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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 interannual 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. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. A modified Becker's split-window approach for retrieving land surface temperature from AVHRR and VIRR

    NASA Astrophysics Data System (ADS)

    Quan, Weijun; Chen, Hongbin; Han, Xiuzhen; Liu, Yonghong; Ye, Caihua

    2012-04-01

    In order to provide a long time-series, high spatial resolution, and high accuracy dataset of land surface temperature (LST) for climatic change research, a modified Becker and Li's split-window approach is proposed in this paper to retrieve LST from the measurements of Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA)-7 to -18 and the Visible and InfraRed Radiometer (VIRR) onboard FY-3A. For this purpose, the Moderate Resolution Transmittance Model (MODTRAN) 4.1 was first employed to compute the spectral radiance at the top of atmosphere (TOA) under a variety of surface and atmosphere conditions. Then, a temperature dataset consists of boundary temperature T s (which is one of the input parameters to MODTRAN), and channels 4 and 5 brightness temperatures ( T 4 and T 5) were constructed. Note that channels 4 and 5 brightness temperatures were simulated from the MODTRAN output spectral radiance by convolving them with the spectral response functions (SRFs) of channels 4 and 5 of AVHRRs and VIRR. The coefficients of modified Becker and Li's split-window approach for various AVHRRs and VIRR were subsequently regressed based on this temperature dataset using the least square method. As an example of validation, one AVHRR satellite image over Beijing acquired at 0312 UTC 27 April 2008 by AVHRR onboard NOAA-17 was selected to retrieve the LST image using the modified Becker and Li's approach. The comparison between this LST image and that from the MODIS level-2 LST product provided by the University of Tokyo in Japan indicates that the correlation coefficient is 0.88, the bias is 0.6 K, and the root mean square deviation (RMSD) is 2.1 K. Furthermore, about 70% and 37% pixels in the LST difference image, which is the result of retrieved LST image from AVHRR minus the corresponding MODIS LST image, have the values within ±2 and ±1 K, respectively.

  12. The 1 km AVHRR global land data set: first stages in implementation

    USGS Publications Warehouse

    Eidenshink, J.C.; Faundeen, J.L.

    1994-01-01

    The global land 1 km data set project represents an international effort to acquire, archive, process, and distribute 1 km AVHRR data of the entire global land surface in order to meet the needs of the international science community. A network of 26 high resolution picture transmission (HRPT) stations, along with data recorded by the National Oceanic and Atmospheric Administration (NOAA), has been acquiring daily global land coverage since 1 April 1992. A data set of over 30000 AVHRR images has been archived and made available for distribution by the United States Geological Survey, EROS Data Center and the European Space Agency. Under the guidance of the International Geosphere Biosphere programme, processing standards for the AVHRR data 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 related to the study of surface vegetation cover. A prototype 10-day composite was produced for the period of 21–30 June 1992. Production of an 18-month time series of 10-day composites is underway.

  13. Seasonal land-cover regions of the United States

    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 U.S. 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 -kilometer-resolution database of land-cover characteristics for the coterminous U.S. 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 152, seasonal land-cover regions. The regionalization is based on a taxonomy of areas with respect to data on land cover, seasonality or phenology, and relative levels of primary production. The resulting database consists of descriptions of the vegetation, land cover, and seasonal, spectral, and site characteristics for each region. These data are used in the construction of an illustrative 1:7,500,000-scaIe 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.

  14. 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

  15. Estimation of Land Surface Temperature for a 1-km AVHRR Time Series

    NASA Astrophysics Data System (ADS)

    Frey, C. M.

    2015-12-01

    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 procedures suitable for time series processing, including mono-window and split window algorithms. The selection is based on a round robin approach, in which selected mono-window and split window algorithms are tested on the basis of TOA radiance/LST pairs, which were generated using a radiative transfer model. 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 validation results are shown.

  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. 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.

  18. 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...

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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

  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. 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.

  8. 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.

  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. 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.

  10. 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.

  11. 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

  12. Analysis of the linkages between rainfall and land surface conditions in the West African monsoon through CMAP, ERS-WSC, and NOAA-AVHRR data

    NASA Astrophysics Data System (ADS)

    Philippon, Nathalie; Mougin, Eric; Jarlan, Lionel; Frison, Pierre-Louis

    2005-12-01

    The European Remote Sensing Wind Scatterometer (ERS-WSC) backscattering coefficient, NOAA Advanced Very High Resolution Radiometer (NOAA-AVHRR) Normalized Difference Vegetation Index (NDVI), and Climate Prediction Center Merged Analysis Precipitation (CMAP) precipitation data sets are studied over the period August 1991 to December 2000 to document (1) the interannual and intra-annual evolutions of vegetation photosynthetic activity and soil-vegetation water content over West Africa and (2) their two-way links with precipitation. Over the Sahel, at interannual timescales the strongest relationships between vegetation, soil moisture, and precipitation are observed from July to October and when 1-month lag is considered between the parameters. This delay reflects the vegetation response time to the moisture pulses that follow precipitation events. The high correlation between NDVI and sigma_0 at interannual timescales confirms the importance of vegetation in the backscattering coefficient. However, sigma_0 shows stronger statistical links with precipitation, suggesting that this product contains additional useful information related in particular to upper soil moisture. Over Guinea, large differences are observed between the two remote sensing products, and their relationship with precipitation at interannual timescales is weaker. Sigma_0 is significantly linked to precipitation from July to November, whereas NDVI does not show any significant relationship with precipitation. NDVI and sigma_0 serial correlations over the Sahel and Guinea suggest that a 2-month memory usually characterizes vegetation photosynthetic activity and soil-vegetation water content anomalies. However, anomalies disappearance in winter then reappearance in the following spring also suggests an interseason memory held by deep soil moisture reservoirs and deep-rooted plants. A composite analysis reveals that the wettest Sahelian rainy seasons were preceded by positive anomalies of soil

  13. 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.

  14. 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

  15. 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.

  16. Data assimilation of AVHRR and MODIS data for land base initialization and boundary conditions in the UTC-M atmospheric boundary layer sea-breeze model of Space Coast Florida

    NASA Astrophysics Data System (ADS)

    Bostater, Charles R., Jr.; King, Jerome A.; Huddleston, Lisa H.; Bassetti, Luce

    2004-02-01

    The purpose of this paper is to present results of simulations of the Florida Tech UTC-M sea-breeze model with the addition of a simplified atmospheric downwelling radiation subroutine combined and a thermal inertia subroutine into the atmospheric planetary boundary layer model, in order to calculate time dependant heat flux boundary conditions at the air-land boundary that are derived from satellite data from AVHRR and MODIS sensors. The improved UTC-M planetary boundary layer model with this thermal sub-model subroutine is used to demonstrate the use of thermal inertia to help estimate heat fluxes at the land-air interface which in turn influences convergence and vertical fluxes near the bottom boundary, and which may affect mesoscale meteorological wind and seabreeze over complex land-water margins. Additionally, message passage interface (MPI) parallelizing Fortran techniques were used to improve the computational time when the model grid was decreased down to 2 or 1 km cell when simulations where performed on the FIT supercomputer based on an IBM Beowulf Linux cluster. We present some results of the UTC-M simulations and associated results due to the influence of the parameterization of the net surface radiation and thermal inertia using the spectral or wavelength (channel) specific data from MODIS and AVHRR satellite sensors.

  17. Using NOAA AVHRR data to assess flood damage in China.

    PubMed

    Wang, Quan; Watanabe, Masataka; Hayashi, Seiji; Murakami, Shogo

    2003-03-01

    The article used two NOAA-14 Advanced Very High Resolution Radiometer (AVHRR) datasets to assess flood damage in the middle and lower reaches of China's Changjiang River (Yangtze River) in 1998. As the AVHRR is an optical sensor, it cannot penetrate the clouds that frequently cover the land during the flood season, and this technology is greatly limited in flood monitoring. However the widely used normalized difference vegetation index (NDVI) can be used to monitor flooding, since water has a much lower NDVI value than other surface features. Though many factors other than flooding (e.g. atmospheric conditions, different sun-target-satellite angles, and cloud) can change NDVI values, inundated areas can be distinguished from other types of ground cover by changes in the NDVI value before and after the flood after eliminating the effects of other factors on NDVI. AVHRR data from 26 May and 22 August, 1998 were selected to represent the ground conditions before and after flooding. After accurate geometric correction by collecting GCPs, and atmospheric and angular corrections by using the 6S code, NDVI values for both days and their differences were calculated for cloud-free pixels. The difference in the NDVI values between these two times, together with the NDVI values and a land-use map, were used to identify inundated areas and to assess the area lost to the flood. The results show a total of 358,867 ha, with 207,556 ha of cultivated fields (paddy and non-irrigated field) inundated during the flood of 1998 in the middle and lower reaches of the Changjiang River Catchment; comparing with the reported total of 321,000 and 197,000 ha, respectively. The discrimination accuracy of this method was tested by comparing the results from two nearly simultaneous sets of remote-sensing data (NOAA's AVHRR data from 10 September, 1998, and JERS-1 synthetic aperture radar (SAR) data from 11 September, 1998, with a lag of about 18.5 hr) over a representative flooded region in the

  18. 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.

  19. 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.

  20. Snow data assimilation-constrained land initialization improves seasonal temperature prediction

    NASA Astrophysics Data System (ADS)

    Lin, Peirong; Wei, Jiangfeng; Yang, Zong-Liang; Zhang, Yongfei; Zhang, Kai

    2016-11-01

    We present the first systematic study to quantify the impact of land initialization on seasonal temperature prediction in the Northern Hemisphere, emphasizing the role of land snow data assimilation (DA). Three suites of ensemble seasonal integrations are conducted for coupled land-atmosphere runs. The land component is initialized using datasets from (1) no DA, (2) assimilating Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction (SCF), and (3) assimilating both MODIS SCF and Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage. Results show that snow DA improves temperature predictions especially in the Tibetan Plateau (by 5-20%) and high latitudes. Improvements at low latitudes are seen immediately and last up to 60 days, whereas improvements at high latitudes only appear later in transitional seasons. At high latitudes, assimilating GRACE data results in marked and prolonged improvements (by 25%) due to large initial snow mass changes. This study has great implications for future land DA and seasonal climate prediction studies.

  1. 78 FR 47004 - Change in Dates of Seasonal Closure of Public Land in the Bald Ridge Area, Park County, WY

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-08-02

    ... Bureau of Land Management Change in Dates of Seasonal Closure of Public Land in the Bald Ridge Area, Park County, WY AGENCY: Bureau of Land Management, Interior. ACTION: Notice. SUMMARY: Notice is hereby given to change the dates of the seasonal closure of public land in the Bald Ridge Area that was...

  2. 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...

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

    USGS Publications Warehouse

    Markon, C.J.; Peterson, Kim 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.

  4. 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.

  5. 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.

  6. Seasonal variation of land surface fluxes in regional scale by using a remote sensing data

    NASA Astrophysics Data System (ADS)

    Moroizumi, T.; Nakamichi, T.; Miura, T.

    2012-12-01

    Land surface fluxes influence the coupling between the surface and the lower atmosphere, and are also important factors for forming a regional climate.In recent years, it became possible to observe the land surface states in the regional area by the development of the remote sensing technology, and some studies for estimating the land surface energy fluxes at regional scale using the remote sensing data have been carried out. In this study, the surface energy fluxes in the Kanto Plain in Japan where various land uses were mixed were estimated using a remote sensing data (Landsat 7 ETM+), and tried the analysis of the seasonal changes in the land surface energy fluxes. The energy balance and the bulk equations were used in order to estimate the land surface energy fluxes. The parameters in those models were identified using the micro-meteorological data observed above the land surface.

  7. Monitoring changes in biodiversity over Canada during the past three decades using a dynamic habitat index derived from a long-term AVHRR record

    NASA Astrophysics Data System (ADS)

    Fontana, F. M.; Coops, N. C.; Khlopenkov, K. V.; Trishchenko, A. P.; Wulder, M. A.

    2010-12-01

    Understanding the drivers of biodiversity and establishing methods for biodiversity monitoring and conservation has gained increasing importance over the past decade, with particular focus in 2010, proclaimed by the United Nations to be the International Year of Biodiversity. In this context, satellite remote sensing can provide broad-scale information on a range of geophysical variables such as fraction of photosynthetically active radiation (fPAR) absorbed by a vegetated canopy, or land cover, both of which have been shown to be useful indirect indicators of biodiversity through a connection to species abundance and richness. One satellite-derived indirect indicator of species diversity is the Dynamic Habitat Index (DHI), which combines the cumulative annual fPAR, providing an indication of overall site greenness, the minimum annual apparent fPAR, indicating the base level of vegetation cover observed at a location, and the variation of fPAR (seasonality), estimated as the coefficient of variation. To date the application of the DHI has been restricted to data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors from 2000 onwards. To obtain a longer term time series and earlier baseline of DHI conditions across Canada utilization of the archive of historical satellite data from the Advanced Very High Resolution Radiometer (AVHRR) sensor is proposed. In this paper we will discuss the reprocessing of the 1 km spatial resolution AVHRR archive (1981-2007) using a recently developed processing system, Canadian AVHRR Processing System (CAPS). The CAPS produces multi-date composites that satisfy the geolocation requirements defined by the Global Climate Observing System (GCOS). For the compositing process, a cloud contamination index as well as information on the view zenith angle and cloud shadows is incorporated, and observations are constrained to either the forward or backward scattering hemisphere to reduce Bidirectional Reflectance Distribution

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. The influence of the land surface on the transition from dry to wet season in Amazonia

    NASA Astrophysics Data System (ADS)

    Fu, R.; Li, W.

    Analysis of the fifteen years of European Centre for Medium Range Weather Forecasts (ECMWF) reanalysis suggests that the transition from dry to wet season in Southern Amazonia is initially driven by increases of surface latent heat flux. These fluxes rapidly reduce Convective Inhibition Energy (CINE) and increase Convective Available Potential Energy (CAPE), consequently providing favourable conditions for increased rainfall even before the large-scale circulation has changed. The increase of rainfall presumably initiates the reversal of the cross-equatorial flow, leading to large-scale net moisture convergence over Southern Amazonia. An analysis of early and late wet season onsets on an interannual scale shows that a longer dry season with lower rainfall reduces surface latent heat flux in the dry and earlier transition periods compared to that of a normal wet season onset. These conditions result in a higher CINE and a lower CAPE, causing a delay in the increase of local rainfall in the initiating phase of the transition and consequently in the wet season onset. Conversely, a wetter dry season leads to a higher surface latent heat flux and weaker CINE, providing a necessary condition for an earlier increase of local rainfall and an earlier wet season onset. Our results imply that if land use change in Amazonia reduces rainfall during dry and transition seasons, it could significantly delay the wet season onset and prolong the dry season.

  13. 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.

  14. How Do Atmosphere and Land Surface Influence Seasonal Changes of Convection in the Tropical Amazon?.

    NASA Astrophysics Data System (ADS)

    Fu, Rong; Zhu, Bin; Dickinson, Robert E.

    1999-05-01

    Although the wet season in the tropical Amazon (10°N-20°S) at any one place and in any one year is initiated rapidly by synoptic systems, large-scale thermodynamic conditions modulate the frequency and intensity of these synoptic systems and hence control the climatology of the wet season. In this study, the satellite radiances, radiosondes, and assimilation data of the atmosphere are analyzed to show that the conditioning of the large-scale thermodynamics for the onset of the wet season is controlled by a moistening of the planetary boundary layer (PBL) and a lowering of temperature at its top, hence reducing convective inhibition energy (CINE). These changes occur either in phase with or lagging by one month the enhancement of low-level moisture convergence. Integration of a slab mixed-layer model shows how a higher humidity can reduce the drying effect of the entrainment and increase the humidity of the daytime PBL. Hence, the increase of low-level moisture convergence may provide enough moisture to initiate the wet seasons.In the southern part of the basin (5°S-20°S), the land surface warming from austral winter to spring reduces the strong stability of the dry season and increases the frequency of unstable profiles for deep convection (fCUS), but convection remains infrequent until, in addition, the PBL is moistened and the inversion decays to lower CINE in October. The latter occur one month after the moisture becomes convergent. The seasonal changes in land surface temperatures are stronger than those over the adjacent oceans and hence have more influence on the gradient between land and ocean, and so on the changes in the large-scale circulation.In the equatorial western Amazon, a warmer land surface provides high fCUS all year round, but the seasonal changes of convection are more controlled by CINE. In the eastern basin, a lower fCUS in spring suppresses the expected wet season. Hence, convection is most frequent during austral fall, but also occurs

  15. 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.

  16. Seasonal-to-Interannual Precipitation Variability and Predictability in a Coupled Land-Atmosphere System

    NASA Technical Reports Server (NTRS)

    Koster, Randal D.; Suarez, M. J.; Heiser, M.

    1998-01-01

    In an earlier GCM study, we showed that interactive land surface processes generally contribute more to continental precipitation variance than do variable sea surface temperatures (SSTs). A new study extends this result through an analysis of 16-member ensembles of multi-decade GCM simulations. We can now show that in many regions, although land processes determine the amplitude of the interannual precipitation anomalies, variable SSTs nevertheless control their timing. The GCM data can be processed into indices that describe geographical variations in (1) the potential for seasonal-to-interannual prediction, and (2) the extent to which the predictability relies on the proper representation of land-atmosphere feedback.

  17. 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.

  18. 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

  19. Seasonal transition of precipitation characteristics associated with land surface conditions in and around Bangladesh

    NASA Astrophysics Data System (ADS)

    Ono, M.; Takahashi, H. G.

    2016-10-01

    This study examined the seasonal transition of precipitation characteristics and its association with land surface conditions in and around Bangladesh, where land surface conditions are predominantly wet. Hourly rain rate data from the Global Satellite Mapping of Precipitation Microwave-Infrared Combined Product and 10 day soil moisture data from the Advanced Microwave Scanning Radiometer Earth Observing System were used over the 7 years from 2003 to 2009. Area mean values of soil moisture, and precipitation amount, frequency, and intensity were calculated for each 10 day period. Results showed that higher precipitation amount and frequency were observed over the wet soil conditions, which indicates that soil moisture was influenced by previous precipitation events. However, the soil moisture could also control the precipitation characteristics. The seasonal and interannual variations in all regions suggested that precipitation amount and frequency increased in moist soil conditions, which is associated with an increase of water vapor supplied from the moist land surface. Over a flat plain (87°E-91°E, 23°N-25°N), a higher afternoon precipitation intensity was observed over drier land surfaces. This relationship was observed on seasonal and interannual variations. This suggests that the land surface conditions in this region can affect the afternoon precipitation intensity to some extent, although changes of atmospheric conditions can be a major factor particularly for the seasonal changes. However, this relationship was not observed in mountainous regions. This can be explained by other factors, such as thermally induced local circulations by the surrounding topography, being stronger than the impact of land surface conditions.

  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. Nitrogen and phosphorus leaching from growing season versus year-round application of wastewater on seasonally frozen lands.

    PubMed

    Zvomuya, Francis; Rosen, Carl J; Gupta, Satish C

    2006-01-01

    Land application of wastewater has become an important disposal option for food-processing plants operating year-round. However, there are concerns about nutrient leaching from winter wastewater application on frozen soils. In this study, P and N leaching were compared between nongrowing season application of tertiary-treated wastewater plus growing season application of partially treated wastewater (NGS) vs. growing season application of partially treated wastewater (GS) containing high levels of soil P. As required by the Minnesota Pollution Control Agency (MPCA), the wastewater applied to the NGS fields during October through March was treated such that it contained < or =6 mg L(-1) total phosphorus (TP), < or =10 mg L(-1) NO3-N, and < or =20 mg L(-1) total Kjeldahl nitrogen (TKN). The only regulation for wastewater application during the growing season (April through September) was that cumulatively it did not exceed the agronomic N requirements of the crop in any sprayfield. Application of tertiary-treated wastewater during the nongrowing season plus partially treated wastewater during the growing season did not significantly increase NO3-N leaching compared with growing season application of nonregulated wastewater. However, median TP concentration in leachate was significantly higher from the NGS (3.56 mg L(-1)) than from the GS sprayfields (0.52 mg L(-1)) or nonirrigated sites (0.52 mg L(-1)). Median TP leaching loss was also significantly higher from the NGS sprayfields (57 kg ha(-1)) than from the GS (7.4 kg ha(-1)) or control sites (6.9 kg ha(-1)). This was mainly due to higher hydraulic loading from winter wastewater application and limited or no crop P uptake during winter. Results from this study indicate that winter application of even low P potato-processing wastewater to high P soils can accelerate P leaching. We conclude that the regulation of winter wastewater application on frozen soils should be based on wastewater P concentration and

  2. 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.

  3. 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.

  4. 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

  5. AVHRR measurements of atmospheric aerosols over oceans

    NASA Astrophysics Data System (ADS)

    Griggs, M.

    1981-11-01

    A large set of AVHRR and ground-truth data was obtained at ten sites around the globe to investigate the possible global variability of the radiance-aerosol content relationship observed previously with LANDSAT data. The aerosol content was inferred from the AVHRR Channel 1 radiance using an algorithm based on previous LANDSAT measurements at San Diego. The data for four sites were analyzed, and showed excellent agreement between the aerosol content measured by the AVHRR and by sunphotometers at San Diego, Sable Island and San Juan, but at Barbados, the AVHRR appeared to overestimate the aerosol content. The reason for the different relationship at the Barbados site was not definitely established, but is most likely related to problems in interpreting the sunphotometer data rather than to a real overestimation by the AVHRR.

  6. Relation of pesticide concentrations to season, streamflow, and land use in seven New Jersey streams

    USGS Publications Warehouse

    Reiser, Robert G.

    1999-01-01

    concentrations that exceeded New Jersey Department of Environmental Protection (NJDEP) human health criteria. Individual and total-pesticide concentrations and total numbers of pesticides detected in the samples varied with season and flow conditions. Median and maximum concentrations of most of the pesticides were highest during runoff in the growing season. Pesticide concentrations were typically lower and less variable in the nongrowing season than in the growing season, regardless of changes in hydrologic conditions; however, median concentrations of most pesticides were slightly lower during runoff than during base flow. The median total-pesticide concentration and median total number of pesticides detected were highest and most variable in runoff samples in the growing season. In the nongrowing season, the median total-pesticide concentration was lowest in runoff samples and least variable during base-flow conditions. Median total numbers of pesticides were lowest and least varibale in the nongrowing season during base-flow conditions at most sites. The highest total-pesticide concentrations were detected in samples from the two small agricultural basins (greater than 25 percent of land use is agricultural) during runoff in late spring and early summer. In general, insecticides were detected more frequently and in greater concentrations at urban sites. Concentrations of agricultural herbicides generally decreased with increasing flow at the four sites with less than 10 percent agriculture land use and increased with increasing flow at the three sites with more than 25 percent agricultural land use. Most of the pesticides that correlated positively with streamflow were detected at sites where land use in the basin would indicate the use of those particular pesticides. Most of the pesticides that correlated negatively with streamflow were present at the site in the Coastal Plain or at sites in which the land use in the basin would not indicate heavy u

  7. [Difference of Karst Carbon Sink Under Different Land Use and Land Cover Areas in Dry Season].

    PubMed

    Zhao, Rui-yi; Liang, Zuo-bing; Wang, Zun-bo; Yu, Zheng-liang; Jiang, Ze-li

    2015-05-01

    In order to identify the distinction of soil CO2 consumed by carbonate rock dissolution, Baishuwan spring, Lanhuagou spring and Hougou spring were selected as objects to monitor the hydrochemistry from November 2013 to May 2014. The results showed that the highest HCO3- concentration was observed in Baishuwan spring which is covered by pine forest, while the lowest HCO3- concentration was observed in Hougou spring which is mainly covered by cultivated land. In Baishuwan spring, HCO3- was mainly derived from carbonic acid dissolving carbonate rock and the molar ratio between Ca(2+) + Mg2+ and HCO3- was close to 0. 5; while the molar ratio between Ca(2+) + Mg2+ and HCO3- exceeded 0.5 because the carbonate rock in Lanhuagou spring and Hougou spring was mainly dissolved by nitric acid and sulfuric acid. Because of the input of litter and the fact that gas-permeability of soil was limited in Baishuwan spring catchment, most of soil CO2 was dissolved in infiltrated water and reacted with bedrock. However, in Lanhuagou spring catchment and Hougou spring catchment, porous soil made soil CO2 easier to return to the atmosphere in the form of soil respiration. Therefore, in order to accurately estimate karst carbon sink, it was required to clarify the distinction of CO2 consumption by carbonate rock dissolution under different land use and land cover areas.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. Annual and seasonal streamflow responses to climate and land-cover changes in the Poyang Lake basin, China

    NASA Astrophysics Data System (ADS)

    Guo, Hua; Hu, Qi; Jiang, Tong

    2008-06-01

    SummaryRepeated severe floods and damages in the Poyang Lake basin in China during the 1990s have raised the concern of how the floods have been affected by regional climate variations and by human induced changes in landscape (e.g., draining wetlands around the lake) and land-use in the basin. To address this concern and related issues it is important to know how the climate, land-use and land-cover changes in the region affect the annual and seasonal variations of basin hydrology and streamflow. This knowledge is essential for long-term planning for land-use to protect water resources and to effectively manage floods in the Poyang Lake basin as well as the lower reaches of the Yangtze River. It also has important ecological and socioeconomic implications for the region. This study used the SWAT model to examine the climate and land-use and land-cover effects on hydrology and streamflow in the Xinjiang River basin of the Poyang Lake. A major finding of this study is that the climate effect is dominant in annual streamflow. While land-cover change may have a moderate impact on annual streamflow it strongly influences seasonal streamflow and alters the annual hydrograph of the basin. Because of the vegetation and associated seasonal variations of its impact on evapotranspiration, increase of forest cover after returning agricultural lands to forest reduces wet season streamflow and raises it in dry season, thus reducing flood potentials in the wet season and drought severity in the dry season. On the other hand, losing forests increases flood potential and also enhances drought impacts. Results of this study improve our understanding of hydrological consequences of land-use and climate changes, and provide needed knowledge for effectively developing and managing land-use for sustainability and productivity in the Poyang Lake basin.

  16. Complex seasonal patterns of primary producers at the land-sea interface

    USGS Publications Warehouse

    Cloern, J.E.; Jassby, A.D.

    2008-01-01

    Seasonal fluctuations of plant biomass and photosynthesis are key features of the Earth system because they drive variability of atmospheric CO 2, water and nutrient cycling, and food supply to consumers. There is no inventory of phytoplankton seasonal cycles in nearshore coastal ecosystems where forcings from ocean, land and atmosphere intersect. We compiled time series of phytoplankton biomass (chlorophyll a) from 114 estuaries, lagoons, inland seas, bays and shallow coastal waters around the world, and searched for seasonal patterns as common timing and amplitude of monthly variability. The data revealed a broad continuum of seasonal patterns, with large variability across and within ecosystems. This contrasts with annual cycles of terrestrial and oceanic primary producers for which seasonal fluctuations are recurrent and synchronous over large geographic regions. This finding bears on two fundamental ecological questions: (1) how do estuarine and coastal consumers adapt to an irregular and unpredictable food supply, and (2) how can we extract signals of climate change from phytoplankton observations in coastal ecosystems where local-scale processes can mask responses to changing climate? ?? 2008 Blackwell Publishing Ltd/CNRS.

  17. Characterization of global vegetation using AVHRR data

    NASA Astrophysics Data System (ADS)

    Kiang, Richard K.

    1998-03-01

    Increase in the levels of carbon dioxide and other greenhouse gases over the next half-century may result in an increase in global mean temperature. The recent discoveries of possible advance of arctic tree line into the tundra and earlier greening of northern vegetation provide additional warnings that global warming may indeed be occurring. On the Earth surface, land cover and its changes affect the coupling between the biosphere and the atmosphere, and control many important Earth system processes. Satellite remote sensing provides long-term, repeated coverage over extended area and is the essential data source for monitoring climate changes. An Advanced Very-High Resolution Radiometer (AVHRR) Pathfinder dataset from 1987, in 1 degree latitude-longitude resolution, is used in this study. Two reflective channels, two thermal channels, and Normalized Difference Vegetation Index are the input parameters. In conjunction with a global vegetation ground truth, a multi-layer neural network is trained and used for global vegetation characterization. As the same type of vegetation may appear very differently over different parts of the Earth at any given time, global classification is more difficult than local classification. It is shown that a multitemporal approach, in which data from multiple dates are used, may improve the accuracy.

  18. 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

  19. 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.

  20. 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.

  1. 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...

  2. Cloud radiative properties over the South Pole from AVHRR infrared data

    SciTech Connect

    Lubin, D.; Harper, D.A.

    1996-12-01

    Over the Antarctic plateau, the radiances measured by the AVHRR middle infrared (11 and 12 {mu}m) channels are shown to depend on effective cloud temperature, emissivity, ice water path, and effective radius of the particle size distribution. The usefulness of these dependencies is limited by radiometric uncertainties of up to 2 K in brightness temperature and by the fact that the radiative transfer solutions are not single valued over all possible ranges of temperature, effective radius, and ice water path. Despite these limitations, AVHRR imagery can be used to characterize cloud optical properties over the Antarctic continent if surface weather observations and/or radiosonde data can be collocated with the satellite overpasses. From AVHRR imagery covering the South Pole during 1992, the mean cloud emissivity is estimated at 0.43 during summer and 0.37 during winter, while the mean summer and winter effective radii are estimated at 12.3 and 5.6 {mu}m. respectively. When a radiative transfer model is used to evaluate these results in comparison with surface pyrgeometer measurements, the comparison suggests that the AVHRR retrieval method captures the overall seasonal behavior in cloud properties. During months when the polar vortex persists, AVHRR infrared radiances may be noticeably influenced by polar stratospheric clouds. 26 refs., 12 figs., 3 tabs.

  3. 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.

  4. 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.

  5. Hydrologic, land cover, and seasonal patterns of waterborne pathogens in Great Lakes tributaries

    USGS Publications Warehouse

    Lenaker, Peter L.; Corsi, Steven; Borchardt, Mark A.; Spencer, Susan K.; Baldwin, Austin K.; Lutz, Michelle A.

    2017-01-01

    Great Lakes tributaries are known to deliver waterborne pathogens from a host of sources. To examine the hydrologic, land cover, and seasonal patterns of waterborne pathogens (i.e. protozoa (2), pathogenic bacteria (4) human viruses, (8) and bovine viruses (8)) eight rivers were monitored in the Great Lakes Basin over 29 months from February 2011 to June 2013. Sampling locations represented a wide variety of land cover classes from urban to agriculture to forest. A custom automated pathogen sampler was deployed at eight sampling locations which provided unattended, flow-weighted, large-volume (120–1630 L) sampling. Human and bovine viruses and pathogenic bacteria were detected by real-time qPCR in 16%, 14%, and 1.4% of 290 samples collected while protozoa were never detected. The most frequently detected pathogens were: bovine polyomavirus (11%), and human adenovirus C, D, F (9%). Human and bovine viruses were present in 16.9% and 14.8% of runoff-event samples (n = 189) resulting from precipitation and snowmelt, and 13.9% and 12.9% of low-flow samples (n = 101), respectively, indicating multiple delivery mechanisms could be influential. Data indicated human and bovine virus prevalence was different depending on land cover within the watershed. Occurrence, concentration, and flux of human viruses were greatest in samples from the three sampling locations with greater than 25% urban influence than those with less than 25% urban influence. Similarly, occurrence, concentration, and flux of bovine viruses were greatest in samples from the two sampling locations with greater than 50 cattle/km2 than those with less than 50 cattle/km2. In seasonal analysis, human and bovine viruses occurred more frequently in spring and winter seasons than during the fall and summer. Concentration, occurrence, and flux in the context of hydrologic condition, seasonality, and land use must be considered for each watershed individually to develop effective watershed management

  6. Hydrologic, land cover, and seasonal patterns of waterborne pathogens in Great Lakes tributaries.

    PubMed

    Lenaker, P L; Corsi, S R; Borchardt, M A; Spencer, S K; Baldwin, A K; Lutz, M A

    2017-04-15

    Great Lakes tributaries are known to deliver waterborne pathogens from a host of sources. To examine the hydrologic, land cover, and seasonal patterns of waterborne pathogens (i.e. protozoa (2), pathogenic bacteria (4) human viruses, (8) and bovine viruses (8)) eight rivers were monitored in the Great Lakes Basin over 29 months from February 2011 to June 2013. Sampling locations represented a wide variety of land cover classes from urban to agriculture to forest. A custom automated pathogen sampler was deployed at eight sampling locations which provided unattended, flow-weighted, large-volume (120-1630 L) sampling. Human and bovine viruses and pathogenic bacteria were detected by real-time qPCR in 16%, 14%, and 1.4% of 290 samples collected while protozoa were never detected. The most frequently detected pathogens were: bovine polyomavirus (11%), and human adenovirus C, D, F (9%). Human and bovine viruses were present in 16.9% and 14.8% of runoff-event samples (n = 189) resulting from precipitation and snowmelt, and 13.9% and 12.9% of low-flow samples (n = 101), respectively, indicating multiple delivery mechanisms could be influential. Data indicated human and bovine virus prevalence was different depending on land cover within the watershed. Occurrence, concentration, and flux of human viruses were greatest in samples from the three sampling locations with greater than 25% urban influence than those with less than 25% urban influence. Similarly, occurrence, concentration, and flux of bovine viruses were greatest in samples from the two sampling locations with greater than 50 cattle/km(2) than those with less than 50 cattle/km(2). In seasonal analysis, human and bovine viruses occurred more frequently in spring and winter seasons than during the fall and summer. Concentration, occurrence, and flux in the context of hydrologic condition, seasonality, and land use must be considered for each watershed individually to develop effective watershed management

  7. Influence of upstream land use on dissolved organic matter and trihalomethane formation potential in watersheds for two different seasons.

    PubMed

    Hur, Jin; Nguyen, Hang Vo-Minh; Lee, Bo-Mi

    2014-06-01

    Different land uses of upstream catchments may affect the quantity and the quality of dissolved organic matter (DOM) in watersheds, but the influence may differ by season. In this study, we examined concentrations and selected spectroscopic properties of DOM and the propensity to form trihalomethanes (THMs) for 19 different middle-sized watersheds across the Han River basin in Korea. Sampling was conducted for non-storm events during pre-monsoon (May) and monsoon seasons (July). The anthropogenic land uses including agricultural and residential areas occupied 2.3 to 49.4% of the upstream catchments of the watersheds. Non-aromatic, labile, and less condensed DOM structures were more abundant in the monsoon season. Parallel factor analysis (PARAFAC) modeling with fluorescence data demonstrated that a combination of three different fluorescence components could explain the seasonal and the spatial distributions of DOM characteristics. Terrestrial humic-like fluorescence was the most abundant component for all the DOM samples, while protein-like fluorescence became more pronounced for the monsoon season. THM concentrations did not differ between the two seasons. Observed seasonal differences in the concentrations and the characteristics of DOM suggested a greater contribution of groundwater to the streams in watersheds in the monsoon versus the pre-monsoon season. Significant correlations among anthropogenic land use, microbial humic-like fluorescence, and the propensity to form THMs were found only for the pre-monsoon season. Principal component analysis (PCA) demonstrated that, regardless of the season, anthropogenic land uses increased the concentrations of DOM and nutrients but that their effects on the DOM properties were not evident for the monsoon season.

  8. 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

  9. Seasonal variations of wind farm impacts on land surface temperature and vegetation over northern Illinois

    NASA Astrophysics Data System (ADS)

    Slawsky, Lauren

    Operating wind turbines enhance near surface turbulence and alter the exchanges of surface energy, water, and momentum, thus affecting local micrometeorology. Climatic impacts of three wind farms in northern Illinois are assessed using land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) data onboard the Terra and Aqua satellites for the period 2003-2013. Changes in LST between two periods (before and after construction of the wind turbines) and between wind farm pixels (WFPs) and nearby non wind farm pixels (NNWFPs) are quantified. An increase in LST is observed at nighttime over each wind farm, with the pattern of this warming effect generally spatially coupled with the wind turbines, while there is no apparent impact on daytime LST. The nighttime LST warming effect varies with the seasons, with the strongest warming in winter months of December, January, and February, and the tightest spatial coupling in summer months of June, July, and August. Analysis of seasonal variations in wind speeds from weather balloon sounding data taken at the 80 meter turbine hub height and Automated Surface Observing System hourly observations at 10 meters from nearby stations suggest stronger winds correspond to seasons with greater warming. The 12:00 Greenwich Mean Time (early morning in Illinois) soundings are representative of the nighttime boundary layer and exhibit strong temperature inversions across all seasons. This supports the idea that the observed warming effect is caused by warm air aloft brought down to the surface by the spinning turbine rotor blades. In addition, MODIS measured vegetation greenness is used to assess the potential impact of this warming on underlying vegetation growth. A decrease in vegetation greenness is seen, particularly during the summer peak growing season, indicating that the turbine enhanced turbulence may promote evapotranspiration and thus reduce soil moisture available for plant photosynthesis.

  10. Contribution of glomalin to dissolve organic carbon under different land uses and seasonality in dry tropics.

    PubMed

    Singh, Ashutosh Kumar; Rai, Apurva; Pandey, Vivek; Singh, Nandita

    2017-05-01

    Glomalin related soil protein (GRSP) is a hydrophobic glycoprotein that is significant for soil organic carbon (SOC) persistence and sequestration, owing to its large contribution to SOC pool and long turnover time. However, the contribution of GRSP to dissolve OC (DOC) leach from soil is not yet comprehensively explored, though it could have implication in understanding SOC dynamics. We, therefore, aim to measure the contribution of GRSP to DOC, in a range of land uses and climatic seasons in the dry tropical ecosystem. Our results demonstrated that a significant proportion of GRSP (water soluble GRSP; WS-GRSP) leached with DOC (7.9-21.9 mg kg(-1)), which accounts for 0.2-0.23% of soils total GRSP (T-GRSP). Forest exhibited significantly higher WS-GRSP and DOC leaching than fallow and agriculture. WS-GRSP and DOC accumulations were higher in the dry season (summer and winter) than in rainy. The extent of seasonal variations was higher in forest than in other two land uses, indicating the role of vegetation and biological activity in soil dissolve organic matter (DOM) dynamics. The regression analysis among WS-GRSP, T-GRSP, DOC and SOC prove that the accumulations and leaching of GRSP and other soil OM (SOM) depend on similar factors. The ratio of WS-GRSP-C to DOC was higher in agriculture soil than in forest and fallow, likely a consequence of altered soil chemistry, and organic matter quantity and quality due to soil management practices. Multivariate analysis reflects a strong linkage among GRSP and SOC storage and leaching, soil nutrients (nitrogen and phosphorus) and other important soil properties (pH and bulk density), suggesting that improving GRSP and other SOM status is an urgent need for the both SOC sequestration and soil health in dry tropical agro-ecosystems.

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

    PubMed

    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.

  12. Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression.

    PubMed

    Chen, Qiang; Mei, Kun; Dahlgren, Randy A; Wang, Ting; Gong, Jian; Zhang, Minghua

    2016-12-01

    As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R(2) values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R(2) ~59.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use conditions within each watershed to

  13. [Seasonal variations of wild apricot seed dispersal and hoarding by rodents in rehabilitated land].

    PubMed

    Ma, Qing-liang; Zhao, Xue-feng; Sun, Ming-yang; Lu, Ji-qi; Kong, Mao-cai

    2010-05-01

    Rodents feed with and disperse plant seeds, which may thereby affect the seed spatiotemporal distribution, germination, and seedling establishment, and eventually play an important role in the restoration of deforested area. Taking the State-owned Yugong Forest Farm in Jiyuan of Henan, China as study site, the tagged seeds of wild apricot (Prunus armeniaca) were artificially released in rehabilitated land in the spring, summer, and autumn 2008, aimed to investigate their dispersal and hoarding by rodents in different seasons. It was found that Apodemus peninsulae, Niviventer confucianus, and Apodemus agrarius were the main rodent species acting on the seed dispersal and hoarding. The dispersal rate of the seeds was significantly lower in spring than in summer, and also, lower in summer than in autumn. The amount of removed seeds was affected by the interaction of season and seed status, being significantly lesser in spring than in summer, and lesser in summer than in autumn. The mean transportation distance differed with seasons, which was longer in autumn than in spring and summer. The cache size in majority caches was 1 seed, but in a few caches, each cache contained 2 or 3 seeds. The cache number was affected by the interaction of season and seed status, i.e., one seed cache was lesser in spring than in summer and autumn, while the caches containing 2 or 3 seeds were more in summer and autumn. Among the 1800 seeds released, there were five seeds hoarded in summer and autumn respectively established seedlings in the next year of the experiment.

  14. Cloud cover analysis with Arctic AVHRR data: 1. Cloud detection

    NASA Astrophysics Data System (ADS)

    Key, J.; Barry, R. G.

    1989-12-01

    Automated analyses of satellite radiance data have concentrated heavily on low and middle latitude situations. Some of the design objectives for the International Satellite Cloud Climatology Project (ISCCP) cloud detection procedure such as space and time contrasts are used in a basic algorithm from which a polar cloud detection algorithm is developed. This algorithm is applied to Arctic data for January and July conditions. Both advanced very high resolution radiometer (AVHRR) and scanning multichannel microwave radiometer (SMMR) data are utilized. Synthetic AVHRR and SMMR data for a 7-day analysis period are also generated to provide a data set with known characteristics on which to test and validate algorithms. Modifications to the basic algorithm for polar conditions include the use of SMMR and SMMR-derived data sets for the estimation of surface parameters, elimination of the spatial test for the warmest pixel, the use of AVHRR channels 1 (0.7 μm), 3 (3.7 μm), and 4 (11 μm) in the temporal tests and the final multispectral thresholding, and the use of surface class characteristic values when clear-sky values cannot be obtained. Additionally, the difference between channels 3 and 4 is included in the temporal test for the detection of optically thin cloud. Greatest improvement in computed cloud fraction is realized over snow and ice surfaces; over open water or snow-free land, all versions perform similarly. Since the inclusion of SMMR for surface analysis and additional spectral channels increases the computational burden, its use may be justified only over snow and ice-covered regions.

  15. Soil Moisture and Sea Surface Temperatures equally important for Land Climate in the Warm Season

    NASA Astrophysics Data System (ADS)

    Orth, R.; Seneviratne, S. I.

    2015-12-01

    Both sea surface temperatures (SSTs) and soil moisture (SM) are important drivers of climate variability over land. In this study we present a comprehensive comparison of SM versus SST impacts on land climate in the warm season. We perform ensemble experiments with the Community Earth System Model (CESM) where we set SM or SSTs to median conditions, respectively, to remove their inter-annual variability, whereby the other component - SST or SM - is still interactively computed. In contrast to earlier experiments performed with prescribed SSTs, our experiments suggest that SM is overall as important as SSTs for land climate, not only in the midlatitudes but also in the tropics and subtropics. Mean temperature and precipitation are reduced by 0.1-0.5 K and 0-0.2 mm, respectively, whereas their variability at different time scales decreases by 10-40% (temperature) and 0-10% (precipitation) when either SM or SSTs are prescribed. Also drought occurrence is affected, with mean changes in the maximum number of cumulative dry days of 0-0.75 days. Both SM and SST-induced changes are strongest for hot temperatures (up to 0.7 K, and 50%), extreme precipitation (up to 0.4 mm, and 20%), and strong droughts (up to 2 days). Local climate changes in response to removed SM variability are controlled - to first order - by the land-atmosphere coupling and the natural SM variability. SST-related changes are partly controlled by the relation of local temperature or precipitation with the El Niño-Southern Oscillation. Moreover removed SM or SST variabilities both induce remote effects by impacting the atmospheric circulation. Our results are similar for the present day and the end of the century. We investigate the inter-dependency between SM and SST and find a sufficient degree of independence for the purpose of this study. The robustness of our findings is shown by comparing the response of CESM to removed SM variability with four other global climate models. In summary, SM and SSTs

  16. Investigating diurnal and seasonal climatic response to land use and land cover change over monsoon Asia with the Community Earth System Model

    NASA Astrophysics Data System (ADS)

    Xu, Zhongfeng; Mahmood, Rezaul; Yang, Zong-Liang; Fu, Congbin; Su, Hua

    2015-02-01

    Land use and land cover change (LULCC) is primarily characterized as forest conversion to cropland for the development of agriculture. Previous climate modeling studies have demonstrated the LULCC impacts on mean climate and its long-term trends. This study investigates the diurnal and seasonal climatic response to LULCC in monsoon Asia through two numerical experiments with potential and current vegetation cover using the fully coupled Community Earth System Model. Results show that LULCC leads to a reduced diurnal temperature range due to the enhanced (reduced) diurnal cycle of the ground heat flux (sensible heat flux). Daily minimum surface air temperature (Tmin) exhibits a clear seasonality over India as it increases most in the premonsoon season and least during the summer monsoon season. Similarly, a strong anticyclonic anomaly is present at 850 hPa over India in spring and over eastern China in autumn, but weak changes in circulation appear in winter and summer. In addition, the LULCC results in significant changes in the variability of the 2 m air temperature, as characterized by an enhanced variability in India and a reduced variability in northern China to eastern Mongolia in autumn and winter. Possible land-atmosphere feedback loops involving surface albedo, soil moisture, evapotranspiration, atmospheric circulation, and precipitation are offered as biogeophysical mechanisms that are responsible for the region-specific LULCC-induced diurnal and seasonal response.

  17. 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.

  18. 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.

  19. 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.

  20. An analysis of seasonal variability of satellite detected land surface temperatures and urban heat islands

    NASA Astrophysics Data System (ADS)

    Weng, Q.

    This research intends to develop a diffusive UHI model and to compare it with UHIs based on impervious coverage as well as those based on population distribution using Indianapolis as a case study Land surface temperatures LSTs in the four seasons were extracted from thermal infrared data of Terra s ASTER imagery and calibrated with emissivity and other parameters Heat islands were modeled as a three-dimensional surface protruding from a planar surface of the surrounding non-urban land cover The complexity of urban heat islands were measured by fractal dimensions Spectral mixture analysis was applied to transform ASTER reflective bands into fraction images including high albedo low albedo green vegetation and soil with a constrained least-square solution Based on the result of the spectral unmixing impervious surface was calculated The spatial variability of texture in LST was found to be highly correlated with those in the fractions and in the population density surface It is suggested that these variables had a direct correspondence with the radiative thermal and moisture properties of the Earth s surface that determine LST and heat islands In order to develop a generalized model of urban heat islands that has a global application fractals and numerical modeling should be combined to develop a guiding framework

  1. 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.

  2. 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.

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

    NASA Astrophysics Data System (ADS)

    Pan, Zhanlei; Johnson, Douglas A.; Wei, Zhijun; Ma, Lei; Rong, Yuping

    2016-11-01

    Heavy grazing and unsuitable farming practices have led to grassland degradation in northern China. This study 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 vegetation steppes subjected to differing stocking rates [ungrazed (UG), moderately grazed (MG) and heavily grazed (HG)], a fertilized annual cropland (CL) and a perennial pasture (PP) used for haying and winter grazing. Values of Fc were measured at 3-day to 2-week intervals during the non-growing season in two contrasting hydrological years (2012-13 and 2013-14) using closed chambers. The Fc during 1 Oct. 2013 to 30 April 2014 averaged 475 mg C m-2 for all sites compared to a significantly (P < 0.05) lower Fc (102 mg C m-2) during 1 Oct. 2012 to 30 April 2013. The seasonal Fc patterns followed the same trend during the two non-growing seasons with greater Fc observed in the autumn and spring freeze-thaw periods compared to the winter permanently frozen period, which accounted for 4.8% of accumulated total non-growing season Fc. The heavily grazed site showed less soil CO2 efflux compared to UG, MG, PP and CL land-use types due to a larger reduction in gross primary productivity (GPP) compared to ecosystem respiration. Grazing reduced Fc by 23% for MG and 32% for HG compared to UG. Soil CO2 efflux from the PP land-use type, which was grazed during the non-growing season, was 23% greater than that from the UG and CL land-use types. Air temperature during the non-growing season was the main factor controlling soil CO2 efflux (R2 = 0.40, P < 0.001), although soil water content also played a role. Precipitation received during the growing season had a large legacy effect on Fc. Annual weather variation overshadowed the influence of land-use types on Fc.

  4. 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

  5. Effects of seasonal and inter-annual land cover changes on the hydrology of the Upper Ganges basin, India

    NASA Astrophysics Data System (ADS)

    Tsarouchi, G.; Mijic, A.; Buytaert, W.

    2013-12-01

    In recent decades India has undergone substantial environmental change. The expansion of agricultural land area to meet the demand of a rapidly increasing population and the increasing intensification of groundwater extractions have led to an alarming drop in the water table levels. The recent floods over northern India have raised concerns about how the regional climate variations and human induced changes in landscape are influencing the temporal dynamics of climate-surface-groundwater interactions. Earlier work by the authors developed high-resolution land cover maps for northern India, based on satellite imagery, for the years 1984, 1998 and 2010. These maps were used to drive the distributed version of the land surface model JULES in order to investigate the impact of inter-annual land cover changes in the hydrology of the Upper Ganges (UG) river basin in India. However, JULES in its current version does not simulate crop growth. Since 60% of the study area is occupied by agriculture, the model was improved with routines that allow for dynamic representation of crop growth. The parametrization was done for the two main crops of the UG basin (wheat and rice), allowing for 2 cropping seasons per year. The impact of seasonal and inter-annual land cover changes was investigated by calculating variations in hydrological components such as stream flow, evapotranspiration and soil moisture. The results show that the seasonal cycle is changing a lot when crop growth is taken into account, whereas annual fluxes do not change much. The dynamic coupling of land-surface schemes and crop models is an essential step toward the analysis of future changes of water resources in India caused by climate change, land use change, and potential interactions between both. This is a prerequisite for constructing decision support tools for regional land-use planning and management.

  6. Land Surface Phenologies and Seasonalities Using Cool Earthlight in the Major Grain Production Areas of Russia, Ukraine, and Kazakhstan

    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 Russia, Ukraine and Kazakhstan 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 April 1st. Tracking the AMSR-E parameters as a function of AGDD revealed the expected seasonal pattern of thermal limitation in high 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 dynamics in our study 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.

  7. The Van Sant AVHRR image projected onto a rhombicosidodecahedron

    NASA Astrophysics Data System (ADS)

    Baron, Michael; Morain, Stan

    1996-03-01

    IDEATION, a design and development corporation, Santa Fe, New Mexico, has modeled Tom Van Sant's ``The Earth From Space'' image to a rhombicosidodecahedron. ``The Earth from Space'' image, produced by the Geosphere® Project in Santa Monica, California, was developed from hundreds of AVHRR pictures and published as a Mercator projection. IDEATION, utilizing a digitized Robinson Projection, fitted the image to foldable, paper components which, when interconnected by means of a unique tabular system, results in a rhombicosidodecahedron representation of the Earth exposing 30 square, 20 triangular, and 12 pentagonal faces. Because the resulting model is not spherical, the borders of the represented features were rectified to match the intersecting planes of the model's faces. The resulting product will be licensed and commercially produced for use by elementary and secondary students. Market research indicates the model will be used in both the demonstration of geometric principles and the teaching of fundamental spatial relations of the Earth's lands and oceans.

  8. Faunal diversity during rainy season in reclaimed sodic land of Uttar Pradesh, India.

    PubMed

    Singh, S K; Srivastava, S P; Tandon, Pankaj; Azad, B S

    2009-07-01

    Faunal diversity is an indicator of soil amelioration. Estimating the population size or density of an animal species in an area is fundamental to understand its status and demography and to plan for its management and conservation. Considering this, faunal diversity in reclamed sodic land was monitored during rainy season 2000-01 at different locations of district viz., Aligarh, Etah, Fatehpur, Mainpuri and Raebareli in Uttar Pradesh. The Shannon-Weiner species diversity index (H) of different fauna complex of each location was compared with zero years (1995-1996) indexes (before reclamation). Insects diversity index, in reclaimed sodic soil, varied from 3.8178 (Fatehpur: Bariyampur) to 4.623 (Fatehpur: Katoghan), which was 3.028 in zero year at Katoghan in Fatehpur 'H' index of other-arthropods ranged widely from 0.9743 (Etah: Bawali) to 2.0674 (Mainpuri: Pundari). The species diversity index of molluscs registered as high as 1.8637 at Ladhauwa site in Aligarh, which exhibited identical with Saripur site of Raebareli. 'H' index of mammal resulted with the highest (2.19) at Pundari in district Mainpuri. The avifauna and amphibian's indices were recovered maximal at Saripur site of Raebareli and Bariyampur site of Fatehpur respectively. Our result revealed that various fauna enriched with soil reclamation, which is good indicator of restoration of land, primarily due to soil-arthropods and earthworms and its eventual improvement along with succeeding rice-wheat cropping system widespread over there. It clearly shows that soil fauna strongly affects the composition of natural vegetation and we suggest that this knowledge might improve the restoration and conservation of biodiversity.

  9. Retrieval of Fog Microphysical Parameters from NOAA AVHRR Data

    NASA Astrophysics Data System (ADS)

    Xu, Ling

    1995-01-01

    Identifying the droplet size distribution, frequency and location of land-based fog is valuable for climate studies, because of the effects on agricultural productivity projections, highway traffic safety, and urban pollution monitoring. It's especially important to the Central Valley of California, which frequently suffers lingering, heavy fog. Land-based fog plays an important role in surface radiation budgets, by blocking daytime solar heating and nocturnal long wave cooling. The droplet size distribution determines the optical depth and radiative attenuation of fog. An operational retrieval method for obtaining droplet size and optical depth has been developed for land -based fog from the multichannel NOAA (National Oceanic and Atmospheric Administration) AVHRR (Advanced Very High Resolution Radiometer) digital image data. The visible and near infrared images provide the reflectances of both channels, which vary with droplet microphysical characteristics. The reflectances are interpolated to radiative cloud modeling results. A new field method has been used for obtaining the measurements of land-based fog microphysical and thermodynamic parameters. A tethered balloon carries a meteorological package and a cloud droplet imaging system which transfer the images to a recording system on the ground. The results from the satellite imagery at Esparto (ESP), California are well matched with field sampling results at the same location.

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

    DOE PAGES

    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-scalemore » 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.« less

  11. 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.

  12. 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.

  13. AVHRR imagery reveals Antarctic ice dynamics

    NASA Technical Reports Server (NTRS)

    Bindschadler, Robert A.; Vornberger, Patricia L.

    1990-01-01

    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.

  14. 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.

  15. 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.

  16. Does Mexican Land Management Influence US Southwest Rainfall? Effects of Vegetation Seasonality and Land Use Change on Atmospheric Moisture Transport in the North American Monsoon

    NASA Astrophysics Data System (ADS)

    Bohn, T. J.; Vivoni, E. R.

    2013-12-01

    Southern Arizona and New Mexico receive 30-50% of their annual rainfall in the summer, as part of the North American Monsoon (NAM). Modeling studies suggest that 15-25% of this rainfall first falls on Mexican land, is transpired by vegetation, and subsequently is transported northward across the border to the US. The main source regions in Mexico lie in the subtropical scrub and tropical deciduous forests in the foothills of the Sierra Madre Occidental, in the states of Sinaloa and Sonora. A key characteristic of these natural ecosystems is their rapid greening at the onset of the monsoon, which maximizes the amount of moisture transpired from the soil into the atmosphere in the days immediately following rainfall. These ecosystems are under threat from a number of human activities, including expansion of rainfed and irrigated agriculture, deforestation for grazing activities and urbanization. These changes in land use result in dramatically different seasonality and magnitude of evapotranspiration. In this study, we examine the differences in spatial and temporal characteristics of evapotranspiration yielded by current and pre-industrial land cover. To this end, we employ the Variable Infiltration Capacity (VIC) land surface model at 1/16 degree resolution, driven by gridded meteorological observations and the MCD15A3 4-day MODIS LAI product, across the NAM region (Arizona, New Mexico, and northern Mexico). We compare the magnitude and timing of land-atmosphere fluxes given by both pre-industrial and current land cover/use, as well as the land cover under several possible alternative land use scenarios. We identify the regions where the largest changes in magnitude and timing of evapotranspiration have occurred, as well as the regions and land use changes that could produce the largest changes in future evapotranspiration under different scenarios. Finally, we explore the consequences these effects have for monsoon moisture transport.

  17. Diurnal and seasonal variations of wind farm impacts on land surface temperature over western Texas

    NASA Astrophysics Data System (ADS)

    Zhou, Liming; Tian, Yuhong; Baidya Roy, Somnath; Dai, Yongjiu; Chen, Haishan

    2013-07-01

    This paper analyzes seasonal and diurnal variations of MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data at ~1.1 km for the period of 2003-2011 over a region in West-Central Texas, where four of the world's largest wind farms are located. Seasonal anomalies are created from MODIS Terra (~10:30 a.m. and 10:30 p.m. local solar time) and Aqua (~1:30 a.m. and 1:30 p.m. local solar time) LSTs, and their spatiotemporal variability is analyzed by comparing the LST changes between wind farm pixels (WFPs) and nearby non wind farm pixels (NNWFPs) using different methods under different quality controls. Our analyses show consistently that there is a warming effect of 0.31-0.70 °C at nighttime for the nine-year period during which data was collected over WFPs relative to NNWFPs, in all seasons for both Terra and Aqua measurements, while the changes at daytime are much noisier. The nighttime warming effect is much larger in summer than winter and at ~10:30 p.m. than ~1:30 a.m. and hence the largest warming effect is observed at ~10:30 p.m. in summer. The spatial pattern and magnitude of this warming effect couple very well with the geographic distribution of wind turbines and such coupling is stronger at nighttime than daytime and in summer than winter. Together, these results suggest that the warming effect observed in MODIS over wind farms are very likely attributable to the development of wind farms. This inference is consistent with the increasing number of operational wind turbines with time during the study period, the diurnal and seasonal variations in the frequency of wind speed and direction distribution, and the changes in near-surface atmospheric boundary layer (ABL) conditions due to wind farm operations. The nocturnal ABL is typically stable and much thinner than the daytime ABL and hence the turbine enhanced vertical mixing produces a stronger nighttime effect. The stronger wind speed and the higher frequency of the wind

  18. 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.

  19. 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

  20. An AVHRR Multiple Cloud-Type Classification Package.

    NASA Astrophysics Data System (ADS)

    Tag, Paul M.; Bankert, Richard L.; Brody, L. Robin

    2000-02-01

    Using imagery from NOAA's Advanced Very High Resolution Radiometer (AVHRR) orbiting sensor, one of the authors (RLB) earlier developed a probabilistic neural network cloud classifier valid over the world's maritime regions. Since then, the authors have created a database of nearly 8000 16 × 16 pixel cloud samples (from 13 Northern Hemispheric land regions) independently classified by three experts. From these samples, 1605 were of sufficient quality to represent 11 conventional cloud types (including clear). This database serves as the training and testing samples for developing a classifier valid over land. Approximately 200 features, calculated from a visible and an infrared channel, form the basis for the computer vision analysis. Using a 1-nearest neighbor classifier, meshed with a feature selection method using backward sequential selection, the authors select the fewest features that maximize classification accuracy. In a leave-one-out test, overall classification accuracies range from 86% to 78% for the water and land classifiers, with accuracies at 88% or greater for general height-dependent groupings. Details of the databases, feature selection method, and classifiers, as well as example simulations, are presented.

  1. 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

  2. Environmental degradation analysis using NOAA/AVHRR data

    NASA Astrophysics Data System (ADS)

    Singh, D.; Meirelles, M. S.; Costa, G. A.; Herlin, I.; Berroir, J. P.; Silva, E. F.

    This work proposes a particular approach to assess information about soil degradation, based on a methodology to calculate soil color from NOAA/AVHRR data. As erosive processes change physical and chemical properties of the soil, altering, consequently, the superficial color, monitoring the change in color over time can help to identify and analyze those processes. The test area of the methodology is the Upper Taquari River Basin, in the central region of Brazil, where the lack of planning of agricultural land use has been causing important erosion with consequent intensification of the deposition of sediments in the water bodies, increasing the spatial and temporal significance of flood events over the Brazilian Pantanal region, a Biosphere Reserve. Based on a theoretical model, which establishes the relationship among the soil color (described in the Munsell Color System), vegetation indices, surface temperature and emissivity, the methodology has three main phases: determination of the correlation models among soil color and vegetation indices, emissivity and surface temperature; generation of digital soil color models; and statistical evaluation of the calculated color. The tests showed that the methodology is efficient in determining soil color using the NDVI, MSAVI and PAVI vegetation indices. Best results were obtained for the hue color component: comparing the calculated hue with ground truth data, the following determination coefficients (r^2) were found: 0.76 for NDVI, 0.74 for MSAVI and 0.75 for PAVI. To further test the methodology, the calculated digital color models were compared with the characteristic color of soil classes in the Upper Taquari Basin. The results of this application confirmed the methodology's capacity to determine the soil color from NOAA/AVHRR data. This type of study is quite helpful to know the erosion of soil as well as some abrupt change in soil due to natural hazards by space borne or air-borne sensors.

  3. Rule-based land use/land cover classification in coastal areas using seasonal remote sensing imagery: a case study from Lianyungang City, China.

    PubMed

    Yang, Xiaoyan; Chen, Longgao; Li, Yingkui; Xi, Wenjia; Chen, Longqian

    2015-07-01

    Land use/land cover (LULC) inventory provides an important dataset in regional planning and environmental assessment. To efficiently obtain the LULC inventory, we compared the LULC classifications based on single satellite imagery with a rule-based classification based on multi-seasonal imagery in Lianyungang City, a coastal city in China, using CBERS-02 (the 2nd China-Brazil Environmental Resource Satellites) images. The overall accuracies of the classification based on single imagery are 78.9, 82.8, and 82.0% in winter, early summer, and autumn, respectively. The rule-based classification improves the accuracy to 87.9% (kappa 0.85), suggesting that combining multi-seasonal images can considerably improve the classification accuracy over any single image-based classification. This method could also be used to analyze seasonal changes of LULC types, especially for those associated with tidal changes in coastal areas. The distribution and inventory of LULC types with an overall accuracy of 87.9% and a spatial resolution of 19.5 m can assist regional planning and environmental assessment efficiently in Lianyungang City. This rule-based classification provides a guidance to improve accuracy for coastal areas with distinct LULC temporal spectral features.

  4. 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.

  5. Arctic ice surface temperature retrieval from AVHRR thermal channels

    NASA Technical Reports Server (NTRS)

    Key, J.; Haeflinger, M.

    1992-01-01

    The relationship between AVHRR thermal radiances and the surface (skin) temperature of Arctic snow-covered sea ice is examined through forward calculations of the radiative transfer equation, providing an ice/snow surface temperature retrieval algorithm for the central Arctic Basin. Temperature and humidity profiles with cloud observations collected on an ice island during 1986-1987 are used. Coefficients that correct for atmospheric attenuation are given for three Arctic clear sky 'seasons', as defined through statistical analysis of the daily profiles, for the NOAA 7, 9, and 11 satellites. Modeled directional snow emissivities, different in the two split-window (11 and 12 micron) channels, are used. While the sensor scan angle is included explicitly in the correction equation, its effect in the dry Arctic atmosphere is small, generally less than 0.1 K. Using the split-window channels and scan angle, the rms error in the estimated ice surface temperature is less than 0.1 K in all seasons. Inclusion channel 3(3.7 microns) during the winter decreases the rms error by less than 0.003

  6. 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.

  7. Assessment of Early Season Agricultural Drought Through Land Surface Water Index (lswi) and Soil Water Balance Model

    NASA Astrophysics Data System (ADS)

    Chandrasekar, K.; Sesha Sai, M. V. R.; Behera, G.

    2011-08-01

    An attempt was made to address the early season agriculture drought, by monitoring the surface soil wetness during 2010 cropping seasons in the states of Andhra Pradesh and Tamil Nadu. Short Wave Infrared (SWIR) based Land Surface Water Index (LSWI) and Soil Water Balance (SWB) model using inputs from remote sensing and ancillary data were used to monitor early season agriculture drought. During the crop season, investigation was made on LSWI characteristics and its response to the rainfall. It was observed that the Rate of Increase (RoI) of LSWI was the highest during the fortnights when the onset of monsoon occurred. The study showed that LSWI is sensitive to the onset of monsoon and initiation of cropping season. The second part of this study attempted to develop a simple book keeping - bucket type - water tight soil water balance model to derive the top 30cm profile soil moisture using climatic, soil and crop parameters as the basic inputs. Soil moisture derived from the model was used to compute the Area Conducive for Sowing (ACS) during the sowing window of the cropping season. The soil moisture was validated spatially and temporally with the ground observed soil moisture values. The ACS was compared with the RoI of LSWI. The results showed that the RoI was high during the sowing window whenever the ACS was greater than 50% of the district area. The observation was consistent in all the districts of the two states. Thus the analysis revealed the potential of LSWI for early season agricultural drought management.

  8. Non-Growing Season Dynamics of Nitrous Oxide Emissions From Cropped Land in Southern Ontario, Canada

    NASA Astrophysics Data System (ADS)

    Zurbrigg, M. E.; Petrone, R. M.; English, M. C.; Spoelstra, J.; Macrae, M. L.

    2009-05-01

    As atmospheric nitrous oxide (N2O) is increasing at a rate of 0.3% per annum and has a global warming potential 300 times greater than that of carbon dioxide (CO2), it is crucial to understand the dynamics of anthropogenic emissions of this greenhouse gas. Although agriculture represents a small proportion of Canadian land use, it is the most significant source of both human-derived and natural N2O emissions in this country. More than 50% of annual N2O emissions from agricultural soils in northern latitudes may take place in the non-growing season (NGS). Southern Ontario is one of the most intensively farmed regions of Canada. Greater understanding of NGS dynamics of N2O flux will help to develop more accurate N2O modeling methodologies for this region and may help in the refinement of agricultural practices which reduce N2O emissions. This study investigated field and lab NGS dynamics of agricultural N2O flux in southern Ontario, where anaerobic conditions, such as those caused by snowmelt, icemelt and rain, promote the reduction of soil nitrate (NO3-) to N2O. Gas samples were collected from permanent soil gas collars in nine field sites following winter and spring thaw events over the NGS of 2007-2008; otherwise samples were collected at biweekly intervals from these collars, or by means of snow gas chambers when the sites were snow-covered. The field sites were situated in three working farm fields where soils were subjected to typical tillage, amendment and cropping practices. Field data were supplemented by experimental results from soil cores taken from one of two fields previously seeded to corn, and subjected to simulated freeze-thaw cycles of average frequency, duration, and amplitude found in this region. The experimental data show a highly significant positive correlation between N2O flux and soil temperature at 5 cm depth (p < 0.0005). Overall, the field data show a positive correlation between N2O flux and soil temperature (p < 0.025). The less

  9. 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

  10. ATLAS of archived vegetation, land-use and seasonal Albedo data sets

    SciTech Connect

    Matthews, E.

    1985-01-01

    Global data bases of vegetation, land use, and land cover have been compiled for use in climate studies at a 1/sup 0/ latitude x 1/sup 0/ longitude resolution, drawing on approximately 100 published sources. Each of these data sets covers the entire land surface of the earth. They all include non-zero data for permanent land only, including continental ice; water, including oceans and lakes, is zero. This report includes maps, presented by continent, of the complete archived data, with the exception of Antarctica. This series of maps is designed to be used independently or as a complement to the archived data.

  11. 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...

  12. 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...

  13. 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...

  14. Wildfire seasonality and land use: when do wildfires prefer to burn?

    PubMed

    Bajocco, Sofia; Pezzatti, Gianni Boris; Mazzoleni, Stefano; Ricotta, Carlo

    2010-05-01

    Because of the increasing anthropogenic fire activity, understanding the role of land-use in shaping wildfire regimes has become a major concern. In the last decade, an increasing number of studies have been carried out on the relationship between land-use and wildfire patterns, in order to identify land-use types where fire behaves selectively, showing a marked preference (or avoidance) in terms of fire incidence. By contrast, the temporal aspects of the relationship between landuse types and wildfire occurrence have received far less attention. The aim of this paper is, thus, to analyze the temporal patterns of fire occurrence in Sardinia (Italy) during the period 2000-2006 to identify land-use types where wildfires occur earlier or later than expected from a random null model. The study highlighted a close relationship between the timing of fire occurrence and land-cover that is primarily governed by two complementary processes: climatic factors that act indirectly on the timing of wildfires determining the spatial distribution of land-use types, and human population and human pressure that directly influence fire ignition. From a practical viewpoint, understanding the temporal trends of wildfires within the different land-use classes can be an effective decision-support tool for fire agencies in managing fire risk and for producing provisional models of fire behavior under changing climatic scenarios and evolving landscapes.

  15. 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.

  16. 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.

  17. 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)....

  18. 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.

  19. The relationship of GIMMS AVHRR NDVI, MODIS NDVI, SPOT NDVI and SeaWiFS NDVI for phenological analysis

    NASA Astrophysics Data System (ADS)

    Chai, J.; de Beurs, K.

    2010-12-01

    Normalized Difference Vegetation Index (NDVI) products derived from the NOAA AVHRR, MODIS, SPOT and SeaWiFS sensors are commonly used for Land Surface Phenology (LSP) analysis. NDVI data can be used to track green vegetation growth stages (emergence, growth, maturity, and harvest), which in turn can help us better monitor the impacts of climate change. However, NDVI products from different instruments vary in spatial resolution, temporal coverage and spectral range. As a result, multi-sensor NDVI products are rarely used in a single phenological study. Most studies that compare NDVI data with the object of extending available records, developed cross sensor translation equations. Instead, in this work, we aim to compare multi-sensor NDVI data by using phenological models. To understand the relationship of LSP derived measurements based on different NDVI datasets, we test two hypotheses: 1)Although there is dissimilarity in data construction, LSP measurements retrieved from NDVI time series from different sensors follow linear relationships if compared by eco-region. To prove this, we compared the Start of Season (SOS) and End of Season (EOS) as extracted from different sensors within the EPA eco-region framework and found that the LSP measurements follow a linear relationship. 2) A phenologically fitted geographic framework could better reflect the similarities among data sources in multi-sensor NDVI comparisons. We found that the EPA eco-region framework appropriately represents the distribution of SOS and EOS in selected areas but that modification of the currently existed eco-region and pheno-region systems could aid future multi-sensor NDVI LSP studies. Comparison and verification are carried out based on different phenological models (SOS, EOS and peak timing).

  20. Seasonal persistence of faecal indicator organisms in soil following dairy slurry application to land by surface broadcasting and shallow injection.

    PubMed

    Hodgson, Christopher J; Oliver, David M; Fish, Robert D; Bulmer, Nicholas M; Heathwaite, A Louise; Winter, Michael; Chadwick, David R

    2016-12-01

    Dairy farming generates large volumes of liquid manure (slurry), which is ultimately recycled to agricultural land as a valuable source of plant nutrients. Different methods of slurry application to land exist; some spread the slurry to the sward surface whereas others deliver the slurry under the sward and into the soil, thus helping to reduce greenhouse gas (GHG) emissions from agriculture. The aim of this study was to investigate the impact of two slurry application methods (surface broadcast versus shallow injection) on the survival of faecal indicator organisms (FIOs) delivered via dairy slurry to replicated grassland plots across contrasting seasons. A significant increase in FIO persistence (measured by the half-life of E. coli and intestinal enterococci) was observed when slurry was applied to grassland via shallow injection, and FIO decay rates were significantly higher for FIOs applied to grassland in spring relative to summer and autumn. Significant differences in the behaviour of E. coli and intestinal enterococci over time were also observed, with E. coli half-lives influenced more strongly by season of application relative to the intestinal enterococci population. While shallow injection of slurry can reduce agricultural GHG emissions to air it can also prolong the persistence of FIOs in soil, potentially increasing the risk of their subsequent transfer to water. Awareness of (and evidence for) the potential for 'pollution-swapping' is critical in order to guard against unintended environmental impacts of agricultural management decisions.

  1. Loss of Arctic Snow Cover and Sea Ice Extent Across the Land-Ocean Boundary During the Melt Season

    NASA Astrophysics Data System (ADS)

    Bliss, A.; Anderson, M. R.

    2010-12-01

    Concern over the rapid changes in the Arctic cryosphere in recent years has spurred much research into the response of sea ice and snow cover to warming temperatures and the resulting climate feedbacks. However, the vast majority of Arctic climate studies do not assess the response of both continental snow cover and sea ice in concert through the data record. This study is designed to compare the monthly Northern Hemispheric continental snow cover extent data available from Rutgers University Global Snow Lab and the passive microwave derived monthly Bootstrap algorithm sea ice extent data available from the National Snow and Ice Data Center (NSIDC) in the Arctic during the melt season (March-August) over the 29-year study period 1979-2007. Since these data are stored in incompatible formats, little research has gone into studying the concurrent variations in the annual loss of continental snow cover and sea ice extent across the land-ocean boundary. However, with a creation of a snow and ice extent climate data record (CDR) incorporating different data formats, one would allow analysis of these data to investigate conditions during the melt season. As a CDR example three autonomous study regions located in Siberia, North America, and Western Russia were determined to reveal any differences in the response of snow and sea ice extents during melt. Each study domain extends from over land, northward, into an Arctic marginal sea, containing a land-ocean boundary that is roughly parallel to latitude and is subject to considerable inter-annual variability in the extent and retreat of both snow and sea ice during the warm season. Each domain area was also selected to include a minimal extent of mountainous areas where persistent snow cover throughout the year could misrepresent the seasonal northward progression of snow cover lost, relative to other land domains in the study. The results show on average, sea ice extent is lost earlier in the year, in May, than snow cover

  2. 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.

  3. 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.

  4. 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.

  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. 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.

  7. 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.

  8. Spatial variations of sea level along the coast of Thailand: Impacts of extreme land subsidence, earthquakes and the seasonal monsoon

    NASA Astrophysics Data System (ADS)

    Saramul, Suriyan; Ezer, Tal

    2014-11-01

    The study addresses two important issues associated with sea level along the coasts of Thailand: first, the fast sea level rise and its spatial variation, and second, the monsoonal-driven seasonal variations in sea level. Tide gauge data that are more extensive than in past studies were obtained from several different local and global sources, and relative sea level rise (RSLR) rates were obtained from two different methods, linear regressions and non-linear Empirical Mode Decomposition/Hilbert-Huang Transform (EMD/HHT) analysis. The results show extremely large spatial variations in RSLR, with rates varying from ~ 1 mm y-1 to ~ 20 mm y-1; the maximum RSLR is found in the upper Gulf of Thailand (GOT) near Bangkok, where local land subsidence due to groundwater extraction dominates the trend. Furthermore, there are indications that RSLR rates increased significantly in all locations after the 2004 Sumatra-Andaman Earthquake and the Indian Ocean tsunami that followed, so that recent RSLR rates seem to have less spatial differences than in the past, but with high rates of ~ 20-30 mm y-1 almost everywhere. The seasonal sea level cycle was found to be very different between stations in the GOT, which have minimum sea level in June-July, and stations in the Andaman Sea, which have minimum sea level in February. The seasonal sea-level variations in the GOT are driven mostly by large-scale wind-driven set-up/set-down processes associated with the seasonal monsoon and have amplitudes about ten times larger than either typical steric changes at those latitudes or astronomical annual tides.

  9. Projected land photosynthesis constrained by changes in the seasonal cycle of atmospheric CO2.

    PubMed

    Wenzel, Sabrina; Cox, Peter M; Eyring, Veronika; Friedlingstein, Pierre

    2016-10-27

    Uncertainties in the response of vegetation to rising atmospheric CO2 concentrations contribute to the large spread in projections of future climate change. Climate-carbon cycle models generally agree that elevated atmospheric CO2 concentrations will enhance terrestrial gross primary productivity (GPP). However, the magnitude of this CO2 fertilization effect varies from a 20 per cent to a 60 per cent increase in GPP for a doubling of atmospheric CO2 concentrations in model studies. Here we demonstrate emergent constraints on large-scale CO2 fertilization using observed changes in the amplitude of the atmospheric CO2 seasonal cycle that are thought to be the result of increasing terrestrial GPP. Our comparison of atmospheric CO2 measurements from Point Barrow in Alaska and Cape Kumukahi in Hawaii with historical simulations of the latest climate-carbon cycle models demonstrates that the increase in the amplitude of the CO2 seasonal cycle at both measurement sites is consistent with increasing annual mean GPP, driven in part by climate warming, but with differences in CO2 fertilization controlling the spread among the model trends. As a result, the relationship between the amplitude of the CO2 seasonal cycle and the magnitude of CO2 fertilization of GPP is almost linear across the entire ensemble of models. When combined with the observed trends in the seasonal CO2 amplitude, these relationships lead to consistent emergent constraints on the CO2 fertilization of GPP. Overall, we estimate a GPP increase of 37 ± 9 per cent for high-latitude ecosystems and 32 ± 9 per cent for extratropical ecosystems under a doubling of atmospheric CO2 concentrations on the basis of the Point Barrow and Cape Kumukahi records, respectively.

  10. Projected land photosynthesis constrained by changes in the seasonal cycle of atmospheric CO2

    NASA Astrophysics Data System (ADS)

    Wenzel, Sabrina; Cox, Peter M.; Eyring, Veronika; Friedlingstein, Pierre

    2016-10-01

    Uncertainties in the response of vegetation to rising atmospheric CO2 concentrations contribute to the large spread in projections of future climate change. Climate-carbon cycle models generally agree that elevated atmospheric CO2 concentrations will enhance terrestrial gross primary productivity (GPP). However, the magnitude of this CO2 fertilization effect varies from a 20 per cent to a 60 per cent increase in GPP for a doubling of atmospheric CO2 concentrations in model studies. Here we demonstrate emergent constraints on large-scale CO2 fertilization using observed changes in the amplitude of the atmospheric CO2 seasonal cycle that are thought to be the result of increasing terrestrial GPP. Our comparison of atmospheric CO2 measurements from Point Barrow in Alaska and Cape Kumukahi in Hawaii with historical simulations of the latest climate-carbon cycle models demonstrates that the increase in the amplitude of the CO2 seasonal cycle at both measurement sites is consistent with increasing annual mean GPP, driven in part by climate warming, but with differences in CO2 fertilization controlling the spread among the model trends. As a result, the relationship between the amplitude of the CO2 seasonal cycle and the magnitude of CO2 fertilization of GPP is almost linear across the entire ensemble of models. When combined with the observed trends in the seasonal CO2 amplitude, these relationships lead to consistent emergent constraints on the CO2 fertilization of GPP. Overall, we estimate a GPP increase of 37 ± 9 per cent for high-latitude ecosystems and 32 ± 9 per cent for extratropical ecosystems under a doubling of atmospheric CO2 concentrations on the basis of the Point Barrow and Cape Kumukahi records, respectively.

  11. A comprehensive emission inventory of biogenic volatile organic compounds in Europe: improved seasonality and land-cover

    NASA Astrophysics Data System (ADS)

    Oderbolz, D. C.; Aksoyoglu, S.; Keller, J.; Barmpadimos, I.; Steinbrecher, R.; Skjøth, C. A.; Plaß-Dülmer, C.; Prévôt, A. S. H.

    2013-02-01

    Biogenic volatile organic compounds (BVOC) emitted from vegetation are important for the formation of secondary pollutants such as ozone and secondary organic aerosols (SOA) in the atmosphere. Therefore, BVOC emission are an important input for air quality models. To model these emissions with high spatial resolution, the accuracy of the underlying vegetation inventory is crucial. We present a BVOC emission model that accommodates different vegetation inventories and uses satellite-based measurements of greenness instead of pre-defined vegetation periods. This approach to seasonality implicitly treats effects caused by water or nutrient availability, altitude and latitude on a plant stand. Additionally, we test the influence of proposed seasonal variability in enzyme activity on BVOC emissions. In its present setup, the emission model calculates hourly emissions of isoprene, monoterpenes, sesquiterpenes and the oxygenated volatile organic compounds (OVOC) methanol, formaldehyde, formic acid, ethanol, acetaldehyde, acetone and acetic acid. In this study, emissions based on three different vegetation inventories are compared with each other and diurnal and seasonal variations in Europe are investigated for the year 2006. Two of these vegetation inventories require information on tree-cover as an input. We compare three different land-cover inventories (USGS GLCC, GLC2000 and Globcover 2.2) with respect to tree-cover. The often-used USGS GLCC land-cover inventory leads to a severe reduction of BVOC emissions due to a potential miss-attribution of broad-leaved trees and reduced tree-cover compared to the two other land-cover inventories. To account for uncertainties in the land-cover classification, we introduce land-cover correction factors for each relevant land-use category to adjust the tree-cover. The results are very sensitive to these factors within the plausible range. For June 2006, total monthly BVOC emissions decreased up to -27% with minimal and increased

  12. The AVHRR component of a long-term global active fire data record

    NASA Astrophysics Data System (ADS)

    Csiszar, I. A.; Giglio, L.; Schroeder, W.; Justice, C. O.

    2010-12-01

    capabilities strongly depend on the observing system, establishing a continuity is also needed among AVHRR and other major observing systems, such as the (Advanced) Along-Track Scanning Radiometer ((A)ATSR), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the upcoming Visible Infrared Imager Radiometer Suite (VIIRS) and Sea and Land Surface Temperature Radiometer (SLSTR). Such continuity can be established by improved understanding of detection capabilities through product validation and simulations and by using geostationary fire observations as a reference to account for differences in satellite overpass times and the consequent different sampling of the diurnal cycle of fire activity from polar orbiters.

  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.; 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. Seasonal modulation of free radical metabolism in estivating land snails Helix aspersa.

    PubMed

    Ramos-Vasconcelos, Gabriella R; Cardoso, Luciano A; Hermes-Lima, Marcelo

    2005-02-01

    We investigated the regulation of free radical metabolism in Helix aspersa snails during a cycle of 20-day estivation and 24-h arousal in summer in comparison with estivation/arousal in winter-snails. In winter-snails (J. Exp. Biol. 206, 675-685, 2003), we had already observed an increase in the selenium-dependent glutathione-peroxidase (Se-GPX) activity in foot muscle and hepatopancreas and in the contents of hepatopancreas GSH-equivalents (GSH-eq=GSH+2 GSSG) during estivation compared with 24-h aroused snails. Summer-estivation prompted a 3.6-fold increase in Se-GPX activity in hepatopancreas, though not in foot muscle. Total-superoxide dismutase and catalase activities in hepatopancreas decreased (by 30-40%) during summer-estivation; however, no changes occurred in the activities of glutathione reductase, glutathione S-transferase and glucose-6-phosphate dehydrogenase in the two organs. GSH-eq levels were increased (by 54%) in foot muscle during estivation, but were unchanged in hepatopancreas. In contrast with winter-snails, oxidative stress markers (lipid peroxidation, carbonyl protein, and the GSSG/GSH-eq ratio) were unaltered during estivation/arousal in summer. These results demonstrate that seasonality modulates not only the absolute activities/levels of antioxidants (enzymes and GSH-eq) in H. aspersa, but also the regulatory process that controls the snail's antioxidant capacity during estivation/arousal. These results suggest that H. aspersa has an "internal clock" controlling the regulation of free radical metabolism in the different seasons.

  16. 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.

  17. 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

  18. Land surface models systematically overestimate the intensity, duration and magnitude of seasonal-scale evaporative droughts

    NASA Astrophysics Data System (ADS)

    Ukkola, A. M.; De Kauwe, M. G.; Pitman, A. J.; Best, M. J.; Abramowitz, G.; Haverd, V.; Decker, M.; Haughton, N.

    2016-10-01

    Land surface models (LSMs) must accurately simulate observed energy and water fluxes during droughts in order to provide reliable estimates of future water resources. We evaluated 8 different LSMs (14 model versions) for simulating evapotranspiration (ET) during periods of evaporative drought (Edrought) across six flux tower sites. Using an empirically defined Edrought threshold (a decline in ET below the observed 15th percentile), we show that LSMs simulated 58 Edrought days per year, on average, across the six sites, ∼3 times as many as the observed 20 d. The simulated Edrought magnitude was ∼8 times greater than observed and twice as intense. Our findings point to systematic biases across LSMs when simulating water and energy fluxes under water-stressed conditions. The overestimation of key Edrought characteristics undermines our confidence in the models’ capability in simulating realistic drought responses to climate change and has wider implications for phenomena sensitive to soil moisture, including heat waves.

  19. EOF analysis of long-term reconstructed AVHRR Pathfinder SST in the South China Sea

    NASA Astrophysics Data System (ADS)

    Huynh, Hong-Ngu T.; Alvera-Azcárate, Aida; Barth, Alexander; Beckers, Jean-Marie

    2014-05-01

    Sea surface temperature (SST) is one of the key variables often used to investigate ocean dynamics, ocean-atmosphere interaction, and climate change. For recent decades, the AVHRR Pathfinder SST, measured by infrared sensors, has been widely used because of its high resolution and long time-series. The disadvantage of the AVHRR Pathfinder SST is high percentage of missing data due to cloud coverage. This becomes more serious in the South China Sea (SCS) because it is located in the tropical region, frequently covered by clouds. In this study, we used the Data INterpolating Empirical Orthogonal Functions (DINEOF) method to reconstruct daily night-time 4 km AVHRR Pathfinder SST spanning from 1989 to 2009 for the whole SCS. In order to better understand the spatial and temporal variability of the SCS SST, an EOF analysis of the reconstructed field is performed in association with surface wind. The first SST mode, accounting for 69% of the variance, presents the cooling (warming) of the basin due to the solar inclination through seasons, water exchange, topography, and monsoon-induced cyclonic circulation. The second SST mode, explaining 24.8% of the variance, shows the advection of cold and warm water from two opposite directions along the southwest-northeast diagonal of the basin. The second SST mode is affected by the atmospheric anticyclone (cyclone) located over the Philippine Sea. Comparing both SST modes with Nino3.0 index, it shows that the interannual variability of the SCS SST is influenced by the moderate and strong ENSO events with a lag of 5-6 months. Moreover, the analysis of the high-resolution reconstructed dataset reveals some oceanic features that could not be captured in the previous EOF analyses.

  20. 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.

  1. [Dendrolimus spp. damage monitoring by using NOAA/AVHRR data].

    PubMed

    Zhang, Yushu; Ban, Xianxiu; Chen, Pengshi; Feng, Rui; Ji, Ruipeng; Xiao, Yan

    2005-05-01

    This paper approached the feasibility of quantitatively monitoring Dendrolimus spp. damage by using NOAA/ AVHRR data. The damaged rate of needle leaf was used to represent Dendrolimus spp. harming degree, and < 30%, 30%-60% and > 60% of damaged rate was defined as low, medium and severe harming degree, respectively. The correlation equation of damaged rate and normalized vegetation index (NDVI) was established, based on the ground spectrum observation. The NDVI was 0.8823 when no damage occurred. A relative NDVI value of damaged to undamaged area was used to express the remote sensing index of low, medium and severe harming degree. The index was 1 for undamaged forest, and 0.78-1, 0.57-0.78 and < 0.57 for low, medium and severe harming degrees, respectively. The mixed pixels were separated by linear addable vertical vegetation index in the monitoring, and the quantitative monitoring and analysis was accomplished for years when the three damage degrees happened. It was shown that AVHRR data could be more available in quantitatively monitoring and analyzing serious damage, while low degree damage was difficult to distinguish by AVHRR data, due to the differences of surface properties and atmospheric influences, as well as the lower space resolution of NOAA/AVHRR. The damaged area estimated by AVHRR was 12.1%-14.3% lower than that by TM.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. Satellite remote sensing of rangelands in Botswana. II - NOAA AVHRR and herbaceous vegetation

    NASA Technical Reports Server (NTRS)

    Prince, S. D.; Tucker, C. J.

    1986-01-01

    The relation between the normalized difference vegetation index (NDVI) and the herbaceous vegetation in Tamasane, Shakwe, and Masama in eastern Botswana is studied using 1983-1984 AVHRR data. The procedures for Landsat MSS interpolation of ground measurements and the data processing of the AVHRR data are described. The temporal sequence AVHRR global-area coverage (GAC) composite NDVI is examined. The AVHRR GAC composite NDVI and biomass and Landsat MSS interpolations of field measurements are analyzed and compared.

  7. 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.

  8. 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

  9. 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.

  10. Response of Arctic Snow and Sea Ice Extents to Melt Season Atmospheric Forcing Across the Land-Ocean Boundary

    NASA Astrophysics Data System (ADS)

    Bliss, A. C.; Anderson, M. R.

    2011-12-01

    Little research has gone into studying the concurrent variations in the annual loss of continental snow cover and sea ice extent across the land-ocean boundary, however, the analysis of these data averaged spatially over three study regions located in North America and Eastern and Western Russia, reveals a distinct difference in the response of anomalous snow and sea ice conditions to the atmospheric forcing. This study compares the monthly continental snow cover and sea ice extent loss in the Arctic, during the melt season months (May-August) for the period 1979-2007, with regional atmospheric conditions known to influence summer melt including: mean sea level pressures, 925 hPa air temperatures, and mean 2 m U and V wind vectors from NCEP/DOE Reanalysis 2. The monthly hemispheric snow cover extent data used are from the Rutgers University Global Snow Lab and sea ice extents for this study are derived from the monthly passive microwave satellite Bootstrap algorithm sea ice concentrations available from the National Snow and Ice Data Center. Three case study years (1985, 1996, and 2007) are used to compare the direct response of monthly anomalous sea ice and snow cover areal extents to monthly mean atmospheric forcing averaged spatially over the extent of each study region. This comparison is then expanded for all summer months over the 29 year study period where the monthly persistence of sea ice and snow cover extent anomalies and changes in the sea ice and snow conditions under differing atmospheric conditions are explored further. The monthly anomalous atmospheric conditions are classified into four categories including: warmer temperatures with higher pressures, warmer temperatures with lower pressures, cooler temperatures with higher pressures, and cooler temperatures with lower pressures. Analysis of the atmospheric conditions surrounding anomalous loss of snow and ice cover over the independent study regions indicates that conditions of warmer temperatures

  11. 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

  12. 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

  13. Spatial analysis and land use regression of VOCs and NO2 in Dallas, Texas during two seasons.

    PubMed

    Smith, Luther A; Mukerjee, Shaibal; Chung, Kuenja C; Afghani, Jim

    2011-04-01

    Passive air sampling for nitrogen dioxide (NO(2)) and select volatile organic compounds (VOCs) was conducted at 24 fire stations and a compliance monitoring site in Dallas, Texas, USA during summer 2006 and winter 2008. This ambient air monitoring network was established to assess intra-urban gradients of air pollutants to evaluate the impact of traffic and urban emissions on air quality. Ambient air monitoring and GIS data from spatially representative fire station sites were collected to assess spatial variability. Pairwise comparisons were conducted on the ambient data from the selected sites based on city section. These weeklong samples yielded NO(2) and benzene levels that were generally higher during the winter than the summer. With respect to the location within the city, the central section of Dallas was generally higher for NO(2) and benzene than north and south. Land use regression (LUR) results revealed spatial gradients in NO(2) and selected VOCs in the central and some northern areas. The process used to select spatially representative sites for air sampling and the results of analyses of coarse- and fine-scale spatial variability of air pollutants on a seasonal basis provide insights to guide future ambient air exposure studies in assessing intra-urban gradients and traffic impacts.

  14. 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.

  15. Role of CO2, climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: a multimodel analysis

    NASA Astrophysics Data System (ADS)

    Zhao, Fang; Zeng, Ning; Asrar, Ghassem; Friedlingstein, Pierre; Ito, Akihiko; Jain, Atul; Kalnay, Eugenia; Kato, Etsushi; Koven, Charles D.; Poulter, Ben; Rafique, Rashid; Sitch, Stephen; Shu, Shijie; Stocker, Beni; Viovy, Nicolas; Wiltshire, Andy; Zaehle, Sonke

    2016-09-01

    We examined the net terrestrial carbon flux to the atmosphere (FTA) simulated by nine models from the TRENDY dynamic global vegetation model project for its seasonal cycle and amplitude trend during 1961-2012. While some models exhibit similar phase and amplitude compared to atmospheric inversions, with spring drawdown and autumn rebound, others tend to rebound early in summer. The model ensemble mean underestimates the magnitude of the seasonal cycle by 40 % compared to atmospheric inversions. Global FTA amplitude increase (19 ± 8 %) and its decadal variability from the model ensemble are generally consistent with constraints from surface atmosphere observations. However, models disagree on attribution of this long-term amplitude increase, with factorial experiments attributing 83 ± 56 %, -3 ± 74 and 20 ± 30 % to rising CO2, climate change and land use/cover change, respectively. Seven out of the nine models suggest that CO2 fertilization is the strongest control - with the notable exception of VEGAS, which attributes approximately equally to the three factors. Generally, all models display an enhanced seasonality over the boreal region in response to high-latitude warming, but a negative climate contribution from part of the Northern Hemisphere temperate region, and the net result is a divergence over climate change effect. Six of the nine models show that land use/cover change amplifies the seasonal cycle of global FTA: some are due to forest regrowth, while others are caused by crop expansion or agricultural intensification, as revealed by their divergent spatial patterns. We also discovered a moderate cross-model correlation between FTA amplitude increase and increase in land carbon sink (R2 = 0.61). Our results suggest that models can show similar results in some benchmarks with different underlying mechanisms; therefore, the spatial traits of CO2 fertilization, climate change and land use/cover changes are crucial in determining the right mechanisms in

  16. 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

  17. 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

  18. AVHRR calibration approach that uses ray-matching, invariant desert, and deep convective cloud techniques

    NASA Astrophysics Data System (ADS)

    Morstad, D.; Doelling, D. R.; Scarino, B.; Gopalan, A.; Bhatt, R.; Minnis, P.

    2010-12-01

    The Advanced Very High Resolution Radiometer (AVHRR) record spans over 30 years and provides a unique opportunity for long-term climate studies. The precision of these climate studies is largely reliant on the consistent absolute calibration of the AVHRR visible data. Currently, AVHRR visible sensors lack onboard calibration and must be vicariously monitored to assure stability over time. AVHRR onboard the NOAA satellites are on a degrading sun-synchronous orbit where the solar zenith angle continuously increases through time. The ray-matching technique can be used to transfer the calibration of a well-calibrated sensor, such as MODIS that employs a solar diffuser, to an un-calibrated sensor, such as AVHRR. In order to transfer the MODIS calibration to AVHRR, existing GEO satellites will be used as a transfer medium. Successive GEO to AVHRR transfers and AVHRR to GEO transfers will be used to maintain a consistent absolute calibration throughout the AVHRR record. To ensure the absolute calibration is accurately transferred, differences in the spectral response functions between each sensor can be removed using ENVISAT Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) hyperspectral data and spectral band adjustment factors. The temporal trends in the absolute calibration of AVHRR and GEO can be validated using pseudo-invariant test sites as well as deep convective cloud targets. This presentation will show examples of ray-matching, spectral band adjustment, DCC, and desert trending techniques and highlight the initial results for lifetime calibration of AVHRR onboard NOAA 16 and NOAA18.

  19. Behaviour of inter crop-growth stages scatterograms for NOAA/AVHRR vegetation indices

    NASA Astrophysics Data System (ADS)

    Gupta, Rajendra Kumar

    NOAA/AVHRR Normalized Difference Vegetation Index (NDVI) and Ratio Vegetation Index (RVI) scatterograms between two crop growth stage for 1986-1987 rabi season over Ludhiana district witnessing 94.9% of sown area under wheat were studied. Dispersions of RVI were less than that of NDVI for all crop growth stages except the stages witnessing no significant change in greenness where the magnitudes of dispersion were similar for RVI as well as NDVI. Scatterograms between dates witnessing high vegetative growth had bowl shapes while vertical cut off was witnessed for moderate rate wider variability (larger standard deviation) vegetative growth. Decrease in vegetative growth as well as in standard deviation resulted in horizontal cut-off. Typical cut off was observed in RVI scatterograms (not observed in NDVI) between mid of Milking-Dough and mid of Maturity-Harvesting stage.

  20. 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.

  1. Seasonal variation of nitrogen-concentration in the surface water and its relationship with land use in a catchment of northern China.

    PubMed

    Chen, Li-ding; Peng, Hong-jia; Fu, Bo-Jie; Qiu, Jun; Zhang, Shu-rong

    2005-01-01

    Surface waters can be contaminated by human activities in two ways: (1) by point sources, such as sewage treatment discharge and storm-water runoff; and (2) by non-point sources, such as runoff from urban and agricultural areas. With point-source pollution effectively controlled, non-point source pollution has become the most important environmental concern in the world. The formation of non-point source pollution is related to both the sources such as soil nutrient, the amount of fertilizer and pesticide applied, the amount of refuse, and the spatial complex combination of land uses within a heterogeneous landscape. Land-use change, dominated by human activities, has a significant impact on water resources and quality. In this study, fifteen surface water monitoring points in the Yuqiao Reservoir Basin, Zunhua, Hebei Province, northern China, were chosen to study the seasonal variation of nitrogen concentration in the surface water. Water samples were collected in low-flow period (June), high-flow period (July) and mean-flow period (October) from 1999 to 2000. The results indicated that the seasonal variation of nitrogen concentration in the surface water among the fifteen monitoring points in the rainfall-rich year is more complex than that in the rainfall-deficit year. It was found that the land use, the characteristics of the surface river system, rainfall, and human activities play an important role in the seasonal variation of N-concentration in surface water.

  2. 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.

  3. Condition of the Ross Ice Shelf derived from AVHRR imagery

    NASA Technical Reports Server (NTRS)

    Casassa, Gino

    1993-01-01

    Advanced Very High Resolution Radiometer (AVHRR) satellite imagery is combined with the Ross Ice Shelf Geophysical and Glaciological Survey (RIGGS) data to study recent changes on the Ross Ice Shelf. Flow stripes that appear on the AVHRR imagery agree with significant changes in ice flow that have occurred over the past 1,100 years on the ice shelf sector fed by East Antarctica. A large looping pattern of flow stripes that disagrees with RIGGS flow lines appears west of Crary Ice Rise, on the eastern part of the ice shelf. This looped pattern is interpreted as relict flow stripes related to past activity of a major ice stream of West Antarctica, which occurred about 800 years ago.

  4. Regression and ratio estimators to integrate AVHRR and MSS data

    NASA Technical Reports Server (NTRS)

    Nelson, Ross

    1989-01-01

    Regression and ratio estimators are used to integrate AVHRR-Global Area Coverage (GAC) and Landsat MSS digital data to estimate forest area in the continental United States. Forestlands are enumerated for the 48 contiguous states using five different AVHRR-GAC data sets. Results indicated that the GAC and MSS forest estimates were not highly correlated. Although the ratio of means and linear regression corrections were, on the average, closer to national U.S. Forest Service forest area estimates, these correction procedures did not consistently improve GAC estimates of forest area. GAC forest area estimates tended to be high in densely forested regions such as the northeast and low in sparsely forested areas.

  5. 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.

  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. 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.

  8. 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.

  9. Regional in-situ optical water quality sensor network quantifies influence of land use and seasonality on storm event nitrate and dissolved organic carbon loading

    NASA Astrophysics Data System (ADS)

    Vaughan, M.; Schroth, A. W.; Bowden, W. B.; Shanley, J. B.; Vermilyea, A.; Sleeper, R.; Gold, A.; Pradhanang, S. M.; Addy, K.; Inamdar, S. P.; Levia, D. F., Jr.; Rowland, R. D.; Winters, C. G.

    2015-12-01

    High frequency optical water quality sensors were used to determine the influence of land use and seasonality on storm nutrient loads at nine stream sites in the North East Water Resources Network (NEWRnet). S::can spectrolysersTM were used to measure UV-Visible absorbance spectra at sub-hourly intervals in streams with primarily forested, urban, and agricultural watersheds. Calibrations for nitrate (NO3) and dissolved organic carbon (DOC) concentrations were developed for in-situ spectrophotometer measurements using multivariate statistical techniques applied to absorbance spectra and laboratory measurements. Calibrations were evaluated for predictive power and compared to assess applicability across multiple land uses and geographical areas. Calibrations were applied to sub-hourly absorbance spectra to determine NO3 and DOC loads for all storms in 2014 and 2015 for which data were available. Hydrographs were partitioned into direct runoff and baseflow components using a digital filter technique. In addition, the amount of biodegradable DOC (BDOC) was determined for a subset of samples and related to spectrophotometer measurements to determine influences of land use on BDOC content during storms. Comparing NO3 and DOC export per watershed area to storm runoff shows that storm severity, storm frequency, and land use have strong influences on regional NO3 and DOC storm export. This study highlights the value of high frequency continuous stream monitoring for land use and watershed management, particularly in the context of storm event loading.

  10. 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).

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. Toward consistent radiometric calibration of the NOAA AVHRR visible and near-infrared data record

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

    The 35-year Advanced Very High Resolution Radiometer (AVHRR) satellite-instrument data record is critical for studying decadal climate change, provided that the AVHRR sensors are consistently calibrated. Owing to the lack of onboard calibration capability, the AVHRR data need to be adjusted using vicarious approaches. One of the greatest challenges hampering these vicarious calibration techniques, however, is the degrading orbits of the NOAA satellites that house the instruments, or, more specifically, the fact that the satellites eventually drift into a terminator orbit several years after launch. This paper presents a uniform sensor calibration approach for the AVHRR visible (VIS) and nearinfrared (NIR) records using specifically designed NOAA-16 AVHRR-based, top-of-atmosphere (TOA) calibration models that take into account orbit degradation. These models are based on multiple invariant Earth targets, including Saharan deserts, polar ice scenes, and tropical deep-convective clouds. All invariant targets are referenced to the Aqua- MODIS Collection-6 calibration via transfer of the Aqua-MODIS calibration to NOAA-16 AVHRR using simultaneous nadir overpass (SNO) comparisons over the North Pole. A spectral band adjustment factor, based on SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY (SCIAMACHY) spectral radiances, is used to account for the spectrally-induced biases caused by the spectral response function (SRF) differences of the AVHRR and MODIS sensors. Validation of the AVHRR Earth target calibration is performed by comparisons with contemporary MODIS SNOs. Calibration consistency between Earth targets validates the historical AVHRR record.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

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

    USGS Publications Warehouse

    Giri, Chandra; Defourny, Pierre; 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.

  3. Seasonal variation of and the influence of land use on carbon and water vapour fluxes at the Swiss Carbomont field site

    NASA Astrophysics Data System (ADS)

    Rogiers, N.; Eugster, W.; Furger, M.; Bantelmann, E.; Siegwolf, R.

    2003-04-01

    Within the EU project CARBOMONT the carbon dioxide and water vapour budget as well as the energy budgets over an Alpine grassland ecosystem are quantified. The goal of our continuous measurements of ecosystem fluxes can improve the understanding of the global carbon and water budgets. PSI has equipped a site at Rigi-Seebodenalp in Central Switzerland. The site is divided into different compartments with different land-use and management: an abandoned wet area, and a pasture for cow and horse foraging with two annual grass cuts. The net ecosystem exchange (NEE = photosynthesis + respiration) is determined with the eddy covariance method. These measurements are supplemented by conventional micrometeorological measurements. Here we try to quantify the fluxes of CO2 and H2O over the vegetation period starting in June 2002 till the end of October. The CO2 and H2O fluxes vary considerably over the course of the vegetation period. The seasonal variation of these fluxes can be explained by a change in the duration of the photosynthetically active period, a change in temperature and in leaf area index. Snow at the end of September reduced the CO2 uptake clearly. Further, the factors influencing the seasonal variation of canopy evaporation (latent heat flux) are determined. The influence of the land use on the turbulent exchange of CO2 is investigated. The cutting of the vegetation resulted in a decreased CO2 uptake during the day.

  4. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Seasonal effects of irrigation on land-atmosphere latent heat, sensible heat, and carbon fluxes in semiarid basin

    NASA Astrophysics Data System (ADS)

    Zeng, Yujin; Xie, Zhenghui; Liu, Shuang

    2017-02-01

    Irrigation, which constitutes ˜ 70 % of the total amount of freshwater consumed by the human population, is significantly impacting land-atmosphere fluxes. In this study, using the improved Community Land Model version 4.5 (CLM4.5) with an active crop model, two high-resolution (˜ 1 km) simulations investigating the effects of irrigation on latent heat (LH), sensible heat (SH), and carbon fluxes (or net ecosystem exchange, NEE) from land to atmosphere in the Heihe River basin in northwestern China were conducted using a high-quality irrigation dataset compiled from 1981 to 2013. The model output and measurements from remote sensing demonstrated the capacity of the developed models to reproduce ecological and hydrological processes. The results revealed that the effects of irrigation on LH and SH are strongest during summer, with a LH increase of ˜ 100 W m-2 and a SH decrease of ˜ 60 W m-2 over intensely irrigated areas. However, the reactions are much weaker during spring and autumn when there is much less irrigation. When the irrigation rate is below 5 mm day-1, the LH generally increases, whereas the SH decreases with growing irrigation rates. However, when the irrigation threshold is in excess of 5 mm day-1, there is no accrued effect of irrigation on the LH and SH. Irrigation produces opposite effects to the NEE during spring and summer. During the spring, irrigation yields more discharged carbon from the land to the atmosphere, increasing the NEE value by 0.4-0.8 gC m-2 day-1, while the summer irrigation favors crop fixing of carbon from atmospheric CO2, decreasing the NEE value by ˜ 0.8 gC m-2 day-1. The repercussions of irrigation on land-atmosphere fluxes are not solely linked to the irrigation amount, and other parameters (especially the temperature) also control the effects of irrigation on LH, SH, and NEE.

  15. Recent trends in agricultural production of Africa based on AVHRR NDVI time series

    NASA Astrophysics Data System (ADS)

    Vrieling, Anton; de Beurs, Kirsten M.; Brown, Molly E.

    2008-10-01

    African agriculture is expected to be hard-hit by ongoing climate change. Effects are heterogeneous within the continent, but in some regions resulting production declines have already impacted food security. Time series of remote sensing data allow us to examine where persistent changes occur. In this study, we propose to examine recent trends in agricultural production using 26 years of NDVI data. We use the 8-km resolution AVHRR NDVI 15-day composites of the GIMMS group (1981-2006). Temporal data-filtering is applied using an iterative Savitzky-Golay algorithm to remove noise in the time series. Except for some regions with persistent cloud cover, this filter produced smooth profiles. Subsequently two methods were used to extract phenology indicators from the profiles for each raster cell. These indicators include start of season, length of season, time of maximum NDVI, maximum NDVI, and cumulated NDVI over the season. Having extracted the indicators for every year, we aggregate them for agricultural areas at sub-national level using a crop mask. The aggregation was done to focus the analysis on agriculture, and allow future comparison with yield statistics. Trend analysis was performed for yearly aggregated indicators to assess where persistent change occurred during the 26-year period. Results show that the phenology extraction method chosen has an important influence on trend outcomes. Consistent trends suggest a rising yield trend for 500-1100 mm rainfall zones ranging from Senegal to Sudan. Negative yield trends are expected for the southern Atlantic coast of West Africa, and for western Tanzania.

  16. 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

  17. 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

  18. 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.

  19. The global land Cryosphere Radiative Effect during the MODIS era

    NASA Astrophysics Data System (ADS)

    Singh, D.; Flanner, M. G.; Perket, J.

    2015-07-01

    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 Spectrometer (MODIS), combined with microwave retrievals of snow presence and radiative kernels produced from 4 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 Hemisphere effect originates from seasonal snow. Consequently, the Northern Hemisphere land CrRE peaks at -6.0 W m-2 in April, whereas the Southern Hemisphere effect more closely follows the austral insolation cycle, peaking 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. Inter-annual 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 Hemisphere land CrRE are about 18 % smaller (less negative) than previous estimates derived from coarse-resolution AVHRR data, though inter-annual variations are well correlated (r = 0.78), indicating that these data are useful in determining longer term trends in land CrRE.

  20. 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.

  1. 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

  2. On the multiscale nature of soil moisture-temperature couplings: the role of seasonality, causation and non-linear feedbacks in land-atmosphere interactions (Invited)

    NASA Astrophysics Data System (ADS)

    Molini, A.; Casagrande, E.; Mueller, B.

    2013-12-01

    Land-Atmosphere (L-A) interactions, their strength and directionality, are one of the main sources of uncertainty in current climate modeling, with strong implications on the accurate assessment of future climate variability and climate change impacts. Beside from the scarcity of direct observations, major uncertainties derive from the inherent complexity and nonlinearity of these interactions, and from their multi-scale character. Statistical analysis of L-A couplings is traditionally based on linear correlation methods and metrics. However, these approaches are not designed to detect causal connections or non-linear couplings and they poorly perform in presence of non-stationarities. Additionally these methods assess L-A couplings essentially in the time domain, despite the fact that L-A dynamical drivers can act simultaneously over a wide range of different space and time scales. This talk explores the multi-scale nature of L-A interactions, through the example of soil moisture-temperature couplings and soil-moisture memory effects. In several regions of the world, soil moisture can have a dampening effect on temperature due to evaporative cooling. By using spectral decomposition techniques and both newly developed satellite based products and re-analysis, we analyze the contribution of different time scales to the build-up of global soil moisture-temperature coupling hot spots, addressing at the same time the role of seasonality, causation and non-linear feedbacks in land-atmosphere interactions. Finally we focus on the role of fine (sub-monthly) time scales and their interplay with the seasonal scales.

  3. Simulating Photosynthetic 13C Fractionation at a Western Subalpine Forest for Seasonal and Multi-Decadal Time Periods with the Community Land Model (CLM 4.5)

    NASA Astrophysics Data System (ADS)

    Raczka, B. M.; Duarte, H.; Koven, C. D.; Ricciuto, D. M.; Thornton, P. E.; Lin, J. C.; Bowling, D. R.

    2015-12-01

    Terrestrial biosphere models are an important tool to diagnose and predict land-atmosphere exchanges of carbon and energy. This is critical in order to quantify the land-carbon feedback into the climate system. Ecological observations are extremely important in order to quantify model skill and to improve techniques in which to simulate ecosystem behavior. Isotope observations of 13C are especially useful in diagnosing the ecosystem response to water stress, atmospheric humidity and CO2 fertilization. We test the representation of isotopes within CLM 4.5 against site level observations of biomass and carbon fluxes measured at Niwot Ridge, Colorado. First we 'spun-up' the model for 1800 years to approximate site level conditions during the 21st century. We accomplished this by imposing a site-level reconstruction of seasonally varying atmospheric δ13C and atmospheric CO2 from 1850-2013 and site level meteorological observations from 1998-2013. We also imposed an empirical-downscaling of simulated photosynthesis to reproduce the observed photosynthesis. We found that the simulated δ13C of biomass pools was more depleted than the observed by 1-2 o/oo. This finding suggests the magnitude of photosynthetic discrimination was overestimated in the model. The model reproduced observed seasonal trends in discrimination with higher values in the spring and fall but lower values in the summer. However, if nitrogen-limitation is imposed in the model the photosynthetic downscaling influences the fractionation in such a way to obscure this observed trend. This suggests an alternative approach should be taken in order to account for nitrogen limitation. During the last century the model simulated an abrupt drop in δ13C for biomass pools, primarily because of the concurrent drop in atmospheric δ13C, but also because of increasing discrimination driven by increases in the ratio of intercellular to atmospheric CO2. Finally, we identified photosynthetic rate, and vapor pressure

  4. A new seasonal-deciduous spring phenology submodel in the Community Land Model 4.5: impacts on carbon and water cycling under future climate scenarios.

    PubMed

    Chen, Min; Melaas, Eli K; Gray, Josh M; Friedl, Mark A; Richardson, Andrew D

    2016-11-01

    A spring 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 (CLM) 4.5. In head-to-head comparison (using satellite data from 2003 to 2013 for validation) for model grid cells over the Northern Hemisphere deciduous broadleaf forests (5.5 million km(2) ), we found that the revised model substantially outperformed the standard CLM seasonal-deciduous spring phenology submodel at both coarse (0.9 × 1.25°) and fine (1 km) scales. The revised model also does a better job of representing recent (decadal) phenological trends observed globally by MODIS, as well as long-term trends (1950-2014) in the PEP725 European phenology dataset. Moreover, forward model runs suggested a stronger advancement (up to 11 days) of spring leaf-out by the end of the 21st century for the revised model. Trends toward earlier advancement are predicted for deciduous forests across the whole Northern Hemisphere boreal and temperate deciduous forest region for the revised model, whereas the standard model predicts earlier leaf-out in colder regions, but later leaf-out in warmer regions, and no trend globally. The earlier spring leaf-out predicted by the revised model resulted in enhanced gross primary production (up to 0.6 Pg C yr(-1) ) and evapotranspiration (up to 24 mm yr(-1) ) when results were integrated across the study region. These results suggest that the standard seasonal-deciduous submodel in CLM should be reconsidered, otherwise substantial errors in predictions of key land-atmosphere interactions and feedbacks may result.

  5. NOAA/AVHRR vegetation indices and agriculture-meteorology processes

    NASA Astrophysics Data System (ADS)

    Gupta, Rajendra Kumar

    1992-07-01

    Enzymes controlled biochemical reactions in photosynthesis and respiration processes are affected by temperature making Growing Degree Days (GDDs) an important crop growth agromet parameter. NOAA/AVHRR Ratio Vegetation Index (RVI) and Normalized Difference Vegetation Index (NDVI) provide integrated aspect of non-linear crop-growth processes. This paper describes the inter-relationships between temporal profiles of air temperature GDDs and RVI/NDVI over Ludhiana district wherein the 94.9% of agriculture area has been under wheat. The Regression Coefficients (RC) for RVI have been lower than that for NDVI in case of mean air temperature GDDs and are significant at 99% confidence level. Similar relationship has been also observed for maximum air temperature GDDs except that regression with RVI is significant at 98% confidence level. Such relationship with minimum air temperature GDDs is significant at 99% confidence level once the regression is restricted to mid of Milking-Dough stage.

  6. Effects of temperature seasonality on tundra vegetation productivity using a daily vegetation dynamics model

    NASA Astrophysics Data System (ADS)

    Epstein, H. E.; Erler, A.; Frazier, J.; Bhatt, U. S.

    2011-12-01

    Changes in the seasonality of air temperature will elicit interacting effects on the dynamics of snow cover, nutrient availability, vegetation growth, and other ecosystem properties and processes in arctic tundra. Simulation models often do not have the fine temporal resolution necessary to develop theory and propose hypotheses for the effects of daily and weekly timescale changes on ecosystem dynamics. We therefore developed a daily version of an arctic tundra vegetation dynamics model (ArcVeg) to simulate how changes in the seasonality of air temperatures influences the dynamics of vegetation growth and carbon sequestration across regions of arctic tundra. High temporal-resolution air and soil temperature data collected from field sites across the five arctic tundra bioclimate subzones were used to develop a daily weather generator operable for sites throughout the arctic tundra. Empirical relationships between temperature and soil nitrogen were used to generate daily dynamics of soil nitrogen availability, which drive the daily uptake of nitrogen and growth among twelve tundra plant functional types. Seasonal dynamics of the remotely sensed normalized difference vegetation index (NDVI) and remotely sensed land surface temperature from the Advanced Very High Resolution Radiometer (AVHRR) GIMMS 3g dataset were used to investigate constraints on the start of the growing season, although there was no indication of any spatially consistent temperature or day-length controls on greening onset. Because of the exponential nature of the relationship between soil temperature and nitrogen mineralization, temperature changes during the peak of the growing season had greater effects on vegetation productivity than changes earlier in the growing season. However, early season changes in temperature had a greater effect on the relative productivities of different plant functional types, with potential influences on species composition.

  7. 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

  8. Environmental degradation analysis using NOAA/AVHRR data

    NASA Astrophysics Data System (ADS)

    Singh, D.; Meirelles, M. S. P.; Costa, G. A.; Herlin, I.; Berroir, J. P.; Silva, E. F.

    This paper proposes a particular approach to assess information about soil degradation, based on a methodology to calculate soil color from NOAA/AVHRR data. As erosive processes change physical and chemical properties of the soil, altering, consequently, the superficial color, monitoring the change in color over time can help to identify and analyze those processes. A relationship among the soil color (described in the Munsell Color System, i.e., in terms of Hue, Value and Chroma), vegetation indices, surface temperature and emissivity has been established, which is based on the theoretical model. The methodology has three main phases: determination of the regression models among soil color and vegetation indices, emissivity and surface temperature; generation of digital soil color models; and statistical evaluation of the estimated color. The tests showed that the methodology is efficient in determining soil color using the various vegetation indices (i.e., Normalized vegetation index NDVI, Modified soil adjusted vegetation index MSAVI). One vegetation index, i.e., Purified adjusted vegetation index (PAVI) is proposed to subsidies the effect of vegetation over the soil. Best results were obtained for the Hue color component. To further test the methodology, the estimated digital color models were compared with the characteristic color of soil classes in the test area. The results of this application confirmed the methodology’s capacity to determine the soil color from NOAA/AVHRR data. This type of study is quite helpful to know the erosion of soil as well as some abrupt change in soil due to natural hazards by space borne or air-borne sensors.

  9. [An operational remote sensing algorithm of land surface evapotranspiration based on NOAA PAL dataset].

    PubMed

    Hou, Ying-Yu; He, Yan-Bo; Wang, Jian-Lin; Tian, Guo-Liang

    2009-10-01

    Based on the time series 10-day composite NOAA Pathfinder AVHRR Land (PAL) dataset (8 km x 8 km), and by using land surface energy balance equation and "VI-Ts" (vegetation index-land surface temperature) method, a new algorithm of land surface evapotranspiration (ET) was constructed. This new algorithm did not need the support from meteorological observation data, and all of its parameters and variables were directly inversed or derived from remote sensing data. A widely accepted ET model of remote sensing, i. e., SEBS model, was chosen to validate the new algorithm. The validation test showed that both the ET and its seasonal variation trend estimated by SEBS model and our new algorithm accorded well, suggesting that the ET estimated from the new algorithm was reliable, being able to reflect the actual land surface ET. The new ET algorithm of remote sensing was practical and operational, which offered a new approach to study the spatiotemporal variation of ET in continental scale and global scale based on the long-term time series satellite remote sensing images.

  10. Aerosol optical depth over complex topography: comparison of AVHRR, MERIS and MODIS aerosol products

    NASA Astrophysics Data System (ADS)

    Riffler, Michael; Popp, Christoph; Hauser, Adrian; Wunderle, Stefan

    Aerosols are a key component in the Earth's atmosphere, influencing the radiation budget due to scattering and absorption of solar and terrestrial radiation and changing cloud physics by serving as cloud condensation nuclei. Furthermore, dispersed particles alter visibility and affect human health. Remote sensing techniques are a common means to monitor aerosol variability on large spatial scales. The accuracy of these retrievals is highest over surfaces with well known spectral properties and low reflectance (e.g. oceans). The retrieval over brighter and heterogeneous land surfaces is more demanding, since temporally unstable surface reflectance and a reduced aerosol signal may result in larger errors. Regions with highly complex topography, like the Alps, can exhibit even larger errors, basically due to directional effects caused by the topography, temporal snow coverage, and usually higher cloud amount. Ground validation of remote sensing aerosol products is generally performed using sun photometer measurements from the AErosol RObotic NETwork (AERONET). However, the lack of such sites in the central parts of the Alps renders validation difficult. To study the potential of aerosol remote sensing in regions with complex topography, namely in the Alps, we make use of an unusual situation on one of the major trans-alpine traffic routes in June 2006: A fatal rock fall caused the nearly one month closure of the Gotthard route in the Central Swiss Reuss Valley. Large parts of the traffic were redirected to the San Bernardino route (eastern Switzerland), which had a large impact on the local traffic amount, and thereby on air quality. Herein we compare the performance of three different sensors (AVHRR, MERIS, MODIS) in detecting this obvious change in the aerosol optical depth of the two alpine valleys in summer 2006. First results from AVHRR show a clear reduction (47%) of the aerosol optical depth along the Gotthard route compared to the five year monthly mean (2003

  11. 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

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. Vegetation classification based on Advanced Very High Resolution Radiometer /AVHRR/ satellite imagery

    NASA Technical Reports Server (NTRS)

    Norwine, J.; Greegor, D. H.

    1983-01-01

    Data from the NOAA-6 spacecraft Advanced Very High Resolution Radiometer (AVHRR) were tested for effectiveness for vegetation classification. Vegetation, climatological, and meteorological data were gathered for three days over 12 locations, and the normalized differences between the AVHRR bands 1 and 2 were determined. A vegetative greenness index was compared with a hydrologic factor and vegetation characteristics as measured by ground truth. A multivariate vegetation gradient model was formulated, incorporating AVHRR and climatological data. The hydrologic factor was calculated in terms of the precipitation, evaporation, maximum and minimum temperatures, and the hydrologic capacity. The observations were taken over Texas, which has a wide range of climates. A high correlation was found in the vegetation-HF index. The AVHRR data are concluded to be an effective tool for analysis of vegetation/climate relationships.

  17. 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.

  18. 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.

  19. 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.

  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

    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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. Seasonally different response of photosynthetic activity to daytime and night-time warming in the Northern Hemisphere

    DOE PAGES

    Tan, Jianguang; Piao, Shilong; Chen, Anping; ...

    2014-08-27

    Over the last century the Northern Hemisphere has experienced rapid climate warming, but this warming has not been evenly distributed seasonally, as well as diurnally. The implications of such seasonal and diurnal heterogeneous warming on regional and global vegetation photosynthetic activity, however, are still poorly understood. Here, we investigated for different seasons how photosynthetic activity of vegetation correlates with changes in seasonal daytime and night-time temperature across the Northern Hemisphere (>30°N), using Normalized Difference Vegetation Index (NDVI) data from 1982 to 2011 obtained from the Advanced Very High Resolution Radiometer (AVHRR). Our analysis revealed some striking seasonal differences in themore » response of NDVI to changes in day- versus night-time temperatures. For instance, while higher daytime temperature (Tmax) is generally associated with higher NDVI values across the boreal zone, the area exhibiting a statistically significant positive correlation between Tmax and NDVI is much larger in spring (41% of area in boreal zone – total area 12.6 × 106 km2) than in summer and autumn (14% and 9%, respectively). In contrast to the predominantly positive response of boreal ecosystems to changes in Tmax, increases in Tmax tended to negatively influence vegetation growth in temperate dry regions, particularly during summer. Changes in night-time temperature (Tmin) correlated negatively with autumnal NDVI in most of the Northern Hemisphere, but had a positive effect on spring and summer NDVI in most temperate regions (e.g., Central North America and Central Asia). Such divergent covariance between the photosynthetic activity of Northern Hemispheric vegetation and day- and night-time temperature changes among different seasons and climate zones suggests a changing dominance of ecophysiological processes across time and space. Lastly, understanding the seasonally different responses of vegetation photosynthetic activity to diurnal

  7. Aerosol retrievals from AVHRR radiances: effects of particle nonsphericity and absorption and an updated long-term global climatology of aerosol properties

    NASA Astrophysics Data System (ADS)

    Mishchenko, M.; Geogdzhaev, I.; Liu, L.; Orgen, A.; Lacis, A.; Rossow, W.; Hovenier, J.; Volten, H.; Muñoz, O.

    2003-09-01

    The paper describes and discusses long-term global retrievals of aerosol properties from channel-1 and -2 Advanced Very High Resolution Radiometer (AVHRR) radiances. We reconfirm the previously reached conclusion that the nonsphericity of dust-like and dry sea salt aerosols can lead to very large errors in the retrieved optical thickness if one mistakenly applies the scattering model for spherical particles. Comparisons of single-scattering albedo and Ångström exponent values retrieved from the AVHRR data and those measured in situ at Sable Island indicate that the currently adopted value 0.003 can be a reasonable choice for the imaginary part of the aerosol refractive index in the global satellite retrievals. Several unexpected features in the long-term satellite record indicate a serious problem with post-launch calibration of channel-2 radiances from the NOAA-11 spacecraft. We solve this problem by using a simple re-calibration procedure removing the observed artifacts and derive a global climatology of aerosol optical thickness and size over the oceans for the period extending from July 1983 to December 1999. The global monthly mean optical thickness and Ångström exponent of tropospheric aerosols show no significant trends over the entire period and oscillate around the average values 0.145 and 0.75, respectively. The Northern hemisphere means optical thickness systematically exceeds that averaged over the Southern hemisphere. The AVHRR retrieval results during the period affected by the Mt. Pinatubo eruption are consistent with the retrievals of the stratospheric aerosol optical thickness based on Stratospheric Aerosol and Gas Experiment (SAGE) data. Time series of the aerosol optical thickness and Ângström exponent derived for four separate geographic regions exhibit varying degrees of seasonal variability controlled by local meteorological events and/or anthropogenic activities.

  8. Improving the SNO calibration accuracy for the reflective solar bands of AVHRR and MODIS

    NASA Astrophysics Data System (ADS)

    Cao, Changyong; Wu, Xiangqian; Wu, Aisheng; Xiong, Xiaoxiong

    2007-09-01

    Analyses of a 4.5 year SNO (Simultaneous Nadir Overpass) time series between AVHRR on NOAA-16 and -17 suggest that the AVHRR observations based on operational vicarious calibration have become very consistent since mid 2004. This study also suggests that the SNO method has reached a high level of relative accuracy (~1.5%, 1 sigma) for both the 0.63 and 0.84 μm bands, which outperforms many other vicarious methods for satellite radiometer calibration. Meanwhile, for AVHRR and MODIS, a 3.5 year SNO time series suggests that the SNO method has achieved a 0.9% relative accuracy (1 sigma) for the 0.63 μm band, while the relative accuracy for the 0.84 um band is on the order of +/- 5% and significantly affected by the spectral response differences between AVHRR and MODIS. Although the AVHRR observations from NOAA-16 and -17 agree well, they significantly disagree with MODIS observations according to the SNO time series. A 9% difference was found for the 0.63 μm band (estimated uncertainty of 0.9%, 1 sigma), and the difference is even larger if the spectral response differences are taken into account. Similar bias for the 0.84 μm band is also found with a larger uncertainty due to major differences in the spectral response functions between MODIS and AVHRR. It is expected that further studies with Hyperion observations at the SNOs would help us estimate the biases and uncertainty due to spectral differences between AVHRR and MODIS. It is expected that in the near future, the calibration of the AVHRR type of instruments can be made consistent through rigorous cross-calibration using the SNO method. These efforts will contribute to the generation of fundamental climate data records (FCDRs) from the nearly 30 years of AVHRR data for a variety of geophysical products including aerosol, vegetation, and surface albedo, in support of global climate change detection studies.

  9. Climate variability and land cover change over the North American monsoon region (Invited)

    NASA Astrophysics Data System (ADS)

    Zeng, X.; Scheftic, W. D.; Broxton, P. D.

    2013-12-01

    The North American Monsoon System over Mexico and southwestern United States represents a weather/climate and ecosystem coupled "macrosystem". The weather and climate affect the seasonal and interannual variability of ecosystem, while the ecosystem change affects surface energy, water, and carbon fluxes that, in turn, affect weather and climate. Furthermore, long-term weather/climate data have a much coarser horizontal resolution than the satellite land cover data. Here the North American Regional Reanalysis (NARR) data at 32 km grid spacing will be combined with various satellite remote sensing products at 1 km and/or 8 km resolution from AVHRR, MODIS, and SPOT for the period of 1982 to present. Our analysis includes: a) precipitation, wind, and precipitable water data from NARR to characterize the North American monsoon; b) land cover type, normalized difference vegetation index (NDVI), green vegetation fraction, and leaf-area index (LAI) data to characterize the seasonal and interannual variability of ecosystem; c) assessing the consistency of various satellite products; and d) testing the coherence in the weather/climate and ecosystem variability.

  10. 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.

  11. Bridging the Gap Between AATSR and SLTR Observations Using AVHRR and IASI

    NASA Astrophysics Data System (ADS)

    Tsamalis, Christoforos; Saunders, Roger

    2015-12-01

    There is a need to find a candidate instrument that can bridge the gap between AATSR and SLSTR climate quality IR observations. Due to restrictions relating to the orbit of ENVISAT and Sentinel-3 only MODIS on TERRA and AVHRR on MetOp-A could potentially provide observations for a period that will overlap significantly with SLSTR. Here, the use of AVHRR is explored due to its collocation on the same platform with IASI, which is the reference instrument for calibration studies in the infrared spectrum. Previous studies have examined the calibration accuracy of the two longwave AVHRR channels using IASI, and so this study focuses mainly on the possible temporal trends, including the SWIR channel at 3.7?. There is a spatial correlation of the IASI-AVHRR differences with the water vapour geographical distribution, while the high noise of the shortwave IASI channels makes the comparison at low temperatures (i.e. at high latitudes) problematic. Temporal trends are found in the differences between IASI and AVHRR channels being less or equal to 10 mK/yr.

  12. 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

    During the first half of our second project year we have accomplished the following: (1) acquired a new AVHRR data set for the Beaufort Sea area spanning an entire year; (2) acquired additional ATSR data for the Arctic and Antarctic now totaling over seven months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; (6) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and SSM/I; and (7) continued work on compositing GAC data for coverage of the entire Arctic and Antarctic. During the second half of the year we will continue along these same lines, and will undertake a detailed validation study of the AVHRR and ATSR retrievals using LEADEX and the Beaufort Sea year-long data. Cloud masking methods used for the AVHRR will be modified for use with the ATSR. Methods of blending in situ and satellite-derived surface temperature data sets will be investigated.

  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. 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.

  15. 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).

  16. 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).

  17. Distributed land surface modeling with utilization of multi-sensor satellite data: application for the vast agricultural terrain in cold region

    NASA Astrophysics Data System (ADS)

    Muzylev, E.; Uspensky, A.; Gelfan, A.; Startseva, Z.; Volkova, E.; Kukharsky, A.; Romanov, P.; Alexandrovich, M.

    2012-04-01

    A technique for satellite-data-based modeling water and heat regimes of a large scale area has been developed and applied for the 227,300 km2 agricultural region in the European Russia. The core component of the technique is the physically based distributed Remote Sensing Based Land Surface Model (RSBLSM) intended for simulating transpiration by vegetation and evaporation from bare soil, vertical transfer of water and heat within soil and vegetation covers during a vegetation season as well as hydrothermal processes in soil and snow covers during a cold season, including snow accumulation and melt, dynamics of soil moisture and temperature during soil freezing and thawing, infiltration into frozen soil. Processes in the "atmosphere-snow-frozen soil" system are critical for cold region agriculture, as they control crop development in early spring before the vegetation season beginning. For assigning the model parameters as well as for preliminary calibrating and validating the model, available multi-year data sets of soil moisture/temperature profiles, evaporation, snow and soil freezing depth measured at the meteorological stations located within the study region have been utilized. To provide an appropriate parametrization of the model for the areas where ground-based measurements are unavailable, estimates have been utilized for vegetation, meteorological and snow characteristics derived from the multispectral measurements of AVHRR/NOAA (1999-2010), MODIS/EOS Terra & Aqua (2002-2010), AMSR-E/Aqua (2003-2004; 2008-2010), and SEVIRI/Meteosat-9 (2009-2010). The technologies of thematic processing the listed satellite data have been developed and applied to estimate the land surface and snow cover characteristics for the study area. The developed technologies of AVHRR data processing have been adapted to retrieve land surface temperature (LST) and emissivity (E), surface-air temperature at a level of vegetation cover (TA), normalized vegetation index (NDVI), leaf

  18. Semi-empirical approach to assess the evapotranspiration using nona/avhrr data

    NASA Astrophysics Data System (ADS)

    Singh, K.; Singh, D.; Herlin, I.; Berroir, J.; Bouzidi, S.; Lahoche, F.

    One of the most significant component of the hydrological budget is Evapotranspiration (ET), It is a Critical hydrological link between the earth surface and the atmosphere, It is therefore important for issues involving many aspects of climate, climate change, and ecosystem response because ET is the process responsible for the transfer of moisture from soil and vegetated surface to the atmosphere. Change in evapotranspiration is likely to have large impacts on terrestrial vegetation. Since the distribution and abundance of plant communities are controlled to a large extent by the quantity and seasonality of plant communities are controlled to a large extent by the quantity and seasonality of moisture. If the changes in water balance are significant, major shifts in vegetative patterns and condition are likely results of climate change, Equally, changes in evapotranspiration are likely to impact atmospheric composition of green house gases, and climate, as the hydrological cycle increases in intensity with warming, Assessment of ET is very tedious and cumbersome process for ground based observers or researchers. Therefore, in this paper, it is attempted to estimate the evapotranspiration using National Oceanic and Atmospheric Administration (NOAA)/ Advanced Very High Resolution Radiometer (AVHRR) data at coarse spatial resolution of 1.1 km. For this purpose, a semi-empirical model has been proposed to estimate the evapot ranspiration. ET can be computed as a gradient between air (T air) and soil (T surf) temperatures ET=X+Y (T surf -T air) (1) X, Y are empirical coefficients, T surf can be estimated from data given by satellite thermal channels, Ta ir can only be obtained with meteorological stations, Since aim of this paper is to compute ET from satellite imagery, therefore we propose a linear relation between, T=(T surf-T air ) and T surf T=A T surf+B (2) Where A and B are empiri cal constants computed using field measurements, Putting these values in equation

  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. 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.

  2. Calibrating historical IR sensors using GEO and AVHRR infrared tropical mean calibration models

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

    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 bias difference time series. Establishing the validity of this empirical model will allow for the calibration of historical AVHRR sensors to within 0.5 K, and

  3. 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

  4. Investigation of soil influences in AVHRR red and near-infrared vegetation index imagery

    NASA Technical Reports Server (NTRS)

    Huete, A. R.; Tucker, C. J.

    1991-01-01

    The effects of soil optical properties on vegetation index imagery are analyzed with ground-based spectral measurements and both simulated and actual AVHRR data from the NOAA satellites. Soil effects on vegetation indices were divided into primary variations associated with the brightness of bare soils, secondary variations attributed to 'color' differences among bare soils, and soil-vegetation spectral mixing. Primary variations were attributed to shifts in the soil line owing to atmosphere or soil composition. Secondary soil variance was responsible for the Saharan desert 'artefact' areas of increased vegetation index response in AVHRR imagery.

  5. 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

    ... modified on the permitted land if I graze adjacent trust or non-trust rangelands under an on-and-off grazing permit? 166.308 Section 166.308 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAND AND WATER GRAZING PERMITS Land and Operations Management § 166.308 Can the number of animals...

  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, 2010 CFR

    2010-04-01

    ... modified on the permitted land if I graze adjacent trust or non-trust rangelands under an on-and-off grazing permit? 166.308 Section 166.308 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAND AND WATER GRAZING PERMITS Land and Operations Management § 166.308 Can the number of animals...

  7. 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.

  8. 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

  9. 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

  10. 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

    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.

  11. 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

  12. 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

  13. 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.

  14. 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

    1995-01-01

    During the second phase project year we have made progress in the development and refinement of surface temperature retrieval algorithms and in product generation. More specifically, we have accomplished the following: (1) acquired a new advanced very high resolution radiometer (AVHRR) data set for the Beaufort Sea area spanning an entire year; (2) acquired additional along-track scanning radiometer(ATSR) data for the Arctic and Antarctic now totalling over eight months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) developed cloud masking procedures for both AVHRR and ATSR; (6) generated a two-week bi-polar global area coverage (GAC) set of composite images from which IST is being estimated; (7) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; and (8) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and special sensor microwave imager (SSM/I).

  15. Calibration results for NOAA-11 AVHRR channels 1 and 2 from congruent path aircraft observations

    NASA Technical Reports Server (NTRS)

    Abel, Peter; Guenther, B.; Galimore, Reginald N.; Cooper, John W.

    1993-01-01

    A method for using congruent atmospheric path aircraft-satellite observations to calibrate a satellite radiometer is presented. A calibrated spectroradiometer aboard a NASA ER-2 aircraft at an altitude of 19 km above White Sands (New Mexico) was oriented to view White Sands at the overpass time of the NOAA-11 AVHRR instrument along the same view vector as the satellite instrument. The data from six flights between November 1988 and October 1990 were transformed into corresponding estimates of AVHRR channel radiance at the satellite (derived from the aircraft measurements), and average counts (from the AVHRR measurements), both averaged across the footprint of the spectroradiometer. Prelaunch measurements of the AVHRR spectral response profiles are assumed, and the radiance spectrum measured by the spectroradiometer was adjusted to satellite altitude using the LOWTRAN-7 computer code. Results show reduced gains in both channel 1 (0.65 micron) and channel 2 (0.85 micron), compared to prelaunch values, with little further reduction in gain after 200 days in orbit. Results for the gain ratio (channel 1/channel 2), which is important for the calculation of the normalized vegetation index, show constant in-orbit values 5 percent above the prelaunch value.

  16. 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.

  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. 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...

  19. 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…

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. Changes in greening in the high Arctic: insights from a 30 year AVHRR max NDVI dataset for Svalbard

    NASA Astrophysics Data System (ADS)

    Vickers, Hannah; Arild Høgda, Kjell; Solbø, Stian; Rune Karlsen, Stein; Tømmervik, Hans; Aanes, Ronny; Hansen, Brage B.

    2016-10-01

    Satellite-aided studies of vegetation cover, biomass and productivity are becoming increasingly important for monitoring the effects of a changing climate on the biosphere. With their large spatial coverage and good temporal resolution, space-borne instruments are ideal to observe remote areas over extended time periods. However, long time series datasets with global coverage have in many cases too low spatial resolution for sparsely vegetated high latitude areas. This study has made use of a newly developed 30 year 1 km spatial resolution dataset from 1986 to 2015, provided by the NOAA AVHRR series of satellites, in order to calculate the annual maximum NDVI over parts of Svalbard (78°N). This parameter is indicative of vegetation productivity and has therefore enabled us to study long-term changes in greening within the Inner Fjord Zone on Svalbard. In addition, local meteorological data are available to link maximum NDVI values to the temporal behavior of the mean growing season (summer) temperature for the study area. Over the 30 year period, we find positive trends in both maximum NDVI (average increase of 29%) and mean summer temperature (59%), which were significantly positively correlated with each other. This suggests a temporal greening trend mediated by summer warming. However, as also recently reported for lower latitudes, the strength of the year-to-year correlation between maximum NDVI and mean summer temperature decreased, suggesting that the response of vegetation to summer warming has not remained the same over the entire study period.

  5. Analysis and Improvement of Geo-Referencing Accuracy in Long Term Global AVHRR Data

    NASA Astrophysics Data System (ADS)

    Khlopenkov, K.; Minnis, P.

    2011-12-01

    Precise geolocation is one of the fundamental requirements for generating high-quality Advanced Very High Resolution Radiometer (AVHRR) Satellite Climate Data Record (SCDR) at 1-km spatial resolution for climate applications. The Global Climate Observing System (GCOS) and Committee on Earth Observing Satellites (CEOS) identified the requirement for the accuracy of geolocation of satellite data for climate applications as 1/3 field-of-view (FOV). This requirement for AVHRR series on the National Oceanic and Atmospheric Administration (NOAA) platforms cannot be met without implementing the ground control point (GCP) correction, especially for historical data, because of the limited accuracy of orbit models and uncertainty in the satellite attitude angles. This work presents a new analysis of the geo-referencing accuracy of global AVHRR data, that uses an automated image matching at pre-selected GCP locations. As a reference image, we have been using the clear-sky monthly composite imagery derived from Moderate Resolution Imaging Spectroradiometer (MODIS) MOD09 dataset at 250-m resolution. The image matching technique is applicable to processing not only the daytime observations from optical solar bands, but also the nighttime imagery by using the long wave thermal channels. The method includes the ortho-rectification to correct for surface elevation and achieves the sub-pixel accuracy in both along-scan and along-track directions. The produced image displacement map is then used to derive a correction to satellite clock error and the attitude angles. The statistics and pattern of these corrections have been analyzed for different NOAA Polar-orbiting satellites by using the HRPT, LAC, and GAC data sets. The application of the developed processing system showed that the algorithm achieved better than 1/3 FOV geolocation accuracy for most of AVHRR 1-km scenes. It has a high efficiency rate (over 97%) for global AVHRR data from NOAA-6 through NOAA-19.

  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. 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.

  8. 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.)

  9. 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.

  10. 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.

  11. Gondwanaland's seasonal cycle

    NASA Technical Reports Server (NTRS)

    Crowley, Thomas J.; Short, David A.; Mengel, John G.

    1987-01-01

    A two-dimensional energy balance climate model has been used to simulate the seasonal temperature cycle on a supercontinent-sized land mass. Experiments with idealized and realistic geography indicate that the land-sea configuration in high latitudes exerts a strong influence on the magnitude of summer warming. These simulations provide significant insight into the evolution of climate during the Palaeozoic, and raise questions about the presumed pre-eminent role of carbon dioxide in explaining long-term climate change.

  12. 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.

  13. Seasonal and nocturnal domiciliary human landing/biting behaviour of Lutzomyia (Lutzomyia) evansi and Lutzomyia (Psychodopygus) panamensis (Diptera; Psychodidae) in a periurban area of a city on the Caribbean coast of eastern Venezuela (Barcelona; Anzoátegui State).

    PubMed

    González, R; De Sousa, L; Devera, R; Jorquera, A; Ledezma, E

    1999-01-01

    In recent years, in addition to American cutaneous leishmaniasis (ACL), a significant number of cases of American visceral leishmaniasis (AVL) have been reported in periurban areas of Barcelona city (Anzoátegui State, Venezuela). We studied the bionomics of Lutzomyia (Lutzomyia) evansi and Lutzomyia (Psychodopygus) panamensis, possible vectors of AVL and ACL, respectively, in El Rincón, a periurban village of that city. To evaluate the seasonal domiciliary landing/biting activity of sandflies on human bait, a house was chosen in El Rincón. Landing catches were carried out between 18:00 and 06:00, once a month for a year. The results show the presence of 2 species, Lu. (Lu.) evansi (89.9%) and Lu. (Psy.) panamensis (10.1%). Lu. evansi was most abundant in the months of October and July, associated with the bimodal cycle of annual rainfall in the area. Maximum landing/biting activity of Lu. evansi was observed at 24:00 and 03:00. These findings suggest that at this time of the year and at these hours there is heightened risk of the transmission of AVL. Lu. panamensis monthly abundance also shows a direct association with rainfall and maximum landing/biting activity was observed between 02:00 and 03:00. The lower domiciliary abundance of Lu. panamensis suggests its greater importance in the extradomiciliary transmission of ACL.

  14. 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

  15. AVHRR, MODIS and Landsat Time Series for the Monitoring of Vegetation Changes Around the World (Invited)

    NASA Astrophysics Data System (ADS)

    de Beurs, K.; Owsley, B.; Julian, J.; Henebry, G. M.

    2013-12-01

    A confluence of computing power, cost of storage, ease of access to data, and ease of product delivery make it possible to harness the power of multiple remote sensing data streams to monitor land surface dynamics. Change detection has always been a fundamental remote sensing task, and there are myriad ways to perceive differences. From a statistical viewpoint, image time series of the vegetated land surface are complicated data to analyze. The time series are often seasonal and have high temporal autocorrelation. These characteristics result in the failure of the data to meet the assumption of most standard parametric statistical tests. Failure of statistical assumptions is not trivial and the use of inappropriate statistical methods may lead to the detection of spurious trends, while any actual trends and/or step changes might be overlooked. While the analysis of messy data, which can be influenced by discontinuity, missing observation, non-linearity and seasonality, is still developing within the remote sensing community, other scientific research areas routinely encounter similar problems and have developed statistically appropriate ways to deal with them. In this talk we describe the process of change analysis as a sequence of tasks: (1) detection of changes; (2) quantification of changes; (3) assessment of changes; (4) attribution of changes; and (5) projection of the potential consequences of changes. To detect, quantify, and assess the significance of broad scale land surface changes, we will first apply the nonparametric Seasonal Kendall (SK) trend test corrected for first-order temporal autocorrelation to MODIS image time series. We will then discuss three case studies, situated in the USA, Russia, and New Zealand in which we combine or fuse satellite data at two spatial resolutions (30m Landsat and 500m MODIS) to assess and attribute changes at fine spatial and temporal scales. In the USA we will investigate changes as a result of urban development, in

  16. Changes In Growing Season Determined From Alaska GLOBE Data And NDVI

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

    The GLOBE program is an international partnership network of K-12 students, teachers, and scientists working together to study and understand the global environment. Through its suite of data collection and extensive network, GLOBE provides a valuable resource for studying the impact of climate change on the environment. Students make observations and measurements on the soils, hydrology, land cover, climate and phenology at or near their schools and report their data through the Internet to the GLOBE data archive. Since 1999, GLOBE students have monitored plant phenology at their schools and have reported annual dates for bud burst, green-up, leaf growth, and green-down for selected trees, shrubs, and grasses. GLOBE students have made over 54,000 phenology measurements with nearly half that data collected by GLOBE students in Alaska. This study reviews the Alaska phenology measurements to discern long-term changes from interannual variations in plant growing season length. Satellite derived vegetation indices from MODIS and AVHRR are also used in this study.

  17. 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.; 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.

  18. 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.

  19. 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.

  20. 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.

  1. Scan Angle Dependence Of Radiance Recorded By The NOAA-AVHRR

    NASA Astrophysics Data System (ADS)

    Duggin, M. J.; Piwinski, D.; Whitehead, V.; Ryland, G.

    1983-08-01

    NOAA-AVHRR data is being used to monitor global vegetation type and condition and to study various environmental factors in addition to performance of meteorological functions. The AVHRR instrument has +/-54° as a maximum scan angle limits and it is necessary to be aware of the effects of sun-target-sensor geometry at extreme scan angles to be able to properly interpret the satellite images. In order to interpret the images for vegetation type and condition analysis it is necessary to calibrate back to the nadir view position. Both simulation studies and empirical investigations with digital scanner data have been performed in order to sufficiently understand the effects of scan angle and sun angle, as well as the effects of atmospheric scattering, to eventually perform adequate calibrations. Not suprisingly, the effects are large and studies are continuing to provide improved calibrations. It is the results of these investigations which we describe in this paper.

  2. Engima of a thermal anomaly - A TM/AVHRR study of the volcanic Arabian highlands

    NASA Technical Reports Server (NTRS)

    Blodget, H. W.; Andre, C. G.; Masuoka, P. M.

    1987-01-01

    Discovery of a large thermal anomaly in the western Arabian highlands on Landsat TM imagery is reported. The anomaly, 15 C warmer than surroundings, forms a 2-km-wide arc around the southern flank of Jebel Chada, a volcano active in 1256 AD. It is recorded by AVHRR imagery as well, despite the 1.1-km spatial resolution of this sensor. Air photos and geologic maps show no bedrock unit that corresponds to the anomaly. Digital techniques were applied to the TM and AVHRR data, including contrast enhancement, density slicing, principal components analysis, and construction of multiband composite images. It is concluded that the anomaly results from a thin cover of volcanic ash or cinder that is optically indistinguishable from underlying basalt, rather than from internal (volcanic or hydrologic) heat sources.

  3. 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).

  4. 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.

  5. 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.

  6. Modification of growing-season surface temperature records in the northern great plains due to land-use transformation: verification of modelling results and implication for global climate change

    NASA Astrophysics Data System (ADS)

    Mahmood, Rezaul; Hubbard, Kenneth G.; Carlson, Christy

    2004-03-01

    Land-use and land-cover change can modify near-surface atmospheric condition. Mesoscale modelling studies have shown that modification in land use affects near-surface soil moisture storage and energy balance. Such a study in the Great Plains showed that changes in land use from natural grass to irrigated agriculture enhanced soil water storage in the root zone and increased latent energy flux. This increase in latent energy flux would correspond to a decrease in sensible heat flux and, therefore, modify near-surface temperature records. To verify this deduction, we have investigated the changes in the historical near-surface temperature records in Nebraska, USA. We have analysed the long-term mean monthly maximum, minimum, and monthly mean air temperature data from five irrigated and five non-irrigated sites. The cooperative weather observation (coop) network is the source of the data. We have found that there is a clear trend in decreasing mean maximum and average temperature data for irrigated sites. For example, York, NE, reports that the mean maximum growing season temperature is decreasing at the rate -0.01°C year-1. The results from non-irrigated sites indicated an increasing trend for the same parameters. The data from Halsey, NE, indicate a +0.01°C year-1 increase in this century. In addition, we have conducted similar analyses of temperature data for the National Climatic Data Center's Historical Climatic Network data set for the same locations. The results are similar to that obtained with the coop data set. Further investigation of dew-point temperature records for irrigated and non-irrigated sites also show an increasing and decreasing trend respectively. Therefore, we conclude that the land-use change in the Great Plains has modified near-surface temperature records.

  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. 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.

  10. 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.

  11. Soil dehydrogenase in a land degradation-rehabilitation gradient: observations from a savanna site with a wet/dry seasonal cycle.

    PubMed

    Doi, Ryoichi; Ranamukhaarachchi, Senaratne Leelananda

    2009-01-01

    Soil dehydrogenase activity is a good indicator of overall microbial activity in soil, and it can serve as a good indicator of soil condition. However, seasonal changes in soil moisture content may have an effect on soil dehydrogenase activity, making an accurate assessment of soil condition difficult. In this study, we attempted to determine the significance of soil dehydrogenase activity for assessing soil condition, and we attempted to find a way to account for the influence of soil moisture content on soil dehydrogenase activity.' Soils were sampled in dry evergreen forest (original vegetation), bare ground (severely degraded) and Acacia plantation plots established on bare ground in 1986 and 1987 in Sakaerat, Thailand. Soil physico-chemical characteristics and dehydrogenase activity in the Acacia plantation soil had few differences from those in the evergreen forest soil. Soil dehydrogenase activity varied significantly between the bare ground and the forests regardless of the season (wet or dry), while the season did not produce a significant variation in soil dehydrogenase activity, as determined by repeated measures analysis of variance (p=0.077). The physico-chemical data provided the first principal component as a good measure of soil fertility. Values of soil dehydrogenase activity significantly correlated to scores of the soil samples of the first principal component (R=0.787, p<0.001). We found that soil dehydrogenase activity is a useful indicator of the extent of soil degradation and the rehabilitative effects of reforestation in this part of Thailand.

  12. 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

  13. A Consistent AVHRR Visible Calibration Record Based on Multiple Methods Applicable for the NOAA Degrading Orbits. Part 2 ; Validation

    NASA Technical Reports Server (NTRS)

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

    2016-01-01

    Consistent cross-sensor Advanced Very High Resolution Radiometer (AVHRR) calibration coefficients are determined using desert, polar ice, and deep convective cloud (DCC) invariant Earth targets. The greatest AVHRR calibration challenge is the slow orbit degradation of the host satellite, which precesses toward a terminator orbit. This issue is solved by characterizing the invariant targets with NOAA-16 AVHRR observed radiances that have been referenced to the Aqua Moderate Resolution Imaging Spectrometer (MODIS) calibration using simultaneous nadir overpass (SNO) observations. Another benefit of the NOAA-16 invariant target-modeled reflectance method is that, because of the similarities among the AVHRR spectral response functions, a smaller spectral band adjustment factor is required than when establishing calibrations relative to a non-AVHRR reference instrument. The sensor- and band-specific calibration uncertainties, with respect to the calibration reference, are, on average, 2 percent and 3 percent for channels 1 and 2, respectively. The uncertainties are smaller for sensors that are in afternoon orbits, have longer records, and spend less time in terminator conditions. The multiple invariant targets referenced to Aqua MODIS (MITRAM) AVHRR calibration coefficients are evaluated for individual target consistency, compared against Aqua MODIS/AVHRR SNOs, and selected published calibration gains. The MITRAM and SNO relative calibration biases mostly agree to within 1 percent for channels 1 and 2, respectively. The individual invariant target and MITRAM sensor relative calibration biases are mostly consistent to within 1 percent and 2 percent for channels 1 and 2, respectively. The differences between the MITRAM and other published calibrations are mostly attributed to the reference instrument calibration differences.

  14. 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.

  15. Development of a land-cover characteristics database for the conterminous U.S.

    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

  16. 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

  17. SYNOPTIC GLOBAL REMOTE SENSING OF LAND SURFACE VEGETATION: OVERVIEW OF DAILY DATA QUALITY, CHALLENGES, AND OPPORTUNITIES

    NASA Astrophysics Data System (ADS)

    Barreto-Munoz, A.; Didan, K.

    2009-12-01

    Continuous acquisition of global satellite imagery over the years has contributed to the creation of a long data record from AVHRR, MODIS, TM, SPOT VGT, and other sensors. These records account now for 30+ years, and as the archive grows, it becomes an invaluable source of data for many environmental related studies dealing with trends and changes from local to global scale. Synoptic global remote sensing provides a multitude of land surface state variables and serves as a major foundation for global change research. However, these records are inhibited with problems that need to be accounted for in order to understand the limits and improve the science results derived from these records. The presence of clouds, aerosols, spatial gaps, variable viewing geometry, inconsistent atmosphere corrections, multiple reprocessing, and different sensors characteristics, makes it difficult to obtain frequently high quality data everywhere and every time. Moreover, these issues are location and season dependent making it even more difficult to construct the consistent time series required to study change over time. To evaluate these records, we analyzed 30+ years (1981 to 1999 and 2000 to 2009) of daily global land surface measurements (CMG resolution) from AVHRR (N07, N09, N11 and N14) and MODIS (AQUA and TERRA, Collection 5, C5). We stratified the data based on land cover, latitudinal zone, and season and we examined the daily data quality, including cloud persistence, aerosol loads, data gaps, and an index of reliability that measures how likely an observation is acceptable for research. The aim was to generate aggregate maps of cloud distribution, aerosol levels distribution, and data reliability distribution in both time and space. This information was then converted into an uncertainty measure at the pixel level that indicates how suspect or significant a result could potentially be, depending on its location and season and consequently what geographic locations and times

  18. Considering Seasons.

    ERIC Educational Resources Information Center

    Gonzalez-Mena, Janet

    1994-01-01

    Argues that the traditional way that the four seasons are taught is culturally biased and does not reflect the actual seasons in many parts of the United States and other nations. Suggests that early childhood programs should take into account the diversity of seasonal transitions. (MDM)

  19. 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.

  20. Utilizing satellite-derived estimates of land surface temperature and vegetation characteristics in modeling the vertical water and heat fluxes for a river basin

    NASA Astrophysics Data System (ADS)

    Muzylev, E. L.; Uspensky, A. B.; Startseva, Z. P.; Volkova, E. V.; Kukharsky, A. V.

    2009-04-01

    New version of the model of vertical water and heat transfer in the "soil-vegetation-atmosphere" system (SVAT) has been developed, accounting for land surface heterogeneities in river basin. The model is specially designed to assimilate satellite data and is intended for calculation of evapotranspiration Ev, soil water content W, sensible and latent heat fluxes and other water and heat balance components as well as vertical soil moisture and temperature profiles and vegetation cover and soil surface temperatures for any time interval within vegetation season. The river basin landscape patchiness is represented in the model with soil constants, leaf area index LAI, vegetation cover fraction B, land surface albedo A, and other vegetation characteristics that were treated as model parameters. The Seim River basin was chosen for investigation, situated in forest-steppe zone of the Central Russia (Kursk region) with watershed area equal to 7460 km2. Satellite-derived estimates of land surface characteristics have been extracted from AVHRR/NOAA (1999-2006 vegetation seasons) and MODIS/EOS Terra and Aqua (2003-2005 vegetation seasons) cloud-free data. The developed technique of AVHRR data processing provides the cloud detection and the retrieval of soil temperature Тsg and emissivity E, surface-air temperature at a level of vegetation cover Ta, effective radiative temperature Ts.eff (weighted linear combination of Ta and Tsg), as well as the derivation of normalized vegetation index NDVI, LAI and B. The updated multi-threshold technique of cloud detection in the AVHRR field of view has been applied to increase the reliability of cloud-free fragments selection. The algorithms of Ta, Ts.eff, Tg derivation utilize linear regression estimators similar to well-known "local" split window technique. The values of E for these regression formulas have been specified using empirical relationships between E and B, E and NDVI as well as the emissivity models for various surface

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. Intraannual and interannual chlorophyll variability in the Arabien Sea and Bay of Bengal as observed from SeaWiFS data: and its interrelationship with Sea Surface Temperature (SST) derived from NOAA/AVHRR

    NASA Astrophysics Data System (ADS)

    Chaturvedi, N.

    Ocean colour is a key parameter for understanding oceanic, biological and physical processes. The satellite acquired ocean colour data constitute a powerful tool for determining the abundance of ocean biota on a global scale. It is well known that the biological processes in the ocean are largely controlled by the presence of phytoplankton, which forms the base of food chain, and is responsible for CO2 fixation acting as sink for CO2. Besides the phytoplankton itself, affects the ocean surface heating and light penetration. Significant large-scale oceanic and atmospheric differences may sufficiently alter the circulation patterns and thermal structure of the region to produce variability in phytoplankton biomass. This is very well observed on satellite images. The penetrative power of solar radiation is a function of the water clarity and may vary at different locations. In the tropics there is sufficient light and heat throughout the year, so that there are continual small rises and falls of population as zooplankton and phytoplankton populations and nutrient levels interact. There are also changes from year to year in plankton population. These can be linked to changes in the climate, through winter mixing variability, temperature and light availability. There may also be changes in the supply of nutrients from land run off.. The variation in the wavelength characteristics of reflected light from the oceans due to changes in biological productivity will also have a climatic influence. Regions of greater productivity would reflect more incident radiation and/also allow less of it to warm the lower reaches of the upper ocean. A contrasting effect of phytoplankton is the warming of the upper ocean by the increased absorption of radiation as biomass increases, is as well reported. At present, the understanding of the time and space variability of most biological properties is quite inadequate. Seasonality is one of the basic mode of variability and that is detectable

  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. 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.

  8. 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.

  9. Correlation of AVHRR Imagery with Sub-Surface Features in California Current

    DTIC Science & Technology

    1989-06-01

    correlation coefficient between AVHRR SST and in-situ temperature at depth for all three phases of the cruise which is attributed to the temporal offset between the satellite image and the data collection. The results of the 1988 cruise show maximum correlations at the surface with significant correlations at the 95% level of confidence to about 130-150 m depth, with positive correlations to 310-350 m depth. Comparing the results of the 1987 and 1988 cruises shows that the offshore filament was much stronger both horizontally and vertically for the latter cruise. Keywords:

  10. Seasonally different response of photosynthetic activity to daytime and night-time warming in the Northern Hemisphere

    SciTech Connect

    Tan, Jianguang; Piao, Shilong; Chen, Anping; Zeng, Zhenzhong; Ciais, Philippe; Janssens, Ivan A.; Mao, Jiafu; Myneni, Ranga B.; Peng, Shushi; Peñuelas, Josep; Shi, Xiaoying; Vicca, Sara

    2014-08-27

    Over the last century the Northern Hemisphere has experienced rapid climate warming, but this warming has not been evenly distributed seasonally, as well as diurnally. The implications of such seasonal and diurnal heterogeneous warming on regional and global vegetation photosynthetic activity, however, are still poorly understood. Here, we investigated for different seasons how photosynthetic activity of vegetation correlates with changes in seasonal daytime and night-time temperature across the Northern Hemisphere (>30°N), using Normalized Difference Vegetation Index (NDVI) data from 1982 to 2011 obtained from the Advanced Very High Resolution Radiometer (AVHRR). Our analysis revealed some striking seasonal differences in the response of NDVI to changes in day- versus night-time temperatures. For instance, while higher daytime temperature (Tmax) is generally associated with higher NDVI values across the boreal zone, the area exhibiting a statistically significant positive correlation between Tmax and NDVI is much larger in spring (41% of area in boreal zone – total area 12.6 × 106 km2) than in summer and autumn (14% and 9%, respectively). In contrast to the predominantly positive response of boreal ecosystems to changes in Tmax, increases in Tmax tended to negatively influence vegetation growth in temperate dry regions, particularly during summer. Changes in night-time temperature (Tmin) correlated negatively with autumnal NDVI in most of the Northern Hemisphere, but had a positive effect on spring and summer NDVI in most temperate regions (e.g., Central North America and Central Asia). Such divergent covariance between the photosynthetic activity of Northern Hemispheric vegetation and day- and night-time temperature changes among different seasons and climate zones suggests a changing dominance of ecophysiological processes across time and space. Lastly, understanding the seasonally

  11. Report on the usefulness of AVHRR and CZCS sensors for delineating potential disposal operations at the 106-mile site

    SciTech Connect

    Cornillon, P.

    1987-03-01

    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 following the day of the dump. All spectral channels were analyzed. In addition, the difference and the ratio of channels 1 and 2 were used. No dumping is evident in any of the images. If dumping is actually visible, the signal must be very weak at the 1-km resolution of the AVHRR sensor. Because of this, the images would have to be absolutely clear. Small scattered clouds or thick haze add too much variability to detect a weak signal. This renders AVHRR data of marginal value (if of value at all) for such work. Because the exact location of the dumps was not known, it is possible that the signal is detectable.

  12. 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

  13. 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.

  14. Relations of Water Quality to Streamflow, Season, and Land Use for Four Tributaries to the Toms River, Ocean County, New Jersey, 1994-99

    USGS Publications Warehouse

    Baker, Ronald J.; Hunchak-Kariouk, Kathryn

    2006-01-01

    The effects of nonpoint-source contamination on the water quality of four tributaries to the Toms River in Ocean County, New Jersey, have been investigated in a 5-year study by the U.S. Geological Survey (USGS), in cooperation with the New Jersey Department of Environmental Protection (NJDEP). The purpose of the study was to relate the extent of land development to loads of nutrients and other contaminants to these streams, and ultimately to Barnegat Bay. Volumetric streamflow (discharge) was measured at 6 monitoring sites during 37 stormflow and base-flow sampling events over a 5-year period (May 1994-September 1999). Concentrations and yields (area-normalized instantaneous load values) of nitrogen and phosphorus species, total suspended solids, and fecal coliform bacteria were quantified, and pH, dissolved oxygen, and stream stage were monitored during base-flow conditions and storms. Sufficient data were collected to allow for a statistical evaluation of differences in water quality among streams in subbasins with high, medium, and low levels of land development. Long Swamp Creek, in a highly developed subbasin (64.2 percent developed); Wrangle Brook, in a moderately developed subbasin (34.5 percent); Davenport Branch, in a slightly developed subbasin (22.8 percent); and Jakes Branch, in an undeveloped subbasin (0 percent) are the subbasins selected for this study. No point-source discharges are known to be present on these streams. Water samples were collected and analyzed by the NJDEP, and discharge measurements and data analysis were conducted by the USGS. Total nitrogen concentrations were lower in Davenport Branch than in Long Swamp Creek and Wrangle Brook during base flow and stormflow. Concentrations of total nitrogen and nitrate were highest in Wrangle Brook (as high as 3.0 mg/L and 1.6 mg/L, respectively) as a result of high concentrations of nitrate in samples collected during base flow; nitrate loading from ground-water discharge is much higher in

  15. 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…

  16. 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.

  17. Mean and inter-year variation of growing-season normalized difference vegetation index for the Sahel 1981-1989

    NASA Technical Reports Server (NTRS)

    Tucker, C. J.; Newcomb, W. W.; Los, S. O.; Prince, S. D.

    1991-01-01

    Images are presented that show the mean and coefficient of variation of nine years (1981-1989) of NOAA AVHRR normalized difference vegetation index (NDVI) data for the growing season (July-October) in Africa, north of the equator. The variation in the growing season NDVI is represented by the coefficient of variation image that shows the large variation in the Sahelian growing season between years. It is concluded that these images illustrate some aspects of the perspective being brought to regional and continental scale processes by coarse resolution satellite sensors and the potential of these sensors to provide consistent, long-term datasets.

  18. A 16-year time series of 1 km AVHRR satellite data of the conterminous United States and Alaska

    USGS Publications Warehouse

    Eidenshink, Jeff

    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.

  19. 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.

  20. Surface Temperature Trends in the Arctic and the Antarctic from AVHRR and In Situ Data

    NASA Astrophysics Data System (ADS)

    Perez, G. J. P.; Comiso, J. C.

    2015-12-01

    The earliest signals of a climate change are expected to be observed in the polar regions in part because of the high reflectively of snow and ice. Because of general inaccessibility, there is a paucity of in situ data and hence the need to use satellite data to observe the large-scale variability and trends in surface temperature in the two regions. The sensor with the longest satellite record on temperature has been the NOAA/Advanced Very High Resolution Radiometer (AVHRR) that has provided continuous thermal infrared data for more than 33 years. The results of analysis of the data show that there is indeed a strong signal coming from the Arctic with the trend in surface temperature (for the region > 64°N) being 0.6°C per decade which is about 3 times the global trend of 0.2°C per decade for the same period. It appeared surprising when the results from a similar region (> 64 °S) in the Antarctic show a much lower trend and comparable to the global trend. The primary source of error in the temperature data is cloud masking associated with the similar signatures of clouds and snow/ice covered surfaces. However, the derived AVHRR data show good consistency with in situ data with standard deviation less than 1°C. The AVHRR time series has also been compared and showed compatibility with data from the Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) which have been available from 2000 to the present. Some differences in the trends from the two hemispheres are expected because of very different geographical environments in the two regions. The relationships of the trend with the atmospheric global circulation in the north, as defined by the Northern Annular Mode (NAM), and that in the south, as defined by the Southern Annular Mode (SAM), have been observed to be generally weak. The occurrences of the Antarctic Circumpolar Wave (ACW) and ENSO were also studied and not considered a significant factor. It is intriguing that the observed variability in

  1. 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.

  2. Operational use of NOAA-AVHRR imagery in the marine environment

    NASA Astrophysics Data System (ADS)

    Roozekrans, Hans

    1994-12-01

    Since early 1990 KNMI has been running an operational system to produce and distribute image-products, based on in real time received and processed NOAA-AVHRR-data. Maps of sea surface temperature and total suspended matter concentrations of the North Sea and IJsselmeer are produced with a regular frequency (minimal once a week). If necessary daily maps are produced, indicating locations of blooms of Coccolithophore algae in the North Sea, of drifting layers of Blue Algae and/or ice-cover on the water-surface of the IJsselmeer. Digital image-files on floppy-disk and color-coded hardcopies of the maps are available for the user. During the last years KNMI, in co-operation with other institutes, has put a lot of effort into the stimulation of operational use of the NOAA image-products in the marine environment.

  3. 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.

  4. AVHRR Infrared brightness temperatures at the cloud tops of sea breeze fronts over the Iberian Mediterranean area and the isle of Mallorca (Spain)

    NASA Astrophysics Data System (ADS)

    Azorin-Molina, C.; Estrela-Navarro, M. J.; Connell, B.; Baena-Calatrava, R.

    2009-09-01

    The main objective of this remote sensing study is to investigate infrared (IR) brightness temperatures at the cloud tops of sea breeze fronts over the Iberian Mediterranean area and the isle of Mallorca, both in Spain. Advanced Very High Resolution Radiometer (AVHRR - HRPT) data from National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites is collected May through October 2004. We use a new daytime over land cloud detection scheme (Azorin et al., 2007) to derive cloud masks from NOAA-17 and NOAA-16 overpasses. In this study, we analyze the frequency of cloud tops that are colder than different IR threshold temperatures in order to represent areas that experience deep convection associated by sea breezes. Here we present cloud frequency composites for different IR thresholds and prevailing large-scale situations which aid in highlighting the location of hotspots. Preliminary results indicate that cloud tops associated with sea breeze convection are normally warmer than 235K, a threshold which is used in the literature for indicating deep convection. We also use surface synoptic observations with the aim to study if sea breeze storms with IR brightness temperatures >235K at 11.0 and 12.0 µm is related to severe thunderstorms (e.g. impact of hail storms on the agriculture economy). Previous studies have concluded that severe and moderate thunderstorms events can occur under sea breeze situations, even though weather reports forecast mostly clear skies. Results from this remote sensing study could have applications for short-term forecasts.

  5. 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.

  6. Long-Term High-Latitude Sea and Ice Surface Temperature Record from AVHRR GAC Data

    NASA Astrophysics Data System (ADS)

    Luis, C. S.; Dybkjær, G.; Eastwood, S.; Tonboe, R. T.; Høyer, J. L.

    2014-12-01

    Surface temperature is among the most important variables in the surface energy balance equation and it significantly affects the atmospheric boundary layer structure, the turbulent heat exchange and, over ice, the ice growth rate. Here we measure the surface temperature using thermal infrared sensors from 10-12 μm wavelength, a method whose primary limitation over sea ice is the detection of clouds. However, in the Arctic and around Antarctica there are very few conventional observations of surface temperature from buoys, and it is sometimes difficult to determine if the temperature is measured at the surface or within the snowpack, the latter of which often results in a warm bias. To reduce this bias, much interest is being paid to alternative remote sensing methods for monitoring high latitude surface temperature. We used Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) data to produce a high latitude sea surface temperature (SST), ice surface temperature (IST) and ice cap skin temperature dataset spanning 27 years (1982-2009). This long-term climate record is the first of its kind for IST. In this project we used brightness temperatures from the infrared channels of AVHRR sensors aboard NOAA and Metop polar-orbiting satellites. Surface temperatures were calculated using separate split window algorithms for day SST, night SST, and IST. The snow surface emissivity across all angles of the swath were simulated specifically for all sensors using an emission model. Additionally, all algorithms were tuned to the Arctic using simulated brightness temperatures from a radiative transfer model with atmospheric profiles and skin temperatures from European Centre for Medium-Range Forecasts (ECMWF) re-analysis data (ERA-Interim). Here we present the results of product quality as compared to in situ measurements from buoys and infrared radiometers, as well as a preliminary analysis of climate trends revealed by the record.

  7. IGBP-DIS global 1 km land cover data set, DISCover: First results

    USGS Publications Warehouse

    Loveland, T.R.; Belward, A.S.

    1997-01-01

    The International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) is co-ordinating the development of global land data sets from Advanced Very High Resolution Radiometer (AVHRR) data. The first is a 1 km spatial resolution land cover product `DISCover', based on monthly Normalized Difference Vegetation Index composites from 1992 and 1993. DISCover is a 17 class land cover dataset based on the science requirements of IGBP elements. Mapping uses unsupervised classification with post-classification refinement using ancillary data. Draft Africa, North America and South America products are now available for peer review.

  8. 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.

  9. 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.

  10. Observations of winter polynyas and fractures using NOAA AVHRR TIR images and Nimbus-7 SMMR sea ice concentration charts

    NASA Technical Reports Server (NTRS)

    Dey, B.; Feldman, Uri

    1989-01-01

    The validity of the daily sea ice concentration charts obtained from Nimbus-7 SMMR data is tested against thermal IR NOAA AVHRR-4 images with a 1.1 x 1.1 km resolution. Polynyas and fractures recorded in both data sets are compared for the same times over the same areas. Although the coarser resolution of SMMR data leads to a loss of detail, it is found that the ice concentration charts provide valuable data on openings in the ice. The SMMR data on the location, orientation, and size of polynyas and fractures are shown to be in good agreement with the AVHRR data. Also, the results suggest that the location and orientation of plynyas and fractures are related to the direction of surface winds.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. 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…

  18. The correlated k-distribution technique as applied to the AVHRR channels

    NASA Technical Reports Server (NTRS)

    Kratz, David P.

    1995-01-01

    Correlated k-distributions have been created to account for the molecular absorption found in the spectral ranges of the five Advanced Very High Resolution Radiometer (AVHRR) satellite channels. The production of the k-distributions was based upon an exponential-sum fitting of transmissions (ESFT) technique which was applied to reference line-by-line absorptance calculations. To account for the overlap of spectral features from different molecular species, the present routines made use of the multiplication transmissivity property which allows for considerable flexibility, especially when altering relative mixing ratios of the various molecular species. To determine the accuracy of the correlated k-distribution technique as compared to the line-by-line procedure, atmospheric flux and heating rate calculations were run for a wide variety of atmospheric conditions. For the atmospheric conditions taken into consideration, the correlated k-distribution technique has yielded results within about 0.5% for both the cases where the satellite spectral response functions were applied and where they were not. The correlated k-distribution's principal advantages is that it can be incorporated directly into multiple scattering routines that consider scattering as well as absorption by clouds and aerosol particles.

  19. 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

  20. Mapping landscape phenology preference of yellow-billed cuckoo with AVHRR data

    USGS Publications Warehouse

    Wallace, Cynthia S.A.; Villarreal, Miguel; Van Riper, Charles

    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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. Early evolution of a stratospheric volcanic eruption cloud as observed with TOMS and AVHRR

    USGS Publications Warehouse

    Schneider, D.J.; Rose, William I.; 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 Chichón, 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 μm 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 μm to about 4 μm.

  6. 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.

  7. 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. PMID:27879852

  8. Alpine Grassland Phenology as Seen in AVHRR, VEGETATION, and MODIS NDVI Time Series - a Comparison with In Situ Measurements.

    PubMed

    Fontana, Fabio; Rixen, Christian; Jonas, Tobias; Aberegg, Gabriel; Wunderle, Stefan

    2008-04-23

    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 largescale vegetation growth dynamics above the tree line in the European Alps.

  9. Stratospheric aerosol perturbing effect on the remote sensing of vegetation: operational method for the correction of AVHRR composite NDVI

    NASA Astrophysics Data System (ADS)

    Vermote, Eric F.; El Saleous, Nazmi

    1995-01-01

    Stratospheric aerosols produced by the eruption of the Mount Pinatubo in the Philippines (6 June, 1991) have a detectable effect on NOAA AVHRR data. Following the eruption, a longitudinally homogeneous dust layer was observed between 20 degree(s)N and 20 degree(s)S. The largest optical thickness observed for the dust layer was 0.4 - 0.6 at 0.5 microns. The amount of aerosols produced by Mount Pinatubo was two to three times greater than that produced by El Chichon and the Stratospheric Aerosol and Gas Experiment (SAGE) on-board the Earth Radiation Budget Experiment was not able to give quantitative estimate of aerosol optical thickness because of saturation problem. The monthly composite Normalized Difference Vegetation Index (NDVI) (generally bounded between -0.1 and 0.6) has systematically decreased by approximately 0.15 two months after the eruption. Such atmospheric effect has never been observed on composite product and is related to the persistence and spatial extent of the aerosol layer causing the composite technique to fail. Therefore, long term monitoring of vegetation using the NDVI necessitates correction of the effect of stratospheric aerosols. In this paper we 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

  10. 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.

  11. Improving Land Cover Product-Based Estimates of the Extent of Fragmented Cover Types

    NASA Technical Reports Server (NTRS)

    Hlavka, Christine A.; Dungan, Jennifer

    2002-01-01

    The effects of changing land use/land cover on regional and global climate ecosystems depends on accurate estimates of the extent of critical land cover types such as Arctic wetlands and fire scars in boreal forests. To address this information requirement, land cover products at coarse spatial resolution such as Advanced Very High Resolution Radiometer (AVHRR) -based maps and the MODIS Land Cover Product are being produced. The accuracy of the extent of highly fragmented cover types such as fire scars and ponds is in doubt because much (the numerous scars and ponds smaller than the pixel size) is missed. A promising method for improving areal estimates involves modeling the observed distribution of the fragment sizes as a type of truncated distribution, then estimating the sum of unobserved sizes in the lower, truncated tail and adding it to the sum of observed fragment sizes. The method has been tested with both simulated and actual cover products.

  12. The Common Land Model (CLM)

    NASA Astrophysics Data System (ADS)

    Dai, Y.; Zeng, X.; Dickinson, R. E.

    2001-05-01

    The Common Land Model (CLM) has recently been developed through a grass-roots collaboration of scientists who have an interest in making a general land model available for public use. Its major components include: (1) Ten prognostic layers in the soil temperature and soil moisture, with a free drainage and a zero heat flux as the bottom boundary conditions; (2) A comprehensive parameterization of snow processes with up to 5 snow layers depending on the total snow depth; (3) Prognostic equations for mass of liquid water and ice water within soil / snow, and explicit treatment of phase changes within soil / snow; (4) Runoff is parameterized from the lowlands in terms of precipitation incident on wet areas and a base flow using ideas from TOPMODEL; (5) Incorporation of a realistic canopy photosynthesis-conductance model to describe the simultaneous transfer of CO2 and water vapor into and out of vegetation, respectively. (6) Its interface with the atmospheric model is characterized by a tiled treatment of subgrid fraction of energy and water balance; (7) Global vegetation cover database derived from satellite AVHRR; Global soil data with vertical profile from IGBP-DIS; and Global survey data for root vertical distribution; (8) The code is based on FORTRAN90. The model has been extensively evaluated in offline tests, land-atmosphere coupled simulations, and in data assimilation. In the presentation, we will discuss the model as well as its offline tests using long observational time series from six different sites: Valdai (grassland), Cabauw (grassland), Hapex-Mobilhy (crop), Amazonian (rainforest), FIFE (grassland) and Tucson (semi-desert).

  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. 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

  15. 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

  16. 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.

  17. 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.

  18. Detection of multilayer cirrus cloud systems using AVHRR Data: Verification based on FIRE II IFO composite measurements

    SciTech Connect

    Ou, S.C.; Liou, K.N.; Baum, B.A.

    1996-02-01

    A numerical scheme has been developed to identify multilayer cirrus cloud systems using Advanced Very High Resolution Radiometer (AVHRR) data. It is based on the physical properties of the AVHRR channels 1-2 reflectance ratios, the brightness temperature differences between channels 4 and 5, and the channel 4 brightness temperatures. In this scheme, clear pixels are first separated from cloudy pixels, which are then classified into three types: cirrus, cirrus/low clouds, and low clouds. The authors have applied this scheme to the satellite data collected over the FIRE II IFO [First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment II intensive field observation] area during nine overpasses within seven observation dates. Determination of the threshold values used in the detection scheme are based on statistical analyses of these satellite data. The authors have validated the detection results against the cloudy condition inferred from the collocated and coincident ground-based lidar and radar images, balloonborne replicator data, and National Center for Atmospheric Research CLASS (Cross-chain Loran Atmospheric Sounding System) humidity soundings on a case-by-case basis. In every case, the satellite detection results are consistent with the cloudy conditions inferred from these dependent and complementary measurements. The present scheme is well suited for the detection of midlatitude, multilayer cirrus cloud systems and tropical anvils. 25 refs., 8 figs., 4 tabs.

  19. Detection of Multilayer Cirrus Cloud Systems Using AVHRR Data: Verification Based on FIRE II IFO Composite Measurements.

    NASA Astrophysics Data System (ADS)

    Ou, S. C.; Liou, K. N.; Baum, B. A.

    1996-02-01

    A numerical scheme has been developed to identify multilayer cirrus cloud systems using Advanced Very Higher Resolution Radiometer (AVHRR) data. It is based on the physical properties of the AVHRR channels 1 2 reflectance ratios, the brightness temperature differences between channels 4 and 5, and the channel 4 brightness temperatures. In this scheme, clear pixels are first separated from cloudy pixels, which are then classified into three types: cirrus, cirrus/low cloud, and low clouds. The authors have applied this scheme to the satellite data collected over the FIRE II IFO [First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment II intensive field observations area during nine overseas within seven observation dates. Determination of the threshold values used in the detection scheme are based on statistical analysts of these satellite data. The authors have validated the detection results against the cloudy conditions inferred from the collocated and coincident ground-based lidar and radar images, balloonborne replicator data, and National Center for Atmospheric Research CLASS (Cross-chain Loran Atmospheric Sounding System) humidity soundings on a case-by-case basis. In every case, the satellite detection results are consistent with the cloudy conditions inferred from these independent and complementary measurement. The present scheme is well suited for the detection of midlatitude, multilayer cirrus cloud systems and tropical anvils.

  20. 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.

  1. 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.

  2. 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

  3. Managing Your Seasonal Allergies

    MedlinePlus

    ... antihistamines, topical nasal steroids, cromolyn sodium, decongestants, or immunotherapy. Read More "Seasonal Allergies" Articles Managing Your Seasonal Allergies / Diagnosis, Treatment & Research ...

  4. 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.

  5. 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

  6. 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.

  7. Potential Effects of Winter Navigation on Movements of Large Land Mammals in Eastern Lake Superior and Saint Mary’s River Area. Great Lakes-Saint Lawrence Seaway Navigation Season Extension Program

    DTIC Science & Technology

    1980-09-01

    considered effects on deer, seasonal migrations, daily movements and direct mortality; the dispersal of wolves , bobcats, lynx, moose, coyotes and red foxes...literature and information search pertaining to movements and dispersal of wolves , coyotes, foxes, bobcats, lynx, deer, and moose, and local records of the...islands in Whitefish Bay tracks of foxes, deer and wolf were identified. The partially obliterated tracks of a pack of five wolves were observed near

  8. 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

  9. 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

  10. Land Use and Mapping

    NASA Technical Reports Server (NTRS)

    Lindgren, D. T.; Simpson, R. B.

    1973-01-01

    From the standpoint of technology, the most encouraging thing about ERTS has been the level of land-use identification. Land-use detail has exceeded the expectations of the Interagency Steering Committee and the requirements of land-use classification proposed by the Department of Interior. Whereas in the latter instance it was anticipated that only nine classes of land use would probably be identifiable, in fact some 14 to 18 classes have been identified. The success in the level of land-use identification results primarily from the various attributes of the ERTS system. These include the ability to provide repetitive coverage, and in particular seasonal coverage; the ability to image in four bands of the electromagnetic spectrum (green, red, and two near-infrared), which allows for manipulation of various combinations of bands; and the provision by the ERTS system of computer-compatible tapes for machine processing of data. Furthermore, the resolution of ERTS imagery has been better than expected. Although there is some question as to its exact resolving power, it is safe to say objects as small as 100 meters (300 feet) in diameter have been identified. Linear features as narrow as 16 meters (50 feet) can be detected (Figure 1).

  11. 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.

  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. 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.

  14. A Global Database of Land Surface Parameters at 1-km Resolution in Meteorological and Climate Models.

    NASA Astrophysics Data System (ADS)

    Masson, Valéry; Champeaux, Jean-Louis; Chauvin, Fabrice; Meriguet, Christelle; Lacaze, Roselyne

    2003-05-01

    Ecoclimap, a new complete surface parameter global dataset at a 1-km resolution, is presented. It is intended to be used to initialize the soil-vegetation-atmosphere transfer schemes (SVATs) in meteorological and climate models (at all horizontal scales). The database supports the `tile' approach, which is utilized by an increasing number of SVATs. Two hundred and fifteen ecosystems representing areas of homogeneous vegetation are derived by combining existing land cover maps and climate maps, in addition to using Advanced Very High Resolution Radiometer (AVHRR) satellite data. Then, all surface parameters are derived for each of these ecosystems using lookup tables with the annual cycle of the leaf area index (LAI) being constrained by the AVHRR information. The resulting LAI is validated against a large amount of in situ ground observations, and it is also compared to LAI derived from the International Satellite Land Surface Climatology Project (ISLSCP-2) database and the Polarization and Directionality of the Earth's Reflectance (POLDER) satellite. The comparison shows that this new LAI both reproduces values coherent at large scales with other datasets, and includes the high spatial variations owing to the input land cover data at a 1-km resolution. In terms of climate modeling studies, the use of this new database is shown to improve the surface climatology of the ARPEGE climate model.

  15. Land cover/land use change in semi-arid Inner Mongolia: 1992-2004

    NASA Astrophysics Data System (ADS)

    John, Ranjeet; Chen, Jiquan; Lu, Nan; Wilske, Burkhard

    2009-10-01

    The semi-arid grasslands in Inner Mongolia (IM) are under increasing stress owing to climate change and rapid socio-economic development in the recent past. We investigated changes in land cover/land use and landscape structure between 1992 and 2004 through the analysis of AVHRR and MODIS derived land cover data. The scale of analysis included the regional level (i.e. the whole of IM) as well as the level of the dominant biomes (i.e. the grassland and desert). We quantified proportional change, rate of change and the changes in class-level landscape metrics using the landscape structure analysis program FRAGSTATS. The dominant land cover types, grassland and barren, 0.47 and 0.27 million km2, respectively, have increased proportionally. Cropland and urban land use also increased to 0.15 million km2 and 2197 km2, respectively. However, the results further indicated increases in both the homogeneity and fragmentation of the landscape. Increasing homogeneity was mainly related to the reduction in minority cover types such as savanna, forests and permanent wetlands and increasing cohesion, aggregation index and clumpy indices. Conversely, increased fragmentation of the landscape was based on the increase in patch density and the interspersion/juxtaposition index (IJI). It is important to note the socio-economic growth in this fragile ecosystem, manifested by an increasing proportion of agricultural and urban land use not just at the regional level but also at the biome level in the context of regional climate change and increasing water stress.

  16. Coupling AVHRR imagery with biogeochemical models of methane emission from rice crops

    NASA Astrophysics Data System (ADS)

    Paliouras, Eleni Joyce

    2000-10-01

    Rice is a staple food source for much of the world and most of it is grown in paddies which remain flooded for a large part of the growing season. This anaerobic environment is ideal for the activities of methanogenic bacteria, that are responsible for the production of methane gas, some of which is released into the atmosphere. In order to better understand the role that rice cropping plays in the levels of atmospheric methane, several models have been developed to predict the methane flux from the paddies. These models generally utilize some type of nominal plant growth curve based on one or two pieces of ground truth data. Ideally, satellite data could be used instead to provide these models with an estimate of biomass change over the growing season, eliminating the need for related ground truth. A technique proposed to accomplish this is presented here, and results that demonstrate its success when applied to rice cropping areas of Texas are discussed. Also presented is a method for utilizing satellite data to map rice cropping areas that could eventually aid in a scheme for populating a GIS-type database with information on exact rice cropping areas. Such a database could then be directly tied to the methane emission models to obtain flux estimates for extensive regional areas.

  17. Evaluation of Canadian Seasonal to Interannual Prediction System: seasonal hindcasts of the recent past climate.

    NASA Astrophysics Data System (ADS)

    Markovic, M.

    2015-12-01

    Canadian Seasonal to Interannual Prediction System (CanSIPS) has been operationally active within the Meteorological Service of Canada since the year of 2011. This coupled (atmosphere-land-ocean) system is in charge of producing seasonal forecasts of near surface temperature and precipitation for the following 12 months with respect to the forecast onset. CanSIPS comprises two coupled atmosphere-land-ocean models: CanCM3 and CanCM4 developed in Canadian Centre for Climate Modelling and Analysis. Each model produces ten-member ensemble forecasts which generate twenty member ensemble predictions. In this work we evaluate seasonal hindcasts of the recent past climate (1981-2010) simulated by the CanSIPS system. The importance of such evaluation stems from the fact that seasonal hindcasts can be used to calibrate the results of the seasonal predictions. Calibrated forecasts have in general more skill compared to the raw predictions. Moreover, verification of seasonal hindcasts enables an estimation of the expected performance of the prediction system over various regions and seasons (i.e. expected skill maps). Evaluation will be presented against reanalysis data. Near surface temperature and precipitation will be assessed over different geographical locations and various lead times.

  18. 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.

  19. Sorting Out Seasonal Allergies

    MedlinePlus

    ... Contact Close ‹ Back to Healthy Living Sorting Out Seasonal Allergies Sneezing, runny nose, nasal congestion. Symptoms of the ... Georgeson. How do I know if I have seasonal allergies? According to Dr. Georgeson, the best way to ...

  20. 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.

  1. Seasonal patterns of SST diurnal variation over the Tropical Warm Pool region

    NASA Astrophysics Data System (ADS)

    Zhang, Haifeng; Beggs, Helen; Wang, Xiao Hua; Kiss, Andrew E.; Griffin, Christopher

    2016-11-01

    Five year (2010-2014) Advanced Very High Resolution Radiometer (AVHRR) sea surface temperature (SST) data produced by the Australian Bureau of Meteorology have been validated against drifting buoy data and then used to study the seasonal patterns of the SST diurnal variation (DV) events over the Tropical Warm Pool region (TWP, 25°S-15°N, 90°E-170°E). The in situ validation results illustrate the overall good quality of the AVHRR SST data set, although an average 0.19 K underestimation of the daytime measurements has been observed. The nighttime observations are in good agreement with in situ buoys with an average bias of 0.03 and a 0.30 K standard deviation of the biases. This SST data set is then used to characterize the SST DV seasonal patterns, together with wind speeds, daily maximum solar shortwave insolation (SSImax), and latent heat flux (LHF). A double-peak seasonal pattern of SST DV is observed over the study region: the strongest DVs are found in March and October and the weakest in June. Sensitivity tests of DV to wind, SSImax, and LHF are conducted. The results indicate (1) different morning and early afternoon winds (7 A.M. to 2 P.M. local time, LT) affect DV by as much as 0.73 K when the half-daily (defined as 2 A.M. to 2 P.M. LT in this study) average winds are fixed between 2 and 3 m s-1; (2) SSImax levels regulate DV less significantly (<0.68 K) under fixed winds; and (3) LHF effects on DV are relatively weak (<0.35 K).

  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. Land-use classification using ASTER data and self-organized neutral networks

    NASA Astrophysics Data System (ADS)

    Jianwen, Ma; Bagan, Hasi

    2005-11-01

    Operationally AVHRR and TM/TM+ data were used and a supervised maximum likelihood classification (MLH) was applied to depict land use changes in Beijing, providing basic maps for planning and development. With rapid growth of the city these are helpful to deal with higher resolution data, whereas new classification algorithms produce land use maps more accurate. In the paper, new sensor ASTER data and the Kohonen self-organized neural network feature map (KSOM) were tested. The TSOM classified 7% more accurately than the maximum likelihood algorithm in general, and 50% more accurately for the classes 'residential area' and 'roads'. The results suggest that ASTER data and the Kohonen self-organized neural network classification can be used as an alternative data and method in a land use update operational system.

  4. 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.

  5. 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…

  6. Seasonal Allergies (Hay Fever)

    MedlinePlus

    ... Old Feeding Your 1- to 2-Year-Old Seasonal Allergies (Hay Fever) KidsHealth > For Parents > Seasonal Allergies (Hay ... en español Alergia estacional (fiebre del heno) About Seasonal Allergies "Achoo!" It's your son's third sneezing fit of ...

  7. 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…

  8. Spaceborne observations from AVHRR and GOES weather satellites during the November 2002 eruption of Reventador Volcano, Ecuador

    NASA Astrophysics Data System (ADS)

    Moxey, L.; Harris, A. J.; Dehn, J.; Rowland, S. K.

    2009-12-01

    Satellite data were used to document the sequence of events during the November 2002 eruption of Reventador Volcano, Ecuador. Single-, multi-band and brightness temperature difference ash detection and monitoring techniques using data from the Advanced Very High Resolution Radiometer (AVHRR) and Geostationary Operational Environmental Satellite (GOES) revealed two primary stages of the eruption: a paroxysmal explosive phase between 3 and 4 November 2002 (Phase I), and an intermittent and mildly explosive phase between 5 and 25 November 2002 (Phase II). Initial phreatic activity at Reventador was observed by GOES at 1045z on 3 November, and by 1412z the volcano had entered a Vulcanian explosion that was not observed from space until the GOES scan at 1415z. This eruption generated a 16-km high, near-circular umbrella cloud 40 km in diameter characterized by long period gravity waves that were discernable from space. Similar processes were observed following the eruptions of Mt. St. Helens (1980) and Mt. Pinatubo (1991). The initial spreading rate of Reventador’s umbrella region was measured at 8.6 ms-1, and had a minimum cloud top-temperature of approximately 195°K (-78° C). After the initial 90 minutes, the radial umbrella cloud evolved into an ellipse due to entrainment by regional winds. Our analyses of plume-top temperatures, plume front velocities, and shadow clinometry indicate that the umbrella cloud transitioned into two elongated ash clouds due to wind shear effects at the Tropopause. The ash reached approximately 14 km (Troposphere) and 16 km (Stratosphere) above sea level and advanced westward and eastward, respectively. Over a period of 60 hours, the ash clouds advanced at 5 - 11 ms-1 and traveled 1900 km W and 400 km E of Reventador before falling below satellite detection thresholds. Volcanic ash dispersion model simulations from HYSPLIT and PUFF independently corroborated the observed transport velocities and trajectories. Ground-based data showed

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. Land Research

    EPA Pesticide Factsheets

    EPA is working to develop methods and guidance to manage and clean up contaminated land, groundwater and nutrient pollution as well as develop innovative approaches to managing materials and waste including energy recovery.

  14. 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

  15. Aerosol Retrievals from Individual AVHRR Channels. Part II: Quality Control, Probability Distribution Functions, Information Content, and Consistency Checks of Retrievals.

    NASA Astrophysics Data System (ADS)

    Ignatov, Alexander; Stowe, Larry

    2002-02-01

    This second part of a two-part study evaluates retrievals of aerosol optical depths, 1 and 2, in Advanced Very High Resolution Radiometer (AVHRR) channels 1 and 2 centered at 1 = 0.63 and 2 = 0.83 m, and an effective Ångström exponent, , derived therefrom as = ln(1/2)/ln(1/2). The retrievals are made with the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer model from four NOAA-14 AVHRR datasets, collected between February 1998 and May 1999 in the latitudinal belt of 5°-25°S. A series of quality control (QC) checks applied to the retrievals to identify outliers are described. These remove a total of 1% of points, which presumably originate from channel misregistration, residual cloud in AVHRR cloud-screened pixels, and substantial deviations from the assumptions used in the retrieval model (e.g., bright coastal and high altitude inland waters). First, from examining histograms of the derived parameters it is found that and are accurately fit by lognormal and normal probability distribution functions (PDFs), respectively. Second, the scattergrams 1 versus 2 are analyzed to see if they form a coherent pattern. They do indeed converge at the origin, as expected, but frequently are outside of the expected domain in 1-2 space, defined by two straight lines corresponding to = 0 and = 2. This results in a low bias in , which tends to fill in an interval of [1, 1] rather than

  16. 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.

  17. Remotely sensed rice yield prediction using multi-temporal NDVI data derived from NOAA's-AVHRR.

    PubMed

    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.

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. Influenza Seasonal Summary, 2014-2015 Season

    DTIC Science & Technology

    2015-08-14

    Previous Centers for Disease Conu·ol and Prevention ( CDC ) rep011s estimated 3,000 to 49,000 influenza-associated deaths per season in the United States (US...patients may elevate resistance to these medications or reduce seasonal availability. 8 The CDC released two updates via the CDC Health Advis01y Network...waiting for confnmatory laborat01y testing. These alelis, released during Week 53 (3 December 2014) and Week 1 (9 Januruy 2015), also reinforced CDC

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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…

  9. 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

  10. Global breast cancer seasonality.

    PubMed

    Oh, Eun-Young; Ansell, Christine; Nawaz, Hamayun; Yang, Chul-Ho; Wood, Patricia A; Hrushesky, William J M

    2010-08-01

    Human breast cancer incidence has seasonal patterns that seem to vary among global populations. The aggregate monthly frequency of breast cancer diagnosis was collected and examined for 2,921,714 breast cancer cases diagnosed across 64 global regions over spans from 2 to 53 years. Breast cancer is consistently diagnosed more often in spring and fall, both in the Northern and Southern Hemispheres, regardless of presumable menopausal status (50). This seasonality is increasingly more prominent as population distance from the equator increases and this latitude dependence is most pronounced among women living in rural areas. Moreover, the overall annual incidence (2005-2006), per 100,000 population, of breast cancer increased as the latitude of population residence increased. These data make it clear that human breast cancer discovery occurs non-randomly throughout each year with peaks near both equinoxes and valleys near both solstices. This stable global breast cancer seasonality has implications for better prevention, more accurate screening, earlier diagnosis, and more effective treatment. This complex latitude-dependent breast cancer seasonality is clearly related to predictable local day/night length changes which occur seasonally. Its mechanism may depend upon seasonal sunlight mediation of vitamin D and seasonal mediation of nocturnal melatonin peak level and duration.

  11. Seasonal Biophysical Dynamics of the Amazon from Space Using MODIS Vegetation Indices

    NASA Astrophysics Data System (ADS)

    Huete, A. R.; Didan, K.; Ratana, P.; Ferreira, L.

    2002-12-01

    We utilized the Terra- Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Index (VI) products to analyze the seasonal and spatial patterns of photosynthetic vegetation activity over the Amazon Basin and surrounding regions of Brazil. The seasonal patterns of vegetation activity were studied along two, eco-climatic transects extending from (1) the cerrado region (Brasilia National Park) to the seasonal tropical forest (Tapajos National Forest) and (2) the caatinga biome to the seasonal and per-humid tropical forests. In addition to the climatic transects, we also investigated the seasonal dynamics of altered, land conversion areas associated with pastures and clearcutting land use activities. Both the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) at 250-m, 500-m, and 1-km were used to extract seasonal profile curves. The quality assurance (QA) information of the output products was used in noise removal and data filtering prior to the generation of the seasonal profiles. Histogram analyses were also performed at coarse (biome) scale and fine, site intensive (flux towers) scale. The seasonal patterns of the cerrado and caatinga were very pronounced with distinct dry and wet seasonal trends. We observed decreasing dry-wet seasonal patterns in the transitional areas near Araguaia National Park. In contrast, the seasonal behavior of the tropical forests were much harder to assess, but indicated slight seasonal trends that ran counter to rainfall activity. This may be attributed to new leaf growth in the dry season. We further found MODIS VI seasonal patterns to vary significantly in land converted and land degraded areas.

  12. Seasonal Allergy Research at NIH

    MedlinePlus

    ... page please turn Javascript on. Feature: Managing Allergies Seasonal Allergy Research at NIH Past Issues / Spring 2013 Table ... More "Managing Allergies" Articles How to Control Your Seasonal Allergies / Allergy Diagnosis and Treatment / Seasonal Allergy Research at ...

  13. 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.

  14. 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.

  15. Seasonality of Suicidal Behavior

    PubMed Central

    Woo, Jong-Min; Okusaga, Olaoluwa; Postolache, Teodor T.

    2012-01-01

    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

  16. 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...

  17. 2012 Swimming Season Factsheets

    EPA Pesticide Factsheets

    To help beachgoers make informed decisions about swimming at U.S. beaches, EPA annually publishes state-by-state data about beach closings and advisories for the previous year's swimming season. These fact sheets summarize that information by state.

  18. 50 CFR 20.110 - Seasons, limits, and other regulations for certain Federal Indian reservations, Indian Territory...

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 50 Wildlife and Fisheries 6 2010-10-01 2010-10-01 false Seasons, limits, and other regulations for certain Federal Indian reservations, Indian Territory, and ceded lands. 20.110 Section 20.110 Wildlife and... BIRD HUNTING Annual Seasons, Limits, and Shooting Hours Schedules § 20.110 Seasons, limits, and...

  19. 50 CFR 20.110 - Seasons, limits, and other regulations for certain Federal Indian reservations, Indian Territory...

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 50 Wildlife and Fisheries 9 2014-10-01 2014-10-01 false Seasons, limits, and other regulations for certain Federal Indian reservations, Indian Territory, and ceded lands. 20.110 Section 20.110 Wildlife and... BIRD HUNTING Annual Seasons, Limits, and Shooting Hours Schedules § 20.110 Seasons, limits, and...

  20. 50 CFR 20.110 - Seasons, limits, and other regulations for certain Federal Indian reservations, Indian Territory...

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 50 Wildlife and Fisheries 8 2011-10-01 2011-10-01 false Seasons, limits, and other regulations for certain Federal Indian reservations, Indian Territory, and ceded lands. 20.110 Section 20.110 Wildlife and... BIRD HUNTING Annual Seasons, Limits, and Shooting Hours Schedules § 20.110 Seasons, limits, and...

  1. 50 CFR 20.110 - Seasons, limits, and other regulations for certain Federal Indian reservations, Indian Territory...

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 50 Wildlife and Fisheries 9 2013-10-01 2013-10-01 false Seasons, limits, and other regulations for certain Federal Indian reservations, Indian Territory, and ceded lands. 20.110 Section 20.110 Wildlife and... BIRD HUNTING Annual Seasons, Limits, and Shooting Hours Schedules § 20.110 Seasons, limits, and...

  2. 50 CFR 20.110 - Seasons, limits, and other regulations for certain Federal Indian reservations, Indian Territory...

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 50 Wildlife and Fisheries 9 2012-10-01 2012-10-01 false Seasons, limits, and other regulations for certain Federal Indian reservations, Indian Territory, and ceded lands. 20.110 Section 20.110 Wildlife and... BIRD HUNTING Annual Seasons, Limits, and Shooting Hours Schedules § 20.110 Seasons, limits, and...

  3. 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.

  4. 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.

  5. Seasonal affective disorder.

    PubMed

    Kurlansik, Stuart L; Ibay, Annamarie D

    2012-12-01

    Seasonal affective disorder is a combination of biologic and mood disturbances with a seasonal pattern, typically occurring in the autumn and winter with remission in the spring or summer. In a given year, about 5 percent of the U.S. population experiences seasonal affective disorder, with symptoms present for about 40 percent of the year. Although the condition is seasonally limited, patients may have significant impairment from the associated depressive symptoms. Treatment can improve these symptoms and also may be used as prophylaxis before the subsequent autumn and winter seasons. Light therapy is generally well tolerated, with most patients experiencing clinical improvement within one to two weeks after the start of treatment. To avoid relapse, light therapy should continue through the end of the winter season until spontaneous remission of symptoms in the spring or summer. Pharmacotherapy with antidepressants and cognitive behavior therapy are also appropriate treatment options and have been shown to be as effective as light therapy. Because of the comparable effectiveness of treatment options, first-line management should be guided by patient preference.

  6. 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.

  7. A satellite-based climatology (1989-2012) of lake surface water temperature from AVHRR 1-km for Central European water bodies

    NASA Astrophysics Data System (ADS)

    Riffler, Michael; Wunderle, Stefan

    2013-04-01

    The temperature of lakes is an important parameter for lake ecosystems influencing the speed of physio-chemical reactions, the concentration of dissolved gazes (e.g. oxygen), and vertical mixing. Even small temperature changes might have irreversible effects on the lacustrine system due to the high specific heat capacity of water. These effects could alter the quality of lake water depending on parameters like lake size and volume. Numerous studies mention lake water temperature as an indicator of climate change and in the Global Climate Observing System (GCOS) requirements it is listed as an essential climate variable. In contrast to in situ observations, satellite imagery offers the possibility to derive spatial patterns of lake surface water temperature (LSWT) and their variability. Moreover, although for some European lakes long in situ time series are available, the temperatures of many lakes are not measured or only on a non-regular basis making these observations insufficient for climate monitoring. However, only few satellite sensors offer the possibility to analyze time series which cover more than 20 years. The Advanced Very High Resolution Radiometer (AVHRR) is among these and has been flown on the National Oceanic and Atmospheric Administration (NOAA) Polar Operational Environmental Satellites (POES) and on the Meteorological Operational Satellites (MetOp) from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) as a heritage instrument for almost 35 years. It will be carried on for at least ten more years finally offering a unique opportunity for satellite-based climate studies. Herein we present the results from a study initiated by the Swiss GCOS office to generate a satellite-based LSWT climatology for the pre-alpine water bodies in Switzerland. It relies on the extensive AVHRR 1-km data record (1985-2012) of the Remote Sensing Research Group at the University of Bern (RSGB) and has been derived from the AVHRR/2

  8. 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

  9. Harvesting in seasonal environments.

    PubMed

    Xu, Cailin; Boyce, Mark S; Daley, Daryl J

    2005-06-01

    Most harvest theory is based on an assumption of a constant or stochastic environment, yet most populations experience some form of environmental seasonality. Assuming that a population follows logistic growth we investigate harvesting in seasonal environments, focusing on maximum annual yield (M.A.Y.) and population persistence under five commonly used harvest strategies. We show that the optimal strategy depends dramatically on the intrinsic growth rate of population and the magnitude of seasonality. The ordered effectiveness of these alternative harvest strategies is given for different combinations of intrinsic growth rate and seasonality. Also, for piecewise continuous-time harvest strategies (i.e., open/closed harvest, and pulse harvest) harvest timing is of crucial importance to annual yield. Optimal timing for harvests coincides with maximal rate of decline in the seasonally fluctuating carrying capacity. For large intrinsic growth rate and small environmental variability several strategies (i.e., constant exploitation rate, linear exploitation rate, and time-dependent harvest) are so effective that M.A.Y. is very close to maximum sustainable yield (M.S.Y.). M.A.Y. of pulse harvest can be even larger than M.S.Y. because in seasonal environments population size varies substantially during the course of the year and how it varies relative to the carrying capacity is what determines the value relative to optimal harvest rate. However, for populations with small intrinsic growth rate but subject to large seasonality none of these strategies is particularly effective with M.A.Y. much lower than M.S.Y. Finding an optimal harvest strategy for this case and to explore harvesting in populations that follow other growth models (e.g., involving predation or age structure) will be an interesting but challenging problem.

  10. 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.

  11. Agro-pastoral expansion and land use/land cover (LU/LC) change dynamics in Central-western Brazil

    NASA Astrophysics Data System (ADS)

    Sanga-Ngoie, K.; Yoshikawa, S.; Kanae, S.

    2011-12-01

    In Brazil, large-scale land cover changes following extensive deforestations are expected to generate big impacts onto the climate and the environment over this area, with eventually many negative feedbacks on the global scale. Mato Grosso State, located in the central western Brazil, is known to be the