Science.gov

Sample records for avhrr seasonal land

  1. BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

    NASA Technical Reports Server (NTRS)

    Steyaert, Lou; Hall, Forrest G.; Newcomer, Jeffrey A. (Editor); Knapp, David E. (Editor); Loveland, Thomas R.; Smith, David E. (Technical Monitor)

    2000-01-01

    features such as fens, bogs, and small water bodies. Field observations and comparisons with Landsat Thematic Mapper (TM) suggest a minimum effective resolution of these land cover classes in the range of three to four kilometers, in part, because of the daily to monthly compositing process. In general, potential accuracy limitations are mitigated by the use of conservative parameterization rules such as aggregation of predominant land cover classes within minimum horizontal grid cell sizes of ten kilometers. The AFM-12 one-kilometer AVHRR seasonal land cover classification data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

  2. AVHRR channel selection for land cover classification

    USGS Publications Warehouse

    Maxwell, S.K.; Hoffer, R.M.; Chapman, P.L.

    2002-01-01

    Mapping land cover of large regions often requires processing of satellite images collected from several time periods at many spectral wavelength channels. However, manipulating and processing large amounts of image data increases the complexity and time, and hence the cost, that it takes to produce a land cover map. Very few studies have evaluated the importance of individual Advanced Very High Resolution Radiometer (AVHRR) channels for discriminating cover types, especially the thermal channels (channels 3, 4 and 5). Studies rarely perform a multi-year analysis to determine the impact of inter-annual variability on the classification results. We evaluated 5 years of AVHRR data using combinations of the original AVHRR spectral channels (1-5) to determine which channels are most important for cover type discrimination, yet stabilize inter-annual variability. Particular attention was placed on the channels in the thermal portion of the spectrum. Fourteen cover types over the entire state of Colorado were evaluated using a supervised classification approach on all two-, three-, four- and five-channel combinations for seven AVHRR biweekly composite datasets covering the entire growing season for each of 5 years. Results show that all three of the major portions of the electromagnetic spectrum represented by the AVHRR sensor are required to discriminate cover types effectively and stabilize inter-annual variability. Of the two-channel combinations, channels 1 (red visible) and 2 (near-infrared) had, by far, the highest average overall accuracy (72.2%), yet the inter-annual classification accuracies were highly variable. Including a thermal channel (channel 4) significantly increased the average overall classification accuracy by 5.5% and stabilized inter-annual variability. Each of the thermal channels gave similar classification accuracies; however, because of the problems in consistently interpreting channel 3 data, either channel 4 or 5 was found to be a more

  3. AVHRR composite period selection for land cover classification

    USGS Publications Warehouse

    Maxwell, S.K.; Hoffer, R.M.; Chapman, P.L.

    2002-01-01

    Multitemporal satellite image datasets provide valuable information on the phenological characteristics of vegetation, thereby significantly increasing the accuracy of cover type classifications compared to single date classifications. However, the processing of these datasets can become very complex when dealing with multitemporal data combined with multispectral data. Advanced Very High Resolution Radiometer (AVHRR) biweekly composite data are commonly used to classify land cover over large regions. Selecting a subset of these biweekly composite periods may be required to reduce the complexity and cost of land cover mapping. The objective of our research was to evaluate the effect of reducing the number of composite periods and altering the spacing of those composite periods on classification accuracy. Because inter-annual variability can have a major impact on classification results, 5 years of AVHRR data were evaluated. AVHRR biweekly composite images for spectral channels 1-4 (visible, near-infrared and two thermal bands) covering the entire growing season were used to classify 14 cover types over the entire state of Colorado for each of five different years. A supervised classification method was applied to maintain consistent procedures for each case tested. Results indicate that the number of composite periods can be halved-reduced from 14 composite dates to seven composite dates-without significantly reducing overall classification accuracy (80.4% Kappa accuracy for the 14-composite data-set as compared to 80.0% for a seven-composite dataset). At least seven composite periods were required to ensure the classification accuracy was not affected by inter-annual variability due to climate fluctuations. Concentrating more composites near the beginning and end of the growing season, as compared to using evenly spaced time periods, consistently produced slightly higher classification values over the 5 years tested (average Kappa) of 80.3% for the heavy early

  4. Mapping the global land surface using 1 km AVHRR data

    USGS Publications Warehouse

    Lauer, D.T.; Eidenshink, J.C.

    1998-01-01

    The scientific requirements for mapping the global land surface using 1 km advanced very high resolution radiometer (AVHRR) data have been set forth by the U.S. Global Change Research Program; the International Geosphere Biosphere Programme (IGBP); The United Nations; the National Oceanic and Atmospheric Administration (NOAA); the Committee on Earth Observations Satellites; and the National Aeronautics and Space Administration (NASA) mission to planet Earth (MTPE) program. Mapping the global land surface using 1 km AVHRR data is an international effort to acquire, archive, process, and distribute 1 km AVHRR data to meet the needs of the international science community. A network of AVHRR receiving stations, along with data recorded by NOAA, has been acquiring daily global land coverage since April 1, 1992. A data set of over 70,000 AVHRR images is archived and distributed by the United States Geological Survey (USGS) EROS Data Center, and the European Space Agency. Under the guidance of the IGBP, processing standards have been developed for calibration, atmospheric correction, geometric registration, and the production of global 10-day maximum normalized difference vegetation index (NDVI) composites. The major uses of the composites are for the study of surface vegetation condition, mapping land cover, and deriving biophysical characteristics of terrestrial ecosystems. A time-series of 54 10-day global vegetation index composites for the period of April 1, 1992 through September 1993 has been produced. The production of a time-series of 33 10-day global vegetation index composites using NOAA-14 data for the period of February 1, 1995 through December 31, 1995 is underway. The data products are available from the USGS, in cooperation with NASA's MTPE program and other international organizations.

  5. Estimation of land surface temperature over the Tibetan Plateau using AVHRR and MODIS data

    NASA Astrophysics Data System (ADS)

    Zhong, Lei; Ma, Yaoming; Su, Zhongbo; Salama, Mhd. Suhyb

    2010-09-01

    Estimation of large-scale land surface temperature from satellite images is of great importance for the study of climate change. This is especially true for the most challenging areas, such as the Tibetan Plateau (TP). In this paper, two split window algorithms (SWAs), one for the NOAA’s Advanced Very High Resolution Radiometer (AVHRR), and the other for the Moderate Resolution Imaging Spectroradiometer (MODIS), were applied to retrieve land surface temperature (LST) over the TP simultaneously. AVHRR and MODIS data from 17 January, 14 April, 23 July, and 16 October 2003 were selected as the cases for winter, spring, summer, and autumn, respectively. Firstly, two key parameters (emissivity and water vapor content) were calculated at the pixel scale. Then, the derived LST was compared with in situ measurements from the Coordinated Enhanced Observing Period (CEOP) Asia-Australia Monsoon Project (CAMP) on the TP (CAMP/Tibet) area. They were in good accordance with each other, with an average percentage error (PE) of 10.5% for AVHRR data and 8.3% for MODIS data, meaning the adopted SWAs were applicable in the TP area. The derived LST also showed a wide range and a clear seasonal difference. The results from AVHRR were also in agreement with MODIS, with the latter usually displaying a higher level of accuracy.

  6. Processing techniques for global land 1-km AVHRR data

    USGS Publications Warehouse

    Eidenshink, Jeffery C.; Steinwand, Daniel R.; Wivell, Charles E.; Hollaren, Douglas M.; Meyer, David

    1993-01-01

    The U.S. Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center (EDC) in cooperation with several international science organizations has developed techniques for processing daily Advanced Very High Resolution Radiometer (AVHRR) 1-km data of the entire global land surface. These techniques include orbital stitching, geometric rectification, radiometric calibration, and atmospheric correction. An orbital stitching algorithm was developed to combine consecutive observations acquired along an orbit by ground receiving stations into contiguous half-orbital segments. The geometric rectification process uses an AVHRR satellite model that contains modules for forward mapping, forward terrain correction, and inverse mapping with terrain correction. The correction is accomplished by using the hydrologic features coastlines and lakes from the Digital Chart of the World. These features are rasterized into the satellite projection and are matched to the AVHRR imagery using binary edge correlation techniques. The resulting coefficients are related to six attitude correction parameters: roll, roll rate, pitch, pitch rate, yaw, and altitude. The image can then be precision corrected to a variety of map projections and user-selected image frames. Because the AVHRR lacks onboard calibration for the optical wavelengths, a series of time-variant calibration coefficients derived from vicarious calibration methods and are used to model the degradation profile of the instruments. Reducing atmospheric effects on AVHRR data is important. A method has been develop that will remove the effects of molecular scattering and absorption from clear sky observations, using climatological measurements of ozone. Other methods to remove the effects of water vapor and aerosols are being investigated.

  7. An evaluation of the global 1-km AVHRR land dataset

    USGS Publications Warehouse

    Teillet, P.M.; El Saleous, N.; Hansen, M.C.; Eidenshink, Jeffery C.; Justice, C.O.; Townshend, J.R.G.

    2000-01-01

    This paper summarizes the steps taken in the generation of the global 1-km AVHRR land dataset, and it documents an evaluation of the data product with respect to the original specifications and its usefulness in research and applications to date. The evaluation addresses data characterization, processing, compositing and handling issues. Examples of the main scientific outputs are presented and options for improved processing are outlined and prioritized. The dataset has made a significant contribution, and a strong recommendation is made for its reprocessing and continuation to produce a long-term record for global change research.

  8. Using NOAA-AVHRR estimates of land surface temperature for regional agrometeorogical modelling

    NASA Astrophysics Data System (ADS)

    de Wit, A. J. W.; Boogaard, H. L.; van Diepen, C. A.

    2004-09-01

    Agrometeorological crop simulation models are used increasingly in spatial applications like regional crop monitoring and yield forecasting. The spatial application of these models involves gathering spatially representative values of meteorological input variables (temperature, radiation and precipitation). This is usually accomplished by interpolating meteorological variables measured at point locations. This paper explores the use of advanced very high resolution radiometer (AVHRR)-derived surface temperature as a replacement for interpolated maximum air temperature in a spatial crop monitoring and yield forecasting system. A 2-year set of daily National Oceanic And Atmospheric Administration (NOAA)-AVHRR images over western Europe was used to derive estimates of daily surface temperature aggregated over 50 km × 50 km gridcells, a land cover database was used to select only pixels that were classified as 'arable land'. On days that did not yield data due to cloud cover, the monthly average surface temperature was substituted. The AVHRR-derived surface temperature is usually higher than the maximum air temperature measured at a weather station. To account for this difference, an empirical model was used that relates surface temperature to maximum air temperature. The model parameters were obtained using calibration with the maximum air temperature measured at five weather stations. Next, it was applied to the entire AVHRR data set in order to convert AVHRR surface temperature into a simulated maximum air temperature. Finally, a case study was carried out by using the WOrld FOod Studies (WOFOST) crop model to simulate growth of winter-wheat and sunflower for Spain using both the simulated maximum air temperature and the interpolated maximum air temperature from weather stations. Our results demonstrate that the spatial patterns of the yearly temperature sums over Spain are similar for both sources of temperature. Therefore, it can be concluded that the AVHRR

  9. Estimation of Land Surface Temperature from 1-km AVHRR data

    NASA Astrophysics Data System (ADS)

    Frey, Corinne

    2016-04-01

    In order to re-process DLRs 1km AVHRR data archive to different geophysical and descriptive parameters of the land surface and the atmosphere, a series of scientific data processors are being developed in the framework of the TIMELINE project. The archive of DLR ranges back to the 80ies. One of the data processors is SurfTemp, which processes L2 LST and emissivity datasets from AVHRR L1b data. The development of the data processor included the selection of statistical procedures suitable for time series processing, including four mono-window and six split window algorithms. For almost all of these algorithms, new constants were generated, which better account for different atmospheric and geometric acquisition situations. The selection of optimal algorithms for SurfTemp is based on a round robin approach, in which the selected mono-window and split window algorithms are tested on the basis of a large number of TOA radiance/LST pairs, which were generated using a radiative transfer model and the SeeBorV5 profile database. The original LSTs are thereby compared to the LSTs derived from the TOA radiances using the mono- and split window algorithms. The algorithm comparison includes measures of precision, as well as the sensitivity of a method to the accuracy of its input data. The results of the round robin are presented, as well as the implementation of selected algorithms into SurfTemp. Further, first cross-validation results between the AVHRR LST and MODIS LST are shown.

  10. Global discrimination of land cover types from metrics derived from AVHRR pathfinder data

    SciTech Connect

    DeFries, R.; Hansen, M.; Townshend, J.

    1995-12-01

    Global data sets of land cover are a significant requirement for global biogeochemical and climate models. Remotely sensed satellite data is an increasingly attractive source for deriving these data sets due to the resulting internal consistency, reproducibility, and coverage in locations where ground knowledge is sparse. Seasonal changes in the greenness of vegetation, described in remotely sensed data as changes in the normalized difference vegetation index (NDVI) throughout the year, have been the basis for discriminating between cover types in previous attempts to derive land cover from AVHRR data at global and continental scales. This study examines the use of metrics derived from the NDVI temporal profile, as well as metrics derived from observations in red, infrared, and thermal bands, to improve discrimination between 12 cover types on a global scale. According to separability measures calculated from Bhattacharya distances, average separabilities improved by using 12 of the 16 metrics tested (1.97) compared to separabilities using 12 monthly NDVI values alone (1.88). Overall, the most robust metrics for discriminating between cover types were: mean NDVI, maximum NDVI, NDVI amplitude, AVHRR Band 2 (near-infrared reflectance) and Band 1 (red reflectance) corresponding to the time of maximum NDVI, and maximum land surface temperature. Deciduous and evergreen vegetation can be distinguished by mean NDVI, maximum NDVI, NDVI amplitude, and maximum land surface temperature. Needleleaf and broadleaf vegetation can be distinguished by either mean NDVI and NDVI amplitude or maximum NDVI and NDVI amplitude.

  11. Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data

    USGS Publications Warehouse

    Loveland, T.R.; Reed, B.C.; Brown, J.F.; Ohlen, D.O.; Zhu, Z.; Yang, L.; Merchant, J.W.

    2000-01-01

    Researchers from the U.S. Geological Survey, University of Nebraska-Lincoln and the European Commission's Joint Research Centre, Ispra, Italy produced a 1 km resolution global land cover characteristics database for use in a wide range of continental- to global-scale environmental studies. This database provides a unique view of the broad patterns of the biogeographical and ecoclimatic diversity of the global land surface, and presents a detailed interpretation of the extent of human development. The project was carried out as an International Geosphere-Biosphere Programme, Data and Information Systems (IGBP-DIS) initiative. The IGBP DISCover global land cover product is an integral component of the global land cover database. DISCover includes 17 general land cover classes defined to meet the needs of IGBP core science projects. A formal accuracy assessment of the DISCover data layer will be completed in 1998. The 1 km global land cover database was developed through a continent-by-continent unsupervised classification of 1 km monthly Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993. Extensive post-classification stratification was necessary to resolve spectral/temporal confusion between disparate land cover types. The complete global database consists of 961 seasonal land cover regions that capture patterns of land cover, seasonality and relative primary productivity. The seasonal land cover regions were aggregated to produce seven separate land cover data sets used for global environmental modelling and assessment. The data sets include IGBP DISCover, U.S. Geological Survey Anderson System, Simple Biosphere Model, Simple Biosphere Model 2, Biosphere-Atmosphere Transfer Scheme, Olson Ecosystems and Running Global Remote Sensing Land Cover. The database also includes all digital sources that were used in the classification. The complete database can be sourced from the website: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html.

  12. The seasonality of AVHRR data of temperate coniferous forests - Relationship with leaf area index

    NASA Technical Reports Server (NTRS)

    Spanner, Michael A.; Pierce, Lars L.; Running, Steven W.; Peterson, David L.

    1990-01-01

    The relationship between the advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) and coniferous forest leaf area index (LAI) over the western United States is examined. AVHRR data from the NOAA-9 satellite were acquired of the western U.S. from March 1986 to November 1987 and monthly maximum value composites of AVHRR NDVI were calculated for 19 coniferous forest stands in Oregon, Washington, Montana, and California. It is concluded that the relationships under investigation vary according to seasonal changes in surface reflectance based on key biotic and abiotic controls including phenological changes in LAI caused by seasonal temperature and precipitation variations, the proportions of surface cover types contributing to the overall reflectance, and effects resulting from large variations in the solar zenith angle.

  13. 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; Roy, David; Ju, Junchang; Schaaf, Crystal; Liu, Jicheng; Privette, Jeffrey; Pincheiro, Ana

    2007-01-01

    The goal of NASA's Land Long Term Iiata Record (LTDR) project is to produce a consistent long term data set from the AVHRR and MODIS instruments for land climate studies. The project will create daily surface reflectance and normalized difference vegetation index (NDVI) products at a resolution of 0.05 deg., which is identical to the Climate Modeling Grid (CMG) used for MODIS products from EOS Terra and Aqua. Higher order products such as burned area, land surface temperature, albedo, bidirectional reflectance distribution function (BRDF) correction, leaf area index (LAI), and fraction of photosyntheticalIy active radiation absorbed by vegetation (fPAR), will be created. The LTDR project will reprocess Global Area Coverage (GAC) data from AVHRR sensors onboard NOAA satellites by applying the preprocessing improvements identified in the AVHRR Pathfinder Il project and atmospheric and BRDF corrections used in MODIS processing. The preprocessing improvements include radiometric in-flight vicarious calibration for the visible and near infrared channels and inverse navigation to relate an Earth location to each sensor instantaneous field of view (IFOV). Atmospheric corrections for Rayleigh scattering, ozone, and water vapor are undertaken, with aerosol correction being implemented. The LTDR also produces a surface reflectance product for channel 3 (3.75 micrometers). Quality assessment (QA) is an integral part of the LTDR production system, which is monitoring temporal trands in the AVHRR products using time-series approaches developed for MODIS land product quality assessment. The land surface reflectance products have been evaluated at AERONET sites. The AVHRR data record from LTDR is also being compared to products from the PAL (Pathfinder AVHRR Land) and GIMMS (Global Inventory Modeling and Mapping Studies) systems to assess the relative merits of this reprocessing vis-a-vis these existing data products. The LTDR products and associated information can be found at

  14. Validation of the modified Becker's split-window approach for retrieving land surface temperature from AVHRR

    NASA Astrophysics Data System (ADS)

    Quan, Weijun; Chen, Hongbin; Han, Xiuzhen; Ma, Zhiqiang

    2015-10-01

    To further verify the modified Becker's split-window approach for retrieving land surface temperature (LST) from long-term Advanced Very High Resolution Radiometer (AVHRR) data, a cross-validation and a radiance-based (R-based) validation are performed and examined in this paper. In the cross-validation, 3481 LST data pairs are extracted from the AVHRR LST product retrieved with the modified Becker's approach and compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST product (MYD11A1) for the period 2002-2008, relative to the positions of 548 weather stations in China. The results show that in most cases, the AVHRR LST values are higher than the MYD11A1. When the AVHRR LSTs are adjusted with a linear regression, the values are close to the MYD11A1, showing a good linear relationship between the two datasets ( R 2 = 0.91). In the R-based validation, comparison is made between AVHRR LST retrieved from the modified Becker's approach and the inversed LST from the Moderate Resolution Transmittance Model (MODTRAN) consolidated with observed temperature and humidity profiles at four radiosonde stations. The results show that the retrieved AVHRR LST deviates from the MODTRAN inversed LST by-1.3 (-2.5) K when the total water vapor amount is less (larger) than 20 mm. This provides useful hints for further improvement of the LST retrieval algorithms' accuracy and consistency.

  15. Seasonal land-cover regions of the US

    USGS Publications Warehouse

    Loveland, Thomas R.; Merchant, James W.; Brown, Jesslyn F.; Ohlen, Donald O.; Reed, Bradley C.; Olson, Paul; Hutchinson, John

    1995-01-01

    Global-change investigations have been hindered by deficiencies in the availability and quality of land-cover data. The US Geological Survey and the University of Nebraska-Lincoln have collaborated on the development of a new approach to land-cover characterization that attempts to address requirements of the global-change research community and others interested in regional patterns of land cover. An experimental 1-km-resolution database of land-cover characteristics for the coterminous US has been prepared to test and evaluate the approach. Using multidate Advanced Very High Resolution Radiometer (AVHRR) satellite data complemented by elevation, climate, ecoregions, and other digital spatial datasets, the authors define 15?? seasonal land-cover regions. Data are used in the construction of an illustrative 1:7500 000-scale map of the seasonal land-cover regions as well as of smaller-scale maps portraying general land cover and seasonality. The seasonal land-cover characteristics database can also be tailored to provide a broad range of other landscape parameters useful in national and global-scale environmental modeling and assessment. -from Authors

  16. Senegalese land surface change analysis and biophysical parameter estimation using NOAA AVHRR spectral data

    NASA Technical Reports Server (NTRS)

    Vukovich, Fred M.; Toll, David L.; Kennard, Ruth L.

    1989-01-01

    Surface biophysical estimates were derived from analysis of NOAA Advanced Very High Spectral Resolution (AVHRR) spectral data of the Senegalese area of west Africa. The parameters derived were of solar albedo, spectral visible and near-infrared band reflectance, spectral vegetative index, and ground temperature. Wet and dry linked AVHRR scenes from 1981 through 1985 in Senegal were analyzed for a semi-wet southerly site near Tambacounda and a predominantly dry northerly site near Podor. Related problems were studied to convert satellite derived radiance to biophysical estimates of the land surface. Problems studied were associated with sensor miscalibration, atmospheric and aerosol spatial variability, surface anisotropy of reflected radiation, narrow satellite band reflectance to broad solar band conversion, and ground emissivity correction. The middle-infrared reflectance was approximated with a visible AVHRR reflectance for improving solar albedo estimates. In addition, the spectral composition of solar irradiance (direct and diffuse radiation) between major spectral regions (i.e., ultraviolet, visible, near-infrared, and middle-infrared) was found to be insensitive to changes in the clear sky atmospheric optical depth in the narrow band to solar band conversion procedure. Solar albedo derived estimates for both sites were not found to change markedly with significant antecedent precipitation events or correspondingly from increases in green leaf vegetation density. The bright soil/substrate contributed to a high albedo for the dry related scenes, whereas the high internal leaf reflectance in green vegetation canopies in the near-infrared contributed to high solar albedo for the wet related scenes. The relationship between solar albedo and ground temperature was poor, indicating the solar albedo has little control of the ground temperature. The normalized difference vegetation index (NDVI) and the derived visible reflectance were more sensitive to antecedent

  17. MEDOKADS - A 20 Year's Daily AVHRR Data Series for Analysis of Land Surface Properties

    NASA Astrophysics Data System (ADS)

    Koslowsky, D.; Billing, H.; Bolle, H.-J.

    2009-04-01

    To derive primary data products from raw AVHRR data, like spectral reflectances or temperatures, it is necessary to correct for sensor degradation and changing hardware specifications, to re-sample the data into a grid of equal pixel size, to perform geographical registration, cloud-screening and normalization for illumination and observation geometry. A data set which resulted from the application of these corrections is the top of the atmosphere Mediterranean Extended One-Km AVHRR Data Set (MEDOKADS) which now covers a period of 20 years. To study land surface processes, the obtained spectral data have to be combined, radiometric corrections for atmospheric effects, emissivity corrections in the case of temperature measurements have to be applied, and the variable over-flight times have to be accounted for. By application of complex evaluation schemes then higher level products are generated, like vegetation indices, surface albedo, and surface energy fluxes. The ultimate goal is to provide the users community with problem-related information. This includes the quantification of changes and the determination of trends. Methods and tools to reach this goal as well as their limitations are discussed. To validate the data, extended field measurements have been performed in which the scaling between local ground measurements and large scale satellite data play a major role. A major problem remains the application of atmospheric corrections because of the not well known variable aerosol content. The supervision of the quality of the derived information leads to the concept of anchor stations at which surface and atmospheric properties should permanently be measured.

  18. Land Surface Albedo From EPS/AVHRR : Method For Retrieval and Validation

    NASA Astrophysics Data System (ADS)

    Jacob, G.

    2015-12-01

    The scope of Land Surface Analysis Satellite Applications Facility (LSA-SAF) is to increase benefit from EUMETSAT Satellites (MSG and EPS) data by providing added value products for the meteorological and environmental science communities with main applications in the fields of climate modelling, environmental management, natural hazards management, and climate change detection. The MSG/SEVIRI daily albedo product is disseminated operationally by the LSA-SAF processing centre based in Portugal since 2009. This product so-called MDAL covers Europe and Africa includes in the visible, near infrared and shortwave bands at a resolution of 3km at the equator. Recently, an albedo product at 1km so-called ETAL has been built from EPS/AVHRR observations in order to primarily MDAL product outside the MSG disk, while ensuring a global coverage. The methodology is common to MSG and EPS data and relies on the inversion of the BRDF (Bidirectional Reflectance Distribution Function) model of Roujean et al. On a given target, ETAL products exploits the variability of viewing angles whereas MDAL looks at the variations of solar illumination. The comparison of ETAL albedo product against MODIS and MSG/SEVIRI products over the year 2015 is instructive in many ways and shows in general a good agreement between them. The dispersion may be accounted by different factors that will be explained The additional information provided by EPS appears to be particularly beneficial for high latitudes during winter and for snow albedo.

  19. Comparison of Landsat MSS, Nimbus 7 CZCS, and NOAA 6/7 AVHRR features for land use analysis

    NASA Technical Reports Server (NTRS)

    Cicone, R. C.; Metzler, M. D.

    1982-01-01

    Spectral characteristics of the Coastal Zone Color Scanner (CZCS) on board Nimbus 7, the Advanced Very High Resolution Radiometer (AVHRR) on NOAA 6 and 7 and the Multispectral Scanner (MSS) on Landsat 1-3 are analyzed to comparatively assess their utility for land use analysis through remote sensing. The examination of simulated in-band radiances suggests that each sensor would respond to incident radiation reflected from a typical agricultural scene in a highly comparable manner, with most of the variation captured in two physically related variables. Several measures of green vegetation are examined and features are proposed for crop condition assessment with consideration of the course resolution characteristics of AVHRR and CZCS.

  20. A RESEARCH PLAN FOR THE USE OF THERMAL AVHRR IMAGERY TO STUDY ANNUAL AND SEASONAL MEAN SURFACE TEMPERATURES FOR LARGE LAKES IN NORTH AMERICA

    EPA Science Inventory

    Surface and vertical temperature data will be obtained from several large lakes With surface areas large enough to be effectively sampled with AVHRR imagery. Yearly and seasonal patterns of surface and whole water column thermal values will be compared to estimates of surface tem...

  1. Water vapour correction of the daily 1 km AVHRR global land dataset: Part I validation and use of the Water Vapour input field

    USGS Publications Warehouse

    DeFelice, Thomas P.; Lloyd, D.; Meyer, D.J.; Baltzer, T. T.; Piraina, P.

    2003-01-01

    An atmospheric correction algorithm developed for the 1 km Advanced Very High Resolution Radiometer (AVHRR) global land dataset was modified to include a near real-time total column water vapour data input field to account for the natural variability of atmospheric water vapour. The real-time data input field used for this study is the Television and Infrared Observational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder A global total column water vapour dataset. It was validated prior to its use in the AVHRR atmospheric correction process using two North American AVHRR scenes, namely 13 June and 28 November 1996. The validation results are consistent with those reported by others and entail a comparison between TOVS, radiosonde, experimental sounding, microwave radiometer, and data from a hand-held sunphotometer. The use of this data layer as input to the AVHRR atmospheric correction process is discussed.

  2. Comparative Analysis of Daytime Fire Detection Algorithms, Using AVHRR Data for the 1995 Fire Season in Canda: Perspective for MODIS

    NASA Technical Reports Server (NTRS)

    Ichoku, Charles; Kaufman, Y. J.; Fraser, R. H.; Jin, J.-Z.; Park, W. M.; Lau, William K. M. (Technical Monitor)

    2001-01-01

    Two fixed-threshold Canada Centre for Remote Sensing and European Space Agency (CCRS and ESA) and three contextual GIGLIO, International Geosphere and Biosphere Project, and Moderate Resolution Imaging Spectroradiometer (GIGLIO, IGBP, and MODIS) algorithms were used for fire detection with Advanced Very High Resolution Radiometer (AVHRR) data acquired over Canada during the 1995 fire season. The CCRS algorithm was developed for the boreal ecosystem, while the other four are for global application. The MODIS algorithm, although developed specifically for use with the MODIS sensor data, was applied to AVHRR in this study for comparative purposes. Fire detection accuracy assessment for the algorithms was based on comparisons with available 1995 burned area ground survey maps covering five Canadian provinces. Overall accuracy estimations in terms of omission (CCRS=46%, ESA=81%, GIGLIO=75%, IGBP=51%, MODIS=81%) and commission (CCRS=0.35%, ESA=0.08%, GIGLIO=0.56%, IGBP=0.75%, MODIS=0.08%) errors over forested areas revealed large differences in performance between the algorithms, with no relevance to type (fixed-threshold or contextual). CCRS performed best in detecting real forest fires, with the least omission error, while ESA and MODIS produced the highest omission error, probably because of their relatively high threshold values designed for global application. The commission error values appear small because the area of pixels falsely identified by each algorithm was expressed as a ratio of the vast unburned forest area. More detailed study shows that most commission errors in all the algorithms were incurred in nonforest agricultural areas, especially on days with very high surface temperatures. The advantage of the high thresholds in ESA and MODIS was that they incurred the least commission errors.

  3. Lag and seasonality considerations in evaluating AVHRR NDVI response to precipitation

    USGS Publications Warehouse

    Ji, Lei; Peters, Albert J.

    2005-01-01

    Assessment of the relationship between the normalized difference vegetation index (NDVI) and precipitation is important in understanding vegetation and climate interaction at a large scale. NDVI response to precipitation, however, is difficult to quantify due to the lag and seasonality effects, which will vary due to vegetation cover type, soils and climate. A time series analysis was performed on biweekly NDVI and precipitation around weather stations in the northern and central U.S. Great Plains. Regression models that incorporate lag and seasonality effects were used to quantify the relationship between NDVI and lagged precipitation in grasslands and croplands. It was found that the time lag was shorter in the early growing season, but longer in the mid- to late-growing season for most locations. The regression models with seasonal adjustment indicate that the relationship between NDVI and precipitation over the entire growing season was strong, with R2 values of 0.69 and 0.72 for grasslands and croplands, respectively. We conclude that vegetation greenness can be predicted using current and antecedent precipitation, if seasonal effects are taken into account.

  4. Monitoring arid lands using AVHRR-observed visible reflectance and SMMR37-GHz polarization difference

    NASA Technical Reports Server (NTRS)

    Choudhury, B. J.

    1990-01-01

    Visible reflectance along a transect through the Sahel and Sudan zones of Africa has been derived from observations by the AVHRR on the NOAA-7 and NOAA-9 satellites and compared with concurrent observations of the 37-GHz polarization difference by the SMMR on the Nimbus-7 satellite. The study period was January 1982 to December 1986, which included an unprecedented drought during 1984 over the Sahel zone. While spatial and temporal patterns of these two data sets are found to be highly correlated, there are also quantitative differences which need to be understood.

  5. A Comparison of Seasonal and Interannual Variability of Soil Dust Aerosols Over the Atlantic Ocean as Inferred by the Toms AI and AVHRR AOT Retrievals

    NASA Technical Reports Server (NTRS)

    Cakmur, R. V.; Miller, R. L.; Tegen, Ina; Hansen, James E. (Technical Monitor)

    2001-01-01

    The seasonal cycle and interannual variability of two estimates of soil (or 'mineral') dust aerosols are compared: Advanced Very High Resolution Radiometer (AVHRR) aerosol optical thickness (AOT) and Total Ozone Mapping Spectrometer (TOMS) aerosol index (AI), Both data sets, comprising more than a decade of global, daily images, are commonly used to evaluate aerosol transport models. The present comparison is based upon monthly averages, constructed from daily images of each data set for the period between 1984 and 1990, a period that excludes contamination from volcanic eruptions. The comparison focuses upon the Northern Hemisphere subtropical Atlantic Ocean, where soil dust aerosols make the largest contribution to the aerosol load, and are assumed to dominate the variability of each data set. While each retrieval is sensitive to a different aerosol radiative property - absorption for the TOMS AI versus reflectance for the AVHRR AOT - the seasonal cycles of dust loading implied by each retrieval are consistent, if seasonal variations in the height of the aerosol layer are taken into account when interpreting the TOMS AI. On interannual time scales, the correlation is low at most locations. It is suggested that the poor interannual correlation is at least partly a consequence of data availability. When the monthly averages are constructed using only days common to both data sets, the correlation is substantially increased: this consistency suggests that both TOMS and AVHRR accurately measure the aerosol load in any given scene. However, the two retrievals have only a few days in common per month so that these restricted monthly averages have a large uncertainty. Calculations suggest that at least 7 to 10 daily images are needed to estimate reliably the average dust load during any particular month, a threshold that is rarely satisfied by the AVHRR AOT due to the presence of clouds in the domain. By rebinning each data set onto a coarser grid, the availability of

  6. Comparison of multi-temporal NOAA-AVHRR and SPOT-XS satellite data for mapping land-cover dynamics in the West African Sahel

    NASA Technical Reports Server (NTRS)

    Marsh, S. E.; Walsh, J. L.; Lee, C. T.; Beck, L. R.; Hutchinson, C. F.

    1992-01-01

    Multi-resolution and multi-temporal remote sensing data (SPOT-XS and AVHRR) were evaluated for mapping local land-cover dynamics in the Sahel of West Africa. The aim of this research was to evaluate the agricultural information that could be derived from both high and low spatial resolution data in areas where there is very often limited ground information. A combination of raster-based image processing and vector-based geographical information system mapping was found to be effective for understanding both spatial and spectral land-cover dynamics. The SPOT data proved useful for mapping local land-cover classes in a dominantly recessive agricultural region. The AVHRR-LAC data could be used to map the dynamics of riparian vegetation, but not the changes associated with recession agriculture. In areas where there was a complex mixture of recession and irrigated agriculture, as well as riparian vegetation, the AVHRR data did not provide an accurate temporal assessment of vegetation dynamics.

  7. Land cover mapping, fire regeneration, and scaling studies in the Canadian boreal forest with 1 km AVHRR and Landsat TM data

    NASA Astrophysics Data System (ADS)

    Steyaert, L. T.; Hall, F. G.; Loveland, T. R.

    1997-12-01

    A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. The land cover classification was developed by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly normalized difference vegetation index (NDVI) image composites (April-September 1992). Quantitative areal proportions of the major boreal forest components were determined for a 821 km × 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within

  8. Land cover mapping, fire regeneration, and scaling studies in the Canadian boreal forest with 1 km AVHRR and Landsat TM data

    USGS Publications Warehouse

    Steyaert, L.T.; Hall, F.G.; Loveland, T.R.

    1997-01-01

    A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. The land cover classification was developed by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly normalized difference vegetation index (NDVI) image composites (April-September 1992). Quantitative areal proportions of the major boreal forest components were determined for a 821 km ?? 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within

  9. Hydrologic models for land-atmosphere retrospective studies of the use of LANDSAT and AVHRR data

    NASA Technical Reports Server (NTRS)

    Duchon, Claude E.; Williams, T. H. Lee; Nicks, Arlin D.

    1988-01-01

    The use of a Geographic Information System (GIS) and LANDSAT analysis in conjunction with the Simulator for Water Resources on a Rural Basin (SWRRB) hydrologic model to examine the water balance on the Little Washita River basin is discussed. LANDSAT analysis was used to divide the basin into eight non-contiguous land covers or subareas: rangeland, grazed range, winter wheat, alfalfa/pasture, bare soil, water, woodland, and impervious land (roads, quarry). The use of a geographic information system allowed for the calculation of SWRRB model parameters in each subarea. Four data sets were constructed in order to compare SWRRB estimates of hydrologic processes using two methods of maximum LAI and two methods of watershed subdivision. Maximum LAI was determined from a continental scale map, which provided a value of 4.5 for the entire basin, and from its association with the type of land-cover (eight values). The two methods of watershed subdivision were determined according to drainage subbasin (four) and the eight land-covers. These data sets were used with the SWRRB model to obtain daily hydrologic estimates for 1985. The results of the one year analysis lead to the conclusion that the greater homogeneity of a land-cover subdivision provides better water yield estimates than those based on a drainage properties subdivision.

  10. A comparison of SMMR and AVHRR data for continental land cover characterization

    NASA Technical Reports Server (NTRS)

    Townshend, J. R. G.; Justice, C. O.; Choudhury, B. J.; Tucker, C. J.; Kalb, V. T.; Goff, T. E.

    1989-01-01

    Images using reflected visible and NIR data and images using passive microwave data were compared in terms of their usefulness for characterizing land-cover types in South America and Africa. The former images are of the normalized difference vegetation index (NDVI), and the latter images are of the microwave polarization difference temperature (MPDT). The combined use of MPDT and NDVI data sets show clear synergistic benefits in using the two data sets. However, the evidence suggests that for most cover types, increasing the temporal frequency of the NDVI images is more advantageous than incorporating MPDT data sets.

  11. Comparison of Vegetation Phenology estimated from MODIS and AVHRR over North America

    NASA Astrophysics Data System (ADS)

    Tan, B.; Morisette, J. T.; Wolfe, R. E.; Gao, F.; Ederer, G. A.; Nightingale, J.; Pedelty, J. A.

    2008-12-01

    Vegetation indices (VIs) derived from satellite data are now commonly used for detecting vegetation phenology at continental to global scales. Vegetation phenology estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) VIs over North America from 2001 to 2006 have been produced and freely available online from http://www.accweb.nascom.nasa.gov. The algorithm to produce this MODIS phenology metrics is based on revised TIMESAT software, which uses the 3rd derivation of a fitted Gauss curve to locate four key phenology dates - begin and end of the greenup and browndown. In order to achieve a long-term phenology record, the same phenology detection algorithm is applied to 1982-2002 GIMMS AVHRR NDVI data sets over North America. To make the phenology estimations from different sensors consistent and comparable, several different methods are utilized in this research. We first compare the phenology metrics estimated from MODIS NDVI and AVHRR NDVI in 2001 and 2002. We found no significant latitudinal gradients in the AVHRR phenology metrics. At the same time, the length of the growing season is artificially overestimated in Northern US and Southern Canada. Both phenomena indicates lower quality from the AVHRR phenology metrics, which is mainly due to the unreliable snow flag of AVHRR data and the absence of ancillary land surface temperature data. To improve the quality of the AVHRR phenology metrics, a more accurate definition of non-growing season is required. We first use the 21-year climatologic mean of minimum NDVI as a threshold to refine the non-growing season pixels. In addition, a sensitivity analysis is performed to address the impact of the threshold on derived phenology metrics. Overall, this research will provide a 25-year phenology product for North America using both MODIS and AVHRR NDVI, which can be applied in regional/continental climate variation analysis and vegetation monitoring. The method to calibrate MODIS and AVHRR phenology products

  12. Hydrologic models for land-atmosphere retrospective studies of the use of LANDSAT and AVHRR data

    NASA Technical Reports Server (NTRS)

    Duchon, Claude E.; Williams, T. H. Lee; Nicks, Arlin D.

    1988-01-01

    The use of a Geographic Information System (GIS) and LANDSAT analysis in conjunction with the Simulator for Water Resources on a Rural Basin (SWRRB) hydrologic model to examine the water balance on the Little Washita River basin is discussed. In the research completed to date LANDSAT analysis was used to divide the basin into eight non-contiguous land covers or sub areas. The use of a geographic informatin system allowed for the calculation of SWRRB model parameters in each subarea. Four data sets were constructed in order to compare SWRRB estimates of hydrologic processes using two methods of maximum LAI and two methods of watershed division. These data sets were used with the SWRRB model to obtain daily hydrologic estimates for 1985.

  13. Relating seasonal patterns of the AVHRR vegetation index to simulated photosynthesis and transpiration of forests in different climates

    NASA Technical Reports Server (NTRS)

    Running, Steven W.; Nemani, Ramakrishna R.

    1988-01-01

    Weekly AVHRR Normalized Difference Vegetation Index (NDVI) values for 1983-1984 for seven sites of diverse climate in North America were correlated with results of an ecosystem simulation model of a hypothetical forest stand for the corresponding period at each site. The tendency of raw NDVI data to overpredict photosynthesis and transpiration on water limited sites was shown to be partially corrected by using an aridity index of annual radiation/annual precipitation. The results suggest that estimates of vegetation productivity using the global vegetation index are only accurate as annual integrations, unless unsubsampled local area coverage NDVI data can be tested against forest photosynthesis, transpiration and aboveground net primary production data measured at shorter time intervals.

  14. Multi-Decadal Pathfinder Data Sets of Global Land Biophysical Variables from AVHRR and MODIS and their Use in GCM Studies of Biogeophysics and Biogeochemistry

    NASA Technical Reports Server (NTRS)

    Myneni, Ranga

    2003-01-01

    The problem of how the scale, or spatial resolution, of reflectance data impacts retrievals of vegetation leaf area index (LAI) and fraction absorbed photosynthetically active radiation (PAR) has been investigated. We define the goal of scaling as the process by which it is established that LAI and FPAR values derived from coarse resolution sensor data equal the arithmetic average of values derived independently from fine resolution sensor data. The increasing probability of land cover mixtures with decreasing resolution is defined as heterogeneity, which is a key concept in scaling studies. The effect of pixel heterogeneity on spectral reflectances and LAI/FPAR retrievals is investigated with 1 km Advanced Very High Resolution Radiometer (AVHRR) data aggregated to different coarse spatial resolutions. It is shown that LAI retrieval errors at coarse resolution are inversely related to the proportion of the dominant land cover in such pixel. Further, large errors in LAI retrievals are incurred when forests are minority biomes in non-forest pixels compared to when forest biomes are mixed with one another, and vice-versa. A physically based technique for scaling with explicit spatial resolution dependent radiative transfer formulation is developed. The successful application of this theory to scaling LAI retrievals from AVHRR data of different resolutions is demonstrated

  15. On The Reproducibility of Seasonal Land-surface Climate

    SciTech Connect

    Phillips, T J

    2004-10-22

    The sensitivity of the continental seasonal climate to initial conditions is estimated from an ensemble of decadal simulations of an atmospheric general circulation model with the same specifications of radiative forcings and monthly ocean boundary conditions, but with different initial states of atmosphere and land. As measures of the ''reproducibility'' of continental climate for different initial conditions, spatio-temporal correlations are computed across paired realizations of eleven model land-surface variables in which the seasonal cycle is either included or excluded--the former case being pertinent to climate simulation, and the latter to seasonal anomaly prediction. It is found that the land-surface variables which include the seasonal cycle are impacted only marginally by changes in initial conditions; moreover, their seasonal climatologies exhibit high spatial reproducibility. In contrast, the reproducibility of a seasonal land-surface anomaly is generally low, although it is substantially higher in the Tropics; its spatial reproducibility also markedly fluctuates in tandem with warm and cold phases of the El Nino/Southern Oscillation. However, the overall degree of reproducibility depends strongly on the particular land-surface anomaly considered. It is also shown that the predictability of a land-surface anomaly implied by its reproducibility statistics is consistent with what is inferred from more conventional predictability metrics. Implications of these results for climate model intercomparison projects and for operational forecasts of seasonal continental climate also are elaborated.

  16. On the Potential Predictability of Seasonal Land-Surface Climate

    SciTech Connect

    Phillips, T J

    2001-10-01

    The chaotic behavior of the continental climate of an atmospheric general circulation model is investigated from an ensemble of decadal simulations with common specifications of radiative forcings and monthly ocean boundary conditions, but different initial states of atmosphere and land. The variability structures of key model land-surface processes appear to agree sufficiently with observational estimates to warrant detailed examination of their predictability on seasonal time scales. This predictability is inferred from several novel measures of spatio-temporal reproducibility applied to eleven model variables. The reproducibility statistics are computed for variables in which the seasonal cycle is included or excluded, the former case being most pertinent to climate model simulations, and the latter to predictions of the seasonal anomalies. Because the reproducibility metrics in the latter case are determined in the context of a ''perfectly'' known ocean state, they are properly viewed as estimates of the potential predictability of seasonal climate. Inferences based on these reproducibility metrics are shown to be in general agreement with those derived from more conventional measures of potential predictability. It is found that the land-surface variables which include the seasonal cycle are impacted only marginally by changes in initial conditions; moreover, their seasonal climatologies exhibit high spatial reproducibility. In contrast, the reproducibility of a seasonal land-surface anomaly is generally low, although it is considerably higher in the Tropics; its spatial reproducibility also fluctuates in tandem with warm and cold phases of the El Nino/Southern Oscillation phenomenon. However, the detailed sensitivities to initial conditions depend somewhat on the land-surface process: pressure and temperature anomalies exhibit the highest temporal reproducibilities, while hydrological and turbulent flux anomalies show the highest spatial reproducibilities

  17. Mesoscale water balance modelling in the Upper Danube watershed using sub-scale land cover information derived from NOAA-AVHRR imagery and GIS-techniques

    NASA Astrophysics Data System (ADS)

    Ludwig, Ralf; Probeck, Markus; Mauser, Wolfram

    Earth observation from space provides unique data to obtain up-to-date information on the rapidly changing state of the environment. While imagery from high spatial resolution sensors are still inadequate to derive consistent land use information for mesoscale areas, fine spatial resolution of land use information is essential for the description of hydrological processes at the landscape level, such as runoff generation and evapotranspiration. The study presents a procedure to overcome existing limitations by using coarse spatial resolution NOAA-AVHRR (Advanced Very High Resolution Radiometer) data within a framework of combined multitemporal imagery and fuzzy-logic based geospatial data analysis. The spectral unmixing methodology determines fractional land cover data for each raster cell in the watershed. It assumes that the spectrum of a surface is linearly composed of the area-weighted spectra of its known components (endmembers). In extension to existing unmixing approaches, each “spectrum” refers to a multitemporal spectral profile of a pixel, which consists of the temporal development of the pixel’s spectral behaviour over an entire vegetation period. In order to minimise classification errors, geographical expert knowledge is utilised to evaluate the geofactors elevation, slope, soil and precipitation in a fuzzy-logic approach to priorily determine a valid set of possible endmembers for each raster cell. The final unmixing results are validated against both a reference classification from LANDSAT-TM imagery and the CORINE land cover classification. The method is employed for the Upper Danube watershed (76.653 km 2) to provide sub-scale land use information, which is used as an input for the physically based and raster-oriented SVAT model PROMET (J. Hydrol. 212-213 (1998) 250; J. Hydrol. 254 (2001) 199). The model is operated in hourly time steps on a 1-km 2 grid, each raster cell comprising the various land cover classes, to simulate the spatial and

  18. Impact of land-surface initialization on sub-seasonal to seasonal forecasts over Europe

    NASA Astrophysics Data System (ADS)

    Prodhomme, Chloé; Doblas-Reyes, Francisco; Bellprat, Omar; Dutra, Emanuel

    2016-08-01

    Land surfaces and soil conditions are key sources of climate predictability at the seasonal time scale. In order to estimate how the initialization of the land surface affects the predictability at seasonal time scale, we run two sets of seasonal hindcasts with the general circulation model EC-Earth2.3. The initialization of those hindcasts is done either with climatological or realistic land initialization in May using the ERA-Land re-analysis. Results show significant improvements in the initialized run occurring up to the last forecast month. The prediction of near-surface summer temperatures and precipitation at the global scale and over Europe are improved, as well as the warm extremes prediction. As an illustration, we show that the 2010 Russian heat wave is only predicted when soil moisture is initialized. No significant improvement is found for the retrospective prediction of the 2003 European heat wave, suggesting this event to be mainly large-scale driven. Thus, we confirm that late-spring soil moisture conditions can be decisive in triggering high-impact events in the following summer in Europe. Accordingly, accurate land-surface initial conditions are essential for seasonal predictions.

  19. Predictive Understanding of Seasonal Hydrological Dynamics under Climate and Land Use-Land Cover Change

    NASA Astrophysics Data System (ADS)

    Batra, N.; Yang, Y. E.; Choi, H. I.; Kumar, P.; Cai, X.; Fraiture, C. D.

    2008-12-01

    Water has always been and will continue to be an important factor in agricultural production and any alteration in the seasonal distribution of water availability due to climate and land use-land cover change (LULCC) will significantly impact the future production. To achieve the ecologic, economic and social objectives of sustainability, physical understanding of the linkages between climatic changes, LULCC and hydrological response is required. Aided by satellite data, modeling and understanding of the interactions between physical processes of the climate system and society, more reliable regional LULCC and climate change projections are now available. However, resulting quantitative projection of changes on the regional scale hydrological components at the seasonal time scale are sparse. This study attempts to quantify the seasonal hydrological response due to projected LULCC and climate change scenario of Intergovernmental Panel on Climate Change (IPCC) in different hydro-climatic regions of the world. The Common Land Model (CLM) is used for global assessment of future hydrologic response with the development of a consistent global GIS based database for the surface boundary conditions and meteorological forcing of the model. Future climate change projections are derived from the IPCC Fourth Assessment Report: Working Group I - The Physical Science Basis. The study is performed over nine river basins selected from Asia, Africa and North America to present the broad climatic and landscape controls on the seasonal hydrological dynamics. Future changes in water availability are quite evident from our results based upon changes in the volume and seasonality of precipitation, runoff and evapotranspiration. Severe water scarcity is projected to occur in certain seasons which may not be known through annual estimates. Knowledge of the projected seasonal hydrological response can be effectively used for developing adaptive management strategies for the sustainability

  20. Classification of simulated and actual NOAA-6 AVHRR data for hydrologic land-surface feature definition. [Advanced Very High Resolution Radiometer

    NASA Technical Reports Server (NTRS)

    Ormsby, J. P.

    1982-01-01

    An examination of the possibilities of using Landsat data to simulate NOAA-6 Advanced Very High Resolution Radiometer (AVHRR) data on two channels, as well as using actual NOAA-6 imagery, for large-scale hydrological studies is presented. A running average was obtained of 18 consecutive pixels of 1 km resolution taken by the Landsat scanners were scaled up to 8-bit data and investigated for different gray levels. AVHRR data comprising five channels of 10-bit, band-interleaved information covering 10 deg latitude were analyzed and a suitable pixel grid was chosen for comparison with the Landsat data in a supervised classification format, an unsupervised mode, and with ground truth. Landcover delineation was explored by removing snow, water, and cloud features from the cluster analysis, and resulted in less than 10% difference. Low resolution large-scale data was determined useful for characterizing some landcover features if weekly and/or monthly updates are maintained.

  1. Forest classification of southeast Asia using NOAA AVHRR data

    SciTech Connect

    Achard, F.; Estreguil, C.

    1995-12-01

    Tropical deforestation is one of the most significant forms of global environmental change. It has been identified as an important component of the global carbon cycle while also having been shown to effect regional climate and hydrology. Methodologies using the 1 km resolution data of the NOAA AVHRR instrument were developed for tropical forest spectral discrimination and mapping at a regional scale. Tropical Southeast Asia was selected as a cause study using a multitemporal AVHRR data set of 1990--1992. This study documents first the relevance of AVHRR data to assess the extent of seasonal and dense forest and, moreover, reports on the derivation of a specific fragmented/disturbed forest class. A geographically dependent methodology is developed: for continental Southeast Asia, where generally good cloud-free images are available during the dry season and seasonal vegetation formations are present, multitemporal AVHRR mosaics were produced before the classification process. For insular Southeast Asia, which is particularly affected by the cloud cover and where only humid vegetation formations are present, a multitemporal set of single-date AVHRR images was first classified, and then the classifications were mosaicked together using a combination of two criteria (image quality and maximum occurrence). Unsupervised classifications using NDVI and Channel 3 radiance were processed in both cases. Verification of the AVHRR class assignment was carried out locally using a few high spatial resolution satellite images. It highlights the sources of misclassification.

  2. Seasonal and Non-seasonal Sea Level Variations by Exchange of Water with Land Hydrology

    NASA Technical Reports Server (NTRS)

    Chao, Benjamin F.; Au, A. Y.

    2004-01-01

    The global ocean exchanges a large amount of water, seasonally or non-seasonally, with land hydrology. Apart from the long-term melting of ice sheets and glaciers, the water is exchanged directly as land runoff R, and indirectly via atmosphere in the form of precipitation minus evapo-transpiration P-E. On land, the hydrological budget balance is soil moisture S = P-E-R. The runoff R has been difficult to monitor; but now by combining the following two data sets one can obtain a global estimate, subject to the spatial and temporal resolutions afforded by the data: (1) The space gravity mission GRACE yields monthly S estimate on a spatial scale larger than approx. 1000 km over the last 2.5 years; (2) The atmospheric circulation model output, such as from NCEP, provides proxy estimates for P-E at monthly and approx. 200 km resolutions. We will discuss these estimates and the effects on the global ocean water budget and hence sea level.

  3. Analysis of forest disturbance using TM and AVHRR data

    NASA Technical Reports Server (NTRS)

    Spanner, Michael A.; Hlavka, Christine A.; Pierce, Lars L.

    1989-01-01

    A methodology that will be used to determine the proportions of undisturbed, successional vegetation and recently disturbed land cover within coniferous forests using remotely sensed data from the advanced very high resolution radiometer (AVHRR) is presented. The method uses thematic mapper (TM) data to determine the proportions of the three stages of forest disturbance and regrowth for each AVHRR pixel in the sample areas, and is then applied to interpret all AVHRR imagery. Preliminary results indicate that there are predictable relationships between TM spectral response and the disturbance classes. Analysis of ellipse plots from a TM classification of the disturbed forested landscape indicates that the forest classes are separable in the red (0.63-0.69 micron) and near-infrared (0.76-0.90 micron) bands, providing evidence that the proportion of disturbance classes may be determined from AVHRR data.

  4. Seasonality of Air-sea-ice-land Variables for Arctic Tundra in Northern Eurasia and North America

    NASA Astrophysics Data System (ADS)

    Bhatt, U. S.; Walker, D. A.; Raynolds, M. K.; Steele, M.; Epstein, H.; Jia, G.; Comiso, J. C.; Pinzon, J. E.; Tucker, C. J.

    2009-12-01

    The strength of tundra productivity trends as measured by the annual maximum Normalized Difference Vegetation Index (MaxNDVI) and time integrated NDVI (TI-NDVI) vary around the Arctic over the 1982-2008 period. Our analysis suggests that the timing of terrestrial vegetation growth is connected to seasonal patterns of sea-ice concentrations, ocean temperatures and land surface temperatures. This study used SSMI estimates of sea ice concentration, based on a bootstrap algorithm and AVHRR radiometric surface temperature. Summer Warmth Index (SWI) was calculated as the sum from May to August of the degree months above freezing of surface temperature at each pixel and is an accepted measure of plant growth potential. The Normalized Difference Vegetation Index (NDVI) represents vegetation greenness and has been used extensively to monitor changes in the Arctic. The albedo of green plants varies with solar radiation wavelength, which is the basis for the NDVI index. The analysis was conducted within 50 km of the Arctic coastline to focus on the region of maximum maritime influence. Time series of regional sea-ice concentration, SWI and NDVI were constructed for the 50-km width domains for the Pan-Arctic, North America, Eurasia and Arctic subregions. Standard climate analysis techniques were applied to the regional time series to investigate the seasonality of sea ice, NDVI and SWI. MaxNDVI has increased in the 50-km land domain contiguous to the Beaufort Sea by 17% since 1982, whereas it has only increased by 3% in the coastal Kara Sea region. Analysis of semimonthly MaxNDVI indicates that the vegetation greens up more rapidly in the spring in the Beaufort than the W. Kara and the Kara has slightly higher NDVI in the fall. The climatological weekly sea ice concentrations in 50-km coastal domain displays an earlier breakup in the Beaufort and a later freeze-up in the Kara Sea area. Regional differences in the seasonal cycle can in part explain the spatially varied trends

  5. Combining MSS and AVHRR imagery to assess vegetation biomass and dynamics in an arid pastoral ecosystem, Turkana District, Kenya

    SciTech Connect

    Ellis, J.E.; Swift, D.M.; Hart, T.C.; Dick, O.B.

    1987-07-01

    Landsat multi-spectral scanner (MSS) imagery was used to develop a vegetation type-biomass map of the 84,000 Km/sup 2/ Turkana District, Kenya. NOAA satellite advanced very high resolution radiometry (AVHRR) imagery was overlaid on the MSS map to trace the seasonal and annual dynamics of vegetation communities used by Turkana pastoral nomads, 1981-1984. Four regions (sub-sectional territories) were compared with respect to peak herbaceous biomass, woody canopy cover, and seasonal fluxes in total green biomass. Results demonstrated major variations among regions and between wet and dry season ranges within regions. Pastoral land use patterns appear to minimize effects of seasonal vegetation fluxes on livestock herds.

  6. EFFECTS OF LAND USE AND SEASON ON MICROORGANISM CONCENTRATIONS IN URBAN STORMWATER RUNOFF

    EPA Science Inventory

    This study investigated differences in pathogen and indicator organism concentrations in stormwater runoff between different urban land uses and seasons. Stormwater samples collected from storm sewers draining small municipal separate storm sewer systems shown to be free of cros...

  7. Seasonal variation of land cover classification accuracy of Landsat 8 images in Burkina Faso

    NASA Astrophysics Data System (ADS)

    Liu, J.; Heiskanen, J.; Aynekulu, E.; Pellikka, P. K. E.

    2015-04-01

    In the seasonal tropics, vegetation shows large reflectance variation because of phenology, which complicates land cover change monitoring. Ideally, multi-temporal images for change monitoring should be from the same season, but availability of cloud-free images is limited in wet season in comparison to dry season. Our aim was to investigate how land cover classification accuracy depends on the season in southern Burkina Faso by analyzing 14 Landsat 8 OLI images from April 2013 to April 2014. Because all the images were acquired within one year, we assumed that most of the observed variation between the images was due to phenology. All the images were cloud masked and atmospherically corrected. Field data was collected from 160 field plots located within a 10 km x 10 km study area between December 2013 and February 2014. The plots were classified to closed forest, open forest and cropland, and used as training and validation data. Random forest classifier was employed for classifications. According to the results, there is a tendency for higher classification accuracy towards the dry season. The highest classification accuracy was provided by an image from December, which corresponds to the dry season and minimum NDVI period. In contrast, an image from October, which corresponds to the wet season and maximum NDVI period provided the lowest accuracy. Furthermore, the multi-temporal classification based on dry and wet season images had higher accuracy than single image classifications, but the improvement was small because seasonal changes affect similarly to the different land cover classes.

  8. The bidirectional effects of AVHRR measurements over boreal regions

    SciTech Connect

    Li, Z.; Cihlar, J.; Zheng, X.; Moreau, L.; Ly, H.

    1996-11-01

    Northern ecosystems play an important role in regional and global weather and climate. The objectives of this paper are to analyze the bidirectional effects of satellite data over six land-cover types in northern regions, and to test a method for the routine correction of these effects. Analyses and corrections were carried out with both single-day and 10-day composite data obtained by the advanced very high resolution radiometer (AVHRR) from central Canada acquired in 1993/1994, in part, for the boreal ecosystem and atmosphere study (BOREAS). The model of Wu et al. developed from a separate data set collected at lower latitudes, was employed for correcting the effects. Using the model of Wu et al., the BRDF-related variability is reduced by about 68% in channel 1 and 71% in channel 2. After a simple adjustment of the model coefficients, a further reduction of 4% (channel 1) and 6% (channel 2) of the BRDF-related variability was achieved for the 10{sup 6} km{sup 2} BOREAS region. The effectiveness of the correction with both original and refined model of Wu et al. was found to be weakly dependent on land-cover type. Corrections for coniferous, mixed wood, and cropland are better than other land-cover types (rangelands/pasture, deciduous, and transitional forests) with residual BRDF errors around 0.05 in both channels. Overall, the model performs reasonably well throughout the growing season. To apply the model, only general knowledge of land-cover type is required, namely forest, cropland, grassland, and bare ground.

  9. The utility of estimating net primary productivity over Alaska using baseline AVHRR data

    USGS Publications Warehouse

    Markon, C.J.; Peterson, K.M.

    2002-01-01

    Net primary productivity (NPP) is a fundamental ecological variable that provides information about the health and status of vegetation communities. The Normalized Difference Vegetation Index, or NDVI, derived from the Advanced Very High Resolution Radiometer (AVHRR) is increasingly being used to model or predict NPP, especially over large remote areas. In this article, seven seasonally based metrics calculated from a seven-year baseline NDVI dataset were used to model NPP over Alaska, USA. For each growing season, they included maximum, mean and summed NDVI, total days, product of total days and maximum NDVI, an integral estimate of NDVI and a summed product of NDVI and solar radiation. Field (plot) derived NPP estimates were assigned to 18 land cover classes from an Alaskan statewide land cover database. Linear relationships between NPP and each NDVI metric were analysed at four scales: plot, 1-km, 10-km and 20-km pixels. Results show moderate to poor relationship between any of the metrics and NPP estimates for all data sets and scales. Use of NDVI for estimating NPP may be possible, but caution is required due to data seasonality, the scaling process used and land surface heterogeneity.

  10. Combining MODIS, AVHRR and in situ data for evapotranspiration estimation over heterogeneous landscape of the Tibetan Plateau

    NASA Astrophysics Data System (ADS)

    Ma, Y.; Zhu, Z.; Zhong, L.; Wang, B.; Han, C.; Wang, Z.; Wang, Y.; Lu, L.; Amatya, P. M.; Ma, W.; Hu, Z.

    2014-02-01

    In this study, a parameterization method based on MODIS (Moderate Resolution Imaging Spectroradiometer) data, AVHRR (Advanced Very High-Resolution Radiometer) data and in situ data is introduced and tested for estimating the regional evaporative fraction Λ over a heterogeneous landscape. As a case study, the algorithm was applied to the Tibetan Plateau (TP) area. Eight MODIS data images (17 January, 14 April, 23 July and 16 October in 2003; 30 January, 15 April, 1 August and 25 October in 2007) and four AVHRR data images (17 January, 14 April, 23 July and 16 October in 2003) were used in this study to compare winter, spring, summer and autumn values and for annual variation analysis. The results were validated using the "ground truth" measured at Tibetan Observation and Research Platform (TORP) and the CAMP/Tibet (CEOP (Coordinated Enhanced Observing Period) Asia-Australia Monsoon Project (CAMP) on the Tibetan Plateau) meteorological stations. The results show that the estimated evaporative fraction Λ in the four different seasons over the TP is in clear accordance with the land surface status. The Λ fractions show a wide range due to the strongly contrasting surface features found on the TP. Also, the estimated Λ values are in good agreement with "ground truth" measurements, and their absolute percentage difference (APD) is less than 10.0% at the validation sites. The AVHRR data were also in agreement with the MODIS data, with the latter usually displaying a higher level of accuracy. It was therefore concluded that the proposed algorithm was successful in retrieving the evaporative fraction Λ using MODIS, AVHRR and in situ data over the TP. MODIS data are the most accurate and should be used widely in evapotranspiration (ET) research in this region.

  11. Seasonal variations in the relationship between landscape pattern and land surface temperature in Indianapolis, USA.

    PubMed

    Liu, Hua; Weng, Qihao

    2008-09-01

    This paper intended to examine the seasonal variations in the relationship between landscape pattern and land surface temperature based on a case study of Indianapolis, United States. The integration of remote sensing, GIS, and landscape ecology methods was used in this study. Four Terra's ASTER images were used to derive the landscape patterns and land surface temperatures (LST) in four seasons in the study area. The spatial and ecological characteristics of landscape patterns and LSTs were examined by the use of landscape metrics. The impact of each land use and land cover type on LST was analyzed based on the measurements of landscape metrics. The results show that the landscape and LST patterns in the winter were unique. The rest of three seasons apparently had more agreeable landscape and LST patterns. The spatial configuration of each LST zone conformed to that of each land use and land cover type with more than 50% of overlap in area for all seasons. This paper may provide useful information for urban planners and environmental managers for assessing and monitoring urban thermal environments as result of urbanization. PMID:17899413

  12. Land surface phenologies and seasonalities using earthlight: A comparison between tropical and temperate croplands

    NASA Astrophysics Data System (ADS)

    Alemu, W. G.; Henebry, G. M.

    2012-12-01

    Phenology and seasonality are complementary aspects of ecosystem functioning: phenology deals with timing of biotic phenomena; whereas, seasonality concerns temporal patterns of abiotic variables. In this study, we assessed the land surface phenologies and seasonalities in tropical croplands of northwest Ethiopia around Lake Tana and in temperate croplands in the Volga River basin of southeastern European Russia using enhanced land parameters derived from the AMSR-E passive microwave radiometer on the NASA Aqua satellite during 2003-2010. AMSR-E sensed microwave radiation emitted by the atmosphere and land surface at multiple frequencies. Data were acquired at both daytime (~1330) and nighttime (~0130) overpasses. The spatial resolution of the dataset is 25 km. We used the following AMSR-E land surface parameters: air temperature (ta), volumetric soil moisture (mv), fractional cover of open water on land (fw), and vegetation canopy microwave transmittance in three different frequencies (tc06, tc10, and tc18). A 15-day retrospective moving average filter was applied to each parameter time series to minimize data gaps due to orbit and swath width. Growing degree-days (GDDs) were calculated using the daytime and nighttime ta values with a base of 273.15 K and then accumulated (AGDD) with an annual restart each winter solstice. The AMSR-E parameters as a function of AGDD followed seasonal temperature patterns in Russia but seasonal rainfall patterns in Ethiopia. . The behavior of GDD as a function of AGDD displayed strong seasonality with quadratic shape in the Russian croplands, in contrast to a weak seasonality in the Ethiopian croplands. The behavior of canopy transmittance (VOD; vegetation optical depth) as a function of AGDD exhibits seasonalities and display polynomial shape graphs in space and time. During the growing season VODs rapidly ascended to a unimodal peak value and decline gradually. There were sharper decreases in VOD toward the end of the growing

  13. Polar Geophysics Products Derived from AVHRR: The "AVHRR Polar Pathfinder

    NASA Technical Reports Server (NTRS)

    Maslanik, James; Fowler, Charles; Scambos, Theodore

    1999-01-01

    This NOAA/NASA Pathfinder effort was established to locate, acquire, and process Advanced Very High Resolution Radiometer (AVHRR) imagery into geo-located and calibrated radiances, cloud masks, surface clear-sky broadband albedo, clear-sky skin temperatures, satellite viewing times, and viewing and solar geometry for the, high-latitude portions of the northern and southern hemispheres (all area north of 48N and south of 53S). AVHRR GAC data for August 1981 - July 1998 were acquired, with some gaps remaining, and processed into twice-daily 5-km grids, with some products also provided at 25-km resolution. AVHRR LAC data for 3.5 years of coverage in the northern hemisphere and 2.75 years of coverage in the southern hemisphere were processed into 1.25-km grids for the same suite of products. The resulting data sets are presently being transferred to the National Snow and Ice Data Center (NSIDC) for archiving and distribution. Using these data, researchers now have at their disposal an extensive AVHRR data set for investigations of high-latitude processes. In addition, the data lend themselves to development and testing of algorithms. The products are particularly relevant for climate research and algorithm development as applied to relatively long time periods and large areas.

  14. The 1990 conterminous U. S. AVHRR data set

    SciTech Connect

    Eidenshink, J.C. USGS, EROS Data Center, Sioux Falls, SD )

    1992-06-01

    The U.S. Geological Survey, using NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) 1-km data, has produced a time series of 19 biweekly maximum normalized difference vegetation index (NDVI) composites of the conterminous United States for the 1990 growing season. Each biweekly composite included data from approximately 20 calibrated and georegistered daily overpasses. The output is a data set which includes all five calibrated AVHRR channels, NDVI values, three satellite/solar viewing angles, and date of observation pointer for each biweekly composite. The data set is intended for assessing seasonal variations in vegetation condition and provides a foundation for studying long-term changes in vegetation resulting from human interactions or global climate alterations. 12 refs.

  15. Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data

    USGS Publications Warehouse

    Gallo, K.; Ji, L.; Reed, B.; Eidenshink, J.; Dwyer, J.

    2005-01-01

    The relationship between AVHRR-derived normalized difference vegetation index (NDVI) values and those of future sensors is critical to continued long-term monitoring of land surface properties. The follow-on operational sensor to the AVHRR, the Visible/Infrared Imager/Radiometer Suite (VIIRS), will be very similar to the NASA Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. NDVI data derived from visible and near-infrared data acquired by the MODIS (Terra and Aqua platforms) and AVHRR (NOAA-16 and NOAA-17) sensors were compared over the same time periods and a variety of land cover classes within the conterminous United States. The results indicate that the 16-day composite NDVI values are quite similar over the composite intervals of 2002 and 2003, and linear relationships exist between the NDVI values from the various sensors. The composite AVHRR NDVI data included water and cloud masks and adjustments for water vapor as did the MODIS NDVI data. When analyzed over a variety of land cover types and composite intervals, the AVHRR derived NDVI data were associated with 89% or more of the variation in the MODIS NDVI values. The results suggest that it may be possible to successfully reprocess historical AVHRR data sets to provide continuity of NDVI products through future sensor systems. ?? 2005 Elsevier Inc. All rights reserved.

  16. Mapping Fire Scars in the Brazilian Cerrado Using AVHRR Imagery

    NASA Technical Reports Server (NTRS)

    Hlavka, C. A.; Ambrosia, V. G.; Brass, J. A.; Rezendez, A.; Alexander, S.; Guild, L. S.; Peterson, David L. (Technical Monitor)

    1995-01-01

    The Brazilian cerrado, or savanna, spans an area of 1,800,000 square kilometers on the great plateau of Central Brazil. Large fires covering hundreds of square kilometers, frequently occur in wildland areas of the cerrado, dominated by grasslands or grasslands mixed with shrubs and small trees, and also within area in the cerrado used for agricultural purposes, particularly for grazing. Smaller fires, typically extending over arm of a few square kilometers or less, are associated with the clewing of crops, such as dry land rice. A method for mapping fire scars and differentiating them from extensive areas of bare sod with AVHRR bands 1 (.55 -.68 micrometer) and 3 (3.5 - 3.9 micrometers) and measures of performance based on comparison with maps of fires with Landsat imagery will be presented. Methods of estimating total area burned from the AVHRR fire scar map will be discussed and related to land use and scar size.

  17. Using MODIS and AVHRR data to determine regional surface heating field and heat flux distributions over the heterogeneous landscape of the Tibetan Plateau

    NASA Astrophysics Data System (ADS)

    Ma, Yaoming; Han, Cunbo; Zhong, Lei; Wang, Binbin; Zhu, Zhikun; Wang, Yongjie; Zhang, Lang; Meng, Chunchun; Xu, Chao; Amatya, Pukar Man

    2014-08-01

    In this study, a parameterization methodology based on Advanced Very High-Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and in situ data is proposed and tested for deriving the regional surface heating field, sensible heat flux, and latent heat flux over a heterogeneous landscape. In this case study, this method is applied to the whole Tibetan Plateau (TP) area. Four sets of AVHRR data and four sets of MODIS data (collected on 17 January 2003, 14 April 2003, 23 July 2003, and 16 October 2003) were used in this study to make comparisons between winter, spring, summer, and autumn values. The satellite-derived results were also validated using the "ground truth" as measured in the stations of CAMP/Tibet (Coordinated Enhanced Observing Period (CEOP) and Asia-Australia Monsoon Project on the Tibetan Plateau). The results show that the surface heating field, sensible heat flux, and latent heat flux in the four seasons across the TP are in close accordance with its land surface status. These parameters range widely due to the strongly contrasting surface features found within the TP region. Also, the estimated surface heating field, sensible heat flux, and latent heat flux all agree with the ground truth data, and usually, the absolute percentage difference between the two sets of data is less than 10 % at the validation stations. The AVHRR results were also in agreement with the MODIS data, with the latter usually displaying a higher level of accuracy. We have thus concluded that the proposed method was successful in retrieving surface heating field, sensible heat flux, and latent heat flux values using AVHRR, MODIS, and in situ data over the heterogeneous land surface of the TP. Shortcomings and possible further improvements in the method are also discussed.

  18. Use of NOAA-N satellites for land/water discrimination and flood monitoring

    NASA Technical Reports Server (NTRS)

    Tappan, G.; Horvath, N. C.; Doraiswamy, P. C.; Engman, T.; Goss, D. W. (Principal Investigator)

    1983-01-01

    A tool for monitoring the extent of major floods was developed using data collected by the NOAA-6 advanced very high resolution radiometer (AVHRR). A basic understanding of the spectral returns in AVHRR channels 1 and 2 for water, soil, and vegetation was reached using a large number of NOAA-6 scenes from different seasons and geographic locations. A look-up table classifier was developed based on analysis of the reflective channel relationships for each surface feature. The classifier automatically separated land from water and produced classification maps which were registered for a number of acquisitions, including coverage of a major flood on the Parana River of Argentina.

  19. Seasonal variability of surface runoff for different land-use types in alpine landscapes

    NASA Astrophysics Data System (ADS)

    Leitinger, G.; Tappeiner, U.; Newesely, Ch.; Obojes, N.; Tasser, E.

    2009-04-01

    Knowledge of surface runoff quantity for distinct hydrological units becomes increasingly important as many rainfall-runoff models use static surface runoff coefficients and therefore neglect eco-hydrological diversity. Especially in small-scale alpine catchments surface runoff and its contribution to mountain torrent runoff is frequently underestimated. Alpine ecosystems are faced with a rapid shift in vegetation patterns due to climate and also land-use change, which alters hydrological behavior in short timescales, even within a season. In a study in the Eastern Alps, Stubai Valley, Austria, surface runoff was investigated by using a rain simulator and accompanying soil water content and soil water tension measurements in different soil depths. Additionally, soil type, soil physical properties and phytomass were assessed. Analyzing more than 40 sprinkler experiments revealed significantly different surface runoff coefficients for different land-use / land-cover types. Moreover, managed areas revealed a clear seasonal variability of surface runoff. The results infer the necessity to consider intensity, duration and date of management when quantifying surface runoff. In other words, as surface runoff reaches the catchment outlet very quickly, water levels will raise much more than for very similar conditions at another date of the season. While almost no surface runoff occurred on abandoned areas, pastures showed high seasonal variability with surface runoff coefficients between 0% and 25%. The results are linked to land-cover type and soil physical properties, among which bulk density and resulting infiltration rates turned out to be most decisive. On pastures soil compaction by grazing cattle could increase stream flow dramatically. However, soil compaction in upper horizons (A-horizon, < 10cm soil depth) was reduced by freeze-and-thaw processes during the winter season. Thereby bulk density decreased and infiltration rates increased. The duration of this

  20. Seasonal shifts in body temperature and use of microhabitats by Galapagos land iguanas (Conolophus pallidus)

    SciTech Connect

    Christian, K.; Tracy, C.R.; Porter, W.P.

    1983-06-01

    Seasonal differences in the body temperatures (T/sub b/) of free-ranging Galapagos land iguanas (Conolophus pallidus) were detected by temperature sensitive telemetry transmitters. Midday T/sub b/'s of iguanas average 4.4/sup 0/C lower in the Garua (cool) season than in the Hot season. Measured T/sub b/'s and those predicted from biophysical models permitted the following conclusions: (1) lower T/sub b/'s during the Garua season represent an active shift in thermoregulation by the iguanas rather than a passive result of a cooler season; (2) the average midday T/sub b/ selected by the iguanas in either season is the T/sub b/ that allows maintenance of a constant T/sub b/ for the longest possible portion of the day; (3) by exploiting the warmer microclimate created by a cliff face, the iguanas are able to maintain a constant T/sub b/ for a full hour longer than they could elsewhere in their home range. Census data demonstrated that the iguanas exploited the warmer microclimate created by the cliff extensively during the Garua season, and the cliff face was visited by the iguanas relatively infrequently during the Hot season. Thus, the exploitation of the microclimate created by the cliff results in seasonal differences in the pattern of space utilization within the home ranges of the iguanas. Within the Garua season the iguanas moved away from the cliff more often on sunny days than during cloudy days. It is concluded that the physical environment is an important determinant of patterns of space utilization both within and between seasons.

  1. The impact of quantified land surface uncertainties on seasonal forecast skill

    NASA Astrophysics Data System (ADS)

    MacLeod, D.

    2015-12-01

    The land surface is a key component in seasonal forecasting, and well-represented soil moisture is particularly important for the simulation of heatwaves. Methods to represent uncertainties in the atmosphere of climate models have been shown to improve forecasts. However these methods have not yet been applied to the land surface component of climate models. We consider three methods of incorporating uncertainties into CHTESSEL, the land surface model of the ECMWF forecasting system. These methods are: stochastic perturbation of soil moisture tendencies, static and then stochastic perturbation of key soil parameters. We present analysis of the results of fully coupled seasonal hindcasts with each method applied. We find significant improvement for extreme events, particularly in terms of forecast reliability of upper and lower quintile soil moisture. These improvements also propagate into the atmosphere, impacting the reliability of seasonal-average predictions of latent and sensible heat flux anomalies and air temperature. This improvement is consistent over the hindcast, and also for particular cases such as the 2003 European summer (MacLeod et al 2015). We also present work with an uncoupled version of CHTESSEL. Extending the method of Wood & Lettenmaier (2008), we quantify the global evolution over forecast lead-time of the relative magnitudes of initial condition, forcing and parameter uncertainty in the land surface. Among other things this gives some indication of where predictability from initial conditions is more persistent, and where uncertainty in land surface parameters has the largest impact on simulated soil moisture. MacLeod DA, CLoke, HL, Pappenberger F and Weisheimer AF (2015), Improved seasonal prediction of the hot summer of 2003 through better representation of uncertainty in the land surface, QJRMSWood, AW, and Lettenmaier DP (2008), An ensemble approach for attribution of hydrologic prediction uncertainty, GRL

  2. Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales.

    PubMed

    Pratt, Bethany; Chang, Heejun

    2012-03-30

    The relationship among land cover, topography, built structure and stream water quality in the Portland Metro region of Oregon and Clark County, Washington areas, USA, is analyzed using ordinary least squares (OLS) and geographically weighted (GWR) multiple regression models. Two scales of analysis, a sectional watershed and a buffer, offered a local and a global investigation of the sources of stream pollutants. Model accuracy, measured by R(2) values, fluctuated according to the scale, season, and regression method used. While most wet season water quality parameters are associated with urban land covers, most dry season water quality parameters are related topographic features such as elevation and slope. GWR models, which take into consideration local relations of spatial autocorrelation, had stronger results than OLS regression models. In the multiple regression models, sectioned watershed results were consistently better than the sectioned buffer results, except for dry season pH and stream temperature parameters. This suggests that while riparian land cover does have an effect on water quality, a wider contributing area needs to be included in order to account for distant sources of pollutants. PMID:22277338

  3. Evaluating atmospheric correction models for retrieving surface temperatures from the AVHRR over a tallgrass prairie

    NASA Technical Reports Server (NTRS)

    Cooper, D. I.; Asrar, G.

    1989-01-01

    The effects of atmospheric attenuation on surface radiative temperatures obtained by the AVHRR over a tallgrass prairie area in the Flint Hills of Kansas are examined. Six atmospheric correction models developed primarily for sea-surface temperature studies are used to test their utility for retrieval of radiative temperatures over the land surface. An uncertainty of + or - 3.0 C was found for the AVHRR data, and used to evaluate the performance of a given model. When the difference between in situ and AVHRR surface temperatures was smaller than the uncertainty, the model was judged to be adequate. Among the six models evaluated, only the NOAA split-window model consistently adjusted the AVHRR surface temperatures within + or - 3.0 C of the in situ measurements.

  4. NOAA AVHRR and its uses for rainfall and evapotranspiration monitoring

    NASA Technical Reports Server (NTRS)

    Kerr, Yann H.; Imbernon, J.; Dedieu, G.; Hautecoeur, O.; Lagouarde, J. P.

    1989-01-01

    NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) Global Vegetation Indices (GVI) were used during the 1986 rainy season (June-September) over Senegal to monitor rainfall. The satellite data were used in conjunction with ground-based measurements so as to derive empirical relationships between rainfall and GVI. The regression obtained was then used to map the total rainfall corresponding to the growing season, yielding good results. Normalized Difference Vegetation Indices (NDVI) derived from High Resolution Picture Transmission (HRPT) data were also compared with actual evapotranspiration (ET) data and proved to be closely correlated with it with a time lapse of 20 days.

  5. Towards a Remote Sensing Based Assessment of Land Susceptibility to Degradation: Examining Seasonal Variation in Land Use-Land Cover for Modelling Land Degradation in a Semi-Arid Context

    NASA Astrophysics Data System (ADS)

    Mashame, Gofamodimo; Akinyemi, Felicia

    2016-06-01

    Land degradation (LD) is among the major environmental and anthropogenic problems driven by land use-land cover (LULC) and climate change worldwide. For example, poor LULC practises such as deforestation, livestock overstocking, overgrazing and arable land use intensification on steep slopes disturbs the soil structure leaving the land susceptible to water erosion, a type of physical land degradation. Land degradation related problems exist in Sub-Saharan African countries such as Botswana which is semi-arid in nature. LULC and LD linkage information is still missing in many semi-arid regions worldwide.Mapping seasonal LULC is therefore very important in understanding LULC and LD linkages. This study assesses the impact of seasonal LULC variation on LD utilizing Remote Sensing (RS) techniques for Palapye region in Central District, Botswana. LULC classes for the dry and rainy seasons were classified using LANDSAT 8 images at Level I according to the Food and Agriculture Organization (FAO) International Organization of Standardization (ISO) code 19144. Level I consists of 10 LULC classes. The seasonal variations in LULC are further related to LD susceptibility in the semi-arid context. The results suggest that about 985 km² (22%) of the study area is susceptible to LD by water, major LULC types affected include: cropland, paved/rocky material, bare land, built-up area, mining area, and water body. Land degradation by water susceptibility due to seasonal land use-land cover variations is highest in the east of the study area where there is high cropland to bare land conversion.

  6. Seasonal greenness variations in Amazon transitional forests in response to light, moisture, and land use

    NASA Astrophysics Data System (ADS)

    Ratana, P.; Huete, A. R.; Davies, K.; Restrepo-Coupe, N.

    2014-12-01

    The Amazon basin consists of structurally diverse tropical forest ecosystems resulting from unique functional responses to seasonal rainfall and radiation drivers, as well as fire and land use pressures. Dry season intensity and duration increase from the tropical wet rainforests at the equator to cerrado at the south, with transitional forests (dry forest, semi-deciduous forests, and cerradão) and the arc of deforestation between the two large biomes. Little known of this distinctive transitional forest composition and functional types, yet this zone is disappearing rapidly due to anthropological pressure and warming events. We hypothesize that these gradients in light, moisture, land use pressures, and forest functional types should be expressed in distinct canopy-level seasonal responses observable in satellite time series data. Yet, recent studies have raised concerns of concurrent seasonal sun geometry influences that confound the interpretation of satellite-derived greenness and suggest that observed tropical forest seasonality are optical artifacts of shifting sun- sensor view geometries. In this study we investigated forest seasonal variations and greenness dynamics across the transition zone, with 10+ years (2003-2013) of Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) data derived from the MCD43A1 product, for a fixed sun angle and fully corrected for sun- sensor view geometries. EVI values were extracted across two latitudinal transects across the Amazon transition zone sampling the eastern and central regions of the basin. We found a clear pattern of shifting forest greenness seasonality resulting from earlier onsets of the dry season from south to the north, irrespective of, and asynchronous with the solstice to equinox sun-earth geometry. From this seasonal profiles dry season greening in the wet forests and browning in the southern tropical dry forests could be observed. In many of the transitional forests, a

  7. A new net primary production estimating model using NOAA-AVHRR applied to the Haihe Basin, China

    NASA Astrophysics Data System (ADS)

    Xu, Xingang; Wu, Bingfang; Li, Qiangzi; Meng, Jihua; Zhang, Fengli

    2006-10-01

    Terrestrial net primary production (NPP), as an important component of carbon cycle on land, not only indicates directly the production level of vegetation community on land, but also shows the status of terrestrial ecosystem. What's more, NPP is also a determinant of carbon sinks on land and a key regulator of ecological processes, including interactions among tropic levels. In the study, three existing models are combined with each other to assess net primary production in Haihe Basin, China. The photosynthetically active radiation (PAR) model of Monteith is used for the calculation of absorbed photosynthetically active radiation (APAR), the light utilization efficiency model of Potter et al. is used for determining the light utilization efficiency, and the surface energy balance system (SEBS) of Su is used into Potter's model to describe water stress in land wetness conditions. To assess NPP, We use NOAA-AVHRR data from November 2003 to September 2004 and the corresponding daily data of temperature and hours of sunshine obtained from meteorological stations in Haihe Basin, China. After atmospheric, geometrical and radiant corrections, every ten days NOAA data are processed to become an image of NDVI by means of the maximal value composition method (MVC) in order to eliminate some noises. Using these data, we compute NPP in spring season and spring season of 2004 in Haihe Basin, China. The result shows, in Haihe Basin, NPP for spring season is averaged to 336.10gC•m -2, and 709.16 gC•m -2 for autumn season. In spatial distribution, NPP is greater in both ends than in middle for spring season, and decrease increasingly from north to south for autumn season. Future work should rely on the integration of high and low resolution images to assess net primary production, which will probably have more accurately estimation.

  8. Seasonal evolution of ecohydrological controls on land surface temperature over complex terrain

    NASA Astrophysics Data System (ADS)

    Xiang, Tiantian; Vivoni, Enrique R.; Gochis, David J.

    2014-05-01

    The spatiotemporal distribution of Land Surface Temperature (LST) is linked to the partitioning of the coupled surface water and energy budgets. In watersheds with a strong seasonality in precipitation and vegetation cover, the temporal evolution of LST patterns are a signature of the interactions between the land surface and atmosphere. Nevertheless, few studies have sought to understand the topographical and ecohydrological controls on LST in regions of complex terrain. Numerical watershed models, tested against spatially distributed field and remote sensing data, can aid in linking the seasonal evolution of LST to meteorology, terrain, soil, and vegetation. In this study, we use a distributed hydrologic model to explore LST patterns in a semiarid mountain basin during the transition from a dry spring to the wetter North American monsoon (NAM). By accounting for vegetation greening through remotely sensed parameters, the model reproduces LST and surface soil moisture observations derived from ground, aircraft, and satellite platforms with good accuracy at individual sites and as spatial basin patterns. Distributed simulations reveal how LST varies with elevation, slope, and aspect and the role played by the seasonal vegetation canopy in cooling the land surface and increasing the spatial variability in LST. As a result, LST is shown to track well with ecosystem-specific changes in vegetation cover, evapotranspiration, and soil moisture during the NAM. Furthermore, vegetation greening is shown to modulate the spatial heterogeneity of LST during the NAM that should be considered in subsequent atmospheric studies in regions of complex terrain.

  9. Typification of Natural Seasonal Dynamics of Vegetation to Reveal Impact of Land Surface Change on Environment (by Satellite Data)

    NASA Astrophysics Data System (ADS)

    Shevyrnogov, A.; Vysotskaya, G.; Sidko, A.; Dunaev, K.

    Deep insight into types of vegetation variability provided by AVHRR space scanner images of vegetation index spatial distribution helps reveal impact of land surface changes on environment.The Institute of Computational Modeling SB RAS has developed nonparametric algorithms of automatic to classify and recognize patterns of these images which helped to reveal: (1) major variability types (generally connected); (2) areas belonging to small classes, which can be used to reveal deviations from ``normal'' (e.g., forest fires, etc.); (3) deviation from a certain type of dynamics indicative of changes in condition of plants, which can be used to diagnose pathology at early stages; (4) impact of economical activities on vegetation in Norilsk area. The authors provide biological interpretation of the satellite data. Computer-animated dynamics and color maps are presented. Nonparametric algorithms of an automatic classification and pattern recognition were provided by the Institute of Computational Modeling SB RAS

  10. Land surface phenologies and seasonalities using cool earthlight in mid-latitude croplands

    NASA Astrophysics Data System (ADS)

    Alemu, W. G.; Henebry, G. M.

    2013-12-01

    Phenology deals with timing of biotic phenomena and seasonality concerns temporal patterns of abiotic variables. Studies of land surface phenology (LSP) and land surface seasonality (LSS) have long been limited to visible to near infrared (VNIR) wavelengths, despite degradation by atmospheric effects and solar illumination constraints. Enhanced land surface parameters derived from passive microwave data enable improved temporal monitoring of agricultural land surface dynamics compared to the vegetation index data available from VNIR data. LSPs and LSSs in grain growing regions of the Volga River Basin of Russia and the spring wheat belts of the USA and Canada were characterized using AMSR-E enhanced land surface parameters for the period from April through October for 2003 through 2010. Growing degree-days (GDDs) were calculated from AMSR-E air temperature retrievals using both ascending and descending passes with a base of 0 ° C and then accumulated (AGDD) with an annual restart each 1 April. Tracking the AMSR-E parameters as a function of AGDD revealed the expected seasonal pattern of thermal limitation in mid-latitude croplands. Vegetation optical depth (VOD), a microwave analog of a vegetation index, was modeled as a function of AGDD with the resulting fitted convex quadratic models yielding both high coefficients of determination (r2 > 0.90) and phenometrics that could characterize cropland differences between the Russian and North American sites. The AMSR-E data were also able to capture the effects of the 2010 heat wave that devastated grain production in European Russia. These results showed the potential of AMSR-E in monitoring and modeling cropland dynamics.

  11. Application of Satellite Data for Early Season Assessment of Fallowed Agricultural Lands for Drought Impact Reporting

    NASA Astrophysics Data System (ADS)

    Rosevelt, C.; Melton, F. S.; Johnson, L.; Verdin, J. P.; Thenkabail, P. S.; mueller, R.; Zakzeski, A.; Jones, J.

    2013-12-01

    Rapid assessment of drought impacts can aid water managers in assessing mitigation options, and guide decision making with respect to requests for local water transfers, county drought disaster designations, or state emergency proclamations. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and land fallowing associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. Here we describe an approach for monthly mapping of land fallowing developed as part of a joint effort by USGS, USDA, and NASA to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of fallowed land from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of normalized difference vegetation index (NDVI) data from Landsat TM, ETM+, and MODIS. Our effort has been focused on development of leading indicators of drought impacts in the March - June timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. This capability complements ongoing work by USDA to produce and publicly release within-season estimates of fallowed acreage from the USDA Cropland Data Layer. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted along transects across the Central Valley at more than 200 fields per month from March - June, 2013. Here we present the algorithm for mapping fallowed acreage early in the season along with results from the accuracy assessment, and discuss potential applications to other regions.

  12. Phenology Monitoring in Alaska with GLOBE Data, AVHRR NDVI and the CLAVR Algorithm

    NASA Astrophysics Data System (ADS)

    Robin, J.; Dubayah, R.; Sparrow, E.; Levine, E.

    2005-12-01

    Since 1999, GLOBE students have made over 75,000 phenology measurements at or near their schools and have reported annual dates for bud burst, green-up, leaf growth, and green-down for selected trees, shrubs, and grasses. Students in Alaska have collected nearly half the phenology data. This data set, largely untapped for scientific purposes, provides an exceptional means to validate satellite-derived phenology for Alaska. In this research we analyze the efficacy of phenology monitoring using maximum AVHRR Normalized Difference Vegetation Index (NDVI) composites, both 7 and 14 day, with the CLAVR (Clouds from AVHRR) cloud detection algorithm. Phenology metrics for Anchorage and Fairbanks were calculated from AVHRR. Metrics included start, end, and length of growing seasons for 2001 through 2004. Corresponding field measurements and observations made by GLOBE students in or near Anchorage and Fairbanks were used to validate the derived phenology metrics. Overall, the students' data showed that budburst occurred earlier in 2003 and 2004 while the derived AVHRR phenology metrics showed earlier budburst for 2002 and 2004. This research provides important lessons regarding how well maximum NDVI compositing of AVHRR data and the CLAVR algorithm perform in northern regions (latitudes 60 degrees and greater). These results are applicable to the future National Polar-Orbiting Operational Environmental Satellite System (NPOESS) monthly gridded NDVI product from the Visible Infrared Imager Radiometer Suite (VIIRS), the AVHRR NDVI product successor.

  13. Detecting Land Cover Change by Trend and Seasonality of Remote Sensing Time Series

    NASA Astrophysics Data System (ADS)

    Oliveira, J. C.; Epiphanio, J. N.; Mello, M. P.

    2013-05-01

    Natural resource managers demand knowledge of information on the spatiotemporal dynamics of land use and land cover change, and detection and characteristics change over time is an initial step for the understanding of the mechanism of change. The propose of this research is the use the approach BFAST (Breaks For Additive Seasonal and Trend) for detects trend and seasonal changes within Normalized Difference Vegetation Index (NDVI) time series. BFAST integrates the decomposition of time series into trend, seasonal, and noise components with methods for detecting change within time series without the need to select a reference period, set a threshold, or define a change trajectory. BFAST iteratively estimates the time and number of changes, and characterizes change by its magnitude and direction. The general model is of the form Yt = Tt + St + et (t= 1,2,3,…, n) where Yt is the observed data at time t, Tt is the trend component, St is the seasonal component, and et is the remainder component. In this study was used MODIS NDVI time series datasets (MOD13Q1) over 11 years (2000 - 2010) on an intensive agricultural area in Mato Grosso - Brazil. At first it was applied a filter for noise reduction (4253H twice) over spectral curve of each MODIS pixel, and subsequently each time series was decomposed into seasonal, trend, and remainder components by BFAST. Were detected one abrupt change from a single pixel of forest and two abrupt changes on trend component to a pixel of the agricultural area. Figure 1 shows the number of phonological change with base in seasonal component for study area. This paper demonstrated the ability of the BFAST to detect long-term phenological change by analyzing time series while accounting for abrupt and gradual changes. The algorithm iteratively estimates the dates and number of changes occurring within seasonal and trend components, and characterizes changes by extracting the magnitude and direction of change. Changes occurring in the

  14. Analysis of regional-scale vegetation dynamics of Mexico using stratified AVHRR NDVI data. [Normalized Difference Vegetaion Index

    NASA Technical Reports Server (NTRS)

    Turcotte, Kevin M.; Kramber, William J.; Venugopal, Gopalan; Lulla, Kamlesh

    1989-01-01

    Previous studies have shown that a good relationship exists between AVHRR Normalized Difference Vegetation Index (NDVI) measurements, and both regional-scale patterns of vegetation seasonality and productivity. Most of these studies used known samples of vegetation types. An alternative approach, and the objective was to examine the above relationships by analyzing one year of AVHRR NDVI data that was stratified using a small-scale vegetation map of Mexico. The results show that there is a good relationship between AVHRR NDVI measurements and regional-scale vegetation dynamics of Mexico.

  15. Seasonal temperature responses to land-use change in the western United States

    USGS Publications Warehouse

    Kueppers, L.M.; Snyder, M.A.; Sloan, L.C.; Cayan, D.; Jin, J.; Kanamaru, H.; Kanamitsu, M.; Miller, N.L.; Tyree, Mary; Du, H.; Weare, B.

    2008-01-01

    In the western United States, more than 79 000??km2 has been converted to irrigated agriculture and urban areas. These changes have the potential to alter surface temperature by modifying the energy budget at the land-atmosphere interface. This study reports the seasonally varying temperature responses of four regional climate models (RCMs) - RSM, RegCM3, MM5-CLM3, and DRCM - to conversion of potential natural vegetation to modern land-cover and land-use over a 1-year period. Three of the RCMs supplemented soil moisture, producing large decreases in the August mean (- 1.4 to - 3.1????C) and maximum (- 2.9 to - 6.1????C) 2-m air temperatures where natural vegetation was converted to irrigated agriculture. Conversion to irrigated agriculture also resulted in large increases in relative humidity (9% to 36% absolute change). Modeled changes in the August minimum 2-m air temperature were not as pronounced or consistent across the models. Converting natural vegetation to urban land-cover produced less pronounced temperature effects in all models, with the magnitude of the effect dependent upon the preexisting vegetation type and urban parameterizations. Overall, the RCM results indicate that the temperature impacts of land-use change are most pronounced during the summer months, when surface heating is strongest and differences in surface soil moisture between irrigated land and natural vegetation are largest. ?? 2007 Elsevier B.V. All rights reserved.

  16. Alternative Approaches to Land Initialization for Seasonal Precipitation and Temperature Forecasts

    NASA Technical Reports Server (NTRS)

    Koster, Randal; Suarez, Max; Liu, Ping; Jambor, Urszula

    2004-01-01

    The seasonal prediction system of the NASA Global Modeling and Assimilation Office is used to generate ensembles of summer forecasts utilizing realistic soil moisture initialization. To derive the realistic land states, we drive offline the system's land model with realistic meteorological forcing over the period 1979-1993 (in cooperation with the Global Land Data Assimilation System project at GSFC) and then extract the state variables' values on the chosen forecast start dates. A parallel series of forecast ensembles is performed with a random (though climatologically consistent) set of land initial conditions; by comparing the two sets of ensembles, we can isolate the impact of land initialization on forecast skill from that of the imposed SSTs. The base initialization experiment is supplemented with several forecast ensembles that use alternative initialization techniques. One ensemble addresses the impact of minimizing climate drift in the system through the scaling of the initial conditions, and another is designed to isolate the importance of the precipitation signal from that of all other signals in the antecedent offline forcing. A third ensemble includes a more realistic initialization of the atmosphere along with the land initialization. The impact of each variation on forecast skill is quantified.

  17. Links between land use change and recent dry season droughts in Amazonia

    NASA Astrophysics Data System (ADS)

    Khanna, J.; Medvigy, D.

    2012-12-01

    The Amazon region experienced catastrophic and unusually severe droughts in 2005 and 2010. These two droughts were phenomenologically different from the other, more common, El Niño-related droughts. Whereas El Niño-related droughts mostly affect the eastern and south-eastern parts of the region during the wet season (December-March), the droughts of 2005 and 2010 were most severe during the dry season (June-August) and affected the southern and western parts of the Amazon. A global warming driven mechanism has been suggested for these droughts wherein decreased moisture transport into the basin during the dry season is caused by anomalously high tropical north Atlantic SSTs, which weaken the northern hemisphere Hadley cell. But the facts that dry season droughts have been historically rare in this region and that the 2005 and 2010 droughts were strongest around locations of recent land use change activity suggest that deforestation may be contributing to this inter-annual variability in precipitation. This study addresses this research question by numerically modeling the 2005 and 2010 drought events for two land use scenarios, one of which (Deforested or DEF) represents the current state of land use in the Amazon and the other (Pristine Forest or PRF) represents a scenario of no deforestation. A variable resolution GCM, the Ocean-Land-Atmosphere Model (OLAM), is used to model these events. Land surface processes and soil moisture during the drought period are simulated using the Land Ecosystem Atmosphere Feedback model. The state of land cover in the Amazon in the two drought years is obtained from satellite-based land cover maps. The land grid has a variable resolution ranging from ≈75km in the South American sector to ≈200km elsewhere. This variable-resolution approach helps resolve topographic features and the medium-to-large scale land use patches in the Amazon area. The atmospheric runs are forced by National Oceanic and Atmospheric Administration

  18. Establishment of warm-season native grasses and forbs on drastically disturbed lands

    SciTech Connect

    Miller, S.

    1998-12-31

    Establishment of warm-season native grasses and forbs (WSNGs) has been viewed by landowners, agronomists, natural resource managers and reclamation specialists as being too expensive and difficult, especially for reclamation, which requires early stand closure and erosion control. Natural resource managers have learned a great deal about establishing WSNGs since the implementation of the 1985 Farm Bill`s Conservation Reserve Program (CRP). Reclamation specialists must begin to use this information to improve reclamation success. Quality control of seed equipment and planting methods has been proven to be the crucial first step in successful establishment. Seedling germination, growth and development of WSNGs are different from that of introduced cool-season grasses and legumes. Specialized seed drills and spring planting periods are essential. Because shoot growth lags far behind root growth the first two seasons, WSNGs often are rejected for reclamation use. Usually, the rejection is based on preconceived notions that bare ground will erode and on reclamation specialists` desire for a closed, uniform, grassy lawn. WSNG`s extensive root systems inhibit rill and gully erosion by the fall of the first season. Planting a weakly competitive, short-lived nurse crop such as perennial ryegrass (Lolium perenne) at low rates with the WSNG mixture can reduce first-season sheet and rill erosion problems and give an appearance of a closed stand. Benefits of WSNGs in soil building and their acid-tolerance make them ideal species for reclamation of drastically disturbed lands. WSNGs and forbs enhance wildlife habitat and promote natural succession and the invasion of the reclamation site by other native species, particularly hardwood trees, increasing diversity and integrating the site into the local ecosystem. This is perhaps their most important attribute. Most alien grasses and legumes inhibit natural succession, slowing the development of a stable mine soil ecosystem. This

  19. Influence of seasonal cycles in Martian atmosphere on entry, descent and landing sequence

    NASA Astrophysics Data System (ADS)

    Marčeta, Dušan; Šegan, Stevo; Rašuo, Boško

    2014-05-01

    The phenomena like high eccentricity of Martian orbit, obliquity of the orbital plane and close alignment of the winter solstice and the orbital perihelion, separately or together can significantly alter not only the level of some Martian atmospheric parameters but also the characteristics of its diurnal and seasonal cycle. Considering that entry, descent and landing (EDL) sequence is mainly driven by the density profile of the atmosphere and aerodynamic characteristic of the entry vehicle. We have performed the analysis of the influence of the seasonal cycles of the atmospheric parameters on EDL profiles by using Mars Global Reference Atmospheric Model (Mars-GRAM). Since the height of the deployment of the parachute and the time passed from the deployment to propulsion firing (descent time) are of crucial importance for safe landing and the achievable landing site elevation we paid special attention to the influence of the areocentric longitude of the Sun (Ls) on these variables. We have found that these variables have periodic variability with respect to Ls and can be very well approximated with a sine wave function whose mean value depends only on the landing site elevation while the amplitudes and phases depend only on the landing site latitude. The amplitudes exhibit behavior which is symmetric with respect to the latitude but the symmetry is shifted from the equator to the northern mid-tropics. We have also noticed that the strong temperature inversions which are usual for middle and higher northern latitudes while Mars is around its orbital perihelion significantly alter the descent time without influencing the height of the parachute deployment. At last, we applied our model to determine the dependence of the accessible landing region on Ls and found that this region reaches maximum when Mars is around the orbital perihelion and can vary 50° in latitude throughout the Martian year.

  20. Predicting Future Temperate and Boreal of Growing Season Start With a Land Surface Model

    NASA Astrophysics Data System (ADS)

    Kaduk, J.

    2008-12-01

    Controlled ecological experiments show that temperate and boreal trees require chilling in winter for rapid leaf out in spring. If the amount of chilling falls below a species specific threshold then an exponentially increasing amount of warming is required to initiate leaf out - potentially actually delaying it in a future warmer climate. The boreal areas could be particularly affected as climate predictions indicate strong warming in these regions. Moreover, currently a large part of the land carbon sink is located in temperate and boreal regions and a changing growing season start might have a large impact on this important sink. Warming-chilling models for green-up, which have been calibrated with remotely sensed normalized difference vegetation index from the years 1983-1995, indicate that in future the chilling requirements reduce the rate of advance of the start of the growing season to earlier times compared to advance rates in the last two decades. Climate scenarios with large warming (IPCC A2 scenarios) show lower advance rates of green- up to earlier times than predictions with a smaller warming (B1 scenarios) due to the reduced chilling in high warming scenarios. When incorporated into a coupled land-surface carbon cycle model based on JULES (the Joint-UK-Land Environment Simulator) the chilling requirements lead to a early growing season photosynthetic carbon up that is correspondingly lower than in simulations where the start of the growing season as simply modelled as responding to warming only. Thus the phenological response in effect provides a positive feedback to global warming.

  1. Seasonal Dynamics of Water Use Strategy of Two Salix Shrubs in Alpine Sandy Land, Tibetan Plateau

    PubMed Central

    Zhu, Yajuan; Wang, Guojie; Li, Renqiang

    2016-01-01

    Water is a limiting factor for plant growth and vegetation dynamics in alpine sandy land of the Tibetan Plateau, especially with the increasing frequency of extreme precipitation events and drought caused by climate change. Therefore, a relatively stable water source from either deeper soil profiles or ground water is necessary for plant growth. Understanding the water use strategy of dominant species in the alpine sandy land ecosystem is important for vegetative rehabilitation and ecological restoration. The stable isotope methodology of δD, δ18O, and δ13C was used to determine main water source and long-term water use efficiency of Salix psammophila and S. cheilophila, two dominant shrubs on interdune of alpine sandy land in northeastern Tibetan Plateau. The root systems of two Salix shrubs were investigated to determine their distribution pattern. The results showed that S. psammophila and S. cheilophila absorbed soil water at different soil depths or ground water in different seasons, depending on water availability and water use strategy. Salix psammophila used ground water during the growing season and relied on shallow soil water recharged by rain in summer. Salix cheilophila used ground water in spring and summer, but relied on shallow soil water recharged by rain in spring and deep soil water recharged by ground water in fall. The two shrubs had dimorphic root systems, which is coincident with their water use strategy. Higher biomass of fine roots in S. psammophila and longer fine roots in S. cheilophila facilitated to absorb water in deeper soil layers. The long-term water use efficiency of two Salix shrubs increased during the dry season in spring. The long-term water use efficiency was higher in S. psammophila than in S. cheilophila, as the former species is better adapted to semiarid climate of alpine sandy land. PMID:27243772

  2. Seasonal Dynamics of Water Use Strategy of Two Salix Shrubs in Alpine Sandy Land, Tibetan Plateau.

    PubMed

    Zhu, Yajuan; Wang, Guojie; Li, Renqiang

    2016-01-01

    Water is a limiting factor for plant growth and vegetation dynamics in alpine sandy land of the Tibetan Plateau, especially with the increasing frequency of extreme precipitation events and drought caused by climate change. Therefore, a relatively stable water source from either deeper soil profiles or ground water is necessary for plant growth. Understanding the water use strategy of dominant species in the alpine sandy land ecosystem is important for vegetative rehabilitation and ecological restoration. The stable isotope methodology of δD, δ18O, and δ13C was used to determine main water source and long-term water use efficiency of Salix psammophila and S. cheilophila, two dominant shrubs on interdune of alpine sandy land in northeastern Tibetan Plateau. The root systems of two Salix shrubs were investigated to determine their distribution pattern. The results showed that S. psammophila and S. cheilophila absorbed soil water at different soil depths or ground water in different seasons, depending on water availability and water use strategy. Salix psammophila used ground water during the growing season and relied on shallow soil water recharged by rain in summer. Salix cheilophila used ground water in spring and summer, but relied on shallow soil water recharged by rain in spring and deep soil water recharged by ground water in fall. The two shrubs had dimorphic root systems, which is coincident with their water use strategy. Higher biomass of fine roots in S. psammophila and longer fine roots in S. cheilophila facilitated to absorb water in deeper soil layers. The long-term water use efficiency of two Salix shrubs increased during the dry season in spring. The long-term water use efficiency was higher in S. psammophila than in S. cheilophila, as the former species is better adapted to semiarid climate of alpine sandy land. PMID:27243772

  3. The role of antecedent land surface conditions in North American Monsoon warm season precipitation

    NASA Astrophysics Data System (ADS)

    Zhu, C.; Lettenmaier, D. P.; Cavazos, T.

    2005-12-01

    North American Monsoon (NAM) warm season precipitation strongly affects the semiarid regions of the southwestern U.S. and northwestern Mexico. A first step in developing useful prediction capabilities for NAM precipitation is to explore links between the NAM seasonal (JJAS) precipitation and the antecedent pre-monsoon (previous autumn, winter, and spring) land surface conditions, such as precipitation, surface air temperature, soil moisture, and snow cover. We define two monsoon regions: western in Arizona and eastern in New Mexico which exhibit a "pure" monsoon signal, and northwestern Mexico as the core NAM region. Land surface data for the east and west regions are monthly aggregates from the extended retrospective North American Land Data Assimilation System (N-LDAS) archive for the period 1950 to 1999, which includes gridded precipitation (P), mean surface air temperature (Ts), and Variable Infiltration Capacity (VIC) land surface model-derived soil moisture (Sm), and snow water equivalent (SWE). For northwestern Mexico three different sources of station data are combined and gridded to be analogous to the N-LDAS archive: Servicio MeterorolOgico Nacional (SMN) daily data (pre-1940 - 2003), SMN daily historical precipitation data (1995 - near real-time), and northwestern Mexico NAME Event Raingage Network (NERN) precipitation daily data (2002 - ). Long-term (1950-2003) retrospective VIC model runs were then performed to produce derived data (soil moisture, snow) analogous to those in the N-LDAS archive. Through correlation and composite analysis, we find that the two southwest US regions and northwestern Mexico exhibit somewhat different land surface feedback mechanism. For the U.S, regions, we previously proposed a land surface feedback hypothesis and found that while NAM precipitation is correlated with the previous winter's precipitation, the corresponding soil moisture anomaly contributes little to the predictability of NAM precipitation. For northwestern

  4. Seasonal ice cycle at the Mars Phoenix landing site: 2. Postlanding CRISM and ground observations

    NASA Astrophysics Data System (ADS)

    Cull, Selby; Arvidson, R. E.; Morris, R. V.; Wolff, M.; Mellon, M. T.; Lemmon, M. T.

    2010-05-01

    The combination of ground observations from the Mars Phoenix Lander and orbital data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) provided a detailed view of the formation of late summer surface water ice at the landing site and surrounding regions. CRISM observations of the landing site during and immediately after Phoenix operations were analyzed to track the seasonal and diurnal ice cycles during the late spring to late summer, and a nonlinear mixing model was used to estimate grain sizes and relative abundances of water ice and dust. The surface around the Phoenix landing site was ice-free from late spring through midsummer, although transient patches of mobile ices were observed in an 85 m diameter crater to the northeast of the landing site. At the ˜10 km diameter Heimdal Crater, located ˜10 km east of the landing site, permanent patches of water ice were observed to brighten during the late spring and darken during the summer, possibly as fine-grained water ice that was cold trapped onto the ice during late spring sintered into larger grains or finally sublimated, exposing larger-grained ice. CRISM spectra first show evidence of widespread ice during the night at solar longitude (Ls) ˜ 109°, ˜9 sols before Phoenix’s Surface Stereo Imager detected it. CRISM spectra first show evidence of afternoon surface ice and water ice clouds after Ls ˜ 155°, after Phoenix operations ended.

  5. GPS observations of seasonal crustal deformation and long-term land subsidence in response to water storage changes in California

    NASA Astrophysics Data System (ADS)

    Anderson, K. J.; De Linage, C.; Famiglietti, J. S.

    2011-12-01

    Observations of vertical land surface height from Scripps Orbit and Permanent Array Center (SOPAC) GPS stations throughout California and the Western United States reveal significant seasonal and long-term land surface responses to water storage changes. Long-term land surface subsidence in the Central Valley is due to aquifer compaction resulting from ongoing groundwater depletion. Seasonal motion of the land surface due to elastic crustal loading provides insight about seasonal surface water loads such as snow water equivalent, soil moisture, and reservoir storage. This research explores the relationship between water storage changes observed by GRACE and Snotel and the land surface responses observed by GPS, and the potential for new applications of GPS for monitoring various components of water storage.

  6. Comparison of MODIS and AVHRR 16-day normalized difference vegetation index composite data

    USGS Publications Warehouse

    Gallo, K.; Ji, L.; Reed, B.; Dwyer, J.; Eidenshink, J.

    2004-01-01

    Normalized difference vegetation index (NDVI) data derived from visible and near-infrared data acquired by the MODIS and AVHRR sensors were compared over the same time periods and a variety of land cover classes within the conterminous USA. The relationship between the AVHRR derived NDVI values and those of future sensors is critical to continued long term monitoring of land surface properties. The results indicate that the 16-day composite values are quite similar over the 23 intervals of 2001 that were analyzed, and a linear relationship exists between the NDVI values from the two sensors. The composite AVHRR NDVI data were associated with over 90% of the variation in the MODIS NDVI values. Copyright 2004 by the American Geophysical Union.

  7. Seasonal variation of the land-sea breeze circulation in the Pearl River Delta region

    NASA Astrophysics Data System (ADS)

    Lu, Xi; Chow, Kim-Chiu; Yao, Teng; Fung, Jimmy C. H.; Lau, Alexis K. H.

    2009-09-01

    The data of a 1-year (2003-2004) simulation with a finest horizontal resolution of 1.5 km, using the Fifth-Generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5), were analyzed to investigate the seasonal-mean features of the land-sea breeze (LSB) and regional circulation over the Pearl River Delta (PRD) region in southern China. The seasonal-mean diurnal variations reveal the general patterns of the LSB in the four seasons. These small-scale mean flow fields in the region have not been revealed in any previous studies. The results reveal a strong anomalous westerly sea breeze toward the eastern coast of the PRD in the early afternoon that is present in all the four seasons but is particularly strong in autumn and winter and may enhance the low-level convergence in Hong Kong. Furthermore, the condition of the atmosphere in autumn and winter is much more stable when compared with that in spring and summer, which is not favorable for the vertical dispersion of pollutants. The overall effect of these mean meteorological conditions may be an important factor for the generally higher air pollution index observed in Hong Kong during autumn and winter.

  8. Non-growing season soil CO2 efflux patterns in five land-use types in northern China

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Overgrazing and unsuitable farming practices have led to grassland degradation in northern China. This studhy examined soil CO2 efflux (Fc) from five land-use types during the non-growing season on the southeastern edge of the Mongolian Plateau in China. The land-use types included three native v...

  9. Cropland land surface phenology and seasonality in East Africa: Ethiopia, Tanzania, and South Sudan

    NASA Astrophysics Data System (ADS)

    Alemu, W. G.; Henebry, G. M.

    2015-12-01

    Most people in East Africa depend on rainfed agriculture. Rainfall in the region has been decreasing recently and is highly variable in space and time leading to high food insecurity. A comprehensive understanding of the regional cropland dynamics is therefore needed. Land surface phenology and land surface seasonality have important roles in monitoring cropland dynamics in a region with sparse coverage of in situ climatic and biophysical observations. However, commonly used optical satellite data are often degraded by cloud cover, aerosols, and dust and they are restricted to daytime observations. Here we used near-daily passive microwave (PM) data at 25 km spatial resolution from a series of microwave radiometers—AMSR-E, FengYun3B/MWRI, AMSR2—to study cropland dynamics for 2003-2013 in three important grain production areas of East Africa: Ethiopia, Tanzania, and South Sudan. PM data can be collected through clouds and at night. Based on Google Earth imagery, we identified several cropland areas corresponding to PM grid cells. Rainfall from TRMM and atmospheric water vapor (V) from PM data displayed temporal patterns that were unimodal in Ethiopia and South Sudan, but bimodal in Tanzania. We fitted convex quadratic models to link growing season increments of V and vegetation optical depth (VOD) to accumulated V (AV). The models yielded high coefficients of determination (r2 ≥0.8) and phenometrics calculated from the parameter coefficients. Peak rainfall lagged peak V, but preceded peak VOD. Growing degree-days (GDD), calculated from the PM air temperature data, displayed a weaker bimodal seasonality in which the lowest values occurred during the peak rainy season, due to the cooling effect of latent heat flux and coupled with higher reflection of insolation by the cloud deck. V as a function of GDD displays quasi-periodic behavior. Drier sites in the region displayed larger (smaller) intra-annual dynamic range of V (GDD) compared to the moister sites.

  10. The Intra-Seasonal Variability of Land-Atmosphere Coupling over North America in CRCM5

    NASA Astrophysics Data System (ADS)

    Yang Kam Wing, G.; Sushama, L.; Diro, G. T.

    2015-12-01

    The intra-seasonal variability of land-atmosphere coupling for the mid- to high-latitude regions of North America is investigated using carefully designed experiments performed with the fifth generation Canadian Regional Climate Model (CRCM5). We ran a coupled CRCM5 simulation, where the land and the atmosphere interact freely, and an uncoupled CRCM5 simulation, where the soil moisture is prescribed, to evaluate the coupling strength under current climatic conditions. Both simulations were driven by ERA-Interim reanalysis for the 1981 - 2010 period at 0.44˚ horizontal resolution, over a North American domain. Analysis of the coupled and uncoupled simulations reveals that soil moisture/temperature coupling is strong over the Canadian Prairies during the summer, spring and fall seasons. The underlying mechanisms, however, vary with season. During the summer months, soil moisture affects the partitioning of net surface radiation into latent and sensible heat fluxes, which then influences the two-meter temperature through evaporative cooling. For the transition months (spring and fall), on the other hand, soil moisture variation - particularly moisture phase, i.e. the fractional liquid and frozen water contents, play a role in altering the surface albedo, which in turn modifies the absorbed shortwave and the emitted longwave radiations. In particular, the outgoing longwave radiation influences the two-meter temperature through radiative cooling. Surface temperature variability during the transition months is also reflected in the snow depth variability, which in turn affects surface albedo, emissivity and soil moisture again through a feedback loop. We also assessed the impact of coupling on temperature extremes during the transition seasons and found a strong relationship between coupling strength and the number of hot days during spring.

  11. Summer-Fall Seasonal Ices at the Mars Phoenix Landing Site: Results from CRISM Observations

    NASA Astrophysics Data System (ADS)

    Cull, S.; Arvidson, R. E.; Morris, R. V.; Wolff, M. J.; Mellon, M. T.; Lemmon, M. T.

    2009-12-01

    We combine ground observations from the Mars Phoenix lander with orbital data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) to chart the onset of seasonal ice at the landing site from late spring (solar longitude [Ls] ~ 84) to late summer (Ls] ~ 117) . We use 25 CRISM observations acquired directly over the landing site and 13 acquired near the landing site. We find that summer ice-free spectra at the Phoenix landing site are approximated by scattering properties similar to Gusev Crater soils. Summer spectra have the strong water absorption at 3 μm, indicating a low level of hydration or adsorption of water, an effect previously observed throughout the northern hemisphere. Patches of permanent water ice appear on the shadowed sides of Heimdal Crater and on the shadowed sides of large mountains to the northeast. These patches were monitored throughout the summer and did not appear to grow or shrink; however, the ice patches darken between Ls~119 and Ls~160, possibly due to the sublimation or sintering of fine-grained ices cold-trapped onto the ice deposits during the spring defrost period. Mobile patches of summertime ice were observed to follow the shadow of a crater wall on an ~85-m crater located ~6.5 km northeast of the landing site. Widespread surface ice was first observed at the Phoenix landing site during the night (3 a.m. Local True Solar Time [LTST]) at Ls~104, and water ice was first observed in the afternoon (3 p.m. LTST) at Ls~154. CRISM observations show the first afternoon water ice clouds at Ls~157. Phoenix Surface Stereo Imager (SSI) images first show evidence of afternoon (1 p.m. LTST) water ice in the shadows of large rocks on operations sol 80 (Ls~112), but did not observe widespread afternoon ice during the mission, which ended at Ls~149.

  12. Inference of the potential predictability of seasonal land-surface climate from AMIP ensemble integrations

    SciTech Connect

    Phillips, T.J.; Santer, B.D.

    1995-12-01

    A number of recent studies of the potential predictability of seasonal climate have utilized AGCM ensemble integrations--i.e., experiments where the atmospheric model is driven by the same ocean boundary conditions and radiative forcings, but is started from different initial states. However, only a few variables of direct relevance to the climate of the land surface have been examined. In this study, the authors infer the potential predictability of 11 climate variables that are indicative of the energetics, dynamics, and hydrology of the land surface. They used a T42Ll9 ECMWF (cycle 36) AGCM having a land-surface scheme with prognostic temperature and moisture of 2 layers occupying the topmost 0.50 meters of soil, but with monthly climatological values of these fields prescribed below. Six model realizations of decadal climate (for the period 1979--1988) were considered. In each experiment, the SSTs and sea ice extents were those specified for the Atmospheric Model Intercomparison Project (AMIP), and some radiative parameters were prescribed as well. However, the initial conditions of the model atmosphere and land surface were different: the first two simulations were initialized from ECMWF analyses, while the initial states of subsequent realizations were assigned values that were the same as those at the last time step of the preceding integration.

  13. Monitoring the inundation extent of the Florida Everglades with AVHRR data in a geographic information system

    NASA Technical Reports Server (NTRS)

    Pelletier, R. E.; Dow, D. D.

    1989-01-01

    The purpose of the study is to develop a geographical information system capable of estimating methane and other greenhouse trace-gas fluxes from the wetlands of the Florida Everglades. Advanced very-high-resolution radiometer (AVHRR) data collected on a near-monthly basis for a year in order to monitor the seasonal dynamics of inundation extent across the Everglades is utilized in the analysis. It is noted that AVHRR data presents advantages over other remote-sensing data sources employed in covering large geographical regions due to its daily coverage with multiple opportunities during a day. This temporal resolution allows the realistic expectation of acquiring data on a frequent basis.

  14. Automatic AVHRR image navigation software

    NASA Technical Reports Server (NTRS)

    Baldwin, Dan; Emery, William

    1992-01-01

    This is the final report describing the work done on the project entitled Automatic AVHRR Image Navigation Software funded through NASA-Washington, award NAGW-3224, Account 153-7529. At the onset of this project, we had developed image navigation software capable of producing geo-registered images from AVHRR data. The registrations were highly accurate but required a priori knowledge of the spacecraft's axes alignment deviations, commonly known as attitude. The three angles needed to describe the attitude are called roll, pitch, and yaw, and are the components of the deviations in the along scan, along track and about center directions. The inclusion of the attitude corrections in the navigation software results in highly accurate georegistrations, however, the computation of the angles is very tedious and involves human interpretation for several steps. The technique also requires easily identifiable ground features which may not be available due to cloud cover or for ocean data. The current project was motivated by the need for a navigation system which was automatic and did not require human intervention or ground control points. The first step in creating such a system must be the ability to parameterize the spacecraft's attitude. The immediate goal of this project was to study the attitude fluctuations and determine if they displayed any systematic behavior which could be modeled or parameterized. We chose a period in 1991-1992 to study the attitude of the NOAA 11 spacecraft using data from the Tiros receiving station at the Colorado Center for Astrodynamic Research (CCAR) at the University of Colorado.

  15. Winter Conditions and Land Cover Structure the Subnivium, A Seasonal Refuge beneath the Snow

    PubMed Central

    Petty, Sonia K.; Zuckerberg, Benjamin; Pauli, Jonathan N.

    2015-01-01

    In seasonally snow-covered environments, many organisms endure winter by using the subnivium, a below-snow thermally stable seasonal refugium. Because the insulation of snow is dependent on snow depth and density, the stability of temperatures within the subnivium varies across land cover types. Additionally, across much of the Northern Hemisphere snow extent, depth and duration are generally decreasing while snow density is increasing due to climate change. These changes are likely to destabilize the thermal profile of the subnivium, although they have not yet been quantified. To explore the effects of land cover and climate change on the subnivium, we measured snow pack characteristics (depth and density), and ambient and subnivium temperatures from three different land cover types (prairie, deciduous forest, and coniferous forest) and within a micro-greenhouse (2.5 x 2.5 x 2 m) that maintained a temperature of 5°C warmer than outdoor ambient temperatures, and automatically opened during snow events throughout the winter of 2013/14. We found that the mean daily subnivium temperature was significantly colder in the deciduous cover type than the prairie cover type, and that prairie had higher maximum subnivium temperatures than both of the other cover types. Our climate change simulation revealed that, although ambient temperatures within the micro-greenhouse were 5°C warmer than outside the greenhouse, the daily minimum subnivium temperature was significantly lower inside the greenhouse. Our findings suggest that climate change could have considerable effects on the refuge quality of the subnivium, and that some cover types appear to be more susceptible to these effects than others. PMID:26024489

  16. Calibration and Validation of the 36-year NOAA/AVHRR Imager Visible Channel Data record in support of the NOAA Climate Data Records program.

    NASA Astrophysics Data System (ADS)

    Gopalan, A.; Doelling, D.; Bhatt, R.; Scarino, B. R.; Bedka, K. M.; Minnis, P.

    2015-12-01

    The NOAA/AVHRR (Advanced Very High Resolution Radiometer) series of polar-orbiting earth-imagers have been flying since 1978 to the present and provide an opportunity to derive a long-term consistent set of well calibrated visible channel radiances for cloud, aerosol, and land use retrievals. This will allow climate modelers to investigate climate natural variability, intra-seasonal oscillations such as the ENSO, and feedback mechanisms over a 36-year record. Large climate perturbations, such as the 1982 and 1998 El Ninos as well as the 1982 El Chichon and 1992 Mt Pinatubo volcanic eruptions, have not been observed since 2000. The vicarious calibration method relies on temporally well characterized multiple pseudo-invariant calibration sites (PICS) referenced to the Aqua-MODIS calibration. The PICS are characterized by NOAA-16 TOA reflectances, over the full range of observed solar zenith angles of a NOAA degrading orbit culminating in a terminator orbit. The NOAA-16 reflectances are first calibrated against Aqua-MODIS using the simultaneous nadir overpass (SNO) method. Site characterization with NOAA-16 has the advantage of reducing the uncertainties associated with spectral band adjustments, since the AVHRR sensor spectral responses are similar. Consistent calibration between the individual desert, polar ice and deep convective cloud PICS approaches validates the methodology. The individual calibration gains are combined to provide the final merged calibration by weighting them by the inverse of their temporal variance. By combining by site stability ensures that site anomalous reflectance drifts do not adversely impact the calibration. Also the merged gain has a lower temporal variability than any individual PICS. In this study we describe the methodology used to derive a new set of calibration coefficients for Channel-1 0.65 (um) and Channel-2 (0.86 um) of the NOAA/AVHRR series of Polar-Orbiting imagers beginning in 1978. We will demonstrate the consistency of

  17. Impact of land-surface elevation and riparian evapotranspiration seasonality on groundwater budget in MODFLOW models

    NASA Astrophysics Data System (ADS)

    Ajami, Hoori; Meixner, Thomas; Maddock, Thomas; Hogan, James F.; Guertin, D. Phillip

    2011-09-01

    Riparian groundwater evapotranspiration (ETg) constitutes a major component of the water balance especially in many arid and semi-arid environments. Although spatial and temporal variability of riparian ETg are controlled by climate, vegetation and subsurface characteristics, depth to water table (DTWT) is often considered the major controlling factor. Relationships between ETg rates and DTWT, referred to as ETg curves, are implemented in MODFLOW ETg packages (EVT, ETS1 and RIP-ET) with different functional forms. Here, the sensitivity of the groundwater budget in MODFLOW groundwater models to ETg parameters (including ETg curves, land-surface elevation and ETg seasonality) are investigated. A MODFLOW model of the hypothetical Dry Alkaline Valley in the Southwestern USA is used to show how spatial representation of riparian vegetation and digital elevation model (DEM) processing methods impact the water budget when RIPGIS-NET (a GIS-based ETg program) is used with MODFLOW's RIP-ET package, and results are compared with the EVT and ETS1 packages. Results show considerable impact on ETg and other groundwater budget components caused by spatial representation of riparian vegetation, vegetation type, fractional coverage areas and land-surface elevation. RIPGIS-NET enhances ETg estimation in MODFLOW by incorporating vegetation and land-surface parameters, providing a tool for ecohydrology studies, riparian ecosystem management and stream restoration.

  18. Comparison of fire fuel maps produced using MSS and AVHRR data

    USGS Publications Warehouse

    Miller, Wayne A.; Johnston, David C.

    1985-01-01

    The fuel information, in support of the Bureau of Land Management's (BLM) national fire program, has been obtained through the manila interpretation of Landsat multi-spectral scanner images and digital image analysis of Advanced Very High Resolution Radiometer (AVHRR) data. The BLM, in cooperation with the Earth Resources Observation Systems Data Center, determined that the accuracy (approximately 90 percent overall) was similar for deriving fire fuel information for Malheur County in eastern Oregon using either approach, and for an area the size of Malheur County (6.4 million acres), the costs were about the same (0.19 cents per acre). But the cost per acre was substantially lower (0.04 cents) where digital analysis of AVHRR data were used to derive fire fuel information for a 42-million-acre area in eastern Oregon. Based on these results, the BLM is using digital analysis of AVHRR data to support its operational fire fuel mapping program.

  19. Arctic sea ice albedo from AVHRR

    SciTech Connect

    Lindsay, R.W.; Rothrock, D.A.

    1994-11-01

    The seasonal cycle of surface albedo of sea ice in the Arctic is estimated from measurements made with the Advanced Very High Resolution Radiometer (AVHRR) on the polar-orbiting satellites NOAA-10 and NOAA-11. The albedos of 145 200-km-square cells are analyzed. The cells are from March through September 1989 and include only those for which the sun is more than 10 deg above the horizon. Cloud masking is performed manually. Corrections are applied for instrument calibration, nonisotropic reflection, atmospheric interference, narrowband to broadband conversion, and normalization to a common solar zenith angle. The estimated albedos are relative, with the instrument gain set to give an albedo of 0.80 for ice floes in March and April. The mean values for the cloud-free portions of individual cells range from 0.18 to 0.91. Monthly averages of cells in the central Arctic range from 0.76 in April to 0.47 in August. The monthly averages of the within-cell standard deviations in the central Arctic are 0.04 in April and 0.06 in September. The surface albedo and surface temperature are correlated most strongly in March (R = -0.77) with little correlation in the summer. The monthly average lead fraction is determined from the mean potential open water, a scaled representation of the temperature or albedo between 0.0 (for ice) and 1.0 (for water); in the central Arctic it rises from an average 0.025 in the spring to 0.06 in September. Sparse data on aerosols, ozone, and water vapor in the atmospheric column contribute uncertainties to instantaneous, area-average albedos of 0.13, 0.04, and 0.08. Uncertainties in monthly average albedos are not this large. Contemporaneous estimation of these variables could reduce the uncertainty in the estimated albedo considerably.

  20. The 2003-04 Sea Ice Season at Barrow as Seen by Land-Based Radar

    NASA Astrophysics Data System (ADS)

    Robson, K. L.; Mahoney, A.; Eicken, H.

    2004-12-01

    The objective was to determine the position of the landfast sea ice edge and its morphology throughout the 2003-04 sea ice season near Barrow using a land-based 10 kW, X-band (3 cm) marine radar mounted on a building near the beach at the Ukpeagvik Inupiat Corporation Naval Artcic Research Laboratory (UIC-NARL). This data would then be used to help understand how landfast ice attaches to coast and what causes it to breakaway. An improved understanding together with real-time data available on the internet will provide more information for the safety of whalers, Native people, and the development of nearshore operations. X-band radar does not discriminate well between level ice and open water, since both areas are characterized by very low back-scatter, but it detects ice floes and rough ice that contain surfaces facing towards the radar. It is very effective at monitoring nearshore sea ice motion in a time series of data. Landfast ice can change very rapidly with break-offs and ice shoves occurring in a matter of hours and nearshore pack ice motion can reverse several times in one day. We were able to monitor these changes by the animation of radar images spaced at five-minute intervals. A very similar land-based radar was installed on the beach approximately 500m further towards Barrow between 1973 and 1979 (Shapiro and Metzner, 1991). In a comparison with this earlier study, the 2003-04 season was noted to be much more dynamic and there was less observed pack ice. In conjunction with field measurements, it was also observed that a stable fast ice edge does not necessarily correlate with a grounded ridge, contrary to the World Meteorological Organization's definition of fast ice.

  1. Iron, manganese and phosphorus partitioning during high flow events: impacts of land cover and seasonality

    NASA Astrophysics Data System (ADS)

    Schroth, A. W.

    2015-12-01

    Metals and phosphorous are essential micro and macronutrients in aquatic ecosystems, and redox sensitive colloidal and particulate metal (oxy)hydroxide phases can be particularly reactive carriers of solid phase P, as well as other nutrients and/or pollutants in riverine chemical loads. High flow events driven by storms and/or snow or glacial melt often dominate the annual load of such constituents, yet remain poorly understood from a biogeochemical perspective. Our research examines the biogeochemical nature of riverine metal and P loads during targeted high flow events to determine to what extent, and under what environmental conditions, are the concentration and biogeochemical composition of riverine loads of P, Fe, and Mn disproportionately high and relatively reactive v. inert. We present a suite of biogeochemical data derived from water and suspended sediment samples that were collected during these events in multiple catchments and over different seasons within the hydrologic year. We examine the size partitioning (particulate, colloidal, 'truly dissolved') of riverine Fe, Mn, and P during events in glaciated, boreal-forested, and agriculturalized catchments of Vermont and Alaska. Suspended sediment loads are also characterized by relative redox sensitivity to examine the potential reactivity of Fe, Mn, and P in sediment transported during particular events. We demonstrate that metal and P concentration, size partitioning, and redox sensitivity differs both seasonally and by land cover, which is due to different source environments and flow paths that are preferentially activated during high discharge. The conceptual model herein developed is critical to understanding the biogeochemical nature of event-based riverine loads, and how this could evolve with changing frequency and severity of high flow events or land cover associated with climate change and landscape management.

  2. Arctic Amplification Feedback Analysis in CMIP5 Models: Land Surfaces, Arctic Ocean and Seasonality

    NASA Astrophysics Data System (ADS)

    Laine, A.; Yoshimori, M.; Abe-Ouchi, A.

    2014-12-01

    The Arctic region is the region where surface warming associated with atmospheric green-house gas concentration increase is expected to be the greatest. This particularity is already being observed currently and is also simulated by climate models. Feedback mechanisms associated with this particularly strong warming, or Artic Amplification, are multiple. The relative role of the different feedbacks are not easy to evaluate precisely using direct model outputs. In this study, we use the "radiative kernels" method (Soden et al, 2008) to perform a multi-model intercomparison analysis. The radiative decomposition is performed at the surface instead of the top of atmosphere in order to consider surface temperature changes specifically. The kernels are derived from the MIROC3.2 model. The intercomparison includes 32 CMIP5 coupled models, whose outputs are analyzed for changes from the late 20th to the late 21st centuries following the rcp4.5 scenario. We consider results separately for land and oceanic surfaces, as the mechanisms and orders of magnitude differ substantially for these two types of surface. We also consider seasons separately as we show that seasonality in the feedback processes is determinant.

  3. Land surface phenologies viewed in the middle infrared: seasonal contrasts between vegetation, soils, and impervious surfaces

    NASA Astrophysics Data System (ADS)

    Henebry, G. M.; Krehbiel, C.; Kovalskyy, V.

    2012-12-01

    The middle infrared (MIR) region of the electromagnetic spectrum spans 3-5 microns. It is the mixing zone between reflected sunlight and emitted earthlight in roughly equal proportions. This region has received very little attention in terrestrial remote sensing. Yet the MIR merits exploration of how it could be used for monitoring land surface phenologies (LSP) and seasonalities due to five characteristics. First, green vegetation is MIR-dark, reflecting just 2-5% of the incident radiation. Second, soils are MIR-bright, reflecting up to one-third of the incident radiation. Third, impervious surfaces, such as concretes, asphalts, and other building and paving materials are also MIR-bright. Fourth, the resulting seasonal contrast in MIR between vegetated and non-vegetated surfaces lets urbanized areas emerge from the vegetated landscape. Fifth, MIR wavelengths penetrate anthropogenic haze and smoke because the particle radii are smaller. Here we use MODIS (MYD02) image time series to illustrate the temporal progressions of MIR at various wavelengths and how they compare to and diverge from the more familiar NDVI and derived LSP metrics.IR portrait of the USA east of W98: maximum value composite of Aqua MODIS MIR band 23 during DOY 219-233 of 2010.

  4. Estimating Evapotranspiration Demands of Different Land Cover Using Diurnal Signals in Dry Season Stream Discharge

    NASA Astrophysics Data System (ADS)

    Bhalla, R. S.; K, K.; Srinivas, V.; Krishnaswamy, J.; Chappell, N. A.; Jones, T.

    2015-12-01

    We use a paired catchment approach to compare the dry season flows between natural grasslands and introduced plantations of black wattle (Acacia mearnsii) in the Nilgiri South range forest which lies in the southern parts of the Western Ghat mountain range in Sothern India, a global biodiversity hot-spot. Discharges were measured using a portable flume and a weir fitted with capacitance probes logging water levels every five minutes in two adjacent catchments. Sensor artefacts in the data were filtered out before analysis. Diurnal variations in dry season flows from March 1st to April 15th, 2014 were used to estimate the daily ET based on Boronina et al. 2005 (Hyd. Proc. 19, 20, pp. 4055-4068.) using the equation 1. : E T daily = ∑ i=1 24 ( Q max - Q i ) Δ t , where E T daily is the daily loss of water from the catchment through ET, Q max is the daily maximum flow rate in the river, Q i is the average flow rate for every hour of the day and Δ t is one hour. Our results show that land use conversion from grasslands to wattle has increased ET by 40.97mm which is to the order of 60% during the period of the study (table 1). This has immediate relevance for dry season flows in the region. Nilgiris provide 40% of the total hydro-power generation for the state of Tamil Nadu and these streams sustain biodiversity and are tributaries of the Cauvery river, the largest the state. They also highlight the potential consequences of programmes such as the National Mission for Greening India which explicitly targets conversions of 10m ha of degraded forests, scrub and grasslands to tree cover and forest. Grassland Wattle Difference 1st Qu. 1.14 1.36 -1.33 Median 1.94 2.04 0.28 Mean 2.06 2.97 0.91 3rd Qu. 2.66 3.51 2.43 Sum 92.63 133.60 40.97 Table 1: Summary statistics for daily dry season ET for catchment under grassland, wattle and the daily differences between the two in mm per day.

  5. Surface Energy Exchange in a Tropical Montane Cloud Forest Environment: Flux Partitioning, and Seasonal and Land Cover-Related Variations

    NASA Astrophysics Data System (ADS)

    Holwerda, F.; Alvarado-Barrientos, M. S.; González-Martínez, T.

    2015-12-01

    Relationships between seasonal climate, land cover and surface energy exchange in tropical montane cloud forest (TMCF) environments are poorly understood. Yet, understanding these linkages is essential to evaluating the impacts of land use and climate change on the functioning of these unique ecosystems. In central Veracruz, Mexico, TMCF occurs between 1100 and 2500 m asl. The canopy of this forest consists of a mix of deciduous and broadleaved-evergreen tree species, the former of which shed their leaves for a short period during the dry season. The aim of this study was to quantify the surface energy balance, and seasonal variations therein, for TMCF, as well as for shaded coffee (CO) and sugarcane (SU), two important land uses that have replaced TMCF at lower elevations. Sensible (H) and latent heat (LE) fluxes were measured using eddy covariance and sap flow methods. Other measurements included: micrometeorological variables, soil heat flux, soil moisture and vegetation characteristics. Partitioning of available energy (A) into H and LE showed important seasonal changes as well as differences among land covers. During the wet-season month of July, average midday Bowen ratios for sunny days were lowest and least variable among land covers: 0.5 in TMCF and SU versus 0.7 in CO. However, because of higher A, along with lower Bowen ratio with respect to CO, LE over TMCF was ca. 20% higher compared to CO and SU. During the late dry-season months of March and April, average midday Bowen ratios for sunny days were generally much higher and more variable among land covers. The higher Bowen ratios indicated a reduction of LE under the drier conditions prevailing (low soil moisture and high VPD), something rarely observed in TMCFs. Moreover, because some trees were still partially leafless in March, LE over TMCF was about half that over CO and SU, suggesting an important effect of phenology on energy exchange of this TMCF. Observed differences between seasons and land

  6. Analysis of urban regions using AVHRR thermal infrared data

    USGS Publications Warehouse

    Wright, Bruce

    1993-01-01

    Using 1-km AVHRR satellite data, relative temperature difference caused by conductivity and inertia were used to distinguish urban and non urban land covers. AVHRR data that were composited on a biweekly basis and distributed by the EROS Data Center in Sioux Falls, South Dakota, were used for the classification process. These composited images are based on the maximum normalized different vegetation index (NDVI) of each pixel during the 2-week period using channels 1 and 2. The resultant images are nearly cloud-free and reduce the need for extensive reclassification processing. Because of the physiographic differences between the Eastern and Western United States, the initial study was limited to the eastern half of the United States. In the East, the time of maximum difference between the urban surfaces and the vegetated non urban areas is the peak greenness period in late summer. A composite image of the Eastern United States for the 2-weel time period from August 30-Septmeber 16, 1991, was used for the extraction of the urban areas. Two channels of thermal data (channels 3 and 4) normalized for regional temperature differences and a composited NDVI image were classified using conventional image processing techniques. The results compare favorably with other large-scale urban area delineations.

  7. Initial Validation of NDVI time seriesfrom AVHRR, VEGETATION, and MODIS

    NASA Technical Reports Server (NTRS)

    Morisette, Jeffrey T.; Pinzon, Jorge E.; Brown, Molly E.; Tucker, Jim; Justice, Christopher O.

    2004-01-01

    The paper will address Theme 7: Multi-sensor opportunities for VEGETATION. We present analysis of a long-term vegetation record derived from three moderate resolution sensors: AVHRR, VEGETATION, and MODIS. While empirically based manipulation can ensure agreement between the three data sets, there is a need to validate the series. This paper uses atmospherically corrected ETM+ data available over the EOS Land Validation Core Sites as an independent data set with which to compare the time series. We use ETM+ data from 15 globally distributed sites, 7 of which contain repeat coverage in time. These high-resolution data are compared to the values of each sensor by spatially aggregating the ETM+ to each specific sensors' spatial coverage. The aggregated ETM+ value provides a point estimate for a specific site on a specific date. The standard deviation of that point estimate is used to construct a confidence interval for that point estimate. The values from each moderate resolution sensor are then evaluated with respect to that confident interval. Result show that AVHRR, VEGETATION, and MODIS data can be combined to assess temporal uncertainties and address data continuity issues and that the atmospherically corrected ETM+ data provide an independent source with which to compare that record. The final product is a consistent time series climate record that links historical observations to current and future measurements.

  8. Automatic cloud detection applied to NOAA-11/AVHRR imagery

    SciTech Connect

    Derrien, M.; Farki, B.; Harang, L.; LeGleau, H.; Noyalet, A.; Pochic, D.; Sairouni, A. . Centre de Meteorologie Spatiale)

    1993-12-01

    The imagery from the AVHRR on board NOAA polar orbiting satellites allows a description of cloud cover, oceanic, and continental surfaces that is used by Meteo-France for nowcasting activities and as input for numerical weather prediction models (NWP). A real-time processing scheme has been designed at the Centre de Meteorologie Spatiale (CMS) in Lannion to extract cloud cover and surface parameters from NOAA-11 AVHRR imagery received at CMS. The key step of this scheme is cloud detection. It is based upon threshold tests applied to different combinations of channels. Its main originality is its complete automation by the computation of the 11[mu]m infrared threshold from a monthly sea surface temperature (SST) climatology over the oceans and from air temperature (near the surface) forecast by NWP over land. A special test has been implemented to detect cloud edges and subpixel clouds over continental surfaces during daytime. It is applied daily in deferred time only to compute normalized difference vegetation index (NDVI). This scheme has been used operationally since February 1990, and its quality has been checked. It has enabled the routine production of various products. A nighttime cloud classification is sent to all French Forecasters; NDVI values are computed daily and used to map the vegetation cover; and SST and thermal fronts are derived operationally from nighttime imagery.

  9. Comparison of AVHRR and SMMR data for monitoring vegetation phenology on a continental scale

    NASA Technical Reports Server (NTRS)

    Justice, C. O.; Townshend, J. R. G.; Choudhury, B. J.

    1989-01-01

    AVHRR normalized difference vegetation index (NDVI) data for a one-year period were compared with Scanning Multichannel Microwave Radiometer microwave polarization difference temperature (MPDT) data for the study of vegetation phenology. It is shown that the MPDT response differs considerably from the seasonal NDVI pattern. The results do not support the hypothetical relationship between MPDT and leaf water content. It is found that only vegetation types with a substantial seasonal variation in the areal extent of vegetated cover show strong seasonality in MPDT data.

  10. Community type differentiation using NOAA/AVHRR data within a sagebrush-steepe ecosystem

    SciTech Connect

    Kremer, R.G.; Running, S.W. . School of Forestry)

    1993-12-01

    The authors assessed the ability of AVHRR/NDVI data to record intrabiome variability of phenological and structural characteristics of three dominant vegetation communities in the intermountain northwest. Seasonal NDVI signatures were developed from biweekly composite data for two grass and one shrub community within a sagebrush-steppe ecosystem. The signatures were found statistically separable (p=0.01) among all three communities in three of 19 composite periods, and between shrub and grass in 15 of 19. Integrated NDVI provided the greatest differentiation among the communities due to ordinal consistency of the three signatures throughout the growing season. A supervised classification of adjacent regions with contrasting topography and substrate was tested for accuracy, and results indicate a strong potential for AVHRR applications to community-level vegetation differentiation. Classification errors are primarily caused by subpixel scale topographic and soil background variations that may not be correctable for coarse resolution imagery.

  11. Adjustment of metabolite composition in the haemolymph to seasonal variations in the land snail Helix pomatia.

    PubMed

    Nicolai, Annegret; Filser, Juliane; Lenz, Roman; Bertrand, Carole; Charrier, Maryvonne

    2011-05-01

    In temperate regions, land snails are subjected to subzero temperatures in winter and hot temperatures often associated to drought in summer. The response to these environmental factors is usually a state of inactivity, hibernation and aestivation, respectively, in a temperature and humidity buffered refuge, accompanied by physiological adjustments to resist cold or heat stress. We investigated how environmental factors in the microhabitat and body condition influence the metabolite composition of haemolymph of the endangered species Helix pomatia. We used UPLC and GC-MS techniques and analyzed annual biochemical variations in a multivariate model. Hibernation and activity months differed in metabolite composition. Snails used photoperiod as cue for seasonal climatic variations to initiate a physiological state and were also highly sensitive to temperature variations, therefore constantly adjusting their physiological processes. Galactose levels gave evidence for the persistence of metabolic activity with energy expenditure during hibernation and for high reproductive activity in June. Triglycerides accumulated prior to hibernation might act as cryoprotectants or energy reserves. During the last month of hibernation snails activated physiological processes related to arousal. During activity, protein metabolism was reflected by high amino acid level. An exceptional aestivation period was observed in April giving evidence for heat stress responses, like the protection of cells from dehydration by polyols and saccharides, the membrane stabilization by cholesterol and enhanced metabolism using the anaerobic succinic acid pathway to sustain costly stress responses. In conclusion, physiological adjustments to environmental variations in Helix pomatia involve water loss regulation, cryoprotectant or heatprotectant accumulation. PMID:21136264

  12. Land-atmosphere coupling manifested in warm-season observations on the U.S. southern great plains

    SciTech Connect

    Phillips, Thomas J.; Klein, Stephen A.

    2014-01-28

    This study examines several observational aspects of land-atmosphere coupling on daily average time scales during warm seasons of the years 1997 to 2008 at the Department of Energy Atmospheric Radiation Measurement Program’s Southern Great Plains (SGP) Central Facility site near Lamont, Oklahoma. Characteristics of the local land-atmosphere coupling are inferred by analyzing the covariability of selected land and atmospheric variables that include precipitation and soil moisture, surface air temperature, relative humidity, radiant and turbulent fluxes, as well as low-level cloud base height and fractional coverage. For both the energetic and hydrological aspects of this coupling, it is found that large-scale atmospheric forcings predominate, with local feedbacks of the land on the atmosphere being comparatively small much of the time. The weak land feedbacks are manifested by 1) the inability of soil moisture to comprehensively impact the coupled land-atmosphere energetics, and 2) the limited recycling of local surface moisture under conditions where most of the rainfall derives from convective cells that originate at remote locations. There is some evidence, nevertheless, of the local land feedback becoming stronger as the soil dries out in the aftermath of precipitation events, or on days when the local boundary-layer clouds are influenced by thermal updrafts known to be associated with convection originating at the surface. Finally, we also discuss potential implications of these results for climate-model representation of regional land-atmosphere coupling.

  13. Comparison of Ant Community Diversity and Functional Group Composition Associated to Land Use Change in a Seasonally Dry Oak Forest.

    PubMed

    Cuautle, M; Vergara, C H; Badano, E I

    2016-04-01

    Ants have been used to assess land use conversion, because they reflect environmental change, and their response to these changes have been useful in the identification of bioindicators. We evaluated ant diversity and composition associated to different land use change in a temperate forest (above 2000 m asl) in Mexico. The study was carried out in "Flor del Bosque" Park a vegetation mosaic of native Oak Forests and introduced Eucalyptus and grasslands. Species richness, dominance and diversity rarefaction curves, based on ant morphospecies and functional groups, were constructed and compared among the three vegetation types, for the rainy and the dry seasons of 2008-2009. Jaccard and Sorensen incidence-based indices were calculated to obtain similarity values among all the habitats. The Oak Forest was a rich dominant community, both in species and functional groups; the Eucalyptus plantation was diverse with low dominance. The most seasonality habitat was the grassland, with low species and high functional group diversity during the dry seasons, but the reverse pattern during the wet season. The Oak Forest was more similar to the Eucalyptus plantation than to the grassland, particularly during the dry season. Oak Forests are dominated by Cold Climate Specialists, specifically Prenolepis imparis (Say). The Eucalyptus and the grassland are characterized by generalized Myrmicinae, as Pheidole spp. and Monomorium ebenium (Forel). The conservation of the native Oak Forest is primordial for the maintenance of Cold Climate Specialist ant communities. The microclimatic conditions in this forest, probably, prevented the invasion by opportunistic species. PMID:26696090

  14. Diagnosing the seasonal land-atmosphere correspondence over northern Australia: dependence on soil moisture state and correspondence strength definition

    NASA Astrophysics Data System (ADS)

    Decker, M.; Pitman, A.; Evans, J.

    2015-08-01

    The similarity of the temporal variations of land and atmospheric states during the onset (September) through to the peak (February) of the wet season over northern Australia is statistically diagnosed using ensembles of offline land surface model simulations that produce a range of different background soil moisture states. We derive the temporal correspondence between variations in the soil moisture and the planetary boundary layer via a statistical measure of rank correlation. The simulated evaporative fraction and the boundary layer are shown to be strongly correlated during both SON (September-October-November) and DJF (December-January-February) despite the differing background soil moisture states between the two seasons and among the ensemble members. The sign and magnitude of the boundary layer-surface layer soil moisture association during the onset of the wet season (SON) differs from the correlation between the evaporative fraction and boundary layer from the same season, and from the correlation between the surface soil moisture and boundary layer association during DJF. The patterns and magnitude of the surface flux-boundary layer correspondence are not captured when the relationship is diagnosed using the surface layer soil moisture alone. The conflicting results arise because the surface layer soil moisture lacks strong correlation with the atmosphere during the monsoon onset because the evapotranspiration is dominated by transpiration. Our results indicate that accurately diagnosing the correspondence and therefore coupling strength in seasonally dry regions, such as northern Australia, requires root zone soil moisture to be included.

  15. Seasonal frost conditions and permafrost regime distribution in the high lands of Sierra Nevada (Spain)

    NASA Astrophysics Data System (ADS)

    Oliva, Marc; Gómez-Ortiz, Antonio; Salvador-Franch, Ferran; Salvà-Catarineu, Montserrat; Palacios, David; Tanarro, Luis Miguel; Ramos, Miguel

    2016-04-01

    Sierra Nevada, Southern Spain (37°S, 3°W), is the massif including the southernmost permafrost remnants in Europe. Over the last decades the distribution of permafrost in this massif has been examined through a combined approach including geomorphological, geophysical and monitoring studies. The purpose of this communication is to summarize all the studies relating to soil thermal regime in the high lands of Sierra Nevada. A 114.5 m deep borehole was drilled in 2000 in the Veleta summit (3380 m) in order to monitor soil temperatures in the summits of the massif. No permafrost regime was detected, with average temperatures stabilizing at 20 m depth at 2 °C. Seasonal frost conditions were also detected in periglacial landforms such as solifluction lobes and sorted-circles. In the Rio Seco cirque the mean annual temperatures in a solifluction lobe located in a southern glacial cirque of the massif (3005 m) were 3.9 °C at 1 m depth between 2006 and 2012; in the north-exposed San Juan valley, soil temperatures in another solifluction landform (2864 m) were 3.9 °C at 1 m depth between 2003 and 2012. In a sorted-circle located in the high plateau of Cerro de los Machos (3297 m) soil temperatures recorded an average of 1.7 °C at 50 cm depth between 2003 and 2011. The only place where temperatures were permanently negative was inside of the only active rock glacier distributed in the Veleta cirque, on the northern slope of the Veleta peak. Here, the remnants of a small glacier that existed during the Little Ice Age (LIA) are still present in the form of buried ice and permafrost buried under the boulders of this rock glacier. Temperatures averaged 0.2 °C at 1 m depth between 2006 and 2013, with permanently negative temperatures below this level until, at least, 10 m depth. Consequently, seasonal frost is widespread nowadays in most of the Sierra Nevada, with permafrost conditions strongly conditioned by the geomorphological setting and the recent environmental

  16. Seasonal and decadal variations of ice-shelf front positions in Dronning Maud Land, East Antarctica

    NASA Astrophysics Data System (ADS)

    Deschamps-Berger, César; Matsuoka, Kenichi; Moholdt, Geir; König, Max

    2015-04-01

    Most of recent rapid changes of the Antarctic ice sheet have been triggered from the ice shelves through enhanced basal melting and/or iceberg calving. The Dronning Maud Land (DML) coastal region is encompassed by many semi-continuous ice shelves, and its mass balance is thus particularly sensitive to changes in the coastal environment. Better knowledge on the region's ice shelves is necessary to predict future behavior of the ice sheet. Here, we present temporal changes of the ice-shelf front positions in DML over the past decade. RADARSAT-2 imagery was used to delineate the front positions at six times between August 2012 and December 2013. Displacements of the ice-shelf edges over this period are mostly in good agreement with displacements derived from satellite interferometery observations. Yet we observe in several sub-regions that displacement during the austral summer is larger than that during the winter. We also observe winter-growth of sea ice from the ice-shelf fronts and outwards to icebergs that are grounded on the continental shelf. Fast sea ice growth and break-up is seasonal and could influence ice-shelf flow close to the fronts. On a longer term, comparison between 2004 and 2009 MOA coast line datasets and our 2012-13 dataset highlights the general stability of the area in the past decade. Between 2004 and 2013, only six ice shelves experienced considerable retreat due to calving of tabular icebergs, leaving the remaining 90 % of the region's ice-shelf fronts advancing in accordance with their local flow.

  17. Variability in ecosystem structure and functioning in a low order stream: Implications of land use and season.

    PubMed

    Englert, Dominic; Zubrod, Jochen P; Schulz, Ralf; Bundschuh, Mirco

    2015-12-15

    Human activity can degrade the habitat quality for aquatic communities, which ultimately impacts the functions these communities provide. Disentangling the complex interaction between environmental and anthropogenic parameters as well as their alteration both along the stream channel, over the seasons, and finally their impact in the aquatic ecosystem represents a fundamental challenge for environmental scientists. Therefore, the present study investigates the implications of successive land uses (i.e., vineyard, urban area, highway and wastewater treatment plant (WWTP)) on structural and functional endpoints related to the ecosystem process of leaf litter breakdown during a winter and summer season in a five km stretch of a second-order stream in southern Germany. This sequence of the different land uses caused, among others, a downstream decline of the ecological status from "high" to "bad" judged based on the SPEARpesticides index together with significant shifts in the macroinvertebrate community composition, which coincided with substantial impairments (up to 100%) in the macroinvertebrate-mediated leaf decomposition. These effects, seem to be mainly driven by alterations in water quality rather than morphological modifications of the stream's habitat since the key shredder Gammarus was not in direct contact with the local habitat during in situ bioassays but showed similar response patterns than the other endpoints. While the relative effect size for most endpoints deviated considerably (sometimes above 2-fold) among seasons, the general response pattern pointed to reductions in energy supply for local and downstream communities. Although the present study focused on a single low-order stream with the main purpose of describing the impact of different land uses on various levels of biological organization, which limits the direct transferability and thus applicability of results to other stream ecosystems, the findings point to the need to develop adequate

  18. Using Mesocosms to Test the Effect of Land Management Practices on Monomethylmercury Production in Freshwater Seasonal Wetlands

    NASA Astrophysics Data System (ADS)

    Heim, W. A.; Negrey, J.; Martenuk, S.; Bonnema, A.; Byington, A.; Masek, J.; Newman, A.; Stephenson, M.; Coale, K. H.

    2013-12-01

    Managed seasonal freshwater wetlands are an ideal habitat for the production of monomethylmercury (MMHg). Wetting and drying cycles created by water management promote growth of wetland vegetation for waterfowl food during the summer growing season. After fall floodup of the fields this vegetation decomposes creating anoxic conditions and an abundant carbon source utilized by MMHg producing microbes. This results in hot moments of MMHg production after floodup and increased MMHg loads from seasonal wetlands. In this work, we determine the effect land management practices have on MMHg production. A manipulative study was conducted during the fall (October-November) of 2012 in a 20 hectacre seasonally flooded wetland located in Yolo Wildlife Area, CA. Polycarbonate cylindrical mesocosms (0.75 m diameter, 0.6 m tall), were placed over 6 differing land management treatment types: disc, simulated cattle grazed, mowed with vegetation removed, mowed with vegetation left in place, scraped with all vegetation removed, and natural undisturbed. Each treatment had n = 5 replicates. Samples were collected for determination of mercury speciation and ancillary measurements. Sampling occurred bi-weekly or weekly over a period of thirty days. Dissolved MMHg concentrations peaked in all treatments by day 16 of the experiment. Comparison of treatments was done on a mass dissolved MMHg basis. Natural and mowed treatments were similar (2.2 and 2.1 μg MMHg respectively). Simulated grazing treatments (1.4 μg MMHg ) resulted in 36% reduction in MMHg relative to the natural treatment. Cleared (0.36 μg MMHg), disced (0.51 μg MMHg), and mowed with vegetation removed (0.88 μg MMHg) produced significantly less MMHg than the natural undisturbed treatment. Our results indicate specific management practices of seasonally flooded wetlands can reduce the net production of MMHg and potentially reduce loads to surrounding water. Net mass MMHg (ug) produced by treatment type within mesocosms in a

  19. AVHRR for monitoring global tropical deforestation

    NASA Technical Reports Server (NTRS)

    Malingreau, J. P.; Laporte, N.; Tucker, C. J.

    1989-01-01

    Advanced Very High Resolution Radiometer (AVHRR) data have been used to assess the dynamics of forest trnsformations in three parts of the tropical belt. A large portion of the Amazon Basin has been systematically covered by Local Area Coverage (LAC) data in the 1985-1987 period. The analysis of the vegetation index and thermal data led to the identification and measurement of large areas of active deforestation. The Kalimantan/Borneo forest fires were monitored and their impact was evaluated using the Global Area Coverage (GAC) 4 km resolution data. Finally, High Resolution Picture Transmission (HRPT) data have provided preliminary information on current activities taking place at the boundary between the savanna and the forest in the Southern part of West Africa. The AVHRR approach is found to be a highly valuable means for carrying out deforestation assessments in regional and global perspectives.

  20. AVHRR imagery reveals Antarctic ice dynamics

    SciTech Connect

    Bindschadler, R.A.; Vornberger, P.L. STX Corp., Lanham, MD )

    1990-06-01

    A portion of AVHRR data taken on December 5, 1987 at 06:15 GMT over a part of Antarctica is used here to show that many of the most significant dynamic features of ice sheets can be identified by a careful examination of AVHRR imagery. The relatively low resolution of this instrument makes it ideal for obtaining a broad view of the ice sheets, while its wide swath allows coverage of areas beyond the reach of high-resolution imagers either currently in orbit or planned. An interpretation is given of the present data, which cover the area of ice streams that drain the interior of the West Antarctic ice sheet into the Ross Ice Shelf. 21 refs.

  1. Water quality of small seasonal wetlands in the Piedmont ecoregion, South Carolina, USA: Effects of land use and hydrological connectivity.

    PubMed

    Yu, Xubiao; Hawley-Howard, Joanna; Pitt, Amber L; Wang, Jun-Jian; Baldwin, Robert F; Chow, Alex T

    2015-04-15

    Small, shallow, seasonal wetlands with short hydroperiod (2-4 months) play an important role in the entrapment of organic matter and nutrients and, due to their wide distribution, in determining the water quality of watersheds. In order to explain the temporal, spatial and compositional variation of water quality of seasonal wetlands, we collected water quality data from forty seasonal wetlands in the lower Blue Ridge and upper Piedmont ecoregions of South Carolina, USA during the wet season of February to April 2011. Results indicated that the surficial hydrological connectivity and surrounding land-use were two key factors controlling variation in dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) in these seasonal wetlands. In the sites without obvious land use changes (average developed area <0.1%), the DOC (p < 0.001, t-test) and TDN (p < 0.05, t-test) of isolated wetlands were significantly higher than that of connected wetlands. However, this phenomenon can be reversed as a result of land use changes. The connected wetlands in more urbanized areas (average developed area = 12.3%) showed higher concentrations of dissolved organic matter (DOM) (DOC: 11.76 ± 6.09 mg L(-1), TDN: 0.74 ± 0.22 mg L(-1), mean ± standard error) compared to those in isolated wetlands (DOC: 7.20 ± 0.62 mg L(-1), TDN: 0.20 ± 0.08 mg L(-1)). The optical parameters derived from UV and fluorescence also confirmed significant portions of protein-like fractions likely originating from land use changes such as wastewater treatment and livestock pastures. The average of C/N molar ratios of all the wetlands decreased from 77.82 ± 6.72 (mean ± standard error) in February to 15.14 ± 1.58 in April, indicating that the decomposition of organic matter increased with the temperature. Results of this study demonstrate that the water quality of small, seasonal wetlands has a direct and close association with the surrounding environment. PMID:25647281

  2. Properties of PSCs and Cirrus Determined from AVHRR Data

    NASA Technical Reports Server (NTRS)

    Hervig, Mark; Pagan, Kathy; Foschi, Patricia G.

    1999-01-01

    Polar stratospheric clouds (PSCS) and cirrus have been investigated using thermal emission measurements at 10.8 and 12 micrometers wavelength (channels 4 and 5) from the Advanced Very High Resolution Radiometer (AVHRR). The AVHRR signal was evaluated from a theoretical basis to understand the emission from clear and cloudy skies, and models were developed to simulate the AVHRR signal. Signal simulations revealed that nitric acid PSCs are invisible to AVHRR, while ice PSCs and cirrus are readily detectable. Methods were developed to retrieve cloud optical depths, average temperatures, average effective radii, and ice water paths, from AVHRR channels 4 and 5. Properties of ice PSCs retrieved from AVHRR were compared to values derived from coincident radiosondes and from the Polar Ozone and Aerosol Measurement II instrument, showing good agreement.

  3. Seasonality in the daytime and night-time intensity of land surface temperature in a tropical city area.

    PubMed

    Ayanlade, Ayansina

    2016-07-01

    Variations in urban land surface temperature (LST) links to the surrounding rural areas result to urban heat island (UHI), which is a global problem challenging both cities in develop and developing countries. Satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS), covering the period between 2002 and 2013 were analysed to examine seasonal variability in the daytime and night-time intensity of urban heat island (UHI), using Lagos metropolitan city of Nigeria as a case study. Contribution index (CI) and landscape index (LI) were used to estimate the LST contributions from non-urban and urban areas to UHI and assess the relationship between the Normalized Difference Vegetation Index (NDVI) and LST. The LI showed that both non-urban and urban areas contribute greatly to strengthen the intensity of LST during the daytime (with LI<1.0) and much more during the daytime in the dry seasons (LI=0.13 in the year 2013). The correlation analysis showed seasonal variation in the relationship (R(2)) between NDVI and the LST for both day and night times. The highest R(2) values were recorded for daytime, especially during the wet season (R(2)>0.90), while R(2) were very low in the night-time especially during dry season. The study indicates that reduction in vegetal cover in Lagos urban areas altered the terrestrial thermal and aerodynamic processes hence resulted in an intensification of UHI in the metropolitan city. PMID:27017074

  4. The seasonal carbon and water balances of the Cerrado environment of Brazil: Past, present, and future influences of land cover and land use

    NASA Astrophysics Data System (ADS)

    Arantes, Arielle Elias; Ferreira, Laerte G.; Coe, Michael T.

    2016-07-01

    The Brazilian savanna (known as Cerrado) is an upland biome made up of various vegetation types from herbaceous to arboreal. In this paper, MODIS remote sensing vegetation greenness from the Enhanced Vegetation Index (EVI) and evapotranspiration (ET) data for the 2000-2012 period were analyzed to understand the differences in the net primary productivity (NPP-proxy), carbon, and the evaporative flux of the major Cerrado natural and anthropic landscapes. The understanding of the carbon and evaporative fluxes of the main natural and anthropic vegetation types is of fundamental importance in studies regarding the impacts of land cover and land use changes in the regional and global climate. The seasonal dynamics of EVI and ET of the main natural and anthropic vegetation types of the Cerrado biome were analyzed using a total of 35 satellite-based samples distributed over representative Cerrado landscapes. Carbon and water fluxes were estimated for different scenarios, such as, a hypothetical unconverted Cerrado, 2002 and 2050 scenarios based on values derived from literature and on the PROBIO land cover and land use map for the Cerrado. The total growing season biomass for 2002 in the Cerrado region was estimated to be 28 gigatons of carbon and the evapotranspiration was 1336 gigatons of water. The mean estimated growing season evapotranspiration and biomass for 2002 was 576 Gt of water and 12 Gt of carbon for pasture and croplands compared to 760 Gt of water and 15 Gt of carbon for the Cerrado natural vegetation. In a modeled future scenario for the year 2050, the ET flux from natural Cerrado vegetation was 394 Gt less than in 2002 and 991 Gt less than in an unconverted scenario, with only natural vegetation, while the carbon was 8 Gt less than in 2002 and 21 Gt less than in this hypothetical pre-conversion Cerrado. On the other hand, the sum of the pasture and cropland ET flux increased by 405 Gt in 2050 relative to 2002 and the carbon by 11 Gt of carbon. Given the

  5. Operational atmospheric correction of AVHRR visible and infrared data

    SciTech Connect

    Vermote, E.; El Saleous, N.; Roger, J.C.

    1995-12-31

    The satellite level radiance is affected by the presence of the atmosphere between the sensor and the target. The ozone and water vapor absorption bands affect the signal recorded by the AVHRR visible and near infrared channels respectively. The Rayleigh scattering mainly affects the visible channel and is more pronounced when dealing with small sun elevations and large view angles. The aerosol scattering affects both channels and is certainly the most challenging term for atmospheric correction because of the spatial and temporal variability of both the type and amount of particles in the atmosphere. This paper presents the equation of the satellite signal, the scheme to retrieve atmospheric properties and corrections applied to AVHRR observations. The operational process uses TOMS data and a digital elevation model to correct for ozone absorption and rayleigh scattering. The water vapor content is evaluated using the split-window technique that is validated over ocean using 1988 SSM/I data. The aerosol amount retrieval over Ocean is achieved in channels 1 and 2 and compared to sun photometer observations to check consistency of the radiative transfer model and the sensor calibration. Over land, the method developed uses reflectance at 3.75 microns to deduce target reflectance in channel 1 and retrieve aerosol optical thickness that can be extrapolated in channel 2. The method to invert the reflectance at 3.75 microns is based on MODTRAN simulations and is validated by comparison to measurements performed during FIFE 87. Finally, aerosol optical thickness retrieved over Brazil and Eastern US is compared to sun photometer measurements.

  6. 25 CFR 166.308 - Can the number of animals and/or season of use be modified on the permitted land if I graze...

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 25 Indians 1 2012-04-01 2011-04-01 true Can the number of animals and/or season of use be modified... WATER GRAZING PERMITS Land and Operations Management § 166.308 Can the number of animals and/or season... on-and-off grazing permit? Yes. The number of animals and/or season of use may be modified...

  7. 25 CFR 166.308 - Can the number of animals and/or season of use be modified on the permitted land if I graze...

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 25 Indians 1 2014-04-01 2014-04-01 false Can the number of animals and/or season of use be... season of use be modified on the permitted land if I graze adjacent trust or non-trust rangelands under an on-and-off grazing permit? Yes. The number of animals and/or season of use may be modified...

  8. 25 CFR 166.308 - Can the number of animals and/or season of use be modified on the permitted land if I graze...

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 25 Indians 1 2011-04-01 2011-04-01 false Can the number of animals and/or season of use be... season of use be modified on the permitted land if I graze adjacent trust or non-trust rangelands under an on-and-off grazing permit? Yes. The number of animals and/or season of use may be modified...

  9. 25 CFR 166.308 - Can the number of animals and/or season of use be modified on the permitted land if I graze...

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 25 Indians 1 2013-04-01 2013-04-01 false Can the number of animals and/or season of use be... season of use be modified on the permitted land if I graze adjacent trust or non-trust rangelands under an on-and-off grazing permit? Yes. The number of animals and/or season of use may be modified...

  10. 25 CFR 166.308 - Can the number of animals and/or season of use be modified on the permitted land if I graze...

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 25 Indians 1 2010-04-01 2010-04-01 false Can the number of animals and/or season of use be... season of use be modified on the permitted land if I graze adjacent trust or non-trust rangelands under an on-and-off grazing permit? Yes. The number of animals and/or season of use may be modified...

  11. Comparison of North and South American biomes from AVHRR observations

    NASA Technical Reports Server (NTRS)

    Goward, Samuel N.; Dye, Dennis; Kerber, Arlene; Kalb, Virginia

    1987-01-01

    Previous analysis of the North American continent with AVHRR-derived vegetation index measurements showed a strong relation between known patterns of vegetation seasonality, productivity and the spectral vegetation index measurements. This study extends that analysis to South America to evaluate the degree to which these findings extend to tropical regions. The results show that the spectral vegetation index measurements provide a general indicator of vegetation activity across the major biomes of the Western Hemisphere of the earth, including tropical regions. The satellite-observed patterns are strongly related to the known climatology of the continents and may offer a means to improve understanding of global bioclimatology. For example, South America is shown to have a longer growing season with much earlier spring green-up than North America. The time integral of the measurements, computed from 12 composited monthly values, produces a value that is related to published net primary productivity data. However, limited net primary production data does not allow complete evaluation of satellite-observed contrasts between North and South American biomes. These results suggest that satellite-derived spectral vegetation index measurements are of great potential value in improving knowledge of the earth's biosphere.

  12. Change and persistence in land surface phenologies of the Don and Dnieper river basins

    NASA Astrophysics Data System (ADS)

    Kovalskyy, V.; Henebry, G. M.

    2009-10-01

    The formal collapse of the Soviet Union at the end of 1991 produced major socio-economic and institutional dislocations across the agricultural sector. The picture of broad scale patterns produced by these transformations continues to be discovered. We examine here the patterns of land surface phenology (LSP) within two key river basins—Don and Dnieper—using AVHRR (Advanced Very High Resolution Radiometer) data from 1982 to 2000 and MODIS (Moderate Resolution Imaging Spectroradiometer) data from 2001 to 2007. We report on the temporal persistence and change of LSPs as summarized by seasonal integration of NDVI (normalized difference vegetation index) time series using accumulated growing degree-days (GDDI NDVI). Three land cover super-classes—forest lands, agricultural lands, and shrub lands—constitute 96% of the land area within the basins. All three in both basins exhibit unidirectional increases in AVHRR GDDI NDVI between the Soviet and post-Soviet epochs. During the MODIS era (2001-2007), different socio-economic trajectories in Ukraine and Russia appear to have led to divergences in the LSPs of the agricultural lands in the two basins. Interannual variation in the shrub lands of the Don river basin has increased since 2000. This is due in part to the better signal-to-noise ratio of the MODIS sensor, but may also be due to a regional drought affecting the Don basin more than the Dnieper basin.

  13. Vegetation, land-use and seasonal albedo data sets: Documentation of archived data tape

    NASA Technical Reports Server (NTRS)

    Matthews, E.

    1984-01-01

    Global data bases of vegetation, land use, and land cover were compiled at a 1 deg latitude x 1 deg longitude resolution, drawing on approximately 100 published sources complemented by a large collection of satellite imagery. Six datasets prepared and archived at NCAR are described: a vegetation data set (VEGTYPE) representing natural (pre-agricultural) vegetation based on the UNESCO classification system; a cultivation intensity data set (CULTINT) defining the areal extent (expressed as %) of presently cultivated land in the 1 x 1 cells; and four integrated surface-albedo data sets (January, April, July, October) for snow-free conditions except for permanently snow-covered continental ice, incorporating natural vegetation and cultivation characteristics from the vegetation and cultivation-intensity data sets. Non-zero data are included for permanent land only, including continental ice. Documentation of the data-tape format as well as descriptions and regional maps of the individual data sets are presented.

  14. VARIATIONS OF MICROORGANISM CONCENTRATIONS IN URBAN STORMWATER RUNOFF WITH LAND USE AND SEASONS

    EPA Science Inventory

    Stormwater runoff samples were collected from outfalls draining small municipal separate storm sewer systems. The samples were collected from three different land use areas based on local designation (high-density residential, low-density residential, and landscaped commercial)....

  15. The effects of seasonal differences in climatic conditions on Landsat spectral signatures and associated land cover classification

    NASA Technical Reports Server (NTRS)

    Harrington, J. A., Jr.

    1982-01-01

    Unsupervised classification algorithms are used to analyze Landsat computer-compatible tape data for an area of approximately 840 sq km in central Oklahoma, over the period from June 12 to August 4, 1979. The results obtained show that changes in remotely sensed spectral signatures and land cover classes are associated with a period of transition from moisture availability in late spring to moisture deficit in midsummer, with the latter being marked by greater visible spectrum reflectance and greater near-IR absorption, although each surface cover type has responded differently to the seasonal change in water availability. Consideration of these results has led to the identification of important factors in the use of multidate satellite data in environmental change monitoring. Naturally induced trends in surface albedo introduce noise into studies aimed at identifying anthropogenic land cover change. Specific problems associated with prairie-forest ecotonal areas in the southern Great Plains involve the seasonally induced differences in separability of forest, bush, and grassland cover types.

  16. Urban climate modifications in hot desert cities: The role of land cover, local climate, and seasonality

    NASA Astrophysics Data System (ADS)

    Lazzarini, Michele; Molini, Annalisa; Marpu, Prashanth R.; Ouarda, Taha B. M. J.; Ghedira, Hosni

    2015-11-01

    Urban climate modifications like the urban heat island (UHI) have been extensively investigated in temperate regions. In contrast, the understanding of how urbanization relates to climate in hot, hyperarid environments is still extremely limited, despite the growing socioeconomic relevance of arid lands and their fast urbanization rate. We explore here the relationship between land cover and temperature regime in hot desert cities (HDCs) based on estimates of land surface temperature, normalized difference vegetation index, and impervious surface areas inferred from Moderate Resolution Imaging Spectroradiometer and Landsat satellite products. Our analysis shows that HDCs display common climatic patterns, with downtown areas on average cooler than suburbs during the daytime (urban cool island) and warmer at night (classical UHI). The observed diurnal cool island effect can be largely explained by relative vegetation abundance, percentage of bare soil, and local climatic conditions and calls for a more in deep investigation of the physical processes regulating boundary layer dynamics in arid regions.

  17. Comparison of Gosat CAI and SPOT Vgt Ndvi Data with Different Season and Land Cover in East Asia

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Wang, X.; Guo, M.; Tani, H.

    2011-08-01

    The Normalized Difference Vegetation Index (NDVI) has become one of the most widely used indices in remote sensing applications in a variety of fields. Many studies have compared the NDVI values for different satellite sensors. Nowadays, the Greenhouse Gases Observing Satellite (GOSAT) was successfully launched on January 23, 2009. It is used to monitor greenhouse gases on the Earth's surface and also has a sensor, the Cloud Aerosol Imager (CAI), that senses red and near infrared spectrums. It can also process NDVI data. Therefore, we are first compare GOSAT CAI and SPOT VGT NDVI data in different seasonal and land cover in East Asian, to explore the relationship between the two types of datasets, and to discuss the possibility of extending SPOT VGT data using GOSAT CAI NDVI data for the same area. We used GOSAT CAI Level 3 data to derive 10-day composite NDVI values for the East Asia region for November 2009 and January, April and July 2010 using the maximum value composite (MVC) method. We compared these values with 10-day composite SPOT VGT NDVI data for the same period. The results show that the correlation coefficients of regression analysis generally revealed a strong correlation between NDVI from the two sensors in November 2009 and January, April and July 2010 (0.88, 0.85, 0.77 and 0.74, respectively). The differences place may be affected by cloud cover. From the combined analysis of seasonal changes and land cover, we found that the correlations between the SPOT VGT and the GOSAT CAI NDVI data are less affected by seasonal change and the SPOT VGT data is more sensitive to high vegetation coverage than the GOSAT CAI data. In the future, through continued monitoring and processing by cloud removal technology, the accuracy of GOSAT CAI NDVI data will be further improved and thus be more widely used.

  18. Development of digital interactive processing system for NOAA satellites AVHRR data

    NASA Astrophysics Data System (ADS)

    Gupta, R. K.; Murthy, N. N.

    The paper discusses the digital image processing system for NOAA/AVHRR data including Land applications - configured around VAX 11/750 host computer supported with FPS 100 Array Processor, Comtal graphic display and HP Plotting devices; wherein the system software for relational Data Base together with query and editing facilities, Man-Machine Interface using form, menu and prompt inputs including validation of user entries for data type and range; preprocessing software for data calibration, Sun-angle correction, Geometric Corrections for Earth curvature effect and Earth rotation offsets and Earth location of AVHRR image have been accomplished. The implemented image enhancement techniques such as grey level stretching, histogram equalization and convolution are discussed. The software implementation details for the computation of vegetative index and normalized vegetative index using NOAA/AVHRR channels 1 and 2 data together with output are presented; scientific background for such computations and obtainability of similar indices from Landsat/MSS data are also included. The paper concludes by specifying the further software developments planned and the progress envisaged in the field of vegetation index studies.

  19. The impact of land use and season on the riverine transport of mercury into the marine coastal zone.

    PubMed

    Saniewska, Dominika; Bełdowska, Magdalena; Bełdowski, Jacek; Saniewski, Michał; Szubska, Marta; Romanowski, Andrzej; Falkowska, Lucyna

    2014-11-01

    In Mediterranean seas and coastal zones, rivers can be the main source of mercury (Hg). Catchment management therefore affects the load of Hg reaching the sea with surface runoff. The major freshwater inflows to the Baltic Sea consist of large rivers. However, their systems are complex and identification of factors affecting the outflow of Hg from its catchments is difficult. For this reason, a study into the impact of watershed land use and season on mercury biogeochemistry and transport in rivers was performed along two small rivers which may be considered typical of the southern Baltic region. Neither of these rivers are currently impacted by industrial effluents, thus allowing assessment of the influence of catchment terrain and season on Hg geochemistry. The study was performed between June 2008 and May 2009 at 13 sampling points situated at different terrain types within the catchments (forest, wetland, agriculture and urban). Hg analyses were conducted by CVAFS. Arable land erosion was found to be an important source of Hg to the aquatic system, similar to urban areas. Furthermore, inflows of untreated storm water discharge resulted in a fivefold increase of Hg concentration in the rivers. The highest Hg concentration in the urban runoff was observed with the greatest amount of precipitation during summer. Moderate rainfalls enhance the inflow of bioavailable dissolved mercury into water bodies. Despite the lack of industrial effluents entering the rivers directly, the sub-catchments with anthropogenic land use were important sources of Hg in the rivers. This was caused by elution of metal, deposited in soils over the past decades, into the rivers. The obtained results are especially important in the light of recent environmental conscience regulations, enforcing the decrease of pollution by Baltic countries. PMID:25085426

  20. Utilization of satellite-derived estimates of meteorological and land surface characteristics in the Land Surface Model for vast agricultural region territory

    NASA Astrophysics Data System (ADS)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Volkova, Elena

    2015-04-01

    The method has been elaborated to evaluate the water and heat regime characteristics of the territory on a regional scale for the vegetation season based on a physical-mathematical model of water and heat exchange between vegetation covered land surface and atmosphere (LSM, Land Surface Model) appropriate for using satellite information on land surface and meteorological conditions. The developed model is intended for calculating soil water content, evapotranspiration (evaporation from bare soil and transpiration by vegetation), vertical water and heat fluxes as well as land surface and vegetation cover temperatures and vertical distributions of temperature and moisture in the active soil layer. Parameters of the model are soil and vegetation characteristics and input variables are meteorological characteristics. Their values have been obtained from ground-based observations at agricultural meteorological stations and satellite-based measurements by scanning radiometers AVHRR/NOAA, MODIS/EOS Terra and Aqua and SEVIRI (geostationary satellites Meteosat-9, -10). The AVHRR data have been used to build the estimates of three types of land surface temperature (LST): land skin temperature Tsg, air temperature at a level of vegetation cover Ta and efficient radiation temperature Tseff, emissivity E, normalized vegetation index NDVI, vegetation cover fraction B, leaf area index LAI, and precipitation. The set of estimates derived from MODIS data has comprised values of LST Tls, E, NDVI and LAI. The SEVIRI-based retrievals have included Tls, Ta, Е at daylight and nighttime, LAI (daily) and precipitation. The case study has been carried out for agricultural Central Black Earth region of the European Russia of 227,300 sq.km containing 7 regions of the Russian Federation for years 2009-2013 vegetation seasons. Estimates of described characteristics have been built with the help of the developed original and improved pre-existing methods and technologies of thematic processing

  1. Food Security Through the Eyes of AVHRR: Changes and Variability of African Food Production

    NASA Astrophysics Data System (ADS)

    Vrieling, A.; de Beurs, K. M.; Brown, M. E.

    2008-12-01

    Food security is defined by FAO as a situation that exists when all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life. Despite globalization and food trade, access to food remains a major problem for an important part of Africa's population. As a contribution to the food security analysis we identify at a coarse scale where trends and high interannual variability of food production occur within Africa. We use the 8-km resolution AVHRR NDVI 15-day composites of the GIMMS group (1981-2006). Two methods were applied to extract phenology indicators from the dataset. The indicators are start of season, length of season, time of maximum NDVI, maximum NDVI, and cumulated NDVI over the season. To focus the analysis on food production we spatially aggregate the annual indicators at sub-national level using a general crop mask. Persistent changes during the 26-year period were assessed using trend analysis on the yearly aggregated indicators. These trends may indicate changes in production, and consequent potential increases of food insecurity. We evaluate then where strong interannual variability of phenology indicators occurs. This relates to regular shortages of food availability. For Africa, field information on phenology or accurate time series of production figures at the sub-national scale are scarce. Validating the outcome of the AVHRR analysis is consequently difficult. We propose to use crop-specific national FAOSTAT yield statistics. For this purpose, we aggregate phenology outputs per country using specific masks for the major staple food crops. Although data quality and scale issues influence results, for several countries and crops significant positive correlations between indicators and crop production exist. We conclude that AVHRR-derived phenology information can provide useful inputs to food security analysis.

  2. Seasonal Response of Overland Flow and Sediment Loading to Climate and Land Use Land Cover Change in the Apalachicola River, Florida

    NASA Astrophysics Data System (ADS)

    Hovenga, P. A.; Wang, D.; Medeiros, S. C.; Hagen, S. C.

    2015-12-01

    Located in Florida's panhandle, the Apalachicola River is the southernmost reach of the Apalachicola-Chattahoochee-Flint (ACF) River basin. Streamflow and sediment drains to Apalachicola Bay within the Northern Gulf of Mexico, resulting in a direct influence on the ecology of the region, in particular seagrass and oyster production. This study examines the seasonal response of overland flow and sediment loading in the Apalachicola River under projected climate change scenarios and land use land cover (LULC) change. A hydrologic model using the Soil Water Assessment Tool (SWAT) was developed for the Apalachicola region to simulate daily discharge and sediment load under present (circa 2000) and future conditions (circa 2100) to understand how parameters respond over a seasonal time frame to changes in climate only, LULC only, and coupled climate / LULC. These physically-based models incorporate digital elevation model (DEM), LULC, soil maps, climate data, and management controls. Long Ashton Research Station-Weather Generator (LARS-WG) was used to create stochastic temperature and precipitation inputs from four Global Climate Models (GCM), each under Intergovernmental Panel on Climate Change (IPCC) carbon emission scenarios for A1B, A2, and B1. These scenarios represent potential future emissions resulting from a range driving forces, e.g. social, economic, environmental, and technologic. Projected 2100 LULC data provided by the United States Geological Survey (USGS) EROS Center was incorporated for each corresponding IPCC scenario. Results from this study can be used to further understand climate and LULC implications to the Apalachicola Bay and surrounding region as well as similar fluvial estuaries while providing tools to better guide management and mitigation practices.

  3. Estimating potential evapotranspiration using Shuttleworth Wallace model and NOAA-AVHRR NDVI data to feed a distributed hydrological model over the Mekong River basin

    NASA Astrophysics Data System (ADS)

    Zhou, M. C.; Ishidaira, H.; Hapuarachchi, H. P.; Magome, J.; Kiem, A. S.; Takeuchi, K.

    2006-07-01

    SummaryOne of key inputs to hydrological modeling is the potential evapotranspiration, either from the interception (PET 0) or from the soil water of root zone (PET). The Shuttleworth-Wallace (S-W) model is developed for their estimation. In this parameterization, neither experimental measurement nor calibration is introduced. Based on IGBP land cover classification, the typical thresholds of vegetation parameters are drawn from the literature. The spatial and temporal variation of vegetation LAI is derived from the composite NOAA-AVHRR NDVI using the SiB2 method. The CRU database supplies with the required meteorological data. They are all publicly available. The developed S-W model is applicable at the global scale, particularly to the data-poor or ungauged large basins. Using the century monthly time series of CRU TS 2.0 and the monthly composite NOAA-AVHRR NDVI from 1981 to 2000, annual PET is estimated 1354 mm over the Mekong River basin, spatially distributed strikingly non-uniformly from 300 to 2040 mm, and seasonally changed significantly with LAI. By replacing the monthly with the 10-day composite NDVI and the albedo of 0.10 with 0.15 for substrate soil surface, annual PET relatively decreases less than 4% and 1.7%, respectively over the whole basin. The correlation with pan evaporation ( Epan) is quite scattered but grouped with the vegetation types and consistent with a rough ratio as reported in the literature. In contrast, the PET and the reference evapotranspiration (RET) are vegetation-type-dependently correlated very well. The PET 0 is estimated 1.63 times of PET in average over the whole basin. The application of BTOPMC model shows that the derived LAI, PET 0 and PET behave very well in the distributed hydrological modeling.

  4. Atlas of Archived Vegetation, Land-use and Seasonal Albedo Data Sets

    NASA Technical Reports Server (NTRS)

    Matthews, E.

    1985-01-01

    Global digital data bases of natural vegetation and land use were compiled, for use in climate studies, at 1 deg resolution from over 100 published sources. A series of 6 data sets, derived from the original compilations, was prepared and archived on tape at the National Center for Atmospheric Research (NCAR) (Matthews, 1984). The first is a vegetation data set representing natural (pre-agricultural) vegetation based on the UNESCO classification system. The second, derived from the land-use compilation, is a cultivation-intensity data set defining the areal extent of presently-cultivated land in the 1 deg cells. The last four are integrated surface-albedo data sets (January, April, July, October) for snow-free conditions, incorporating natural-vegetation and cultivation characteristics from the vegetation and cultivation-intensity data sets. Each of these data sets covers the entire surface of the earth. They include non-zero data for permanent land only, including continental ice; water, including oceans and lakes, is zero. The present report includes maps, presented by continent, of the complete archived data, with the exception of Antarctica.

  5. LAND USE AND SEASONAL EFFECTS ON URBAN STORMWATER RUNOFF MICROORGANISM CONCENTRATIONS

    EPA Science Inventory

    Stormwater samples collected from storm sewers draining small municipal separate storm sewer systems shown to be free of cross connections within an urban watershed dominated by a single land use were analyzed for pathogens (Pseudomonas aeruginosa and Staphylococcus aureus) and i...

  6. Nitrogen Loss from a Mixed Land Use Watershed as Influenced by Hydrology and Growing Seasons

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Non-point nitrogen loss from agriculture is an environmental concern among scientists, decision-makers, and the public. This study investigated nitrate-N and total N losses from a mixed land use watershed (39.5 ha) as influenced by hydrology (flow type, runoff volume, storm sizes, and precipitation ...

  7. Nitrogen loss from a mixed land use watershed as influenced by hydrology and seasons

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Non-point nitrogen loss from agriculture is an environmental concern among scientists, decision-makers, and the public. This study investigated NO3-N and total N losses from a mixed land use watershed (39.5 ha) in the Appalachian Valley and Ridge Physiographic Province as influenced by hydrology (fl...

  8. Unmixing AVHRR Imagery to Assess Clearcuts and Forest Regrowth in Oregon

    NASA Technical Reports Server (NTRS)

    Hlavka, Christine A.; Spanner, Michael A.

    1995-01-01

    Advanced Very High Resolution Radiometer imagery provides frequent and low-cost coverage of the earth, but its coarse spatial resolution (approx. 1.1 km by 1.1 km) does not lend itself to standard techniques of automated categorization of land cover classes because the pixels are generally mixed; that is, the extent of the pixel includes several land use/cover classes. Unmixing procedures were developed to extract land use/cover class signatures from mixed pixels, using Landsat Thematic Mapper data as a source for the training set, and to estimate fractions of class coverage within pixels. Application of these unmixing procedures to mapping forest clearcuts and regrowth in Oregon indicated that unmixing is a promising approach for mapping major trends in land cover with AVHRR bands 1 and 2. Including thermal bands by unmixing AVHRR bands 1-4 did not lead to significant improvements in accuracy, but experiments with unmixing these four bands did indicate that use of weighted least squares techniques might lead to improvements in other applications of unmixing.

  9. Monitoring Long-term Regional Changes in the Arctic and Antarctic with AVHRR 5 km Polar Pathfinder Data

    NASA Astrophysics Data System (ADS)

    Wolfe, J.; Fowler, C.; Scambos, T.

    2001-12-01

    This project illustrates applications of Advanced Very High Resolution Radiometer (AVHRR) 5 km Polar Pathfinder data in large-scale climate studies for the Arctic and Antarctica. The National Snow and Ice Data center (NSIDC) archives and distributes AVHRR Polar Pathfinder data at 1.25 km and 5 km resolution. The 5 km data include five AVHRR channels, clear sky surface broadband albedo and skin temperature, solar zenith angle, satellite elevation angle, sun-satellite relative azimuth angle, surface type mask, cloud mask, and Universal Coordinated Time (UTC) of acquisition. Data are composited onto two grids per day based on common local solar times and scan angle. Temporal coverage is from July 1981 to August 1998. AVHRR 5 km data provide a time series of consistent observations. The temporal coverage is designed to provide information on diurnal variations and seasonal-to-interannual evolution in climate and surface conditions. The 5 km products are useful for studies of regional changes and monitoring over longer time periods. Applications of 5 km products are illustrated by: (1) monitoring a time series of coastline changes along the Northern West Antarctic coast, (2) measuring mean monthly and interannual melt patterns in the South Dome of Greenland with a transect of reflectance and surface temperature observations, and (3) monitoring interannual albedo and temperature patterns of selected small lakes in the Northwest Territories of Canada.

  10. Assessing the consistency between AVHRR and MODIS NDVI datasets for estimating terrestrial net primary productivity over India

    NASA Astrophysics Data System (ADS)

    Nayak, R. K.; Mishra, N.; Dadhwal, V. K.; Patel, N. R.; Salim, M.; Rao, K. H.; S Dutt, C. B.

    2016-08-01

    This study examines the consistency between the AVHRR and MODIS normalized difference vegetation index (NDVI) datasets in estimating net primary productivity (NPP) and net ecosystem productivity (NEP) over India during 2001-2006 in a terrestrial ecosystem model. Harmonic analysis is employed to estimate seasonal components of the time series. The stationary components (representing long-term mean) of the respective NDVI time series are highly coherent and exhibit inherent natural vegetation characteristics with high values over the forest, moderate over the cropland, and small over the grassland. Both data exhibit strong semi-annual oscillations over the cropland dominated Indo-Gangetic plains while annual oscillations are strong over most parts of the country. MODIS has larger annual amplitude than that of the AVHRR. The similar variability exists on the estimates of NPP and NEP across India. In an annual scale, MODIS-based NPP budget is 1.78 PgC, which is 27% higher than the AVHRR- based estimate. It revealed that the Indian terrestrial ecosystem remained the sink of atmospheric CO 2 during the study period with 42 TgC y -1 NEP budget associated with MODIS-based estimate against 18 TgC y -1 for the AVHRR-based estimate.

  11. The effect of water vapour on the normalized difference vegetation index derived for the Sahelian region from NOAA AVHRR data

    NASA Technical Reports Server (NTRS)

    Justice, Christopher O.; Eck, T. F.; Tanre, Didier; Holben, B. N.

    1991-01-01

    The near-infrared channel of the NOAA advanced very high resolution radiometer (AVHRR) contains a water vapor absorption band that affects the determination of the normalized difference vegetation index (NDVI). Daily and seasonal variations in atmospheric water vapor within the Sahel are shown to affect the use of the NDVI for the estimation of primary production. This water vapor effect is quantified for the Sahel by radiative transfer modeling and empirically using observations made in Mali in 1986.

  12. Towards the improvement of the NCEP Noah land surface model in the North American Land Data Assimilation System during the warm season

    NASA Astrophysics Data System (ADS)

    Wei, H.; Mitchell, K.; Ek, M.

    2006-05-01

    The NCEP Noah land surface model (LSM) has been extensively evaluated with in situ observations over the southern Great Plains during the North American Land Data Assimilation System (NLDAS) Phase I simulation periods (May - September of 1998 and 1999). The model does a fairly good job but still some discrepancies in the surface energy partition between model and observations. The Bowen ratio is too low in the spring and too high in the summer. To improve the performance, we have further refined some parameters particularly those related to the calculation of canopy resistance such as the soil moisture stress function, minimum canopy resistance values. Varied LAI has been applied as well to reflect its seasonal variation which has significant consequence on the temporal evolution of surface fluxes. The diagnose shows how the model can be improved. All the improvement from this study will be carried over to NLDAS Phase II, which will carry over a long-term 25-30 year retrospective simulation for drought monitoring and other purposes.

  13. Seasonal-scale Observational Data Analysis and Atmospheric Phenomenology for the Cold Land Processes Experiment

    NASA Technical Reports Server (NTRS)

    Poulos, Gregory S.; Stamus, Peter A.; Snook, John S.

    2005-01-01

    The Cold Land Processes Experiment (CLPX) experiment emphasized the development of a strong synergism between process-oriented understanding, land surface models and microwave remote sensing. Our work sought to investigate which topographically- generated atmospheric phenomena are most relevant to the CLPX MSA's for the purpose of evaluating their climatic importance to net local moisture fluxes and snow transport through the use of high-resolution data assimilation/atmospheric numerical modeling techniques. Our task was to create three long-term, scientific quality atmospheric datasets for quantitative analysis (for all CLPX researchers) and provide a summary of the meteorologically-relevant phenomena of the three MSAs (see Figure) over northern Colorado. Our efforts required the ingest of a variety of CLPX datasets and the execution an atmospheric and land surface data assimilation system based on the Navier-Stokes equations (the Local Analysis and Prediction System, LAPS, and an atmospheric numerical weather prediction model, as required) at topographically- relevant grid spacing (approx. 500 m). The resulting dataset will be analyzed by the CLPX community as a part of their larger research goals to determine the relative influence of various atmospheric phenomena on processes relevant to CLPX scientific goals.

  14. The impact of anthropogenic land-cover change on the Florida Peninsula Sea Breezes and warm season sensible weather

    USGS Publications Warehouse

    Marshall, C.H.; Pielke, R.A., Sr.; Steyaert, L.T.; Willard, D.A.

    2004-01-01

    During the twentieth century, the natural landscape of the Florida peninsula was transformed extensively by agriculture, urbanization, and the diversion of surface water features. The purpose of this paper is to present a numerical modeling study in which the possible impacts of this transformation on the warm season climate of the region were investigated. For three separate July-August periods (1973, 1989, and 1994), a pair of simulations was performed with the Regional Atmospheric Modeling System. Within each pair, the simulations differed only in the specification of land-cover class. The two different classes were specified using highly detailed datasets that were constructed to represent pre-1900 natural land cover and 1993 land-use patterns, thus capturing the landscape transformation within each pair of simulations. When the pre-1900 natural cover was replaced with the 1993 land-use dataset, the simulated spatial patterns of the surface sensible and latent heat flux were altered significantly, resulting in changes in the structure and strength of climatologically persistent, surface-forced mesoscale circulations-particularly the afternoon sea-breeze fronts. This mechanism was associated with marked changes in the spatial distribution of convective rainfall totals over the peninsula. When averaged over the model domain, this redistribution was reflected as an overall decrease in the 2-month precipitation total. In addition, the domain average of the diurnal cycle of 2-m temperature was amplified, with a noted increase in the daytime maximum. These results were consistent among all three simulated periods, and largely unchanged when subjected to a number of model sensitivity factors. Furthermore, the model results are in reasonable agreement with an analysis of observational data that indicates decreasing regional precipitation and increasing daytime maximum temperature during the twentieth century. These results could have important implications for water

  15. AVHRR image navigation - Summary and review

    NASA Technical Reports Server (NTRS)

    Emery, William J.; Brown, Jim; Nowak, Z. Paul

    1989-01-01

    The navigation of imagery from polar orbiting weather satellites includes the correction for geometric distortions due to earth shape/earth rotation, satellite orbit variations, and satellite attitude along with the resampling of the satellite image to a selected geographic map projection. The routine image navigation procedure also compensates for the distortion of the satellite imagery due to the nonlinear scanning of the sensor system. This paper reviews general methods for performing this image navigation, ranging from a method that assumes no orbital information and, thus, relies on nominal orbital parameter values and image corrections computed by matching ground control points (GCPs), to a method that uses high-quality satellite ephemeris data to make the correction with a limited number of GCPs. A procedure to optimize the image navigation by using a spatial remapping, or interpolation, is introduced and outlined. Recommendations are made for people interested in the processing of AVHRR imagery.

  16. Evapotranspiration from combined reflected solar and emitted terrestrial radiation - Preliminary FIFE results from AVHRR data

    NASA Astrophysics Data System (ADS)

    Goward, S. N.; Hope, A. S.

    The relation between remotely sensed spectral vegetation indices and thermal IR measurements is studied. Land surface evapotranspiration is evaluated based on this relationship. Analysis of the AVHRR data, obtained in Kansas in 1987, reveal a strong correlation between the spectral vegetation indices and surface temperature and this relation covaries with surface moisture conditions. It is noted that the relation between remotely sensed measurements of canopy green foliage and surface temperature is useful for examining variations in the interface thermal inertia and energy balance Bowen ratio.

  17. Evapotranspiration from combined reflected solar and emitted terrestrial radiation - Preliminary FIFE results from AVHRR data

    NASA Technical Reports Server (NTRS)

    Goward, S. N.; Hope, A. S.

    1989-01-01

    The relation between remotely sensed spectral vegetation indices and thermal IR measurements is studied. Land surface evapotranspiration is evaluated based on this relationship. Analysis of the AVHRR data, obtained in Kansas in 1987, reveal a strong correlation between the spectral vegetation indices and surface temperature and this relation covaries with surface moisture conditions. It is noted that the relation between remotely sensed measurements of canopy green foliage and surface temperature is useful for examining variations in the interface thermal inertia and energy balance Bowen ratio.

  18. Analysis of land and lake surface temperature patterns during the open water and ice growth seasons in the Great Slave Lake region, Canada, from MODIS (2002-2009)

    NASA Astrophysics Data System (ADS)

    Kheyrollah Pour, H.; Duguay, C. R.

    2010-12-01

    It is now well recognized that lakes can have a considerable influence on local and regional weather and climate. Air-water exchanges of heat and moisture have climatological implications for lakes and also the climate in the vicinity of the lakes. Temperature changes in lakes are strongly influenced by changes in seasonal air temperature. Daily temperature variations also affect the temperature of lakes, especially in the surface layers. The most practical way to obtain continuous measurements of surface temperature is by means of satellite remote sensing. In this study, satellite-derived land surface temperature (LST) products from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Earth Observing System Terra and Aqua satellite platforms are used to analyse land and lake surface temperature patterns during the open water and ice growth seasons (2002-2009) in the Great Slave Lake (GSL) region, Canada. Land and lake temperatures from MODIS are contrasted and compared with near-surface air temperature measurements obtained from two nearby weather stations (Yellowknife and Hay River). Early results show that surface water temperature on GSL is colder than the surrounding land in the first two months of the open water season (June-July). It becomes equivalent to that of land in August and then becomes warmer starting in September until spring thaw. During the winter ice growth season, the lake loses heat by conduction through the upper ice surface due to the gradient from the relatively warmer water below the ice and the colder air above the ice/snow interface. For this period, GSL remains warmer than land until spring break-up. For a few weeks, between the initiation of break-up until the lake becomes free of ice, land is warmer since spring melt proceeds more quickly on land than on GSL. Mean monthly MODIS LST values on GSL (2002-2009) are shown to vary from -21±2 (February) to 10±2 (August).

  19. Capability of AVHRR data in discriminating rangeland cover mixtures

    USGS Publications Warehouse

    Senay, Gabriel B.; Elliott, R.L.

    2002-01-01

    A combination of high temporal resolution Advanced Very High Resolution Radiometer (AVHRR) data and high spatial information Map Information Analysis and Display System (MIADS) landuse/landcover data from the United States Department of Agriculture-Natural Resources Conservation Service (USDA-NRCS) were used to investigate the feasibility of using the combined dataset for regional evapotranspiration (ET) studies. It was shown that the biweekly maximum Normalized Difference Vegetation Index (NDVI) composite AVHRR data were capable of discriminating rangelands with different types of trees and shrubs species. AVHRR data also showed a potential to distinguish canopy cover differences within a mix of similar species. The combination of MIADS data and AVHRR data can be used to study temporal dynamics of various cover types for use in regional ET estimates.

  20. The impact of land use, season, age, and sex on the prevalence and intensity of Baylisascaris procyonis infections in raccoons (Procyon lotor) from Ontario, Canada.

    PubMed

    Jardine, Claire M; Pearl, David L; Puskas, Kirstie; Campbell, Doug G; Shirose, Lenny; Peregrine, Andrew S

    2014-10-01

    We assessed the impact of land use, demographic factors, and season on the prevalence and intensity of Baylisascaris procyonis infections in raccoons (Procyon lotor) in Ontario, Canada. From March to October 2012, we recorded the number of B. procyonis in the intestinal tracts of raccoons submitted to the Canadian Cooperative Wildlife Health Centre for necropsy. Logistic regression models were used to examine associations between the presence of B. procyonis and age (adult, juvenile), sex, land use (suburban/urban, rural), and season (March-June and July-October); negative binomial regression models were used to examine associations between the number of worms and the same variables. We detected B. procyonis in 38% (95% confidence interval 30-47%) of raccoons examined (n=128). In univariable models, the presence of B. procyonis was significantly associated with age, land use, and season (P<0.05). Age was not retained in the multivariable model, and the impact of sex on the presence of B. procyonis varied with land use and season. For example, from March to June, suburban/urban male raccoons were significantly more likely to be infected with B. procyonis than suburban/urban female raccoons. However, later in the summer (July-October), the opposite was true. The median number of worms in the intestinal tracts of infected raccoons was 3 (range 1-116). Worm number was significantly associated with age and season in univariable models; in the multivariable model, juvenile raccoons had significantly more worms than adults, and the impact of season on the number of worms varied with land use and sex. A better understanding of the epidemiology of B. procyonis in raccoons is important for developing appropriate strategies to reduce the risk of human exposure to B. procyonis from the environment. PMID:25098302

  1. Integrating vegetation index time series and meteorological data to understand the effect of the land use/land cover (LULC) in the climatic seasonality of the Brazilian Cerrado

    NASA Astrophysics Data System (ADS)

    Lins, D. B.; Zullo, J.; Friedel, M. J.

    2013-12-01

    The Cerrado (savanna ecosystem) of São Paulo state (Brazil) represent a complex mosaic of different typologies of uses, actors and biophysical and social restrictions. Originally, 14% of the state of São Paulo area was covered by the diversity of Cerrado phytophysiognomies. Currently, only 1% of this original composition remains fragmented into numerous relicts of biodiversity, mainly concentrated in the central-eastern of the state. A relevant part of the fragments are found in areas of intense coverage change by human activities, whereas the greatest pressure comes from sugar cane cultivation, either by direct replacement of Cerrado vegetation or occupying pasture areas in the fragments edges. As a result, new local level dynamics has been introduced, directly or indirectly, affecting the established of processes in climate systems. In this study, the main goal is analyzing the relationship between the Cerrado landscape changing and the climate dynamics in regional and local areas. The multi-temporal MODIS 250 m Vegetation Index (VI) datasets (period of 2000 to 2012) are integrated with precipitation data of the correspondent period (http://www.agritempo.gov.br/),one of the most important variable of the spatial phytophysiognomies distribution. The integration of meteorological data enable the development of an integrated approach to understand the relationship between climatic seasonality and the changes in the spatial patterns. A procedure to congregated diverse dynamics information is the Self Organizing Map (SOM, Kohonen, 2001), a technique that relies on unsupervised competitive learning (Kohonen and Somervuo 2002) to recognize patterns. In this approach, high-dimensional data are represented on two dimensions, making possible to obtain patterns that takes into account information from different natures. Observed advances will contribute to bring machine-learning techniques as a valid tool to provide improve in land use/land cover (LULC) analyzes at

  2. Computation and use of the reflectivity at 3.75 micrometers from AVHRR thermal channels

    NASA Technical Reports Server (NTRS)

    Roger, J. C.; Vermote, E. F.

    1994-01-01

    Global study of land surface properties uses AVHRR channels 1 and 2, but channel 3 may be of interest, although its use requires preprocessing. It consists of both a reflective part and an emissive part, the former can be derived from T3, T4 and T5. Since the water vapor affects channel 3, its content is retrieved from the channel 4 and 5 using the split window technique. A formula of reflective part retrieval at 3.75 micrometers is tested in the case of sunglint observations where the emissivities of channels 4 and 5 can be set to the unity. The formula is adapted and validated to land surface using the FIFE-87 data set. Preliminary applications of the reflectance at 3.75 micrometers to the studies of surface properties retrieval, aerosol retrieval over land, and desertic aerosol retrieval, are addressed.

  3. Contributions of Deciduous and Evergreen Trees to the Seasonal Dynamics of CO2 and Water Vapor Exchange Over Developed Land in the Midcontinental United States

    NASA Astrophysics Data System (ADS)

    Peters, E. B.; Montgomery, R.; McFadden, J. P.

    2007-12-01

    Half the world's population currently lives in urbanized areas, a proportion expected to increase to 60% by 2030. The clearing of agricultural and natural ecosystems for urban and suburban development is consequently one of the fastest rates of land use change around the world. Although developed land areas represent major sources of CO2 and alter hydrology, they are also ecosystems with significant vegetation cover that takes up CO2 and humidifies the atmospheric boundary layer. Direct measurements are needed to develop a mechanistic understanding of how vegetation contributes to the land-based CO2 sinks and evapotranspiration in developed areas, especially residential developed land which accounts for most of the land-use change in the United States. We quantified whole-tree transpiration, and modeled canopy conductance and canopy photosynthesis using thermal dissipation sap flow and leaf-level gas exchange measurements on stands of deciduous and evergreen trees in a suburban residential neighborhood of Minneapolis-St. Paul, Minnesota. A suite of environmental variables was continuously monitored at each site. During the 2007 growing season, seasonal drought and synoptic and diurnal variations of vapor pressure deficit (VPD) strongly controlled transpiration and photosynthesis in both the deciduous and the evergreen stands. The results are analyzed against a phenology data set (including leaf area index (LAI), and plant and soil biophysical properties) measured at a larger number of stands within a suburban region during the 2006 growing season. These results will allow us to determine the relative contributions of different tree plant functional types to the seasonal dynamics of CO2 exchange and evapotranspiration in developed land, and to scale up the effect of these land cover types on regional carbon and water budgets. This study is a contribution to the North American Carbon Program (NACP) Mid-Continent Intensive Field Campaign.

  4. A Satellite Based Modeling Framework for Estimating Seasonal Carbon Fluxes Over Agricultural Lands

    NASA Astrophysics Data System (ADS)

    Bandaru, V.; Houborg, R.; Izaurralde, R. C.

    2014-12-01

    Croplands are typically characterized by fine-scale heterogeneity, which makes it difficult to accurately estimate cropland carbon fluxes over large regions given the fairly coarse spatial resolution of high-frequency satellite observations. It is, however, important that we improve our ability to estimate spatially and temporally resolved carbon fluxes because croplands constitute a large land area and have a large impact on global carbon cycle. A Satellite based Dynamic Cropland Carbon (SDCC) modeling framework was developed to estimate spatially resolved crop specific daily carbon fluxes over large regions. This modeling framework uses the REGularized canopy reFLECtance (REGFLEC) model to estimate crop specific leaf area index (LAI) using downscaled MODIS reflectance data, and subsequently LAI estimates are integrated into the Environmental Policy Integrated Model (EPIC) model to determine daily net primary productivity (NPP) and net ecosystem productivity (NEP). Firstly, we evaluate the performance of this modeling framework over three eddy covariance flux tower sites (Bondville, IL; Fermi Agricultural Site, IL; and Rosemount site, MN). Daily NPP and NEP of corn and soybean crops are estimated (based on REGFLEC LAI) for year 2007 and 2008 over the flux tower sites and compared against flux tower observations and model estimates based on in-situ LAI. Secondly, we apply the SDCC framework for estimating regional NPP and NEP for corn, soybean and sorghum crops in Nebraska during year 2007 and 2008. The methods and results will be presented.

  5. A Satellite Based Modeling Framework for Estimating Seasonal Carbon Fluxes Over Agricultural Lands

    NASA Astrophysics Data System (ADS)

    Bandaru, V.; Izaurralde, R. C.; Sahajpal, R.; Houborg, R.; Milla, Z.

    2013-12-01

    Croplands are typically characterized by fine-scale heterogeneity, which makes it difficult to accurately estimate cropland carbon fluxes over large regions given the fairly coarse spatial resolution of high-frequency satellite observations. It is, however, important that we improve our ability to estimate spatially and temporally resolved carbon fluxes because croplands constitute a large land area and have a large impact on global carbon cycle. A Satellite based Dynamic Cropland Carbon (SDCC) modeling framework was developed to estimate spatially resolved crop specific daily carbon fluxes over large regions. This modeling framework uses the REGularized canopy reFLECtance (REGFLEC) model to estimate crop specific leaf area index (LAI) using downscaled MODIS reflectance data, and subsequently LAI estimates are integrated into the Environmental Policy Integrated Model (EPIC) model to determine daily net primary productivity (NPP) and net ecosystem productivity (NEP). Firstly, we evaluate the performance of this modeling framework over three eddy covariance flux tower sites (Bondville, IL; Fermi Agricultural Site, IL; and Rosemount site, MN). Daily NPP and NEP of corn and soybean crops are estimated (based on REGFLEC LAI) for year 2007 and 2008 over the flux tower sites and compared against flux tower observations and model estimates based on in-situ LAI. Secondly, we apply the SDCC framework for estimating regional NPP and NEP for corn, soybean and sorghum crops in Nebraska during year 2007 and 2008. The methods and results will be presented.

  6. Temporal and spatial change in coastal ecosystems using remote sensing: Example with Florida Bay, USA, emphasizing AVHRR imagery

    SciTech Connect

    Stumpf, R.P.; Frayer, M.L.

    1997-06-01

    Florida Bay, at the southern tip of Florida, USA, has undergone dramatic changes in recent years. Following seagrass dieoffs starting in the late 1980`s, both algal blooms and high turbidity (the latter from resuspended sediments) have been reported as more common in the Bay. Remotely sensed data, particularly from the AVHRR (advanced very high resolution radiometer), can provide information on conditions prior to the start of monitoring programs as well as provide additional spatial detail on water clarity and particulate loads in this estuary . The AVHRR record currently available to us consists of over 600 usable scenes from December, 1989. Comparisons with field data have provided relationships with light attenuation, total suspended solids, and other turbidity measures. The imagery shows the seasonal change in turbidity resulting from high winds associated with winter cold fronts. Over the seven-year record, areas of clear water have decreased in the north-central Bay, while expanding in the southwestern Bay.

  7. Using Ecosystem Functional Types in land-surface modeling to characterize and monitor the spatial and inter-annual variability of vegetation dynamics

    NASA Astrophysics Data System (ADS)

    Alcaraz-Segura, D.; Paruelo, J.; Epstein, H. E.; Berbery, E. H.; Kalnay, E.; Cabello, J.; Jobbagy, E. G.

    2009-12-01

    Including the inter-annual variability of vegetation dynamics into land-surface models is necessary to account for land use/cover change effects on Global Climate Models. However, land-surface models use land-cover classifications dictated by structural attributes of vegetation that have little sensitivity to environmental change and are difficult to update and result in a delayed response. This rigid representation of vegetation reduces the ability of models to represent rapid changes including land-use shifts, fires, floods, droughts, and insect outbreaks. Functional attributes of vegetation describing its energy and matter exchange with the atmosphere, have a shorter response to environmental changes and are relatively easy to monitor with satellite data. We applied the concept of Ecosystem Functional Types (EFTs; patches of the land-surface with similar carbon gain dynamics) to characterize the spatial and inter-annual variability of vegetation dynamics across natural and agricultural systems in the La Plata Basin of South America. Three descriptors of carbon gain dynamics were derived from seasonal curves of Normalized Difference Vegetation Index (NDVI) and used to identify EFTs based on annual mean (surrogate of primary production), seasonal coefficient of variation (indicator of seasonality), and date of maximum NDVI (descriptor of phenology). Results from two NDVI datasets were compared (AVHRR-LTDR version 2, 1982-1999, 15-day and 5 km resolution; and MOD13A2 MODIS, 2000-2006, 16-day and 1 km resolution). Both datasets showed greater spatial and inter-annual variability of the EFT composition in agricultural areas compared to natural areas. During 1982-1999, the percentage of the La Plata Basin occupied by EFTs with low productivity, high seasonality, and spring and fall NDVI maxima tended to decrease, while EFTs with high productivity, low seasonality, and summer maxima tended to increase. We speculate that these trends may be due to a positive trend in

  8. Time series decomposition of remotely sensed land surface temperature and investigation of trends and seasonal variations in surface urban heat islands

    NASA Astrophysics Data System (ADS)

    Quan, Jinling; Zhan, Wenfeng; Chen, Yunhao; Wang, Mengjie; Wang, Jinfei

    2016-03-01

    Previous time series methods have difficulties in simultaneous characterization of seasonal, gradual, and abrupt changes of remotely sensed land surface temperature (LST). This study proposed a model to decompose LST time series into trend, seasonal, and noise components. The trend component indicates long-term climate change and land development and is described as a piecewise linear function with iterative breakpoint detection. The seasonal component illustrates annual insolation variations and is modeled as a sinusoidal function on the detrended data. This model is able to separate the seasonal variation in LST from the long-term (including gradual and abrupt) change. Model application to nighttime Moderate Resolution Imaging Spectroradiometer (MODIS)/LST time series during 2000-2012 over Beijing yielded an overall root-mean-square error of 1.62 K between the combination of the decomposed trend and seasonal components and the actual MODIS/LSTs. LST decreased (~ -0.086 K/yr, p < 0.1) in 53% of the study area, whereas it increased with breakpoints in 2009 (~0.084 K/yr before and ~0.245 K/yr after 2009) between the fifth and sixth ring roads. The decreasing trend was stronger over croplands than over urban lands (p < 0.05), resulting in an increasing trend in surface urban heat island intensity (SUHII, 0.022 ± 0.006 K/yr). This was mainly attributed to the trends in urban-rural differences in rainfall and albedo. The SUHII demonstrated a concave seasonal variation primarily due to the seasonal variations of urban-rural differences in temperature cooling rate (related to canyon structure, vegetation, and soil moisture) and surface heat dissipation (affected by humidity and wind).

  9. A spatial analysis of seasonal variation in dissolved nutrients and greenhouse gasses along two river networks draining watersheds of contrasting land use

    NASA Astrophysics Data System (ADS)

    Dee, Martha; Tank, Jennifer; Marzadri, Alessandra; Tonina, Daniele; Bellin, Alberto

    2016-04-01

    Widespread human activity such as agriculture and urban land use has increased the availability of dissolved reactive nutrients in river networks. As such, the biogeochemical processing of these nutrients in streams and rivers may make them significant sources of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) gasses which are responsible for the majority of heat trapping capacity in the modern atmosphere. We replicated a synoptic sampling regime across seasons to measure dissolved inorganic nutrients and gasses at 80 stream/river sites in two contrasting U.S. watersheds, the Manistee River Basin (MI) which is ~83% forested and the Tippecanoe River Basin (IN) is 82% agricultural land use. We used Spatial Stream Network (SSN) geostatistical modeling to differentiate the spatial heterogeneity of dissolved nutrients and greenhouse gasses among seasons and between watersheds of contrasting land use. We modeled the spatial distribution of dissolved nutrients in each basin to separate the effects of catchment and in-stream processes compounded with fine-scale versus broad-scale gradients of stream water chemistry. Preliminary results suggest that dissolved nutrient and gas concentrations in both river networks during winter and spring were strongly influenced by land use type, exhibiting an "accumulating" broad-scale gradient. In contrast, during the primary growing season of summer and early autumn we found that networks displayed an array of "hotspots" or small-scale spatial dependence. As the world's land area undergoes continued development, high-resolution datasets will be critical in understanding the seasonal heterogeneity of spatial patterns along river networks and will allow us to predict the future impact of land use in a changing climate.

  10. A New Look at the AVHRR Polar Pathfinder Data and Why Good Data Sometimes Goes Bad

    NASA Astrophysics Data System (ADS)

    Grant, G.; Campbell, G.; Gallaher, D. W.; Stroeve, J. C.; Key, J. R.

    2012-12-01

    Intensification of global warming in recent decades has caused a rise of interest in year-to-year and decadal-scale climate variability in the Arctic. This is because the Arctic is believed to be one of the most sensitive and vulnerable regions to climatic changes. The enhanced vulnerability of the Arctic results from several positive feedbacks, including the temperature-albedo-melt feedback and the cloud-radiation feedback. Recent observations of record regional anomalies in sea ice extent, thinning of the margins of the Greenland ice sheet and reduction in northern hemispheric snow cover may reflect the effect of these feedbacks. The new AVHRR Polar Pathfinder (APP) data set at the National Snow and Ice Data Center (NSIDC) spans 30 years (1981-2011), providing a long-term record of surface temperature, albedo and cloud cover for investigation of several of these feedback mechanisms. Accuracy of long-term trend analysis depends on the ability to produce a consistent data record over multiple satellites and AVHRR sensor generations. While orbital parameters, resolutions, and sensors themselves have undergone only minor changes or stayed the same, calibration coefficients, gridding and projection parameters, and other data processing details have evolved over time. Unless the periodic post-processing is extremely methodical and quality controlled, it is likely that some changes will be missed: errors will creep in 'under the radar'. Analysis shows that updated calibration coefficients for the old AVHRR Polar Pathfinder visible channels were not applied correctly. Furthermore, image georeferencing changed significantly between software versions, and accurate swath compositing failed for an entire summer season. When viewed using only a small spatial extent or limited time span, these errors were not readily apparent. However, examination of the entire old APP albedo data record for the Greenland Ice sheet using high spatiotemporal resolution highlights the problems

  11. Diurnal and Seasonal Cold Lands Signatures in SSM/I-scale Microwave Radiometry of the North Slope of Alaska

    NASA Technical Reports Server (NTRS)

    Kim, Edward J.; England, Anthony W.; Hildebrand, Peter H. (Technical Monitor)

    2001-01-01

    In this paper, we explore scaling and data assimilation-related issues associated with utilizing passive microwave satellite observations of Cold Lands-in this case, the climatologically and ecologically sensitive arctic tundra. Our approach expands on our earlier work using a one-year dataset from the Radiobrightness Energy Balance Experiment-3 (REBEX-3). REBEX-3 featured a tower-based SSM/I (Special Sensor Microwave/Imager) simulator deployed on the North Slope of Alaska in 1994-95. Two findings are significant here. First, a comparison of tower and satellite signatures at 19 and 37 GHz strongly suggested that the North Slope is radiometrically homogeneous for spatial scales up to SSM/I footprints (approximately 25 km), an unusual and valuable characteristic for monitoring and retrieving land surface conditions. And second, at the plot scale, signatures of snow/no-snow and freeze/thaw transitions were identifiable for tussock tundra land cover, so that even snow-free frozen tundra could be unambiguously distinguished from tundra covered with dry snow, another unusual and valuable characteristic. We present results from analyzing satellite brightness signatures of selected North Slope pixels corresponding to instrumented sites along a transect from the Brooks Range to the Arctic Ocean. A custom EASE (Equal Area Scalable Earth)-Grid processor was used to extract SSMJI data for every orbit with observations of this region during the 1994-95 year. The resulting high temporal-resolution (4-8 points/day), gridded data were then analyzed for evidence of the same diurnal and seasonal signatures seen at the plot scale (through micrometeorological and/or brightness data). Differences between satellite and tower brightness observations are quantified for various conditions at the REBEX-3 site. Such differences from the less-frequent and/or larger-scale satellite observations represent a form of input 'noise' in data assimilation applications. For the other sites, the

  12. Angular and Seasonal Variation of Spectral Surface Reflectance Ratios: Implications for the Remote Sensing of Aerosol over Land

    NASA Technical Reports Server (NTRS)

    Remer, L. A.; Wald, A. E.; Kaufman, Y. J.

    1999-01-01

    We obtain valuable information on the angular and seasonal variability of surface reflectance using a hand-held spectrometer from a light aircraft. The data is used to test a procedure that allows us to estimate visible surface reflectance from the longer wavelength 2.1 micrometer channel (mid-IR). Estimating or avoiding surface reflectance in the visible is a vital first step in most algorithms that retrieve aerosol optical thickness over land targets. The data indicate that specular reflection found when viewing targets from the forward direction can severely corrupt the relationships between the visible and 2.1 micrometer reflectance that were derived from nadir data. There is a month by month variation in the ratios between the visible and the mid-IR, weakly correlated to the Normalized Difference Vegetation Index (NDVI). If specular reflection is not avoided, the errors resulting from estimating surface reflectance from the mid-IR exceed the acceptable limit of DELTA-rho approximately 0.01 in roughly 40% of the cases, using the current algorithm. This is reduced to 25% of the cases if specular reflection is avoided. An alternative method that uses path radiance rather than explicitly estimating visible surface reflectance results in similar errors. The two methods have different strengths and weaknesses that require further study.

  13. Calibration of AVHRR sensors using the reflectance-based method

    NASA Astrophysics Data System (ADS)

    Czapla-Myers, Jeffrey S.; Thome, Kurtis J.; Leisso, Nathan P.

    2007-09-01

    The Remote Sensing Group at the University of Arizona has been active in the vicarious calibration of numerous sensors through the use of ground-based test sites. Recent efforts have included work to develop cross-calibration information between these sensors using the results from the reflectance-based approach. The current work extends the cross-calibration to the AVHRR series of sensors, specifically NOAA-17, and NOAA-18. The results include work done based on data collected by ground-based personnel nearly coincident with the sensor overpasses. The available number of calibrations for the AVHRR series is increased through a set of ground-based radiometers that are deployed without the need for on-site personnel and have been operating for more than three years at Railroad Valley Playa. The spectral, spatial, and temporal characteristics of the 1-km2 large-footprint site at Railroad Valley are well understood. It is therefore well suited for the radiometric calibration of AVHRR, which has a nadir-viewing footprint of 1.1 x 1.1 km. The at-sensor radiance is predicted via a radiative transfer code using atmospheric data from a fully-automated solar radiometer. The results for AVHRR show that errors are currently larger for the automated data sets, but results indicate that the AVHRR sensors studied in this work are consistent with the Aqua and Terra MODIS sensors to within the uncertainties of each sensor.

  14. Temporal Dynamics of Vegetation Phenological in Mongolia Using NOAA-AVHRR Data -- the Saw-tooth Pattern

    NASA Astrophysics Data System (ADS)

    Karnieli, A.; Bayasgalan, M.; Khudulmur, S.; Bayarjargal, Y.; Tucker, C. J.

    2004-12-01

    The objective of this study was to examine the temporal trend of the Mongolian natural vegetation phenology during 18 years between 1981 and 1999, in various ecosystems, by using two Pathfinder NOAA-AVHRR Land (PAL) products -- the Normalized Different Vegetation Index (NDVI) and Land Surface Temperature (LST). Mongolia was selected as a study area for implementing the above objectives since it enables a regional research (rather than continental or global scale). The north-south cross section is relatively short (ca. 500 km) between latitude 42o to 52o N, and covers 6 different ecosystems -- Tundra, Mountain, Forest Steppe, Steppe, Desert Steppe, and Desert. Along this cross section, precipitation ranges from more than 350 (in the north) to less than 75 mm. The entire territory consists only on natural vegetation without anthropogenic influences such as urban heat island, industry, agricultural crops etc. For estimating the growing season dynamics, an accurate determination of the beginning (greenup onset) and ending (senescence, or decline) dates of the vegetation phenology were computed. For achieving these dates four combined criteria were calculated based on the NDVI and LST datasets. Main finding of the project shows that no significant results are achieved when analyzing the entire study period over 18 years. However, when breaking the period into two sub-periods, from 1982 to 1991 and from 1992 to 1999, phenology parameters can be easily detected and results are more significant. It is shown that on the average of the entire territory, the onset starts 10 and 16 days earlier, and the decline occurs 6 and 3 days later, during the first and second sub-periods, respectively. Consequently, on the average the phenology cycle of the growing season lasts 17--19 days longer. The above-mentioned sub-periods can be visualized as a saw-tooth pattern. It is due to the eruption of Mount Pinatubo in the Philippines in June 1991, led to a global cooling of 0.5oC due to

  15. Role of Bandwidth in Computation of NDVI From Landsat TM and NOAA AVHRR Bands

    NASA Astrophysics Data System (ADS)

    Gupta, R. K.; Vijayan, D.; Prasad, T. S.; Tirumaladevi, N. Ch.

    The observations for wheat, onion, potato and chickpea over the Crop Growth Cycle (CGC) in 3 nm bandwidth were converted to AVHRR and TM bands in visible/red and near-IR spectral regions. Correlation between TM and AVHRR NDVI were very high for all these crops. The additional 0.725-0.76 μm bandwidth in AVHRR as compared to TM was causing reduction in NDVI values for AVHRR when crop NDVI value was more than 0.46

  16. The analysis of polar clouds from AVHRR satellite data using pattern recognition techniques

    NASA Technical Reports Server (NTRS)

    Smith, William L.; Ebert, Elizabeth

    1990-01-01

    The cloud cover in a set of summertime and wintertime AVHRR data from the Arctic and Antarctic regions was analyzed using a pattern recognition algorithm. The data were collected by the NOAA-7 satellite on 6 to 13 Jan. and 1 to 7 Jul. 1984 between 60 deg and 90 deg north and south latitude in 5 spectral channels, at the Global Area Coverage (GAC) resolution of approximately 4 km. This data embodied a Polar Cloud Pilot Data Set which was analyzed by a number of research groups as part of a polar cloud algorithm intercomparison study. This study was intended to determine whether the additional information contained in the AVHRR channels (beyond the standard visible and infrared bands on geostationary satellites) could be effectively utilized in cloud algorithms to resolve some of the cloud detection problems caused by low visible and thermal contrasts in the polar regions. The analysis described makes use of a pattern recognition algorithm which estimates the surface and cloud classification, cloud fraction, and surface and cloudy visible (channel 1) albedo and infrared (channel 4) brightness temperatures on a 2.5 x 2.5 deg latitude-longitude grid. In each grid box several spectral and textural features were computed from the calibrated pixel values in the multispectral imagery, then used to classify the region into one of eighteen surface and/or cloud types using the maximum likelihood decision rule. A slightly different version of the algorithm was used for each season and hemisphere because of differences in categories and because of the lack of visible imagery during winter. The classification of the scene is used to specify the optimal AVHRR channel for separating clear and cloudy pixels using a hybrid histogram-spatial coherence method. This method estimates values for cloud fraction, clear and cloudy albedos and brightness temperatures in each grid box. The choice of a class-dependent AVHRR channel allows for better separation of clear and cloudy pixels than

  17. Challenges of AVHRR Vegetation Data for Real Time Applications

    NASA Technical Reports Server (NTRS)

    Brown, Molly

    2008-01-01

    Remote sensing data has long been used to monitor global ecosystems for floods and droughts and AVHRR data, as one of the first product, has many users interested in receiving the data within hours of acquisition. With the introduction of a new series of sensors in 2000 (the AVHRR/3 series), the quality of the NDVI datasets available for real time environmental monitoring has declined. This paper provides evidence of problems of cloud contamination, calibration and noise in the real time data which are not present in the historical AVHRR NDVIg dataset. These differences introduce significant uncertainty in the use of the real time data, degrading their utility for detecting climate variations in near real time.

  18. AVHRR monitoring of U.S. crops during the 1988 drought

    NASA Technical Reports Server (NTRS)

    Teng, William L.

    1990-01-01

    Effects of the 1988 drought on crops in the U.S. Corn Belt were assessed and monitored by the Foreign Crop Condition Assessment Division (FCCAD), U.S. Department of Agriculture. The primary data were vegetation index numbers (VINs), each of which was calculated as an average vegetation index of a geographically referenced cell of AVHRR pixels. Using VINs, the FCCAD was able to detect the existence of drought early in the season, monitor changing conditions, and provide objective assessments of the drought's extent and severity. Field observations confirmed the image analyses, and underlined the importance of the timing of extreme weather events with respect to crop stages for interpreting VINs. The analyses were conducted in an operational environment, providing a unique test of the AVHRR data for large area, near real-time crop monitoring. Because large area, operational remote sensing of crops is quite different from traditional, controlled, small plot research studies, more work is needed to link the two; this would improve crop assessment capabilities.

  19. Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

    NASA Technical Reports Server (NTRS)

    Key, Jeff; Maslanik, James; Steffen, Konrad

    1994-01-01

    One essential parameter used in the estimation of radiative and turbulent heat fluxes from satellite data is surface temperature. Sea and land surface temperature (SST and LST) retrieval algorithms that utilize the thermal infrared portion of the spectrum have been developed, with the degree of success dependent primarily upon the variability of the surface and atmospheric characteristics. However, little effort has been directed to the retrieval of the sea ice surface temperature (IST) in the Arctic and Antarctic pack ice or the ice sheet surface temperature over Antarctica and Greenland. The reason is not one of methodology, but rather our limited knowledge of atmospheric temperature, humidity, and aerosol vertical, spatial and temporal distributions, the microphysical properties of polar clouds, and the spectral characteristics of snow, ice, and water surfaces. Over the open ocean the surface is warm, dark, and relatively homogeneous. This makes SST retrieval, including cloud clearing, a fairly straightforward task. Over the ice, however, the surface within a single satellite pixel is likely to be highly heterogeneous, a mixture of ice of various thicknesses, open water, and snow cover in the case of sea ice. Additionally, the Arctic is cloudy - very cloudy - with typical cloud cover amounts ranging from 60-90 percent. There are few observations of cloud cover amounts over Antarctica. The goal of this research is to increase our knowledge of surface temperature patterns and magnitudes in both polar regions, by examining existing data and improving our ability to use satellite data as a monitoring tool. Four instruments are of interest in this study: the AVHRR, ATSR, SMMR, and SSM/I. Our objectives are as follows. Refine the existing AVHRR retrieval algorithm defined in Key and Haefliger (1992; hereafter KH92) and applied elsewhere. Develop a method for IST retrieval from ATSR data similar to the one used for SST. Further investigate the possibility of estimating

  20. Linkages between Land Surface Phenology Metrics and Natural and Anthropogenic Events in Drylands (Invited)

    NASA Astrophysics Data System (ADS)

    de Beurs, K.; Brown, M. E.; Ahram, A.; Walker, J.; Henebry, G. M.

    2013-12-01

    Tracking vegetation dynamics across landscapes using remote sensing, or 'land surface phenology,' is a key mechanism that allows us to understand ecosystem changes. Land surface phenology models rely on vegetation information from remote sensing, such as the datasets derived from the Advanced Very High Resolution Radiometer (AVHRR), the newer MODIS sensors on Aqua and Terra, and sometimes the higher spatial resolution Landsat data. Vegetation index data can aid in the assessment of variables such as the start of season, growing season length and overall growing season productivity. In this talk we use Landsat, MODIS and AVHRR data and derive growing season metrics based on land surface phenology models that couple vegetation indices with satellite derived accumulated growing degreeday and evapotranspiration estimates. We calculate the timing and the height of the peak of the growing season and discuss the linkage of these land surface phenology metrics with natural and anthropogenic changes on the ground in dryland ecosystems. First we will discuss how the land surface phenology metrics link with annual and interannual price fluctuations in 229 markets distributed over Africa. Our results show that there is a significant correlation between the peak height of the growing season and price increases for markets in countries such as Nigeria, Somalia and Niger. We then demonstrate how land surface phenology metrics can improve models of post-conflict resolution in global drylands. We link the Uppsala Conflict Data Program's dataset of political, economic and social factors involved in civil war termination with an NDVI derived phenology metric and the Palmer Drought Severity Index (PDSI). An analysis of 89 individual conflicts in 42 dryland countries (totaling 892 individual country-years of data between 1982 and 2005) revealed that, even accounting for economic and political factors, countries that have higher NDVI growth following conflict have a lower risk of

  1. Landscape-scale characterization of vegetation phenology using AVHRR-NDVI and Landsat-TM data

    NASA Astrophysics Data System (ADS)

    Simoniello, Tiziana; Carone, M. T.; Lanfredi, Maria; Macchiato, Maria; Cuomo, Vincenzo

    2004-02-01

    The strict link between intra-annual vegetation dynamics (phenology) and Earth's climate makes phenological information fundamental to improve understanding and models of inter-annual variability in terrestrial carbon exchange and climate-biosphere interactions. In order to monitor phenology in a landscape characterized by heterogeneous features rapidly changing over the territory, we performed multitemporal classifications of NDVI-AVHRR data and interfaced them with Landsat-TM data and orography. The sample area is the Vulture basin (Southern Italy), where cultivated and densely vegetated areas coexist with urban and recently built industrial areas. These land cover patterns rapidly change over the territory at very small spatial scales; it is a complex zone very interesting for studying the use of remote sensing techniques in the integrated monitoring context. Clusters having homogeneous NDVI time behaviors were identified. In spite of its spatial resolution, AVHRR NDVI effectively picks up the characteristic phenology for different covers and altitudes. Moreover, some pixels having particular microclimate were clustered and their characterization was only possible by using orography and TM classification information. The comparison of two intra-annual classifications (1996 and 1998) showed that the proposed approach can be very useful for studying change in pattern of vegetation dynamics.

  2. AVHRR-based drought-observing system for monitoring the environment and socioeconomic activities

    NASA Astrophysics Data System (ADS)

    Kogan, F.

    From all natural disaster, drought is the least understandable and the most damaging environmental phenomenon. Although in pre-satellite era, climate data were used for drought monitoring, drought specifics created problems in early drought detection start/end, monitoring its expansion/contraction, intensity and area coverage and the most important, timely estimation of the impacts on the environment and socioeconomic activities. The latest prevented to take prompt measures in mitigating negative consequences of drought for the society. Advances in remote sensing of the past ten years, contributed to the development of comprehensive drought monitoring system and numerous applications, which helped to make decisions for monitoring the environment and predicting sustainable socioeconomic activities. This paper discusses satellite-based land-surface observing system, which provides wells of information used for monitoring such unusual natural disaster as drought. This system was developed from the observations of the Advanced Very High Resolution Radiometer (AVHRR) flown on NOAA operational polar-orbiting satellites. The AVHRR data were packed into the Global Vegetation Index (GVI) product, which have served the global community since 1981. The GVI provided reflectances and indices (4 km spacial resolution) every seven days for each 16 km map cell between 75EN and 55ES covering all land ecosystems. The data includes raw and calibrated radiances in the visible, near infrared and infrared spectral bands, processed (with eliminated high frequency noise) radiances, normalized difference vegetation index (NDVI), 20-year climatology, vegetation condition indices and also products, such as vegetation health, drought, vegetation fraction, fire risk etc. In the past ten years, users around the world used this information addressing different issues of drought impacts on socioeconomic activities and responded positively to real time drought information place regularly on the

  3. BOREAS Level 3-b AVHRR-LAC Imagery: Scaled At-sensor Radiance in LGSOWG Format

    NASA Technical Reports Server (NTRS)

    Hall, Forrest G. (Editor); Nickeson, Jaime; Newcomer, Jeffrey A.; Cihlar, Josef

    2000-01-01

    The BOREAS Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. Data acquired from the AVHRR instrument on the NOAA-9, -11, -12, and -14 satellites were processed and archived for the BOREAS region by the MRSC and BORIS. The data were acquired by CCRS and were provided for use by BOREAS researchers. A few winter acquisitions are available, but the archive contains primarily growing season imagery. These gridded, at-sensor radiance image data cover the period of 30-Jan-1994 to 18-Sep-1996. Geographically, the data cover the entire 1,000-km x 1,000-km BOREAS region. The data are stored in binary image format files.

  4. Effect of land cover and use on dry season river runoff, runoff efficiency, and peak storm runoff in the seasonal tropics of Central Panama

    USGS Publications Warehouse

    Ogden, Fred L.; Crouch, Trey D.; Stallard, Robert F.; Hall, Jefferson S.

    2013-01-01

    A paired catchment methodology was used with more than 3 years of data to test whether forests increase base flow in the dry season, despite reduced annual runoff caused by evapotranspiration (the “sponge-effect hypothesis”), and whether forests reduce maximum runoff rates and totals during storms. The three study catchments were: a 142.3 ha old secondary forest, a 175.6 ha mosaic of mixed age forest, pasture, and subsistence agriculture, and a 35.9 ha actively grazed pasture subcatchment of the mosaic catchment. The two larger catchments are adjacent, with similar morphology, soils, underlying geology, and rainfall. Annual water balances, peak runoff rates, runoff efficiencies, and dry season recessions show significant differences. Dry season runoff from the forested catchment receded more slowly than from the mosaic and pasture catchments. The runoff rate from the forest catchment was 1–50% greater than that from the similarly sized mosaic catchment at the end of the dry season. This observation supports the sponge-effect hypothesis. The pasture and mosaic catchment median runoff efficiencies were 2.7 and 1.8 times that of the forest catchment, respectively, and increased with total storm rainfall. Peak runoff rates from the pasture and mosaic catchments were 1.7 and 1.4 times those of the forest catchment, respectively. The forest catchment produced 35% less total runoff and smaller peak runoff rates during the flood of record in the Panama Canal Watershed. Flood peak reduction and increased streamflows through dry periods are important benefits relevant to watershed management, payment for ecosystem services, water-quality management, reservoir sedimentation, and fresh water security in the Panama Canal watershed and similar tropical landscapes.

  5. Effects of realistic land surface initializations on subseasonal to seasonal soil moisture and temperature predictability in North America and in changing climate simulated by CCSM4

    NASA Astrophysics Data System (ADS)

    Kumar, Sanjiv; Dirmeyer, Paul A.; Lawrence, David M.; DelSole, Timothy; Altshuler, Eric L.; Cash, Benjamin A.; Fennessy, Michael J.; Guo, Zhichang; Kinter, James L.; Straus, David M.

    2014-12-01

    Fully coupled global climate model experiments are performed using the Community Climate System Model version 4.0 (CCSM4) for preindustrial, present, and future climate to study the effects of realistic land surface initializations on subseasonal to seasonal climate forecasts. Model forecasts are verified against model control simulations (perfect model experiments), thus overcoming to some extent issues of uncertainties in the observations and/or model parameterizations. Findings suggest that realistic land surface initialization is important for climate predictability at subseasonal to seasonal time scales. We found the highest predictability for soil moisture, followed by evapotranspiration, temperature, and precipitation. The predictability is highest for the 16 to 30 days forecast period, and it progressively decreases for the second and third month forecasts. We found significant changes in the spatial distributions of temperature predictability in the present and future climate compared to the preindustrial climate, although the spatial average changes for North America were rather small (<10%). To attribute the potential cause of changes in land-driven temperature predictability, they are correlated with the changes in land related climate metrics. The changes in temperature predictability are positively (0.40), and negatively (-0.35) correlated with the changes in nonrainy days evaporative fraction, and changes in dryness index respectively. From this result, the hypothesis arises that wetter conditions favor higher land-driven temperature predictability in North America. We tested the hypothesis by rearranging the predictability experiment ensembles and found support for the hypothesis in the midlatitude regions and short-term forecasts (16 to 30 days).

  6. Atmospheric boundary layer characteristics and land-atmosphere energy transfer in the Third Pole area

    NASA Astrophysics Data System (ADS)

    Ma, Y.; Zhu, Z.; Amatya, P. M.; Chen, X.; Hu, Z.; Zhang, L.; Li, M.; Ma, W.

    2015-05-01

    The Tibetan Plateau and nearby surrounding area (the Third Pole area) dramatically impacts the world's environment and especially controls climatic and environmental changes in China, Asia and even in the Northern Hemisphere. Supported by the Chinese Academy of Sciences (CAS) and some international organizations, the Third Pole Environment (TPE) Programme is now under way. First, the background of the establishment of the TPE, the establishment and monitoring plans on long-term for the TPE and six comprehensive observation and study stations are introduced. Then the preliminary observational analysis results on atmosphere-land interaction are presented. The study on the regional distribution of land surface heat fluxes is of paramount importance over the heterogeneous landscape of the Third Pole area. A parameterization methodology based on satellite and in situ data is described and tested for deriving the regional surface heat fluxes (net radiation flux, soil heat flux, sensible heat flux and latent heat flux) over the heterogeneous landscape. As a case study, the methodology was applied to the whole Tibetan Plateau area. Eight images of MODIS data and four images of AVHRR data were used for the comparison among winter, spring, summer and autumn, and the annual variation analyses. The derived results were also validated by using the ``ground truth'' measured in the stations of the TPE. The results show that the derived surface heat fluxes in the four different seasons over the Tibetan Plateau area are in good agreement with the ground measurements. The results from AVHRR were also in agreement with MODIS. It is therefore concluded that the proposed methodology is successful for the retrieval of surface heat fluxes using the MODIS data, AVHRR data and in situ data over the Tibetan Plateau area.

  7. Flux tower in a mixed forest: spatial representativeness of seasonal footprints and the influence of land cover variability on the flux measurement

    NASA Astrophysics Data System (ADS)

    Kim, J.; Schaaf, C.; Hwang, T.

    2015-12-01

    Flux tower measurements using eddy-covariance techniques are used as the primary data for calibration and validation of remote sensing estimates and ecosystem models. Therefore, understanding the characteristics of the land surface contributing to the flux, the so-called footprint, is critical to upscale tower flux to the regional landscape. This is especially true for the towers locating in heterogeneous ecosystems such as mixed forests. Here we (1) estimated the seasonal footprints of a flux tower, the EMS-tower (US-Ha1) in the Long Term Ecological Research (LTER) Harvard Forest, from 1992 to 2008 with a footprint climatology. The Harvard Forest is a temperate mixed-species ecosystem that is composed of deciduous stands (red oak and red maple) and evergreen coniferous stands (eastern hemlock and white pine). The heterogeneity of the landscape is primarily driven by the phenology of the deciduous stands which are not uniformly distributed over the forest and around the tower. The overall prevailing footprints are known to lie toward the southwest and northwest, but there were profound interannual variability in the extents and the orientations of the seasonal footprints. Furthermore we (2) examined whether vegetation density variation within the tower footprint in each season could adequately represent the vegetation density characteristics of moderate spatial resolution remote sensing estimates and ecosystem models (i.e. 1.0 km and 1.5 km). The footprints were found to cover enough area to be representative of the 1.0 km scale but not 1.5 km scale. Finally we (3) investigated the influence of the interannual variations in the land cover variability in the footprints on the seasonal flux measurements from 1999 to 2008, and found almost half of the interannual anomalies in the summertime GPP flux can be explained by the coniferous stand fraction within the footprint.

  8. Vegetation monitoring and classification using NOAA/AVHRR satellite data

    NASA Technical Reports Server (NTRS)

    Greegor, D. H., Jr.; Norwine, J. R.

    1983-01-01

    A vegetation gradient model, based on a new surface hydrologic index and NOAA/AVHRR meteorological satellite data, has been analyzed along a 1300 km east-west transect across the state of Texas. The model was developed to test the potential usefulness of such low-resolution data for vegetation stratification and monitoring. Normalized Difference values (ratio of AVHRR bands 1 and 2, considered to be an index of greenness) were determined and evaluated against climatological and vegetation characteristics at 50 sample locations (regular intervals of 0.25 deg longitude) along the transect on five days in 1980. Statistical treatment of the data indicate that a multivariate model incorporating satellite-measured spectral greenness values and a surface hydrologic factor offer promise as a new technique for regional-scale vegetation stratification and monitoring.

  9. Radiation energy budget studies using collocated AVHRR and ERBE observations

    SciTech Connect

    Ackerman, S.A.; Inoue, Toshiro

    1994-03-01

    Changes in the energy balance at the top of the atmosphere are specified as a function of atmospheric and surface properties using observations from the Advanced Very High Resolution Radiometer (AVHRR) and the Earth Radiation Budget Experiment (ERBE) scanner. By collocating the observations from the two instruments, flown on NOAA-9, the authors take advantage of the remote-sensing capabilities of each instrument. The AVHRR spectral channels were selected based on regions that are strongly transparent to clear sky conditions and are therefore useful for characterizing both surface and cloud-top conditions. The ERBE instruments make broadband observations that are important for climate studies. The approach of collocating these observations in time and space is used to study the radiative energy budget of three geographic regions: oceanic, savanna, and desert. 25 refs., 8 figs.

  10. Developing NOAA's Climate Data Records From AVHRR and Other Data

    NASA Astrophysics Data System (ADS)

    Privette, J. L.; Bates, J. J.; Kearns, E. J.

    2010-12-01

    As part of the provisional NOAA Climate Service, NOAA is providing leadership in the development of authoritative, measurement-based information on climate change and variability. NOAA’s National Climatic Data Center (NCDC) recently initiated a satellite Climate Data Record Program (CDRP) to provide sustained and objective climate information derived from meteorological satellite data that NOAA has collected over the past 30+ years - particularly from its Polar Orbiting Environmental Satellites (POES) program. These are the longest sustained global measurement records in the world and represent billions of dollars of investment. NOAA is now applying advanced analysis methods -- which have improved remarkably over the last decade -- to the POES AVHRR and other instrument data. Data from other satellite programs, including NASA and international research programs and the Defense Meteorological Satellite Program (DMSP), are also being used. This process will unravel the underlying climate trend and variability information and return new value from the records. In parallel, NCDC will extend these records by applying the same methods to present-day and future satellite measurements, including the Joint Polar Satellite System (JPSS) and Jason-3. In this presentation, we will describe the AVHRR-related algorithm development activities that CDRP recently selected and funded through open competitions. We will particularly discuss some of the technical challenges related to adapting and using AVHRR algorithms with the VIIRS data that should become available with the launch of the NPOESS Preparatory Project (NPP) satellite in early 2012. We will also describe IT system development activities that will provide data processing and reprocessing, storage and management. We will also outline the maturing Program framework, including the strategies for coding and development standards, community reviews, independent program oversight, and research-to-operations algorithm

  11. Monitoring Seasonal Land Subsidence and Uplift in the Green Valley Area of the Tucson Active Management Area Groundwater Basin, Southern Arizona using Interferometric Synthetic Aperture Radar (InSAR) Data and Global Navigation Satellite System (GNSS) Data

    NASA Astrophysics Data System (ADS)

    Conway, B. D.

    2013-12-01

    The Green Valley land subsidence feature is located in southern Arizona, approximately 20 miles south of the Tucson metropolitan area within the town of Sahuarita. Groundwater levels fluctuate as much as 110 feet annually, caused by seasonal pumping demands of a nearby pecan orchard. Recent Arizona Department of Water Resources (ADWR) InSAR data and GNSS survey data reveal that seasonal land subsidence and subsequent uplift are occurring as a direct result of seasonal groundwater level fluctuations. Data from a nearby ADWR transducer shows that the groundwater level begins to decline around middle to late February, dropping as much as 110 feet by the end of June. Groundwater levels generally remain somewhat stable until the middle of October, when the groundwater level begins to rise. Groundwater levels will rise as much as 110 feet by the middle of February; a complete 12-month recovery. ADWR InSAR and GNSS survey data show that land subsidence occurs from February until May followed by a stable period, then uplift occurs from October to February. The Green Valley land subsidence feature is a dynamic hydrogeological system that requires continued deformation monitoring using both InSAR and GNSS data. Radarsat-2 Interferograms that illustrate both seasonal subsidence and uplift. Surveyed elevation and groundwater level change data that document how seasonal groundwater fluctuations result in seasonal land subsidence and uplift.

  12. Monitoring East African vegetation using AVHRR data

    NASA Technical Reports Server (NTRS)

    Justice, C. O.; Holben, B. N.; Gwynne, M. D.

    1986-01-01

    NOAA Advanced Very High Resolution Radiometer satellite data are applied to regional vegetation monitoring in East Africa. Normalized Difference Vegetation Index (NDVI) data for a one-year period from May 1983 are used to examine the phenology of a range of vegetation types. The integrated NDVI data for the same period are compared with an ecoclimatic zone map of the region and show marked similarities. Particular emphasis is placed on quantifying the phenology of the Acacia Commiphora bushlands. Considerable variation was found in the phenology of the bushlands as determined by the satellite NDVI, and is explained through the high spatial variability in the distribution of rainfall and the resulting green-up of the vegetation. The relationship between rainfall and NDVI is further examined for selected meteorological stations existing within the bushland. A preliminary estimate is made of the length of growing season using an NDVI thresholding technique.

  13. Monitoring interannual variation in global crop yield using long-term AVHRR and MODIS observations

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaoyang; Zhang, Qingyuan

    2016-04-01

    Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data have been extensively applied for crop yield prediction because of their daily temporal resolution and a global coverage. This study investigated global crop yield using daily two band Enhanced Vegetation Index (EVI2) derived from AVHRR (1981-1999) and MODIS (2000-2013) observations at a spatial resolution of 0.05° (∼5 km). Specifically, EVI2 temporal trajectory of crop growth was simulated using a hybrid piecewise logistic model (HPLM) for individual pixels, which was used to detect crop phenological metrics. The derived crop phenology was then applied to calculate crop greenness defined as EVI2 amplitude and EVI2 integration during annual crop growing seasons, which was further aggregated for croplands in each country, respectively. The interannual variations in EVI2 amplitude and EVI2 integration were combined to correlate to the variation in cereal yield from 1982-2012 for individual countries using a stepwise regression model, respectively. The results show that the confidence level of the established regression models was higher than 90% (P value < 0.1) in most countries in the northern hemisphere although it was relatively poor in the southern hemisphere (mainly in Africa). The error in the yield predication was relatively smaller in America, Europe and East Asia than that in Africa. In the 10 countries with largest cereal production across the world, the prediction error was less than 9% during past three decades. This suggests that crop phenology-controlled greenness from coarse resolution satellite data has the capability of predicting national crop yield across the world, which could provide timely and reliable crop information for global agricultural trade and policymakers.

  14. LAI, FAPAR and FCOVER products derived from AVHRR long time series: principles and evaluation

    NASA Astrophysics Data System (ADS)

    Verger, A.; Baret, F.; Weiss, M.; Lacaze, R.; Makhmara, H.; Pacholczyk, P.; Smets, B.; Kandasamy, S.; Vermote, E.

    2012-04-01

    Continuous and long term global monitoring of the terrestrial biosphere has draught an intense interest in the recent years in the context of climate and global change. Developing methodologies for generating historical data records from data collected with different satellite sensors over the past three decades by taking benefits from the improvements identified in the processing of the new generation sensors is a new central issue in remote sensing community. In this context, the Bio-geophysical Parameters (BioPar) service within Geoland2 project (http://www.geoland2.eu) aims at developing pre-operational infrastructures for providing global land products both in near real time and off-line mode with long time series. In this contribution, we describe the principles of the GEOLAND algorithm for generating long term datasets of three key biophysical variables, leaf area index (LAI), Fraction of Absorbed Photosynthetic Active Radiation (FAPAR) and cover fraction (FCOVER), that play a key role in several processes, including photosynthesis, respiration and transpiration. LAI, FAPAR and FCOVER are produced globally from AVHRR Long Term Data Record (LTDR) for the 1981-2000 period at 0.05° spatial resolution and 10 days temporal sampling frequency. The proposed algorithm aims to ensure robustness of the derived long time series and consistency with the ones developed in the recent years, and particularly with GEOLAND products derived from VEGETATION sensor. The approach is based on the capacity of neural networks to learn a particular biophysical product (GEOLAND) from reflectances from another sensor (AVHRR normalized reflectances in the red and near infrared bands). Outliers due to possible cloud contamination or residual atmospheric correction are iteratively eliminated. Prior information based on the climatology is used to get more robust estimates. A specific gap filing and smoothing procedure was applied to generate continuous and smooth time series of decadal

  15. A Non-Stationary 1981-2012 AVHRR NDVI(sub 3g) Time Series

    NASA Technical Reports Server (NTRS)

    Pinzon, Jorge E.; Tucker, Compton J.

    2014-01-01

    The NDVI(sub 3g) time series is an improved 8-km normalized difference vegetation index (NDVI) data set produced from Advanced Very High Resolution Radiometer (AVHRR) instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA) and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of plus or minus 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.

  16. A Non-Stationary 1981-2015 AVHRR NDVI3g Time Series

    NASA Astrophysics Data System (ADS)

    Pinzon, J. E.

    2015-12-01

    Long-term records of vegetation indices from Earth Observing instruments play a major role in monitoring terrestrial ecosystems and further our understanding on the varying effects of climate on vegetation. We describe 34+ years of an improved non-stationary 8-km normalized difference vegetation index (NDVI) produced from Advanced Very High Resolution Radiometer (AVHRR) instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA) and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of ± 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.

  17. Spatial and temporal vegetation change in Southern Brazilian Amazon using GIS and NOAA /AVHRR data

    NASA Astrophysics Data System (ADS)

    Kazadi, S.; Yoshikawa, S.

    2007-05-01

    Over the past two decades, environmental alteration in the Amazon Basin due to land development, population increase, and the consequent deforestation, has become a serious ecological problem in this region known to be, both climatologically and biogenetically, one of the most important regions in the world. In Mato Grosso, the Brazilian state with the highest deforestation rate, vegetation cover change has been reported to occur over large areas due to the introduction of large-scale mechanized agriculture, extensive cattle ranching and slash-and-burn cultivation. Spatial and temporal land cover (vegetation) change is noted to potentially set up temperature increase and rainfall decrease. We stress on the importance of vegetation change information as crucial inputs for eco-climatic analysis of these spatial patterns of change and their temporal trend at local scale, as well as for real-time monitoring or detection of the deforestation events for appropriate action by the Brazilian government. In this study, Principal Component Analysis (PCA) is performed onto NOAA AVHRR remote-sensed and multi- spectral data covering the 1981-2003 period, using GIS. Our investigation focuses on developing a vegetation quantification algorithm for change detection in the vegetation cover over every few years, using the PCA first component, which is shown to characterize the overall vegetation cover types. Land cover features and their spatio-temporal change over the Southern Brazilian Amazon are analyzed and discussed, and their relationships with global and regional eco-climatic phenomena is highlighted.

  18. Seasonal variations in dust concentration and dust emission observed over Horqin Sandy Land area in China from December 2010 to November 2011

    NASA Astrophysics Data System (ADS)

    Li, Xiaolan; Zhang, Hongsheng

    2012-12-01

    Hourly mean dust concentration observations and meteorological measurements obtained from a sandstorm monitoring station in Horqin Sandy Land area in China from December 2010 to November 2011 were used to investigate the seasonal variations in dust concentration and dust emission flux as well as their relationship with meteorological parameters and soil condition. Based on 14 local dust emission events in spring 2011, the friction velocity (u*) and free convective velocity (w*) were calculated, and their correlation with dust emission flux was used to evaluate the dynamic and thermal impact on dust emission by turbulence. Results indicated that dust events occur in every season with peak dust activity in spring. The maximum dust concentration is 1654.1 μg m-3 and dust emission flux is 98.4 μg m-2 s-1. Freezing of soil in winter effectively decreases soil erodibility and suppresses dust emission. However, soil moisture does not show a significant impact on dust emission in this semi-arid Horqin Sandy Land area. Both friction velocity and free convective velocity could reflect the trend in dust emission flux, but both with obvious underestimation. The thermal impact on dust emission by turbulence is found to be far less than its dynamic impact.

  19. Improving the seasonal-deciduous spring phenology submodel in the Community Land Model 4.5: Impacts on carbon and water cycling under future climate scenarios

    NASA Astrophysics Data System (ADS)

    Chen, M.; Melaas, E. K.; Gray, J. M.; Friedl, M. A.; Richardson, A. D.

    2015-12-01

    A seasonal-deciduous phenology model that combines photoperiod with accumulated heating and chilling to predict spring leaf out dates is optimized using PhenoCam observations and coupled into the Community Land Model 4.5. In head-to-head comparison (using start of spring dates derived from MODIS remote sensing for validation) across Northern Hemisphere boreal and temperate deciduous forests (5.5 million km2), the revised model substantially out-performed the standard model. Forward model runs suggested a stronger advancement (up to 7 days) of spring leaf out by the end of the 21st century for the revised model. The earlier spring leaf out predicted by the revised model increased both gross primary production (up to 0.5 Pg C yr-1) and evapotranspiration (up to 25 mm yr-1) when results were integrated across the study region. To reduce errors in model predictions of key land-atmosphere interactions and feedbacks, the standard seasonal-deciduous phenology submodel in CLM should be reconsidered.

  20. Synergism between NOAA-AVHRR and Meteosat data for studying vegetation development in semi-arid West Africa

    NASA Technical Reports Server (NTRS)

    Justice, C. O.; Dugdale, G.; Narracott, A. S.; Townshend, J. R. G.; Kumar, M.

    1991-01-01

    Rainfall estimates, based on cold cloud duration estimated from Meteosat data, are compared with vegetation development depicted by data of the normalized difference vegetation index (NDVI) from the NOAA AVHRR for part of the Sahel. Decadal data from the 1985 and 1986 growing seasons are examined to determine the synergism of the datasets for rangeland monitoring. There is a general correspondence between the two datasets with a marked lag between rainfall and NDVI of between 10 and 20 days. This time lag is particularly noticeable at the beginning of the rainy season and in the more northern areas where rainfall is the limiting factor for growth. Principal component analysis was used to examine deviations from the general relationship between rainfall and the NDVI. Areas of low NDVI values for a given input of rainfall were identified: at a regional scale, they give an indication o areas of low production potential and possible degradation of ecosystems.

  1. APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

    NASA Astrophysics Data System (ADS)

    Klüser, L.; Killius, N.; Gesell, G.

    2015-04-01

    The cloud processing scheme APOLLO (Avhrr Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. While building upon the physical principles having served well in the original APOLLO a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is not performed as a binary yes/no decision based on these physical principals but is expressed as cloud probability for each satellite pixel. Consequently the outcome of the algorithm can be tuned from clear confident to cloud confident depending on the purpose. The probabilistic approach allows to retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for the application with large amounts of historical satellite data. Thus the radiative transfer solution is approximated by the same two stream approach which also had been used for the original APOLLO. This allows the algorithm to be robust enough for being applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e. within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from on NOAA-18 are presented.

  2. APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

    NASA Astrophysics Data System (ADS)

    Klüser, L.; Killius, N.; Gesell, G.

    2015-10-01

    The cloud processing scheme APOLLO (AVHRR Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. It builds upon the physical principles that have served well in the original APOLLO scheme. Nevertheless, a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is no longer performed as a binary yes/no decision based on these physical principles. It is rather expressed as cloud probability for each satellite pixel. Consequently, the outcome of the algorithm can be tuned from being sure to reliably identify clear pixels to conditions of reliably identifying definitely cloudy pixels, depending on the purpose. The probabilistic approach allows retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for application to large amounts of historical satellite data. The radiative transfer solution is approximated by the same two-stream approach which also had been used for the original APOLLO. This allows the algorithm to be applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e., within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example

  3. Land cover characterization and mapping of continental southeast Asia using multi-resolution satellite sensor data

    USGS Publications Warehouse

    Giri, Chandra; Defourny, P.; Shrestha, Surendra

    2003-01-01

    Land use/land cover change, particularly that of tropical deforestation and forest degradation, has been occurring at an unprecedented rate and scale in Southeast Asia. The rapid rate of economic development, demographics and poverty are believed to be the underlying forces responsible for the change. Accurate and up-to-date information to support the above statement is, however, not available. The available data, if any, are outdated and are not comparable for various technical reasons. Time series analysis of land cover change and the identification of the driving forces responsible for these changes are needed for the sustainable management of natural resources and also for projecting future land cover trajectories. We analysed the multi-temporal and multi-seasonal NOAA Advanced Very High Resolution Radiometer (AVHRR) satellite data of 1985/86 and 1992 to (1) prepare historical land cover maps and (2) to identify areas undergoing major land cover transformations (called ‘hot spots’). The identified ‘hot spot’ areas were investigated in detail using high-resolution satellite sensor data such as Landsat and SPOT supplemented by intensive field surveys. Shifting cultivation, intensification of agricultural activities and change of cropping patterns, and conversion of forest to agricultural land were found to be the principal reasons for land use/land cover change in the Oudomxay province of Lao PDR, the Mekong Delta of Vietnam and the Loei province of Thailand, respectively. Moreover, typical land use/land cover change patterns of the ‘hot spot’ areas were also examined. In addition, we developed an operational methodology for land use/land cover change analysis at the national level with the help of national remote sensing institutions.

  4. Atmospheric correction of AVHRR data for biophysical remote sensing of the Sahel

    SciTech Connect

    Hanan, N.P.; Prince, S.D.; Holben, B.N.

    1995-02-01

    The importance of atmospheric correction of reflectances measured with the Advanced Very High Resolution Radiometer(AVHRR) for biophysical studies using the normalized difference vegetation index (NDVI) is examined for a study area in the Sahel for which measurements of aerosol and water vapor were available. During the rainy season atmospheric aerosols were relatively more variable than water vapor. Atmospheric corrections were applied to Channel 1 (red) and Channel 2 (near-infrared) for the effects of molecular absorption and Rayleigh scatter, aerosol scatter and absorption, and water vapor absorption. The results were expressed as the difference between corrected and uncorrected reflectances ({Delta}{rho}). In Channel 1 the magnitude and variability of {Delta}{rho} was mostly caused by aerosols. In Channel 2 the magnitude of {Delta}{rho} was caused by water vapor, but most of the variability was caused by aerosols. Most of the degradation in the NDVI signal ({delta}{nu}{iota}) was caused by water vapor but the variability in {Delta}{nu}{iota} was caused by both water vapor and aerosol. Atmospheric corrections using seasonal averages of atmospheric water vapor and aerosol optical depths resulted in corrections that were similar to the full corrections using daily values. In the Sahel it may therefore be acceptable to use average values for the atmospheric variables to correct satellite data when sunphotometer data are not available, although the effects of interannual variability in mean atmospheric conditions are not known.

  5. Representation of vegetation by continental data sets derived from NOAA-AVHRR data

    NASA Technical Reports Server (NTRS)

    Justice, C. O.; Townshend, J. R. G.; Kalb, V. L.

    1991-01-01

    Images of the normalized difference vegetation index (NDVI) are examined with specific attention given to the effect of spatial scales on the understanding of surface phenomena. A scale variance analysis is conducted on NDVI annual and seasonal images of Africa taken from 1987 NOAA-AVHRR data at spatial scales ranging from 8-512 km. The scales at which spatial variation takes place are determined and the relative magnitude of the variations are considered. Substantial differences are demonstrated, notably an increase in spatial variation with coarsening spatial resolution. Different responses in scale variance as a function of spatial resolution are noted in an analysis of maximum value composites for February and September; the difference is most marked in areas with very seasonal vegetation. The spatial variation at different scales is attributed to different factors, and methods involving the averaging of areas of transition and surface heterogeneity can oversimplify surface conditions. The spatial characteristics and the temporal variability of areas should be considered to accurately apply satellite data to global models.

  6. Early warning of malaria at Bikaner, Rajasthan in India using AVHRR-based satellite data

    NASA Astrophysics Data System (ADS)

    Roytman, Leonid; Nizamuddin, Mohammad; Akhand, Kawsar; Kogan, Felix; Goldberg, Mitchell

    2013-09-01

    A better understanding of the relationship between satellites observed vegetation health, and malaria epidemics could help mitigate the worldwide increase in incidence of mosquito-transmitted diseases. This research investigates last 17- years association between vegetation health (condition) index and malaria transmission in Bikaner, Rajasthan in India an arid and hot summer area. The vegetation health (condition) index, derived from a combination of Advanced Very High Resolution Radiometer (AVHRR) based Normalized Difference Vegetation Index (NDVI) and 10-μm to 11-μm thermal radiances, was designed for monitoring moisture and thermal impacts on vegetation health. We demonstrate that thermal condition is more sensitive to malaria transmission with different seasonal malaria activities. The weekly VH indices were correlated with the epidemiological data. A good correlation was found between malaria cases and Temperature Condition Index (TCI) one at least two months earlier than the malaria transmission season. Following the results of correlation analysis, Principal Component Regression (PCR) method was used to construct a model of less than 10% error to predict malaria as a function of the TCI.

  7. Wavelet analysis of NOAA AVHRR multichannel surface temperature of the Japan Sea

    SciTech Connect

    Ostrovskii, A.

    1995-12-31

    The NOAA Advanced Very High Resolution Radiometer (AVHRR) multichannel sea surface temperature (SST) images of the Japan Sea are analyzed with the orthonormal wavelet transform (WT) technique. The decoding-encoding WT allows better representation of the subpolar front, mesoscale eddies, and streamers that appear in the SST patterns. The analysis shows remarkable difference in the typical SST patterns in October 1993 and April--May 1994. While SST patterns were fuzzy in autumn, they appeared sharp in spring. The plumes of irregular shapes with characteristic horizontal scale of less than 30 km developed over the SST field at the beginning of the cooling season when the horizontal temperature gradients were essentially eroded. In contrast, very narrow and elongated up to 100 km streaks appeared at the beginning of the heating season when the temperature gradients were sharp. The spectral analysis of SST results in the power law behavior of k{sup {minus}2.0} in October and k{sup {minus}2.8} in May, for the scales ranging from 10 km to 100 km. These observations suggest that the surface cooling in the autumn favors the enhancement of three dimensional mixing, while during the onset of heating the horizontal stirring becomes more pronounced at geostrophic turbulence scales.

  8. Analyzing the Effect of Intraseasonal Meteorological Variability and Land Cover on Aerosol-Cloud Interactions During the Amazonian Biomass Burning Season

    NASA Technical Reports Server (NTRS)

    TenHoeve, J. E.; Remer, L. A.; Jacobson, M. Z.

    2010-01-01

    High resolution aerosol, cloud, water vapor, and atmospheric profile data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are utilized to examine the impact of aerosols on clouds during the Amazonian biomass burning season in Rondnia, Brazil. It is found that increasing background column water vapor (CWV) throughout this transition season between the Amazon dry and wet seasons exerts a strong effect on cloud properties. As a result, aerosol-cloud correlations should be stratified by column water vapor to achieve a more accurate assessment of the effect of aerosols on clouds. Previous studies ignored the systematic changes to meteorological factors during the transition season, leading to possible misinterpretation of their results. Cloud fraction is shown generally to increase with aerosol optical depth (AOD) for both low and high values of column water vapor, whereas the relationship between cloud optical depth (COD) and AOD exhibits a different relationship. COD increases with AOD until AOD approx. 0.25 due to the first indirect (microphysical) effect. At higher values of AOD, COD is found to decrease with increasing AOD, which may be due to: (1) the inhibition of cloud development by absorbing aerosols (radiative effect) and/or (2) a retrieval artifact in which the measured reflectance in the visible is less than expected from a cloud top either from the darkening of clouds through the addition of carbonaceous biomass burning aerosols or subpixel dark surface contamination in the measured cloud reflectance. If (1) is a contributing mechanism, as we suspect, then a linear relationship between the indirect effect and increasing AOD, assumed in a majority of GCMs, is inaccurate since these models do not include treatment of aerosol absorption in and around clouds. The effect of aerosols on both column water vapor and clouds over varying land surface types is also analyzed. The study finds that the difference in column water vapor between forest and

  9. Spectral Compatibility Analysis of the Enhanced Vegetation Indices (EVI) across VIIRS, MODIS, and AVHRR Using EO-1 Hyperion

    NASA Astrophysics Data System (ADS)

    Miura, T.; Turner, J. P.; Huete, A. R.

    2012-12-01

    Spectral vegetation indices (VIs) are one of the more important satellite products for monitoring terrestrial vegetation and characterizing their seasonal dynamics and interannual variability in regional to global scales. The enhanced vegetation index (EVI), designed for the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) sensors, has been shown to effectively characterize global vegetation states and ecosystem processes, and encompass the range of biophysical/biochemical information in manners to complement the conventional, normalized difference vegetation index (NDVI). Because the EVI is limited to sensor systems designed with a blue band, a 2-band EVI, without a blue band, was recently developed (referred to as the EVI2), which has the best similarity with the 3-band EVI, particularly when residual atmospheric effects are insignificant and data quality is good. In this study, we evaluated cross-sensor spectral compatibilities of the EVI and EVI2 across Visible/Infrared Imager/Radiometer Suite (VIIRS), MODIS, and NOAA-14 and -19 Advanced Very High Resolution Radiometer (AVHRR/2 and AVHRR/3, respectively) bandpasses using a global set of Earth Observing One (EO-1) Hyperion hyperspectral data. Hyperion scenes were spectrally aggregated into red and near-infrared (NIR) bandpasses of the four sensors and blue bandpasses of the MODIS and VIIRS sensors, and spatially aggregated into 1 km resolution pixels. Two atmospheric correction scenarios were also applied to examine the impact of the atmosphere on inter-sensor EVI/EVI2 compatibility: (1) Rayleigh/ozone/water vapor (ROW)-corrected and (2) total-atmosphere-corrected "top-of-canopy (TOC)" reflectances. The EVI and EVI2 were computed from these reflectance data. The highest compatibility was obtained for VIIRS EVI2 vs. MODIS EVI2 and for AVHRR/3 EVI2 vs. AVHRR/2 EVI2. VIIRS EVI vs. MODIS EVI was subject to large systematic

  10. Monitoring of wildfires in boreal forests using large area AVHRR NDVI composite image data

    SciTech Connect

    Kasischke, E.S.; French, N.H.F. ); Harrell, P.; Christensen, N.L. Jr. ); Ustin, S.L. ); Barry, D. )

    1993-06-01

    Normalized difference vegetation index (NDVI) composite image data, produced from AVHRR data collected in 1990, were evaluated for locating and mapping the areal extent of wildfires in the boreal forests of Alaska during that year. A technique was developed to map forest fire boundaries by subtracting a late-summer AVHRR NDVI image from an early summer scene. The locations and boundaries of wildfires within the interior region of Alaska were obtained from the Alaska Fire Service, and compared to the AVHRR-derived fire-boundary map. It was found that AVHRR detected 89.5% of all fires with sizes greater than 2,000ha with no false alarms and that, for most cases, the general shape of the fire boundary detected by AVHRR matched those mapped by field observers. However, the total area contained within the fire boundaries mapped by AVHRR were only 61% of those mapped by the field observers. However, the AVHRR data used in this study did not span the entire time period during which fires occurred, and it is believed the areal estimates could be improved significantly if an expanded AVHRR data set were used.

  11. Monitoring of wildfires in boreal forests using large area AVHRR NDVI composite image data

    NASA Technical Reports Server (NTRS)

    Kasischke, Eric S.; French, Nancy H. F.; Harrell, Peter; Christensen, Norman L., Jr.; Ustin, Susan L.; Barry, Donald

    1993-01-01

    Normalized difference vegetation index (NDVI) composite image data, produced from AVHRR data collected in 1990, were evaluated for locating and mapping the areal extent of wildfires in the boreal forests of Alaska during that year. A technique was developed to map forest fire boundaries by subtracting a late-summer AVHRR NDVI image from an early summer scene. The locations and boundaries of wildfires within the interior region of Alaska were obtained from the Alaska Fire Service, and compared to the AVHRR-derived fire-boundary map. It was found that AVHRR detected 89.5 percent of all fires with sizes greater than 2000 ha with no false alarms and that, for most cases, the general shape of the fire boundary detected by AVHRR matched those mapped by field observers. However, the total area contained within the fire boundaries mapped by AVHRR were only 61 percent of those mapped by the field observers. However, the AVHRR data used in this study did not span the entire time period during which fires occurred, and it is believed the areal estimates could be improved significantly if an expanded AVHRR data set were used.

  12. Aerosol Retrievals over the Ocean using Channel 1 and 2 AVHRR Data: A Sensitivity Analysis and Preliminary Results

    NASA Technical Reports Server (NTRS)

    Mishchenko, Michael I.; Geogdzhayev, Igor V.; Cairns, Brian; Rossow, William B.; Lacis, Andrew A.

    1999-01-01

    This paper outlines the methodology of interpreting channel 1 and 2 AVHRR radiance data over the oceans and describes a detailed analysis of the sensitivity of monthly averages of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. The analysis is based on using real AVHRR data and exploiting accurate numerical techniques for computing single and multiple scattering and spectral absorption of light in the vertically inhomogeneous atmosphere-ocean system. We show that two-channel algorithms can be expected to provide significantly more accurate and less biased retrievals of the aerosol optical thickness than one-channel algorithms and that imperfect cloud screening and calibration uncertainties are by far the largest sources of errors in the retrieved aerosol parameters. Both underestimating and overestimating aerosol absorption as well as the potentially strong variability of the real part of the aerosol refractive index may lead to regional and/or seasonal biases in optical thickness retrievals. The Angstrom exponent appears to be the most invariant aerosol size characteristic and should be retrieved along with optical thickness as the second aerosol parameter.

  13. Winter wheat production forecast in United States of America using AVHRR historical data and NCAR Growing Degree Day

    NASA Astrophysics Data System (ADS)

    Claverie, M.; Franch, B.; Vermote, E.; Becker-Reshef, I.; Justice, C. O.

    2015-12-01

    Wheat is one of the key cereals crop grown worldwide. Thus, accurate and timely forecasts of its production are critical for informing agricultural policies and investments, as well as increasing market efficiency and stability. Becker-Reshef et al. (2010) used an empirical generalized model for forecasting winter wheat production using combined BRDF-corrected daily surface reflectance from the Moderate resolution Imaging Spectroradiometer (MODIS) Climate Modeling Grid (CMG) with detailed official crop statistics and crop type masks. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season, percent wheat within the CMG pixel, and the final yields. This method predicts the yield approximately one month to six weeks prior to harvest. Recently, Franch et al. (2015) included Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data in order to improve the winter wheat production forecast by increasing the timeliness of the forecasts between a month to a month and a half prior to the peak NDVI (i.e. 1-2.5 months prior to harvest), while conserving the accuracy of the original model. In this study, we apply these methods to historical data from the Advanced Very High Resolution Radiometer (AVHRR). We apply both the original and the modified model to United States of America from 1990 to 2014 and inter-compare the AVHRR results to MODIS from 2000 to 2014.

  14. Monitoring phenological changes in lake ice as a robust indicator of regional climate change using the AVHRR

    SciTech Connect

    Wynne Randolph, H.; Lillesand, T.M. )

    1993-06-01

    The length of the growing season, effectively defined by the onset or breakup of ice, may be one of the more important ways in which climate change is likely to influence lake environments. In addition, interannual variation in the dates of lake ice formation and breakup has been shown to be an effective climate change indicator. We explored the use of data from the Advanced Very High Resolution Radiometer (AVHRR) to discriminate the presence of lake ice during the winter of 1990-1991 on the 45 lakes and reservoirs in Wisconsin with a surface area of greater than 1,000 hectares. Our results suggest both the feasibility of using the AVHRR to determine the date of lake ice breakup as well as the strong correlation (R=[minus]0.87) of the dates so derived with January-March mean local temperatures. These results indicate the inherent promise of utilizing archive satellite to detect the climate expected as a result of greenhouse warming.

  15. Agriculture mask for crop growth monitoring in Poland using NOAA-AVHRR time series. (Polish Title: Maska obszarów rolniczych dostosowana do monitoringu wzrostu roślin uprawnych w Polsce przy użyciu szeregów czasowych NOAA-AVHRR)

    NASA Astrophysics Data System (ADS)

    Turlej, K.; Bojanowski, J.; Bartold, M.

    2013-12-01

    Low spatial resolution of the NOAA-AVHRR images causes that observation footprints of the pixels can overlay the surface of more than one land cover type. The pure signal can be obtained for pixels covering only one land cover class. The extraction of the vegetation index (e.g. NDVI) for one land cover class can be interfered by the presence of other classes within the surface covered by a pixel. Additionally, the inaccuracy of the geometric correction of satellite images can increase the possibility that analysed pixel covers different land cover type than could be expected based on the analysis of the land cover map overlaid on the satellite image. In this study, we presented a new agriculture mask for Poland developed from the CORINE Land Cover 2006 database. The mask of one-kilometre spatial resolution indicates the pixels of the NOAA-AVHRR, which should be used for calculation of mean vegetation indices for regions (i.e. voivodeships or provinces). The proposed mask preserves the uniform spatial distribution of pixels within each Polish region. To validate the new mask, we calculated twelve-year-long time series (1997-2008) of Vegetation Condition Index and Temperature Condition Index of agriculture areas for each voivodeship in Poland. The newly received time series of voivodeships showed higher correlation with crop yield than when using the classical agriculture mask, which classifies a pixel as agricultural if at least 50% of its area is covered by the agriculture land.

  16. Coupling fast all-season soil strength land surface model with weather research and forecasting model to assess low-level icing in complex terrain

    NASA Astrophysics Data System (ADS)

    Sines, Taleena R.

    Icing poses as a severe hazard to aircraft safety with financial resources and even human lives hanging in the balance when the decision to ground a flight must be made. When analyzing the effects of ice on aviation, a chief cause for danger is the disruption of smooth airflow, which increases the drag force on the aircraft therefore decreasing its ability to create lift. The Weather Research and Forecast (WRF) model Advanced Research WRF (WRF-ARW) is a collaboratively created, flexible model designed to run on distributed computing systems for a variety of applications including forecasting research, parameterization research, and real-time numerical weather prediction. Land-surface models, one of the physics options available in the WRF-ARW, output surface heat and moisture flux given radiation, precipitation, and surface properties such as soil type. The Fast All-Season Soil STrength (FASST) land-surface model was developed by the U.S. Army ERDC-CRREL in Hanover, New Hampshire. Designed to use both meteorological and terrain data, the model calculates heat and moisture within the surface layer as well as the exchange of these parameters between the soil, surface elements (such as snow and vegetation), and atmosphere. Focusing on the Presidential Mountain Range of New Hampshire under the NASA Experimental Program to Stimulate Competitive Research (EPSCoR) Icing Assessments in Cold and Alpine Environments project, one of the main goals is to create a customized, high resolution model to predict and assess ice accretion in complex terrain. The purpose of this research is to couple the FASST land-surface model with the WRF to improve icing forecasts in complex terrain. Coupling FASST with the WRF-ARW may improve icing forecasts because of its sophisticated approach to handling processes such as meltwater, freezing, thawing, and others that would affect the water and energy budget and in turn affect icing forecasts. Several transformations had to take place in order

  17. Comparison of AVHRR and ECMWF ERA-Interim data with buoy observational data for sea surface temperature over the Southern Coast of the Caspian Sea

    NASA Astrophysics Data System (ADS)

    Ghafarian, Parvin; Pegahfar, Nafiseh

    2016-07-01

    Sea surface temperature plays an important role in formation or intensification of many atmospheric phenomena such as tropical storms, lake-effect snow and sea breeze. Also, this variable is one of the input data in atmospheric, climate and oceanic models and also used climate change interpretation. According to the sparse location of observational stations over the ocean basins and seas, so satellite products can play an important role over such areas. The southern coast of the Caspian Sea (CS) is a prone area to experience some extreme challenging events forming due to sea surface temperature (SST) variation. In this research, SST data obtained by the AVHRR (Advanced Very High Resolution Radiometer) and those modeled by ECMWF data have been compared with observational data from buoy instrument. The horizontal resolution of AVHRR data is 0.125 degree, while that is 0.75 degree for ECMWF. The comparison process has been done in various seasons especially for some stormy days in winter and spring led to the lake-effect snow and waterspout. Analysis has been done applying nearest-neighbor interpolation and statistical methods. Our findings indicated that SST measured by AVHRR, comparing with ECMWF data, is more close to the observational data.

  18. Analyzing Land Cover Change in Kazakhstan: Land Surface Phenology, Climatic Variation, and Sensor Artifacts

    NASA Astrophysics Data System (ADS)

    de Beurs, K. M.; Henebry, G. M.

    2003-12-01

    The collapse of the economic and political institutions of the Soviet Union in the early 1990s led to widespread agricultural de-intensification, land abandonment, loss of livestock, and decreased grazing pressure. In semi-arid to arid regions dominated by dryland agriculture and grazing, the quantification of land cover change must distinguish anthropogenic forcings from interannual climatic variation and the peculiarities associated with specific sensor systems. Were the land cover changes that occurred in Kazakhstan following independence in 1991 of sufficient magnitude to alter the land surface phenology at resolutions relevant to climate models? To explore this question it is necessary first to partition the sources of variation in the image archive. We used the standard Pathfinder AVHRR Land (PAL) dataset, which consists of global 10 d maximum NDVI composites from 7/1981 to 9/2001 at 8 km resolution. To what extent are the PAL data affected by sensor artifacts that may mask other kinds of change? We evaluated 19 subsets of 1600 sq km, one for each ecoregion of Kazakhstan as delineated by the World Wildlife Fund. To minimize residual cloud contamination in the PAL data, a modified version of the best index slope extraction algorithm was applied. The method filters distortions without altering the seasonal NDVI pattern. We pursued two complementary aspects of change analysis: (1) detection of trends within each sensor's tenure and (2) detection of trends and discontinuities across the entire observational period. Seasonal polynomial models of NDVI phenology were developed to relate accumulated growing degree-day with NDVI. To test for trends within periods, both the residuals and the filtered data were submitted to seasonal Mann-Kendall tests that were modified to correct for serial correlation. To identify discontinuities, the entire series was tested using the standard normal homogeneity test (SNHT) without trend. The Kruskal-Wallis test with Bonferroni

  19. Dry seasons identified in oak tree-ring chronology in the Czech Lands over the last millennium

    NASA Astrophysics Data System (ADS)

    Dobrovolny, Petr; Brazdil, Rudolf; Büntgen, Ulf; Rybnicek, Michal; Kolar, Tomas; Reznickova, Ladislava; Valasek, Hubert; Kotyza, Oldrich

    2015-04-01

    from SW and low precipitation totals with higher probability of drought occurrence. Our results provide consistent physical explanation of extremely dry seasons occurring in Central Europe. However, direct comparisons of individual RW extreme seasons with existing documentary evidence show the complexity the problem as some extremes identified in oak RW chronology were not confirmed in documentary archives and vice versa. We discuss possible causes of such differences related to the fact that various proxies may have problems to record real intensity or duration of extreme events e.g. due to non-linear response of proxy data to climate drivers or due to shift in seasonality.

  20. Revisiting AVHRR tropospheric aerosol trends using principal component analysis

    NASA Astrophysics Data System (ADS)

    Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

    2014-03-01

    The advanced very high resolution radiometer (AVHRR) satellite instruments provide a nearly 25 year continuous record of global aerosol properties over the ocean. It offers valuable insights into the long-term change in global aerosol loading. However, the AVHRR data record is heavily influenced by two volcanic eruptions, El Chichon on March 1982 and Mount Pinatubo on June 1991. The gradual decay of volcanic aerosols may last years after the eruption, which potentially masks the estimation of aerosol trends in the lower troposphere, especially those of anthropogenic origin. In this study, we show that a principal component analysis approach effectively captures the bulk of the spatial and temporal variability of volcanic aerosols into a single mode. The spatial pattern and time series of this mode provide a good match to the global distribution and decay of volcanic aerosols. We further reconstruct the data set by removing the volcanic aerosol component and reestimate the global and regional aerosol trends. Globally, the reconstructed data set reveals an increase of aerosol optical depth from 1985 to 1990 and decreasing trend from 1994 to 2006. Regionally, in the 1980s, positive trends are observed over the North Atlantic and North Arabian Sea, while negative tendencies are present off the West African coast and North Pacific. During the 1994 to 2006 period, the Gulf of Mexico, North Atlantic close to Europe, and North Africa exhibit negative trends, while the coastal regions of East and South Asia, the Sahel region, and South America show positive trends.

  1. A CERES-like Cloud Property Climatology Using AVHRR Data

    NASA Astrophysics Data System (ADS)

    Minnis, P.; Bedka, K. M.; Yost, C. R.; Trepte, Q.; Bedka, S. T.; Sun-Mack, S.; Doelling, D.

    2015-12-01

    Clouds affect the climate system by modulating the radiation budget and distributing precipitation. Variations in cloud patterns and properties are expected to accompany changes in climate. The NASA Clouds and the Earth's Radiant Energy System (CERES) Project developed an end-to-end analysis system to measure broadband radiances from a radiometer and retrieve cloud properties from collocated high-resolution MODerate-resolution Imaging Spectroradiometer (MODIS) data to generate a long-term climate data record of clouds and clear-sky properties and top-of-atmosphere radiation budget. The first MODIS was not launched until 2000, so the current CERES record is only 15 years long at this point. The core of the algorithms used to retrieve the cloud properties from MODIS is based on the spectral complement of the Advanced Very High Resolution Radiometer (AVHRR), which has been aboard a string of satellites since 1978. The CERES cloud algorithms were adapted for application to AVHRR data and have been used to produce an ongoing CERES-like cloud property and surface temperature product that includes an initial narrowband-based radiation budget. This presentation will summarize this new product, which covers nearly 37 years, and its comparability with cloud parameters from CERES, CALIPSO, and other satellites. Examples of some applications of this dataset are given and the potential for generating a long-term radiation budget CDR is also discussed.

  2. Pre-launch calibration of AVHRR reflected-solar channels

    NASA Astrophysics Data System (ADS)

    Abel, Peter

    1991-07-01

    Demand for quantitative (rather than qualitative) measurements of reflected-solar radiance has grown during the period of availability of AVHRR data, but even today the most important applications involve image products. The principal purpose of pre-launch radiance calibration of Channels 1 and 2 (centered at approximately 630 and 850 nm) has therefore been to ensure that the channel gains are correctly set to make best use of the dynamic range of the instrument rather than to calibrate the radiance response characteristics of the instrument with high accuracy. This emphasis was encouraged by the technical difficulty of accurate calibration in this part of the spectrum, as well as by the absence of in-orbit calibration for Channels 1 and 2. This paper briefly reviews pre-launch calibration methodology for the AVHRR at the manufacturer's facility, and the absolute accuracy of the process, which is adequate only for the purpose of setting the gain of the instrument. A 1989 proposal by the National Institute for Standards and Technology (NIST), formerly known as the National Bureau of Standards (NBS), to improve the accuracy has not yet been funded. The importance of improving the accuracy is expected to increase in the future as new applications for quantitative measurements emerge in support of research into the mechanisms of global change.

  3. Revisiting AVHRR Tropospheric Aerosol Trends Using Principal Component Analysis

    NASA Technical Reports Server (NTRS)

    Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

    2014-01-01

    The advanced very high resolution radiometer (AVHRR) satellite instruments provide a nearly 25 year continuous record of global aerosol properties over the ocean. It offers valuable insights into the long-term change in global aerosol loading. However, the AVHRR data record is heavily influenced by two volcanic eruptions, El Chichon on March 1982 and Mount Pinatubo on June 1991. The gradual decay of volcanic aerosols may last years after the eruption, which potentially masks the estimation of aerosol trends in the lower troposphere, especially those of anthropogenic origin. In this study, we show that a principal component analysis approach effectively captures the bulk of the spatial and temporal variability of volcanic aerosols into a single mode. The spatial pattern and time series of this mode provide a good match to the global distribution and decay of volcanic aerosols. We further reconstruct the data set by removing the volcanic aerosol component and reestimate the global and regional aerosol trends. Globally, the reconstructed data set reveals an increase of aerosol optical depth from 1985 to 1990 and decreasing trend from 1994 to 2006. Regionally, in the 1980s, positive trends are observed over the North Atlantic and North Arabian Sea, while negative tendencies are present off the West African coast and North Pacific. During the 1994 to 2006 period, the Gulf of Mexico, North Atlantic close to Europe, and North Africa exhibit negative trends, while the coastal regions of East and South Asia, the Sahel region, and South America show positive trends.

  4. Influence of Terrain and Land Cover on the Isotopic Composition of Seasonal Snowpack in Rocky Mountain Headwater Catchments Affected by Bark Beetle Induced Tree Mortality

    NASA Astrophysics Data System (ADS)

    Kipnis, E. L.; Murphy, M.; Klatt, A. L.; Miller, S. N.; Williams, D. G.

    2015-12-01

    Session H103: The Hydrology-Vegetation-Climate Nexus: Identifying Process Interactions and Environmental Shifts in Mountain Catchments Influence of Terrain and Land Cover on the Isotopic Composition of Seasonal Snowpack in Rocky Mountain Headwater Catchments Affected by Bark Beetle Induced Tree Mortality Evan L Kipnis, Melanie A Murphey, Alan Klatt, Scott N Miller, David G Williams Snowpack accumulation and ablation remain difficult to estimate in forested headwater catchments. How physical terrain and forest cover separately and interactively influence spatial patterns of snow accumulation and ablation largely shapes the hydrologic response to land cover disturbances. Analysis of water isotopes in snowpack provides a powerful tool for examining integrated effects of water vapor exchange, selective redistribution, and melt. Snow water equivalence (SWE), δ2H, δ18O and deuterium excess (D-excess) of snowpack were examined throughout winter 2013-2014 across two headwater catchments impacted by bark beetle induced tree mortality. A USGS 10m DEM and a derived land cover product from 1m NAIP imagery were used to examine the effects of terrain features (e.g., elevation, slope, aspect) and canopy disturbance (e.g., live, bark-beetle killed) as predictors of D-excess, an expression of kinetic isotope effects, in snowpack. A weighting of Akaike's Information Criterion (AIC) values from multiple spatially lagged regression models describing D-excess variation for peak snowpack revealed strong effects of elevation and canopy mortality, and weaker, but significant effects of aspect and slope. Snowpack D-excess was lower in beetle-killed canopy patches compared to live green canopy patches, and at lower compared to high elevation locations, suggesting that integrated isotopic effects of vapor exchange, vertical advection of melted snow, and selective accumulation and redistribution varied systematically across the two catchments. The observed patterns illustrate the potential

  5. Multi-Season Regional Analysis of Multi-Species Occupancy: Implications for Bird Conservation in Agricultural Lands in East-Central Argentina

    PubMed Central

    Goijman, Andrea Paula; Conroy, Michael. J.; Bernardos, Jaime Nicolás; Zaccagnini, María Elena

    2015-01-01

    Rapid expansion and intensification of agriculture create challenges for the conservation of biodiversity and associated ecosystem services. In Argentina, the total row crop planted area has increased in recent decades with the expansion of soybean cultivation, homogenizing the landscape. In 2003 we started the first long-term, large-scale bird monitoring program in agroecosystems of central Argentina, in portions of the Pampas and Espinal ecoregions. Using data from this program, we evaluated the effect of land use and cover extent on birds between 2003-2012, accounting for imperfect detection probabilities using a Bayesian hierarchical, multi-species and multi-season occupancy model. We tested predictions that species diversity is positively related to habitat heterogeneity, which in intensified agroecosystems is thought to be mediated by food availability; thus the extent of land use and cover is predicted to affect foraging guilds differently. We also infer about ecosystem services provisioning and inform management recommendations for conservation of birds. Overall our results support the predictions. Although many species within each guild responded differently to land use and native forest cover, we identified generalities for most trophic guilds. For example, granivorous gleaners, ground insectivores and omnivores responded negatively to high proportions of soybean, while insectivore gleaners and aerial foragers seemed more tolerant. Habitat heterogeneity would likely benefit most species in an intensified agroecosystem, and can be achieved with a diversity of crops, pastures, and natural areas within the landscape. Although most studied species are insectivores, potentially beneficial for pest control, some guilds such as ground insectivores are poorly represented, suggesting that agricultural intensification reduces ecological functions, which may be recovered through management. Continuation of the bird monitoring program will allow us to continue to

  6. Multi-Season Regional Analysis of Multi-Species Occupancy: Implications for Bird Conservation in Agricultural Lands in East-Central Argentina.

    PubMed

    Goijman, Andrea Paula; Conroy, Michael J; Bernardos, Jaime Nicolás; Zaccagnini, María Elena

    2015-01-01

    Rapid expansion and intensification of agriculture create challenges for the conservation of biodiversity and associated ecosystem services. In Argentina, the total row crop planted area has increased in recent decades with the expansion of soybean cultivation, homogenizing the landscape. In 2003 we started the first long-term, large-scale bird monitoring program in agroecosystems of central Argentina, in portions of the Pampas and Espinal ecoregions. Using data from this program, we evaluated the effect of land use and cover extent on birds between 2003-2012, accounting for imperfect detection probabilities using a Bayesian hierarchical, multi-species and multi-season occupancy model. We tested predictions that species diversity is positively related to habitat heterogeneity, which in intensified agroecosystems is thought to be mediated by food availability; thus the extent of land use and cover is predicted to affect foraging guilds differently. We also infer about ecosystem services provisioning and inform management recommendations for conservation of birds. Overall our results support the predictions. Although many species within each guild responded differently to land use and native forest cover, we identified generalities for most trophic guilds. For example, granivorous gleaners, ground insectivores and omnivores responded negatively to high proportions of soybean, while insectivore gleaners and aerial foragers seemed more tolerant. Habitat heterogeneity would likely benefit most species in an intensified agroecosystem, and can be achieved with a diversity of crops, pastures, and natural areas within the landscape. Although most studied species are insectivores, potentially beneficial for pest control, some guilds such as ground insectivores are poorly represented, suggesting that agricultural intensification reduces ecological functions, which may be recovered through management. Continuation of the bird monitoring program will allow us to continue to

  7. Estimation of regional surface resistance to evapotranspiration from NDVI and thermal-IR AVHRR data. [Normalized Difference Vegetation Index

    NASA Technical Reports Server (NTRS)

    Nemani, Ramakrishna R.; Running, Steven W.

    1989-01-01

    Infrared surface temperatures from satellite sensors have been used to infer evaporation and soil moisture distribution over large areas. However, surface energy partitioning to latent versus sensible heat changes with surface vegetation cover and water availability. The hypothesis that the relationship between surface temperature and canopy density is sensitivite to seasonal changes in canopy resistance of conifer forests is presently tested. Surface temperature and canopy density were computed for a 20 x 25 km forested region in Montana, from the NOAA/AVHRR for 8 days during the summer of 1985. A forest ecosystem model, FOREST-BGC, simulated canopy resistance for the same period. For all eight days, surface temperatures had high association with canopy density, measured as Normalized Difference Vegetation Index, implying that latent heat exchange is the major cause of spatial variations in surface radiant tmeperatures.

  8. Analysis of AVHRR, CZCS and historical in situ data off the Oregon Coast

    NASA Technical Reports Server (NTRS)

    Strub, P. Ted; Chelton, Dudley B.

    1990-01-01

    The original scientific objectives of this grant were to: (1) characterize the seasonal cycles and interannual variability for phytoplankton concentrations and sea surface temperature (SST) in the California Current using satellite data; and (2) to explore the spatial and temporal relationship between these variables and surface wind forcing. An additional methodological objective was to develop statistical methods for forming mean fields, which minimize the effects of random data gaps and errors in the irregularly sampled CZCS (Coastal Zone Color Scanner) and AVHRR (Advanced Very High Resolution Radiometer) satellite data. A final task was to evaluate the level of uncertainty in the wind fields used for the statistical analysis. Funding in the first year included part of the cost of an image processing system to enable this and other projects to process and analyze satellite data. This report consists of summaries of the major projects carried out with all or partial support from this grant. The appendices include a list of papers and professional presentations supported by the grant, as well as reprints of the major papers and reports.

  9. The Calibration of AVHRR Visible Dual Gain using Meteosat-8 for NOAA-16 to 18

    NASA Technical Reports Server (NTRS)

    Doelling, David R.; Garber, Donald P.; Avey, L. A.; Nguyen, Louis; Minnis, Patrick

    2007-01-01

    The NOAA AVHRR program has given the remote sensing community over 25 years of imager radiances to retrieve global cloud, vegetation, and aerosol properties. This dataset can be used for long-term climate research, if the AVHRR instrument is well calibrated. Unfortunately, the AVHRR instrument does not have onboard visible calibration and does degrade over time. Vicarious post-launch calibration is necessary to obtain cloud properties that are not biased over time. The recent AVHRR-3 instrument has a dual gain in the visible channels in order to achieve greater radiance resolution in the clear-sky. This has made vicarious calibration of the AVHRR-3 more difficult to unravel. Reference satellite radiances from well-calibrated instruments, usually equipped with solar diffusers, such as MODIS, have been used to successfully vicariously calibrate other visible instruments. Transfer of calibration from one satellite to another using co-angled, collocated, coincident radiances has been well validated. Terra or Aqua MODIS and AVHRR comparisons can only be performed over the poles during summer. However, geostationary satellites offer a transfer medium that captures both parts of the dual gain. This AVHRR-3 calibration strategy uses, calibrated with MODIS, Meteosat-8 radiances simultaneously to determine the dual gains using 50km regions. The dual gain coefficients will be compared with the nominal coefficients. Results will be shown for all visible channels for NOAA-17.

  10. Improvement of Cold Season Land Precipitation Retrievals Through The Use Of WRF Simulations and High Frequency Microwave Radiative Transfer Model

    NASA Astrophysics Data System (ADS)

    Wang, N.; Ferraro, R. R.; Gopalan, K.; Tao, W.; Shi, J. J.

    2009-12-01

    As we move from the TRMM to GPM era, more emphasis will be placed on a larger regime of precipitation in mid- and high-latitudes, including light rain, mixed-phase precipitation and snowfall. In these areas, a large and highly variable portion of the total annual precipitation is snow. There is a wealth of observational evidence of brightness temperature depression from frozen hydrometeor scattering at the high frequency from aircraft and spacecraft microwave instruments. Research on the development of snowfall retrieval over land has become increasing important in the last few years (Chen and Staelin, 2003; Kongoli et al., 2004; Skofronick-Jackson et al., 2004, Noh et al., 2006; Aonashi et al., 2007; Liu, 2008; Grecu and Olson, 2008; Kim et al., 2008). However, there is still a considerable amount of work that needs to be done to develop global snowfall detection and retrieval algorithms. This paper describes the development and testing of snowfall models and retrieval algorithms using WRF snowfall simulations and high frequency radiative transfer models for snowfall events took place in January 2007 over Ontario, Canada.

  11. The enhanced NOAA global land dataset from the advanced very high resolution radiometer

    SciTech Connect

    Gutman, G.; Tarpley, D.; Ignatov, A.

    1995-07-01

    Global mapped data of reflected radiation in the visible (0.63 {mu}m) and near-infrared (0.85 {mu}m) wavebands on the Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration satellites have been collected as the global vegetation index (GVI) dataset since 1982. Its primary objective has been vegetation studies (hence its title) using the normalized difference vegetation index (NDVI) calculated from the visible and near-IR data. The second-generation GVI, which started in April 1985, has also included brightness temperatures in the thermal IR (11 and 12 {mu}m) and the associated observation-illumination geometry. This multiyear, multispectral, multisatellite dataset is a unique tool for global land studies. At the same time, it raises challenging remote sensing and data management problems with respect to uniformity in time, enhancement of signal-to-noise ratio, retrieval of geophysical parameters from satellite radiances, and large data volumes. The authors explored a four-level generic structure for processing AVHRR data-the first two levels being remote sensing oriented and the other two directed at environmental studies-and will describe the present status of each level. The uniformity of GVI data was improved by applying an updated calibration, and noise was reduced by applying a more accurate cloud-screening procedure. In addition to the enhanced weekly data (recalibrated with appended quality/cloud flags), the available land environmental products include monthly 0-15{degrees}-resolution global maps of top-of-the-atmosphere visible and near-IR reflectances, NDVI, brightness temperatures, and a precipitable water index for April 1985-September 1994. For the first time, a 5-yr monthly climatology (means and standard deviations) of each quantity was produced. These products show strong potential for detecting and analyzing large-scale spatial and seasonal land variability. 57 refs., 8 figs.

  12. Surface vegetative biomass modelling from combined AVHRR and Landsat satellite data

    NASA Technical Reports Server (NTRS)

    Logan, T. L.; Strahler, A. H.

    1984-01-01

    A methodology for the estimation of regional biomass on the basis of Landsat and Polar Orbiter Satellite Advanced Very High Resolution Radiometer (AVHRR) imagery has been developed by the present study, which concentrated on the Sierra Nevada-Cascade Mountains ecological province of California. The Landsat data are only used initially, to calibrate the AVHRR-based biomass data. The essential element of the present approach is a 'pixel proportions' model. An integer block of Landsat pixels corresponds to each AVHRR pixel. The Landsat pixels are converted into biomass pixels using species biomass expression equations available in the literature.

  13. Modeling water and heat balance components of large territory for vegetation season using information from polar-orbital and geostationary meteorological satellites

    NASA Astrophysics Data System (ADS)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

    2015-04-01

    -2013 vegetation seasons. To provide the retrieval of Ts.eff, E, Ta, NDVI, B, and LAI the previously developed technologies of AVHRR data processing have been refined and adapted to the region of interest. The updated linear regression estimators for Ts.eff and Tà have been built using representative training samples compiled for above vegetation seasons. The updated software package has been applied for AVHRR data processing to generate estimates of named values. To verify the accuracy of these estimates the error statistics of Ts.eff and Ta derivation has been investigated for various days of named seasons using comparison with in-situ ground-based measurements. On the base of special technology and Internet resources the remote sensing products Tls, E, NDVI, LAI derived from MODIS data and covering the study area have been extracted from LP DAAC web-site for the same vegetation seasons. The reliability of the MODIS-derived Tls estimates has been confirmed via comparison with analogous and collocated ground-, AVHRR-, and SEVIRI-based ones. The prepared remote sensing dataset has also included the SEVIRI-derived estimates of Tls, E, NDVI, Ta at daylight and night-time and daily estimates of LAI. The Tls estimates has been built utilizing the method and technology developed for the retrieval of Tls and E from 15 minutes time interval SEVIRI data in IR channels 10.8 and 12.0 µm (classified as 100% cloud-free and covering the area of interest) at three successive times without accurate a priori knowledge of E. Comparison of the SEVIRI-based Tls retrievals with independent collocated Tls estimates generated at the Land Surface Analysis Satellite Applications Facility (LSA SAF, Lisbon, Portugal) has given daily- or monthly-averaged values of RMS deviation in the range of 2°C for various dates and months during the mentioned vegetation seasons which is quite acceptable result. The reliability of the SEVIRI-based Tls estimates for the study area has been also confirmed by comparing

  14. Modeling Agricultural Crop Production in China using AVHRR-based Vegetation Health Indices

    NASA Astrophysics Data System (ADS)

    Yang, B.; Kogan, F.; Guo, W.; Zhiyuan, P.; Xianfeng, J.

    Weather related crop losses have always been a concern for farmers On a wider scale it has always influenced decision of Governments traders and other policy makers for the purpose of balanced food supplies trade and distribution of aid to the nations in need Therefore national policy and decision makers are giving increasing importance to early assessment of crop losses in response to weather fluctuations This presentation emphasizes utility of AVHRR-based Vegetation health index VHI for early warning of drought-related losses of agricultural production in China The VHI is a three-channel index characterizing greenness vigor and temperature of land surface which can be used as proxy for estimation of how healthy and potentially productive could be vegetation China is the largest in the world producer of grain including wheat and rice and cotton In the major agricultural areas China s crop production is very dependent on weather The VHI being a proxy indicator of weather impact on vegetation showed some correlation with productivity of agricultural crops during the critical period of their development The periods of the strongest correlation were investigated and used to build regression models where crop yield deviation from technological trend was accepted as a dependent and VHI as independent variables The models were developed for several major crops including wheat corn and soybeans

  15. Assimilation of GOES Land Surface Data Within a Rapid Update Cycle Format: Impact on MM5 Warm Season QPF

    NASA Technical Reports Server (NTRS)

    Lapenta, William M.; Suggs, Ron; Jedlovec, Gary; McNider, Richard T.; Dembek, Scott; Arnold, James E. (Technical Monitor)

    2001-01-01

    temperatures for all cycles on each day. The LRUC will be used during the 2001 summer months to identify the impact of the assimilation on warm season QPF Results will be presented at the meeting.

  16. Biospheric environmental monitoring at BOREAS with AVHRR observations

    NASA Astrophysics Data System (ADS)

    Czajkowski, Kevin P.; Mulhern, Theresa; Goward, Samuel N.; Cihlar, Josef; Dubayah, Ralph O.; Prince, Stephen D.

    1997-12-01

    Global models of biospheric processes such as production efficiency models need environmental input and validation data sets at high temporal and spatial resolution. Methods developed to assess biospheric environmental conditions from advanced very high resolution radiometer (AVHRR) observations, specifically air temperature and surface moisture, are explored through exploitation of field measurements collected at the Boreal Ecosystem-Atmosphere Study site. The surface temperature/spectral vegetation index (TVX) concept provides the potential for estimating air temperature and surface moisture from AVHRR-type satellite observations. Initial results show that the slope of TVX over boreal landscapes is related to near-surface soil moisture in addition to vegetation type and solar irradiance. Also, the TVX air temperature estimation correlates well with shelter height observations. However, our analysis shows that challenges remain in using the TVX approach, largely because it is difficult to isolate the effects of variations in atmospheric conditions from physical environmental conditions at the Earth's surface. Clouds significantly limit the application of the TVX technique. It is also limited when the variability of the normalized difference vegetation index is low or a sharp vegetation boundary is contained within the TVX contextual array. The TVX air temperature can be used to approximate shelter height temperature to within ±5 K under most conditions; however, there are outliers with differences as large as 15 K which, at this time, cannot be explained. The air temperature estimation also exhibits a 3.2 K warm bias. Part of this bias is a result of errors in the split window surface temperature estimate used in the TVX regression.

  17. Differences in visible and near-IR responses, and derived vegetation indices, for the NOAA-9 and NOAA-10 AVHRRs: a case study

    USGS Publications Warehouse

    Gallo, Kevin P.; Eidenshink, Jeffery C.

    1988-01-01

    This study evaluates the differences in the visible and near-IR responses of the Advanced Very High Resolution Radiometers (AVHRR) of the National Oceanic and Atmospheric Administration (NOAA)-9 and -10 satellites for coincident sample locations. The study also evaluates the differences in vegetation indices computed from those data. Data were acquired of the southeast portion of the United States for the 6 December 1986 daylight orbits of NOAA-9 and NOAA-10 satellites. The results suggest that, with appropriate gain and offset, the vegetation indices of the two sensor systems may be interchangeable for assessment of land surfaces.

  18. Correlations of onshore/offshore structure from a combined AVHRR/Geosat altimeter image of the Antarctic Plate

    SciTech Connect

    Dalziel, I.W.D.; Royer, J.Y.; Lawver, L.A. ); Sandwell, D.T. )

    1990-06-01

    Data collected by the Advanced Very High Resolution Radiometer (AVHRR) aboard Nimbus-X and the satellite altimeter aboard Geosat have provided an extraordinary view of the Antarctic continent and the surrounding seafloor. To examine the relationship between onshore and offshore structure, the authors have merged an AVHRR mosaic image produced by the British National Remote Sensing Centre with a geoid image derived from two years of Geosat altimetry. They averaged 4-4 repeat cycles of Geosat data to improve the accuracy, resolution, and coverage of the marine geoid, especially in areas usually obscured by year-round ice. In addition to constructing the geoid image, the Geosat data were combined with available shipboard bathymetric data and magnetic anomaly identifications to construct a tectonic element chart of the Southern Ocean. The major tectonic elements include several large age-offset fracture zones that place tight constraints on the breakup of Gondwana. In many cases, onshore extensions of these major fracture zones correlate with prominent continental structures. For example, the Tasman FZ extends from the western edge of Tasmania for 2,500 km across the southern Indian Ocean and terminates along the eastern edge of George V Basin. Onshore, this prominent lineation continues along the edge of the Trans-Antarctic Mountains in Victoria Land, Antarctica. Similarly, the Udintsev FZ extends from the northern edge of the Chatham Rise for 4-500 km across the South Pacific to a point north of Thurston I., where it fades out. The onshore extension of the Udintsev FZ may mark a major tectonic and physiographic boundary between the Weddellia and Marie Byrd Land crustal blocks of West Antarctica. Other prominent onshore/offshore correlations include the continuation of the Queen Fabiola Mountains as the Gunnerus Ridge and the continuation of the Lambert-Amery aulacogen seaward onto the continental margin.

  19. Assessing land cover performance in Senegal, West Africa using 1-km integrated NDVI and local variance analysis

    USGS Publications Warehouse

    Budde, M.E.; Tappan, G.; Rowland, J.; Lewis, J.; Tieszen, L.L.

    2004-01-01

    The researchers calculated seasonal integrated normalized difference vegetation index (NDVI) for each of 7 years using a time-series of 1-km data from the Advanced Very High Resolution Radiometer (AVHRR) (1992-93, 1995) and SPOT Vegetation (1998-2001) sensors. We used a local variance technique to identify each pixel as normal or either positively or negatively anomalous when compared to its surroundings. We then summarized the number of years that a given pixel was identified as an anomaly. The resulting anomaly maps were analysed using Landsat TM imagery and extensive ground knowledge to assess the results. This technique identified anomalies that can be linked to numerous anthropogenic impacts including agricultural and urban expansion, maintenance of protected areas and increased fallow. Local variance analysis is a reliable method for assessing vegetation degradation resulting from human pressures or increased land productivity from natural resource management practices. ?? 2004 Published by Elsevier Ltd.

  20. Characterizing Mediterranean Land Surfaces as Component of the Regional Climate System by Remote Sensing

    NASA Technical Reports Server (NTRS)

    Bolle, H.-J.; Koslowsky, D.; Menenti, M.; Nerry, F.; Otterman, Joseph; Starr, D.

    1998-01-01

    Extensive areas in the Mediterranean region are subject to land degradation and desertification. The high variability of the coupling between the surface and the atmosphere affects the regional climate. Relevant surface characteristics, such as spectral reflectance, surface emissivity in the thermal-infrared region, and vegetation indices, serve as "primary" level indicators for the state of the surface. Their spatial, seasonal and interannual variability can be monitored from satellites. Using relationships between these primary data and combining them with prior information about the land surfaces (such as topography, dominant soil type, land use, collateral ground measurements and models), a second layer of information is built up which specifies the land surfaces as a component of the regional climate system. To this category of parameters which are directly involved in the exchange of energy, momentum and mass between the surface and the atmosphere, belong broadband albedo, thermodynamic surface temperature, vegetation types, vegetation cover density, soil top moisture, and soil heat flux. Information about these parameters finally leads to the computation of sensible and latent heat fluxes. The methodology was tested with pilot data sets. Full resolution, properly calibrated and normalized NOAA-AVHRR multi-annual primary data sets are presently compiled for the whole Mediterranean area, to study interannual variability and longer term trends.

  1. Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

    USGS Publications Warehouse

    Stow, D.A.; Hope, A.; McGuire, D.; Verbyla, D.; Gamon, J.; Huemmrich, F.; Houston, S.; Racine, C.; Sturm, M.; Tape, K.; Hinzman, L.; Yoshikawa, K.; Tweedie, C.; Noyle, B.; Silapaswan, C.; Douglas, D.; Griffith, B.; Jia, G.; Epstein, H.; Walker, D.; Daeschner, S.; Petersen, A.; Zhou, L.; Myneni, R.

    2004-01-01

    The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation Land-Air-Ice Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations. The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored. ?? 2003 Elsevier Inc. All rights reserved.

  2. Remote sensing of vegetation and land-cover change in Arctic tundra ecosystems

    USGS Publications Warehouse

    Checkstow, D.A.; Hope, A.; McGuire, D.; Verbyla, D.; Gamon, J.; Huemmrich, F.; Houston, S.; Racine, C.; Sturm, M.; Tape, K.; Hinzman, L.; Yoshikawa, K.; Tweedie, C.

    2004-01-01

    The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation Land-Air-Ice Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations. The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored.

  3. AVHRR Surface Temperature and Narrow-Band Albedo Comparison with Ground Measurements for the Greenland Ice Sheet

    NASA Technical Reports Server (NTRS)

    Haefliger, M.; Steffen, K.; Fowler, C.

    1993-01-01

    An ice-surface temperature retrieval algorithm for the Greenland ice sheet was developed using NOAA 11 thermal radiances from channels 4 and 5. Temperature, pressure and humidity profiles, cloud observations and skin temperatures from the Swiss Federal Institute of Technology (ETH) camp, located at the equilibrium line altitude at 49 deg17 min W, 69 deg 34 min N, were used in the LOWTRAN 7 model. Through a statistical analysis of daily clear sky profiles, the coefficients that correct for the atmospheric effects were determined for the ETH-Camp field season (May to August). Surface temperatures retrieved by this method were then compared against the in situ observations with a maximum difference of 0.6 K. The NOAA 11 narrow-band planetary albedo values for channels 1 and 2 were calculated using pre-launch calibration coefficients. Scattering and absorption by the atmosphere were modelled with LOWTRAN 7. Then, narrow-band albedo values for the AVHRR visible and near infrared channels were compared with in situ high resolution spectral reflectance measurements. In the visible band (580-680 nm), AVHRR-derived narrow-band albedo and the in situ measurements corrected with radiative transfer model LOWTRAN 7 showed a difference of less than 2%. For the near infrared channel (725-1100 nm) the difference between the measured and modelled narrow-band albedo was 14%. These discrepancies could be either the result of inaccurate aerosol scattering modelling (lack of the in situ observation), or the result of sensor drift due to degradation.

  4. Land use regression models to estimate the annual and seasonal spatial variability of sulfur dioxide and particulate matter in Tehran, Iran.

    PubMed

    Amini, Hassan; Taghavi-Shahri, Seyed Mahmood; Henderson, Sarah B; Naddafi, Kazem; Nabizadeh, Ramin; Yunesian, Masud

    2014-08-01

    The Middle Eastern city of Tehran, Iran has poor air quality compared with cities of similar size in Europe and North America. Spatial annual and seasonal patterns of SO2 and PM10 concentrations were estimated using land use regression (LUR) methods applied to data from 21 air quality monitoring stations. A systematic algorithm for LUR model building was developed to select variables based on (1) consistency with a priori assumptions about the assumed directions of the effects, (2) a p-value of <0.1 for each predictor, (3) improvements to the leave-one-out cross-validation (LOOCV) R(2), (4) a multicollinearity index called the variance inflation factor, and (5) a grouped (leave-25%-out) cross-validation (GCV) for final model. In addition, several new predictive variables and variable types were explored. The annual mean concentrations of SO2 and PM10 across the stations were 38 ppb and 100.8 μg/m(3), respectively. The R(2) values ranged from 0.69 to 0.84 for SO2 models and from 0.62 to 0.67 for PM10 models. The LOOCV and GCV R(2) values ranged, respectively, from 0.40 to 0.56 and 0.40 to 0.50 for the SO2 models; they were 0.48 to 0.57 and 0.50 to 0.55, respectively, for the PM10 models. There were clear differences between the SO2 and PM10 models, but the warmer and cooler season models were consistent with the annual models for both pollutants. Although there was limited similarity between the SO2 and PM10 predictive variables, measures of street density and proximity to airport or air cargo facilities were consistent across both pollutants. In 2010, the entire population of Tehran lived in areas where the World Health Organization guidelines for 24-hour mean SO2 (7 ppb) and annual average PM10 (20 μg/m(3)) were exceeded. PMID:24836390

  5. A technique for extrapolating and validating forest cover across large regions - Calibrating AVHRR data with TM data

    NASA Technical Reports Server (NTRS)

    Iverson, L. R.; Cook, E. A.; Graham, R. L.

    1989-01-01

    A method is presented for extending high-resolution forest cover information across large regions. Using Landsat TM data with AVHRR data, an empirical relationship beween AVHRR spectral signatures and forest cover is developed. The resulting regression equation is applied to an AVHRR scene covering a large area centered around southern Illinois. The map is used to estimate forest cover within a geographical information system. The results are compared with U.S. Forest Service estimates, showing good agreement.

  6. Estimating spectral albedo and nadir reflectance through inversion of simple BRDF models with AVHRR/MODIS-like data

    NASA Astrophysics Data System (ADS)

    Privette, Jeffrey L.; Eck, Thomas F.; Deering, Donald W.

    1997-12-01

    In recent years, many computationally efficient bidirectional reflectance models have been developed to account for angular effects in land remote sensing data, particularly those from the NOAA advanced very high resolution radiometer (AVHRR), polarization and directionality of the Earth's reflectances (POLDER), and the planned EOS moderate-resolution imaging spectrometer (MODIS) and multi-angle imaging spectroradiometer (MISR) sensors. In this study, we assessed the relative ability of 10 such models to predict commonly used remote sensing products (nadir reflectance and albedo). Specifically, we inverted each model with ground-based data from the portable apparatus for rapid acquisition of bidirectional observations of the land and atmosphere (PARABOLA) arranged in subsets representative of satellite sampling geometries. We used data from nine land cover types, ranging from soil to grassland (First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE)) to forest (Boreal Ecosystem-Atmosphere Study (BOREAS)). Retrieved parameters were used in forward model runs to estimate nadir reflectance and spectral albedo over a wide range of solar angles. We rank the models by the accuracy of the estimated products and find results to be strongly dependent on the view azimuth angle range of the inversion data, and less dependent on the spectral band and land cover type. Overall, the nonlinear model of Rahman et al. [993] and the linear kernel-driven RossThickLiSparse model [Wanner et al., 1995] were most accurate. The latter was at least 25 times faster to invert than the former. Interestingly, we found these two models were not able to match the various bidirectional reflectance distribution function (BRDF) shapes as well as other models, suggesting their superior performance lies in their ability to be more reliably inverted with sparse data sets. These results should be useful to those interested in the computationally fast normalization

  7. Influence of seasonal and inter-annual hydro-meteorological variability on surface water fecal coliform concentration under varying land-use composition.

    PubMed

    St Laurent, Jacques; Mazumder, Asit

    2014-01-01

    Quantifying the influence of hydro-meteorological variability on surface source water fecal contamination is critical to the maintenance of safe drinking water. Historically, this has not been possible due to the scarcity of data on fecal indicator bacteria (FIB). We examined the relationship between hydro-meteorological variability and the most commonly measured FIB, fecal coliform (FC), concentration for 43 surface water sites within the hydro-climatologically complex region of British Columbia. The strength of relationship was highly variable among sites, but tended to be stronger in catchments with nival (snowmelt-dominated) hydro-meteorological regimes and greater land-use impacts. We observed positive relationships between inter-annual FC concentration and hydro-meteorological variability for around 50% of the 19 sites examined. These sites are likely to experience increased fecal contamination due to the projected intensification of the hydrological cycle. Seasonal FC concentration variability appeared to be driven by snowmelt and rainfall-induced runoff for around 30% of the 43 sites examined. Earlier snowmelt in nival catchments may advance the timing of peak contamination, and the projected decrease in annual snow-to-precipitation ratio is likely to increase fecal contamination levels during summer, fall, and winter among these sites. Safeguarding drinking water quality in the face of such impacts will require increased monitoring of FIB and waterborne pathogens, especially during periods of high hydro-meteorological variability. This data can then be used to develop predictive models, inform source water protection measures, and improve drinking water treatment. PMID:24095594

  8. Evaluation of Decision Trees for Cloud Detection from AVHRR Data

    NASA Technical Reports Server (NTRS)

    Shiffman, Smadar; Nemani, Ramakrishna

    2005-01-01

    Automated cloud detection and tracking is an important step in assessing changes in radiation budgets associated with global climate change via remote sensing. Data products based on satellite imagery are available to the scientific community for studying trends in the Earth's atmosphere. The data products include pixel-based cloud masks that assign cloud-cover classifications to pixels. Many cloud-mask algorithms have the form of decision trees. The decision trees employ sequential tests that scientists designed based on empirical astrophysics studies and simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In a previous study we compared automatically learned decision trees to cloud masks included in Advanced Very High Resolution Radiometer (AVHRR) data products from the year 2000. In this paper we report the replication of the study for five-year data, and for a gold standard based on surface observations performed by scientists at weather stations in the British Islands. For our sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks p < 0.001.

  9. An algorithm for the retrieval of suspended sediment in coastal waters of China from AVHRR data

    NASA Astrophysics Data System (ADS)

    Li, Yan; Huang, Wei; Fang, Ming

    1998-04-01

    An algorithm using an analytical model based on the difference of the NOAA/AVHRR (Advanced Very High Resolution Radiometer) Channel 1 (580-680 nm) and Channel 2 (720-1100 nm) reflectance data is developed for the retrieval of suspended sediment in coastal and shelf waters. The model assumes that the suspended sediment concentration, S, is a function of the difference of the water leaving reflectance of Channels 1 and 2, Rd. The formula is governed by the optical parameters of water and suspended sediment, including volume scattering and absorption coefficients of the two channels. The analytical model yielded a best fit curve when the water leaving reflectance of the two channels were plotted against each other for Case 2 water, where the suspended sediment concentration ranged from 5 to over 100 g m -3. A standard curve of S against Rd was obtained. Using Tassan (1994)'s recommendations for the contribution of water and suspended sediment to the in-water absorption and backscattering coefficients in his three-component color model, the suspended sediment concentration corresponding to the maximum point of Rd was about 60 g m -3, and was independent of the atmospheric optical properties. Thus, this process provides a convenient tool to remove the atmospheric fluctuations of atmospheric transmittance by reconciling the maximum point of the image with the standard curve. The algorithm was tested using data from seven transects in the China Sea, and the retrieved results for the Zhujiang (Pearl River) Estuary were compared with the sea-truth data with good agreement. This suggests that the algorithm can be used as a seasonal regional model for water masses along the China coast.

  10. Melt Pond Development on Arctic Land-Fast Sea Ice in Relation to Snow and Ice Properties During the Ice Growth Season

    NASA Astrophysics Data System (ADS)

    Petrich, C.; Eicken, H.; Pringle, D.; Sturm, M.; Perovich, D.; Polashenski, C.; Finnegan, D.

    2008-12-01

    The dynamics of melt pond development on sea ice were studied on a well-defined patch of level land-fast sea ice off the coast of Barrow, Alaska in 2008. The pond development was correlated with both sea ice properties and the history of snow distribution during the ice growth season. In mid January, the ice was covered by an almost level snow layer of 4~cm thickness. We observed an increase in snow depth and development of snow dunes since February. At least some snow dunes stayed in place, and at the end of April ice thickness was negatively correlated with the thickness of compacted snow dunes. Snow salinity remained above 5~psu in the bottom 4 to 5~cm of the snow pack throughout the ice growth season. In comparison, snow more than 5~cm above the snow--ice interface was almost devoid of salt. The air temperature increased rapidly in early May and started to exceed 0°C on May 15. From this day on, thermistor string data show that the sea ice temperature profile deviated from linear with the lowest temperature inside the body of ice rather than at the surface. Superimposed ice was present with certainty after May 24. The superimposed ice investigated in early June exhibited a rough texture consistent with meltwater percolation columns in the snow pack. It was found only under snow dunes; no superimposed ice was observed under thin snow (2~cm) or melt ponds. Meltwater collected at topographic low points that surrounded distinct ice islands. Aerial photography and surface LiDAR measurements at various times during the early melt season showed that the location of these ice islands coincided with the locations of wind packed snow dunes that had been tracked since February. The lateral movement of surface waters was relatively slow during the very early stages of melt pond formation. However, we observed a significant lateral redistribution of meltwater under the ice surface; this redistribution happened through distinct veins. The sea ice salinity profiles showed

  11. Long time-series of turbid coastal water using AVHRR: An example from Florida Bay, USA

    USGS Publications Warehouse

    Stumpf, R.P.; Frayer, M.L.

    1997-01-01

    The AVHRR can provide information on the reflectance of turbid case II water, permitting examination of large estuaries and plumes from major rivers. The AVHRR has been onboard several NOAA satellites, with afternoon overpasses since 1981, offering a long time-series to examine changes in coastal water. We are using AVHRR data starting in December 1989, to examine water clarity in Florida Bay, which has undergone a decline since the late 1980's. The processing involves obtaining a nominal reflectance for red light with standard corrections including those for Rayleigh and aerosol path radiances. Established relationships between reflectance and the water properties being measured in the Bay provide estimates of diffuse attenuation and light limitation for phytoplankton and seagrass productivity studies. Processing also includes monthly averages of reflectance and attenuation. The AVHRR data set describes spatial and temporal patterns, including resuspension of bottom sediments in the winter, and changes in water clarity. The AVHRR also indicates that Florida Bay has much higher reflectivity relative to attenuation than other southeastern US estuaries. ??2005 Copyright SPIE - The International Society for Optical Engineering.

  12. Estimation of carbon emissions from wildfires in Alaskan boreal forests using AVHRR data

    SciTech Connect

    Kasischke, E.S.; French, N.H.F.; Bourgeau-Chavez, L.L )

    1993-06-01

    The objectives of this research study were to evaluate the utility of using AVHRR data for locating and measuring the areal extent of wildfires in the boreal forests of Alaska and to estimate the amount of carbon being released during these fires. Techniques were developed to using the normalized difference vegetation signature derived from AVHRR data to detect and measure the area of fires in Alaska. A model was developed to estimate the amount of biomass/carbon being stored in Alaskan boreal forests, and the amount of carbon released during fires. The AVHRR analysis resulted in detection of > 83% of all forest fires greater than 2,000 ha in size in the years 1990 and 1991. The areal estimate derived from AVHRR data were 75% of the area mapped by the Alaska Fire Service for these years. Using fire areas and locations for 1954 through 1992, it was determined that on average, 13.0 gm-C-m-2 of boreal forest area is released during fires every year. This estimate is two to six times greater than previous reported estimates. Our conclusions are that the analysis of AVHRR data represents a viable means for detecting and mapping fires in boreal regions on a global basis.

  13. Agreement evaluation of AVHRR and MODIS 16-day composite NDVI data sets

    USGS Publications Warehouse

    Ji, L.; Gallo, K.; Eidenshink, J.C.; Dwyer, J.

    2008-01-01

    Satellite-derived normalized difference vegetation index (NDVI) data have been used extensively to detect and monitor vegetation conditions at regional and global levels. A combination of NDVI data sets derived from AVHRR and MODIS can be used to construct a long NDVI time series that may also be extended to VIIRS. Comparative analysis of NDVI data derived from AVHRR and MODIS is critical to understanding the data continuity through the time series. In this study, the AVHRR and MODIS 16-day composite NDVI products were compared using regression and agreement analysis methods. The analysis shows a high agreement between the AVHRR-NDVI and MODIS-NDVI observed from 2002 and 2003 for the conterminous United States, but the difference between the two data sets is appreciable. Twenty per cent of the total difference between the two data sets is due to systematic difference, with the remainder due to unsystematic difference. The systematic difference can be eliminated with a linear regression-based transformation between two data sets, and the unsystematic difference can be reduced partially by applying spatial filters to the data. We conclude that the continuity of NDVI time series from AVHRR to MODIS is satisfactory, but a linear transformation between the two sets is recommended.

  14. NOAA/AVHRR vegetation indices as agrometeorological growth parameter

    NASA Astrophysics Data System (ADS)

    Gupta, R. K.

    1993-05-01

    This paper deals with the utility of NOAA/AVHRR vegetation indices as agrometeorological growth parameters. The area chosen to the study was the Punjab and the Haryana states of India, both comprising districts primarily under wheat cultivation with 68-76% geographical area under agriculture and 89-96% agricultural area under wheat. Application of geometric correction to visible and near IR band images followed by computation of NDVI and RVI images yielded less error than the conventional method of correction to NDVI/RVI images. Images having far-side boundary pixel upto 38 degree scan angle did not cause significant error at district level statistics. RVI was more sensitive than NDVI from emergence to near jointing and maturity to senescence stages. Prior to jointing stage and after dough stage RVI can be transformed to NDVI, to enable its joint use with NDVI. The maximum and mean air temperatures based growing degree days (GDD) related well with the NDVI/RVI temporal profile over the entire crop growth cycle at 98-99% significance level. However, shapewise the maximum temperature based GDD was superior to mean temperature based GDD, whereas minimum temperature based GDD had statistically significant relationship only upto dough stage at 95% significance level. The integrated NDVI (INDVI) values computed for mid of late-tillering to jointing stage were significantly related to the yield (r-square = 0.867, at 99.34% significance level). When INDVI at this stage was coupled with that of mid of milking and dough - nearing maturity stages, the predictability of wheat yields increased (r-square = 0.891, at 99.32% significance level).

  15. Methodology for estimating burned area from AVHRR reflectance data

    SciTech Connect

    Razafimpanilo, H.; Frouin, R.; Iacobellis, S.F.; Somerville, R.C.J.

    1995-12-01

    It is well recognized that global fire activity needs to be monitored closely, because of its potential impact on climate and the environment. Two methods are described to determined burned area from Advanced Very High Resolution Radiometer (AVHRR) data. The first method, or the linear method, employs Channel 2 reflectance, R{sub 2}, and is based on the nearly linear relationship between the fraction of pixel burned, P, and R{sub 2}. The second method, or the nonlinear method, employs the Normalized Difference Vegetation Index (NDVI) derived from Channels 1 and 2 reflectances, and is based on the nonlinear relationship P = f(NDVI), a polynomial of order 2 in NDVI. The coefficients of the polynomial are parameterized as a function of the NDVI of the background before the fire event. Radiative transfer simulations indicate that the linear method, unlike the nonlinear method, must be applied to top-of-atmosphere reflectances that have been corrected for atmospheric influence. Sensitivity studies suggest that the methods are subject to some limitations. To avoid discontinuity problems, the original background (just before the fire) must be characterized by a Channel 2 reflectance above 0.07 and by a positive NDVI. To separate the useful signal from atmospheric effects, the fire scar must occupy at least 20% and 12% of the pixel area in the case of savanna and green vegetation (e.g., forest), respectively. When applied to uniform pixels, the mean relative error on the fraction of area burned is about 20% for the linear method and 10% for the nonlinear method. The linear method gives better results for nonuniform pixels, but neither method can be used when the pixel contains low reflectance backgrounds (e.g., water).

  16. Global land cover classification by remote sensing - Present capabilities and future possibilities

    NASA Technical Reports Server (NTRS)

    Townshend, John; Justice, Christopher; Li, Wei; Gurney, Charlotte; Mcmanus, Jim

    1991-01-01

    The adequacy of traditional approaches to the derivation of global information on land cover is examined. The contribution of coarse resolution satellite data from the NOAA series of satellites is discussed. The Moderate Resolution Imaging Spectrometer of the Earth Observing System is considered to be a substantially better instrument than the AVHRR in terms of several spectral, radiometric, and geometric properties. In terms of its total field of view and frequency of imaging, the instrument will be comparable to the AVHRR for global land cover monitoring.

  17. Carbon Dynamics of Surface Soil after Land Use Change in a Seasonal Tropical Forest in North-eastern Thailand: Application of a Stable Carbon Isotope Mixing Model

    NASA Astrophysics Data System (ADS)

    Sakai, M.; Visaratana, T.; Sukchan, S.; Thaingam, R.; Okada, N.

    2015-12-01

    Globally, soil is vital to the mitigation of climate change. In tropical forests, the soil contains an estimated 216 Gt of carbon, equivalent to half of the total carbon in the tropical forest ecosystem. Little is known regarding changes in soil carbon following land use changes in tropical regions. We examined the differences in carbon dynamics in a chronosequence of Acacia mangium plantations established on grasslands following the deforestation of natural forest in north-eastern Thailand. The study site was located at the Sakaerat Silvicultural Research Station (14º28'06.1″N, 101º54'15.0″E; altitude 420 m asl), Nakhon Rachasima Province, north-eastern Thailand. Mean annual air temperature was 26ºC, and annual precipitation was 1,100 mm, with a dry (November-April) and wet (May-October) season. Soil carbon and the stable carbon isotope ratio (d13C) in the surface soil (0-5 and 5-10 cm deep) were determined at 12 and 24 years following establishment of A. mangium plantations, as well as for secondary forest and grassland. Using the stable carbon isotope mixing model based on differences in the natural abundance of d13C in plants with C3 (i.e., trees) and C4 (i.e., grasses) pathways for CO2 fixation, the amount of soil carbon derived from the plantations, forest, and grassland was calculated. Soil carbon at a depth of 10 cm was higher in the secondary forest (1,929 gCm-2) and grassland (2,508 gCm-2) than in the plantations (1,703 gCm-2 at 12 years, 1,673gCm-2 at 24 years). Soil carbon derived from A. mangium was 67% (0-5 cm deep) and 62% (5-10 cm deep) of total soil carbon at 12 years, and was 100% (0-5 cm deep) and 90% (5-10 cm deep) at 24 years in the plantations. We found that most of the soil carbon at a depth of 0-5 cm in the young plantation changed from grass-derived to tree-derived carbon within a relatively short period of 24 years. Because of changes in soil carbon, exotic, fast growing plantations like those of A. mangium are needed to quickly

  18. AVHRR-Based Polar Pathfinder Products: Evaluation, Enhancement and Transition to MODIS

    NASA Technical Reports Server (NTRS)

    Fowler, Charles; Masalanik, James; Stone, Robert; Stroeve, Julienne; Emery, William

    2001-01-01

    The Advanced Very High Resolution Radiometer (AVHRR)-Based Polar Pathfinder (APP) products include calibrated AVHRR channel data, surface temperatures, albedo, satellite scan and solar geometries, and cloud mask, all composited into twice-per-day images, and daily averaged fields of sea ice motion, for regions poleward of 50 latitude. Our general goals under this grant: (1) Quantify the APP accuracy and sources of error by comparing Pathfinder products with field measurements; (2) Determine the consistency of mean fields and trends in comparison with longer time series of available station data and forecast model output; (3) Investigate the consistency of the products between the different AVHRR instruments over the 1982-present period of the NOAA program; and (4) Compare and annual cycle of the APP products with MODIS to establish a baseline for extending Pathfinder-type products into the new ESE period.

  19. BOREAS Level-4b AVHRR-LAC Ten-Day Composite Images: At-sensor Radiance

    NASA Technical Reports Server (NTRS)

    Cihlar, Josef; Chen, Jing; Nickerson, Jaime; Newcomer, Jeffrey A.; Huang, Feng-Ting; Hall, Forrest G. (Editor)

    2000-01-01

    The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. Manitoba Remote Sensing Center (MRSC) and BOREAS Information System (BORIS) personnel acquired, processed, and archived data from the Advanced Very High Resolution Radiometer (AVHRR) instruments on the National Oceanic and Atmospheric Administration (NOAA-11) and -14 satellites. The AVHRR data were acquired by CCRS and were provided to BORIS for use by BOREAS researchers. These AVHRR level-4b data are gridded, 10-day composites of at-sensor radiance values produced from sets of single-day images. Temporally, the 10- day compositing periods begin 11-Apr-1994 and end 10-Sep-1994. Spatially, the data cover the entire BOREAS region. The data are stored in binary image format files.

  20. BOREAS Level-4c AVHRR-LAC Ten-Day Composite Images: Surface Parameters

    NASA Technical Reports Server (NTRS)

    Cihlar, Josef; Chen, Jing; Huang, Fengting; Nickeson, Jaime; Newcomer, Jeffrey A.; Hall, Forrest G. (Editor)

    2000-01-01

    The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. Manitoba Remote Sensing Center (MRSC) and BOREAS Information System (BORIS) personnel acquired, processed, and archived data from the Advanced Very High Resolution Radiometer (AVHRR) instruments on the NOAA-11 and -14 satellites. The AVHRR data were acquired by CCRS and were provided to BORIS for use by BOREAS researchers. These AVHRR level-4c data are gridded, 10-day composites of surface parameters produced from sets of single-day images. Temporally, the 10-day compositing periods begin 11-Apr-1994 and end 10-Sep-1994. Spatially, the data cover the entire BOREAS region. The data are stored in binary image format files. Note: Some of the data files on the BOREAS CD-ROMs have been compressed using the Gzip program.

  1. Application of a genetic algorithm for crop model steering using NOAA-AVHRR data

    NASA Astrophysics Data System (ADS)

    de Wit, Allard J. W.

    1999-12-01

    The main objective of this study was to investigate whether AVHRR data could be useful for crop model simulation steering by intrinsically taking the mixed pixel effects into account. The second objective was to determine if the application of a genetic algorithm could be an effective technique for crop model steering. The principles were tested for the Seville test site using synthetic data and AVHRR data from 1995 and 1996 because these years show a large contrast in crop development. The main conclusions are that a genetic algorithm is a very powerful technique for crop model optimization, but adaptations are needed to the current optimization scheme in order to be able to steer the WOFOST crop model on the basis of NOAA-AVHRR data.

  2. Calibrating Historical IR Sensors Using GEO, and AVHRR Infrared Tropical Mean Calibration Models

    NASA Technical Reports Server (NTRS)

    Scarino, Benjamin; Doelling, David R.; Minnis, Patrick; Gopalan, Arun; Haney, Conor; Bhatt, Rajendra

    2014-01-01

    Long-term, remote-sensing-based climate data records (CDRs) are highly dependent on having consistent, wellcalibrated satellite instrument measurements of the Earth's radiant energy. Therefore, by making historical satellite calibrations consistent with those of today's imagers, the Earth-observing community can benefit from a CDR that spans a minimum of 30 years. Most operational meteorological satellites rely on an onboard blackbody and space looks to provide on-orbit IR calibration, but neither target is traceable to absolute standards. The IR channels can also be affected by ice on the detector window, angle dependency of the scan mirror emissivity, stray-light, and detector-to-detector striping. Being able to quantify and correct such degradations would mean IR data from any satellite imager could contribute to a CDR. Recent efforts have focused on utilizing well-calibrated modern hyper-spectral sensors to intercalibrate concurrent operational IR imagers to a single reference. In order to consistently calibrate both historical and current IR imagers to the same reference, however, another strategy is needed. Large, well-characterized tropical-domain Earth targets have the potential of providing an Earth-view reference accuracy of within 0.5 K. To that effort, NASA Langley is developing an IR tropical mean calibration model in order to calibrate historical Advanced Very High Resolution Radiometer (AVHRR) instruments. Using Meteosat-9 (Met-9) as a reference, empirical models are built based on spatially/temporally binned Met-9 and AVHRR tropical IR brightness temperatures. By demonstrating the stability of the Met-9 tropical models, NOAA-18 AVHRR can be calibrated to Met-9 by matching the AVHRR monthly histogram averages with the Met-9 model. This method is validated with ray-matched AVHRR and Met-9 biasdifference time series. Establishing the validity of this empirical model will allow for the calibration of historical AVHRR sensors to within 0.5 K, and thereby

  3. Utilization of satellite remote sensing data on land surface characteristics in water and heat balance component modeling for vegetation covered territories

    NASA Astrophysics Data System (ADS)

    Muzylev, Eugene; Uspensky, Alexander; Startseva, Zoya; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

    2010-05-01

    The model of vertical water and heat transfer in the "soil-vegetation-atmosphere" system (SVAT) for vegetation covered territory has been developed, allowing assimilating satellite remote sensing data on land surface condition as well as accounting for heterogeneities of vegetation and meteorological characteristics. The model provides the calculation of water and heat balance components (such as evapotranspiration Ev, soil water content W, sensible and latent heat fluxes and others ) as well as vertical soil moisture and temperature distributions, temperatures of soil surface and foliage, land surface brightness temperature for any time interval within vegetation season. To describe the landscape diversity soil constants and leaf area index LAI, vegetation cover fraction B, and other vegetation characteristics are used. All these values are considered to be the model parameters. Territory of Kursk region with square about 15 thousands km2 situated in the Black Earth zone of Central Russia was chosen for investigation. Satellite-derived estimates of land surface characteristics have been constructed under cloud-free condition basing AVHRR/NOAA, MODIS/EOS Terra and EOS Aqua, SEVIRI/Meteosat-8, -9 data. The developed technologies of AVHRR data thematic processing have been refined providing the retrieval of surface skin brightness temperature Tsg, air foliage temperature Ta, efficient surface temperature Ts.eff and emissivity E, as well as derivation of vegetation index NDVI, B, and LAI. The linear regression estimators for Tsg, Ta and LAI have been built using representative training samples for 2003-2009 vegetation seasons. The updated software package has been applied for AVHRR data thematic processing to generate named remote sensing products for various dates of the above vegetation seasons. The error statistics of Ta, Ts.eff and Тsg derivation has been investigated for various samples using comparison with in-situ measurements that has given RMS errors in the

  4. Land Surface Phenologies in the North American Great Plains: Detecting Climate Change Amidst Climate Variation

    NASA Astrophysics Data System (ADS)

    Henebry, G. M.; Goodin, D. G.

    2004-12-01

    The continental climate of the North American Great Plains is characterized by high interannual variability in growing season weather. Local averages of temperature and precipitation are not very helpful for predicting expected growing season conditions for vegetation production. We examined the temperature and precipitation records from a network of 'sentinel' weather stations across Kansas, Nebraska, and South Dakota. We assigned these stations into one or more of Wendland and Bryson's airstream regions (ASRs). For each station for each year, we calculated the day of year that the accumulated growing degree-days using a base of 0 oC reaches particular thermal thresholds. We call these Threshold Arrival Dates (TADs). Within each ASR we analyzed the station time series of TADs for two thermal thresholds--at the beginning and at the middle of the growing season for C4 grasses--using 30 year moving averages and Mann-Kendall trend tests. We found that the interannual variation of the onset of the growing season for C4 has increased over the period of record and especially in the last 30 years. At the same time, the central tendencies of the TADs have not changed significantly over the period of record. We also analyzed the TAD series using frequency domain analyses to identify characteristic periodicities. The spectral densities of the TADs point to possible linkages with climate modes. Finally, using the NASA Pathfinder AVHRR Land NDVI dataset, we demonstrate how to interpret the land surface phenologies revealed by synoptic sensors within the broader context of the regions' climatic envelopes.

  5. Effects of land use change and seasonality of precipitation on soil nitrogen in a dry tropical forest area in the Western Llanos of Venezuela.

    PubMed

    González-Pedraza, Ana Francisca; Dezzeo, Nelda

    2014-01-01

    We evaluated changes of different soil nitrogen forms (total N, available ammonium and nitrate, total N in microbial biomass, and soil N mineralization) after conversion of semideciduous dry tropical forest in 5- and 18-year-old pastures (YP and OP, resp.) in the western Llanos of Venezuela. This evaluation was made at early rainy season, at end rainy season, and during dry season. With few exceptions, no significant differences were detected in the total N in the three study sites. Compared to forest soils, YP showed ammonium losses from 4.2 to 62.9% and nitrate losses from 20.0 to 77.8%, depending on the season of the year. In OP, the ammonium content increased from 50.0 to 69.0% at the end of the rainy season and decreased during the dry season between 25.0 and 55.5%, whereas the nitrate content increased significantly at early rainy season. The net mineralization and the potentially mineralizable N were significantly higher (P < 0.05) in OP than in forest and YP, which would indicate a better quality of the substrate in OP for mineralization. The mineralization rate constant was higher in YP than in forest and OP. This could be associated with a reduced capacity of these soils to preserve the available nitrogen. PMID:25610907

  6. Effects of Land Use Change and Seasonality of Precipitation on Soil Nitrogen in a Dry Tropical Forest Area in the Western Llanos of Venezuela

    PubMed Central

    González-Pedraza, Ana Francisca; Dezzeo, Nelda

    2014-01-01

    We evaluated changes of different soil nitrogen forms (total N, available ammonium and nitrate, total N in microbial biomass, and soil N mineralization) after conversion of semideciduous dry tropical forest in 5- and 18-year-old pastures (YP and OP, resp.) in the western Llanos of Venezuela. This evaluation was made at early rainy season, at end rainy season, and during dry season. With few exceptions, no significant differences were detected in the total N in the three study sites. Compared to forest soils, YP showed ammonium losses from 4.2 to 62.9% and nitrate losses from 20.0 to 77.8%, depending on the season of the year. In OP, the ammonium content increased from 50.0 to 69.0% at the end of the rainy season and decreased during the dry season between 25.0 and 55.5%, whereas the nitrate content increased significantly at early rainy season. The net mineralization and the potentially mineralizable N were significantly higher (P < 0.05) in OP than in forest and YP, which would indicate a better quality of the substrate in OP for mineralization. The mineralization rate constant was higher in YP than in forest and OP. This could be associated with a reduced capacity of these soils to preserve the available nitrogen. PMID:25610907

  7. A System for Monitoring and Forecasting Land Surface Phenology Using Time Series of JPSS VIIRS Observations and Its Applications

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Yu, Y.; Liu, L.

    2015-12-01

    Land surface phenology quantifies seasonal dynamics of vegetation properties including the timing and magnitude of vegetation greenness from satellite observations. Over the last decade, historical time series of AVHRR and MODIS data has been used to characterize the seasonal and interannual variation in terrestrial ecosystems and their responses to a changing and variable climate. The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on board the operational JPSS satellites provides land surface observations in a timely fashion, which has the capability to monitor phenological development in near real time. This capability is particularly important for assisting agriculture, natural resource management, and land modeling for weather prediction systems. Here we introduce a system to monitor in real time and forecast in the short term phenological development based on daily VIIRS observations available with a one-day latency. The system integrates a climatological land surface phenology from long-term MODIS data and available VIIRS observations to simulate a set of potential temporal trajectories of greenness development at a given time and pixel. The greenness trajectories, which are qualified using daily two-band Enhanced Vegetation Index (EVI2), are applied to identify spring green leaf development and autumn color foliage status in real time and to predict the occurrence of future phenological events. This system currently monitors vegetation development across the North America every three days and makes prediction to 10 days ahead. We further introduce the applications of near real time spring green leaf and fall color foliage. Specifically, this system is used for tracing the crop progress across the United States, guiding the field observations in US National Phenology Network, servicing tourists for the observation of color fall foliage, and parameterizing seasonal surface physical conditions for numerical weather prediction models.

  8. Evaluating the Consistency of the 1982–1999 NDVI Trends in the Iberian Peninsula across Four Time-series Derived from the AVHRR Sensor: LTDR, GIMMS, FASIR, and PAL-II

    PubMed Central

    Alcaraz-Segura, Domingo; Liras, Elisa; Tabik, Siham; Paruelo, José; Cabello, Javier

    2010-01-01

    Successive efforts have processed the Advanced Very High Resolution Radiometer (AVHRR) sensor archive to produce Normalized Difference Vegetation Index (NDVI) datasets (i.e., PAL, FASIR, GIMMS, and LTDR) under different corrections and processing schemes. Since NDVI datasets are used to evaluate carbon gains, differences among them may affect nations’ carbon budgets in meeting international targets (such as the Kyoto Protocol). This study addresses the consistency across AVHRR NDVI datasets in the Iberian Peninsula (Spain and Portugal) by evaluating whether their 1982–1999 NDVI trends show similar spatial patterns. Significant trends were calculated with the seasonal Mann-Kendall trend test and their spatial consistency with partial Mantel tests. Over 23% of the Peninsula (N, E, and central mountain ranges) showed positive and significant NDVI trends across the four datasets and an additional 18% across three datasets. In 20% of Iberia (SW quadrant), the four datasets exhibited an absence of significant trends and an additional 22% across three datasets. Significant NDVI decreases were scarce (croplands in the Guadalquivir and Segura basins, La Mancha plains, and Valencia). Spatial consistency of significant trends across at least three datasets was observed in 83% of the Peninsula, but it decreased to 47% when comparing across the four datasets. FASIR, PAL, and LTDR were the most spatially similar datasets, while GIMMS was the most different. The different performance of each AVHRR dataset to detect significant NDVI trends (e.g., LTDR detected greater significant trends (both positive and negative) and in 32% more pixels than GIMMS) has great implications to evaluate carbon budgets. The lack of spatial consistency across NDVI datasets derived from the same AVHRR sensor archive, makes it advisable to evaluate carbon gains trends using several satellite datasets and, whether possible, independent/additional data sources to contrast. PMID:22205868

  9. Probabilistic approach to cloud and snow detection on AVHRR imagery

    NASA Astrophysics Data System (ADS)

    Musial, J. P.; Hüsler, F.; Sütterlin, M.; Neuhaus, C.; Wunderle, S.

    2013-09-01

    The derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. The information about a confidence level of provided physical quantities is required to construct an error budget of higher level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data the common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher level products and may alter their usability. Within this scope a novel Probabilistic Cloud Mask (PCM) algorithm suited for the 1×1 km Advanced Very High Resolution Radiometer (AVHRR) data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clear-sky/snow conditions. As opposed to the majority of available techniques which are usually based on a decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve the probability estimates from the pre-computed Look Up Tables (LUTs). Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of thresholds. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the Invariant Coordinate System (ICS) transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the PPSv2012 and MOD35 collection 6 cloud masks, SYNOP weather

  10. Interannual Variations in Global Vegetation Phenology Derived from a Long Term AVHRR and MODIS Data Record

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Friedl, M. A.; Yu, Y.

    2013-12-01

    Land surface phenology metrics are widely retrieved from satellite observations at regional and global scales, and have been shown to be valuable for monitoring terrestrial ecosystem dynamics in response to extreme climate events and predicting biological responses to future climate scenarios. While the response of spring vegetation greenup to climate warming at mid-to-high latitudes is well-documented, understanding of diverse phenological responses to climate change over entire growing cycles and at broad geographic scales is incomplete. Many studies assume that the timing of individual phenological indicators in responses to climate forcing is independent of phenological events that occur at other times during the growing season. In this paper we use a different strategy. Specifically, we hypothesize that integrating sequences of key phenological indicators across growing seasons provides a more effective way to capture long-term variation in phenology in response to climate change. To explore this hypothesis we use global land surface phenology metrics derived from the Version 3 Long Term Vegetation Index Products from Multiple Satellite Data Records data set to examine interannual variations and trends in global land surface phenology from 1982-2010. Using daily enhanced vegetation index (EVI) data at a spatial resolution of 0.05 degrees, we model the phenological trajectory for each individual pixel using piecewise logistic models. The modeled trajectories were then used to detect phenological indicators including the onset of greenness increase, the onset of greenness maximum, the onset of greenness decrease, the onset of greenness minimum, and the growing season length, among others at global scale. The quality of land surface phenology detection for individual pixels was calculated based on metrics that characterize the EVI quality and model fits in annual time series at each pixel. Phenological indicators characterized as having good quality were then

  11. Improved SST estimates for AVHRR from ATSR data through a neural network approach

    SciTech Connect

    Arulmani, C.; Gurney, R.J.

    1997-08-01

    Many applications such as weather forecasting, oceanography and to determine the possible climate change need frequent data such as Sea Surface Temperature (SST) with wider spatial coverage and reliable accurate estimates. Even though the sampling requirements for SST`s can be met from Advanced Very High Resolution Radiometer (AVHRR) data, the accuracy required from these SSTs remains a challenge. The Along Track Scanning Radiometer (ATSR) retrieved SST`s offer better estimates than the AVHRR Multichannel Sea Surface Temperature (MCSST) algorithm, but the swath width of the ATSR is 512 km and the repetition cycle is approximately 3 days. In this study an attempt has been made to generate a new SST retrieval model for AVHRR using the SST`s retrieved from ATSR data. A multilayer neural network approach is employed to generate the model parameters. The new approach for the retrieval of SST for AVHRR data using the neural network yields the residual error within {plus_minus} 0.24{degrees}C when compared with the ATSR derived SSTs.

  12. Sea ice motions in the Central Arctic pack ice as inferred from AVHRR imagery

    NASA Technical Reports Server (NTRS)

    Emery, William; Maslanik, James; Fowler, Charles

    1995-01-01

    Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is currently limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoys data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Principal objectives of this project were to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions. Each of these main objectives was addressed. We conclude that AVHRR data, particularly when blended with other available observations, provide a valuable data set for studying sea ice processes. In a follow-on project, we are now extending this work to cover larger areas and to address science questions in more detail.

  13. Ranching in the Amazon basin - Large-scale changes observed by AVHRR

    NASA Technical Reports Server (NTRS)

    Malingreau, J. P.; Tucker, C. J.

    1990-01-01

    The contribution that AVHRR data can make to resolving the controversy about the deforestation of the Amazon region is discussed. The most significant types of information which such data can supply are pointed out. A color composite is shown and discussed, showing how it points out areas of deforestation.

  14. Novel algorithm for sea water quality monitoring by NOAA-AVHRR optical channels

    NASA Astrophysics Data System (ADS)

    Carla, Roberto; Maccioni, Andrea

    2000-12-01

    Many techniques have ben developed for the assessment and monitoring of sea suspended matter (SSM) by the two optical channels of the NOAA-AVHRR. However, they are useful only for cloudless conditions. In this work a new algorithm is proposed, which is based on the two AVHRR optical channels revealing SSM patterns also in hazy conditions or under thin clouds. It combines two indexes derived from the AVHRR optical bands in order to account for the effect of the atmosphere on albedo and moreover on the sea spatial patterns. A criterion based on the statistical comparison of the two indexes discriminates between clear areas and pixels belonging to one of two different classes of suspended sediments. The performance of the proposed algorithm has been tested on a set of NOAA-AVHRR imagery of the Adriatic sea acquired in the winter and summer 1997-98. The results showed spatial patterns steadily varying in time, which are recognized as inorganic sediments or chlorophyll.

  15. AVHRR-Based Polar Pathfinder Products: Evaluation, Enhancement, and Transition to MODIS

    NASA Technical Reports Server (NTRS)

    Fowler, Charles; Maslanik, James; Stone, Robert; Stroeve, Julienne; Emery, William

    2001-01-01

    The AVHRR-Based Polar Pathfinder (APP) products include calibrated AVHRR channel data, surface temperatures, albedo, satellite scan and solar geometries, and a cloud mask composited into twice- per-day images, and daily averaged fields of sea ice motion, for regions poleward of 50 deg. latitude. Our goals under this grant, in general, are four-fold: 1. To quantify the APP accuracy and sources of error by comparing Pathfinder products with field measurements. 2. To determine the consistency of mean fields and trends in comparison with longer time series of available station data and forecast model output. 3. To investigate the consistency of the products between the different AVHRR instruments over the 1982-present period of the NOAA program. 4. To compare an annual cycle of the AVHRR Pathfinder products with MODIS to establish a baseline for extending Pathfinder-type products into the new ESE period. Year One tasks include intercomparisons of the Pathfinder products with field measurements, testing of algorithm assumptions, collection of field data, and further validation and possible improvement of the multi-sensor ice motion fields. Achievements for these tasks are summarized below.

  16. Introducing Real-Time AVHRR-APT Satellite Imagery in the Classroom Environment

    ERIC Educational Resources Information Center

    Moxey, Lucas; Tucker, Compton; Sloan, Jim; Chadwick, John

    2004-01-01

    A low-cost (US$350) satellite receiving station was assembled and operated within a classroom environment in Gainesville (Florida) on October 2001 for acquiring satellite data directly from the Advanced Very High Resolution Radiometer (AVHRR) satellites. The simplicity of the satellite signal makes this source of real-time satellite data readily…

  17. Snow and Ice Applications of AVHRR in Polar Regions: Report of a Workshop

    NASA Technical Reports Server (NTRS)

    Steffen, K.; Bindschadler, R.; Casassa, G.; Comiso, J.; Eppler, D.; Fetterer, F.; Hawkins, J.; Key, J.; Rothrock, D.; Thomas, R.; Weaver, R.; Welch, R.

    1993-01-01

    The third symposium on Remote Sensing of Snow and Ice, organized by the International Glaciological Society, took place in Boulder, Colorado, 17-22 May 1992. As part of this meeting a total of 21 papers was presented on snow and ice applications of Advanced Very High Resolution Radiometer (AVHRR) satellite data in polar regions. Also during this meeting a NASA sponsored Workshop was held to review the status of polar surface measurements from AVHRR. In the following we have summarized the ideas and recommendations from the workshop, and the conclusions of relevant papers given during the regular symposium sessions. The seven topics discussed include cloud masking, ice surface temperature, narrow-band albedo, ice concentration, lead statistics, sea-ice motion and ice-sheet studies with specifics on applications, algorithms and accuracy, following recommendations for future improvements. In general, we can affirm the strong potential of AVHRR for studying sea ice and snow covered surfaces, and we highly recommend this satellite data set for long-term monitoring of polar process studies. However, progress is needed to reduce the uncertainty of the retrieved parameters for all of the above mentioned topics to make this data set useful for direct climate applications such as heat balance studies and others. Further, the acquisition and processing of polar AVHRR data must become better coordinated between receiving stations, data centers and funding agencies to guarantee a long-term commitment to the collection and distribution of high quality data.

  18. Neural Networks as a Tool for Constructing Continuous NDVI Time Series from AVHRR and MODIS

    NASA Technical Reports Server (NTRS)

    Brown, Molly E.; Lary, David J.; Vrieling, Anton; Stathakis, Demetris; Mussa, Hamse

    2008-01-01

    The long term Advanced Very High Resolution Radiometer-Normalized Difference Vegetation Index (AVHRR-NDVI) record provides a critical historical perspective on vegetation dynamics necessary for global change research. Despite the proliferation of new sources of global, moderate resolution vegetation datasets, the remote sensing community is still struggling to create datasets derived from multiple sensors that allow the simultaneous use of spectral vegetation for time series analysis. To overcome the non-stationary aspect of NDVI, we use an artificial neural network (ANN) to map the NDVI indices from AVHRR to those from MODIS using atmospheric, surface type and sensor-specific inputs to account for the differences between the sensors. The NDVI dynamics and range of MODIS NDVI data at one degree is matched and extended through the AVHRR record. Four years of overlap between the two sensors is used to train a neural network to remove atmospheric and sensor specific effects on the AVHRR NDVI. In this paper, we present the resulting continuous dataset, its relationship to MODIS data, and a validation of the product.

  19. Detection and mapping vegetation cover based on the Spectral Angle Mapper algorithm using NOAA AVHRR data

    NASA Astrophysics Data System (ADS)

    Yagoub, Houria; Belbachir, Ahmed Hafid; Benabadji, Noureddine

    2014-06-01

    Satellite data, taken from the National Oceanic and Atmospheric Administration (NOAA) have been proposed and used for the detection and the cartography of vegetation cover in North Africa. The data used were acquired at the Analysis and Application of Radiation Laboratory (LAAR) from the Advanced Very High Resolution Radiometer (AVHRR) sensor of 1 km spatial resolution. The Spectral Angle Mapper Algorithm (SAM) is used for the classification of many studies using high resolution satellite data. In the present paper, we propose to apply the SAM algorithm to the moderate resolution of the NOAA AVHRR sensor data for classifying the vegetation cover. This study allows also exploiting other classification methods for the low resolution. First, the normalized difference vegetation index (NDVI) is extracted from two channels 1 and 2 of the AVHRR sensor. In order to obtain an initial density representation of vegetal formation distribution, a methodology, based on the combination between the threshold method and the decision tree, is used. This combination is carried out due to the lack of accurate data related to the thresholds that delimit each class. In a second time, and based on spectral behavior, a vegetation cover map is developed using SAM algorithm. Finally, with the use of low resolution satellite images (NOAA AVHRR) and with only two channels, it is possible to identify the most dominant species in North Africa such as: forests of the Liege oaks, other forests, cereal's cultivation, steppes and bar soil.

  20. Determining the rate of forest conversion in Mato Grosso, Brazil, using Landsat MSS and AVHRR data

    NASA Technical Reports Server (NTRS)

    Nelson, Ross; Horning, Ned; Stone, Thomas A.

    1987-01-01

    AVHRR-LAC thermal data and Landsat MSS and TM spectral data were used to estimate the rate of forest clearing in Mato Grosso, Brazil, between 1981 and 1984. The Brazilian state was stratified into forest and nonforest. A list sampling procedure was used in the forest stratum to select Landsat MSS scenes for processing based on estimates of fire activity in the scenes. Fire activity in 1984 was estimated using AVHRR-LAC thermal data. State-wide estimates of forest conversion indicate that between 1981 and 1984, 353,966 ha + or - 77,000 ha (0.4 percent of the state area) were converted per year. No evidence of reforestation was found in this digital sample. The relationship between forest clearing rate (based on MSS-TM analysis) and fire activity (estimated using AVHRR data) was noisy (R-squared = 0.41). The results suggest that AVHRR data may be put to better use as a stratification tool than as a subsidiary variable in list sampling.

  1. Assessing phenological change in China from 1982 to 2006 using AVHRR imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Long term trends in vegetation phenology indicate ecosystem change due to the combined impacts of human activities and climate. In this study, we used 1982 to 2006 Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (AVHRR NDVI) imagery across China and the TIMESAT progra...

  2. A spatial regression procedure for evaluating the relationship between AVHRR-NDVI and climate in the northern Great Plains

    USGS Publications Warehouse

    Ji, Lei; Peters, Albert J.

    2004-01-01

    The relationship between vegetation and climate in the grassland and cropland of the northern US Great Plains was investigated with Normalized Difference Vegetation Index (NDVI) (1989–1993) images derived from the Advanced Very High Resolution Radiometer (AVHRR), and climate data from automated weather stations. The relationship was quantified using a spatial regression technique that adjusts for spatial autocorrelation inherent in these data. Conventional regression techniques used frequently in previous studies are not adequate, because they are based on the assumption of independent observations. Six climate variables during the growing season; precipitation, potential evapotranspiration, daily maximum and minimum air temperature, soil temperature, solar irradiation were regressed on NDVI derived from a 10-km weather station buffer. The regression model identified precipitation and potential evapotranspiration as the most significant climatic variables, indicating that the water balance is the most important factor controlling vegetation condition at an annual timescale. The model indicates that 46% and 24% of variation in NDVI is accounted for by climate in grassland and cropland, respectively, indicating that grassland vegetation has a more pronounced response to climate variation than cropland. Other factors contributing to NDVI variation include environmental factors (soil, groundwater and terrain), human manipulation of crops, and sensor variation.

  3. Mapping Landscape Phenology Preference of Yellow-billed Cuckoo with AVHRR data

    NASA Astrophysics Data System (ADS)

    Wallace, C.; Villarreal, M. L.; Van Riper, C., III

    2011-12-01

    The yellow-billed cuckoo (Coccycus americanus occidentalis) is a neo-tropical migrant bird that travels north from South America into the southwestern United States during the summer to nest. In Arizona, favored riparian forest and woodland nesting habitat has declined in recent decades, due primarily to human activities and the prolonged drought conditions. As a result, western yellow-billed cuckoos have been petitioned for possible listing under the Endangered Species Act. In this study, we map yellow-billed cuckoo habitat in the state of Arizona using the temporal greenness dynamics of the landscape, or the landscape phenology. Landscape phenometrics were derived from Advanced Very High Resolution Radiometer (AVHRR) satellite Normalized Difference Vegetation Index (NDVI) composite data using Fourier harmonic analysis. Applying Fourier analysis to the waveform composed of the 26 annual composite NDVI values produces phenometrics related to the overall vegetation amount, variability and timing. Field data on Cuckoo presence were obtained from 1998 surveys conducted by Northern Arizona University (NAU), the Arizona Game and Fish Department (AGFD) and the U.S. Geological Survey (USGS). To focus the research within probable landscapes, an AGFD vegetation map (derived from the Arizona GAP program) was used to extract polygons of riparian vegetation and cottonwood-willow riparian vegetation. To create the models, we coupled the satellite phenometrics with field data of cuckoo presence or absence and with points sampling the entirety of mapped riparian and cottonwood-willow vegetation types. Statistical tests reveal that locations with cuckoos present are landscapes with greenness that is significantly more variable and that peaks significantly later than locations in average riparian vegetation, average cottonwood-willow vegetation, or with cuckoos absent. Interestingly, the mean peak greenness date of July 3 for survey locations with cuckoos present coincides with the

  4. A regional scale soil mapping approach using integrated AVHRR and DEM data

    NASA Astrophysics Data System (ADS)

    Dobos, Endre; Montanarella, Luca; Nègre, Thierry; Micheli, Erika

    There is an increasing need for reasonably accurate small-scale soil databases. The compilation of a continental or global-scale soil database requires a lot of spatially and thematically accurate soil data. The aim of this study was to test a method for small-scale soil mapping in Italy using Advanced Very High Resolution Radiometer (AVHRR) and digital elevation data. This method was employed in an earlier study in Hungary for a much smaller area and a significantly different soil-forming environment. An integrated, 45-layer AVHRR-terrain database was used for the study, including a digital elevation model (DEM), slope, curvature, aspect, potential drainage density, and the five bands of AVHRR data for eight different dates. The data were processed using the Discriminant Analysis Feature Extraction (DAFE) function, which is based on a canonical analysis procedure. Two types of images (basic and transformed) were classified using the maximum likelihood classifier. Two training sets were chosen that have identical geographic coverage, but differ in the level of soil classification. One set was based on the soil units (SU) of the FAO-revised legend, while the other set represented major soil groupings (MSG). The best 10, 15, 20, 25, 30, 35, 40 and 45 layers were selected using the Bhattachryya feature selection method and were then classified. The results of the different sets were compared. The performance of the purely AVHRR and purely terrain-data-based images, respectively, were also interpreted. The results indicate that the terrain descriptors alone are not sufficient for soil classification. However, the feature selection algorithms always selected the DEM and its derivatives among the first ones, highlighting their importance for soil-landscape characterization. When using AVHRR data alone, test class performances of 49.8 percent (MSG) and 48.6 percent (SU) were achieved. Integration of terrain data into the AVHRR database produced relatively small

  5. Ice surface temperatures: seasonal cycle and daily variability from in-situ and satellite observations

    NASA Astrophysics Data System (ADS)

    Madsen, Kristine S.; Dybkjær, Gorm; Høyer, Jacob L.; Nielsen-Englyst, Pia; Rasmussen, Till A. S.; Tonboe, Rasmus T.

    2016-04-01

    Surface temperature is an important parameter for understanding the climate system, including the Polar Regions. Yet, in-situ temperature measurements over ice- and snow covered regions are sparse and unevenly distributed, and atmospheric circulation models estimating surface temperature may have large biases. To change this picture, we will analyse the seasonal cycle and daily variability of in-situ and satellite observations, and give an example of how to utilize the data in a sea ice model. We have compiled a data set of in-situ surface and 2 m air temperature observations over land ice, snow, sea ice, and from the marginal ice zone. 2523 time series of varying length from 14 data providers, with a total of more than 13 million observations, have been quality controlled and gathered in a uniform format. An overview of this data set will be presented. In addition, IST satellite observations have been processed from the Metop/AVHRR sensor and a merged analysis product has been constructed based upon the Metop/AVHRR, IASI and Modis IST observations. The satellite and in-situ observations of IST are analysed in parallel, to characterize the IST variability on diurnal and seasonal scales and its spatial patterns. The in-situ data are used to estimate sampling effects within the satellite observations and the good coverage of the satellite observations are used to complete the geographical variability. As an example of the application of satellite IST data, results will be shown from a coupled HYCOM-CICE ocean and sea ice model run, where the IST products have been ingested. The impact of using IST in models will be assessed. This work is a part of the EUSTACE project under Horizon 2020, where the ice surface temperatures form an important piece of the puzzle of creating an observationally based record of surface temperatures for all corners of the Earth, and of the ESA GlobTemperature project which aims at applying surface temperatures in models in order to

  6. Land Cover Analysis of Temperate Asia

    NASA Technical Reports Server (NTRS)

    Justice, Chris

    1998-01-01

    Satellite data from the advanced very high resolution radiometer (AVHRR) instrument were used to produce a general land cover distribution of temperate Asia (referred to hence as Central Asia) from 1982, starting with the NOAA-7 satellite, and continuing through 1991, ending with the NOAA-11 satellite. Emphasis was placed upon delineating the and and semi-arid zones of Central Asia (largely Mongolia and adjacent areas), mapping broad categories of aggregated land cover, and upon studying photosynthetic capacity increases in Central Asia from 1982 to 1991.

  7. Environmental remote sensing using the advanced very high resolution radiometer (AVHRR). (Latest citations from the NTIS database). Published Search

    SciTech Connect

    Not Available

    1993-07-01

    The bibliography contains citations concerning the acquisition, processing, and applications of the Advanced Very High Resolution Radiometer (AVHRR) used on polar satellites operated by the National Oceanic and Atmospheric Administration (NOAA) for the Department of Commerce. AVHRR provides global visible and infrared imagery. The cited reports contain information on calibration, registration, and image processing of AVHRR data. Included are reports on AHVRR use in the study of aerosols, atmospheric circulation, agriculture, forest fires, deforestation, sun glint, sedimentation, cloud classification, sea ice, snowmelts, ocean productivity, sea surface temperatures, and vegetation. (Contains a minimum of 120 citations and includes a subject term index and title list.)

  8. Using NOAA/AVHRR based remote sensing data and PCR method for estimation of Aus rice yield in Bangladesh

    NASA Astrophysics Data System (ADS)

    Nizamuddin, Mohammad; Akhand, Kawsar; Roytman, Leonid; Kogan, Felix; Goldberg, Mitch

    2015-06-01

    Rice is a dominant food crop of Bangladesh accounting about 75 percent of agricultural land use for rice cultivation and currently Bangladesh is the world's fourth largest rice producing country. Rice provides about two-third of total calorie supply and about one-half of the agricultural GDP and one-sixth of the national income in Bangladesh. Aus is one of the main rice varieties in Bangladesh. Crop production, especially rice, the main food staple, is the most susceptible to climate change and variability. Any change in climate will, thus, increase uncertainty regarding rice production as climate is major cause year-to-year variability in rice productivity. This paper shows the application of remote sensing data for estimating Aus rice yield in Bangladesh using official statistics of rice yield with real time acquired satellite data from Advanced Very High Resolution Radiometer (AVHRR) sensor and Principal Component Regression (PCR) method was used to construct a model. The simulated result was compared with official agricultural statistics showing that the error of estimation of Aus rice yield was less than 10%. Remote sensing, therefore, is a valuable tool for estimating crop yields well in advance of harvest, and at a low cost.

  9. Spaceborne microwave remote sensing of seasonal freeze-thaw processes in theterrestrial high l atitudes : relationships with land-atmosphere CO2 exchange

    NASA Technical Reports Server (NTRS)

    McDonald, Kyle C.; Kimball, John S.; Zhao, Maosheng; Njoku, Eni; Zimmermann, Reiner; Running, Steven W.

    2004-01-01

    Landscape transitions between seasonally frozen and thawed conditions occur each year over roughly 50 million square kilometers of Earth's Northern Hemisphere. These relatively abrupt transitions represent the closest analog to a biospheric and hydrologic on/off switch existing in nature, affecting surface meteorological conditions, ecological trace gas dynamics, energy exchange and hydrologic activity profoundly. We utilize time series satellite-borne microwave remote sensing measurements from the Special Sensor Microwave Imager (SSM/I) to examine spatial and temporal variability in seasonal freeze/thaw cycles for the pan-Arctic basin and Alaska. Regional measurements of spring thaw timing are derived using daily brightness temperature measurements from the 19 GHz, horizontally polarized channel, separately for overpasses with 6 AM and 6 PM equatorial crossing times. Spatial and temporal patterns in regional freeze/thaw dynamics show distinct differences between North America and Eurasia, and boreal forest and Arctic tundra biomes. Annual anomalies in the timing of thawing in spring also correspond closely to seasonal atmospheric CO2 concentration anomalies derived from NOAA CMDL arctic and subarctic monitoring stations. Classification differences between AM and PM overpass data average approximately 5 days for the region, though both appear to be effective surrogates for monitoring annual growing seasons at high latitudes.

  10. Spaceborne Microwave Remote Sensing of Seasonal Freeze-Thaw Processes in the Terrestrial High Latitudes: Relationships with Land-Atmosphere CO2 exchange

    NASA Technical Reports Server (NTRS)

    McDonald, Kyle C.; Kimball, John S.; Zhao, Maosheng; Njoku, Eni; Zimmermann, Reiner; Running, Steven W.

    2004-01-01

    Landscape transitions between seasonally frozen and thawed conditions occur each year over roughly 50 million square kilometers of Earth's Northern Hemisphere. These relatively abrupt transitions represent the closest analog to a biospheric and hydrologic on/off switch existing in nature, affecting surface meteorological conditions, ecological trace gas dynamics, energy exchange and hydrologic activity profoundly. We utilize time series satellite-borne microwave remote sensing measurements from the Special Sensor Microwave Imager (SSM/I) to examine spatial and temporal variability in seasonal freeze/thaw cycles for the pan-Arctic basin and Alaska. Regional measurements of spring thaw timing are derived using daily brightness temperature measurements from the 19 GHz, horizontally polarized channel, separately for overpasses with 6 AM and 6 PM equatorial crossing times. Spatial and temporal patterns in regional freeze/thaw dynamics show distinct differences between North America and Eurasia, and boreal forest and Arctic tundra biomes. Annual anomalies in the timing of thawing in spring also correspond closely to seasonal atmospheric CO2 concentration anomalies derived from NOAA CMDL arctic and subarctic monitoring stations. Classification differences between AM and PM overpass data average approximately 5 days for the region, though both appear to be effective surrogates for monitoring annual growing seasons at high latitudes.

  11. Estimating seasonal changes of land cover, surface wetness and latent heat flux of wet polygonal tundra (Samoylov Island, Lena-Delta, Siberia) with high-resolution aerial and hyperspectral CHRIS Proba satellite imagery

    NASA Astrophysics Data System (ADS)

    Muster, S.; Langer, M.; Boike, J.

    2009-12-01

    Vegetation cover, land cover and surface wetness are few of the many factors exerting control on the partitioning of energy to latent, sensible and ground heat flux. Spatial estimates of these factors can be inferred from remote sensing data. The fractionated polygonal tundra landscape of Samoylov Island of wet and dry surfaces induces strong spatial variations of resistance to evapotranspiration. The development of low-centered ice-wedge polygons results in a prominent microrelief that is the most important factor for small-scale differences in vegetation type and near surface soil moisture. Depressed polygon centers alternate with elevated polygon rims with elevation differences of up to 0.5 m over a few meters distance. In the depressed polygon centers, drainage is strongly impeded due to the underlying permafrost resulting in water-saturated soils or small ponds. A process-based understanding of the surface energy balance, however, needs to consider both the temporal and the spatial variations of the surface. In the course of the summer season, the surface wetness changes significantly since the water table falls about 5 cm below the surface. This change in surface wetness is likely to be associated with changing evapotranspiration rates. We consider the effect of seasonal changes in land cover, vegetation cover and surface wetness on latent heat flux by investigating a time-series of high-resolution aerial and hyperspectral satellite imagery and comparing them to ground-based measurements of near-surface soil moisture and latent heat flux. Two sets of aerial images from August 15 and September 11, 2008 in the VNIR provide detailed information of the polygonal landscape with a resolution of 0.3m. CHRIS Proba imagery provides hyperspectral data with 18 spectral bands in the VNIR range (400 - 1050 nm) and a resolution of 17 m. Acquisition dates are June 21, July 23 and September 10, 2008. Daily point-based measurements of near-surface soil moisture and latent

  12. Wyoming greater sage-grouse habitat prioritization: a collection of multi-scale seasonal models and geographic information systems land management tools

    USGS Publications Warehouse

    O'Donnell, Michael S.; Aldridge, Cameron L.; Doherty, Kevin E.; Fedy, Bradley C.

    2015-01-01

    We deliver all products described herein as online geographic information system data for visualization and downloading. We outline the data properties for each model and their data inputs, describe the process of selecting appropriate data products for multifarious applications, describe all data products and software, provide newly derived model composites, and discuss how land managers may use the models to inform future sage-grouse studies and potentially refine conservation efforts. The models, software tools, and associated opportunities for novel applications of these products should provide a suite of additional, but not exclusive, tools for assessing Wyoming Greater Sage-grouse habitats, which land managers, conservationists, and scientists can apply to myriad applications.

  13. An approach for using AVHRR data to monitor U.S. great plains grasslands

    USGS Publications Warehouse

    Reed, B.C.; Loveland, T.R.; Tieszen, L.L.

    1996-01-01

    Environmental monitoring requires regular observations regarding the status of the landscape- The concept behind most monitoring efforts using satellite data involve deriving normalized difference vegetation index (NDVI) values or accumulating the NDVI over a specified time period. These efforts attempt to estimate the continuous growth of green biomass by using continuous additions of NDVI as a surrogate measure. To build upon this concept, this study proposes three refinements; 1) use an objective definition of the current growing season to adjust the time window during which the NDVI is accumulated, 2) accumulate only the NDVI values which are affected by green vegetation, and 3) base monitoring units upon land cover type. These refinements improve the sensitivity of detecting interannual vegetation variability, reduce the need for extensive and detailed knowledge of ground conditions and crop calendars, provide a framework in which several types of monitoring can take place over diverse land cover types, and provide an objective time frame during which monitoring takes place.

  14. The impact of spectral emissivity on the measurement of land surface temperature from a satellite

    NASA Technical Reports Server (NTRS)

    Becker, F.

    1987-01-01

    The effect of emissivity on the measurement of land surface (LS) temperature from satellite radiances using the split-window method is investigated. Formulas are derived to relate the LS temperatures to two brightness temperatures measured from space in the AVHRR 4 and AVHRR 5 channels, and their accuracies are discussed. Results indicate that to determine LS temperatures from a satellite, the spectral emissivity must be known to an accuracy on the order of 0.005 for the average and 0.0007 for the difference in order to obtain an error of the order of 0.5 K.

  15. The Calibration of AVHRR/3 Visible Dual Gain Using Meteosat-8 as a MODIS Calibration Transfer Medium

    NASA Technical Reports Server (NTRS)

    Avey, Lance; Garber, Donald; Nguyen, Louis; Minnis, Patrick

    2007-01-01

    This viewgraph presentation reviews the NOAA-17 AVHRR visible channels calibrated against MET-8/MODIS using dual gain regression methods. The topics include: 1) Motivation; 2) Methodology; 3) Dual Gain Regression Methods; 4) Examples of Regression methods; 5) AVHRR/3 Regression Strategy; 6) Cross-Calibration Method; 7) Spectral Response Functions; 8) MET8/NOAA-17; 9) Example of gain ratio adjustment; 10) Effect of mixed low/high count FOV; 11) Monitor dual gains over time; and 12) Conclusions

  16. A dynamically-coupled groundwater, land surface and regional climate model to predict seasonal watershed flow and groundwater response, FINAL LDRD REPORT.

    SciTech Connect

    Maxwell, R; Kollet, S; Chow, F; Granvold, P; Duan, Q

    2007-02-23

    This final report is organized in four sections. Section 1 is the project summary (below), Section 2 is a submitted manuscript that describes the offline, or spinup simulations in detail, Section 3 is also a submitted manuscript that describes the online, or fully-coupled simulations in detail and Section 3, which is report that describes work done via a subcontract with UC Berkeley. The goal of this project was to develop and apply a coupled regional climate, land-surface, groundwater flow model as a means to further understand important mass and energy couplings between regional climate, the land surface, and groundwater. The project involved coupling three distinct submodels that are traditionally used independently with abstracted and potentially oversimplified (inter-model) boundary conditions. This coupled model lead to (1) an improved understanding of the sensitivity and importance of coupled physical processes from the subsurface to the atmosphere; (2) a new tool for predicting hydrologic conditions (rainfall, temperature, snowfall, snowmelt, runoff, infiltration and groundwater flow) at the watershed scale over a range of timeframes; (3) a simulation of hydrologic response of a characteristic watershed that will provide insight into the certainty of hydrologic forecasting, dominance and sensitivity of groundwater dynamics on land-surface fluxes; and (4) a more realistic model representation of weather predictions, precipitation and temperature, at the regional scale. Regional climate models are typically used for the simulation of weather, precipitation and temperature behavior over 10-1000 km domains for weather or climate prediction purposes, and are typically driven by boundary conditions derived from global climate models (GCMs), observations or both. The land or ocean surface typically represents a bottom boundary condition of these models, where important mass (water) and energy fluxes are approximated. The viability and influence of these

  17. Automated cloud screening of AVHRR imagery using split-and-merge clustering

    NASA Technical Reports Server (NTRS)

    Gallaudet, Timothy C.; Simpson, James J.

    1991-01-01

    Previous methods to segment clouds from ocean in AVHRR imagery have shown varying degrees of success, with nighttime approaches being the most limited. An improved method of automatic image segmentation, the principal component transformation split-and-merge clustering (PCTSMC) algorithm, is presented and applied to cloud screening of both nighttime and daytime AVHRR data. The method combines spectral differencing, the principal component transformation, and split-and-merge clustering to sample objectively the natural classes in the data. This segmentation method is then augmented by supervised classification techniques to screen clouds from the imagery. Comparisons with other nighttime methods demonstrate its improved capability in this application. The sensitivity of the method to clustering parameters is presented; the results show that the method is insensitive to the split-and-merge thresholds.

  18. Comparison of TOMS and AVHRR volcanic ssh retrievals from the August 1992 eruption of Mt. Spurr

    USGS Publications Warehouse

    Krotkov, N.A.; Torres, O.; Seftor, C.; Krueger, A.J.; Kostinski, A.; Rose, William I., Jr.; Bluth, G.J.S.; Schneider, D.; Schaefer, S.J.

    1999-01-01

    On August 19, 1992, the Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA-12 and NASA's Total Ozone Mapping Spectrometer (TOMS) onboard the Nimbus-7 satellite simultaneously detected and mapped the ash cloud from the eruption of Mt. Spurr, Alaska. The spatial extent and geometry of the cloud derived from the two datasets are in good agreement and both AVHRR split window IR (11-12??m brightness temperature difference) and the TOMS UV Aerosol Index (0.34-0.38??m ultraviolet backscattering and absorption) methods give the same range of total cloud ash mass. Redundant methods for determination of ash masses in drifting volcanic clouds offer many advantages for potential application to the mitigation of aircraft hazards.

  19. Long Term Cloud Property Datasets From MODIS and AVHRR Using the CERES Cloud Algorithm

    NASA Technical Reports Server (NTRS)

    Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan; Hong, Gang; Bhatt, Rajendra

    2015-01-01

    Cloud properties play a critical role in climate change. Monitoring cloud properties over long time periods is needed to detect changes and to validate and constrain models. The Clouds and the Earth's Radiant Energy System (CERES) project has developed several cloud datasets from Aqua and Terra MODIS data to better interpret broadband radiation measurements and improve understanding of the role of clouds in the radiation budget. The algorithms applied to MODIS data have been adapted to utilize various combinations of channels on the Advanced Very High Resolution Radiometer (AVHRR) on the long-term time series of NOAA and MetOp satellites to provide a new cloud climate data record. These datasets can be useful for a variety of studies. This paper presents results of the MODIS and AVHRR analyses covering the period from 1980-2014. Validation and comparisons with other datasets are also given.

  20. REPETITIVE DIGITAL NOAA-AVHRR DATA FOR ALASKAN ENGINEERING AND SCIENTIFIC APPLICATIONS.

    USGS Publications Warehouse

    Christie, William M.; Pawlowski, Robert J.; Fleming, Michael D.

    1986-01-01

    Selected digitally enhanced NOAA - Advanced Very High Resolution Radiometer (AVHRR) images taken by the NOAA 6, 7, 8 and 9 Polar Orbiting Satellites demonstrate the capability and application of repetitive low-resolution satellite data to Alaska's engineering and science community. Selected cloud-free visible and thermal infrared images are enhanced to depict distinct oceanographic and geologic processes along Alaska's west coast and adjacent seas. Included are the advance of the Bering Sea ice field, transport of Yukon River sediment into Norton Sound, and monitoring of plume trajectories from the Mount Augustine volcanic eruptions. Presented illustrations are representative of the 94 scenes in a cooperative USGS EROS/NOAA Alaskan AVHRR Digital Archive. This paper will discuss the cooperative efforts in establishing the first year data set and identifying Alaskan applications.

  1. Comparison of the vegetation index computed from modis, AVHRR and ASTER data over Hokkaido, Japan BUHEAOSIEN

    NASA Astrophysics Data System (ADS)

    Tsuchiya, K.; Kaneko, M.

    An attempt is made to compare the vegetation index computed from the data of different spatial and spectral resolution, i.e. the data of MODIS (MODerate resolution Imaging Spectrometer), AVHRR (Advanced Very High Resolution Radiometer) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer). As the vegetation index the most widely used NDVI (Normalized Difference Vegetation Index) is selected. Since the index is computed from the ratio of the data of two bands the effects of atmosphere, temporal degradation of sensor sensitivity, viewing geometry, etc are eliminated to a certain extent. The spectral ranges and spatial resolution of each NDVI are as follows. MODIS-NDVI:0.62-0.70, 0.841-0.876μm 250m ; AVHRR-NDVI: 0.58-0.68, 0.82-0.87μm; 1.1km. ASTER- NDVI:0.63 -0.69, 0.76 -0.86 μm, 15m. The computation is made for the data of Hokkaido, Japan. In addition to NDVI, EVI (Enhanced Vegetation Index) and LAI (Leaf Area Index) are also computed for the data of MODIS. The result indicates that both MODIS-NDVI and AVHRR-NDVI show a good result, with MODIS-NDVI a little better result. Between NDVI and EVI computed from the data of MODIS, EVI shows a little better result for the study of phenological change of vegetation. MODIS-LAI is useful in distinguishing the vegetation in a wetland. Since the spatial resolution of ASTER is more than one order of magnitude higher than that of MODIS and AVHRR it is rather difficult to obtain a reasonable evaluation since it depends on the purpose of application. In the area with a complicated vegetation and topographical distribution it is found that ASTER-NDVI is very useful.

  2. Evaluation of Long-Term Calibrations of the AVHRR Visible Radiances

    NASA Technical Reports Server (NTRS)

    Rossow, William B.; Ferrier, Joseph

    2015-01-01

    Two systematic calibrations have been compiled for the visible radiances measured by the series of AVHRR instruments flown on the NOAA operational polar weather satellites: one by the International Satellite Cloud Climatology Project (ISCCP), anchored on NASA ER-2 underflights in the 1980s and early 1990s and covering the period 1981-2009, and one by the PATMOS-x project, anchored on comparisons to the MODIS instruments on the Aqua and Terra satellites in the 2000s and covering the period 1979-2010 (this result also includes calibration for the near-IR channels). Both methods have had to extend their anchor calibrations over a long series of instruments using different vicarious approaches, so a comparison provides an opportunity to evaluate how well this extension works by cross-checking the results at the anchor points. The basic result of this comparison is that for the ''afternoon'' series of AVHRRs, the calibrations agree to within their mutual uncertainties. However, this retrospective evaluation also shows that the representation of the time variations can be simplified. The ISCCP procedure had much more difficulty extending the calibration to the ''morning'' series of AVHRRs with the calibrations for NOAA-15 and NOAA-17 exceeding the estimated uncertainties. Given the general agreement, a new calibration for all AVHRR visible radiances (except TIROS-N, NOAA-6, NOAA-19, and MetOp-A) is proposed that is based on the average of the best linear fits to the two time records. The estimated uncertainty of these calibrations is 63% absolute (scaled radiance units).

  3. An improved method to derive surface albedo from narrowband AVHRR satellite data : narrowband to broadband conversion.

    SciTech Connect

    Song, J.; Gao, W.; Environmental Research; Northern Illinois Univ.

    1999-02-01

    A method was investigated to estimate broadband surface shortwave albedo from the narrowband reflectances obtained by the Advanced Very High Resolution Radiometers (AVHRRs) on board the polar orbiting satellites. Field experiments were conducted to measure simultaneously multispectral narrowband reflectances and broadband albedo over various vegetation and soil surfaces. These data were combined to examine the behavior of narrowband-to-broadband (NTB) conversion factors for different surfaces. Many previous studies have used constant NTB conversion factors for the AVHRR data. The results from this investigation indicate that the optimal NTB conversion factors for AVHRR channels 1 and 2 have a strong dependence on the amount of green vegetation within the field of view. Two conversion factors, f1 and f2, were established to quantify, respectively, (1) the relationship between the reflectance in the narrow red wave band and the total reflectance within the whole visible subregion (0.3-0.685 m) and (2) the relationship between the reflectance in the narrow near-infrared wave band and the total reflectance within the whole near-infrared subregion (0.685-2.8 m). Values of f1 and f2, calculated from field data, correlated well with the normalized difference vegetation index (NDVI), largely because of the unique characteristics of light absorption and scattering within the red and near-infrared wave bands by green leaves. The f1-NDVI and f2-NDVI relationships developed from this study were used to infer empirical coefficients needed to estimate surface albedo from AVHRR data. The surface albedo values calculated by the new method agreed with ground-based measurements within a root-mean-square error of 0.02, which is better than other methods that use constant empirical coefficients. Testing with albedo measurements made by unmanned aerospace vehicles during a field campaign also indicates that the new method provides an improved estimate of surface albedo.

  4. Assessing vegetation dynamics impacted by climate change in the southwestern karst region of China with AVHRR NDVI and AVHRR NPP time-series

    NASA Astrophysics Data System (ADS)

    Wang, J.; Meng, J. J.; Cai, Y. L.

    2008-05-01

    The relationship between climate change and vegetation dynamics in the southwestern karst region of China has been identified by recent studies. Based on previous researches and AVHRR (Advanced Very High Resolution Radiometer) GIMMS (Global Inventory Monitoring and Modeling Studies) NDVI (Normalized Difference Vegetation Index) (1982 2003) and AVHRR GloPEM (Global Production Efficiency Model) NPP (Net Primary Production) (1981 2000) datasets, vegetation dynamics impacted by climate change in the southwestern karst region of China were assessed. The results show that: (1) since the early 1980s, both vegetation cover density and net primary production have insignificant ascending tendencies. However, the inter-annual variation rates of vegetation indexes have apparent spatial differentiations; (2) the correlation coefficients between the inter-annual variations of vegetation indexes and the inter-annual variations of climate factors vary geographically; (3) as indicated by NDVI and NPP, various vegetation types have different responses to climate change, and the annual mean temperature variation has more significant impact on vegetation dynamics than the annual precipitation variation in the study area; (4) distribution laws of correlation coefficients between the inter-annual variations of vegetation indexes and the inter-annual variations of climate factors in different climate conditions are apparent. All these findings will enrich our knowledge of the natural forces which impact the stability of the karst ecosystems and provide scientific basis for the management of the karst ecosystems.

  5. Seasonal dynamics of the land surface energy balance of a boreal forest-peatland landscape affected by degrading permafrost in the Taiga Plains, Canada

    NASA Astrophysics Data System (ADS)

    Helbig, M.; Wischnewski, K.; Chasmer, L.; Quinton, W. L.; Kljun, N.; Detto, M.; Sonnentag, O.

    2014-12-01

    Northern boreal ecosystems along the southern limit of permafrost comprise a mosaic of forests with permafrost, and permafrost-free peatland and lake ecosystems. The proportion of permafrost-free areas has rapidly increased over the last decades due to increasingly warmer air temperatures. This change in land cover causes changes in vegetation composition and structure affecting land surface characteristics such as albedo and surface roughness with important implications for the land surface energy balance and thus regional climate. For example, a decrease in sensible heat flux potentially cools the atmosphere and thus constitutes a negative feedback to the climate system. Changes in latent heat fluxes alter regional water vapour dynamics and thus may affect precipitation patterns. To better understand the land surface energy balance under the influence of degrading permafrost, we measured sensible and latent heat fluxes with two eddy covariance systems, one at 15 m and one at 2 m above the ground surface, along with net radiation and soil heat flux at Scotty Creek, a watershed in the discontinuous permafrost zone in the southern part of the Northwest Territories, Canada. The flux footprint of the 15 m-eddy covariance system covers an area equally covered by black spruce forests and permafrost-free, treeless peatlands whereas the flux footprint of the adjacent 2 m-eddy covariance system covers a single bog within the footprint of the 15 m system. Peak sensible heat fluxes at the bog were up to 200 W m-2 smaller than the landscape-scale fluxes between April and July 2014. During the snow free period, peak latent heat fluxes at the wet bog were about 50 W m-2 higher than the landscape-scale fluxes. Albedo of the forest was generally smaller compared to the bog except for the immediate post-melt period when the bog was affected by widespread surface flooding. This difference in albedo leads to higher net radiation at the forest site, particularly during the snow cover

  6. Linear and nonlinear trending and prediction for AVHRR time series data

    NASA Technical Reports Server (NTRS)

    Smid, J.; Volf, P.; Slama, M.; Palus, M.

    1995-01-01

    The variability of AVHRR calibration coefficient in time was analyzed using algorithms of linear and non-linear time series analysis. Specifically we have used the spline trend modeling, autoregressive process analysis, incremental neural network learning algorithm and redundancy functional testing. The analysis performed on available AVHRR data sets revealed that (1) the calibration data have nonlinear dependencies, (2) the calibration data depend strongly on the target temperature, (3) both calibration coefficients and the temperature time series can be modeled, in the first approximation, as autonomous dynamical systems, (4) the high frequency residuals of the analyzed data sets can be best modeled as an autoregressive process of the 10th degree. We have dealt with a nonlinear identification problem and the problem of noise filtering (data smoothing). The system identification and filtering are significant problems for AVHRR data sets. The algorithms outlined in this study can be used for the future EOS missions. Prediction and smoothing algorithms for time series of calibration data provide a functional characterization of the data. Those algorithms can be particularly useful when calibration data are incomplete or sparse.

  7. High-resolution polar climate parameters derived from 1-km AVHRR data

    SciTech Connect

    Hutchinson, T.A.; Scambos, T.A.

    1997-11-01

    This paper describes the development of a time-series of composites of albedo, surface temperature, and sea ice motion. The composites will be generated from high-resolution (Local Area Coverage and High Resolution Picture Transmission) Advanced Very High Resolution Radiometer (AVHRR). Composites of albedo and surface (skin) temperature will be derived from AVHRR data within three hours of two selected local times (0400 and 1400 for the northern hemisphere, and 0200 and 1600 for the southern hemisphere) for each day. These products will be gridded at 1.25 km cell size in an equal-area projection compatible with recent gridded products from Special Sensor Microwave/Imager data and planned products from the TIROS Operational Verticle Sounder and other AVHRR data sets. Sea ice motion will be calculated once per day by comparing clear-sky image data of sea ice over a three-day period, and reported on a 1.25 km grid. A brief discussion of a reconnaissance survey of the output geophysical parameters for the Northern Hemisphere between August and October 1993 is also presented. 9 refs., 5 figs., 2 tabs.

  8. On the Use of Deep Convective Clouds to Calibrate AVHRR Data

    NASA Technical Reports Server (NTRS)

    Doelling, David R.; Nguyen, Louis; Minnis, Patrick

    2004-01-01

    Remote sensing of cloud and radiation properties from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) satellites requires constant monitoring of the visible sensors. NOAA satellites do not have onboard visible calibration and need to be calibrated vicariously in order to determine the calibration and the degradation rate. Deep convective clouds are extremely bright and cold, are at the tropopause, have nearly a Lambertian reflectance, and provide predictable albedos. The use of deep convective clouds as calibration targets is developed into a calibration technique and applied to NOAA-16 and NOAA-17. The technique computes the relative gain drift over the life-span of the satellite. This technique is validated by comparing the gain drifts derived from inter-calibration of coincident AVHRR and Moderate-Resolution Imaging Spectroradiometer (MODIS) radiances. A ray-matched technique, which uses collocated, coincident, and co-angled pixel satellite radiance pairs is used to intercalibrate MODIS and AVHRR. The deep convective cloud calibration technique was found to be independent of solar zenith angle, by using well calibrated Visible Infrared Scanner (VIRS) radiances onboard the Tropical Rainfall Measuring Mission (TRMM) satellite, which precesses through all solar zenith angles in 23 days.

  9. Urban vegetation land covers change detection using multi-temporal MODIS Terra/Aqua data

    NASA Astrophysics Data System (ADS)

    Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Dida, Adrian I.; Ionescu, Ovidiu M.

    2013-10-01

    Urban vegetation land cover change is a direct measure of quantitative increase or decrease in sources of urban pollution and the dimension of extreme climate events and changes that determine environment quality. Spatio- temporal monitoring of urban vegetation land cover changes is a very important task for establishing the links between policy decisions, regulatory actions and subsequent land use activities. Former studies incorporating two-date change detection using Landsat TM/ETM data had limited performance for urban biophysically complex systems applications. In this paper, we describe recent results using data from NASA's Moderate Resolution Imaging Spectroradiometer and NOAA/AVHRR satellite to study urban vegetation land cover dynamics. This study explored the use of time-series MODIS Terra/Aqua Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI), data to provide change detection information for metropolitan area of Bucharest in Romania. Training and validation are based on a reference dataset collected from IKONOS high resolution remote sensing data. The mean detection accuracy for period 2002- 2012 was assessed to be of 89%, with a reasonable balance between change commission errors (21.7%), change omission errors (28.5%), and Kappa coefficient of 0.69. Annual change detection rates across the urban/periurban areas over the study period (2002-2012) were estimated at 0.78% per annum in the range of 0.45% (2002) to 0.75% (2012).Vegetation dynamics in urban areas at seasonal and longer timescales reflect large-scale interactions between the terrestrial biosphere and the climate system.

  10. Future Landing Capabilities of the Mars 2020 Entry, Descent, and Landing System

    NASA Astrophysics Data System (ADS)

    Kipp, K. A.; Hines, E. K.; Chen, A.

    2014-06-01

    This study examines landing site elevation capability as a function of landing season, for a future mission using the heritage MSL/Mars 2020 EDL system. Results are presented for a 1200kg landed mass with different parachute technology assumptions.

  11. Seasonal Forecasting of Fires across Southern Borneo, 1997-2010

    NASA Astrophysics Data System (ADS)

    Spessa, Allan; Field, Robert; Kaiser, Johannes; Langner, Andreas; Moore, Jonathan; Pappenberger, Florian; Siegert, Florian; Weber, Ulrich

    2014-05-01

    several studies using historical data have established negative relationships between fires and antecedent rainfall, and/or positive relationships between fires and deforestation in regions affected by El Nino, comparatively little work has attempted to predict fires and emissions in such regions. Ensemble seasonal climate forecasts issued with several months lead-time have been applied to support risk assessment systems in many fields, notably agricultural production and natural disaster management of flooding, heat waves, drought and fire. The USA, for example, has a long-standing seasonal fire danger prediction system. Fire danger monitoring systems have been operating in Indonesia for over a decade, but, as of yet, no fire danger prediction systems exist. Given the effort required to mobilise suppression and prevention measures in Indonesia, one could argue that high fire danger periods must be anticipated months in advance for mitigation and response measures to be effective. To address this need, the goal of our work was to examine the utility of seasonal rainfall forecasts in predicting severe fires in Indonesia more than one month in advance, using southern Borneo (comprising the bulk of Kalimantan) as a case study. Here we present the results of comparing seasonal forecasts of monthly rainfall from ECMWF's System 4 against i) observed rainfall (GPCP), and ii) burnt area and deforestation (MODIS, AVHRR and Landsat) across southern Borneo for the period 1997-2010. Our results demonstrate the utility of using ECMWF's seasonal climate forecasts for predicting fire activity in the region. Potential applications include improved fire mitigation and responsiveness, and improved risk assessments of biodiversity and carbon losses through fire. These are important considerations for forest protection programmes (e.g. REDD+), forest carbon markets and forest (re)insurance enterprises.

  12. Evaluation of NPP VIIRS Vegetation Index EDR performance using MODIS and AVHRR data records

    NASA Astrophysics Data System (ADS)

    vargas, M.; Shabanov, N.; Miura, T.

    2012-12-01

    Vegetation Index (VI) is one key parameter to specify the boundary condition in global climate models, weather forecasting models and numerous remote sensing applications for monitoring environmental state and its change. The VI Environmental Data Record (EDR), which includes the Top of Atmosphere Normalized Difference Vegetation Index (TOA NDVI) and the Top of Canopy Enhanced Vegetation Index (TOC EVI), is currently operationally generated from data delivered by the Visible Infrared Imaging radiometer Suite (VIIRS) instrument onboard the National Polar-orbiting Partnership (NPP) platform launched in October 2011. The VI EDR was implemented to provide continuity for 30+ years of historical VI records provided by MODIS and AVHRR sensors. This presentation reports on the results of the analysis performed by the JPSS VI group at NOAA-NESDIS-STAR on two major aspects of performance of the VI EDR in the early phase of the NPP mission: (1) assessment of accuracy of the VIIRS VI EDR product with respect to input data including Surface Reflectances, Cloud and Aerosol masks as function of vegetation (biome) types; (2) temporal and spatial consistency of VIIRS VI EDR with respect to heritage MODIS and AVHRR VI products. This analysis is based on data from VIIRS (daily TOA NDVI and TOC EVI, and daily surface reflectances), Terra MODIS (16 days composites of TOC EVI and TOC NDVI, and daily TOA radiances) and NOAA-18 AVHRR (7-days composites of TOA NDVI). MODIS 8-biome landcover mask was used to quantify variations in VI product performance as function of vegetation type. Best overall agreement is achieved between VIIRS and MODIS data (TOC EVI and TOC NDVI) in terms of minimum systematic discrepancy (minimum bias and STD) and highest correlation of spatial patterns (highest r^2). The agreement is highest for biomes with low vegetation cover, but degrades with increased foliage density. VIIRS cloud mask provides a fair screening of daily data over the globe. While performance of

  13. Towards community consensus clear-sky ocean radiances and SSTs from AVHRR

    NASA Astrophysics Data System (ADS)

    Ignatov, A.; Dash, P.; Liang, X.; Sapper, J.; Kihai, Y.; Petrenko, B.; Cao, C.; Wu, F.; Heidinger, A. K.; Grumbine, R. W.; Leborgne, P.; May, D.; McKenzie, B. D.; Martin, M.; Reynolds, R. W.; Casey, K. S.; Evans, R. H.; Vazquez, J.; Armstrong, E. M.; Maturi, E.; Harris, A.; Mittaz, J. P.

    2010-12-01

    Several Level 2 (L2) SST products have been operationally produced from AVHRR clear-sky radiances since the late 1970s, initially at NOAA/NESDIS, and later at NAVO and Meteo France. Reprocessing of AVHRR data back to 1981 is done under the Pathfinder SST Program. By virtue of their long time series, consistent global coverage, accuracy and spatial resolution, AVHRR L2 SST products have critically contributed to the generation of several Level 4 (L4) products. Examples of L4 products are Reynolds, Real Time Global (RTG), Operational SST and Sea Ice Analysis (OSTIA), and GOES-POES blended SSTs. A large number of available L2 and L4 SST products call for establishing community consensus performance metrics towards their monitoring in near real time and evaluating for stability and self- and cross-consistency. These activities are coordinated by the Group for High Resolution SST (GHRSST) http://www.ghrsst.org/The-Inter-Calibration-TAG-%28IC-TAG%29.html. Our experience suggests that monitoring clear-sky brightness temperatures (BTs) in AVHRR thermal bands is likewise important in resolving anomalies observed in SSTs. The SST Quality Monitor (SQUAM, http://www.star.nesdis.noaa.gov/sod/sst/squam/) and the Monitoring of IR Clear-sky Radiances over Ocean for SST (MICROS, http://www.star.nesdis.noaa.gov/sod/sst/micros/) tools were established for monitoring and cross-evaluating various SST and BT products. SQUAM currently monitors four major operational L2 SST products: the NESDIS heritage Main Unit Task and the newer Advanced Clear-Sky Processor for oceans, the NAVO SEATEMP, the O&SI SAF SST generated at Meteo FRANCE, and Pathfinder v5. SQUAM also monitors the following L4 products: two daily Reynolds, two RTG (low and high resolution), OSTIA, NAVOCEANO K10, GHRSST Multi-Product Ensemble, and POES-GOES blended SST product. MICROS monitors clear-sky BTs associated with SSTs, by comparing them with modeled BTs simulated using first guess SST and upper air fields. Currently

  14. Assessing satellite-derived start-of-season measures in the conterminous USA

    USGS Publications Warehouse

    Schwartz, Mark D.; Reed, Bradley C.; White, Michael A.

    2002-01-01

    National Oceanic and Atmospheric Administration (NOAA)-series satellites, carrying advanced very high-resolution radiometer (AVHRR) sensors, have allowed moderate resolution (1 km) measurements of the normalized difference vegetation index (NDVI) to be collected from the Earth's land surfaces for over 20 years. Across the conterminous USA, a readily accessible and decade-long data set is now available to study many aspects of vegetation activity in this region. One feature, the onset of deciduous plant growth at the start of the spring season (SOS) is of special interest, as it appears to be crucial for accurate computation of several important biospheric processes, and a sensitive measure of the impacts of global change. In this study, satellite-derived SOS dates produced by the delayed moving average (DMA) and seasonal midpoint NDVI (SMN) methods, and modelled surface phenology (spring indices, SI) were compared at widespread deciduous forest and mixed woodland sites during 1990–93 and 1995–99, and these three measures were also matched to native species bud-break data collected at the Harvard Forest (Massachusetts) over the same time period. The results show that both SOS methods are doing a modestly accurate job of tracking the general pattern of surface phenology, but highlight the temporal limitations of biweekly satellite data. Specifically, at deciduous forest sites: (1) SMN SOS dates are close in time to SI first bloom dates (average bias of +0.74 days), whereas DMA SOS dates are considerably earlier (average bias of −41.24 days) and also systematically earlier in late spring than in early spring; (2) SMN SOS tracks overall yearly trends in deciduous forests somewhat better than DMA SOS, but with larger average error (MAEs 8.64 days and 7.37 days respectively); and (3) error in both SOS techniques varies considerably by year. Copyright © 2002 Royal Meteorological Society.

  15. The CACAO Method for Smoothing, Gap Filling, and Characterizing Seasonal Anomalies in Satellite Time Series

    NASA Technical Reports Server (NTRS)

    Verger, Aleixandre; Baret, F.; Weiss, M.; Kandasamy, S.; Vermote, E.

    2013-01-01

    Consistent, continuous, and long time series of global biophysical variables derived from satellite data are required for global change research. A novel climatology fitting approach called CACAO (Consistent Adjustment of the Climatology to Actual Observations) is proposed to reduce noise and fill gaps in time series by scaling and shifting the seasonal climatological patterns to the actual observations. The shift and scale CACAO parameters adjusted for each season allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. CACAO was assessed first over simulated daily Leaf Area Index (LAI) time series with varying fractions of missing data and noise. Then, performances were analyzed over actual satellite LAI products derived from AVHRR Long-Term Data Record for the 1981-2000 period over the BELMANIP2 globally representative sample of sites. Comparison with two widely used temporal filtering methods-the asymmetric Gaussian (AG) model and the Savitzky-Golay (SG) filter as implemented in TIMESAT-revealed that CACAO achieved better performances for smoothing AVHRR time series characterized by high level of noise and frequent missing observations. The resulting smoothed time series captures well the vegetation dynamics and shows no gaps as compared to the 50-60% of still missing data after AG or SG reconstructions. Results of simulation experiments as well as confrontation with actual AVHRR time series indicate that the proposed CACAO method is more robust to noise and missing data than AG and SG methods for phenology extraction.

  16. Recent History of Large-Scale Ecosystem Disturbances in North America Derived from the AVHRR Satellite Record

    NASA Technical Reports Server (NTRS)

    Potter, Christopher; Tan, Pang-Ning; Kumar, Vipin; Kicharik, Chris; Klooster, Steven; Genovese, Vanessa

    2004-01-01

    Ecosystem structure and function are strongly impacted by disturbance events, many of which in North America are associated with seasonal temperature extremes, wildfires, and tropical storms. This study was conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the Advanced Very High Resolution Radiometer (AVHRR) as a means to characterize major ecosystem disturbance events and regimes. The fraction absorbed of photosynthetically active radiation (FPAR) by vegetation canopies worldwide has been computed at a monthly time interval from 1982 to 2000 and gridded at a spatial resolution of 8-km globally. Potential disturbance events were identified in the FPAR time series by locating anomalously low values (FPAR-LO) that lasted longer than 12 consecutive months at any 8-km pixel. We can find verifiable evidence of numerous disturbance types across North America, including major regional patterns of cold and heat waves, forest fires, tropical storms, and large-scale forest logging. Summed over 19 years, areas potentially influenced by major ecosystem disturbances (one FPAR-LO event over the period 1982-2000) total to more than 766,000 km2. The periods of highest detection frequency were 1987-1989, 1995-1997, and 1999. Sub- continental regions of Alaska and Central Canada had the highest proportion (greater than 90%) of FPAR-LO pixels detected in forests, tundra shrublands, and wetland areas. The Great Lakes region showed the highest proportion (39%) of FPAR-LO pixels detected in cropland areas, whereas the western United States showed the highest proportion (16%) of FPAR-LO pixels detected in grassland areas. Based on this analysis, an historical picture is emerging of periodic droughts and heat waves, possibly coupled with herbivorous insect outbreaks, as among the most important causes of ecosystem disturbance in North America.

  17. Hydrology of a zero-order Southern Piedmont watershed through 45 years of changing agricultural land use. Part 1. Monthly and seasonal rainfall-runoff relationships

    NASA Astrophysics Data System (ADS)

    Endale, Dinku M.; Fisher, Dwight S.; Steiner, Jean L.

    2006-01-01

    Few studies have reported runoff from small agricultural watersheds over sufficiently long period so that the effect of different cover types on runoff can be examined. We analyzed 45-yrs of monthly and annual rainfall-runoff characteristics of a small (7.8 ha) zero-order typical Southern Piedmont watershed in southeastern United States. Agricultural land use varied as follows: 1. Row cropping (5-yrs); 2. Kudzu ( Pueraria lobata; 5-yrs); 3. Grazed kudzu and rescuegrass ( Bromus catharticus; 7-yrs); and 4. Grazed bermudagrass and winter annuals ( Cynodon dactylon; 28-yrs). Land use and rainfall variability influenced runoff characteristics. Row cropping produced the largest runoff amount, percentage of the rainfall partitioned into runoff, and peak flow rates. Kudzu reduced spring runoff and almost eliminated summer runoff, as did a mixture of kudzu and rescuegrass (KR) compared to row cropping. Peak flow rates were also reduced during the kudzu and KR. Peak flow rates increased under bermudagrass but were lower than during row cropping. A simple process-based 'tanh' model modified to take the previous month's rainfall into account produced monthly rainfall and runoff correlations with coefficient of determination ( R2) of 0.74. The model was tested on independent data collected during drought. Mean monthly runoff was 1.65 times the observed runoff. Sustained hydrologic monitoring is essential to understanding long-term rainfall-runoff relationships in agricultural watersheds.

  18. Development of a land-cover characteristics database for the conterminous US

    USGS Publications Warehouse

    Loveland, T.R.; Merchant, J.W.; Ohlen, D.O.; Brown, J.F.

    1991-01-01

    Information regarding the characteristics and spatial distribution of the Earth's land cover is critical to global environmental research. A prototype land-cover database for the conterminous United States designed for use in a variety of global modelling, monitoring, mapping, and analytical endeavors has been created. The resultant database contains multiple layers, including the source AVHRR data, the ancillary data layers, the land-cover regions defined by the research, and translation tables linking the regions to other land classification schema (for example, UNESCO, USGS Anderson System). The land-cover characteristics database can be analyzed, transformed, or aggregated by users to meet a broad spectrum of requirements. -from Authors

  19. Classification of satellite time series-derived land surface phenology focused on the northern Fertile Crescent

    NASA Astrophysics Data System (ADS)

    Bunker, Brian

    Land surface phenology describes events in a seasonal vegetation cycle and can be used in a variety of applications from predicting onset of future drought conditions, to revealing potential limits of historical dry farming, to guiding more accurate dating of archeological sites. Traditional methods of monitoring vegetation phenology use data collected in situ. However, vegetation health indices derived from satellite remote sensor data, such as the normalized difference vegetation index (NDVI), have been used as proxy for vegetation phenology due to their repeated acquisition and broad area coverage. Land surface phenology is accessible in the NDVI satellite record when images are processed to be intercomparable over time and temporally ordered to create a time series. This study utilized NDVI time series to classify areas of similar vegetation phenology in the northern Fertile Crescent, an area from the middle Mediterranean coast to southern/south-eastern Turkey to western Iran and northern Iraq. Phenological monitoring of the northern Fertile Crescent is critical due to the area's minimal water resources, susceptibility to drought, and understanding ancient historical reliance on precipitation for subsistence dry farming. Delineation of phenological classes provides areal and temporal synopsis of vegetation productivity time series. Phenological classes were developed from NDVI time series calculated from NOAA's Advanced Very High Resolution Radiometer (AVHRR) imagery with 8 × 8 km spatial resolution over twenty-five years, and by NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) with 250 × 250 m spatial resolution over twelve years. Both AVHRR and MODIS time series were subjected to data reduction techniques in spatial and temporal dimensions. Optimized ISODATA clusters were developed for both of these data reduction techniques in order to compare the effects of spatial versus temporal aggregation. Within the northern Fertile Crescent study area

  20. 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

  1. Lake surface water temperatures of European Alpine lakes (1989-2013) based on the Advanced Very High Resolution Radiometer (AVHRR) 1 km data set

    NASA Astrophysics Data System (ADS)

    Riffler, M.; Lieberherr, G.; Wunderle, S.

    2015-02-01

    Lake water temperature (LWT) is an important driver of lake ecosystems and it has been identified as an indicator of climate change. Consequently, the Global Climate Observing System (GCOS) lists LWT as an essential climate variable. Although for some European lakes long in situ time series of LWT do exist, many lakes are not observed or only on a non-regular basis making these observations insufficient for climate monitoring. Satellite data can provide the information needed. However, only few satellite sensors offer the possibility to analyse time series which cover 25 years or more. The Advanced Very High Resolution Radiometer (AVHRR) is among these and has been flown as a heritage instrument for almost 35 years. It will be carried on for at least ten more years, offering a unique opportunity for satellite-based climate studies. Herein we present a satellite-based lake surface water temperature (LSWT) data set for European water bodies in or near the Alps based on the extensive AVHRR 1 km data record (1989-2013) of the Remote Sensing Research Group at the University of Bern. It has been compiled out of AVHRR/2 (NOAA-07, -09, -11, -14) and AVHRR/3 (NOAA-16, -17, -18, -19 and MetOp-A) data. The high accuracy needed for climate related studies requires careful pre-processing and consideration of the atmospheric state. The LSWT retrieval is based on a simulation-based scheme making use of the Radiative Transfer for TOVS (RTTOV) Version 10 together with ERA-interim reanalysis data from the European Centre for Medium-range Weather Forecasts. The resulting LSWTs were extensively compared with in situ measurements from lakes with various sizes between 14 and 580 km2 and the resulting biases and RMSEs were found to be within the range of -0.5 to 0.6 K and 1.0 to 1.6 K, respectively. The upper limits of the reported errors could be rather attributed to uncertainties in the data comparison between in situ and satellite observations than inaccuracies of the satellite

  2. Changing Seasons

    ERIC Educational Resources Information Center

    Karolak, Eric

    2011-01-01

    In some ways, there is a season of change at the national level in early childhood. Some things are wrapping up while some developments aim to prepare the "field" for improvements in the next year and beyond, just as a garden plot is readied for the next planting season. Change is in the air, and there's hope of renewal, but what changes and how…

  3. Improvement of Cold Season Land Precipitation Retrievals through the use of Field Campaign Data and High Frequency Microwave Radiative Transfer Model

    NASA Astrophysics Data System (ADS)

    Wang, N.-Y.; Ferraro, R.

    2009-04-01

    As we move from the TRMM to GPM era, more emphasis will be placed on a larger regime of precipitation in mid- and high-latitudes, including light rain, mixed-phase precipitation and snowfall. In these areas, a large and highly variable portion of the total annual precipitation is snow. The remote sensing of snowfall is especially challenging because of several factors (1) the lack of liquid precipitation in the snowfall limits the passive microwave retrieval to the scattering signals at the high frequency, which is indirectly associated with surface precipitation (2) The optical properties of frozen hydrometeor is more variable and less well known than those of rain (3) The surface emissivity of snow is highly variable in time and space, which further hampers the uses of the window channels. There is a wealth of observational evidence of brightness temperature depression from frozen hydrometeor scattering at the high frequency from aircraft and spacecraft microwave instruments. Research on the development of snowfall retrieval over land has become increasing important in the last few years (Chen and Staelin, 2003; Kongoli et al., 2004; Skofronick-Jackson et al., 2004). However, there is still a considerable amount of work that needs to be done to develop global snowfall detection and retrieval algorithms. This paper describes the development and testing of snowfall models and retrieval algorithms using pre-launch GPM field campaign data (e.g., CV3P) and high frequency radiative transfer models.

  4. AVHRR-Based Polar Pathfinder Products: Evaluation, Enhancement and Transition to MODIS

    NASA Technical Reports Server (NTRS)

    Fowler, Charles; Maslanik, James; Stone, Robert; Stroeve, Julienne; Emery, William

    2000-01-01

    Study of the environment has historically been done with observations and measurements in relatively few local areas. While some of these have been done over long time spans, most have not. The NOAA/NASA Pathfinder project was initiated to complement these data sets with satellite data that can provide information over larger spatial areas and longer time spans. The AVHRR Polar Pathfinder (APR) program was part of this project. The APR was to supply data from the NOAA AVHRR instruments that was consistently generated in a format usable to a wide range of scientific investigators. A grant was obtained from the NASA Research Announcement 97-MTPE-03 to evaluate the APP products, to provide any enhancements, and to compare with products from the new MODIS instrument. There was about a two year overlap between the projects, and this validation effort had several impacts on the APP products. The APP products are derived from the instruments aboard 4 NOAA satellites, NOAA-7, 9, 11, and 14. Initial validation efforts compared the thermal calibrations of these instruments, and differences are found. Calibration has undergone many revisions and techniques have changed since the satellites were launched. The first calibration methods were optimized for global ocean temperatures, as this was one of the primary and important uses of the AVHRR instruments. As the APP program started, newer methods that provided more accurate temperature retrievals over a wider range of temperatures were being developed. The calibration of a wider range of temperatures were necessary because of the extremely low values in the polar regions. These methods were also designed so that calibrated data was also consistent between all the NOAA satellites. These newer calibration methods were then adopted primarily because of the initial finding of this validation effort.

  5. Iterative edge- and wavelet-based image registration of AVHRR and GOES satellite imagery

    NASA Technical Reports Server (NTRS)

    LeMoigne, Jacqueline; El-Saleous, Nazmi; Vermote, Eric

    1997-01-01

    Most automatic registration methods are either correlation-based, feature-based, or a combination of both. Examples of features which can be utilized for automatic image registration are edges, regions, corners, or wavelet-extracted features. In this paper, we describe two proposed approaches, based on edge or edge-like features, which are very appropriate to highlight regions of interest such as coastlines. The two iterative methods utilize the Normalized Cross-Correlation of edge and wavelet features and are applied to such problems as image-to-map registration, landmarking, and channel-to-channel co-registration, utilizing test data, AVHRR data, as well as GOES image data.

  6. The effect of surface anisotropy and viewing geometry on the estimation of NDVI from AVHRR

    USGS Publications Warehouse

    Meyer, D.; Verstraete, M.; Pinty, B.

    1995-01-01

    Since terrestrial surfaces are anisotropic, all spectral reflectance measurements obtained with a small instantaneous field of view instrument are specific to these angular conditions, and the value of the corresponding NDVI, computed from these bidirectional reflectances, is relative to the particular geometry of illumination and viewing at the time of the measurement. This paper documents the importance of these geometric effects through simulations of the AVHRR data acquisition process, and investigates the systematic biases that result from the combination of ecosystem-specific anisotropies with instrument-specific sampling capabilities. Typical errors in the value of NDVI are estimated, and strategies to reduce these effects are explored. -from Authors

  7. Application of NDVI to detecting algal bloom in the Bohai Sea of China from AVHRR

    NASA Astrophysics Data System (ADS)

    Zhao, Dongzhi

    2003-05-01

    This paper analyses the relation between data measured in situ and the NDVI derived from AVHRR of NOAA-14 during algal bloom in the Bohai sea in 1998 to establish surface biomass model of Ceratium furca(EHr.). This model is easy to utilize data received from multi-source satellite in operation, and gets directly the index of phytoplankton biomass. The area and distribution of high biomass is also presented. Based on this model, propagation speed of phytoplankton reveals progress of algal bloom development. The result of this model can discriminate algal bloom water from silt or suspended particle material (SPM).

  8. Polar cloud and surface classification using AVHRR imagery - An intercomparison of methods

    NASA Technical Reports Server (NTRS)

    Welch, R. M.; Sengupta, S. K.; Goroch, A. K.; Rabindra, P.; Rangaraj, N.; Navar, M. S.

    1992-01-01

    Six Advanced Very High-Resolution Radiometer local area coverage (AVHRR LAC) arctic scenes are classified into ten classes. Three different classifiers are examined: (1) the traditional stepwise discriminant analysis (SDA) method; (2) the feed-forward back-propagation (FFBP) neural network; and (3) the probabilistic neural network (PNN). More than 200 spectral and textural measures are computed. These are reduced to 20 features using sequential forward selection. Theoretical accuracy of the classifiers is determined using the bootstrap approach. Overall accuracy is 85.6 percent, 87.6 percent, and 87.0 percent for the SDA, FFBP, and PNN classifiers, respectively, with standard deviations of approximately 1 percent.

  9. A 1981-2012 Non-stationary AVHRR NDVI Global 8-km Data Set (Invited)

    NASA Astrophysics Data System (ADS)

    Tucker, C. J.; Pinzon, J. E.

    2013-12-01

    The longest global daily satellite data record is from the polar-orbiting advanced very high resolution radiometer or AVHRR instruments that started in July 1981 and continues uninterrupted to this day. In spite of non-optimum visible and near-infrared bandwidths, lack of orbital station-keeping early in the record, and '4-km' spatial resolution, we have produced a non-stationary and consistent NDVI record from that matches up well with coincident MODIS NDVI data. We review our processing methods and describe detailed coincident comparisons with MODIS NDVI data in many climate regions.

  10. NOAA-10 AVHRR thermal-infrared image of the Colorado Rocky Mountains

    USGS Publications Warehouse

    Gallo, Kevin P.; Quirk, Bruce K.; Hood, Joy J.

    1988-01-01

    This month we demonstrate an example of the use of thermal infrared imagery to produce a relatively sharp surrogate shaded-relief image. The image shows one aspect of the drama and usefulness of calibrated thermal imagery that (because of compatible projection and pixel size) can be easily combined with other spectral bands of a satellite image. Such data can be enhanced in yet another way by stereoscopically combining two similar images with different orbital paths, such as was shown in the AVHRR column for January 1988.

  11. An algorithm for the detection of the white-tide ('mucilage') phenomenon in the Adriatic Sea using AVHRR data

    SciTech Connect

    Tassan, S. )

    1993-06-01

    An algorithm using AVHRR data has been set up for the detection of a white tide consisting of algae secretion ('mucilage'), an event occurring in the Adriatic Sea under particular meteorological conditions. The algorithm, which includes an ad hoc procedure for cloud masking, has been tested with reference to the mucilage map obtained from the analysis of contemporary Thematic Mapper data, as well as by comparing consecutive AVHRR scenes. The main features of the exceptional mucilage phenomenon that took place in the northern basin of the Adriatic Sea in summer 1989 are shown by a time series of maps.

  12. Microwave Brightness Of Land Surfaces From Outer Space

    NASA Technical Reports Server (NTRS)

    Kerr, Yann H.; Njoku, Eni G.

    1991-01-01

    Mathematical model approximates microwave radiation emitted by land surfaces traveling to microwave radiometer in outer space. Applied to measurements made by Scanning Multichannel Microwave Radiometer (SMMR). Developed for interpretation of microwave imagery of Earth to obtain distributions of various chemical, physical, and biological characteristics across its surface. Intended primarily for use in mapping moisture content of soil and fraction of Earth covered by vegetation. Advanced Very-High-Resolution Radiometer (AVHRR), provides additional information on vegetative cover, thereby making possible retrieval of soil-moisture values from SMMR measurements. Possible to monitor changes of land surface during intervals of 5 to 10 years, providing significant data for mathematical models of evolution of climate.

  13. The global land shortwave cryosphere radiative effect during the MODIS era

    NASA Astrophysics Data System (ADS)

    Singh, D.; Flanner, M. G.; Perket, J.

    2015-11-01

    The shortwave cryosphere radiative effect (CrRE) is the instantaneous influence of snow and ice cover on Earth's top-of-atmosphere (TOA) solar energy budget. Here, we apply measurements from the MODerate resolution Imaging Spectroradiometer (MODIS), combined with microwave retrievals of snow presence and radiative kernels produced from four different models, to derive CrRE over global land during 2001-2013. We estimate global annual-mean land CrRE during this period of -2.6 W m-2, with variations from -2.2 to -3.0 W m-2 resulting from use of different kernels and variations of -2.4 to -2.6 W m-2 resulting from different algorithmic determinations of snow presence and surface albedo. Slightly more than half of the global land CrRE originates from perennial snow on Antarctica, whereas the majority of the northern hemispheric effect originates from seasonal snow. Consequently, the northern hemispheric land CrRE peaks at -6.0 W m-2 in April, whereas the southern hemispheric effect more closely follows the austral insolation cycle, peaking at -9.0 W m-2 in December. Mountain glaciers resolved in 0.05° MODIS data contribute about -0.037 W m-2 (1.4 %) of the global effect, with the majority (94 %) of this contribution originating from the Himalayas. Interannual trends in the global annual-mean land CrRE are not statistically significant during the MODIS era, but trends are positive (less negative) over large areas of northern Asia, especially during spring, and slightly negative over Antarctica, possibly due to increased snowfall. During a common overlap period of 2001-2008, our MODIS estimates of the northern hemispheric land CrRE are about 18 % smaller (less negative) than previous estimates derived from coarse-resolution AVHRR data, though interannual variations are well correlated (r = 0.78), indicating that these data are useful in determining longer-term trends in land CrRE.

  14. SeaShark and Starfish opertional data processing schemes for AVHRR and SeaWiFs

    NASA Astrophysics Data System (ADS)

    Flowerdew, R. J.; Corlyon, Anaa M.; Greer, W. A. D.; Newby, Steve J.; Winder, C. P.

    1997-02-01

    SeaShark is an operational software package for processing, archiving and cataloguing AVHRR and SeaWiFS data using an operator friendly GUI. Upon receipt of a customer order, it produces standard AVHRR data products, including Sea Surface Temperature (SST) and it has recently been modified to include SeaWiFS level 2 data processing. This uses an atmospheric correction scheme developed by the Plymouth Marine Laboratory, UK (PML) that builds upon the standard Gordon and Wang approach to be applicable over both case 1 and case 2 waters. Higher level products are then generated using PML algorithms, including chlorophyll a, a CZCS-type pigment, Kd, and suspended particulate matter. Outputs are in CEOS-compatible format. The software also produces fast delivery products (FDPs) of chlorophyll a and SST. These FDPs are combined in the StarFish software package to provide maps indicating potential location of phytoplankton and the preferred thermal environment of certain pelagic fish species. Fishing vessels may obtain these maps over Inmarsat, allowing them to achieve a greater efficiency hence lower cost.

  15. Phenology of forest-grassland transition zones in the Community Land Model

    NASA Astrophysics Data System (ADS)

    Dahlin, K.; Fisher, R. A.

    2013-12-01

    Forest-grassland transition zones (savannas, woodlands, wooded grasslands, and shrublands) are highly sensitive to climate and may already be changing due to warming, changes in precipitation patterns, and/or CO2 fertilization. Shifts between closed canopy forest and open grassland, as well as shifts in phenology, could have large impacts on the global carbon cycle, water balance, albedo, and on the humans and other animals that depend on these regions. From an earth system perspective these impacts may then feed back into the climate system and impact how, when, and where climate change occurs. Here we compare 29 years of monthly leaf area index (LAI) outputs from several offline versions of the Community Land Model (CLM), the land component of the Community Earth System Model, to LAI derived from the AVHRR NDVI3g product (LAI3g). Specifically, we focus on seasonal patterns in regions dominated by tropical broadleaved deciduous trees (T-BDT), broadleaved deciduous shrubs (BDS) and grasslands (C3 and C4) in CLM, all of which follow a 'stress deciduous' phenological algorithm. We consider and compare two versions of CLM (v. 4CN and v. 4.5BGC) to the satellite derived product. We found that both versions of CLM were able to capture seasonal variations in grasslands relatively well at the regional scale, but that the 'stress deciduous' phenology algorithm did not perform well in areas dominated by T-BDT or BDS. When we compared the performance of the models at single points we found slight improvements in CLM4.5BGC over CLM4CN, but generally that the magnitude of seasonality was too low in CLM as compared to the LAI3g satellite product. To explore the parameters within CLM that had the most leverage on seasonality of LAI, we used a Latin hypercube approach to vary values for critical soil water potential (threshold at which plants drop leaves), the critical number of days that soil water potential must be too low for leaves to drop, and the carbon allocation scheme

  16. A 16-year time series of 1 km AVHRR satellite data of the conterminous United States and Alaska

    USGS Publications Warehouse

    Eldenshink, J.

    2006-01-01

    The U.S. Geological Survey (USGS) has developed a 16-year time series of vegetation condition information for the conterminous United States and, Alaska using 1 km Advanced Very High Resolution Radiometer (AVHRR) data. The AVHRR data have been processed using consistent methods that account for radiometric variability due to calibration uncertainty, the effects of the atmosphere on surface radiometric measurements obtained from wide field-of-view observations, and the geometric registration accuracy. The conterminous United States and Alaska data sets have an atmospheric correction for water vapor, ozone, and Rayleigh scattering and include a cloud mask derived using the Clouds from AVHRR (CLAVR) algorithm. In comparison with other AVHRR time series data sets, the conterminous United States and Alaska data are processed using similar techniques. The primary difference is that the conterminous United States and Alaska data are at 1 km resolution, while others are at 8 km resolution. The time series consists of weekly and biweekly maximum normalized difference vegetation index (NDVI) composites. ?? 2006 American Society for Photogrammetry and Remote Sensing.

  17. Sea ice motions in the central arctic ice central arctic pack ice as inferred from AVHRR imagery

    NASA Technical Reports Server (NTRS)

    Emery, William; Maslanik, James; Fowler, Charles

    1993-01-01

    Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoy data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Merging the remotely-sensed ice motions with SAR, AVHRR, OLS, and SSM/I imagery permits studies of ice processes over a range of space and time scales. A medium-resolution passive microwave sensor might be ideal for this purpose, but no such satellite will be available in the near future. Combinations of existing data types are thus likely to be our best bet for generating motion fields with a coverage and resolution best suited to climate studies. Principal objectives of this project are to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions.

  18. REPORT ON THE USEFULNESS OF AVHRR AND CZCS SENSORS FOR DELINEATING POTENTIAL DISPOSAL OPERATIONS AT THE 106-MILE SITE

    EPA Science Inventory

    In this work data from the AVHRR sensor for 18 TIROS-N series satellite passes were examined for signs of ocean dumping at Deepwater Dumpsite 106. The passes selected occurred within five days following the actual dump although in most cases they occurred on the same day or that ...

  19. Inter-annual and seasonal trends of vegetation condition in the Upper Blue Nile (Abay) Basin: dual-scale time series analysis

    NASA Astrophysics Data System (ADS)

    Teferi, E.; Uhlenbrook, S.; Bewket, W.

    2015-09-01

    A long-term decline in ecosystem functioning and productivity, often called land degradation, is a serious environmental challenge to Ethiopia that needs to be understood so as to develop sustainable land use strategies. This study examines inter-annual and seasonal trends of vegetation cover in the Upper Blue Nile (UBN) or Abbay Basin. The Advanced Very High Resolution Radiometer (AVHRR)-based Global Inventory, Monitoring, and Modeling Studies (GIMMS) normalized difference vegetation index (NDVI) was used for long-term vegetation trend analysis at low spatial resolution. Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data (MOD13Q1) were used for medium-scale vegetation trend analysis. Harmonic analyses and non-parametric trend tests were applied to both GIMMS NDVI (1981-2006) and MODIS NDVI (2001-2011) data sets. Based on a robust trend estimator (Theil-Sen slope), most parts of the UBN (~ 77 %) showed a positive trend in monthly GIMMS NDVI, with a mean rate of 0.0015 NDVI units (3.77 % yr-1), out of which 41.15 % of the basin depicted significant increases (p < 0.05), with a mean rate of 0.0023 NDVI units (5.59 % yr-1) during the period. However, the MODIS-based vegetation trend analysis revealed that about 36 % of the UBN showed a significant decreasing trend (p < 0.05) over the period 2001-2011 at an average rate of 0.0768 NDVI yr-1. This indicates that the greening trend of the vegetation condition was followed by decreasing trend since the mid-2000s in the basin, which requires the attention of land users and decision makers. Seasonal trend analysis was found to be very useful to identify changes in vegetation condition that could be masked if only inter-annual vegetation trend analysis was performed. Over half (60 %) of the Abay Basin was found to exhibit significant trends in seasonality over the 25-year period (1982-2006). About 17 and 16 % of the significant trends consisted of areas experiencing a uniform increase in NDVI throughout the year

  20. Application of AVHRR vegetation index to study atmosphere-biosphere exchange of CO2: Results from a 3-D tracer transport model

    NASA Technical Reports Server (NTRS)

    Fung, Inez Y.; Tucker, C. J.; Prentice, Katharine C.

    1985-01-01

    The 'normalized difference vegetation indices' (NVI) derived from AVHRR radiances are combined with field data of soil respiration and a global map of net primary productivity to prescribe, for the globe, the seasonal exchange of CO2 between the atmosphere and the terrestrial biosphere. The monthly fluxes of CO2 thus obtained are used as inputs to a 3-D tracer transport model which uses winds generated by a 3-D atmospheric general circulation model to advect CO2 as an inert constituent. Analysis of the 3-D model results shows reasonable agreement between the simulated and observed annual cycles of atmospheric CO2 at the locations of the remote monitoring stations. The application is shown of atmospheric CO2 distributions to calibrate the NVI in terms of carbon fluxes. The approach suggests that the NVI may be used to provide quantitative information about long term and global scale variations of photosynthetic activity and of atmospheric CO2 concentrations provided that variations in the atmospheric circulation and in atmospheric composition are known.

  1. A Satellite Time Slots Climatology of the Urban Heat Island of Guadalajara Megacity in Mexico from NOAA ¡/AVHRR THERMAL Infrared Monitoring (TIR)

    NASA Astrophysics Data System (ADS)

    Galindo, I.

    2009-04-01

    The urban heat island (UHI) of the metropolitan area of the second megacity of Mexico, named Guadalajara in Mexico is studied using thermal infrared data (TIR) (10 £ l £ 12 mm) obtained from the Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA polar orbitters whose signals are received on real time at our ground station for the period 1996-2006. The TIR data are selected by means of a software, since they depend on natural causes (e.g., atmospheric transparency, surface temperature, spectral emissivity and topography) and observational (time and incidence angle of the satellite pass, season of the year, etc.). The above conditions have a variable contribution to the measurements which it can be so high that they simulate the temporal-space fluctuations considered as thermal anomalies. Using a Geographic Information System and spatial analysis techniques temperatures are obtained for diofferent times of the day (satellite slots) and dropped into a grid with a 2.5 km distance between points (latitude, longitude). The temperatures obtained for each satellite pass slot (four per day) are monthly averaged and the temperature anomalies are represented in thermal isolines for the study area. The temperature difference usually is larger at night than during the day, reaching a thermal gradient of 9 °C.

  2. Predicting malaria seasons in Kenya using multitemporal meteorological satellite sensor data.

    PubMed

    Hay, S I; Snow, R W; Rogers, D J

    1998-01-01

    This article describes research that predicts the seasonality of malaria in Kenya using remotely sensed images from satellite sensors. The predictions were made using relationships established between long-term data on paediatric severe malaria admissions and simultaneously collected data from the Advanced Very High Resolution Radiometer (AVHRR) on the National Oceanic and Atmospheric Administrations (NOAA) polar-orbiting meteorological satellites and the High Resolution Radiometer (HRR) on the European Organization for the Exploitation of Meteorological Satellites' (EUMETSAT) geostationary Meteosat satellites. The remotely sensed data were processed to provide surrogate information on land surface temperature, reflectance in the middle infra-red, rainfall, and the normalized difference vegetation index (NDVI). These variables were then subjected to temporal Fourier processing and the fitted Fourier data were compared with the mean percentage of total annual malaria admissions recorded in each month. The NDVI in the preceding month correlated most significantly and consistently with malaria presentations across the 3 sites (mean adjusted r2 = 0.71, range 0.61-0.79). Regression analyses showed that an NDVI threshold of 0.35-0.40 was required for more than 5% of the annual malaria cases to be presented in a given month. These thresholds were then extrapolated spatially with the temporal Fourier-processed NDVI data to define the number of months, in which malaria admissions could be expected across Kenya in an average year, at an 8 x 8 km resolution. The resulting maps were compared with the only existing map (Butler's) of malaria transmission periods for Kenya, compiled from expert opinion. Conclusions are drawn on the appropriateness of remote sensing techniques for compiling national strategies for malaria intervention. PMID:9692138

  3. Vegetation dynamics using AVHRR/NDVI: Regional climate, carbon dioxide fertilization and crop yield relations

    NASA Astrophysics Data System (ADS)

    Lim, Chai Kyung

    Vegetation development is closely related to climate factors, and, therefore, it is important to understand how it responds to global climate changes. For the last two decades it has been possible to monitor vegetation development at continental or global scales utilizing remote sensing Normalized Difference Vegetation Index (NDVI) data. We have developed a frequency analysis method to investigate land's vegetation greenness change and its response to the El Nino Southern Oscillation (ENSO). We found an ENSO influence on a tropical forest, southern semi-deciduous forest and a northeastern mixed forest. Our analysis shows the annual trends in vegetation greenness respond more sensitively than averaging methods. Atmospheric CO2 increase is another concern for climate change, for which fertilization effect on land vegetation has been suggested. Atmospheric CO2 and NDVI have a seasonal pattern of negative correlation, which makes it difficult to discern any positive influence of CO2 on vegetation. We adopted the concept of the rate of change in atmospheric CO2 concentration and NDVI to overcome this set pattern, and to reveal undergoing fluctuations. We found evidence that suggests a CO2 fertilization effect in some arctic and sub arctic regions and northern and inland parts of the eastern humid temperate zones in North America. Although NDVI reveals the vegetation greenness only at a fixed time and location, we have transformed NDVI effectively to describe the vegetation growth dynamics in the form of a new index, Normalized Growth Index (NGI). Utilizing NGI, we found the vegetation growth during the growing season is highly negatively correlated with the initial minimum vegetation greenness. One needs to be careful when comparing Net Primary Production (NPP) using NDVI between different types of vegetation, because the same NDVI value can imply the existence of different biomass due to different Leaf Area Index (LAI). To overcome this difficulty we have developed

  4. In-flight measurements of space count in the AVHRR solar reflectance bands

    NASA Astrophysics Data System (ADS)

    Ignatov, Alexander; Cao, Changyong; Sullivan, Jerry T.; Levin, Robert H.; Wu, Xiangqian; Galvin, Roy P.

    2005-01-01

    The solar reflectance bands (SRB) of the Advanced Very High Resolution Radiometers (AVHRR) flown onboard NOAA satellites are often referred to as non-calibrated in-flight. In contrast, the Earth emission bands (EEB) are calibrated using two reference points, deep space and the internal calibration target. In the SRBs, measurements of space count (SC) are also available, however, historically they are not used to specify the calibration offset ("zero count", ZC), which does not even appear in the calibration equation. A regression calibration formulation is used instead, equivalent to setting the ZC to a constant, whose value is specified from pre-launch measurements. Our analyses supported by a review of the instrument design and a wealth of historical SC information show that the SC varies in-flight and it differs from its pre-launch value. We therefore suggest that (1) the AVHRR calibration equation in the SRBs be re-formulated to explicitly use the ZC, consistently with the EEBs, and (2) the value of ZC be specified from the onboard measurements of SC. This study emphasizes the importance of clear discrimination between the SC (which is a measured quantity and therefore takes on a range of values, characterized by the empirical probability density function, PDF), from the ZC (which is a parameter in the calibration equation, i.e. a number whose value needs to be estimated from the measured SC as a mean, median or other statistic of the measured PDF). The ZC-formulation of the calibration equation is physically solid, and it minimizes human-induced calibration errors resulting from the use of a regression formulation with an un-constrained intercept. Specifying the calibration offset improves radiances, most notably at the low end of radiometric scale, and subsequently provides for more accurate vicarious determinations of the calibration slope (inverse gain). These calibration improvements are important for the products derived from the AVHRR low-radiances, such

  5. Multilevel cloud retrieval using multispectral HIRS and AVHRR data: Nighttime oceanic analysis

    NASA Technical Reports Server (NTRS)

    Baum, Bryan A.; Arduini, Robert F.; Wielicki, Bruce A.; Minnis, Patrick; Tsay, Si-Chee

    1994-01-01

    A multispectral, multiresolution (MSMR) method is developed for analyzing scenes of overlapping cloud layers. The MSMR method is applied to data from the NOAA 11 advanced very high resolution radiometer (AVHRR) and the high-resolution infrared radiometer sounder (HIRS-2). The data are from a nighttime oceanic scene in which a semitransparent cirrus veil overlays a large-scale stratus cloud. Low-cloud and clear-sky radiances are determined using a spatial coherence technique. Middle to upper level cloud pressures and radiances are estimated from HIRS-2 15 micrometer CO2 band radiometric data. The MSMR method improves the interpretation of a nighttime, oceanic scene containing thin cirrus over a large-scale stratiform cloud. If, for example, the same scene is analyzed using only the AVHRR 10.8 micrometer channel, the accompanying retrieved cloud heights are found to be between the cirrus and stratus cloud heights and are incorrectly identified as midlevel altostratus clouds. Theoretical radiative transfer model results for both water droplet spheres and randomly oriented hexagonal ice crystals are compared to observed AVHRR brightness temperature differences (BTD) between the 3.7- and 10.8 micrometer channels (BTD(sup 34)) and between the 10.8- and 12- micrometer channels (BTD(sup 45)) to distinguish among the effects of cloud optical depth, particle size, and phase for both single-layer clouds and overlapping two-layer clouds. Theoretical BTD calculations are used to estimate the range of effective particle sizes for eac h cloud layer. The data for the cirrus in the case study region near Bermuda are consistent with theoretical results for relatively small randomly oriented hexagonal ice crystals. The observed BTD(sup 34) and BTD(sup 45) values are lower for the cirrus above a lower-level cloud than for single-level cirrus with no underlying cloud. In certain cases the BTD analysis provides a way to distinguish between clouds composed of supercooled water droplets

  6. Performance evaluation of Landsat 8 TIRS and the NOAA/METOP AVHRR sensors for lake surface water temperature retrieval

    NASA Astrophysics Data System (ADS)

    Lieberherr, Gian; Bur, Patrick; Wunderle, Stefan

    2016-04-01

    Lake surface water temperature (LSWT) is an important driver of lake ecosystems and it has been identified as an indicator of climate change. In-situ data for European lake water temperatures are very heterogeneous in terms of spatio-temporal coverage and retrieval methods. Satellite derived long term LSWT time series, as derived for example from the AVHRR sensor (since early 80ies), can serve as a baseline when merging different data sets. Another important advantage of satellite based temperature measurement is the representation of spatial temperature distribution within a waterbody. Focusing on spatial temperature distribution, the coarse resolutions of older sensors (1.1km for AVHRR sensor) is a limiting factor. Thus, during this study, the performance of LSWT retrieval from the TIRS sensor on the Landsat 8 platform was evaluated. The TIRS sensor has a resolution of 100m which allows to see small spatial temperature gradients, and it also offers the possibility to retrieve LSWT from smaller lakes where it was not possible with the AVHRR sensor. The temperature retrieval method used for both sensors was an optimized split window approach with lake specific and sensor specific coefficients. To validate and to evaluate the performance of the retrievals, the LSWT derived from Landsat 8 TIRS and from AVHRR where compared to each other, and also to different in-situ measurements. The accuracy of the temperature retrieval with the Landsat 8 sensor is shown to be generally better than with the AVHRR sensor. This is due to the higher resolution of the TIRS sensor, leading to lower contamination rate for individual pixels.

  7. Some practical aspects of lossless and nearly-lossless compression of AVHRR imagery

    NASA Technical Reports Server (NTRS)

    Hogan, David B.; Miller, Chris X.; Christensen, Than Lee; Moorti, Raj

    1994-01-01

    Compression of Advanced Very high Resolution Radiometers (AVHRR) imagery operating in a lossless or nearly-lossless mode is evaluated. Several practical issues are analyzed including: variability of compression over time and among channels, rate-smoothing buffer size, multi-spectral preprocessing of data, day/night handling, and impact on key operational data applications. This analysis is based on a DPCM algorithm employing the Universal Noiseless Coder, which is a candidate for inclusion in many future remote sensing systems. It is shown that compression rates of about 2:1 (daytime) can be achieved with modest buffer sizes (less than or equal to 2.5 Mbytes) and a relatively simple multi-spectral preprocessing step.

  8. BOREAS RSS-7 Regional LAI and FPAR Images From 10-Day AVHRR-LAC Composites

    NASA Technical Reports Server (NTRS)

    Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Chen, Jing; Cihlar, Josef

    2000-01-01

    The BOReal Ecosystem-Atmosphere Study Remote Sensing Science (BOREAS RSS-7) team collected various data sets to develop and validate an algorithm to allow the retrieval of the spatial distribution of Leaf Area Index (LAI) from remotely sensed images. Advanced Very High Resolution Radiometer (AVHRR) level-4c 10-day composite Normalized Difference Vegetation Index (NDVI) images produced at CCRS were used to produce images of LAI and the Fraction of Photosynthetically Active Radiation (FPAR) absorbed by plant canopies for the three summer IFCs in 1994 across the BOREAS region. The algorithms were developed based on ground measurements and Landsat Thematic Mapper (TM) images. The data are stored in binary image format files.

  9. Large-area relation of Landsat MSS and NOAA-6 AVHRR spectral data to wheat yields

    NASA Technical Reports Server (NTRS)

    Barnett, T. L.; Thompson, D. R.

    1983-01-01

    Landsat MSS data transformed into Kauth-Thomas greenness were averaged over 5 n.mi x 6 n.mi. sample segments from the U.S. Great Plains winter and spring wheat (Triticum aestivum) regions, and related by regression analysis to yields reported by county, crop reporting district (CRD) and state levels. Evidence of a linear relation between winter- and spring-wheat yields and Landsat spectral data at a broad scale is shown for 1978 and 1979. A common slope of about 1.6 (Bu/A)/unit greenness is discerned for the relation between yield and spectral greenness. Tests at both a smaller scale on sets of field-level spectal data and yield and at a large scale on 25 mi. x 25 mi. gridded spectral data from the NOAA-6 AVHRR sensor support the relation. The implications of these results to yield estimation from satellite spectral data are discussed.

  10. Error correction of the Normalized Difference Vegetation Index and Brightness Temperature calculated from the AVHRR observations

    NASA Astrophysics Data System (ADS)

    Rahman, Mohammed Zahidur

    This thesis investigates Normalized Difference Vegetation Index (NDVI) and Brightness Temperature (BT) stability in the NOAA/NESDIS Global Vegetation Index (GVI) data during 1982-2003. This data was collected from five NOAA series satellites. We have proposed to apply Empirical distribution function (EDF) to improve the stability of the NDVI and BT data derived from the AVHRR sensor on NOAA polar orbiting satellite. The instability of data results from orbit degradation as well as the circuit drifts over the life or a satellite. Degradation of NDVI and BT over time and shifts of NDVI and BT between the satellites was estimated China data set, for it includes a wide variety or different ecosystems represented globally. It was found that data for the years 1988, 1992, 1993, 1994, 1995 and 2000 are not stable enough compared to other years because of satellite orbit drift, AVHRR sensor degradation, and also Mt Pinatubo volcanic eruption in 1992. We assume data from NOAA-7(1982, 1983), NOAA-9 (1985, 1986), NOAA-11(1989, 1990), NOAA-14(1996, 1997), and NOAA-16 (2001, 2002) to be standard because theses satellite's equator crossing time falls between 1330 and 1500. Data from this particular period of the day maximized the value of coefficients. The crux of the proposed correction procedure consists of dividing standard year's data sets into two subsets. The subset 1(standard data correction sets) is used for correcting unstable years and then corrected data for this years compared with the standard data in the subset 2 (standard data validation sets). In this dissertation, we apply EDF to correct this deficiency of data for the affected years. We normalize or correct data by the method of empirical distribution functions compared with the standard. Using these normalized values, we estimate new NDVI and BT time series which provides NDVI and BT data for these years that match in subset 2 that is used for data validation.

  11. An efficient contextual algorithm to detect subsurface fires with NOAA/AVHRR data

    SciTech Connect

    Gautam, R.S.; Singh, D.; Mittal, A.

    2008-07-15

    This paper deals with the potential application of National Oceanic and Atmospheric Administration (NOAA)/Advanced Very High Resolution Radiometer (AVHRR) data to detect subsurface fire (subsurface hotspots) by proposing an efficient contextual algorithm. Although few algorithms based on the fixed-thresholding approach have been proposed for subsurface hotspot detection, however, for each application, thresholds have to be specifically tuned to cope with unique environmental conditions. The main objective of this paper is to develop an instrument-independent adaptive method by which direct threshold or multithreshold can be avoided. The proposed contextual algorithm is helpful to monitor subsurface hotspots with operational satellite data, such as the Jharia region of India, without making any region-specific guess in thresholding. Novelty of the proposed work lies in the fact that once the algorithmic model is developed for the particular region of interest after optimizing the model parameters, there is no need to optimize those parameters again for further satellite images. Hence, the developed model can be used for optimized automated detection and monitoring of subsurface hotspots for future images of the particular region of interest. The algorithm is adaptive in nature and uses vegetation index and different NOAA/AVHRR channel's statistics to detect hotspots in the region of interest. The performance of the algorithm is assessed in terms of sensitivity and specificity and compared with other well-known thresholding, techniques such as Otsu's thresholding, entropy-based thresholding, and existing contextual algorithm proposed by Flasse and Ceccato. The proposed algorithm is found to give better hotspot detection accuracy with lesser false alarm rate.

  12. Watershed Seasons

    ERIC Educational Resources Information Center

    Endreny, Anna

    2007-01-01

    All schools are located in "watersheds," land that drains into bodies of water. Some watersheds, like the one which encompasses the school discussed in this article, include bodies of water that are walking distance from the school. The watershed cited in this article has a brook and wetland within a several-block walk from the school. This…

  13. The sea surface temperature field in the Eastern Mediterranean from advanced very high resolution radiometer (AVHRR) data. Part II. Interannual variability

    NASA Astrophysics Data System (ADS)

    Marullo, S.; Santoleri, R.; Malanotte-Rizzoli, P.; Bergamasco, A.

    1999-04-01

    A ten-year dataset of AVHRR-SST (Sea Surface Temperature) with 18 km space resolution and weekly frequency has been analyzed in the Eastern Mediterranean. In Part I of the present study, we examined the seasonal variability of the basin and we defined the time and space scales of the monthly climatologies of the sea surface temperature distributions. A detailed and quantitative comparison was also carried out between the SST distribution of September 1987 and the surface temperature map of the corresponding hydrological survey of the POEM (Physical Oceanography of the Eastern Mediterranean) Programme. In this second part, we extend the analysis to examine and quantify the interannual variabilities. We summarize our results as follows. The analysis reveals the presence of an interannual cycle in the Ionian basin in the decade 1983-1992. The climatological pattern of the isotherms oscillates between two main states corresponding to the winter (zonal) and the summer (meridional) distributions. The apparent interannual cycle appears in the SST distribution only in winter and only in the Ionian basin, while the Levantine basin shows only fluctuations around the climatology. Thus, the interannual signal in our dataset is present but is much less important than the seasonal one. To confirm and quantify the above conclusions, we evaluate the Empirical Orthogonal Function of the SST time series. Gradient EOF's modes show the presence of a very strong yearly signal explaining 60% of the variance and a less intense seasonal signal that account for 16% of the variance. No interannual variability is represented by EOF gradient modes even though it can be observed in the increasing trend of the time varying amplitude of the first EOF mode. To observe the interannual variability signal, a seasonal temperature cycle was subtracted from each image instead of the ensemble (spatial) mean. A new EOF mode that accounts for 20% of the variance emerges between the first and second

  14. Analysis of trends in fused AVHRR and MODIS NDVI data for 1982-2006: Indication for a CO2 fertilization effect in global vegetation

    NASA Astrophysics Data System (ADS)

    Los, S. O.

    2013-04-01

    CO2 fertilization would be a large component of the land carbon sink. In the supporting information the RVI is used as a common standard to fuse MODIS and advanced very high resolution radiometer (AVHRR) NDVI data. This fusion compares well with SeaWiFS data.

  15. User's guide to image processing applications of the NOAA satellite HRPT/AVHRR data. Part 1: Introduction to the satellite system and its applications. Part 2: Processing and analysis of AVHRR imagery

    NASA Technical Reports Server (NTRS)

    Huh, Oscar Karl; Leibowitz, Scott G.; Dirosa, Donald; Hill, John M.

    1986-01-01

    The use of NOAA Advanced Very High Resolution Radar/High Resolution Picture Transmission (AVHRR/HRPT) imagery for earth resource applications is provided for the applications scientist for use within the various Earth science, resource, and agricultural disciplines. A guide to processing NOAA AVHRR data using the hardware and software systems integrated for this NASA project is provided. The processing steps from raw data on computer compatible tapes (1B data format) through usable qualitative and quantitative products for applications are given. The manual is divided into two parts. The first section describes the NOAA satellite system, its sensors, and the theoretical basis for using these data for environmental applications. Part 2 is a hands-on description of how to use a specific image processing system, the International Imaging Systems, Inc. (I2S) Model 75 Array Processor and S575 software, to process these data.

  16. 25 CFR 170.123 - What are seasonal transportation routes?

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 25 Indians 1 2012-04-01 2011-04-01 true What are seasonal transportation routes? 170.123 Section 170.123 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAND AND WATER INDIAN RESERVATION... § 170.123 What are seasonal transportation routes? Seasonal transportation routes are...

  17. 25 CFR 170.123 - What are seasonal transportation routes?

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 25 Indians 1 2014-04-01 2014-04-01 false What are seasonal transportation routes? 170.123 Section 170.123 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAND AND WATER INDIAN RESERVATION... § 170.123 What are seasonal transportation routes? Seasonal transportation routes are...

  18. Assess Calibration Consistency of MODIS and AVHRR Thermal Infrared Bands Using SNO Observations Corrected for Atmospheric Effects

    NASA Technical Reports Server (NTRS)

    Wu, Aisheng; Xie, Yong; Xiong, Xiaoxiong; Chu, I-Wen

    2012-01-01

    Monitoring environmental changes from space requires extremely well-calibrated observations to achieve the necessary high accuracy and stability. The calibration differences between the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Very High Resolution Radiometer (AVHRR) thermal bands provide a valuable quality assessment of the instrument performance. This letter compares the calibration differences between the Aqua MODIS and NOAA-18 AVHRR bands at 11.0 and 12.0 /Lm using simultaneous nadir overpass observations obtained in nearly parallel orbits. Impacts due to the relative spectral-response differences between the two sensors are estimated by MODTRAN simulations with real-time atmospheric profiles of temperature, water vapor, atmospheric pressure and ozone, and surface skin temperatures. Results show that the temperature difference after the removal of atmospheric impacts is within 0.30 K (or 0.40% in radiance) across the effective calibration range (or the 1l.0 l'm band/channel. For the 12.0 pm band, the differences are OAO K (or 0.50%) at the typical radiance and up to 0.70 K (or 0.90%) close to the maximum radiance, indicating an excellent calibration consistency between MODIS and AVHRR for both bands.

  19. Evidence for Phanerozoic reactivation of the Najd Fault System in AVHRR, TM, and SPOT images of central Arabia

    NASA Technical Reports Server (NTRS)

    Andre, Constance G.

    1989-01-01

    SPOT stereoscopic and TM multispectral images support evidence in AVHRR thermal-IR images of a major unmapped shear zone in Phanerozoic cover rocks southeast of the ancient Najd Fault System in the Arabian Shield. This shear zone and faults of the Najd share a common alignment, orientation, and sinistral sense of movement. These similarities suggest a 200-km extension of the Najd Fault System and reactivation since it formed in the late Precambrian. Topographic and lithologic features in the TM and SPOT data along one of three faults inferred from the AVHRR data indicate sinistral offsets up to 2.5 km, en echelon folds and secondary faults like those predicted by models of left-lateral strike-slip faulting. The age of the affected outcrops indicates reactivation of Najd faults in the Cretaceous, judging from TM and SPOT data or in the Tertiary, based on AVHRR data. The total length of the system visible at the surface measures 1300 km. If the Najd Fault System is extrapolated beneath sands of the Empty Quarter to faults of a similar trend in South Yemen, the shear zone would span the Arabian Plate. Furthermore, if extensions into the Arabian Sea bed and into Egypt proposed by others are considered, it would exceed 3000 km.

  20. Ash and ice clouds during the Mt Kelud February 2014 eruption as interpreted from IASI and AVHRR/3 observations

    NASA Astrophysics Data System (ADS)

    Kylling, Arve

    2016-05-01

    During the Mt Kelud February 2014 eruption the ash cloud was detectable on 13-14 February in the infrared with the reverse absorption technique by, for example, the Advanced Very High Resolution Radiometer (AVHRR/3). The Infrared Atmospheric Sounding Interferometer (IASI) observed the ash cloud also on 15 February when AVHRR did not detect any ash signal. The differences between ash detection with AVHRR/3 and IASI are discussed along with the reasons for the differences, supported by radiative transfer modelling. The effect of concurrent ice clouds on the ash detection and the ash signal in the IASI measurements is demonstrated. Specifically, a radiative transfer model is used to simulate IASI spectra with ash-only, with ice cloud only and with both ash and ice clouds. It is shown that modelled IASI spectra with ash and ice clouds reproduce the measured IASI spectra better than ash-only- or ice-only-modelled spectra. The ash and ice modelled spectra that best reproduce the IASI spectra contain about a factor of 12 less ash than the ash-only spectra that come closest to reproducing the measured spectra.

  1. Stratospheric aerosol perturbing effect on remote sensing of vegetation: Operational method for the correction of AVHRR composite NDVI

    SciTech Connect

    Vermote, E.; El Saleous, N.

    1995-12-31

    In this paper the authors present an operational stratospheric aerosol correction scheme adopted by the Laboratory for Terrestrial Physics, NASA/GSFC. The stratospheric aerosol distribution is assumed to be only variable with latitude. Each 9 days the latitudinal distribution of the optical thickness is computed by inverting radiances observed in AVHRR channel 1 (0.63 microns) and channel 2 (0.83 microns) over the Pacific Ocean. This radiance data set is used to check the validity of model used for inversion by checking consistency of the optical thickness deduced from each channel as well as optical thickness deduced from different scattering angles. The deduced optical thickness and spectral dependence are compared to Mauna Loa observation from 1991 to end of 1992 for validation. Using the optical thickness profile previously computed and radiative transfer code assuming lambertian boundary condition, each pixel of channel 1 and 2 are corrected prior to computation of NDVI. Comparison between corrected, non-corrected, and years prior to Pinatubo eruption (1989, 1990) NDVI composite, shows the necessity and the accuracy of the operational correction scheme. The same technique is applied to the afternoon satellite AVHRR archive (NOAA 7, 9, 11) from 1981 to 1993. The stratospheric profile derived over ocean shows that the El Chichon eruption was of less importance than Pinatubo. The stratospheric aerosol optical depth distribution computed from AVHRR data during the El Chichon period compared well to latitudinal monthly profile based on SAGE observations.

  2. Managing the Sneezing Season

    MedlinePlus

    ... Javascript on. Feature: Managing Allergies Managing the Sneezing Season Past Issues / Summer 2011 Table of Contents Seasonal ... Read More "Managing Allergies" Articles Managing the Sneezing Season / A Pollen Primer / Seasonal Allergies: Symptoms, Diagnosis, and ...

  3. Extension, validation, and analysis of the multi-decadal GACP/AVHRR aerosol optical thickness record

    NASA Astrophysics Data System (ADS)

    Mishchenko, M. I.; Geogdzhayev, I. V.

    2015-12-01

    The main product of the Global Aerosol Climatology Project (GACP) is a continuous record of the aerosol optical thickness (AOT) over the oceans based on channel-1 and -2 radiances from successively flown AVHRR instruments. We extend the previous GACP dataset by four years though the end of 2009 using NOAA-17 and -18 AVHRR data recalibrated against MODIS radiances according to Heidinger et al. (2010), thereby making the GACP record almost three decades long. The temporal overlap of the new NOAA-17 and the previous NOAA-16 record reveals an excellent agreement of the corresponding global monthly mean AOT values, thereby confirming the robustness of the vicarious radiance calibration used in the original GACP product. A comprehensive set of monthly mean AOT data from coastal and insular AERONET stations was used to validate GACP retrievals for the period 1995-2009. To put the GACP performance in broader perspective, we also compared AERONET and MODIS Aqua level-2 data for 2003-2009 using the same methodology. Monthly mean AOTs from the two over-the-ocean satellite datasets are well correlated with the ground-based values, the correlation coefficients being 0.81-0.85 for GACP and 0.74-0.79 for MODIS. Regression analyses demonstrated that the GACP mean AOTs are approximately 17%-27% lower than the AERONET values on average, while the MODIS mean AOTs are 5%-25% higher. The previously identified negative trend in the global GACP AOT which started in the late 1980s and continued into the early 2000s was confirmed. Its magnitude and duration indicate that it was caused by changes in tropospheric aerosols. The latest multi-satellite segment of the GACP record shows that this trend tapered off, with no noticeable AOT change after 2002. This result is consistent with the MODIS and MISR AOT records as well as with the recent gradual reversal from brightening to dimming revealed by surface flux measurements in many aerosol producing regions. Thus the robustness of the GACP

  4. ASTER/AVHRR Data Hybridization to determine Pyroclastic Flow cooling curves

    NASA Astrophysics Data System (ADS)

    Reath, K. A.; Wright, R.; Ramsey, M. S.

    2014-12-01

    Shiveluch Volcano (Kamchatka, Russia) has been in a consistent state of eruption for the past 15 years. During this period different eruption styles have been documented including: sub-plinian events, dome growth and collapse, and subsequent debris flow deposits. For example, on June 25-26, 2009 a pyroclastic debris flow was emplaced and the eruption onset that produced it was recorded by a series of seismic events spanning several hours. However, due to cloud cover, visual confirmation of the exact emplacement time was obscured. Orbital remote sensing was able to image the deposit repeatedly over the subsequent months. ASTER is a high spatial resolution (90m), low temporal resolution (2 - 4 days at the poles, 16 days at the equator) thermal infrared (TIR) sensor on the NASA Terra satellite. AVHRR is a high temporal resolution (minutes to several hours), low spatial resolution (1km) spaceborne TIR sensor on a series of NOAA satellites. Combined, these sensors provide a unique opportunity to fuse high-spatial and high-temporal resolution data to better observe changes on the surface of the deposit over time. For example, ASTER data were used to determine the flow area and to provide several data points for average temperature while AVHRR data were used to increase the amount of data points. Through this method an accurate average cooling rate over a three month period was determined. This cooling curve was then examined to derive several features about the deposit that were previously unknown. The time of emplacement and period of time needed for negligible thermal output were first determined by extrapolating the cooling curve in time. The total amount of heat output and total flow volume of the deposit were also calculated. This volume was then compared to the volume of the dome to calculate the percentage of collapse. This method can be repeated for other flow deposits to determine if there is a consistent correlation between the dome growth rate, the average

  5. Trends in Land Surface Phenologies Across Central Asia and the Central Eurasian Grain Belt as Viewed From MODIS Collection 5 NBAR

    NASA Astrophysics Data System (ADS)

    Wright, C. R.; Henebry, G. M.; Kovalskyy, V.; de Beurs, K. M.

    2008-12-01

    The disintegration of the Soviet Union in 1991 precipitated a multitude of institutional changes, including the disestablishment of a centrally-planned agricultural sector. Our previous work with AVHRR data has shown that among the environmental consequences were significant shifts in land surface phenologies (LSPs) across Kazakhstan, Uzbekistan, and Turkmenistan. Here we explored trends in LSPs across Central Asia and the central Eurasian Grain Belt that stretches westward across northern Kazakhstan and southern Russia into eastern Ukraine. We used the recently released of MODIS Collection 5 Nadir BRDF Adjusted Reflectance (NBAR) product and the Global Precipitation Climatology Centre (GPCC) Full Data Reanalysis v4, a monthly 0.5 degree product. We characterized trends from 2000-2007 using the nonparametric seasonal Mann- Kendall trend test on a per-pixel basis, thereby generating surfaces of per-pixel trend estimates with corresponding estimates of model uncertainty at each pixel. In the Pontic Steppe ecoregion of northwestern Kazakhstan, a region characterized by temperate grasslands, savannas, and shrublands, we found spatially coherent, highly significant (p<0.01) negative trends in MODIS NDVI. This appears to be driven by regional drought, and visual inspection of Landsat TM imagery from the study area indicates drying of relatively abundant depressional wetlands accompanied by a number of large fires over the period of interest. In the neighboring Kazakh Steppe ecoregion, a landscape dominated by small-grain production, we find similar, but noisier negative trends (typically p<0.05), likely reflecting a combination of drought and highly heterogeneous land use practices. By contrast, in the Central Asian Southern Desert ecoregion of Uzbekistan, we find highly significant (p<0.01) positive trends in NDVI from 2000-2007. These xeric shrublands are nearly entirely dependent on winter and spring precipitation for water inputs. GPCC trends indicate in some regions

  6. AVHRR imagery used to identify hurricane damage in a forested wetland of Louisiana

    USGS Publications Warehouse

    Ramsey, Elijah W., III; Chappell, D.K.; Baldwin, D.G.

    1997-01-01

    Certain events provide a unique opportunity to test the monitoring capability of AVHBR imagery. On 26 August 1992, Hurricane Andrew passed through Louisiana, impacting a large area of forested wetlands. One response to the widespread defoliation resulting from the hurricane impact was an abnormal bloom of new leaves and new growth in the underlying vegetation between September and October. To capture this atypical phenology, a time sequence of AVHRR images was transformed into a normalized difference vegetation index, NDVI, as an indicator of vegetation changes in the forest impacted by the passage of a hurricane. Using geographic information system functions, three sites in the impacted forest were vectorized as polygons, and the inclusive pixels were extracted for subsequent graphical and univariate statistical analysis. Temporal curves of mean NDVIs for the three sites for before, during, and after the hurricane passage, and aggregate curves of the impacted forest to an undisturbed forest, were compared. These comparisons corroborated the atypical phenology of the impacted forested wetland and directly related the cause to the hurricane passage.

  7. Potential for early warning of maalria in India using NOAA-AVHRR based vegetation health indices

    NASA Astrophysics Data System (ADS)

    Dhiman, R. C.; Kogan, Felix; Singh, Neeru; Singh, R. P.; Dash, A. P.

    Malaria is still a major public health problem in India with about 1 82 million cases annually and 1000 deaths As per World Health Organization WHO estimates about 1 3 million Disability Adjusted Life Years DALYs are lost annually due to malaria in India Central peninsular region of India is prone to malaria outbreaks Meteorological parameters changes in ecological conditions development of resistance in mosquito vectors development of resistance in Plasmodium falciparum parasite and lack of surveillance are the likely reasons of outbreaks Based on satellite data and climatic factors efforts have been made to develop Early Warning System EWS in Africa but there is no headway in this regard in India In order to find out the potential of NOAA satellite AVHRR derived Vegetation Condition Index VCI Temperature Condition Index TCI and a cumulative indicator Vegetation Health Index VHI were attempted to find out their potential for development of EWS Studies were initiated by analysing epidemiological data of malaria vis-a-vis VCI TCI and VHI from Bikaner and Jaisalmer districts of Rajasthan and Tumkur and Raichur districts of Karnataka Correlation coefficients between VCI and monthly malaria cases for epidemic years were computed Positive correlation 0 67 has been found with one-month lag between VCI and malaria incidence in respect of Tumkur while a negative correlation with TCI -0 45 is observed In Bikaner VCI is found to be negatively related -0 71 with malaria cases in epidemic year of 1994 Weekly

  8. Characteristics of the 1 km AVHRR data set for North America

    USGS Publications Warehouse

    Zhu, Z.-L.; Yang, L.

    1996-01-01

    The North America portion of a new global 1 km AVHRR time-series dataset was produced recently by the U.S. Geological Survey, EROS Data Center. Characteristics of the dataset were evaluated for scan-angle distribution, image area distortion as the result of map projection, distribution of high solar zenith angle, and cloud presence in image composites produced using maximum values of normalized difference vegetation index (NDVI). The evaluation showed that the compositing procedure exhibits a bias favouring off-nadir pixels, particularly at post-nadir (forward scanning) positions in the winter months. Results for scan angle distribution and image area distortion provide a basis for calculating the data's effective minimum mapping area for various geographical locations. The amount of missing data due to large solar zenith angle effect varies from 42 per cent in January to 1 per cent in July. Cloud contaminated pixels estimated for the thirty-six 10-day composites range from 7??5 per cent in May to 1??6 per cent in November. Recompositing the North America data set from 10-day cycles to monthly cycles can effectively reduce the amount of cloudy pixels in the data.

  9. Methodology for interpretation of SST retrievals using the AVHRR split window algorithm

    NASA Technical Reports Server (NTRS)

    Barbieri, R. W.; Mcclain, C. R.; Endres, D. L.

    1983-01-01

    Intercomparisons of sea surface temperature (SST) products derived from the operational NOAA-7 AVHRR-II algorithm and in situ observations are made. The 1982 data sets consist of ship survey data during the winter from the Mid-Atlantic Bight (MAB), ship and buoy measurements during April and September in the Gulf of Mexico and shipboard observations during April off the N.W. Spanish coast. The analyses included single pixel comparisons and the warmest pixel technique for 2 x 2 pixel and 10 x 10 pixel areas. The reason for using multi-pixel areas was for avoiding cloud contaminated pixels in the vicinity of the field measurements. Care must be taken when applying the warmest pixel technique near oceanic fronts. The Gulf of Mexico results clearly indicate a persistent degradation in algorithm accuracy due to El Chichon aerosols. The MAB and Spanish data sets indicate that very accurate estimates can be achieved if care is taken to avoid clouds and oceanic fronts.

  10. Vegetation monitoring and yield prediction from NOAA-AVHRR GAC data in the Argentinean Pampa

    NASA Astrophysics Data System (ADS)

    Kerdiles, Herve; Magrin, G.; Rebella, Cesar M.; Seguin, B.

    1995-01-01

    Ten years of NOAA GAC data over the Argentinean Pampa were analyzed in relation with climate and crop production. Correlations between crop yield and monthly NDVI (cumulated or not, weighted by the global radiation or not) reached 0.87 for wheat, 0.85 for soybean and 0.83 for corn, despite the classical limitations of AVHRR data (mixed response, atmospheric and directional noise, sensor calibration), the monthly frequency and the size of the test areas (10,000 km2). The quality of these results was partly due to the extensive character of the Pampa's cropping system since the correlation between final yield and NDVI relies on the following two hypothesis: NDVI can predict biomass and biomass is a good indicator of final grain yield. The best correlations were observed with the NDVI sensed at maximum green biomass, hence permitting yield estimations one to two months before harvest. Standard errors of regression were of 0.22, 0.17, and 0.63 t/ha for wheat, soybean, and maize respectively, for a mean yield around 1.7, 2.2, and 3.8 t/ha, respectively. Last, the complement between NDVI data and crop physiologically based models was examined. Despite the data related limitations, the relationship between CERES wheat predicted LAI and NOAA monthly GAC NDVI appeared as promising.

  11. Intercomparison Between in situ and AVHRR Polar Pathfinder-Derived Surface Albedo over Greenland

    NASA Technical Reports Server (NTRS)

    Stroeve, Julienne C.; Box, Jason E.; Fowler, Charles; Haran, Terence; Key, Jeffery

    2001-01-01

    The Advanced Very High Resolution (AVHRR) Polar Pathfinder Data (APP) provides the first long time series of consistent, calibrated surface albedo and surface temperature data for the polar regions. Validations of these products have consisted of individual studies that analyzed algorithm performance for limited regions and or time periods. This paper reports on comparisons made between the APP-derived surface albedo and that measured at fourteen automatic weather stations (AWS) around the Greenland ice sheet from January 1997 to August 1998. Results show that satellite-derived surface albedo values are on average 10% less than those measured by the AWS stations. However, the station measurements tend to be biased high by about 4% and thus the differences in absolute albedo may be less (e.g. 6%). In regions of the ice sheet where the albedo variability is small, such as the dry snow facies, the APP albedo uncertainty exceeds the natural variability. Further work is needed to improve the absolute accuracy of the APP-derived surface albedo. Even so, the data provide temporally and spatially consistent estimates of the Greenland ice sheet albedo.

  12. Cloud climatology in the Canary Islands region using NOAA-AVHRR data

    NASA Astrophysics Data System (ADS)

    González, Albano; Cerdeña, Abidán; Pérez, Juan C.; Díaz, Ana M.

    2007-10-01

    In this work a threshold technique for cloud detection and classification is applied to 9 years NOAA-AVHRR imagery in order to obtain a cloud climatology of the Canary Islands region (Northeast Atlantic Ocean). Once the clouds are classified, a retrieval method is used to estimate cloud macro- and micro-physical parameters, such as, effective particle size, optical thickness and top temperature. This retrieval method is based on the inversion of the simulated radiances obtained by a numerical radiative transfer model, libRadtran, using artificial neural networks (ANNs). The ANNs, whose architecture was based on Multilayer Perceptron model, were trained with simulated theoretical radiances using backpropagation with momentum method, and their architectures were optimized through genetic algorithms. The global procedure was performed for both day and night overpasses and, from a set of more than 9000 images, maps of relative frequency were calculated. These results were compared with ISCCP data for the 21-year period 1984-2004. The relationships between the retrieved cloud properties and some climate and atmospheric variables were also considered.

  13. Mapping landscape phenology preference of yellow-billed cuckoo with AVHRR data

    USGS Publications Warehouse

    Wallace, Cynthia S.A.; Villarreal, Miguel; Van Riper, Charles, III

    2013-01-01

    We mapped habitat for threatened Yellow-billed Cuckoo (Coccycus americanus occidentalis) in the State of Arizona using the temporal greenness dynamics of the landscape, or the landscape phenology. Landscape phenometrics were derived from Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) data for 1998 and 1999 by using Fourier harmonic analysis to analyze the waveform of the annual NDVI profile at each pixel. We modeled the spatial distribution of Yellow-billed Cuckoo habitat by coupling the field data of Cuckoo presence or absence and point-based samples of riparian and cottonwood-willow vegetation types with satellite phenometrics for 1998. Models were validated using field and satellite data collected in 1999. The results indicate that Yellow-billed Cuckoo occupy locations within their preferred habitat that exhibit peak greenness after the start of the summer monsoon and are greener and more dynamic than “average” habitat. Identification of preferred phenotypes within recognized habitat areas can be used to refine habitat models, inform predictions of habitat response to climate change, and suggest adaptation strategies.

  14. Condition of New Mexico rangelands derived from multi-year AVHRR imagery and associated spatial variables

    SciTech Connect

    Lancaster, J.; Wade, T.; Minor, T.

    1996-07-01

    The Desert Research Institute in cooperation with the Environmental Protection Agency Characterization Research Division, Las Vegas, has been evaluating indicators of rangeland health derived from remote sensing technology. The primary objective of this project was to determine the ability of multi-date remote sensing imagery to detect variation in vegetation productivity, as a potential indicator of ecosystem condition in the western U.S. The conterminous U.S. AVHRR biweekly composites were acquired from EROS Data Center for the six years 1989-1994. Normalized Difference Vegetation Index (NDVI) data for New Mexico were imported into a Geographical Information System. Using a digital vegetation map for the state, woodland and montane vegetation types were masked, leaving two grassland and four shrub-dominated vegetation classes. Average annual NDVI was calculated for each year, and a series of regression analysis were performed using 1989 as the reference year (independent variable), and each subsequent year as dependent variables. Outliers were identified as pixels two standard deviations from the calculated regression line, indicating 14 areas of change, three with lower productivity versus 1989, and 11 with higher productivity. Mining, military activity and irrigated agriculture were among the causes of change.

  15. Identifying environmental features for land management decisions

    NASA Technical Reports Server (NTRS)

    1984-01-01

    Multivariate statistical analysis and imaging processing techniques are being applied to the study of arid/semiarid environments, with emphasis on desertification. Field level indicators of land-soil biota degradation are being sifted out with staging up to the low aircraft reconnaissance level, to LANDSAT TM & MSS, and even to the AVHRR level. Three completed projects are reviewed: riparian habitat on the Humboldt River floodplain, Salt Lake County Urban expansion detection, and salinization/desertification detection in the delta area. Beginning projects summarized include: comparative condition of rangeland in Rush Valley; modeling a GIS/remote sensing data base for Cache County; universal soil loss equation applied to Pinyon-Juniper; relating MSS to ground radiometry near Battle Mountain; and riparian habitat mapping on Mary's River, Nevada.

  16. Application of principal component analysis and information fusion technique to detect hotspots in NOAA/AVHRR images of Jharia coalfield, India - article no. 013523

    SciTech Connect

    Gautam, R.S.; Singh, D.; Mittal, A.

    2007-07-01

    Present paper proposes an algorithm for hotspot (sub-surface fire) detection in NOAA/AVHRR images in Jharia region of India by employing Principal Component Analysis (PCA) and fusion technique. Proposed technique is very simple to implement and is more adaptive in comparison to thresholding, multi-thresholding and contextual algorithms. The algorithm takes into account the information of AVHRR channels 1, 2, 3, 4 and vegetation indices NDVI and MSAVI for the required purpose. Proposed technique consists of three steps: (1) detection and removal of cloud and water pixels from preprocessed AVHRR image and screening out the noise of channel 3, (2) application of PCA on multi-channel information along with vegetation index information of NOAA/AVHRR image to obtain principal components, and (3) fusion of information obtained from principal component 1 and 2 to classify image pixels as hotspots. Image processing techniques are applied to fuse information in first two principal component images and no absolute threshold is incorporated to specify whether particular pixel belongs to hotspot class or not, hence, proposed method is adaptive in nature and works successfully for most of the AVHRR images with average 87.27% detection accuracy and 0.201% false alarm rate while comparing with ground truth points in Jharia region of India.

  17. Inter-annual and seasonal trends of vegetation condition in the Upper Blue Nile (Abbay) basin: dual scale time series analysis

    NASA Astrophysics Data System (ADS)

    Teferi, E.; Uhlenbrook, S.; Bewket, W.

    2015-02-01

    A long-term decline in ecosystem functioning and productivity, often called land degradation, is a serious environmental and development challenge to Ethiopia that needs to be understood so as to develop sustainable land use strategies. This study examines inter-annual and seasonal trends of vegetation cover in the Upper Blue Nile (UBN) or Abbay basin. Advanced Very High Resolution Radiometer (AVHRR) based Global Inventory, Monitoring, and Modelling Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) was used for course scale long-term vegetation trend analysis. Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI data (MOD13Q1) was used for finer scale vegetation trend analysis. Harmonic analyses and non-parametric trend tests were applied to both GIMMS NDVI (1981-2006) and MODIS NDVI (2001-2011) data sets. Based on a robust trend estimator (Theil-Sen slope) most part of the UBN (~77%) showed a positive trend in monthly GIMMS NDVI with a mean rate of 0.0015 NDVI units (3.77% yr-1), out of which 41.15% of the basin depicted significant increases (P < 0.05) with a mean rate of 0.0023 NDVI units (5.59% yr-1) during the period. However, the finer scale (250 m) MODIS-based vegetation trend analysis revealed that about 36% of the UBN shows a significantly decreasing trend (P < 0.05) over the period 2001-2011 at an average rate of 0.0768 NDVI yr-1. This indicates that the greening trend of vegetation condition was followed by browning trend since the mid-2000s in the basin, which requires the attention of land users and decision makers. Seasonal trend analysis was found to be very useful in identifying changes in vegetation condition that could be masked if only inter-annual vegetation trend analysis was performed. The finer scale intra-annual trend analysis revealed trends that were more linked to human activities. This study concludes that integrated analysis of course and fine scale, inter-annual and intra-annual trends enables a more robust

  18. Seasonality of Arctic Mediterranean Exchanges

    NASA Astrophysics Data System (ADS)

    Rieper, Christoph; Quadfasel, Detlef

    2015-04-01

    The Arctic Mediterranean communicates through a number of passages with the Atlantic and the Pacific Oceans. Most of the volume exchange happens at the Greenland-Scotland-Ridge: warm and saline Atlantic Water flows in at the surface, cold, dense Overflow Water flows back at the bottom and fresh and cold Polar Water flows out along the East Greenland coast. All surface inflows show a seasonal signal whereas only the outflow through the Faroe Bank Channel exhibits significant seasonality. Here we present a quantification of the seasonal cycle of the exchanges across the Greenland-Scotland ridge based on volume estimates of the in- and outflows within the last 20 years (ADCP and altimetry). Our approach is comparatistic: we compare different properties of the seasonal cycle like the strength or the phase between the different in- and outflows. On the seasonal time scale the in- and outflows across the Greenland-Scotland-Ridge are not balanced. The net flux thus has to be balanced by the other passages on the Canadian Archipelago, Bering Strait as well as runoff from land.

  19. SST algorithms in ACSPO reanalysis of AVHRR GAC data from 2002-2013

    NASA Astrophysics Data System (ADS)

    Petrenko, B.; Ignatov, A.; Kihai, Y.; Zhou, X.; Stroup, J.

    2014-05-01

    In response to a request from the NOAA Coral Reef Watch Program, NOAA SST Team initiated reprocessing of 4 km resolution GAC data from AVHRRs flown onboard NOAA and MetOp satellites. The objective is to create a longterm Level 2 Advanced Clear-Sky Processor for Oceans (ACSPO) SST product, consistent with NOAA operations. ACSPO-Reanalysis (RAN) is used as input in the NOAA geo-polar blended Level 4 SST and potentially other Level 4 SST products. In the first stage of reprocessing (reanalysis 1, or RAN1), data from NOAA-15, -16, -17, -18, -19, and Metop-A and -B, from 2002-present have been processed with ACSPO v2.20, and matched up with quality controlled in situ data from in situ Quality Monitor (iQuam) version 1. The ~12 years time series of matchups were used to develop and explore the SST retrieval algorithms, with emphasis on minimizing spatial biases in retrieved SSTs, close reproduction of the magnitudes of true SST variations, and maximizing temporal, spatial and inter-platform stability of retrieval metrics. Two types of SST algorithms were considered: conventional SST regressions, and recently developed incremental regressions. The conventional equations were adopted in the EUMETSAT OSI-SAF formulation, which, according to our previous analyses, provide relatively small regional biases and well-balanced combination of precision and sensitivity, in its class. Incremental regression equations were specifically elaborated to automatically correct for model minus observation biases, always present when RTM simulations are employed. Improved temporal stability was achieved by recalculation of SST coefficients from matchups on a daily basis, with a +/-45 day window around the current date. This presentation describes the candidate SST algorithms considered for the next round of ACSPO reanalysis, RAN2.

  20. Operational surface UV radiation product from GOME-2 and AVHRR/3 data

    NASA Astrophysics Data System (ADS)

    Kujanpää, J.; Kalakoski, N.

    2015-10-01

    The surface ultraviolet (UV) radiation product, version 1.20, generated operationally in the framework of the Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M SAF) of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) is described. The product is based on the total ozone column derived from the measurements of the second Global Ozone Monitoring Experiment (GOME-2) instrument aboard EUMETSAT's polar orbiting meteorological operational (Metop) satellites. Cloud cover is taken into account by retrieving cloud optical depth from the channel 1 reflectance of the third Advanced Very High-Resolution Radiometer (AVHRR/3) instrument aboard both Metop in the morning orbit and Polar Orbiting Environmental Satellites (POES) of the National Oceanic and Atmospheric Administration (NOAA) in the afternoon orbit. In addition, more overpasses are used at high latitudes where the swaths of consecutive orbits overlap. The input satellite data are received from EUMETSAT's Multicast Distribution System (EUMETCast). The surface UV product includes daily maximum dose rates and integrated daily doses with different biological weighting functions, integrated ultraviolet B (UVB) and ultraviolet A (UVA) radiation, solar noon UV index and daily maximum photolysis frequencies of ozone and nitrogen dioxide at the surface level. The quantities are computed in a 0.5°×0.5° regular latitude-longitude grid and stored as daily files in the hierarchical data format (HDF5) within 2 weeks from sensing. The product files are archived in the O3M SAF distributed archive and can be ordered via the EUMETSAT Data Centre.

  1. Early evolution of a stratospheric volcanic eruption cloud as observed with TOMS and AVHRR

    USGS Publications Warehouse

    Schneider, D.J.; Rose, William I., Jr.; Coke, L.R.; Bluth, G.J.S.; Sprod, I.E.; Krueger, A.J.

    1999-01-01

    This paper is a detailed study of remote sensing data from the total ozone mapping spectrometer (TOMS) and the advanced very high resolution radiometer (AVHRR) satellite detectors, of the 1982 eruption of El Chicho??n, Mexico. The volcanic cloud/atmosphere interactions in the first four days of this eruption were investigated by combining ultraviolet retrievals to estimate the mass of sulfur dioxide in the volcanic cloud [Krueger et al., 1995] with thermal infrared retrievals of the size, optical depth, and mass of fine-grained (1-10 ??m radius) volcanic ash [Wen and Rose, 1994]. Our study provides the first direct evidence of gravitational separation of ash from a stratospheric, gas-rich, plinian eruption column and documents the marked differences in residence times of volcanic ash and sulfur dioxide in volcanic clouds. The eruption column reached as high as 32 km [Carey and Sigurdsson, 1986] and was injected into an atmosphere with a strong wind shear, which allowed for an observation of the separation of sulfur dioxide and volcanic ash. The upper, more sulfur dioxide-rich part of the cloud was transported to the west in the stratosphere, while the fine-grained ash traveled to the south in the troposphere. The mass of sulfur dioxide released was estimated at 7.1 ?? 109 kg with the mass decreasing by approximately 4% 1 day after the peak. The mass of fine-grained volcanic ash detected was estimated at 6.5 ?? 109 kg, amounting to about 0.7% of the estimated mass of the ash which fell out in the mapped ash blanket close to the volcano. Over the following days, 98% of this remaining fine ash was removed from the volcanic cloud, and the effective radius of ash in the volcanic cloud decreased from about 8 ??m to about 4 ??m. Copyright 1999 by the American Geophysical Union.

  2. Retrieval of aerosol optical properties over land using PMAp

    NASA Astrophysics Data System (ADS)

    Grzegorski, Michael; Munro, Rosemary; Lang, Ruediger; Poli, Gabriele; Holdak, Andriy

    2015-04-01

    The retrieval of aerosol optical properties is an important task for industry and climate forecasting. An ideal instrument should include observations with moderate spectral and high spatial resolutions for a wide range of wavelengths (from the UV to the TIR), measurements of the polarization state at different wavelengths and measurements of the same scene for different observation geometries. As such an ideal instrument is currently unavailable the usage of different instruments on one satellite platform is an alternative choice. Since February 2014, the Polar Multi sensor Aerosol product (PMAp) is delivered as operational GOME product to our customers. The algorithms retrieve aerosol optical properties over ocean (AOD, volcanic ash, aerosol type) using a multi-sensor approach (GOME, AVHRR, IASI). The next releases of PMAp will provide an extended set of aerosol and cloud properties which include AOD over land and an improved volcanic ash retrieval combining AVHRR and IASI. This presentation gives an overview on the existing product and the prototypes in development. The major focus is the discussion of the AOD retrieval over land implemented in the upcoming PMAp2 release. In addition, the results of our current validation studies (e.g. comparisons to AERONET, other satellite platforms and model data) are shown.

  3. Alpine Grassland Phenology as Seen in AVHRR, VEGETATION, and MODIS NDVI Time Series - a Comparison with In Situ Measurements

    PubMed Central

    Fontana, Fabio; Rixen, Christian; Jonas, Tobias; Aberegg, Gabriel; Wunderle, Stefan

    2008-01-01

    This study evaluates the ability to track grassland growth phenology in the Swiss Alps with NOAA-16 Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) time series. Three growth parameters from 15 alpine and subalpine grassland sites were investigated between 2001 and 2005: Melt-Out (MO), Start Of Growth (SOG), and End Of Growth (EOG). We tried to estimate these phenological dates from yearly NDVI time series by identifying dates, where certain fractions (thresholds) of the maximum annual NDVI amplitude were crossed for the first time. For this purpose, the NDVI time series were smoothed using two commonly used approaches (Fourier adjustment or alternatively Savitzky-Golay filtering). Moreover, AVHRR NDVI time series were compared against data from the newer generation sensors SPOT VEGETATION and TERRA MODIS. All remote sensing NDVI time series were highly correlated with single point ground measurements and therefore accurately represented growth dynamics of alpine grassland. The newer generation sensors VGT and MODIS performed better than AVHRR, however, differences were minor. Thresholds for the determination of MO, SOG, and EOG were similar across sensors and smoothing methods, which demonstrated the robustness of the results. For our purpose, the Fourier adjustment algorithm created better NDVI time series than the Savitzky-Golay filter, since latter appeared to be more sensitive to noisy NDVI time series. Findings show that the application of various thresholds to NDVI time series allows the observation of the temporal progression of vegetation growth at the selected sites with high consistency. Hence, we believe that our study helps to better understand large-scale vegetation growth dynamics above the tree line in the European Alps.

  4. 43 CFR 418.8 - Types of eligible land.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... and number of acres of eligible land irrigated in the Project. Possible irrigation of ineligible land... transfers are approved by the Nevada State Engineer. (c) Other eligible land. The Bureau will also identify eligible land that was not irrigated during the prior irrigation season....

  5. Free Delivery of a 30-YEAR Vegetation Product Archive by the Biopar Land Monitoring Core Service

    NASA Astrophysics Data System (ADS)

    Pacholczyk, P.; Makhmara, H.; Lacaze, R. N.; Baret, F.; Weiss, M.; Verger, A.

    2012-12-01

    Geoland2 project is part of the GMES EU-lead initiative and intends to prepare, validate and demonstrate pre-operational service chains and products of the Land Monitoring Core Service. The BioPar Core Monitoring Service distributes through the Geoland 2 portal global products related to biophysical variables : the Leaf Area Index (LAI), the Fraction of green Vegetation Cover (FCover), the fraction of absorbed photosynthetically active radiation (FAPAR) and the Normalized Differential Vegetation Index (NDVI). Long term global biophysical products are of great interest for earth science modeling applications and global change monitoring. Since end of 2011 a 12-year archive (1999-2011) of these biophysical vegetation products derived from SPOT/VEGETATION sensor, called GEOV1_VGT, is available and is continuously updated every ten days. Since this summer, a 20-year archive (1981-2000) of LAI, FAPAR and FCover biophysical vegetation products derived from the AVHRR long term data archive, called GEOV1_AVHRR, has been processed by CNES and is now available through the Geoland 2 portal. The LAI, FAPAR and FCover products issued from VGT and AVHRR data have the same characteristics (temporal resolution 10 days, global coverage) except for the spatial resolution (1/112° for VGT and 0.05° for AVHRR), with an overlap of two years (1999-2000). The evaluation of GEOV1_VGT and GEOV1_AVHRR archive indicates a very good agreement between the two datasets, including a similar level of accuracy in comparison with ground-based measurements made during the 1999-2000 overlap period. Despite that a more consistent 30-year global product at a lower resolution is very useful for communities studying carbon cycle, climate or water cycle. The last step, foreseen for this Autumn, is to process these two archives and to provide to the users a continuous 30-year vegetation product (called GEOV1_GCM) at 0.5° scale. Close to its end the BioPar project has provided demonstration products

  6. Satellite derived 30-year trends in terrestrial frozen and non-frozen seasons and associated impacts to vegetation and atmospheric CO2

    NASA Astrophysics Data System (ADS)

    Kim, Y.; Kimball, J. S.; McDonald, K. C.; Glassy, J. M.

    2010-12-01

    Approximately 66 million km2 (52.5 %) of the global vegetated land area experiences seasonally frozen temperatures as a major constraint to ecosystem processes. The freeze-thaw (F/T) status of the landscape as derived from satellite microwave remote sensing is closely linked to surface energy budget and hydrological activity, vegetation phenology, terrestrial carbon budgets and land-atmosphere trace gas exchange. We utilized a seasonal threshold algorithm based temporal change classification of 37GHz frequency, vertically polarized brightness temperatures (Tb) from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) pathfinder and Special Sensor Microwave Imager (SSM/I) to classify daily F/T status for all global land areas where seasonal frozen temperatures are a major constraint to ecosystem processes. A temporally consistent, long-term (30 year) daily F/T record was created by pixel-wise correction of the SMMR Tb record based on empirical analyses of overlapping SMMR and SSM/I measurements acquired during 1987. The resulting combined F/T record was validated against in situ temperature measurements from the global weather station network and applied to quantify regional patterns and trends in timing and length of frozen and non-frozen seasons. The F/T results were compared against other surrogate measures of biosphere activity including satellite AVHRR (GIMMS) based vegetation greenness (NDVI) and atmospheric CO2 concentrations over northern (>50N) land areas. The resulting F/T record showed mean annual classification accuracies of 91 (+/-1.0) and 84 (+/- 0.9) percent for PM and AM overpass retrievals relative to in situ weather station records. The F/T record showed significant (P=0.008) long-term trends in non-frozen period (0.207 days/yr) that were largely driven by earlier onset of spring thaw (-0.121 days/yr) and a small, delayed trend the arrival of the frozen period (0.107 days/yr). These results coincide with 0.025 C/yr warming trends in

  7. Fusion of Noaa-avhrr Imagery and Gis-techniques To Derive Sub-scale Landcover Information For Water Balance Modeling In The Upper Danube Watershed

    NASA Astrophysics Data System (ADS)

    Probeck, M.; Ludwig, R.; Mauser, W.

    Earth observation from space provides unique data to obtain up-to-date information on the rapidly changing state of the environment. While imagery from high resolution sensors are still inadequate to derive landuse information for mesoscale areas, fine spatial resolution of landuse heterogeneity is essential for the description of hydrolog- ical processes at the landscape level, such as runoff generation and evapotranspiration. The present method overcomes existing limitations by using coarse resolution NOAA- AVHRR data within a fuzzy-logic based framework of combined multitemporal im- agery and geospatial data analysis. The unmixing methodology determines fractional land cover data for each pixel, assuming that the spectrum of a surface is linearly com- posed of the area-weighted spectra of its known components (endmembers). In order to minimize classification errors, geographical expert knowledge is utilized to evaluate the geofactors elevation, slope, soil and precipitation in a fuzzy-logic approach to pri- orily determine a valid set of possible endmembers for each raster-cell. In extension to existing unmixing approaches, each spectrum refers to a multitemporal spectral pro- file of each pixel, which consists of the temporal development of the pixel`s spectral behaviour over an entire vegetation period. The results of the classification technique are validated against both a reference classification from LANDSAT-TM imagery and the CORINE land cover classification. The method is employed for the Upper Danube watershed (~ 77.000 km2) to provide landuse information, which is used as an input for the physically based SVAT-model PROMET (Mauser &Schädlich 1997, Strasser &Mauser 2001). The model is operated in hourly time steps on a 1 km2-grid, each raster cell comprising the various landcover classes, to simulate the spatial and tempo- ral course of evapotranspiration, soil moisture, snow and runoff formation. Sensitivity analysis of event based modelings as well

  8. Dynamic Land Surface Classifcations using Microwave Frequencies

    NASA Astrophysics Data System (ADS)

    Jackson, H.; Tian, Y.; Peters-Lidard, C. D.; Harrison, K. W.

    2014-12-01

    Land surface emissivity in microwave frequencies is critical to the remote sensing of soil moisture, precipitation, and vegetation. Different land surfaces have different spectral signatures in the microwave portions of the electromagnetic spectrum. Their spatial and temporal behaviors are also highly variable. These properties are yet not well understood in microwave frequencies, despite their capability in detecting water-related variables in the atmosphere and land surface. A classification scheme was developed to stratify the Earth's land surfaces based on their seasonally dynamic microwave signatures. An unsupervised clustering approach was used identify and distinguish data groupings along two microwave based indicies. Land surface data clusters were mapped to determine their spatial relationships to known land cover groupings. Differences in land surface clusters were analyzed in their spatial consistency and their direction and magnitude of land surface change. It was found that vegetation and topography were the predominant contributors to change between seasons. Land surface extremes of sandy desert and closed canopy tropical forest displayed minimal intra-annual variability while transitional zones, such as the Sahel and North American temperate forests, exhibited the most variability. Distinct microwave signatures varied between seasons along a latittudinal gradient. Overall variability in land surface types increased at high lattitudes. This classification will help inform research studies maniputlating the microwave frequencies of the electromagnetic spectrum to better characterize land surface dynamics, and will be very useful in the validation of radiative transfer models and quantification of uncertainty in global precipitation monitoring.

  9. An improved RST approach for timely alert and Near Real Time monitoring of oil spill disasters by using AVHRR data

    NASA Astrophysics Data System (ADS)

    Grimaldi, C. S. L.; Casciello, D.; Coviello, I.; Lacava, T.; Pergola, N.; Tramutoli, V.

    2011-05-01

    Information acquired and provided in Near Real Time is fundamental in contributing to reduce the impact of different sea pollution sources on the maritime environment. Optical data acquired by sensors aboard meteorological satellites, thanks to their high temporal resolution as well as to their delivery policy, can be profitably used for a Near Real Time sea monitoring, provided that accurate and reliable methodologies for analysis and investigation are designed, implemented and fully assessed. In this paper, the results achieved by the application of an improved version of RST (Robust Satellite Technique) to oil spill detection and monitoring will be shown. In particular, thermal infrared data acquired by the NOAA-AVHRR (National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer) have been analyzed and a new RST-based change detection index applied to the case of the oil spills that occurred off the Kuwait and Saudi Arabian coasts in January 1991 and during the Lebanon War in July 2006. The results obtained, even in comparison with those achieved by other AVHRR-based techniques, confirm the unique performance of the proposed approach in automatically detecting the presence of oil spill with a high level of reliability and sensitivity. Moreover, the potential of the extension of the proposed technique to sensors onboard geostationary satellites will be discussed within the context of oil spill monitoring systems, integrating products generated by high temporal (optical) and high spatial (radar) resolution satellite systems.

  10. Climate Sensitivity Studies of the Greenland Ice Sheet Using Satellite AVHRR, SMMR, SSM/I and in Situ Data

    NASA Technical Reports Server (NTRS)

    Steffen, K.; Abdalati, W.; Stroeve, J.

    1993-01-01

    The feasibility of using satellite data for climate research over the Greenland ice sheet is discussed. In particular, we demonstrate the usefulness of Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage (LAC) and Global Area Coverage (GAC) data for narrow-band albedo retrieval. Our study supports the use of lower resolution AVHRR (GAC) data for process studies over most of the Greenland ice sheet. Based on LAC data time series analysis, we can resolve relative albedo changes on the order of 2-5%. In addition, we examine Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) passive microwave data for snow typing and other signals of climatological significance. Based on relationships between in situ measurements and horizontally polarized 19 and 37 GHz observations, wet snow regions are identified. The wet snow regions increase in aerial percentage from 9% of the total ice surface in June to a maximum of 26% in August 1990. Furthermore, the relationship between brightness temperatures and accumulation rates in the northeastern part of Greenland is described. We found a consistent increase in accumulation rate for the northeastern part of the ice sheet from 1981 to 1986.

  11. Calibration of the Visible and Near-Infrared Channels of the Advanced Very High Resolution Radiometer (AVHRR) After Launch

    NASA Technical Reports Server (NTRS)

    Rao, C. R. Nagaraja; Chen, Jianhua

    1993-01-01

    The relative degradation in time of the visible(channel 1: approx.0.58-0.6 microns) and near-infrared(channel 2: approx. O.72-1.1 microns) channels of the Advanced Very High Resolution Radiometer(AVHRR), onboard the NOAA Polar-orbiting Operational Environmental Satellites(POES), has been determined, using the southeastern Libyan desert(21-23 deg N latitude; 28- 29 deg E longitude) as a time-invariant calibration target. A statistical procedure was used on the reflectance data for the two channels from the B3 data of the International Satellite Cloud Climatology Project(ISCCP) to obtain the degradation rates for the AVERRs on NOAA-7, -9, and -11 spacecraft. The degradation rates per year for channels 1 and 2 are respectively: 3.6% and 4.3%(NOAA-7); 5.9% and 3.5%(NOAA-9); and 1.2% and 2.0%(NOAA-11). The use of the degradation rates thus determined, in conjunction with 'absolute' calibrations obtained from congruent aircraft and satellite measurements, in the development of correction algorithms is illustrated with the AVHRR on the NOAA-9 spacecraft.

  12. A 30-Year Multi-Sensor Vegetation Index and Land Surface Phenology Data Record: Methods Challenges and Potentials

    NASA Astrophysics Data System (ADS)

    Didan, K.; Barreto-munoz, A.; Miura, T.; Tsend-Ayush, J.

    2013-12-01

    During the last five years the Vegetation Index and Phenology Lab. (vip.arizona.edu) embarked on an effort to process a global multi-sensor Earth Science Data Record of NDVI, EVI2, and land surface Phenology. Data from AVHRR, MODIS, and SPOT-VGT, covering the period 1981 to present, were processed into a seamless and sensor independent record using a suite of community algorithms for data filtering, across-sensor continuity, Vegetation Index (NDVI and EVI2), land surface Phenology, and spatial and temporal gap filling. Currently at Version 3.0 these ESDRs are suitable for the study of land surface vegetation dynamics, long term change and trends, anomalies, and can support various ecosystem and climate modeling efforts by providing key parameters. While adapting the various algorithms to processing this new data record many challenges emerged, ranging from excessive missing and poor quality data to complex and temporally dependent divergence across the various sensors making continuity quite difficult. The first step to addressing these challenges was the adoption of very strict and low tolerance to noise data filters, where the intrinsic input data quality is used along with the long term expected dynamic range to screen for outliers and poor quality. A sophisticated and explicit per-pixel and seasonally dependent across-sensor translation algorithm was developed to address the continuity more properly. To generate the land surface phenology we adapted various community algorithms to work with and take advantage of this new record. Both the standard MODIS Vegetation dynamic algorithm and an in-house homogeneous cluster algorithm were applied to the data. We've also completed a spatially and temporally explicit error and uncertainty characterization of this record. Results indicate a VI error in the range of 5-10% VI units and a 5-40 days error in the date dependent phenology parameters, with an average error of 15 days. This VIP record accounts now for more than

  13. Operational surface UV radiation product from GOME-2 and AVHRR/3 data

    NASA Astrophysics Data System (ADS)

    Kujanpää, J.; Kalakoski, N.

    2015-05-01

    The surface ultraviolet (UV) radiation product, version 1.20, generated operationally in the framework of the Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M SAF) of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) is described. The product is based on the total ozone column derived from the measurements of the second Global Ozone Monitoring Experiment (GOME-2) instrument aboard EUMETSAT's polar orbiting meteorological operational (Metop) satellites. The input total ozone product is generated by the German Aerospace Center (DLR) also within the O3M SAF framework. Polar orbiting satellites provide global coverage but infrequent sampling of the diurnal cloud cover. The diurnal variation of the surface UV radiation is extremely strong due to modulation by solar elevation and rapidly changing cloud cover. At the minimum, one sample of the cloud cover in the morning and another in the afternoon are needed to derive daily maximum and daily integrated surface UV radiation quantities. This is achieved by retrieving cloud optical depth from the channel 1 reflectance of the third Advanced Very High Resolution Radiometer (AVHRR/3) instrument aboard both Metop in the morning orbit (daytime descending node around 09:30 LT) and Polar Orbiting Environmental Satellites (POES) of the National Oceanic and Atmospheric Administration (NOAA) in the afternoon orbit (daytime ascending node around 14:30 LT). In addition, more overpasses are used at high latitudes where the swaths of consecutive orbits overlap. The input satellite data are received from EUMETSAT's Multicast Distribution System (EUMETCast) using commercial telecommunication satellites for broadcasting the data to the user community. The surface UV product includes daily maximum dose rates and integrated daily doses with different biological weighting functions, integrated UVB and UVA radiation, solar noon UV Index and daily maximum photolysis

  14. Cloud Masking and Surface Temperature Distribution in the Polar Regions Using AVHRR and other Satellite Data

    NASA Technical Reports Server (NTRS)

    Comiso, Joey C.

    1995-01-01

    Surface temperature is one of the key variables associated with weather and climate. Accurate measurements of surface air temperatures are routinely made in meteorological stations around the world. Also, satellite data have been used to produce synoptic global temperature distributions. However, not much attention has been paid on temperature distributions in the polar regions. In the polar regions, the number of stations is very sparse. Because of adverse weather conditions and general inaccessibility, surface field measurements are also limited. Furthermore, accurate retrievals from satellite data in the region have been difficult to make because of persistent cloudiness and ambiguities in the discrimination of clouds from snow or ice. Surface temperature observations are required in the polar regions for air-sea-ice interaction studies, especially in the calculation of heat, salinity, and humidity fluxes. They are also useful in identifying areas of melt or meltponding within the sea ice pack and the ice sheets and in the calculation of emissivities of these surfaces. Moreover, the polar regions are unique in that they are the sites of temperature extremes, the location of which is difficult to identify without a global monitoring system. Furthermore, the regions may provide an early signal to a potential climate change because such signal is expected to be amplified in the region due to feedback effects. In cloud free areas, the thermal channels from infrared systems provide surface temperatures at relatively good accuracies. Previous capabilities include the use of the Temperature Humidity Infrared Radiometer (THIR) onboard the Nimbus-7 satellite which was launched in 1978. Current capabilities include the use of the Advance Very High Resolution Radiometer (AVHRR) aboard NOAA satellites. Together, these two systems cover a span of 16 years of thermal infrared data. Techniques for retrieving surface temperatures with these sensors in the polar regions have

  15. Probabilistic approach to cloud and snow detection on Advanced Very High Resolution Radiometer (AVHRR) imagery

    NASA Astrophysics Data System (ADS)

    Musial, J. P.; Hüsler, F.; Sütterlin, M.; Neuhaus, C.; Wunderle, S.

    2014-03-01

    Derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. Information about a confidence level of provided physical quantities is required to construct an error budget of higher-level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data a common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher-level products and may alter their usability. Within this scope a novel probabilistic cloud mask (PCM) algorithm suited for the 1 km × 1 km Advanced Very High Resolution Radiometer (AVHRR) data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clear-sky/snow conditions. As opposed to the majority of available techniques which are usually based on the decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve probability estimates from the precomputed look-up tables (LUTs). Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of intervals. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the invariant coordinate system (ICS) transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the Polar Platform System (PPS) version 2012 and Moderate Resolution Imaging

  16. Daytime Land Cloud Detection Enhancements For The VIIRS Cloud Mask

    NASA Astrophysics Data System (ADS)

    Frey, R. A.; Heidinger, A. K.; Hutchinson, K. D.; Iisager, B.

    2005-12-01

    The first in a new series of polar-orbiting satellites, National Polar-Orbiting Operational Satellite System (NPOESS), is scheduled to be launched in 2008. The Visible/Infrared Imager/Radiometer Suite (VIIRS) is a major component of the series and will replace the AVHRR instrument on operational polar orbiters. A crucial piece of the VIIRS data processing chain is the VIIRS Cloud Mask (VCM). A high quality cloud detection system is necessary as a first step for most if not all of the algorithms which produce the 18 EDRs (Environmental Data Records) from VIIRS. A cloud detection scheme similar to the one developed for MODIS data (MOD35) will be implemented for VIIRS, but several enhancements have been investigated for daytime land scenes. During daylight hours over vegetated surfaces and in the absence of snow cover, use of the high contrast between clouds and surface in visible wavelengths offers the most sensitive clear/cloud discrimination. However, visible surface reflectances vary from about 10% over tropical rain forests to as high as 50% in arid regions, making the use of a single cloud test threshold very difficult. A set of reflectance thresholds based on NDVI and scattering angle has been developed from historical AVHRR data. Clear-sky NDVIs were accumulated as a function of scattering angle over a multi-year period and from morning and afternoon satellites, from which cloud test thresholds were developed. The thresholds were then tested on several AVHRR scenes. For extremely arid scenes, where visible reflectances from clouds and surface are similar, a cloud test using 0.4 μm data has been devised. This poster describes the development of both new cloud tests and associated thresholds, from initial tests using MODIS data to the calculation and implementation of the thresholds.

  17. Satellite and ground-based observations of patterns and seasonality of sea-ice, summer warmth, snow, and NDVI along the North America and Eurasia Arctic transects

    NASA Astrophysics Data System (ADS)

    Walker, D. A.; Epstein, H. E.; Raynolds, M. K.; Bhatt, U. S.; Bieniek, P. A.

    2011-12-01

    We analyzed vegetation, climate, and spectral data from zonal sites along two >1500 km long transects that span all five Arctic bioclimate subzones in North America and Eurasia to help interpret the long-term changes in satellite-derived trends of pattern and seasonality of vegetation greenness. Despite large differences in environment and vegetation along the two transects, there is nearly an identical logarithmic relationship between biomass and the summer maximum normalized difference vegetation index derived from AVHRR sensors (MaxNDVI) along the two transects. Summer open water in the Northern Alaska/Beaufort Sea region has increased by 39%, the summer warmth index (SWI) of the tundra increased by 14%, MaxNDVI by 28% and time-integrated NDVI (TI-NDVI) by 21%. The increased open water in the Beaufort is associated with a warming of the land and a large positive increase in the NDVI. In the eastern Kara Sea/Yamal Peninsula region, summer-fall open water has increased by 115%, the SWI decreased by -3%, MaxNDVI increased by only 6%, and TI-NDVI by 2%. The greatly reduced sea ice has affected the summer total warmth and NDVI of the Eurasia transect minimally possibly due to increased winter snow and delayed snowmelt in much of northwest Russian Arctic. In northern Alaska, there is distinctive trend of earlier snow melt at most stations; whereas the northern Yamal has seen an increase in the snow water equivalent and delayed melt on much of the Yagorsky, Yamal, Gydan, and Taimyr peninsulas. This appears to be associated with the reduction in the total summer warmth and relatively small increase in NDVI.

  18. Assessment of Digital Land Cover Maps for Hydrological Modeling in the Yampa River Basin, Colorado, USA

    NASA Astrophysics Data System (ADS)

    Repass, J. M.; Fassnacht, S.; Reich, R.

    2004-12-01

    Land cover data are required to parameterize watersheds for hydrological modeling. There is a multitude of different land cover maps, and determining which input data map for the model can be unclear. The goal of this study is to quantify the differences between various publically available land cover maps to determine their relative suitability for hydrological modeling of the Yampa River Basin in northern Colorado. The land cover maps compared in this study are derived from Advanced Very High Resolution Radiometer (AVHRR), Landsat Thematic Mapper (TM), and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. These maps are compared to a 30-m land cover map modeled from ground data and MODIS imagery. This map is regarded as "truth" in this investigation due to its fine resolution and use of recent ground data and imagery, and will be used to rank publicly available AVHRR and MODIS land cover maps. In order to compare the different land cover products, all data must be degraded to the coarsest spatial resolution (1 km) and the coarsest species resolution. Once this is accomplished, the maps are compared on 4 levels. The 4 comparisons are based on: (i) the relative agreement of the total aggregated land class percentages for the 1-km data present after the data has been cross-walked; (ii) pixel accuracy; (iii) scene accuracy; and (iv) cumulative streamflow model output from the US Geological Survey Precipitation-Runoff Modeling System (PRMS) in relation to observed cumulative streamflow. The results determine the best input land cover data for modeling streamflow in the Yampa River Basin, and provide information about the required spatial, spectral, and classification resolution of these maps to optimize results for streamflow modeling.

  19. 43 CFR 413.3 - Assessment of settlement lands.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ..., DEPARTMENT OF THE INTERIOR ASSESSMENT BY IRRIGATION DISTRICTS OF LANDS OWNED BY THE UNITED STATES, COLUMBIA... thereafter contracts to sell or exchange such lands before the end of the irrigation season following the... the water service which will be available to the purchaser during that irrigation season or...

  20. 43 CFR 413.3 - Assessment of settlement lands.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ..., DEPARTMENT OF THE INTERIOR ASSESSMENT BY IRRIGATION DISTRICTS OF LANDS OWNED BY THE UNITED STATES, COLUMBIA... thereafter contracts to sell or exchange such lands before the end of the irrigation season following the... the water service which will be available to the purchaser during that irrigation season or...

  1. 43 CFR 413.3 - Assessment of settlement lands.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ..., DEPARTMENT OF THE INTERIOR ASSESSMENT BY IRRIGATION DISTRICTS OF LANDS OWNED BY THE UNITED STATES, COLUMBIA... thereafter contracts to sell or exchange such lands before the end of the irrigation season following the... the water service which will be available to the purchaser during that irrigation season or...

  2. Variation and Trends of Landscape Dynamics, Land Surface Phenology and Net Primary Production of the Appalachian Mountains

    SciTech Connect

    Wang, Yeqiao; Zhao, Jianjun; Zhou, Yuyu; Zhang, Hongyan

    2012-12-15

    The gradients of the Appalachian Mountains in elevations and latitudes provide a unique regional perspective of landscape variations in the eastern United States and a section of the southeastern Canada. This study reveals patterns and trends of landscape dynamics, land surface phenology and ecosystem production along the Appalachian Mountains using time series data from Global Inventory Modeling and Mapping Studies (GIMMS) and AVHRR Global Production Efficiency Model (GloPEM) datasets. We analyzed the spatial and temporal patterns of Normalized Difference Vegetation Index (NDVI), length of growing season (LOS) and net primary production (NPP) of selected ecoregions along the Appalachian Mountains regions. We compared the results out of the Appalachian Mountains regions in different spatial contexts including the North America and the Appalachian Trail corridor area. To reveal latitudinal variations we analyzed data and compared the results between 30°N-40°N and 40°N-50°N latitudes. The result revealed significant decreases in annual peak NDVI in the Appalachian Mountains regions. The trend for the Appalachian Mountains regions was -0.0018 (R2=0.55, P<0.0001) NDVI unit decrease per year during 25 years between 1982 and 2006. The LOS had prolonged 0.3 day yr-1 during 25 years over the Appalachian Mountains regions. The NPP increased by 2.68 gC m-2yr-2 in Appalachian Mountains regions from 1981 to 2000. The comparison with the North America reveals the effects of topography and ecosystem compositions of the Appalachian Mountains. The comparison with the Appalachian Trail corridor area provides a regional mega-transect view of the measured variables.

  3. Changes in land surface albedo in response of climate change and human activities

    NASA Astrophysics Data System (ADS)

    Liang, S.

    2013-05-01

    Our Earth's environment is experiencing rapid changes due to natural variability and human activities. Albedo is an important indicator of the changes in land surface properties. This presentation will consist of two parts. The first part is on our efforts for generating global long-term high-quality land surface albedo products. In the past few years, we have been actively working on estimation of land surface albedo from multiple satellite data, such as AVHRR, MODIS, and VIIRS. One of our key products is the Global Land Surface Satellite (GLASS) albedo product from both AVHRR (1981-1999) and MODIS (2000-2010) data at 1-5km spatial and 8-day temporal resolutions. The projects, algorithm development, and product validation would be outlined. The second part will be on spatiotemporal analysis of global albedo changes and their attributions. The emphasis will be on the regional "hotspots", such as Greenland, Tibetan plateau, and northern China where albedo changes are associated with climate change, drought, forest fires, reforestation and afforestation, and agricultural irrigation.

  4. The contribution of Remote Sensing to the Indian Land Surface Processes Experiment (LASPEX)

    NASA Astrophysics Data System (ADS)

    Gupta, R.; Vijayan, D.; Prasad, T.

    During the conduct of the Indian Land Surface Processes (LSP) Experiment (LASPEX) in Sabarmati river basin, tower based measurements for wind, temperature and humidity fields were collected over 5 locations with primary and intensive ground based observations at Anand, Gujarat. Remote sensing component consisted of (a) ground based measurements of spectral radiances in 3 nm bandwidth (hyperspectral) in visible through near IR region; in blue, green, red and near IR bands of IRS LISS and LANDSAT TM; leaf area index (LAI); crop and air temperatures over Anand site; (b) crop distribution information in Anand -Kandha - Derol region to relate with satellite based measurements in 36,72,188 and 1100 m spatial resolutions. Fourth order polynomial fit was observed between LAI and spectral vegetation indices for wheat. By convolving respective filter functions with 3 nm bandwidth measurements, NDVI for bandwidths corresponding to TM and AVHRR were found to be correlated with r' in 0.96 - 0.99 range, and higher value observed for AVHRR NDVI was related to additional 725 - 760 nm bandwidth in AVHRR near IR band. Hyperspectral index defined by (R77 7-R747 )/R 673 , Rrefers to reflectance in wavelength centered at , was useful in discriminating low evapotranspiration (ET) chickpea and high ET wheat. Using hyperspectral data, 650-673 nm and 760-830 nm were found as optimum spectral region for computing NDVI; and relationships between LAI and various pigment indices and red-edge indices were studied. Using 1100 m resolution A VHRR data, the relationship between NDVI and roughness parameter (computed from tower based measurements) in direct as well as fractal based mode had been developed. The surface temperature over the region was obtained using split thermal window algorithm and NDVI as surrogate parameter to define relative contribution of emissivity for soil and crop components in the pixel. Sensible heat flux, computed using AVHRR data based roughness parameter and surface

  5. Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982-2010.

    PubMed

    Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

    2014-05-01

    Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and GSL varied considerably during 1982-2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

  6. Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982-2010

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

    2014-05-01

    Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and GSL varied considerably during 1982-2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

  7. Interannual Variations and Trends in Global Land Surface Phenology Derived from Enhanced Vegetation Index During 1982-2010

    NASA Technical Reports Server (NTRS)

    Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

    2014-01-01

    Land swiace phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstmted to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This srudy detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examIned across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and OSL varied considerably during 1982-2010 across the globe. Generally, the interarmual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative OSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

  8. MSG/SEVIRI, NOAA/AVHRR and EOS/MODIS TIR observations during the Abruzzo 6 April 2009 earthquake (ML~ 5.8)

    NASA Astrophysics Data System (ADS)

    Genzano, Nicola; Corrado, Rosita; Filizzola, Carolina; Lacava, Teodosio; Lisi, Mariano; Marchese, Francesco; Mazzeo, Giuseppe; Paciello, Rossana; Pergola, Nicola; Tramutoli, Valerio

    2010-05-01

    Space-time fluctuations of Earth's emitted Thermal Infrared (TIR) radiation have been observed from satellite months to weeks before earthquakes occurrence. Different authors, in order to explain the appearance of anomalously high TIR records near the place and the time of earthquake occurrence, attributed their appearance to the increase of green-house gas (such as CO2, CH4, etc.) emission rates, to the modification of ground water regime and/or to the increase of convective heat flux. In this contest, an approach called Robust Satellite Techniques (RST) has been proposed in order to discriminate normal (i.e. related to the change of natural factor and/or observation conditions) TIR signal fluctuations from anomalous signal transient possibly associated to earthquake occurrence. In the past RST was already tested in the case of tens of earthquakes with a wide range of magnitudes (from 4.0 to 7.9) occurred in different continents and in various geo-tectonic setting (e.g. 1980 Irpinia-Basilicata earthquake; Izmit earthquake, 17 August 1999; Hector Mine earthquake, 16 October 1999, etc.). The RST analysis is based on a statistically definition of "TIR anomalies" and a suitable method for their identification even in very different local (e.g. related to atmosphere and/or surface) and observational (e.g. related to time/season, but also to solar and satellite zenithal angles) conditions, and has been always carried out by using a validation/confutation approach, to verify the presence/absence of anomalous space-time TIR transients in the presence/absence of seismic activity. In this work the same approach is applied to the case of Abruzzo 6 April 2009 event (ML=5.8) and compared with an identical analysis (confutation) performed in seismically unperturbed years. RST analysis was performed on a historical data set made of 30 years of contemporary observations done by 3 independent satellite systems (5 years of MSG/SEVIRI, 15 years of NOAA/AVHRR and 10 years of EOS

  9. Monthly fractional green vegetation cover associated with land cover classes of the conterminous USA

    USGS Publications Warehouse

    Gallo, Kevin P.; Tarpley, Dan; Mitchell, Ken; Csiszar, Ivan; Owen, editors, Timothy W.; Reed, Bradley C.

    2001-01-01

    The land cover classes developed under the coordination of the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) have been analyzed for a study area that includes the Conterminous United States and portions of Mexico and Canada. The 1-km resolution data have been analyzed to produce a gridded data set that includes within each 20-km grid cell: 1) the three most dominant land cover classes, 2) the fractional area associated with each of the three dominant classes, and 3) the fractional area covered by water. Additionally, the monthly fraction of green vegetation cover (fgreen) associated with each of the three dominant land cover classes per grid cell was derived from a 5-year climatology of 1-km resolution NOAA-AVHRR data. The variables derived in this study provide a potential improvement over the use of monthly fgreen linked to a single land cover class per model grid cell.

  10. Seasonal thermal energy storage

    SciTech Connect

    Allen, R.D.; Kannberg, L.D.; Raymond, J.R.

    1984-05-01

    This report describes the following: (1) the US Department of Energy Seasonal Thermal Energy Storage Program, (2) aquifer thermal energy storage technology, (3) alternative STES technology, (4) foreign studies in seasonal thermal energy storage, and (5) economic assessment.

  11. Dry season streamflow persistence in seasonal climates

    NASA Astrophysics Data System (ADS)

    Dralle, David N.; Karst, Nathaniel J.; Thompson, Sally E.

    2016-01-01

    Seasonally dry ecosystems exhibit periods of high water availability followed by extended intervals during which rainfall is negligible and streamflows decline. Eventually, such declining flows will fall below the minimum values required to support ecosystem functions or services. The time at which dry season flows drop below these minimum values (Q*), relative to the start of the dry season, is termed the "persistence time" (). The persistence time determines how long seasonal streams can support various human or ecological functions during the dry season. In this study, we extended recent work in the stochastic hydrology of seasonally dry climates to develop an analytical model for the probability distribution function (PDF) of the persistence time. The proposed model accurately captures the mean of the persistence time distribution, but underestimates its variance. We demonstrate that this underestimation arises in part due to correlation between the parameters used to describe the dry season recession, but that this correlation can be removed by rescaling the flow variables. The mean persistence time predictions form one example of the broader class of streamflow statistics known as crossing properties, which could feasibly be combined with simple ecological models to form a basis for rapid risk assessment under different climate or management scenarios.

  12. Land cover mapping of Greater Mesoamerica using MODIS data

    USGS Publications Warehouse

    Giri, Chandra; Jenkins, Clinton N.

    2005-01-01

    A new land cover database of Greater Mesoamerica has been prepared using moderate resolution imaging spectroradiometer (MODIS, 500 m resolution) satellite data. Daily surface reflectance MODIS data and a suite of ancillary data were used in preparing the database by employing a decision tree classification approach. The new land cover data are an improvement over traditional advanced very high resolution radiometer (AVHRR) based land cover data in terms of both spatial and thematic details. The dominant land cover type in Greater Mesoamerica is forest (39%), followed by shrubland (30%) and cropland (22%). Country analysis shows forest as the dominant land cover type in Belize (62%), Cost Rica (52%), Guatemala (53%), Honduras (56%), Nicaragua (53%), and Panama (48%), cropland as the dominant land cover type in El Salvador (60.5%), and shrubland as the dominant land cover type in Mexico (37%). A three-step approach was used to assess the quality of the classified land cover data: (i) qualitative assessment provided good insight in identifying and correcting gross errors; (ii) correlation analysis of MODIS- and Landsat-derived land cover data revealed strong positive association for forest (r2 = 0.88), shrubland (r2 = 0.75), and cropland (r2 = 0.97) but weak positive association for grassland (r2 = 0.26); and (iii) an error matrix generated using unseen training data provided an overall accuracy of 77.3% with a Kappa coefficient of 0.73608. Overall, MODIS 500 m data and the methodology used were found to be quite useful for broad-scale land cover mapping of Greater Mesoamerica.

  13. Seasonal Variation in Epidemiology

    ERIC Educational Resources Information Center

    Marrero, Osvaldo

    2013-01-01

    Seasonality analyses are important in medical research. If the incidence of a disease shows a seasonal pattern, then an environmental factor must be considered in its etiology. We discuss a method for the simultaneous analysis of seasonal variation in multiple groups. The nuts and bolts are explained using simple trigonometry, an elementary…

  14. Personal, Seasonal Suns

    ERIC Educational Resources Information Center

    Sutley, Jane

    2010-01-01

    This article presents an art project designed for upper-elementary students to (1) imagine visual differences in the sun's appearance during the four seasons; (2) develop ideas for visually translating their personal experiences regarding the seasons to their sun drawings; (3) create four distinctive seasonal suns using colors and imagery to…

  15. Land surface temperature measurements from EOS MODIS data

    NASA Technical Reports Server (NTRS)

    Wan, Zhengming

    1994-01-01

    A generalized split-window method for retrieving land-surface temperature (LST) from AVHRR and MODIS data has been developed. Accurate radiative transfer simulations show that the coefficients in the split-window algorithm for LST must depend on the viewing angle, if we are to achieve a LST accuracy of about 1 K for the whole scan swath range (+/-55.4 deg and +/-55 deg from nadir for AVHRR and MODIS, respectively) and for the ranges of surface temperature and atmospheric conditions over land, which are much wider than those over oceans. We obtain these coefficients from regression analysis of radiative transfer simulations, and we analyze sensitivity and error by using results from systematic radiative transfer simulations over wide ranges of surface temperatures and emissivities, and atmospheric water vapor abundance and temperatures. Simulations indicated that as atmospheric column water vapor increases and viewing angle is larger than 45 deg it is necessary to optimize the split-window method by separating the ranges of the atmospheric column water vapor and lower boundary temperature, and the surface temperature into tractable sub-ranges. The atmospheric lower boundary temperature and (vertical) column water vapor values retrieved from HIRS/2 or MODIS atmospheric sounding channels can be used to determine the range where the optimum coefficients of the split-window method are given. This new LST algorithm not only retrieves LST more accurately but also is less sensitive than viewing-angle independent LST algorithms to the uncertainty in the band emissivities of the land-surface in the split-window and to the instrument noise.

  16. Evaluating land application effects

    SciTech Connect

    Sarkis, K. )

    1987-01-01

    The Philadelphia, PA Water Department embarked on a land application program of its treated wastewater sludge in 1977. Initially, liquid sludge averaging from 1-5% solids was applied to approximately 400 acres of corn, soybeans, and sod at rates sufficient to supply crop nitrogen needs. During the 1978 through 1984 growing seasons, crops and soils were monitored for heavy metals (bioavailability of cadmium, copper, nickel, chromium, lead and zinc) and in 1984 for PCB accumulation. This report summarizes results of the monitoring program until 1984.

  17. An introduction to mid-Atlantic seasonal pools

    USGS Publications Warehouse

    Brown, L.J.; Jung, R.E.

    2005-01-01

    Seasonal pools, also known as vernal ponds, provide important ecological services to the mid-Atlantic region. This publication serves as an introduction to seasonal pool ecology and management; it also provides tools for exploring seasonal pools, including a full-color field guide to wildlife. Seasonal pools are defined as having four distinctive features: surface water isolation, periodic drying, small size and shallow depth, and support of a characteristic biological community. Seasonal pools experience regular drying that excludes populations of predatory fish. Thus, pools in the mid-Atlantic region provide critical breeding habitat for amphibian and invertebrate species (e.g., spotted salamander (Ambystoma maculatum), wood frog (Rana sylvatica), and fairy shrimp (Order Anostraca)) that would be at increased risk of predation in more permanent waters. The distinctive features of seasonal pools also make them vulnerable to human disturbance. In the mid-Atlantic region, land-use changes pose the greatest challenges to seasonal pool conservation. Seasonal pools are threatened by direct loss (e.g., filling or draining of the pool) as well as by destruction and fragmentation of adjoining terrestrial habitat. Many of the species that depend on seasonal pools for breeding spend the majority of their lives in the surrounding lands that extend a radius of 1000 feet or more from the pools; these vital habitats are being transected by roads and converted to other land uses. Other threats to seasonal pools include biological introductions and removals, mosquito control practices, amphibian diseases, atmospheric deposition, and climate change. The authors recommend a three-pronged strategy for seasonal pool conservation and management in the mid-Atlantic region: education and research, inventory and monitoring of seasonal pools, and landscape-level planning and management.

  18. Regional Comparisons of Satellite (AVHRR) and Space Shuttle (MAPS) Derived Estimates of CO and Aerosol Concentrations

    NASA Technical Reports Server (NTRS)

    Vulcan, D. V.; Christopher, S. A.; Welch, R. M.; Connors, V. S.

    1996-01-01

    Biomass burning is considered to be a major source of trace gas species and aerosol particles which play a vital role in tropospheric chemistry and climate. Anthropogenic biomass burning has largely expanded in the last 15 years, due to increased deforestation practices in the Amazon Basin, as well as to clear land for shifting cultivation in South America, southern Asia, and Africa. Biomass burning produces large amounts of carbon dioxide, carbon monoxide (CO), water, hydrocarbons, nitrous oxides, and smoke particles.

  19. Validation of Land Cover Maps Utilizing Astronaut Acquired Imagery

    NASA Technical Reports Server (NTRS)

    Estes, John E.; Gebelein, Jennifer

    1999-01-01

    This report is produced in accordance with the requirements outlined in the NASA Research Grant NAG9-1032 titled "Validation of Land Cover Maps Utilizing Astronaut Acquired Imagery". This grant funds the Remote Sensing Research Unit of the University of California, Santa Barbara. This document summarizes the research progress and accomplishments to date and describes current on-going research activities. Even though this grant has technically expired, in a contractual sense, work continues on this project. Therefore, this summary will include all work done through and 5 May 1999. The principal goal of this effort is to test the accuracy of a sub-regional portion of an AVHRR-based land cover product. Land cover mapped to three different classification systems, in the southwestern United States, have been subjected to two specific accuracy assessments. One assessment utilizing astronaut acquired photography, and a second assessment employing Landsat Thematic Mapper imagery, augmented in some cases, high aerial photography. Validation of these three land cover products has proceeded using a stratified sampling methodology. We believe this research will provide an important initial test of the potential use of imagery acquired from Shuttle and ultimately the International Space Station (ISS) for the operational validation of the Moderate Resolution Imaging Spectrometer (MODIS) land cover products.

  20. Determination of water-soluble and insoluble (dilute-HCl-extractable) fractions of Cd, Pb and Cu in Antarctic aerosol by square wave anodic stripping voltammetry: distribution and summer seasonal evolution at Terra Nova Bay (Victoria Land).

    PubMed

    Annibaldi, A; Truzzi, C; Illuminati, S; Bassotti, E; Scarponi, G

    2007-02-01

    Eight PM10 aerosol samples were collected in the vicinity of the "Mario Zucchelli" Italian Antarctic Station (formerly Terra Nova Bay Station) during the 2000-2001 austral summer using a high-volume sampler and precleaned cellulose filters. The aerosol mass was determined by differential weighing of filters carried out in a clean chemistry laboratory under controlled temperature and humidity. A two-step sequential extraction procedure was used to separate the water-soluble and the insoluble (dilute-HCl-extractable) fractions. Cd, Pb and Cu were determined in the two fractions using an ultrasensitive square wave anodic stripping voltammetric (SWASV) procedure set up for and applied to aerosol samples for the first time. Total extractable metals showed maxima at midsummer for Cd and Pb and a less clear trend for Cu. In particular, particulate metal concentrations ranged as follows: Cd 0.84-9.2 microg g(-1) (average 4.7 microg g(-1)), Pb 13.2-81 microg g(-1) (average 33 microg g(-1)), Cu 126-628 microg g(-1) (average 378 microg g(-1)). In terms of atmospheric concentration, the values were: Cd 0.55-6.3 pg m(-3) (average 3.4 pg m(-3)), Pb 8.7-48 pg m(-3) (average 24 pg m(-3)), Cu 75-365 pg m(-3) (average 266 pg m(-3)). At the beginning of the season the three metals appear widely distributed in the insoluble (HCl-extractable) fraction (higher proportions for Cd and Pb, 90-100%, and lower for Cu, 70-90%) with maxima in the second half of December. The soluble fraction then increases, and at the end of the season Cd and Pb are approximately equidistributed between the two fractions, while for Cu the soluble fraction reaches its maximum level of 36%. Practically negligible contributions are estimated for crustal and sea-spray sources. Low but significant volcanic contributions are estimated for Cd and Pb (approximately 10% and approximately 5%, respectively), while there is an evident although not quantified marine biogenic source, at least for Cd. The estimated natural

  1. On the new GPCC gridded reference data sets of observed (daily) monthly land-surface precipitation since (1988) 1901 published in 2014 including an all seasons open source test product

    NASA Astrophysics Data System (ADS)

    Ziese, Markus; Andreas, Becker; Peter, Finger; Anja, Meyer-Christoffer; Kirstin, Schamm; Udo, Schneider

    2014-05-01

    Since 1989 the Global Precipitation Climatology Centre (GPCC) collects world-wide observational in-situ data from rain gauges in order to provide gridded high quality and resolution land surface precipitation analyses as mandated by WMO's World Climate Research Program and the Global Climate Observing System (GCOS). In doing so a thorough quality control (QC) is performed on the original data prior to its entrance into the ever growing GPCC data archive being the world-wide largest with monthly totals for more than 90000 stations. Since 2012 also daily data is processed and the archive already holds daily data for more than 30000 stations with the aim to reach at least the same scope as for monthly data, ultimately. All archived data stems from various sources, e.g. national meteorological and hydrological services and regional or global data collections and is thus stored in source specific slots, allowing cross-checks on redundant records and subsequent QC at different sophistication levels depending on the timeliness demand on each product. All data products are referenced by digital object identifiers (DOIs all starting with "10.5676/DWD_GPCC/") and thus published in public domain (ftp://ftp-anon.dwd.de/pub/data/gpcc/html/download_gate.html) for minimum 10 years per product and version. In 2014 the monthly Full Data Reanalysis and the Climatology product releases of December 2011 are due for update. As the new Climatology product is also used as background climatology for all other data products, the Monitoring Product shall be re-processed for all years since 1986. Moreover the First Guess Products (daily and monthly) will benefit from the improved climatology. Finally, GPCC will release its first Full Data Daily Reanalysis product comprising the land-surface precipitation for every day since 1 January 1988. It will be extended backward in course of GPCC's participation in the ERA_CLIM2 re-analysis project. The double to triple size of the GPCC data archive

  2. Mapping Land Cover Types in Amazon Basin Using 1km JERS-1 Mosaic

    NASA Technical Reports Server (NTRS)

    Saatchi, Sassan S.; Nelson, Bruce; Podest, Erika; Holt, John

    2000-01-01

    In this paper, the 100 meter JERS-1 Amazon mosaic image was used in a new classifier to generate a I km resolution land cover map. The inputs to the classifier were 1 km resolution mean backscatter and seven first order texture measures derived from the 100 m data by using a 10 x 10 independent sampling window. The classification approach included two interdependent stages: 1) a supervised maximum a posteriori Bayesian approach to classify the mean backscatter image into 5 general land cover categories of forest, savannah, inundated, white sand, and anthropogenic vegetation classes, and 2) a texture measure decision rule approach to further discriminate subcategory classes based on taxonomic information and biomass levels. Fourteen classes were successfully separated at 1 km scale. The results were verified by examining the accuracy of the approach by comparison with the IBGE and the AVHRR 1 km resolution land cover maps.

  3. Effects of new MODIS land cover map replacement in a regional climate model on surface temperature and humidity

    NASA Astrophysics Data System (ADS)

    Yucel, I.

    This study investigates the extent to which utilizing 1-km new the Moderate-resolution Imaging-Spectroradiometer (MODIS) land use data in the Pennsylvania State University/NCAR's MM5 coupled with Oregon State University (OSU) provides an improved regional diagnosis of near-surface atmospheric state variables as well as characteristics of the planetary boundary layer (PBL). Those variables are strongly influenced by the energy, matter and momentum exchange between the land surface and the atmosphere. MODIS data provides not only a detailed spatial distribution of vegetation, but also a delineation between water bodies and land surface for MM5 high-resolution applications. Advances in remote sensing technology allow MODIS to collect higher-quality data than previous sensors, yielding the most detailed land cover classification maps to date. The new maps are better because the quality of MODIS data is much higher than the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer (AVHRR). The default 25-category United States Geological Survey (USGS) land cover classification in MM5 was produced using data acquired in from 1992-1993 by AVHRR. Parameter sets of 17-category MODIS land use dataset are determined by making close match between MODIS, USGS and SIB categories to use in OSU land-surface model. 1-km Land-Water Mask (LWM) data is also derived from this new data as an input to MM5. When the MM5 horizontal grid increment is larger than 1-km (4-km and 12-km in current study), the dominant vegetation type in each grid box is selected to represent the ``grid level'' vegetation characteristics. The MODIS data consider the influence of detailed picture of the distribution of Earth's ecosystems in the surface energy and water budget and hence the evolution of the boundary layer. The impact on the near-surface temperature and humidity is given by making comparison between model and observations at selected land surface types.

  4. Global and Regional Trends of Aerosol Optical Depth over Land and Ocean Using SeaWiFS Measurements from 1997 to 2010

    NASA Technical Reports Server (NTRS)

    Hsu, N. C.; Gautam, R.; Sayer, A. M.; Bettenhausen, C.; Li, C.; Jeong, M. J.; Tsay, S. C.; Holben, B. N.

    2012-01-01

    Both sensor calibration and satellite retrieval algorithm play an important role in the ability to determine accurately long-term trends from satellite data. Owing to the unprecedented accuracy and long-term stability of its radiometric calibration, the SeaWiFS measurements exhibit minimal uncertainty with respect to sensor calibration. In this study, we take advantage of this well-calibrated set of measurements by applying a newly-developed aerosol optical depth (AOD) retrieval algorithm over land and ocean to investigate the distribution of AOD, and to identify emerging patterns and trends in global and regional aerosol loading during its 13-year mission. Our results indicate that the averaged AOD trend over global ocean is weakly positive from 1998 to 2010 and comparable to that observed by MODIS but opposite in sign to that observed by AVHRR during overlapping years. On a smaller scale, different trends are found for different regions. For example, large upward trends are found over the Arabian Peninsula that indicate a strengthening of the seasonal cycle of dust emission and transport processes over the whole region as well as over downwind oceanic regions. In contrast, a negative-neutral tendency is observed over the desert/arid Saharan region as well as in the associated dust outflow over the north Atlantic. Additionally, we found decreasing trends over the eastern US and Europe, and increasing trends over countries such as China and India that are experiencing rapid economic development. In general, these results are consistent with those derived from ground-based AERONET measurements.

  5. Study to assess the importance of errors introduced by applying NOAA 6 and NOAA 7 AVHRR data as an estimator of vegetative vigor: Feasibility study of data normalization

    NASA Technical Reports Server (NTRS)

    Duggin, M. J. (Principal Investigator); Piwinski, D.

    1982-01-01

    The use of NOAA AVHRR data to map and monitor vegetation types and conditions in near real-time can be enhanced by using a portion of each GAC image that is larger than the central 25% now considered. Enlargement of the cloud free image data set can permit development of a series of algorithms for correcting imagery for ground reflectance and for atmospheric scattering anisotropy within certain accuracy limits. Empirical correction algorithms used to normalize digital radiance or VIN data must contain factors for growth stage and for instrument spectral response. While it is not possible to correct for random fluctuations in target radiance, it is possible to estimate the necessary radiance difference between targets in order to provide target discrimination and quantification within predetermined limits of accuracy. A major difficulty lies in the lack of documentation of preprocessing algorithms used on AVHRR digital data.

  6. Session on coupled land surface/hydrological/atmospheric models

    NASA Technical Reports Server (NTRS)

    Pielke, Roger

    1993-01-01

    The current model capabilities in the context of land surface interactions with the atmosphere include only one-dimensional characteristics of vegetation and soil surface heat, moisture, momentum, and selected other trace gas fluxes (e.g., CO2). The influence of spatially coherent fluxes that result from landscape heterogeneity were not included. Valuable representations of several aspects of the landscape pattern currently exist. These include digital elevation data and measures of the leaf area index (i.e., Normalized Difference Vegetation Index (NDVI) from Advanced Very High Resolution Radiometer (AVHRR) data). A major deficiency, however, is the lack of an ability to sample spatially representative shallow and (especially) deep soil moisture. Numerous mesoscale modeling and observed studies demonstrated the sensitivity of planetary boundary layer structure and deep convection to the magnitude of the surface moisture flux.

  7. Seasonal energy storage using bioenergy production from abandoned croplands

    NASA Astrophysics Data System (ADS)

    Campbell, J. Elliott; Lobell, David B.; Genova, Robert C.; Zumkehr, Andrew; Field, Christopher B.

    2013-09-01

    Bioenergy has the unique potential to provide a dispatchable and carbon-negative component to renewable energy portfolios. However, the sustainability, spatial distribution, and capacity for bioenergy are critically dependent on highly uncertain land-use impacts of biomass agriculture. Biomass cultivation on abandoned agriculture lands is thought to reduce land-use impacts relative to biomass production on currently used croplands. While coarse global estimates of abandoned agriculture lands have been used for large-scale bioenergy assessments, more practical technological and policy applications will require regional, high-resolution information on land availability. Here, we present US county-level estimates of the magnitude and distribution of abandoned cropland and potential bioenergy production on this land using remote sensing data, agriculture inventories, and land-use modeling. These abandoned land estimates are 61% larger than previous estimates for the US, mainly due to the coarse resolution of data applied in previous studies. We apply the land availability results to consider the capacity of biomass electricity to meet the seasonal energy storage requirement in a national energy system that is dominated by wind and solar electricity production. Bioenergy from abandoned croplands can supply most of the seasonal storage needs for a range of energy production scenarios, regions, and biomass yield estimates. These data provide the basis for further down-scaling using models of spatially gridded land-use areas as well as a range of applications for the exploration of bioenergy sustainability.

  8. On the seasonal phytoplankton concentration and sea surface temperature cycles of the Gulf of Mexico as determined by satellites

    NASA Technical Reports Server (NTRS)

    Mueller-Karger, Frank E.; Walsh, John J.; Meyers, Mark B.; Evans, Robert H.

    1991-01-01

    Multiyear series of coastal zone color scanner (CZCS) and AVHRR observations are presently used to derive monthly climatologies of near-surface phytoplankton pigment concentration and SST for the Gulf of Mexico; these, in combination with 1946-1987 SST data and NOAA hydrographic profile data covering 1914-1985, show that the most important single factor controlling seasonal cycle surface-pigment concentration is the depth of the mixed layer. The CZCS images indicate that seasonal variation seaward of the continental shelf is synchronous throughout the Gulf. The combination of ocean color and IR images allows year-round observation of surface circulation spatial structure in the Gulf, as well as of the dispersal pattern of the Mississippi River's plume.

  9. Seasonal affective disorder

    MedlinePlus

    ... depression References American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders . 5th ed. Arlington, VA: American Psychiatric Publishing. 2013. Osborn J, Raetz J, Kost A. Seasonal ...

  10. Quantification of Surface Suspended Sediments along a River Dominated Coast with NOAA AVHRR and SeaWiFS Measurements: Louisiana, USA

    NASA Technical Reports Server (NTRS)

    Myint, S. W.; Walker, N. D.

    2002-01-01

    The ability to quantify suspended sediment concentrations accurately over both time and space using satellite data has been a goal of many environmental researchers over the past few decades This study utilizes data acquired by the NOAA Advanced Very High Resolution Radiometer (AVHRR) and the Orbview-2 Sea-viewing wide field-of-view (SeaWiFS) ocean colour sensor, coupled with field measurements to develop statistical models for the estimation of near-surface suspended sediment and suspended solids "Ground truth" water samples were obtained via helicopter, small boat and automatic water sampler within a few hours of satellite overpasses The NOAA AVHRR atmospheric correction was modified for the high levels of turbidity along the Louisiana coast. Models were developed based on the field measurements and reflectance/radiance measurements in the visible and near infrared Channels of NOAA-14 and Orbview-2 SeaWiFS. The best models for predicting surface suspended sediment concentrations were obtained with a NOAA AVHRR Channel 1 (580-680nm) cubic model, Channel 2 (725-1100 nm) linear mod$ and SeaWiFs Channel 6 (660-68Onm) power modeL The suspended sediment models developed using SeaWiFS Channel 5 (545-565 nm) were inferior, a result that we attribute mainly to the atmospheric correction technique, the shallow depth of the water samples and absorption effects from non-sediment water constituents.

  11. Characteristics of seasonal vegetation cover in the conterminous USA

    USGS Publications Warehouse

    Gallo, Kevin P.; Reed, Bradley C.; Owen, editors, Timothy W.; Adegoke, Jimmy O.

    2005-01-01

    A data set of the fractional green vegetation cover (FGREEN) for the Conterminous USA was evaluated for regional and seasonal variation. The value of FGREEN was derived monthly for the three most dominant land cover classes per 20 km by 20 km grid cell within the study area. At this grid cell resolution (comprised of 400 1-km pixels), 97 percent of the grid cells included three or fewer land cover classes. FGREEN was found to vary regionally due to local land cover and climate variations. FGREEN was found significantly different between one or more of the land cover classes, for one or more months, in 58 percent of the grid cells included in the study. Monthly FGREEN values for the land cover classes vary sufficiently between the land cover classes to warrant monthly FGREEN data for each of the one to three most dominant land cover classes per grid cell.

  12. Drought Risk Identification: Early Warning System of Seasonal Agrometeorological Drought

    NASA Astrophysics Data System (ADS)

    Dalecios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.

    2014-05-01

    By considering drought as a hazard, drought types are classified into three categories, namely meteorological or climatological, agrometeorological or agricultural and hydrological drought and as a fourth class the socioeconomic impacts can be considered. This paper addresses agrometeorological drought affecting agriculture within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with the quantification and monitoring of agrometeorological drought, which constitute part of risk identification. For the quantitative assessment of agrometeorological or agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the Vegetation Health Index (VHI). The computation of VHI is based on satellite data of temperature and the Normalized Difference Vegetation Index (NDVI). The spatiotemporal features of drought, which are extracted from VHI are: areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of NOAA/AVHRR satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural region of Greece characterized by vulnerable and drought-prone agriculture. The results show that every year there is a seasonal agrometeorological drought with a gradual increase in the areal extent and severity with peaks appearing usually during the summer. Drought monitoring is conducted by monthly remotely sensed VHI images. Drought early warning is developed using empirical relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought, respectively. The two fitted curves offer a seasonal

  13. Cloud-screening for Africa using a geographically and seasonally variable infrared threshold

    NASA Technical Reports Server (NTRS)

    Eck, T. F.; Kalb, V. L.

    1991-01-01

    A spatially variable monthly, infrared cloud-threshold data base has been used to screen cloud-contaminated observations from radiances measured by the NOAA-9 AVHRR over Africa. Cloud-screening through a monthly average infrared threshold based on measured surface air temperature, which is geographically dependent, shows an improvement over using a seasonally and geographically independent thermal cloud threshold of 287 K. It is found that differences in cloud-screening for these two thresholds occur for cases of lower altitude clouds or subpixel clouds where the radiative temperature is higher than the 287 K infrared threshold, yet colder than the variable threshold developed by Stowe et al. (1988) for the Nimbus-7 global cloud climatology. The variable IR threshold is shown to be effective over persistently cloud-covered regions, such as the coastal region of the Gulf of Guinea, but may introduce some erroneous cloud identifications over mountains.

  14. Seasonality and dietary requirements: will eating seasonal food contribute to health and environmental sustainability?

    PubMed

    Macdiarmid, Jennie I

    2014-08-01

    Eating more seasonal food is one proposal for moving towards more sustainable consumption patterns, based on the assumption that it could reduce the environmental impact of the diet. The aim of the present paper is to consider the implications of eating seasonal food on the different elements of sustainability (i.e. health, economics, society), not just the environment. Seasonality can be defined as either globally seasonal (i.e. produced in the natural production season but consumed anywhere in the world) or locally seasonal (i.e. produced in the natural production season and consumed within the same climatic zone). The environmental, health, economic and societal impact varies by the definition used. Global seasonality has the nutritional benefit of providing a more varied and consistent supply of fresh produce year round, but this increases demand for foods that in turn can have a high environmental cost in the country of production (e.g. water stress, land use change with loss of biodiversity). Greenhouse gas emissions of globally seasonal food are not necessarily higher than food produced locally as it depends more on the production system used than transportation. Eating more seasonal food, however, is only one element of a sustainable diet and should not overshadow some of the potentially more difficult dietary behaviours to change that could have greater environmental and health benefits (e.g. reducing overconsumption or meat consumption). For future guidelines for sustainable diets to be realistic they will need to take into account modern lifestyles, cultural and social expectations in the current food environment. PMID:25027288

  15. Teaching with the Seasons.

    ERIC Educational Resources Information Center

    Weber, Larry

    1998-01-01

    Describes a natural science course designed to teach students that nature is nearby rather than somewhere else. Students learn about local flora and fauna, track the weather, and closely monitor the progression of the seasons. The course uses no textbook, regularly uses the outdoors as a classroom, and follows the seasons' phenology as the…

  16. Mediterranean desertification and land degradation: Mapping related land use change syndromes based on satellite observations

    NASA Astrophysics Data System (ADS)

    Hill, J.; Stellmes, M.; Udelhoven, Th.; Röder, A.; Sommer, S.

    2008-12-01

    In past decades, the European Mediterranean has undergone widespread land use transformations. These are largely driven by changes of socio-economic conditions, such as accession to the European Community, and had strong effects on the way the land is being used. Aiming at a systematic description of such change processes on a global level, the syndrome concept was proposed to describe archetypical, co-evolutionary patterns of human-nature interactions, and has been specifically linked to the desertification issue. In this study, we present an adaptation of the syndrome approach to the Iberian Peninsula. We suggest a data processing and interpretation framework to map the spatial extent of specific syndromes. The mapping approach is based on the time series analysis of satellite data. We have characterized vegetation dynamics using NDVI estimates from the coarse scale, hyper-temporal 1-km MEDOKADS archive, which is based on calibrated NOAA-AVHRR images. Results indicate that local patches of abrupt disturbance, mainly caused by fire, are contrasted by a widespread increase in vegetation, which is in large parts attributed to the abandonment of rural areas. Although this questions the dominance of classical desertification traits, i.e. decline of productivity after disturbance, it is concluded that the recent greening presents a different sort of environmental risk, as it may negatively impact on fire regimes and the hydrological cycle.

  17. Mapping and monitoring net primary productivity with AVHRR NDVI time-series: statistical equivalence of cumulative vegetation indices

    NASA Astrophysics Data System (ADS)

    Ricotta, Carlo; Avena, Giancarlo; De Palma, Alessandra

    In the last two decades, numerous investigators have proposed cumulative vegetation indices (i.e., functions which encode the cumulative effect of NDVI maximum value composite time-series into a single variable) for net primary productivity (NPP) mapping and monitoring on a regional to continental basis. In this paper, we investigate the relationships among three of the most commonly used cumulative vegetation indices, expanding on the definition of equivalence of remotely sensed vegetation indices for decision making. We consider two cumulative vegetation indices as equivalent, if the value of one index is statistically predictable from the value of the other index. Using an annual time-series of broad-scale AVHRR NDVI monthly maximum value composites of the island of Corsica (France), we show that the pairwise linear association among the analysed cumulative vegetation indices shows coefficients of determination ( R2) higher than 0.99. That is, knowing the value of one index is statistically equivalent to knowing the value of the other indices for application purposes.

  18. Deployment of Autonomous GPS Stations in Marie Byrd Land, Antartica

    NASA Technical Reports Server (NTRS)

    Donnellan, A.; Luyendyk, B.; Smith, M.; Dace, G.

    1999-01-01

    During the 1998-1999 Antarctic field season, we installed three autonomous GPS stations in Marie Byrd Land, West Antarctica to measure glacio-isostatic rebound and rates of spreading across the West Antartic Rift System.

  19. Adaptation to seasonality and the winter freeze.

    PubMed

    Preston, Jill C; Sandve, Simen R

    2013-01-01

    Flowering plants initially diversified during the Mesozoic era at least 140 million years ago in regions of the world where temperate seasonal environments were not encountered. Since then several cooling events resulted in the contraction of warm and wet environments and the establishment of novel temperate zones in both hemispheres. In response, less than half of modern angiosperm families have members that evolved specific adaptations to cold seasonal climates, including cold acclimation, freezing tolerance, endodormancy, and vernalization responsiveness. Despite compelling evidence for multiple independent origins, the level of genetic constraint on the evolution of adaptations to seasonal cold is not well understood. However, the recent increase in molecular genetic studies examining the response of model and crop species to seasonal cold offers new insight into the evolutionary lability of these traits. This insight has major implications for our understanding of complex trait evolution, and the potential role of local adaptation in response to past and future climate change. In this review, we discuss the biochemical, morphological, and developmental basis of adaptations to seasonal cold, and synthesize recent literature on the genetic basis of these traits in a phylogenomic context. We find evidence for multiple genetic links between distinct physiological responses to cold, possibly reinforcing the coordinated expression of these traits. Furthermore, repeated recruitment of the same or similar ancestral pathways suggests that land plants might be somewhat pre-adapted to dealing with temperature stress, perhaps making inducible cold traits relatively easy to evolve. PMID:23761798

  20. Adaptation to seasonality and the winter freeze

    PubMed Central

    Preston, Jill C.; Sandve, Simen R.

    2013-01-01

    Flowering plants initially diversified during the Mesozoic era at least 140 million years ago in regions of the world where temperate seasonal environments were not encountered. Since then several cooling events resulted in the contraction of warm and wet environments and the establishment of novel temperate zones in both hemispheres. In response, less than half of modern angiosperm families have members that evolved specific adaptations to cold seasonal climates, including cold acclimation, freezing tolerance, endodormancy, and vernalization responsiveness. Despite compelling evidence for multiple independent origins, the level of genetic constraint on the evolution of adaptations to seasonal cold is not well understood. However, the recent increase in molecular genetic studies examining the response of model and crop species to seasonal cold offers new insight into the evolutionary lability of these traits. This insight has major implications for our understanding of complex trait evolution, and the potential role of local adaptation in response to past and future climate change. In this review, we discuss the biochemical, morphological, and developmental basis of adaptations to seasonal cold, and synthesize recent literature on the genetic basis of these traits in a phylogenomic context. We find evidence for multiple genetic links between distinct physiological responses to cold, possibly reinforcing the coordinated expression of these traits. Furthermore, repeated recruitment of the same or similar ancestral pathways suggests that land plants might be somewhat pre-adapted to dealing with temperature stress, perhaps making inducible cold traits relatively easy to evolve. PMID:23761798

  1. Remotely Sensed Rice Yield Prediction Using Multi-Temporal NDVI Data Derived from NOAA's-AVHRR

    PubMed Central

    Huang, Jingfeng; Wang, Xiuzhen; Li, Xinxing; Tian, Hanqin; Pan, Zhuokun

    2013-01-01

    Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha−1. Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly. PMID:23967112

  2. Recent trends of SST in the Western Mediterranean basins from AVHRR Pathfinder data (1985-2007)

    NASA Astrophysics Data System (ADS)

    López García, M. J.; Camarasa Belmonte, A. M.

    2011-08-01

    Climate change in the Mediterranean region cannot be understood without taking into account changes in the Mediterranean Sea, which is an important source of moisture and heat for the Mediterranean climate system. Many research papers have been published in the last two decades increasing our knowledge about long-term trends and inter-annual variability of temperature and salinity in the Western Mediterranean. Although recent changes have been better documented, there remain uncertainties because different results are obtained depending on the period of time analyzed or the geographic region selected. This paper analyses the regional, seasonal and decadal variability of sea surface temperature in the Western Mediterranean basins (Northern (Ligurian Sea and Gulf of Lions), Balearic, Algerian and Alboran) by means of thermal satellite images. Monthly data from the PO.DAAC (Physical Oceanography Distributed Active Archive Center) have been processed for the period 1985-2007. Results show an averaged warming linear trend of 0.03 °C/yr. This rate is higher during the spring (0.06 °C/yr) in all the basins and the highest values were registered in the Northern basin in June. The study suggests that an early warming of the Sea is occurring in all the basins during the spring, with an increment of 0.5-1 °C in the mean SST of April, May and June over the two decades studied. The analysis of thermal anomalies confirms the warming trend with a dominance of negative anomalies during 1985-1996 and a dominance of positive anomalies during the last decade (1997-2007). Intense anomalies are more frequent in the Northern basin.

  3. The use of NOAA AVHRR data for assessment of the urban heat island effect

    SciTech Connect

    Gallo, K.P.; Tarpley, J.D. ); McNab, A.L.; Karl, T.R. ); Brown, J.F. ); Hood, J.J. )

    1993-05-01

    A vegetation index and a radiative surface temperature were derived from satellite data acquired at approximately 1330 LST for each of 37 cities and for their respective nearby rural regions from 28 June through 8 August 1991. Urban-rural differences for the vegetation index and the surface temperatures were computed and then compared to observed urban-rural differences in minimum air temperatures. The purpose of these comparisons was to evaluate the use of satellite data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). The temporal consistency of the data, from daily data to weekly, biweekly, and monthly intervals, was also evaluated. The satellite-derived normalized difference (ND) vegetation-index data, samples over urban and rural regions composed of a variety of land surface environments, were linearly related to the difference in observed urban and rural minimum temperatures. The relationship between the ND index and observed differences in minimum temperature was improved when analyses were restricted by elevation differences between the sample locations and when biweekly or monthly intervals were utilized. The difference in the ND index between urban and rural regions appears to be an indicator of the difference in surface properties (evaporation and heat storage capacity) between the two environments that are responsible for differences in urban and rural minimum temperatures. The urban and rural differences in the ND index explain a greater amount of the variation observed in minimum temperature differences than past analyses that utilized urban population data. The use of satellite data may contribute to a globally consistent method for analysis of urban heat island bias. 36 refs., 7 figs., 4 tabs.

  4. Controlling Seasonal Allergies

    MedlinePlus

    ... diagnosis, treatment, and prevention of asthma and allergic diseases. Immune Tolerance Network (ITN): The ITN is an international ... mold spores can cause seasonal allergic reactions. The immune system is ... Diseases (NIAID) and National Institute of Environmental Health Sciences ( ...

  5. PMC from 2009 Season

    NASA Video Gallery

    Polar Mesospheric Clouds (PMC) from the Aeronomy of Ice in the Mesosphere Cloud Imaging and Particle Size (AIM-CIPS) instrument for the 2009 season in the northern polar region. The North Pole (90N...

  6. Seasonality of suicidal behavior.

    PubMed

    Woo, Jong-Min; Okusaga, Olaoluwa; Postolache, Teodor T

    2012-02-01

    A seasonal suicide peak in spring is highly replicated, but its specific cause is unknown. We reviewed the literature on suicide risk factors which can be associated with seasonal variation of suicide rates, assessing published articles from 1979 to 2011. Such risk factors include environmental determinants, including physical, chemical, and biological factors. We also summarized the influence of potential demographic and clinical characteristics such as age, gender, month of birth, socioeconomic status, methods of prior suicide attempt, and comorbid psychiatric and medical diseases. Comprehensive evaluation of risk factors which could be linked to the seasonal variation in suicide is important, not only to identify the major driving force for the seasonality of suicide, but also could lead to better suicide prevention in general. PMID:22470308

  7. Sorting Out Seasonal Allergies

    MedlinePlus

    ... Back to Health Library Sorting Out Seasonal Allergies Sneezing, runny nose, nasal congestion. Symptoms of the common ... simple preventive measures, you can help reduce your sneezing, coughing and general stuffiness, according to Pamela A. ...

  8. True Color Earth Data Set Includes Seasonal Dynamics

    NASA Astrophysics Data System (ADS)

    Stöckli, Reto; Vermote, Eric; Saleous, Nazmi; Simmon, Robert; Herring, David

    2006-01-01

    Space exploration has changed our visual perception of planet Earth. In the 1950s, satellites revolutionized weather forecasting. Astronaut photography in the early 1970s showed us the Earth in color, the so-called `Blue Marble' (Figure 1, left). Since 1972, satellite sensors have been acquiring atmosphere, land, ice, and ocean data with increasing spectral and spatial resolution. Satellite remote sensing systems such as the NASA Earth Observing System (EOS) help us to understand and monitor Earth's physical, chemical, and biological processes [Running et al., 1999]. The false-color Earth image shown in the center of Figure 1, named Blue Marble, was created in 2000 with data from the Advanced Very High Resolution Radiometer (AVHRR), the Geostationary Operational Environmental Satellite (GOES 8), and the Sea viewing Wide Field-of-view Sensor (SeaWiFS). New sensors such as the Moderate-Resolution Imaging Spectroradiometer (MODIS), aboard NASA Terra and Aqua satellites, allow the derivation of a wide range of geophysical parameters from measured radiances of a single sensor.

  9. Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

    NASA Technical Reports Server (NTRS)

    Potter, C. S.

    1997-01-01

    This study describes the use of satellite data to calibrate a new climate-vegetation greenness function for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes of the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980s in order to refine our empirical understanding of intraannual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global l(sup o) gridded data sets suggest that three climate indexes: growing degree days, annual precipitation total, and an annual moisture index together can account to 70-80 percent of the variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same climate index values from the previous year explained no significant additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes was closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from l(sup o) grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes were not accurately predicted are mainly high latitude ecosystems and other remote locations where climate station data are sparse.

  10. Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

    NASA Technical Reports Server (NTRS)

    Potter, C. S.; Brooks, V.

    1997-01-01

    This paper describes the use of satellite data to calibrate a new climate-vegetation greenness relationship for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes If the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980's in order to refine our understanding of intra-annual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global 1o gridded data sets suggest that three climate indexes: degree days (growing/chilling), annual precipitation total, and an annual moisture index together can account to 70-80 percent of the geographic variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same annual climate index values from the previous year explains no substantial additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes is closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from lo grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI for several different years at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes are not accurately predicted are mainly high latitude zones, mixed and disturbed vegetation types, and other remote locations where climate station data are sparse.

  11. Improvements in AVHRR Daytime Cloud Detection Over the ARM NSA Site

    NASA Technical Reports Server (NTRS)

    Chakrapani, V.; Spangenberg, D. A.; Doelling, D. R.; Minnis, P.; Trepte, Q. Z.; Arduini, R. F.

    2001-01-01

    Clouds play an important role in the radiation budget over Arctic and Antarctic. Because of limited surface observing capabilities, it is necessary to detect clouds over large areas using satellite imagery. At low and mid-latitudes, satellite-observed visible (VIS; 0.65 micrometers) and infrared (IR; 11 micrometers) radiance data are used to derive cloud fraction, temperature, and optical depth. However, the extreme variability in the VIS surface albedo makes the detection of clouds from satellite a difficult process in polar regions. The IR data often show that the surface is nearly the same temperature or even colder than clouds, further complicating cloud detection. Also, the boundary layer can have large areas of haze, thin fog, or diamond dust that are not seen in standard satellite imagery. Other spectral radiances measured by satellite imagers provide additional information that can be used to more accurately discriminate clouds from snow and ice. Most techniques currently use a fixed reflectance or temperature threshold to decide between clouds and clear snow. Using a subjective approach, Minnis et al. (2001) found that the clear snow radiance signatures vary as a function of viewing and illumination conditions as well as snow condition. To routinely process satellite imagery over polar regions with an automated algorithm, it is necessary to account for this angular variability and the change in the background reflectance as snow melts, vegetation grows over land, and melt ponds form on pack ice. This paper documents the initial satellite-based cloud product over the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site at Barrow for use by the modeling community. Cloud amount and height are determined subjectively using an adaptation of the methodology of Minnis et al. (2001) and the radiation fields arc determined following the methods of Doelling et al. (2001) as applied to data taken during the Surface Heat and Energy Budget of the

  12. Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

    NASA Technical Reports Server (NTRS)

    Minnis, P.; Sun-Mack, S.; Bedka, K. M.; Yost, C. R.; Trepte, Q. Z.; Smith, W. L., Jr.; Painemal, D.; Chen, Y.; Palikonda, R.; Dong, X.; Xi, B.

    2016-01-01

    Validation is a key component of remote sensing that can take many different forms. The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) is applied to many different imager datasets including those from the geostationary satellites, Meteosat, Himiwari-8, INSAT-3D, GOES, and MTSAT, as well as from the low-Earth orbiting satellite imagers, MODIS, AVHRR, and VIIRS. While each of these imagers have similar sets of channels with wavelengths near 0.65, 3.7, 11, and 12 micrometers, many differences among them can lead to discrepancies in the retrievals. These differences include spatial resolution, spectral response functions, viewing conditions, and calibrations, among others. Even when analyzed with nearly identical algorithms, it is necessary, because of those discrepancies, to validate the results from each imager separately in order to assess the uncertainties in the individual parameters. This paper presents comparisons of various SatCORPS-retrieved cloud parameters with independent measurements and retrievals from a variety of instruments. These include surface and space-based lidar and radar data from CALIPSO and CloudSat, respectively, to assess the cloud fraction, height, base, optical depth, and ice water path; satellite and surface microwave radiometers to evaluate cloud liquid water path; surface-based radiometers to evaluate optical depth and effective particle size; and airborne in-situ data to evaluate ice water content, effective particle size, and other parameters. The results of comparisons are compared and contrasted and the factors influencing the differences are discussed.

  13. Remote sensing of biomass dynamics in drylands: Evaluating vegetation optical depth (VOD) using AVHRR NDVI and in situ data

    NASA Astrophysics Data System (ADS)

    Tian, F.; Brandt, M.; Liu, Y.; Fensholt, R.

    2015-12-01

    Monitoring long-term biomass dynamics in global drylands is of great importance for global carbon cycle modeling and has been done extensively based on the normalized difference vegetation index (NDVI) derived from AVHRR (Advanced Very High Resolution Radiometer) observations. However, there are limitations from both the characteristics of NDVI (e.g. atmosphere and cloud contamination, saturation in densely vegetated areas, and affected by varying vegetation species compositions) and sensor related artifacts (e.g. orbital drifts, sensor changes). Being sensitive to the vegetation water content and not affected by clouds, the Vegetation Optical Depth (VOD) derived from satellite passive microwave observations can be an alternative to NDVI for monitoring biomass dynamics in drylands, yet further evaluations based on ground measurements are needed. In this study, we assess the capability of a long-term VOD dataset (1992-2011) to capture the temporal and spatial variability of in situ measured biomass data (herbaceous and woody foliage mass) in the semi-arid Senegalese Sahel. The GIMMS3g (Global Inventory Modeling and Mapping Studies, 3rd generation) NDVI dataset is included for comparison purpose. Both VOD and NDVI reflect the temporal and spatial pattern of the ground data very well, however, the phenological metrics leading to the best correlations differ between VOD and NDVI. While the annual sum and maximum perform best for VOD, the growing integrals have the highest correlations for NDVI. Furthermore, VOD proves to be robust against typical NDVI drawbacks (species compositions, and saturation effects). Overall, in spite of the coarse resolution, the study shows that satellite passive microwave observation based VOD is an efficient proxy for estimating biomass production of the entire vegetation layer in the Sahel and potentially in other dryland areas.

  14. Seasonal streamflow prediction in Colombia using atmospheric and oceanic patterns

    NASA Astrophysics Data System (ADS)

    Córdoba-Machado, Samir; Palomino-Lemus, Reiner; Gámiz-Fortis, Sonia Raquel; Castro-Díez, Yolanda; Esteban-Parra, María Jesús

    2016-07-01

    The predictability of the Magdalena River seasonal streamflow anomalies is evaluated using previous Sea Surface Temperature (SST), Precipitation (Pt) and Temperature over land (Tm) seasonal anomalies. Through a moving correlation analysis of 30 years, several regions that show stable significant teleconnections between the seasonal streamflow and SST, Pt and Tm from previous seasons have been identified during the period 1936-2009. For lags from one to four 3-month seasons (i.e. up to one year) for the SST and one to two seasons (i.e. up to six months) for Pt and Tm, the Magdalena River seasonal streamflow presents significant and stable correlations with the tropical Pacific SST (El Niño region), with Pt in South America and with Tm over the north of South America, mainly at lags of one and two seasons. The first PCs resulting from the significant and stable regions of the SST, Pt, and Tm fields are used in a forecast scheme to predict seasonal streamflow anomalies. The prediction based on this scheme shows an acceptable prediction skill and represents a relative improvement compared with the predictability of teleconnection indices associated with El Niño, which are traditionally used to predict streamflow in the country. This improvement is particularly more noticeable when lag between streamflow and predictors increases.

  15. Dynamics of the Chesapeake Bay outflow plume: Realistic plume simulation and its seasonal and interannual variability

    NASA Astrophysics Data System (ADS)

    Jiang, Long; Xia, Meng

    2016-02-01

    The three-dimensional unstructured-grid Finite Volume Coastal Ocean Model (FVCOM) was implemented for Chesapeake Bay and its adjacent coastal ocean to delineate the realistic Chesapeake Bay outflow plume (CBOP) as well as its seasonal and interannual variability. Applying the appropriate horizontal and vertical resolution, the model exhibited relatively high skill in matching the observational water level, temperature, and salinity from 2003 to 2012. The simulated surface plume structure was verified by comparing output to the HF radar current measurements, earlier field observations, and the MODIS and AVHRR satellite imagery. According to the orientation, shape, and size of the CBOP from both model snapshots and satellite images, five types of real-time plume behavior were detected, which implied strong regulation by wind and river discharge. In addition to the episodic plume modulation, horizontal and vertical structure of the CBOP exhibited variations on seasonal and interannual temporal scales. Seasonally, river discharge with a 1 month lag was primarily responsible for the surface plume area variation, while the plume thickness was mainly correlated to wind magnitude. On the interannual scale, river discharge was the predominant source of variability in both surface plume area and depth; however, the southerly winds also influenced the offshore plume depth. In addition, large-scale climate variability, such as the North Atlantic Oscillation, could potentially affect the plume signature in the long term by altering wind and upwelling dynamics, underlining the need to understand the impacts of climate change on buoyant plumes, such as the CBOP.

  16. Interannual and Seasonal Variability of Biomass Burning Emissions Constrained by Satellite Observations

    NASA Technical Reports Server (NTRS)

    Duncan, Bryan N.; Martin, Randall V.; Staudt, Amanda C.; Yevich, Rosemarie; Logan, Jennifer A.

    2003-01-01

    We present a methodology for estimating the seasonal and interannual variation of biomass burning designed for use in global chemical transport models. The average seasonal variation is estimated from 4 years of fire-count data from the Along Track Scanning Radiometer (ATSR) and 1-2 years of similar data from the Advanced Very High Resolution Radiometer (AVHRR) World Fire Atlases. We use the Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) data product as a surrogate to estimate interannual variability in biomass burning for six regions: Southeast Asia, Indonesia and Malaysia, Brazil, Central America and Mexico, Canada and Alaska, and Asiatic Russia. The AI data set is available from 1979 to the present with an interruption in satellite observations from mid-1993 to mid-1996; this data gap is filled where possible with estimates of area burned from the literature for different regions. Between August 1996 and July 2000, the ATSR fire-counts are used to provide specific locations of emissions and a record of interannual variability throughout the world. We use our methodology to estimate mean seasonal and interannual variations for emissions of carbon monoxide from biomass burning, and we find that no trend is apparent in these emissions over the last two decades, but that there is significant interannual variability.

  17. Seasonal thermal energy storage

    NASA Astrophysics Data System (ADS)

    Allen, R. D.; Kannberg, L. D.; Raymond, J. R.

    1984-05-01

    Seasonal thermal energy storage (STES) using heat or cold available from surplus, waste, climatic, or cogeneration sources show great promise to reduce peak demand, reduce electric utility load problems, and contribute to establishing favorable economics for district heating and cooling systems. Heated and chilled water can be injected, stored, and recovered from aquifers. Geologic materials are good thermal insulators, and potentially suitable aquifers are distributed throughout the United States. Potential energy sources for use in an aquifer thermal energy storage system include solar heat, power plant cogeneration, winter chill, and industrial waste heat source. Topics covered include: (1) the U.S. Department of Energy seasonal thermal energy storage program; (2) aquifer thermal energy storage technology; (3) alternative STES technology; (4) foreign studies in seasonal thermal energy storage; and (5) economic assessment.

  18. Using satellite-derived snow cover to assess and improve the snowpack physics of the Noah Land Surface Model of NCEP

    NASA Astrophysics Data System (ADS)

    Mitchell, K.; Wei, H.; Ek, M.; Lohmann, D.; Ramsay, B.; Tarpley, D.; Sheffield, J.; Wood, E.

    During the 1990's and continuing to the present, advances in land surface modeling at NCEP have been an important source of improving prediction skill in NCEP global and regional weather and climate models. Many advancements in NCEP's Noah Land Surface Model (Noah LSM) emerged from two thrusts: 1) NCEP's participation in the several land modeling foci of the Global Energy and Water Cycle Experiment (GEWEX), such as GCIP/GAPP, ISLSCP (GSWP I and II), PILPS (2a, 2c, 2d, 2e), and GLASS (Rhone), and 2) the multi-institution collaboration led by NCEP to develop and execute the North American Land Data Assimilation System (NLDAS). Concurrently, NCEP's advancement of the Noah LSM benefited repeatedly from the succession of advances in various satellite-derived land-surface products, including snow cover, green vegetation cover, land surface skin temperature, and surface albedo. Recently for example, NCEP has improved the performance of the snowpack physics in its Noah LSM by means of multi-year inter-comparisons of model simulations and satellite-based analyses of snow cover over continental scales. The satellite-based fields of snow cover applied by NCEP are those of the NESDIS daily, N. Hemisphere 24-km, Interactive Multi-sensor Snow (IMS) product, which has been operational since January of 1997. The generation of IMS snow-cover utilizes inputs from both polar orbiting (NOAA/AVHRR visible and DMSP/SSMI microwave) and geostationary satellites (GOES, METEOSAT, and GMS). On 23 Feb 2004, the operational resolution of the IMS snow-cover product increased to 4-km (from 24-km). The comparison of the Noah LSM simulations of snow cover with the NESDIS IMS analyses of snow cover over the continental U.S. (CONUS) for three successive winter seasons in the NLDAS project revealed a systematic early bias in the Noah timing of springtime snowpack depletion. Subsequent investigation via model sensitivity tests and intercomparison with other land models revealed a low bias in snow

  19. Development of West African Rainy Seasons (Invited)

    NASA Astrophysics Data System (ADS)

    Cook, K. H.

    2013-12-01

    The development of West African rainy seasons in the observed climatology can be understood in terms of two factors: continentality, i.e., the shape and placement of the African continent, and solar forcing. First, the observed features of the West African spring and summer precipitation climatology that distinguish it from the precipitation climatology of the tropical Atlantic to the east and Central/Eastern Africa to the west are presented. These include a lingering of the precipitation maximum along the Guinean coast in June and the apparent sudden movement of the precipitation maximum into the Sahel in early July. Then, these distinguishing features of the West Africa precipitation climatology are explained in terms of the regional dynamics and, finally, related to continentality and solar forcing through the roles of the African easterly jet, land surface temperature, and seasonally-varying SSTs.

  20. Seasonality of volcanic eruptions

    NASA Astrophysics Data System (ADS)

    Mason, B. G.; Pyle, D. M.; Dade, W. B.; Jupp, T.

    2004-04-01

    An analysis of volcanic activity during the last three hundred years reveals that volcanic eruptions exhibit seasonality to a statistically significant degree. This remarkable pattern is observed primarily along the Pacific "Ring of Fire" and locally at some individual volcanoes. Globally, seasonal fluctuations amount to 18% of the historical average monthly eruption rate. In some regions, seasonal fluctuations amount to as much as 50% of the average eruption rate. Seasonality principally reflects the temporal distribution of the smaller, dated eruptions (volcanic explosivity index of 0-2) that dominate the eruption catalog. We suggest that the pattern of seasonality correlates with the annual Earth surface deformation that accompanies the movement of surface water mass during the annual hydrological cycle and illustrate this with respect to global models of surface deformation and regional measurements of annual sea level change. For example, seasonal peaks in the eruption rate of volcanoes in Central America, the Alaskan Peninsula, and Kamchatka coincide with periods of falling regional sea level. In Melanesia, in contrast, peak numbers of volcanic eruptions occur during months of maximal regional sea level and falling regional atmospheric pressure. We suggest that the well-documented slow deformation of Earth's surface that accompanies the annual movements of water mass from oceans to continents acts to impose a fluctuating boundary condition on volcanoes, such that volcanic eruptions tend to be concentrated during periods of local or regional surface change rather than simply being distributed randomly throughout the year. Our findings have important ramifications for volcanic risk assessment and volcanoclimate feedback mechanisms.

  1. Connecting Indicators with land degradation and desertification

    NASA Astrophysics Data System (ADS)

    Kosmas, C.

    2012-04-01

    A series of 72 selected candidate indicators corresponding to the physical environment, social, economic, and land management characteristics were defined in 1672 field sites located in 17 study sites in the Mediterranean and eastern Europe, Latin America, Africa, and Asia. The selected indicators refer to specific farm characteristics such as family status, land tenure, present and previous types of land use, period of existing type of land use, soil depth, slope gradient, tillage operations, tillage depth and direction, etc., as well as to regional characteristics such as annual rainfall, rain seasonality, water availability, water quality and quantity, rate of land abandonment, rate of burned area, etc. Based on existing geo-referenced database, classes have been designated for each indicator and presented in a tabulated form. Weighing indices have been assigned to each class based on existing research or empirically assessing the importance to land degradation and desertification. Various processes or causes related to land degradation and desertification important for the study sites have been studied and the most relevant indicators have been defined. Questionnaires for each process or cause have been prepared and data were collected at field site level in collaboration with land users. The obtained data were statistically analyzed to identify the most important indicators related to each process or cause affecting land degradation and desertification. The analyses have shown that indicators may be widely, even globally, used for assessing the various land degradation and desertification processes or causes at field level. Of course, some indicators related to agriculture, social, and institutional characteristics in some cases show trends that are opposite to what happens in other study sites. These trends can be explained by further investigation including other indicators or processes affecting land degradation and desertification that it was not possible

  2. An Automated Neural Network Cloud Classifier for Use over Land and Ocean Surfaces.

    NASA Astrophysics Data System (ADS)

    Miller, Shawn W.; Emery, William J.

    1997-10-01

    An automated neural network cloud classifier that functions over both land and ocean backgrounds is presented. Motivated by the development of a combined visible, infrared, and microwave rain-rate retrieval algorithm for use with data from the 1997 Tropical Rainfall Measuring Mission (TRMM), an automated cloud classification technique is sought to discern different types of clouds and, hence, different types of precipitating systems from Advanced Very High Resolution Radiometer (AVHRR) type imagery. When this technique is applied to TRMM visible-infrared imagery, it will allow the choice of a passive microwave rain-rate algorithm, which performs well for the observed precipitation type, theoretically increasing accuracy at the instantaneous level when compared with the use of any single microwave algorithm. A neural network classifier, selected because of the strengths of neural networks with respect to within-class variability and nonnormal cluster distributions, is developed, trained, and tested on AVHRR data received from three different polar-orbiting satellites and spanning the continental United States and adjacent waters, as well as portions of the Tropics from the Tropical Ocean and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). The results are analyzed and suggestions are made for future work on this technique. The network selected the correct class for 96% of the training samples and 82% of the test samples, indicating that this type of approach to automated cloud classification holds considerable promise and is worthy of additional research and refinement.

  3. The dry season intensity as a key driver of NPP trends

    NASA Astrophysics Data System (ADS)

    Murray-Tortarolo, Guillermo; Friedlingstein, Pierre; Sitch, Stephen; Seneviratne, Sonia I.; Fletcher, Imogen; Mueller, Brigitte; Greve, Peter; Anav, Alessandro; Liu, Yi; Ahlström, Anders; Huntingford, Chris; Levis, Sam; Levy, Peter; Lomas, Mark; Poulter, Benjamin; Viovy, Nicholas; Zaehle, Sonke; Zeng, Ning

    2016-03-01

    We analyze the impacts of changing dry season length and intensity on vegetation productivity and biomass. Our results show a wetness asymmetry in dry ecosystems, with dry seasons becoming drier and wet seasons becoming wetter, likely caused by climate change. The increasingly intense dry seasons were consistently correlated with a decreasing trend in net primary productivity (NPP) and biomass from different products and could potentially mean a reduction of 10-13% in NPP by 2100. We found that annual NPP in dry ecosystems is particularly sensitive to the intensity of the dry season, whereas an increase in precipitation during the wet season has a smaller effect. We conclude that changes in water availability over the dry season affect vegetation throughout the whole year, driving changes in regional NPP. Moreover, these results suggest that usage of seasonal water fluxes is necessary to improve our understanding of the link between water availability and the land carbon cycle.

  4. What is the potential predictability of seasonal floods and droughts?

    SciTech Connect

    Phillips, T.J.

    1996-05-01

    The potential predictability (PP) of seasonal anomalies in continental hydrology may be thought of as the upper bound in forecast accuracy to be expected when the state of the oceans is known perfectly. We assume that the PP of the seasonal anomalies of continental hydrology is related to their degree of reproducibility in the presence of identical ocean boundary conditions across a number of simulations. In this study, the PP of seasonal anomalies in surface hydrological variables is estimated from an ensemble of 6 decadal integration of the ECMWF global atmospheric model coupled to a land-surface scheme which includes interception and transpiration by a simple vegetation canopy. Identical observed (AMIP) monthly sea surface temperatures are specified in each simulation, while the initial condition of the atmosphere and land surface are allowed to vary.

  5. Land Use and Land Cover Change

    SciTech Connect

    Brown, Daniel; Polsky, Colin; Bolstad, Paul V.; Brody, Samuel D.; Hulse, David; Kroh, Roger; Loveland, Thomas; Thomson, Allison M.

    2014-05-01

    A contribution to the 3rd National Climate Assessment report, discussing the following key messages: 1. Choices about land-use and land-cover patterns have affected and will continue to affect how vulnerable or resilient human communities and ecosystems are to the effects of climate change. 2. Land-use and land-cover changes affect local, regional, and global climate processes. 3. Individuals, organizations, and governments have the capacity to make land-use decisions to adapt to the effects of climate change. 4. Choices about land use and land management provide a means of reducing atmospheric greenhouse gas levels.

  6. Study of atmospheric and bidirectional effects on surface reflectance and vegetation index time series: Application to NOAA AVHRR and preparation for future space missions

    NASA Technical Reports Server (NTRS)

    Frouin, Robert

    1993-01-01

    The objectives of the investigation, namely 'to characterize the atmospheric and directional effects on surface reflectance and vegetation index using the First International Satellite Cloud Climatology Project (ISLCSP) Field Experiment (FIFE) data set, develop new algorithms to obtain better Advanced Very High Resolution Radiometer (AVHRR) indices, and define possible improvements for future satellite missions', were addressed in three separate, yet complementary studies. First, it was shown, from theoretical calculations, that visible and near infrared reflectances combined linearly at optimum (one or two) viewing angles relate linearly to the fraction of photosynthetically available radiation absorbed by plants, f(sub par), can be used independently of the type of foliage and substrate, eliminate the effects of sub-pixel spatial heterogeneity, and improve the accuracy of the f(sub par) estimates when compared to the Normalized Difference Vegetation Index, NDVI. Second, it was demonstrated that NDVI, even though it is not a linear combination of radiances or reflectances, can be spatially integrated without significant loss of information from scales of 300 to 1000 m. Third, AVHRR visible and near-infrared reflectances over the FIFE site, separating temporal and bidirectional components and determining the model parameters through an original iterative scheme was successfully modeled. It appears that NDVI generated from the top-of-atmosphere reflectances normalized by the bidirectional effects (as determined in the scheme) is a better vegetation index than maximum NDVI. Details about the three studies are presented.

  7. An Integrated Approach (TRMM, MODIS, AVHRR, and Rain Gauge) for Assessment of Precipitation in Arid Areas: A Case Study from the Eastern Desert of Egypt

    NASA Astrophysics Data System (ADS)

    Milewski, A.; Sultan, M.; Becker, R.; Abdeldayem, A. W.

    2005-05-01

    Water shortages are major obstacles to sustainable development and a cause for poverty in arid and semiarid countries. In these domains often the case, the appropriate systems (precipitation networks) that are needed to estimate precipitation on a regional scale are absent. We developed an integrated methodology to address this problem using data sets that are available on a global scale. We developed an integrated approach to improve estimates of renewable water resources. The approach utilizes the following data sets (1) TRMM-3B42V6 to extract 3-hourly precipitation data, (2) daily AVHRR data for soil moisture and NDVI measurements, (3) METEOSAT-7 for monitoring cloud movement, and (4) rain gauge data for ground truthing. Our approach entails identifying rain storm events from TRMM data. Following the identification of the events, we verify the individual events by examining the cloud patterns, examining the temporal variations in NDVI and soil moisture, and through comparisons with rain gauge data. For the year 1998, we examined in a GIS environment the following: TRMM scenes (2920 scenes), AVHRR data (365 scenes), METEOSAT (8760 scenes), and available rain gauge data. Findings indicate: (1) A general correspondence between TRMM data and rain gauge data, (2) A progressive increase in NDVI measurements following precipitation (peak after ~10 days), and (3) instantaneous increase in soil moisture. A similar (yet with a more restricted data set) exercise was conducted in year 1994, where a major flood occurred.

  8. Study of atmospheric and bidirectional effects on surface reflectance and vegetation index time series: Application to NOAA AVHRR and preparation for future space missions. Final report

    SciTech Connect

    Frouin, R.

    1993-06-01

    The objectives of the investigation, namely to characterize the atmospheric and directional effects on surface reflectance and vegetation index using the First International Satellite Cloud Climatology Project (ISLCSP) Field Experiment (FIFE) data set, develop new algorithms to obtain better Advanced Very High Resolution Radiometer (AVHRR) indices, and define possible improvements for future satellite missions, were addressed in three separate, yet complementary studies. First, it was shown, from theoretical calculations, that visible and near infrared reflectances combined linearly at optimum (one or two) viewing angles relate linearly to the fraction of photosynthetically available radiation absorbed by plants, f[sub par], can be used independently of the type of foliage and substrate, eliminate the effects of sub-pixel spatial heterogeneity, and improve the accuracy of the f[sub par] estimates when compared to the Normalized Difference Vegetation Index, NDVI. Second, it was demonstrated that NDVI, even though it is not a linear combination of radiances or reflectances, can be spatially integrated without significant loss of information from scales of 300 to 1000 m. Third, AVHRR visible and near-infrared reflectances over the FIFE site, separating temporal and bidirectional components and determining the model parameters through an original iterative scheme was successfully modeled. It appears that NDVI generated from the top-of-atmosphere reflectances normalized by the bidirectional effects (as determined in the scheme) is a better vegetation index than maximum NDVI. Details about the three studies are presented.

  9. Assessing hurricane season

    NASA Astrophysics Data System (ADS)

    Showstack, Randy

    2011-12-01

    With the official conclusion of the Atlantic hurricane season on 29 November, Irene was the only hurricane to strike the United States this year and the first one since Hurricane Ike made landfall in Texas in 2008, according to the National Oceanic and Atmospheric Administration (NOAA). Irene “broke the ‘hurricane amnesia’ that can develop when so much time lapses between landfalling storms,” indicated Jack Hayes, director of NOAA's National Weather Service. “This season is a reminder that storms can hit any part of our coast and that all regions need to be prepared each and every season.” During the season, there were 19 tropical storms, including 7 that became hurricanes; 3 of those were major hurricanes, of category 3 or above. The activity level was in line with NOAA predictions. The agency stated that Hurricane Irene was an example of improved accuracy in forecasting storm tracks: NOAA National Hurricane Center had accurately predicted the hurricane's landfall in North Carolina and its path northward more than 4 days in advance.

  10. Teaching Science: Eclipse Seasons.

    ERIC Educational Resources Information Center

    Leyden, Michael B.

    1995-01-01

    Demonstrates the need for a three-dimensional model as an aid for teaching students why eclipses do not occur ev