratio of FIA NPP to MODIS GPP. The first objective was analyzed using total of 54,969 MODIS pixels and co-located FIA plots to validate MODIS GPP estimates. Eight SVs were used to test six hypotheses about the conditions under which MODIS GPP would be most strongly validated. SVs were assessed in terms of the tradeoff between improved relations and reduced number of samples. MODIS seasonal variation and FIA tree density were the two most efficient SVs followed by basic quality checks for each data set. The sequential application of SVs provided an efficient dataset of 17,090 co-located MODIS pixels and FIA plots, that raised the Pearson's correlation coefficient from 0.01 for the complete dataset of 54,969 plots to 0.48 for this screened subset of 17,090 plots. The second objective was addressed by aggregating data over increasing spatial extents so as to not lose plot- and pixel-level information. These data were then analyzed to determine the optimal scale with which to represent the spatial pattern of NPP. The results suggested an optimal scale of 390 km2. At that scale MODIS and FIA were most strongly correlated while maximizing the number of observation. The maps conveyed both local-scale spatial structure from FIA and broad-scale climatic trends from MODIS. The third objective examined whether carbon use efficiency (CUE) was constant or variable in relation to forest types, and to geographic and climatic variables. The results indicated that while CUEs exhibited unclear patterns by forest types, CUEs are variable to other environmental variables. CUEs are most strongly related to the climatic factors of precipitation followed by temperature. More complex and weaker relationships were found for the geographic factors of latitude and altitude, as they reflected a combination of phenomenological driving forces. The results of the three objectives will help us to identify factors that control carbon cycles and to quantify forest productivity. This will help improve our knowledge about how forest primary productivity may change in relation to ongoing climate change.

Remote Sensing of Water Vapor and Thin Cirrus Clouds using MODIS Near-IR Channels

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Kaufman, Yoram J.

2001-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major facility instrument on board the Terra Spacecraft, was successfully launched into space in December of 1999. MODIS has several near-IR channels within and around the 0.94 micrometer water vapor bands for remote sensing of integrated atmospheric water vapor over land and above clouds. MODIS also has a special near-IR channel centered at 1.375-micron with a width of 30 nm for remote sensing of cirrus clouds. In this paper, we describe briefly the physical principles on remote sensing of water vapor and cirrus clouds using these channels. We also present sample water vapor images and cirrus cloud images obtained from MODIS data.

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

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

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi

2014-04-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m -2 yr -1 and total NPP in the range of 318–490more » Tg C yr -1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m -2 yr -1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m -2 yr -1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. Finally, we suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.« less

An automated tool for a daily harmful algal bloom monitoring using MODIS imagery downscaled to 250 meters spatial resolution

NASA Astrophysics Data System (ADS)

El Alem, A.

2016-12-01

Harmful algal bloom (HAB) causes negative impacts to other organisms by producing natural toxins, mechanical damage to other micro-organisms, or simply by degrading waters quality. Contaminated waters could expose several billions of population to serious intoxications problems. Traditionally, HAB monitoring is made with standard methods limited to a restricted network of sampling points. However, rapid evolution of HABs makes it difficult to monitor their variation in time and space, threating then public safety. Daily monitoring is then the best way to control and to mitigate their harmful effect upon population, particularly for sources feeding cities. Recently, an approach for estimating chlorophyll-a (Chl-a) concentration, as a proxy of HAB presence, in inland waters based MODIS imagery downscaled to 250 meters spatial resolution was developed. Statistical evaluation of the developed approach highlighted the accuracy of Chl-a estimate with a R2 = 0.98, a relative RMSE of 15%, a relative BIAS of -2%, and a relative NASH of 0.95. Temporal resolution of MODIS sensor allows then a daily monitoring of HAB spatial distribution for inland waters of more than 2.25 Km2 of surface. Groupe-Hemisphere, a company specialized in environmental and sustainable planning in Quebec, has shown a great interest to the developed approach. Given the complexity of the preprocessing (geometric and atmospheric corrections as well as downscaling spatial resolution) and processing (Chl-a estimate) of images, a standalone application under the MATLAB's GUI environment was developed. The application allows an automated process for all preprocessing and processing steps. Outputs produced by the application for end users, many of whom may be decision makers or policy makers in the public and private sectors, allows a near-real time monitoring of water quality for a more efficient management.

Comparing cropland net primary production estimates from inventory, a satellite-based model, and a process-based model in the Midwest of the United States

USGS Publications Warehouse

Li, Zhengpeng; Liu, Shuguang; Tan, Zhengxi; Bliss, Norman B.; Young, Claudia J.; West, Tristram O.; Ogle, Stephen M.

2014-01-01

Accurately quantifying the spatial and temporal variability of net primary production (NPP) for croplands is essential to understand regional cropland carbon dynamics. We compared three NPP estimates for croplands in the Midwestern United States: inventory-based estimates using crop yield data from the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS); estimates from the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) NPP product; and estimates from the General Ensemble biogeochemical Modeling System (GEMS) process-based model. The three methods estimated mean NPP in the range of 469–687 g C m−2 yr−1and total NPP in the range of 318–490 Tg C yr−1 for croplands in the Midwest in 2007 and 2008. The NPP estimates from crop yield data and the GEMS model showed the mean NPP for croplands was over 650 g C m−2 yr−1 while the MODIS NPP product estimated the mean NPP was less than 500 g C m−2 yr−1. MODIS NPP also showed very different spatial variability of the cropland NPP from the other two methods. We found these differences were mainly caused by the difference in the land cover data and the crop specific information used in the methods. Our study demonstrated that the detailed mapping of the temporal and spatial change of crop species is critical for estimating the spatial and temporal variability of cropland NPP. We suggest that high resolution land cover data with species–specific crop information should be used in satellite-based and process-based models to improve carbon estimates for croplands.

The use of EO Optical data for the Italian Supersites volcanoes monitoring

NASA Astrophysics Data System (ADS)

Silvestri, Malvina

2016-04-01

This work describes the INGV experience in the capability to import many different EO optical data into in house developed systems and to maintain a repository where the acquired data have been stored. These data are used for generating selected products which are functional to face the different volcanic activity phases. Examples on the processing of long time series based EO data of Mt Etna activity and Campi Flegrei observation by using remote sensing techniques and at different spatial resolution data (ASTER - 90mt, AVHRR -1km, MODIS-1km, MSG SEVIRI-3km) are also showed. Both volcanoes belong to Italian Supersites initiative of the geohazard scientific community. In the frame of the EC FP7 MED-SUV project (call FP7 ENV.2012.6.4-2), this work wants to describe the main activities concerning the generation of brightness temperature map from the satellite data acquired in real-time from INGV MEOS Multi-mission Antenna (for MODIS, Moderate Resolution Imaging Spectroradiometer and geostationary satellite data) and AVHRR-TERASCAN (for AVHRR, Advanced Very High Resolution Radiometer data). The advantage of direct download of EO data by means INGV antennas (with particular attention to AVHRR and MODIS) even though low spatial resolution offers the possibility of a systematic data processing having a daily updating of information for prompt response and hazard mitigation. At the same time it has been necessary the use of large archives to inventory and monitor dynamic and dangerous phenomena, like volcanic activity, globally.

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.

Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR.

PubMed

Mobli, Mehdi; Hoch, Jeffrey C

2014-11-01

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR. Copyright © 2014 Elsevier B.V. All rights reserved.

MODIS Observations of Smoke and Fires

NASA Technical Reports Server (NTRS)

Kaufman, Yoram; Ichoku, Charles; Remer, Lorraine; Lau, William K. M. (Technical Monitor)

2002-01-01

The MODIS (Moderate Resolution Imaging Spectroradiometer) instruments collect daily measurements of our planet since early 2000 from the Terra spaceborne polar platform. It has unique channels to observe smoke over land and ocean and to observe fires. Using unsaturated channels at 3.9 micron MODIS detects the fires and estimates the fire radiative energy. Using solar channels in the visible (0.47 and 0.66 micron) and in the mid IR (2.1 micron) MODIS measures the smoke optical thickness distribution and evolution over the land. Seven Channels in the solar spectrum are used to detect the smoke properties and distribution over the oceans. Data from the Aerosol Robotic Network, are used to validate the MODIS observations. The MODIS aerosol data presented in a movie form is used to observe the generation of smoke plumes and their dispersion around the globe. For example a key conclusion is that smoke in particular from Southern Africa can pollute significantly the 'pristine' Southern Hemisphere zonal range of 45'S-60'S, and the Northern Pacific.

Towards a systematic nationwide screening strategy for MODY.

PubMed

Shields, Beverley; Colclough, Kevin

2017-04-01

MODY is an early-onset monogenic form of diabetes. Correctly identifying MODY is of considerable importance as diagnosing the specific genetic subtype can inform the optimal treatment, with many patients being able to discontinue unnecessary insulin treatment. Diagnostic molecular genetic testing to confirm MODY is expensive, so screening strategies are required to identify the most appropriate patients for testing. In this issue of Diabetologia, Johansson and colleagues (DOI 10.1007/s00125-016-4167-1 ) describe a nationwide systematic screening approach to identify individuals with MODY in the paediatric age range. They focused testing on patients negative for both GAD and islet antigen 2 (IA-2) islet autoantibodies, thereby ruling out those with markers of type 1 diabetes, the most common form of diabetes in this age group. This commentary discusses the advantages and limitations of the approach, and the caution required when interpreting variants of uncertain pathogenicity identified from testing whole populations rather than targeting only patients with a strong MODY phenotype.

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.

Evaluation of AIRS, MODIS, and HIRS 11 Micron Brightness Temperature Difference Changes from 2002 through 2006

NASA Technical Reports Server (NTRS)

Broberg, Steven E.; Aumann, Hartmut H.; Gregorich, David T.; Xiong, X.

2006-01-01

In an effort to validate the accuracy and stability of AIRS data at low scene temperatures (200-250 K range), we evaluated brightness temperatures at 11 microns with Aqua MODIS band 31 and HIRS/3 channel 8 for Antarctic granules between September 2002 and May 2006. We found excellent agreement with MODIS (at the 0.2 K level) over the full emperature range in data from early in the Aqua mission. However, in more recent data, starting in April 2005, we found a scene temperature dependence in MODIS-AIRS brightness temperature differences, with a discrepancy of 1- 1.5 K at 200 K. The comparison between AIRS and HIRS/3 (channel 8) on NOAA 16 for the same time period yields excellent agreement. The cause and time dependence of the disagreement with MODIS is under evaluation, but the change was coincident with a change in the MODIS production software from collection 4 to 5.

[Comparison of GIMMS and MODIS normalized vegetation index composite data for Qing-Hai-Tibet Plateau].

PubMed

Du, Jia-Qiang; Shu, Jian-Min; Wang, Yue-Hui; Li, Ying-Chang; Zhang, Lin-Bo; Guo, Yang

2014-02-01

Consistent NDVI time series are basic and prerequisite in long-term monitoring of land surface properties. Advanced very high resolution radiometer (AVHRR) measurements provide the longest records of continuous global satellite measurements sensitive to live green vegetation, and moderate resolution imaging spectroradiometer (MODIS) is more recent typical with high spatial and temporal resolution. Understanding the relationship between the AVHRR-derived NDVI and MODIS NDVI is critical to continued long-term monitoring of ecological resources. NDVI time series acquired by the global inventory modeling and mapping studies (GIMMS) and Terra MODIS were compared over the same time periods from 2000 to 2006 at four scales of Qinghai-Tibet Plateau (whole region, sub-region, biome and pixel) to assess the level of agreement in terms of absolute values and dynamic change by independently assessing the performance of GIMMS and MODIS NDVI and using 495 Landsat samples of 20 km x20 km covering major land cover type. High correlations existed between the two datasets at the four scales, indicating their mostly equal capability of capturing seasonal and monthly phenological variations (mostly at 0. 001 significance level). Simi- larities of the two datasets differed significantly among different vegetation types. The relative low correlation coefficients and large difference of NDVI value between the two datasets were found among dense vegetation types including broadleaf forest and needleleaf forest, yet the correlations were strong and the deviations were small in more homogeneous vegetation types, such as meadow, steppe and crop. 82% of study area was characterized by strong consistency between GIMMS and MODIS NDVI at pixel scale. In the Landsat NDVI vs. GIMMS and MODIS NDVI comparison of absolute values, the MODIS NDVI performed slightly better than GIMMS NDVI, whereas in the comparison of temporal change values, the GIMMS data set performed best. Similar with comparison results of GIMMS and MODIS NDVI, the consistency across the three datasets was clearly different among various vegetation types. In dynamic changes, differences between Landsat and MODIS NDVI were smaller than Landsat NDVI vs. GIMMS NDVI for forest, but Landsat and GIMMS NDVI agreed better for grass and crop. The results suggested that spatial patterns and dynamic trends of GIMMS NDVI were found to be in overall acceptable agreement with MODIS NDVI. It might be feasible to successfully integrate historical GIMMS and more recent MODIS NDVI to provide continuity of NDVI products. The accuracy of merging AVHRR historical data recorded with more modern MODIS NDVI data strongly depends on vegetation type, season and phenological period, and spatial scale. The integration of the two datasets for needleleaf forest, broadleaf forest, and for all vegetation types in the phenological transition periods in spring and autumn should be treated with caution.

Building a symbolic computer algebra toolbox to compute 2D Fourier transforms in polar coordinates

PubMed Central

Dovlo, Edem; Baddour, Natalie

2015-01-01

The development of a symbolic computer algebra toolbox for the computation of two dimensional (2D) Fourier transforms in polar coordinates is presented. Multidimensional Fourier transforms are widely used in image processing, tomographic reconstructions and in fact any application that requires a multidimensional convolution. By examining a function in the frequency domain, additional information and insights may be obtained. The advantages of our method include: • The implementation of the 2D Fourier transform in polar coordinates within the toolbox via the combination of two significantly simpler transforms. • The modular approach along with the idea of lookup tables implemented help avoid the issue of indeterminate results which may occur when attempting to directly evaluate the transform. • The concept also helps prevent unnecessary computation of already known transforms thereby saving memory and processing time. PMID:26150988

Fast data reconstructed method of Fourier transform imaging spectrometer based on multi-core CPU

NASA Astrophysics Data System (ADS)

Yu, Chunchao; Du, Debiao; Xia, Zongze; Song, Li; Zheng, Weijian; Yan, Min; Lei, Zhenggang

2017-10-01

Imaging spectrometer can gain two-dimensional space image and one-dimensional spectrum at the same time, which shows high utility in color and spectral measurements, the true color image synthesis, military reconnaissance and so on. In order to realize the fast reconstructed processing of the Fourier transform imaging spectrometer data, the paper designed the optimization reconstructed algorithm with OpenMP parallel calculating technology, which was further used for the optimization process for the HyperSpectral Imager of `HJ-1' Chinese satellite. The results show that the method based on multi-core parallel computing technology can control the multi-core CPU hardware resources competently and significantly enhance the calculation of the spectrum reconstruction processing efficiency. If the technology is applied to more cores workstation in parallel computing, it will be possible to complete Fourier transform imaging spectrometer real-time data processing with a single computer.

Control of ACAT2 liver expression by HNF4{alpha}: lesson from MODY1 patients.

PubMed

Pramfalk, C; Karlsson, E; Groop, L; Rudel, L L; Angelin, B; Eriksson, M; Parini, P

2009-08-01

ACAT2 is thought to be responsible for cholesteryl ester production in chylomicron and VLDL assembly. Recently, we identified HNF1alpha as an important regulator of the human ACAT2 promoter. Thus, we hypothesized that MODY3 (HNF1alpha gene mutations) and possibly MODY1 (HNF4alpha, upstream regulator of HNF1alpha, gene mutations) subjects may have lower VLDL esterified cholesterol. Serum analysis and lipoprotein separation using size-exclusion chromatography were performed in controls and MODY1 and MODY3 subjects. In vitro analyses included mutagenesis and cotransfections in HuH7 cells. Finally, the relevance in vivo of these findings was tested by ChIP assays in human liver. Whereas patients with MODY3 had normal lipoprotein composition, those with MODY1 had lower levels of VLDL and LDL esterified cholesterol, as well as of VLDL triglyceride. Mutagenesis revealed one important HNF4 binding site in the human ACAT2 promoter. ChIP assays and protein-to-protein interaction studies showed that HNF4alpha, directly or indirectly (via HNF1alpha), can bind to the ACAT2 promoter. We identified HNF4alpha as an important regulator of the hepatocyte-specific expression of the human ACAT2 promoter. Our results suggest that the lower levels of esterified cholesterol in VLDL- and LDL-particles in patients with MODY1 may-at least in part-be attributable to lower ACAT2 activity in these patients.

Application and Comparison of the MODIS-Derived Enhanced Vegetation Index to VIIRS, Landsat 5 TM and Landsat 8 OLI Platforms: A Case Study in the Arid Colorado River Delta, Mexico.

PubMed

Jarchow, Christopher J; Didan, Kamel; Barreto-Muñoz, Armando; Nagler, Pamela L; Glenn, Edward P

2018-05-13

The Enhanced Vegetation Index (EVI) is a key Earth science parameter used to assess vegetation, originally developed and calibrated for the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. With the impending decommissioning of the MODIS sensors by the year 2020/2022, alternative platforms will need to be used to estimate EVI. We compared Landsat 5 (2000⁻2011), 8 (2013⁻2016) and the Visible Infrared Imaging Radiometer Suite (VIIRS; 2013⁻2016) to MODIS EVI (2000⁻2016) over a 420,083-ha area of the arid lower Colorado River Delta in Mexico. Over large areas with mixed land cover or agricultural fields, we found high correspondence between Landsat and MODIS EVI (R² = 0.93 for the entire area studied and 0.97 for agricultural fields), but the relationship was weak over bare soil (R² = 0.27) and riparian vegetation (R² = 0.48). The correlation between MODIS and Landsat EVI was higher over large, homogeneous areas and was generally lower in narrow riparian areas. VIIRS and MODIS EVI were highly similar (R² = 0.99 for the entire area studied) and did not show the same decrease in performance in smaller, narrower regions as Landsat. Landsat and VIIRS provide EVI estimates of similar quality and characteristics to MODIS, but scale, seasonality and land cover type(s) should be considered before implementing Landsat EVI in a particular area.

Maturity Onset Diabetes of the Young (MODY) in Tunisia: Low frequencies of GCK and HNF1A mutations.

PubMed

Ben Khelifa, S; Martinez, R; Dandana, A; Khochtali, I; Ferchichi, S; Castaño, L

2018-04-20

Maturity Onset Diabetes of the Young (MODY) is a monogenic form of diabetes characterized by autosomal dominant inheritance, an early clinical onset and a primary defect in β-cell function. Mutations in the GCK and HNF1A genes are the most common cause of MODY among Caucasians. The etiology of MODY in Tunisia stills a challenge for researchers. The aim of this study was to screen for mutations in GCK, HNF1A, HNF4A and INS genes in North African Tunisians subjects, in whom the clinical profile was very suggestive of MODY. A total of 23 unrelated patients, with clinical presentation of MODY were tested for mutations in GCK, HNF1A, HNF4A and INS genes, using Denaturing High Performance Liquid Chromatography (DHPLC), Multiplex Ligation-depend Probe Amplification (MLPA) and sequencing analysis. We identified the previously reported mutation c-169C > T in one patient as well as a new mutation c-457C > T in two unrelated patients. No mutations were detected in the HNF1A and INS genes. Despite restrictive clinical criteria used for selecting patients in this study, the most common genes known for MODY do not explain the majority of cases in Tunisians. This suggests that there are others candidate or unidentified genes contributing to the etiology of MODY in Tunisians families. Copyright © 2018 Elsevier B.V. All rights reserved.

Terra and Aqua MODIS Thermal Emissive Bands On-Orbit Calibration and Performance

NASA Technical Reports Server (NTRS)

Xiong, Xiaoxiong; Wu, Aisheng; Wenny, Brian N.; Madhavan, Sriharsha; Wang, Zhipeng; Li, Yonghong; Chen, Na; Barnes, William L.; Salomonson, Vincent V.

2015-01-01

Since launch, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua spacecraft have operated successfully for more than 14 and 12 years, respectively. A key instrument for National Aeronautics and Space Administration Earth Observing System missions, MODIS was designed to make continuous observations for studies of Earth's land, ocean, and atmospheric properties and to extend existing data records from heritage Earth observing sensors. The 16 thermal emissive bands (TEBs) (3.75-14.24 micrometers) are calibrated on orbit using a temperature controlled blackbody (BB). Both Terra and Aqua MODIS BBs have displayed minimal drift over the mission lifetime, and the seasonal variations of the BB temperature are extremely small in Aqua MODIS. The long-term gain and noise equivalent difference in temperature performance of the 160 TEB detectors on both MODIS instruments have been well behaved and generally very stable. Small but noticeable variations of Aqua MODIS bands 33-36 (13.34-14.24 micrometer) response in recent years are primarily due to loss of temperature control margin of its passive cryoradiative cooler. As a result, fixed calibration coefficients, previously used by bands when the BB temperature is above their saturation temperatures, are replaced by the focal-plane-temperature-dependent calibration coefficients. This paper presents an overview of the MODIS TEB calibration, the on-orbit performance, and the challenging issues likely to impact the instruments as they continue operating well past their designed lifetime of six years.

ASSESSMENT OF MODIS LAI (W4) IN LOBLOLLY PINE (P. TAEDA) FOREST TYPE, APPOMATTOX, VIRGINIA

EPA Science Inventory

The United States Environmental Protection Agency initiated MODIS MODI5A2LAI validation research (2002) in the evergreen needle leaf biome, as defined in the MOD12 classification, in a regional study located in the southeastern United States.

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.

INFFTM: Fast evaluation of 3d Fourier series in MATLAB with an application to quantum vortex reconnections

NASA Astrophysics Data System (ADS)

Caliari, Marco; Zuccher, Simone

2017-04-01

Although Fourier series approximation is ubiquitous in computational physics owing to the Fast Fourier Transform (FFT) algorithm, efficient techniques for the fast evaluation of a three-dimensional truncated Fourier series at a set of arbitrary points are quite rare, especially in MATLAB language. Here we employ the Nonequispaced Fast Fourier Transform (NFFT, by J. Keiner, S. Kunis, and D. Potts), a C library designed for this purpose, and provide a Matlab® and GNU Octave interface that makes NFFT easily available to the Numerical Analysis community. We test the effectiveness of our package in the framework of quantum vortex reconnections, where pseudospectral Fourier methods are commonly used and local high resolution is required in the post-processing stage. We show that the efficient evaluation of a truncated Fourier series at arbitrary points provides excellent results at a computational cost much smaller than carrying out a numerical simulation of the problem on a sufficiently fine regular grid that can reproduce comparable details of the reconnecting vortices.

Estimation of photosynthetic capacity using MODIS polarization: 1988 proposal to NASA Headquarters

NASA Technical Reports Server (NTRS)

Vanderbilt, Vern C.

1992-01-01

The remote sensing community has clearly identified the utility of NDVI (normalized difference vegetation index) and SR (simple ratio) and other vegetation indices for estimating such metrics of landscape ecology as green foliar biomass, photosynthetic capacity, and net primary production. Both theoretical and empirical investigations have established cause and effect relationships between the photosynthetic process in plant canopies and these combinations of remotely sensed data. Yet it has also been established that the relationships exhibit considerable variability that appears to be ecosystem-dependent and may represent a source of ecologically important information. The overall hypothesis of this proposal is that the ecosystem-dependent variability in the various vegetation indices is in part attributable to the effects of specular reflection. The polarization channels on MODIS provide the potential to estimate this specularly reflected light and allow the modification of the vegetation indices to better measure the photosynthetic process in plant canopies. In addition, these polarization channels potentially provide additional ecologically important information about the plant canopy.

Creation of the BMA ensemble for SST using a parallel processing technique

NASA Astrophysics Data System (ADS)

Kim, Kwangjin; Lee, Yang Won

2013-10-01

Despite the same purpose, each satellite product has different value because of its inescapable uncertainty. Also the satellite products have been calculated for a long time, and the kinds of the products are various and enormous. So the efforts for reducing the uncertainty and dealing with enormous data will be necessary. In this paper, we create an ensemble Sea Surface Temperature (SST) using MODIS Aqua, MODIS Terra and COMS (Communication Ocean and Meteorological Satellite). We used Bayesian Model Averaging (BMA) as ensemble method. The principle of the BMA is synthesizing the conditional probability density function (PDF) using posterior probability as weight. The posterior probability is estimated using EM algorithm. The BMA PDF is obtained by weighted average. As the result, the ensemble SST showed the lowest RMSE and MAE, which proves the applicability of BMA for satellite data ensemble. As future work, parallel processing techniques using Hadoop framework will be adopted for more efficient computation of very big satellite data.

[MODIS Investigation

NASA Technical Reports Server (NTRS)

Abbott, Mark R.

1996-01-01

Our first activity is based on delivery of code to Bob Evans (University of Miami) for integration and eventual delivery to the MODIS Science Data Support Team. As we noted in our previous semi-annual report, coding required the development and analysis of an end-to-end model of fluorescence line height (FLH) errors and sensitivity. This model is described in a paper in press in Remote Sensing of the Environment. Once the code was delivered to Miami, we continue to use this error analysis to evaluate proposed changes in MODIS sensor specifications and performance. Simply evaluating such changes on a band by band basis may obscure the true impacts of changes in sensor performance that are manifested in the complete algorithm. This is especially true with FLH that is sensitive to band placement and width. The error model will be used by Howard Gordon (Miami) to evaluate the effects of absorbing aerosols on the FLH algorithm performance. Presently, FLH relies only on simple corrections for atmospheric effects (viewing geometry, Rayleigh scattering) without correcting for aerosols. Our analysis suggests that aerosols should have a small impact relative to changes in the quantum yield of fluorescence in phytoplankton. However, the effect of absorbing aerosol is a new process and will be evaluated by Gordon.

Reduction of Aerosol Absorption in Beijing Since 2007 from MODIS and AERONET

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Smirnov, A.; Holben, B.; Chin, M.; Streets, D. G.; Lu, Z.; Kahn, R.; Slutsker, I.; Laszlo, I.; Kondragunta, S.;

Estimating Irrigation Water Requirements using MODIS Vegetation Indices and Inverse Biophysical Modeling

NASA Technical Reports Server (NTRS)

Imhoff, Marc L.; Bounoua, Lahouari; Harriss, Robert; Harriss, Robert; Wells, Gordon; Glantz, Michael; Dukhovny, Victor A.; Orlovsky, Leah

2007-01-01

An inverse process approach using satellite-driven (MODIS) biophysical modeling was used to quantitatively assess water resource demand in semi-arid and arid agricultural lands by comparing the carbon and water flux modeled under both equilibrium (in balance with prevailing climate) and non-equilibrium (irrigated) conditions. Since satellite observations of irrigated areas show higher leaf area indices (LAI) than is supportable by local precipitation, we postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. For an observation year we used MODIS vegetation indices, local climate data, and the SiB2 photosynthesis-conductance model to examine the relationship between climate and the water stress function for a given grid-cell and observed leaf area. To estimate the minimum amount of supplemental water required for an observed cell, we added enough precipitation to the prevailing climatology at each time step to minimize the water stress function and bring the soil to field capacity. The experiment was conducted on irrigated lands on the U.S. Mexico border and Central Asia and compared to estimates of irrigation water used.

The Snow Data System at NASA JPL

NASA Astrophysics Data System (ADS)

Laidlaw, R.; Painter, T. H.; Mattmann, C. A.; Ramirez, P.; Brodzik, M. J.; Rittger, K.; Bormann, K. J.; Burgess, A. B.; Zimdars, P.; McGibbney, L. J.; Goodale, C. E.; Joyce, M.

2015-12-01

The Snow Data System at NASA JPL includes a data processing pipeline built with open source software, Apache 'Object Oriented Data Technology' (OODT). It produces a variety of data products using inputs from satellites such as MODIS, VIIRS and Landsat. Processing is carried out in parallel across a high-powered computing cluster. Algorithms such as 'Snow Covered Area and Grain-size' (SCAG) and 'Dust Radiative Forcing in Snow' (DRFS) are applied to satellite inputs to produce output images that are used by many scientists and institutions around the world. This poster will describe the Snow Data System, its outputs and their uses and applications, along with recent advancements to the system and plans for the future. Advancements for 2015 include automated daily processing of historic MODIS data for SCAG (MODSCAG) and DRFS (MODDRFS), automation of SCAG processing for VIIRS satellite inputs (VIIRSCAG) and an updated version of SCAG for Landsat Thematic Mapper inputs (TMSCAG) that takes advantage of Graphics Processing Units (GPUs) for faster processing speeds. The pipeline has been upgraded to use the latest version of OODT and its workflows have been streamlined to enable computer operators to process data on demand. Additional products have been added, such as rolling 8-day composites of MODSCAG data, a new version of the MODSCAG 'annual minimum ice and snow extent' (MODICE) product, and recoded MODSCAG data for the 'Satellite Snow Product Intercomparison and Evaluation Experiment' (SnowPEx) project.

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.

High-Resolution Specification of the Land and Ocean Surface for Improving Regional Mesoscale Model Predictions

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Lazarus, Steven M.; Splitt, Michael E.; Crosson, William L.; Lapenta, William M.; Jedlovec, Gary J.; Peters-Lidard, Christa D.

2008-01-01

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many meteorological processes. High-resolution, accurate representations of surface properties such as sea-surface temperature (SST), soil temperature and moisture content, ground fluxes, and vegetation are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of sensible weather. The NASA Short-term Prediction Research and Transition (SPoRT) Center has been conducting separate studies to examine the impacts of high-resolution land-surface initialization data from the Goddard Space Flight Center Land Information System (LIS) on subsequent WRF forecasts, as well as the influence of initializing WRF with SST composites derived from the MODIS instrument. This current project addresses the combined impacts of using high-resolution lower boundary data over both land (LIS data) and water (MODIS SSTs) on the subsequent daily WRF forecasts over Florida during May 2004. For this experiment, the WRF model is configured to run on a nested domain with 9- km and 3-kin grid spacing, centered on the Florida peninsula and adjacent coastal waters of the Gulf of Mexico and Atlantic Ocean. A control configuration of WRF is established to take all initial condition data from the NCEP Eta model. Meanwhile, two WRF experimental runs are configured to use high-resolution initialization data from (1) LIS land-surface data only, and (2) a combination of LIS data and high-resolution MODIS SST composites. The experiment involves running 24-hour simulations of the control WRF configuration, the MS-initialized WRF, and the LIS+MODIS-initialized WRF daily for the entire month of May 2004. All atmospheric data for initial and boundary conditions for the Control, LIS, and LIS+MODIS runs come from the NCEP Eta model on a 40-km grid. Verification statistics are generated at land surface observation sites and buoys, and the impacts of the high-resolution lower boundary data on the development and evolution of mesoscale circulations such as sea and land breezes are examined, This paper will present the results of these WRF modeling experiments using LIS and MODIS lower boundary datasets over the Florida peninsula during May 2004.

The Q Continuum: Encounter with the Cloud Mask

NASA Astrophysics Data System (ADS)

Ackerman, S. A.; Frey, R.; Holz, R.; Philips, C.; Dutcher, S.

2017-12-01

We are developing a common cloud mask for MODIS and VIIRS observations, referred to as the MODIS VIIRS Continuity Mask (MVCM). Our focus is on extending the MODIS-heritage cloud detection approach in order to generate appropriate climate data records for clouds and climate studies. The MVCM is based on heritage from the MODIS cloud mask (MOD35 and MYD35) and employs a series of tests on MODIS reflectances and brightness temperatures. Cloud detection is based on contrasts (i.e., cloud versus background surface) at pixel resolution. The MVCM follows the same approach. These cloud masks use multiple cloud detection tests to indicate the confidence level that the observation is of a clear-sky scene. The outcome of a test ranges from 0 (cloudy) to 1 (clear-sky scene). Because of overlap in the sensitivities of the various spectral tests to the type of cloud, each test is considered in one of several groups. The final cloud mask is determined from the product of the minimum confidence of each group and is referred to as the Q value as defined in Ackerman et al (1998). In MOD35 and MYD35 processing, the Q value is not output, rather predetermined Q values determine the result: If Q ≥ .99 the scene is clear; .95 ≤ Q < .99 the pixel is probably a clear scene, .66 ≤ Q < .95 is probably cloudy and Q < .66 is cloudy. Thus representing Q discretely and not as a continuum. For the MVCM, the numerical value of the Q is output along with the classification of clear, probably clear, probably cloudy, and cloudy. Through comparisons with collocated CALIOP and MODIS observations, we will assess the categorization of the Q values as a function of scene type ). While validation studies have indicated the utility and statistical correctness of the cloud mask approach, the algorithm does not possess immeasurable power and perfection. This comparison will assess the time and space dependence of Q and assure that the laws of physics are followed, at least according to normal human notions. Using CALIOP as representing truth, a receiver operating characteristic curve (ROC) will be analyzed to determine the optimum Q for various scenes and seasons, thus providing a continuum of discriminating thresholds.

Acceleration of integral imaging based incoherent Fourier hologram capture using graphic processing unit.

PubMed

Jeong, Kyeong-Min; Kim, Hee-Seung; Hong, Sung-In; Lee, Sung-Keun; Jo, Na-Young; Kim, Yong-Soo; Lim, Hong-Gi; Park, Jae-Hyeung

2012-10-08

Speed enhancement of integral imaging based incoherent Fourier hologram capture using a graphic processing unit is reported. Integral imaging based method enables exact hologram capture of real-existing three-dimensional objects under regular incoherent illumination. In our implementation, we apply parallel computation scheme using the graphic processing unit, accelerating the processing speed. Using enhanced speed of hologram capture, we also implement a pseudo real-time hologram capture and optical reconstruction system. The overall operation speed is measured to be 1 frame per second.