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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 inter-annual variability. Each of the thermal channels gave similar classification accuracies; however, because of the problems in consistently interpreting channel 3 data, either channel 4 or 5 was found to be a more

  3. AVHRR composite period selection for land cover classification

    USGS Publications Warehouse

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

    2002-01-01

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

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

    USGS Publications Warehouse

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

    1998-01-01

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

  5. 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. Mapping global land surface albedo from NOAA AVHRR

    NASA Astrophysics Data System (ADS)

    Csiszar, I.; Gutman, G.

    1999-03-01

    A set of algorithms is combined for a simple derivation of land surface albedo from measurements of reflected visible and near-infrared radiation made by the advanced very high resolution radiometer (AVHRR) onboard the National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites. The system consists of a narrowband-to-broadband conversion and bidirectional correction at the top of the atmosphere and an atmospheric correction. We demonstrate the results with 1 month worth of data from the NOAA National Environmental Satellite, Data, and Information Service (NESDIS) global vegetation index (GVI) weekly data set and the NOAA/NASA Pathfinder Atmosphere (PATMOS) project daily data. Error analysis of the methodology indicates that the surface albedo can be retrieved with 10-15% relative accuracy. Monthly albedo maps derived from September 1989 GVI and PATMOS data agree well except for small discrepancies attributed mainly to different preprocessing and residual atmospheric effects. A 5-year mean September map derived from the GVI multiannual time series is consistent with that derived from low-resolution Earth Radiation Budget Experiment data as well as with a September map compiled from ground observations and used in many numerical weather and climate models. Instantaneous GVI-derived albedos were found to be consistent with surface albedo measurements over various surface types. The discrepancies found can be attributed to differences in areal coverage and representativeness of the satellite and ground data. The present pilot study is a prototype for a routine real-time production of high-resolution global surface albedo maps from NOAA AVHRR Global Area Coverage (GAC) data.

  10. 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.

  11. Global data on land surface parameters from NOAA AVHRR for use in numerical climate models

    SciTech Connect

    Gutman, G.G. )

    1994-05-01

    This paper reviews satellite datasets from the NOAA Advanced Very High Resolution Radiometer that could be employed in support of numerical climate modeling at regional and global scales. Presently available NOAA operational and research datasets of different resolutions as well as the NASA-NOAA Pathfinder dataset, available in the near future, are briefly described. Specific problems in deriving surface characteristics in the context of their potential use of models are discussed. Possible ways of solving these problems are briefly described, based on the state-of-the-art level of understanding in this area of research. Some examples of seasonal variability of AVHRR-derived surface parameters, such as albedo, greenness, and clear-sky midafternoon temperature, for different climatic regions are presented. Validation issues and potential operational production of such land climate parameters are discussed.

  12. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  14. 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.

  15. Seasonal and interannual responses of the vegetation and production of crops in Cordoba Argentina assessed by AVHRR derived vegetation indices

    NASA Astrophysics Data System (ADS)

    Seiler, R. A.; Kogan, F.; Wei, Guo; Vinocur, M.

    Advanced Very High Resolution Radiometer (AVHRR) -based vegetation indices are widely accepted as good indicators for providing vegetation properties and associated changes for large scale geographic regions. Also, their capability to indicate moisture conditions makes them an important data source for monitoring climate variations and droughts. The objective of this study was to test the AVHRR-vegetation conditions indices data set as indicators of the weather variability through the seasonal and interannual responses of the vegetation and the production of crops. Time-series of AVHRR vegetation condition indices during 1981 2003 were used to generate the seasonal and interannual vegetation curves for departments (administrative unites) of the Cordoba province in Argentina. Yield series of corn by departments were analyzed against AVHRR derived indices and corn yield predicting models were developed. Vegetation condition curves were able to differentiate vegetation responses associated with normal/above normal and below normal precipitation during the growing season. Corn yield models based on the vegetation condition indices explained up to 80% of the yield variation of corn, according to departments. Results from the analysis showed that the variability of the indices serves as good proxy for identifying environmental sources of variations mainly climate, and thus to provide insights for further analysis to understand the potential of the regional climate for crop production and the effects of the climate variability on vegetation and on corn yield.

  16. Can interannual land surface signal be discerned in composite AVHRR data?

    NASA Astrophysics Data System (ADS)

    Cihlar, J.; Chen, J. M.; Li, Z.; Huang, F.; Latifovic, R.; Dixon, R.

    1998-09-01

    The ability to make repeated measurements of the changing Earth's surface is the principal advantage of satellite remote sensing. To realize its potential, it is necessary that true surface changes be isolated in the satellite signal from other effects which also influence the signal. In this study, we explore the magnitude of such effects in composite NOAA advanced very high resolution radiometer (AVHRR) images with a pixel spacing of 1 km. A compositing procedure is frequently used in the preparation of data sets for land biosphere studies to minimize the effect of clouds. However, the composite images contain residual artifacts which make it difficult to compare measurements at various times. We have employed a 4-year (1993-1996) AVHRR data set from NOAA 11 and 14 covering the Canadian landmass and corrected these data for the influence of the remaining clouds (full pixel or subpixel), atmospheric attenuation, and bidirectional reflectance. We have found that such corrections are essential for studies of interannual variations. The magnitude of the interannual signal varied with the AVHRR channel, land cover type, and satellite sensor but it was reduced by a factor of 2 to 8 between top of the atmosphere and the normalized surface reflectance. The remaining variations consisted of true interannual signal and the residual noise in the data (including sensor calibration) which was not removed by the correction process. Assuming that barren or sparsely vegetated land in northern Canada has not changed over the 4-year period, the mean residual uncertainty in surface reflectance of the selected sites was 0.012 for AVHRR channel 1, 0.042 for channel 2, and 0.068 for the normalized difference vegetation index (NDVI). These values decreased to 0.011, 0.024 and 0.038, respectively, when excluding 1994 data because their atmospheric and bidirectional corrections were hampered by high solar zenith angles (mean values above 55° in all 1994 composite periods). The errors

  17. 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

  18. 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

  19. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

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

  1. Monitoring land cover changes in Morocco using environmental indicators derived from NDVI and LST data of NOAA-AVHRR imagery

    NASA Astrophysics Data System (ADS)

    Erraji, A.; Yessef, M.; Bouhaloua, M.; Bicheron, P.

    With regard to the rapid evolution of natural resources and man made structures, Morocco is facing increasing needs for data and information to assess land cover changes and impacts at broad spatial scales. The proposed paper presents the results of a study on the potential of low resolution images (the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR)) for global and spatial-temporal monitoring of vegetation changes. Based on the Normalized Vegetation Index (NDVI) and Land Surface Temperature (LST) two indicators are produced for the monitoring of land cover dynamics in the whole country. This method was inspired by the method called Vector of Land Cover Dynamic (VLCD) published by Raissouni and Sobrino (2001). Using the 1-km AVHRR data from 1996 to 2003 and a global stratification as mapping criterion several graphs and change maps are elaborated. The analysis of the spatial-temporal evolution of the representative zones has shown a concentrated land cover dynamic in areas localized in the central and the south to south-east part of the country. These land cover changes are essentially related to the conjugated actions of severe climate conditions and human actions during this period.

  2. 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...

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Running, Steven W.; Nemani, Ramakrishna R.

    1988-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Myneni, Ranga

    2003-01-01

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

  15. On The Reproducibility of Seasonal Land-surface Climate

    SciTech Connect

    Phillips, T J

    2004-10-22

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

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

    SciTech Connect

    Phillips, T J

    2001-10-01

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

  17. 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.

  18. 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

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  1. 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.

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

    SciTech Connect

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

    1987-07-01

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

  3. 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...

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

    USGS Publications Warehouse

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

    2002-01-01

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

  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. 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

  7. 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.

  8. 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.

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

    NASA Technical Reports Server (NTRS)

    Cooper, D. I.; Asrar, G.

    1989-01-01

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

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. Dry season distribution of land crabs, Gecarcinus quadratus (Crustacea: Gecarcinidae), in Corcovado National Park, Costa Rica.

    PubMed

    Griffiths, Megan E; Mohammad, Basma A; Vega, Andres

    2007-03-01

    The land crab Gecarcinus quadratus is an engineering species that controls nutrient cycling in tropical forests. Factors regulating their coastal distribution are not fully understood. We quantified land crab distribution during the dry season at Sirena Field Station in Corcovado National Park, Costa Rica, and found that land crab burrow density decreases with increasing distance from the ocean. Leaf litter depth and tree seedling density are negatively correlated with land crab burrow density. Burrows are strongly associated with sand substrate and burrow density is comparatively low in clay substrate. Results suggest that G. quadratus is limited to a narrow coastal zone with sand substrate, and this distribution could have profound effects on plant community structure.

  17. Dry season distribution of land crabs, Gecarcinus quadratus (Crustacea: Gecarcinidae), in Corcovado National Park, Costa Rica.

    PubMed

    Griffiths, Megan E; Mohammad, Basma A; Vega, Andres

    2007-03-01

    The land crab Gecarcinus quadratus is an engineering species that controls nutrient cycling in tropical forests. Factors regulating their coastal distribution are not fully understood. We quantified land crab distribution during the dry season at Sirena Field Station in Corcovado National Park, Costa Rica, and found that land crab burrow density decreases with increasing distance from the ocean. Leaf litter depth and tree seedling density are negatively correlated with land crab burrow density. Burrows are strongly associated with sand substrate and burrow density is comparatively low in clay substrate. Results suggest that G. quadratus is limited to a narrow coastal zone with sand substrate, and this distribution could have profound effects on plant community structure. PMID:18457130

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

    USGS Publications Warehouse

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

    2004-01-01

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

  19. Arctic sea ice albedo from AVHRR

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

    The seasonal cycle of surface albedo of sea ice in the Arctic is estimated from measurements made with the Advanced Very High Resolution Radiometer (AVHRR) on the polar-orbiting satellites NOAA-10 and NOAA-11. The albedos of 145 200-km-square cells are analyzed. The cells are from March through September 1989 and include only those for which the sun is more than 10 deg above the horizon. Cloud masking is performed manually. Corrections are applied for instrument calibration, nonisotropic reflection, atmospheric interference, narrowband to broadband conversion, and normalization to a common solar zenith angle. The estimated albedos are relative, with the instrument gain set to give an albedo of 0.80 for ice floes in March and April. The mean values for the cloud-free portions of individual cells range from 0.18 to 0.91. Monthly averages of cells in the central Arctic range from 0.76 in April to 0.47 in August. The monthly averages of the within-cell standard deviations in the central Arctic are 0.04 in April and 0.06 in September. The surface albedo and surface temperature are correlated most strongly in March (R = -0.77) with little correlation in the summer. The monthly average lead fraction is determined from the mean potential open water, a scaled representation of the temperature or albedo between 0.0 (for ice) and 1.0 (for water); in the central Arctic it rises from an average 0.025 in the spring to 0.06 in September. Sparse data on aerosols, ozone, and water vapor in the atmospheric column contribute uncertainties to instantaneous, area-average albedos of 0.13, 0.04, and 0.08. Uncertainties in monthly average albedos are not this large. Contemporaneous estimation of these variables could reduce the uncertainty in the estimated albedo considerably. The poor calibration of AVHRR channels 1 and 2 is another large impediment to making accurate albedo estimates.

  20. 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

  1. [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. PMID:26314105

  2. 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.

  3. 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.

  4. 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.

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

    NASA Astrophysics Data System (ADS)

    Khanna, J.; Medvigy, D.

    2012-12-01

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

  6. 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

  7. 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.

  8. 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.

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

    PubMed

    Zhu, Yajuan; Wang, Guojie; Li, Renqiang

    2016-01-01

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

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

    PubMed

    Zhu, Yajuan; Wang, Guojie; Li, Renqiang

    2016-01-01

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

  11. 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

  12. Seasonal dynamics of surface runoff in mountain grassland ecosystems differing in land use

    NASA Astrophysics Data System (ADS)

    Leitinger, Georg; Tasser, Erich; Newesely, Christian; Obojes, Nikolaus; Tappeiner, Ulrike

    2010-05-01

    SummaryBetter understanding of surface runoff quantity for distinct hydrological units becomes increasingly important as many rainfall-runoff models use static surface runoff coefficients and neglect key factors affecting ecohydrological dynamics, e.g. land cover and land use. Especially in small-scale alpine catchments, surface runoff and its contribution to mountain torrent runoff is frequently underestimated. In our study, the seasonal variability of surface runoff on abandoned areas and pastures in the alpine catchment 'Kaserstattalm' (Stubai Valley, Austria, Eastern Alps) was analyzed using a rain simulator along with soil water content ( SWC) and soil water tension ( SWT) measurements. Additionally, seasonal variability of soil physical and soil hydraulic properties were assessed. Analyzing more than 30 rainfall simulations on 10 m 2 plots at a rate of 90 mm h -1 (equivalent to convective precipitation events with 100 years return period) revealed a mean surface runoff coefficient of 0.01 on abandoned areas and 0.18 on pastures. Regarding seasonal variability, relevant surface runoff was limited to pastures in autumn with a maximum runoff coefficient of 0.25. The field capacity ( Fc) of all soils was found to be stable throughout the season. However, for pastures, cattle trampling led to a significant increase of dry bulk density ( BD) of up to +0.33 g cm -3 ( p ⩽ 0.01) in the top 0.1 m of the soil which is attributed to a compaction of macropores. Although measured infiltration rates decreased by more than 60%, BD could 'recover' during the winter season presumably due to freezing-and-thawing cycles and bioturbation processes decreasing soil compaction. This study highlights that impacts of land-use changes on soil physical properties make surface runoff difficult to model. Moreover, dynamic and interactive behaviour of soil parameters have to be considered in order to make realistic assessments and accurate predictions of surface runoff rates. Finally

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

    USGS Publications Warehouse

    Miller, Wayne A.; Johnston, David C.

    1985-01-01

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

  14. Arctic sea ice albedo from AVHRR

    SciTech Connect

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

    1994-11-01

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

  15. 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...

  16. 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.

  17. 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.

  18. 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.

  19. 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. PMID:26024489

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

    PubMed Central

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

    2015-01-01

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

  1. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-09-01

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

  3. [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.

  4. 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.

  5. 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.

  6. 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

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

    SciTech Connect

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

    1993-12-01

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

  8. 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.

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

    NASA Astrophysics Data System (ADS)

    Schroth, A. W.

    2015-12-01

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

  10. A satellite-based snow cover climatology (1985-2011) for the European Alps derived from AVHRR data

    NASA Astrophysics Data System (ADS)

    Hüsler, F.; Jonas, T.; Riffler, M.; Musial, J. P.; Wunderle, S.

    2014-01-01

    Seasonal snow cover is of great environmental and socio-economic importance for the European Alps. Therefore a high priority has been assigned to quantifying its temporal and spatial variability. Complementary to land-based monitoring networks, optical satellite observations can be used to derive spatially comprehensive information on snow cover extent. For understanding long-term changes in alpine snow cover extent, the data acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensors mounted onboard the National Oceanic and Atmospheric Association (NOAA) and Meteorological Operational satellite (MetOp) platforms offer a unique source of information. In this paper, we present the first space-borne 1 km snow extent climatology for the Alpine region derived from AVHRR data over the period 1985-2011. The objective of this study is twofold: first, to generate a new set of cloud-free satellite snow products using a specific cloud gap-filling technique and second, to examine the spatiotemporal distribution of snow cover in the European Alps over the last 27 yr from the satellite perspective. For this purpose, snow parameters such as snow onset day, snow cover duration (SCD), melt-out date and the snow cover area percentage (SCA) were employed to analyze spatiotemporal variability of snow cover over the course of three decades. On the regional scale, significant trends were found toward a shorter SCD at lower elevations in the south-east and south-west. However, our results do not show any significant trends in the monthly mean SCA over the last 27 yr. This is in agreement with other research findings and may indicate a deceleration of the decreasing snow trend in the Alpine region. Furthermore, such data may provide spatially and temporally homogeneous snow information for comprehensive use in related research fields (i.e., hydrologic and economic applications) or can serve as a reference for climate models.

  11. 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.

  12. Cold season ammonia emissions from land spreading with anaerobic digestates from biogas production

    NASA Astrophysics Data System (ADS)

    Köster, Jan Reent; Dittert, Klaus; Mühling, Karl-Hermann; Kage, Henning; Pacholski, Andreas

    2014-02-01

    Anaerobic digestates (AD) from biogas production are applied to agricultural land as organic fertilizers, but pose an ammonia (NH3) emission source. However, data about NH3 emissions of cold season AD land spreading is still lacking. Therefore, in the present study NH3 emissions of AD application under winter conditions were determined. AD was applied via trail hoses to a field plot of 27 ha in Northern Germany during the winter with temperatures around the freezing point and partly frozen soil. NH4+ N application rate was, including a preceding urea application, 123 kg NH4+ and urea N ha-1. The NH3 volatilization was monitored using Open Path Fourier Transform Infrared spectroscopy in combination with a micrometeorological transport model. Cumulative NH3 volatilization during the six day measurements was 17.5 kg NH3 N ha-1 which corresponds to 33.1% of the NH4+ N in applied AD. This NH3 loss is relatively high for low temperature conditions and was most likely caused by the frozen soil restricting AD infiltration.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  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. 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

  20. 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.

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

    PubMed

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

    2016-04-01

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

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

  4. 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

  5. Weather variability and interannual responses of the vegetation and crops in Cordoba-Argentina assessed by AVHRR derived vegetation indices

    NASA Astrophysics Data System (ADS)

    Seiler, R.; Kogan, F.; Vinocur, M.

    Advanced Very High Resolution Radiometer (AVHRR) based vegetation indices are widely accepted as good indicators for providing vegetation properties and associated changes for large scale geographic regions. Also, their capability to indicate moisture conditions makes them an important data source for monitoring climate variations and droughts. The objective of this study was to assess the seasonal interannual responses of vegetation and crops to the weather variability. Time-series analysis of AVHRR Normalized Difference Vegetation Index (NDVI) and vegetation health indices weekly composite data collected during 1981-2003 were used to generate the seasonal vegetation curves for each of the departments (administrative unite) of the Cordoba province in Argentina, and to calculate the onset of the growing seasons. Yield series of corn and soybean for each of the departments were analyzed against AVHRR derived indices and seasonal precipitation data from the meteorological stations in the province. Results from the analysis showed that the variability of the indices serves as good proxy for identifying climate variations and thus provide insights into understanding the regional climate carrying capacity, the climate anomalies and the effects of the climate variability on vegetation, on the onset and length of the growing season and on the yields of agricultural crops.

  6. 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

  7. 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

  8. Impacts of forest harvest on cold season land surface conditions and land-atmosphere interactions in northern Great Lakes states

    NASA Astrophysics Data System (ADS)

    Garcia, Matthew; Özdogan, Mutlu; Townsend, Philip A.

    2014-09-01

    Land cover change, including temporary disturbances such as forest harvests, can significantly affect established regimes of surface energy balance and moisture exchange, altering flux processes that drive weather and climate. We examined the impacts of forest harvest on winter land-atmosphere interactions in a temperate region using high-resolution numerical modeling methods in paired simulations. Using the WRF-ARW atmospheric model and the Noah land surface model, we simulated the balance of surface sensible and latent heat fluxes and the development and dissipation of a stable nocturnal boundary layer during generally calm synoptic conditions. Our results show reduced daily-average snow-covered land surface sensible heat flux (by 80%) and latent heat flux (by 60%) to the atmosphere in forest clearings due to albedo effects and rebalancing of the surface energy budget. We found a land surface cooling effect (-8 W m-2) in snow-covered cleared areas, consistent with prior modeling studies and conceptual understanding of the mechanisms for midlatitude deforestation to offset anthropogenic global warming at local scales. Results also demonstrate impacts of forest clearing on the passage of a weak cold front due to altered near-surface winds and boundary layer stability. We show significant differences in both surface conditions and fluxes between harvested and undisturbed forest areas. Our results demonstrate the potential utility of high-resolution remote sensing analyses to represent transient land cover changes in model simulations of weather and climate, which are usually undertaken at coarser resolutions and often overlook these changes at the land surface.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  10. Interannual Variations and Recurrent Seasonal Discrepancies in Land Surface Latent and Sensible Heat Fluxes from Satellite Data and a Land Surface Model

    NASA Astrophysics Data System (ADS)

    Lipton, A.; Liang, P.; Jimenez, C.; Moncet, J. L.; Aires, F.; Prigent, C.; Lynch, R.; d'Entremont, R. P.

    2014-12-01

    Interannual variability of land surface latent and sensible heat fluxes has been analyzed at seasonal and sub-seasonal time scales for flux estimates derived from satellite data and from a land surface model. The satellite-derived estimates were produced with a neural network operating on a combination of microwave, visible, and infrared satellite data products. Properties of these flux datasets were assessed by subjective and statistical methods, including comparisons with data from flux towers. The agreement with tower fluxes is closer for the satellite-derived fluxes than for the LSM fluxes with respect to overall temporal variability. For interannual variations of sub-seasonal fluxes, the satellite/NN and LSM fluxes have similar, moderate correlations (~0.4) with the tower fluxes. Driving factors contributing to the interannual variability and recurrent discrepancies between these flux estimates were identified. These factors include the sensitivity of satellite-derived fluxes to the satellite inputs and the responses of modeled fluxes to changes in soil moisture induced by prior precipitation.

  11. 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.

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

    PubMed

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

    2015-04-15

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

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

    PubMed

    Ayanlade, Ayansina

    2016-07-01

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

  14. 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

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  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. 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...

  20. 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...

  1. 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...

  2. 25 CFR 166.308 - Can the number of animals and/or season of use be modified on the permitted land if I graze...

    Code of Federal Regulations, 2011 CFR

    2011-04-01

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

  3. 25 CFR 166.308 - Can the number of animals and/or season of use be modified on the permitted land if I graze...

    Code of Federal Regulations, 2010 CFR

    2010-04-01

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

  4. Hailstreak Occurrence and Persistence Observed With AVHRR NDVI Image Time Series

    NASA Astrophysics Data System (ADS)

    Henebry, G. M.; Ratcliffe, I. C.

    2002-12-01

    Hail is a major cause of crop loss and property damage in the United States. Hailstreaks are columns of hail that have swept the ground. The abrupt devegetation of the land surface by hailstreaks can have significant biogeophysical consequences. Changes in the surface energy balance and local wind fields can give rise to 'inland sea-breeze' phenomenon that may serve to trigger convection. We investigated the relationship between hail occurrences and the appearance and persistence of hailstreaks in composited image time series. Due to abrupt changes in vegetation density, hailstreaks can be identified in Normalized Difference Vegetation Index (NDVI) imagery. To enhance detection of hailstreaks, ΔNDVI images were generated from a standard set of biweekly maximum AVHRR NDVI composites for the conterminous US produced by the USGS EROS Data Center. These data have a nominal spatial resolution of 1 km. Overlaying the digitized point locations of the National Weather Service reports of hail onto the ΔNDVI imagery, hailstreaks were identified as dark areas coincident with or proximate to hail reports. From 1990-1999, 112 events of significant hailstreaks were observed. Hailstreaks appear mostly in the Great Plains states of Nebraska, Kansas, and the Dakotas, with significant clusters in Minnesota, Iowa, and Texas. The hailstreaks ranged in length from 9 to 367 km (median=66 km; mean=82 km) and in area from 21 to 8443 sq km (median=408 sq km; mean=707 sq km). A total of 79,227 sq km of vegetation were impacted by hailstreaks during the 1990s; however, this estimate is a lower bound due to the compositing process that selects for maximum NDVI. The seasonality of hailstreaks peaked in summer (69%), with 58% appearing in June or July. More hailstreaks appeared in the spring (26%) than in autumn (5%). Observed hailstreak persistence ranged from 9 to 95 d (median=34 d; mean=37 d; mode=28 d). Hailstreak persistence was a complex function of seasonal timing of the event

  5. 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.

  6. A satellite-based snow cover climatology (1985-2011) for the European Alps derived from AVHRR data

    NASA Astrophysics Data System (ADS)

    Hüsler, F.; Jonas, T.; Riffler, M.; Musial, J. P.; Wunderle, S.

    2013-06-01

    Seasonal snow cover is of great environmental and socio-economic importance for the European Alps. Therefore a high priority has been assigned to quantifying its temporal and spatial variability. Complementary to land-based monitoring networks, optical satellite observations can be used to derive spatially comprehensive information on snow cover extent. For understanding long-term changes in alpine snow cover extent, the data acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensors mounted onboard the National Oceanic and Atmospheric Association (NOAA) and Meteorological Operational satellite (MetOp) platforms offer a~unique source of information. In this paper, we present the first space-borne 1 km snow extent climatology for the Alpine region derived from AVHRR data over the period 1985-2011. The objective of this study is twofold: first, to generate a new set of cloud-free satellite snow products using a specific cloud gap-filling technique and second, to examine the spatiotemporal distribution of snow cover in the European Alps over the last 27 yr from the satellite perspective. For this purpose, snow parameters such as snow onset day, snow cover duration (SCD), melt-out date and the snow cover area percentage (SCA) were employed to analyze spatio-temporal variability of snow cover over the course of 3 decades. On the regional scale, significant trends were found toward a shorter SCD at lower elevations in the south-east and south-west. However, our results do not show any significant trends in the monthly mean SCA over the last 27 yr. This is in agreement with other research findings and may indicate a~deceleration of the decreasing snow trend in the Alpine region. Given the importance of mountain regions for climate change assessment, this study recommends the complementary use of remote sensing data for long-term snow applications. It bears the potential to provide spatially and temporally comprehensive snow information for use in related

  7. Summer season land cover—Convective cloud associations for the midwest U.S. “Corn Belt”

    NASA Astrophysics Data System (ADS)

    Carleton, Andrew M.; Adegoke, Jimmy; Allard, Jason; Arnold, David L.; Travis, David J.

    Human-induced land cover modifications impact the planetary boundary layer's (PBL) thermal and moisture regimes on mesoscales. We investigate the association of croplands, forest, and the crop-forest “boundary” (CFB) with convective-cloud development (timing, amount) for three target areas (TAs) in the U.S. Midwest “Corn Belt”, during the summer seasons (JJA) 1991-98. For each land cover, hourly satellite-retrieved albedo and cloud-top temperature values are composited for three classes of mid-tropospheric synoptic circulation. On days with the strongest anticyclonicity, there are no consistent differences in convection related to land cover type: cloud development is regionalized and tied primarily to synoptic conditions. However, on days having weaker anticyclonicity the CFB is the dominant site of free convection, suggesting that Non-Classical Mesoscale Circulations (NCMCs) between cropped and adjacent forest areas may operate when reduced subsidence in the mid-troposphere does not effectively cap the PBL. Index terms: Land/atmosphere interactions (3322), Mesoscale meteorology (3329), Climate dynamics (1620), Anthropogenic effects (1803).

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

    NASA Technical Reports Server (NTRS)

    Matthews, E.

    1984-01-01

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

  9. 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)....

  10. 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.

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

    NASA Technical Reports Server (NTRS)

    Harrington, J. A., Jr.

    1982-01-01

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

  12. 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. PMID:27604756

  13. Soil moisture variability and land use in a seasonally arid environment

    NASA Astrophysics Data System (ADS)

    Williams, A. G.; Ternan, J. L.; Fitzjohn, C.; de Alba, S.; Perez-Gonzalez, A.

    2003-02-01

    Soil moisture patterns were recorded for six different land uses, including oak forest, matorral scrub, olives, and a cultivated field, in central Spain during 1998-99. Volumetric water content was determined using time domain reflectometry at more than 140 sites in each, extending across a range of topographic units. Soil moisture content was a function of land use, with the oak forest being wetter than either the matorral shrubby area or the cultivated site. The spatial patterns for a wet period were kriged and are presented as interpolated contour plots. Geo-statistical analysis confirmed that the patterns were highly heterogeneous, as the variograms showed a pure nugget for each land use, except for the two olive sites, where some spatial structure could be observed. During the investigation the soils were in the dry state and the soil moisture distribution was controlled by local factors; it was not possible to determine which environmental factor had the most influence.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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.

  19. A novel approach to emission modelling 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.

    2012-08-01

    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

  20. 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

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

    SciTech Connect

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

    1997-06-01

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

  2. 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.

  3. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  5. 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.

  6. [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.

  7. Relative sea-level change, Kjove Land, Scoresby Sund, East Greenland: Implications for seasonality in Younger Dryas time

    NASA Astrophysics Data System (ADS)

    Hall, B.; Baroni, C.; Denton, G.; Kelly, M. A.; Lowell, T.

    2008-12-01

    The age of the Milne Land Stade (MLS) moraines in the Scoresby Sund region of East Greenland is key for testing the hypothesis that strong seasonality marked abrupt cooling events, such as the Younger Dryas, registered in Greenland ice cores. The relevant chronology is based on 69 radiocarbon dates of shells from raised beaches and deltas related to marine inundation and isostatic rebound that accompanied glacier retreat from the moraines. Taken together, these dates form the basis for a relative sea-level curve that shows very high rates of emergence typical of recently deglaciated regions. Upward extrapolation of this curve suggests that the marine limit (134 m a.s.l.) dates to about 12,400 cal yr B.P. The shorelines that mark the marine limit lie within areas that were ice-covered when the glaciers were at the outer limit of the MLS advance; hence, the moraines that form the outer limit must antedate 12,400 cal yr B.P. and probably are from earliest Younger Dryas or Allerød time. At Holger Danskes Briller, an inner moraine grades to a massive ice-contact delta, now at 101 m a.s.l., which is dated to 11,000-11,300 cal yr B.P. The age of the outer MLS moraines, along with constraints on the maximum possible Younger Dryas ice extent and snowline lowering are consistent with the idea that East Greenland climate experienced strong seasonality during Younger Dryas time.

  8. 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

  9. 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.

  10. Seasonal, intraseasonal, and interannual variability of global land fires and their effects on atmospheric aerosol distribution

    NASA Astrophysics Data System (ADS)

    Ji, Yimin; Stocker, Erich

    2002-12-01

    In order to understand the variability of global land fires and their effects on the distribution of atmospheric aerosols, statistical methods were applied to the Tropical Rainfall Measuring Mission (TRMM) fire products as well as the Total Ozone Mapping Spectrometer (TOMS) aerosol index products for a period of 4 years from January 1998 to December 2001. The fire data in this period manifested a strong annual cycle of land fires in Southeast Asia with a peak in March and in Africa and North and South America with a peak in August. The data also indicated interannual variations in Indonesia and Central America associated with the 1998-1999 El Niño-Southern Oscillation cycle. The variability of global atmospheric aerosol is consistent with the fire variations over these regions. However, in southwestern Australia, intense fires were recorded in TRMM fire data, but no smoke was observed in the TOMS aerosol product. Excluding the Australian region, the correlation between fire count and TOMS aerosol index is about 0.55 for fire pixels. Empirical orthogonal function analysis (EOF) and singular spectrum analysis methods were used to analyze the TRMM Science Data and Information System pentad fire composite data and TOMS pentad aerosol index data for this 4 year period. The EOF analyses showed contrast between the Northern and Southern Hemispheres and also intercontinental transitions in Africa and America. These analyses also identified 25-60 day intraseasonal oscillations that were superimposed on the annual cycles of both fire and aerosol data. The intraseasonal variability of fires showed a similarity of Madden-Julian oscillation mode.

  11. The impact of land initialization on seasonal forecasts of surface air temperature: role of snow data assimilation in the Northern Hemisphere

    NASA Astrophysics Data System (ADS)

    Lin, P.; Wei, J.; Zhang, Y.; Yang, Z. L.

    2015-12-01

    Land initializations (i.e., snow, soil moisture, leaf area index) have been recognized as important sources of seasonal climate predictability besides ocean and atmosphere initializations. However, studies focusing on assessing how land data assimilation (DA) contributes to seasonal forecast skills are still lacking due to the limited number of large-scale land DA studies. In this study, taking advantage of the snow outputs from a multivariate global land DA system (i.e., DART/CLM), we systematically investigated the role of large-scale snow DA in influencing seasonal forecasts of surface air temperature. Three suites of ensemble seasonal forecast experiments were performed using the Community Earth System Model (CESM v1.2.1), in which three different snow initialization datasets were used. They are (1) CLM4 simulation without DA, (2) CLM4 simulation with MODIS snow cover DA, and (3) CLM4 simulation with joint GRACE and MODIS snow DA. Each suite of the experiment starts from multiple initialization dates of eight years from 2003 to 2010 and has three-month lead times. All experiments used the same atmosphere initializations from ERA-Interim (perturbed to get 8 ensembles) and the same prescribed SSTs. Our results show that snow DA plays an important role in surface air temperature predictions in regions such as Europe, western Canada, northern Alaska, Mongolia Plateau, Tibetan Plateau, and the Rocky Mountains. The analyses also account for multiple lead times as snow can influence the atmosphere through immediate snow-albedo effect and through delayed snow hydrological effect after snow melts and wets the soil. This is a first study to quantify the impacts of snow initializations on seasonal forecasts of surface air temperature with an emphasis on large-scale snow DA. The insights are helpful to both land DA studies as well as research on seasonal climate forecasts.

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. The seasonality of phosphorus transfers from land to water: implications for trophic impacts and policy evaluation.

    PubMed

    Jordan, P; Melland, A R; Mellander, P-E; Shortle, G; Wall, D

    2012-09-15

    The Nitrates Directive regulations are a Programme of Measures under the EU Water Framework Directive to protect waters from agricultural transfers of nitrogen and phosphorus. Soil phosphorus management to an agronomic optimum and closed winter periods for organic and inorganic fertiliser amendments are among a suite of policy measures to curtail diffuse pollution at catchment scale. In this investigation, two intensive grassland and two arable catchments (7-12 km(2)) in the Republic of Ireland were studied to link a high resolution spatial survey (≤2 ha) of soil P availability with P delivery in receiving rivers; monitored on a sub-hourly basis over one year. Data indicated that source risk, as defined by soil P availability and organic P loading, was less important than mobilisation and hydrological transfer potential which increased delivery due to runoff flashiness as described by a hydrological metric during the winter. Overall, however, annual TP loads were low to moderate (0.175 to 0.785 kg ha(-1) yr(-1)). The data also highlighted, without exception, the influences of summer background P loading and subsequent ecologically significant P concentrations from persistent point sources. This may have implications for expected ecological status and recovery in these catchments, which appeared more at risk in catchments with little buffering in terms of summer base flow dilution. Wetter winters and drier summers under climate change scenarios would likely increase stream P concentrations both during storms and during baseflows and would be particularly magnified in those catchments with flashy runoff and suppressed baseflow. These seasonal insights into source-to-delivery functions and risk (re)assessment were only possible with high resolution (spatial and temporal) data collection and will be important in influencing expectations of policies that are evaluated at larger scales but with coarser resolution sampling. PMID:22425173

  1. Alpine cloud climatology using long-term NOAA-AVHRR satellite data

    NASA Astrophysics Data System (ADS)

    Kästner, M.; Kriebel, K. T.

    Three different climates have been identified by our evaluation of AVHRR (Advanced Very High Resolution Radiometer) data using APOLLO (AVHRR Processing scheme Over Land, Clouds and Ocean) for a five-years cloud climatology of the Alpine region. The cloud cover data from four layers were spatially averaged in boxes of 15km by 14km. The study area only covers 540km by 560km, but contains regions with moderate, Alpine and Mediterranean climate. Data from the period July 1989 until December 1996 have been considered. The temporal resolution is one scene per day, the early afternoon pass, yielding monthly means of satellite derived cloud coverages 5% to 10% above the daily mean compared to conventional surface observation. At non-vegetated sites the cloudiness is sometimes significantly overestimated. Averaging high resolution cloud data seems to be superior to low resolution measurements of cloud properties and averaging is favourable in topographical homogeneous regions only. The annual course of cloud cover reveals typical regional features as foehn or temporal singularities as the so-called Christmas thaw. The cloud cover maps in spatially high resolution show local luff/lee features which outline the orography. Less cloud cover is found over the Alps than over the forelands in winter, an accumulation of thick cirrus is found over the High Alps and an accumulation of thin cirrus north of the Alps.

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

    NASA Astrophysics Data System (ADS)

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

    2004-02-01

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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. [Community structure and seasonal change of soil micro-arthropodes in the Lower Reaches of Liaohe River Plain under different land utilization].

    PubMed

    Ke, Xin; Liang, Wenju; Yu, Wantai; Xie, Rongdong; Weng, Chaolian; Yang, Yiming; Yin, Wenying

    2004-04-01

    The data on the soil micro-arthropodes under four land utilization types (fallow, forest, upland field and paddy) in the Lower Reaches of Liaohe River Plain were collected in a period from October 2000 to October 2001. Using the community parameters of population density, group richness, diversity index and evenness, the community structure and its seasonal changes were described. There were 12 groups of soil micro-arthropodes in this region, and of the groups, Collembola and Acarina were dominant, and Diptera, Coleoptera and Hymenoptera were often seen in fallow, forest and upland field, while Collembola, Acarina and Diptera were dominant in paddy. Both land utilization and seasonal change influenced the population density, group richness and diversity index of soil micro-arthropodes. The vertical distribution in both density and group number of arthropods in soil was in the order of surface > middle > bottom.

  12. Transition of the Large-Scale Atmospheric and Land Surface Conditions from the Dry to the Wet Season over Amazonia as Diagnosed by the ECMWF Re-Analysis.

    NASA Astrophysics Data System (ADS)

    Li, Wenhong; Fu, Rong

    2004-07-01

    Using 15-yr instantaneous European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA) data, the authors have examined the large-scale atmospheric conditions and the local surface fluxes through the transition periods from the dry to wet seasons over the southern Amazon region (5° 15°S, 45° 75°W). The composite results suggest that the transition can be divided into three phases: initiating, developing, and mature. The initiating phase is dominated by the local buildup of the available potential energy. This begins about 90 days prior to the onset of the wet season by the increase of local land surface fluxes, especially latent heat flux, which increases the available potential energy of the lower troposphere. The cross-equatorial flow and upper-tropospheric circulation remain unchanged from those of the dry season. The developing phase is dominated by the seasonal transition of the large-scale circulation, which accelerates by dynamic feedbacks to an increase of locally thermal-driven rainfall, starting about 45 days before the onset of the wet season. During this stage, the reversal of the low-level, cross-equatorial flow in the western Amazon increases moisture transport from the tropical Atlantic Ocean and leads to net moisture convergence in the southern Amazon region. In the upper troposphere, the divergent kinetic energy begins to be converted into rotational kinetic energy, and geopotential height increases rapidly. These processes lead to the onset of the wet season and the increase of anticyclonic vorticity at the upper troposphere. After onset, the lower-tropospheric potential energy reaches equilibrium, but the conversion from divergent to rotational kinetic energy continues to spin up the upper-tropospheric anticyclonic circulation associated with the Bolivian high until it reaches its full strength.This analysis suggests that a weaker (stronger) increase of land surface latent (sensible) heat flux during the dry season and the initiating

  13. 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.

  14. Analysis of smoke and cloud impact on seasonal and interannual variations in normalized difference vegetation index in Amazon

    NASA Astrophysics Data System (ADS)

    Kobayashi, H.; Dye, D. G.

    2004-12-01

    Normalized difference vegetation index (NDVI) derived from National Oceanic and Atmospheric Administration (NOAA)/Advanced Very High Resolution Radiometer (AVHRR) is a unique measurement of long-term variations in global vegetation dynamics. The NDVI data have been used for the detection of the seasonal and interannual variations in vegetation. However, as reported in several studies, NDVI decreases with the increase in clouds and/or smoke aerosol contaminated in the pixels. This study assesses the smoke and clouds effect on long-term Global Inventory Modeling and Mapping Studies (GIMMS) and Pathfinder AVHRR Land (PAL) NDVI data in Amazon. This knowledge will help developing the correction method in the tropics in the future. To assess the smoke and cloud effects on GIMMS and PAL, we used another satellite-derived data sets; NDVI derived from SPOT/VEGETATION (VGT) data and Aerosol Index (AI) derived from Total Ozone Mapping Spectrometer (TOMS). Since April 1998, VGT has measured the earth surface globally including in Amazon. The advantage of the VGT is that it has blue channel where the smoke and cloud can be easily detected. By analyzing the VGT NDVI and comparing with the AVHRR-based NDVI, we inferred smoke and cloud effect on the AVHRR-based NDVI. From the results of the VGT analysis, we found the large NDVI seasonality in South and Southeastern Amazon. In these areas, the NDVI gradually increased from April to July and decreased from August to October. However the sufficient NDVI data were not existed from August to November when the smoke and cloud pixels were masked using blue reflectance. Thus it is said that the smoke and clouds mainly cause the large decreases in NDVI between August and November and NDVI has little vegetation signature in these months. Also we examined the interannual variations in NDVI and smoke aerosol. Then the decrease in NDVI is well consistent with the increase in the increase in AI. Our results suggest that the months between April

  15. 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.

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

    NASA Astrophysics Data System (ADS)

    Pinzon, J. E.

    2015-12-01

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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

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

    NASA Astrophysics Data System (ADS)

    Kazadi, S.; Yoshikawa, S.

    2007-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  4. The water balance of two semi-arid shrubs on abandoned land in South-Eastern Spain after cold season rainfall

    NASA Astrophysics Data System (ADS)

    Archer, N.; Hess, T.; Quinton, J.

    The inland, mountainous marginal areas (land abandoned by farming and colonised by shrubs) of the Iberian Peninsular, Spain, generally receive a higher rainfall than the coastal areas (Lazaro and Rey, 1991) and may store water after cold season (autumn and winter) rainfall. By measuring runoff, change of soil water content and rainfall, this study tests the hypothesis that two shrubs on two sites on abandoned land do not use all the water available after cold season rainfall. One site was on an upper alluvial slope dominated by Anthyllis cytisoides and the other on a lower alluvial slope dominated by Retama sphaerocarpa. The root systems of A. cytisoides and R. sphaerocarpa penetrate to 3 m and 20 m, respectively. A. cytisoides senesces during the dry season and R. sphaerocarpa is evergreen. The water balance is dominated by high actual evapotranspiration (ET), which is limited by rainfall. Reference evapotranspiration was high; runoff was low and soil water storage occurred above 2 m depth. ET and water storage were highest under A. cytisoides shrubs. Runoff was lower on the ‘Anthyllis’ site. The spatial variability of soil water is high and the problems of its measurement are discussed. The quantity of rainfall infiltrated was greater under shrubs than grass-areas, suggesting that shrub roots facilitated preferential flow. The growing season of A. cytisoides began when water was available in the upper soil layers and senescence occurred when the upper soil layers dried to less than 4% water content. A. cytisoides, therefore, relies on water from these layers. The main growth of R. sphaerocarpa occurred when the upper soil layers were relatively dry, so that R. sphaerocarpa must extract water from deeper layers. Results suggest that A. cytisoides accumulates rainfall and runoff and directs water to lower layers for later use, while R. sphaerocarpa extracts water from deeper soil layers. By mid-summer both shrubs had extracted all the available water

  5. 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.

  6. 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).

  7. 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.

  8. 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.

  9. 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.

  10. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1993-01-01

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

  12. 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.

  13. Responses of seasonal and diurnal soil CO2 effluxes to land-use change from paddy fields to Lei bamboo (Phyllostachys praecox) stands

    NASA Astrophysics Data System (ADS)

    Zhang, Tao; Li, Yongfu; Chang, Scott X.; Jiang, Peikun; Zhou, Guomo; Zhang, Jiaojiao; Liu, Juan

    2013-10-01

    Land-use change often markedly alters soil carbon (C) dynamics such as soil surface CO2 efflux. This study aims to test the hypotheses that converting paddy fields to bamboo stands would markedly reduce soil CO2 efflux and their temperature sensitivity (change of soil CO2 efflux rate by increasing 10 °C of temperature), and change the relationship between soil CO2 efflux and other environmental factors. A 12-month field study was conducted to measure the seasonal and diurnal soil CO2 effluxes in three adjacent paddy field-bamboo forest pairs with the automated soil CO2 flux system (LI-8100). Results showed that soil CO2 effluxes from both of the two land-uses had distinct seasonal patterns, and were reduced from 45.4 to 34.7 t CO2 ha-1 yr-1 in cumulative CO2 emissions when paddy fields were converted to bamboo stands. About 80% of the variation in soil respiration in the bamboo stands was explained by soil temperature; however, a positive relationship between soil CO2 efflux and soil temperature in the paddy field was observed only when the soil was not submerged under water, indicating that soil water saturation in the paddy fields altered the soil CO2 efflux-temperature relationship. A negative relationship (P < 0.01) between soil CO2 efflux and soil moisture was observed in the paddy fields, while no such relationship was observed in the bamboo stands. The apparent temperature sensitivity of soil respiration (Q10) was dependent on the depth of the soil temperature measurement and was increased by converting paddy fields to bamboo stands, rejecting the hypothesis. In Lei bamboo stands, the R2 for the soil respiration-temperature regression was higher using seasonal and diurnal CO2 efflux data together than using the seasonal data alone. We conclude that the conversion of paddy fields to Lei bamboo stands decreased the annual soil CO2 efflux but increased its temperature sensitivity, and altered the relationship between soil respiration and soil moisture. When

  14. 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.

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

    SciTech Connect

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

    1993-06-01

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

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    USGS Publications Warehouse

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

    2003-01-01

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

  19. 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.

  20. 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.

  1. 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.

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

    NASA Astrophysics Data System (ADS)

    Li, Xiaolan; Zhang, Hongsheng

    2012-12-01

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

  3. 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.

  4. 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.

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

    NASA Technical Reports Server (NTRS)

    Strub, P. Ted; Chelton, Dudley B.

    1990-01-01

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

  6. 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.

  7. Lossless compression of NOAA-AVHRR satellite data

    NASA Technical Reports Server (NTRS)

    Takamura, Seishi; Takagi, Mikio

    1994-01-01

    A high-performance lossless compression system for satellite NOAA data is developed. The data is called 'high resolution picture transmission' (HRPT) data, and consists of around 93 percent advanced very high resolution radiometer (AVHRR) multi-channel image data and 7 percent of miscellaneous data. In compressing the image portion, we classify each pixel into 10 different groups and apply a multi-channel prediction and a non-linear error conversion. The entropy coder is an arithmetic coder which is adaptive and regenerates the approximation of the statistical properties of the source as an initial probability table. To compress the non-image part, we used the general compressor (gzip). From experimental results, the original information is compressed down to 25 percent to approx. 40 percent.

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  9. 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

  10. 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

  11. 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

  12. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  14. [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.

  15. [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. PMID:20077694

  16. 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

  17. 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

  18. 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

  19. 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

  20. Combination of MODIS Snow, Cloud and Land Spatial Coverage Data with SNOTEL to Generate Inter-Annual and Within-Season Snow Depletion Curves and Maps

    NASA Astrophysics Data System (ADS)

    Qualls, R. J.; Arogundade, A. B.

    2015-12-01

    Quantification of spatial coverage of snow and its temporal decline throughout the snowmelt season is an important input for snowmelt runoff models in the prediction of runoff and simulation of streamflow. Several remote sensing methods of snow cover mapping exist today with differing spatial and temporal resolutions that can be used in determining the progressive reduction of snow cover during snowmelt. The Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite sensor has provided global coverage with daily temporal resolution and a spatial resolution on the order of 1 km2 since the year 2000. Several challenges hinder the development and routine use of MODIS snow covered area products, which include cloud and forest obscuration of snow-covered surfaces. Furthermore, the relatively recent launch of the MODIS sensor prevents its direct use in historical or future (e.g., climate change scenario) studies. Based on numerous observations in the literature that snowmelt occurs in a repeating spatial pattern, albeit shifted and/or accelerated or decelerated in time, from one year to the next, a method is presented that makes use of remotely sensed MODIS snow, land and cloud data and concurrent ground-based Snow Telemetry (SNOTEL) data to construct a single, inter-annually applicable and temporally dimensionless snow depletion curve and a corresponding snow depletion map. MODIS Cloud data and ground-based SNOTEL snowfall data during the snowmelt season are used together with the inter-annual snowmelt curve/map to generate within-year snowmelt curves that account for the impact of additional melt-season snowfall. The method is successfully applied to the 9000 km2 Upper Snake River Basin in Wyoming, USA as a test case. The method may be used with historical SNOTEL data to reconstruct snow depletion curves or maps for base periods preceding the availability of current satellite remote sensing, and with synthesized weather datasets for future periods associated with

  1. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  3. 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.

  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. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. Assessing the response of seasonal variation of net primary productivity to climate using remote sensing data and geographic information system techniques in Xinjiang.

    PubMed

    Peng, Dai-Liang; Huang, Jing-Feng; Cai, Cheng-Xia; Deng, Rui; Xu, Jun-Feng

    2008-12-01

    Net primary productivity (NPP) is a key component of energy and matter transformation in the terrestrial ecosystem, and the responses of NPP to global change locally and regionally have been one of the most important aspects in climate-vegetation relationship studies. In order to isolate causal climatic factors, it is very important to assess the response of seasonal variation of NPP to climate. In this paper, NPP in Xinjiang was estimated by NOAA/AVHRR Normalized Difference Vegetation Index (NDVI) data and geographic information system (GIS) techniques. The impact of climatic factors (air temperature, precipitation and sunshine percentage) on seasonal variations of NPP was studied by time lag and serial correlation ageing analysis. The results showed that the NPP for different land cover types have a similar correlation with any one of the three climatic factors, and precipitation is the major climatic factor influencing the seasonal variation of NPP in Xinjiang. It was found that the positive correlation at 0 lag appeared between NPP and precipitation and the serial correlation ageing was 0 d in most areas of Xinjiang, which indicated that the response of NPP to precipitation was immediate. However, NPP of different land cover types showed significant positive correlation at 2 month lag with air temperature, and the impact of which could persist 1 month as a whole. No correlation was found between NPP and sunshine percentage.

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

    USGS Publications Warehouse

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

    1997-01-01

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

  12. 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.

  13. 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.

  14. Ten years of monitoring areal snowpack in the Southern Alps using NOAA-AVHRR imagery, ground measurements and hydrological data

    NASA Astrophysics Data System (ADS)

    Ranzi, R.; Grossi, G.; Bacchi, B.

    1999-09-01

    Monitoring snow cover in alpine areas is important for the estimation of the water storage during the snowmelt season, especially in view of irrigation, hydropower production and water supply. Cost-efficiency and fine temporal resolution of images from the satellite-borne NOAA-AVHRR sensor indicate this source of information as a suitable candidate for monitoring snow cover extent. This information can also be used for validation of distributed snowmelt models. As a result of a long-term study, ten years of snow covered area depletion curves have been estimated using remote sensing in seven watersheds of size larger than 400 km2 in the Southern Alps.Coupling of satellite imagery with detailed topographic data and some ground measurements of snowpack depth and density provides regional estimates of snow water equivalent in northern Italy, upstream of Lakes Maggiore, Como, Iseo, Idro, and Garda. The basin water equivalent estimates are compared with the values obtained from the hydrological water balance equation used in two of the selected watersheds and computed for different snowmelt seasons.

  15. 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.

  16. Stress activated protein kinases, JNKs and p38 MAPK, are differentially activated in ganglia and heart of land snail Helix lucorum (L.) during seasonal hibernation and arousal.

    PubMed

    Michaelidis, Basile; Hatzikamari, Maria; Antoniou, Vassiliki; Anestis, Andreas; Lazou, Antigone

    2009-06-01

    The present work aimed to investigate the phosphorylation and hence activation of stress activated protein kinases, p38 MAPK and JNKs in the tissues of the snail Helix lucorum during seasonal hibernation. Snails were put in large glass boxes, which were placed outdoors so that they were exposed to natural conditions of light and temperature. Phosphorylation and hence activation of JNKs and p38 MAPK was determined in both heart and ganglia. Deep hibernation caused significant increases in the levels of the phosphorylated form of JNK and p38-MAPK in both heart and ganglia. Phosphorylation of JNK remained elevated in the ganglia or increased after a transient drop in the heart, when the snails were prepared for arousal. In addition, phosphorylation of p38-MAPK was further increased in the heart during this period. These data support the conclusion that MAPK signalling cascade might contribute in the physiological and biochemical remodelling in the tissues of land snails during hibernation and upon preparation for arousal.

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. Dependence of NOAA-AVHRR recorded radiance on scan angle, atmospheric turbidity and unresolved cloud

    NASA Technical Reports Server (NTRS)

    Piwinski, D. J.; Schoch, L. B.; Duggin, M. J.; Whitehead, V.; Ryland, E.

    1984-01-01

    Experimental evidence on the scan angle and sun angle dependence of radiance recorded by the Advanced Very High Resolution Radiometer (AVHRR) devices on the NOAA-6 and NOAA-7 satellites is presented. The effects of atmospheric turbidity at various scan angles is shown, and simulations of angular anisotropy and recorded radiance are compared with the recorded digital data from the AVHRR obtained over the Great Plains area of the US. Evidence is presented on the effects of unresolved cloud on the recorded radiance and vegetative indices from uniform, vegetative targets.

  2. 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

  3. 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.

  4. 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

  5. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  7. 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…

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1987-01-01

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

  14. 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

  15. 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.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

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

  18. Effects of viewing geometry on AVHRR observations of volcanic thermal anomalies

    SciTech Connect

    Mouginis-Mark, P.J.; Garbeil, H.; Flament, P. )

    1994-04-01

    The authors investigated the influence of viewing geometry and dynamic range of the Advanced Very High Resolution Radiometer (AVHRR) sensor on detecting eruptions on poorly monitored volcanoes. Numerical models of sunwarmed flows and typical active features associated with Hawaiian eruptions (overturning lava lakes, surface flows of three different sizes, and lava tubes with skylights) show that new lava flows at [approximately]1,000 C can be identified at all scan angles if the area of the activity exceeds [approximately]60 m[sup 2] given a background temperature of 20 C. More difficult is the detection of small breakouts of lava flows or tube-fed flows when these features lie towards the edge of the swath; because of the dynamic range and gain setting of the sensor (Bands 3, 4, and 5 saturate at [approximately] 49 C) it is possible that similar thermal signatures may be produced when inactive flows are heated by the Sun. The ability of the AVHRR to detect on-going activity in Hawaii in July 1991 is tested by comparing Landsat Thematic Mapper and nadir AVHRR scenes obtained within [approximately] 3.5 hours of each other. For an active pahoehoe flowfield with a well-developed tube system, this comparison shows that within the area of thermally alarmed AVHRR pixels < 5 % of the TM midinfrared pixels had elevated data values, indicating the relatively small size of the surface activity. An off-nadir AVHRR scene acquired 47.5 h later is used to illustrate the effect of increased pixel size when viewing subpixel hot spots.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  20. 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.)

  1. 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.

  2. 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

  3. 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.

  4. 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.

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

    PubMed

    González-Pedraza, Ana Francisca; Dezzeo, Nelda

    2014-01-01

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

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

    PubMed Central

    González-Pedraza, Ana Francisca; Dezzeo, Nelda

    2014-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2007-01-01

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

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Vegetation assessment using a combination of visible, near-IR and thermal-IR AVHRR data

    NASA Technical Reports Server (NTRS)

    Whitehead, V. S.; Johnson, W.; Boatright, J.

    1985-01-01

    Twelve hour temperature difference (thermal inertia) maps generated by rectifying and registering ascending (day) passes and descending (night) passes of the NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) are compared to vegetation index maps generated from the visible and near IR data from the day pass of that satellite. There appears to be significant and unique information concerning surface characteristics in the temperature difference data on the 1 km scale of the AVHRR. A scatter diagram is provided which shows the pattern of day-night temperature difference compared to vegetation index for irrigated agriculture, dry rangeland, lakes, wet areas and burned rangeland. A detailed description of the techniques employed to provide the day-night temperature maps is provided.

  18. Vegetation assessment using a combination of visible, near-IR, and thermal-IR AVHRR data

    NASA Technical Reports Server (NTRS)

    Whitehead, V. S.; Johnson, W. R.; Boatright, J. A.

    1986-01-01

    Twelve-hour temperature difference (thermal inertia) maps generated by rectifying and registering ascending (day) passes and descending (night) passes of the NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) are compared to vegetation index maps generated from the visible and near IR data from the day pass of that satellite. There appears to be significant and unique information concerning surface characteristics in the temperature difference data on the 1-km scale of the AVHRR. A scatter diagram is provided which shows the pattern of day-night temperature difference compared to vegetation index for irrigated agriculture, dry rangeland, lakes, wet areas and burned rangeland. A detailed description of the techniques employed to provide the day-night temperature maps is provided.

  19. 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).

  20. Cloud properties from the analysis of AVHRR observations for FIRE 2

    NASA Technical Reports Server (NTRS)

    Lin, Xijian; Coakley, James A., Jr.

    1993-01-01

    Preliminary results are presented for cloud properties from the analysis of AVHRR observations for FIRE 2. The properties were obtained from a combination of the spatial coherence method and a multispectral retrieval scheme. Geographically gritted fields for the number of cloud layers were produced. For single layered cloud systems, fractional cloud cover, cloud emission temperature, cloud emissivity, and particle size were retrieved. Statistics on the properties of upper-level clouds and the Coffeeville cloud conditions are presented.

  1. 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.

  2. 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.

  3. 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.

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

    NASA Technical Reports Server (NTRS)

    Becker, F.

    1987-01-01

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

  5. 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.

  6. 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.

  7. 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.

  8. Seasonal changes of CO(2), CH(4) and N(2)O fluxes in relation to land-use change in tropical peatlands located in coastal area of South Kalimantan.

    PubMed

    Inubushi, K; Furukawa, Y; Hadi, A; Purnomo, E; Tsuruta, H

    2003-07-01

    Tropical peatland could be a source of greenhouse gases emission because it contains large amounts of soil carbon and nitrogen. However these emissions are strongly influenced by soil moisture conditions. Tropical climate is characterized typically by wet and dry seasons. Seasonal changes in the emission of carbon dioxide (CO(2)), methane (CH(4)) and nitrous oxide (N(2)O) were investigated over a year at three sites (secondary forest, paddy field and upland field) in the tropical peatland in South Kalimantan, Indonesia. The amount of these gases emitted from the fields varied widely according to the seasonal pattern of precipitation, especially methane emission rates were positively correlated with precipitation. Converting from secondary forest peatland to paddy field tended to increase annual emissions of CO(2) and CH(4) to the atmosphere (from 1.2 to 1.5 kg CO(2)-C m(-2)y(-1) and from 1.2 to 1.9 g CH(4)-C m(-2)y(-1)), while changing land-use from secondary forest to upland tended to decrease these gases emissions (from 1.2 to 1.0 kg CO(2)-C m(-2)y(-1) and from 1.2 to 0.6 g CH(4)-C m(-2)y(-1)), but no clear trend was observed for N(2)O which kept negative value as annual rates at three sites. PMID:12738298

  9. 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.

  10. 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. PMID:19637703

  11. 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

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

    NASA Astrophysics Data System (ADS)

    Caliskan, S.; de Beurs, K.

    2010-12-01

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

  13. Development of a land-cover characteristics database for the conterminous US

    USGS Publications Warehouse

    Loveland, T.R.; Merchant, J.W.; Ohlen, D.O.; Brown, J.F.

    1991-01-01

    Information regarding the characteristics and spatial distribution of the Earth's land cover is critical to global environmental research. A prototype land-cover database for the conterminous United States designed for use in a variety of global modelling, monitoring, mapping, and analytical endeavors has been created. The resultant database contains multiple layers, including the source AVHRR data, the ancillary data layers, the land-cover regions defined by the research, and translation tables linking the regions to other land classification schema (for example, UNESCO, USGS Anderson System). The land-cover characteristics database can be analyzed, transformed, or aggregated by users to meet a broad spectrum of requirements. -from Authors

  14. 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.

  15. 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

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

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

    Study of the environment has historically been done with observations and measurements in relatively few local areas. While some of these have been done over long time spans, most have not. The NOAA/NASA Pathfinder project was initiated to complement these data sets with satellite data that can provide information over larger spatial areas and longer time spans. The AVHRR Polar Pathfinder (APR) program was part of this project. The APR was to supply data from the NOAA AVHRR instruments that was consistently generated in a format usable to a wide range of scientific investigators. A grant was obtained from the NASA Research Announcement 97-MTPE-03 to evaluate the APP products, to provide any enhancements, and to compare with products from the new MODIS instrument. There was about a two year overlap between the projects, and this validation effort had several impacts on the APP products. The APP products are derived from the instruments aboard 4 NOAA satellites, NOAA-7, 9, 11, and 14. Initial validation efforts compared the thermal calibrations of these instruments, and differences are found. Calibration has undergone many revisions and techniques have changed since the satellites were launched. The first calibration methods were optimized for global ocean temperatures, as this was one of the primary and important uses of the AVHRR instruments. As the APP program started, newer methods that provided more accurate temperature retrievals over a wider range of temperatures were being developed. The calibration of a wider range of temperatures were necessary because of the extremely low values in the polar regions. These methods were also designed so that calibrated data was also consistent between all the NOAA satellites. These newer calibration methods were then adopted primarily because of the initial finding of this validation effort.

  17. 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.

  18. 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

  19. 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

  20. Application of NDVI to detecting algal bloom in the Bohai Sea of China from AVHRR

    NASA Astrophysics Data System (ADS)

    Zhao, Dongzhi

    2003-05-01

    This paper analyses the relation between data measured in situ and the NDVI derived from AVHRR of NOAA-14 during algal bloom in the Bohai sea in 1998 to establish surface biomass model of Ceratium furca(EHr.). This model is easy to utilize data received from multi-source satellite in operation, and gets directly the index of phytoplankton biomass. The area and distribution of high biomass is also presented. Based on this model, propagation speed of phytoplankton reveals progress of algal bloom development. The result of this model can discriminate algal bloom water from silt or suspended particle material (SPM).

  1. 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.

  2. 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.

  3. AVHRR-based vegetation and temperature condition indices for drought detection in Argentina

    NASA Astrophysics Data System (ADS)

    Seiler, R. A.; Kogan, F.; Sullivan, J.

    The AVHRR-based Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) have been developed and successfully used for monitoring drought in the USA., the Former Soviet Union, Zimbabwe, and China. This research was designed to apply and validate those indices for drought detection and impact assessment on agricultural yields in Cordoba province of Argentina. Seventy one percent of corn yield variability was explained by the spectral indices averaged over January and February. The VCI and TCI were useful to assess the spatial characteristics, the duration and severity of drought, and were in a good agreement with precipitation patterns.

  4. 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

  5. Directional reflectance response in AVHRR red and near-IR bands for three cover types and varying atmospheric conditions

    NASA Technical Reports Server (NTRS)

    Holben, B.; Kimes, D.; Fraser, R. S.

    1986-01-01

    Surface directional red and near-infrared reflectances of bare soil, orchard grass, and fescue were extracted from a multitemporal data set to correspond to NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) scanning and illumination geometry at 30 deg latitude. Radiances were simulated at satellite altitude and a ratio vegetation index was calculated. The results show that off-nadir directional reflectance measured at the surface in the red and near-IR portions of the spectrum are approximately maintained with AVHRR viewing and illumination characteristics. The two-channel reflectance response is such that the ratio vegetation index is more constant with scan angle and atmospheric conditions than individual channels. It is shown that inclusion of atmospheric and surface reflectance data can greatly improve interpretation of AVHRR data, when knowledge of the range of atmospheric conditions and approximate directional reflectances of major cover types are known.

  6. 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.

  7. Using CEOS reference standard test sites to track the calibration stability of NOAA-19 AVHRR reflective solar channels

    NASA Astrophysics Data System (ADS)

    Wu, Aisheng; Angal, Amit; Xiong, Jack; Cao, Changyong

    2010-10-01

    In recent years, there is an increasing interest to establish a global integrated network of calibration sites for the purpose of tracking sensor performance, conducting cross-sensor comparison and assessing data quality and consistency. Based on such a need, the Committee on Earth Observation Satellites (CEOS) proposed eight instrumented sites for which surface measurements can be acquired through field campaigns and five pseudo-invariant desert sites typically consisting of sand dunes. In this study, we select one site from each category to study the calibration stability of reflective solar channels of NOAA- 19 Advanced Very High Resolution Radiometer (AVHRR) (launched on February 6, 2009). Since AVHRR does not have an onboard calibrator for the reflective solar channels and vicarious calibration often needs long-term observations to derive reliable trends, this study will provide an early assessment of sensor on-orbit calibration performance and establish a preliminary trend to examine its calibration consistency with other sensors. The Antarctic Dome C site is selected primarily to monitor the on-orbit calibration performance whereas Libya 4 test site is used to evaluate the cross-calibration consistency of AVHRR with other sensors. A site-specific Bi-directional Reflectance Distribution Function (BRDF) model developed based on observations made by Moderate Resolution Imaging Spectroradiometer (MODIS) is used to normalize AVHRR observed Top-of-Atmosphere (TOA) reflectances. Impact due to calibration applied to NOAA-19 AVHRR L1B is assessed separately using a constant detector response. Results show that for NOAA-19 AVHRR solar channels 1 and 2, variations in reflectance during the first year after launch are still around 6% and more than 10%, respectively, either due to sensor change or improper adjustment of calibration coefficients. While two sites provide consistent trends for the visible channel, the Dome C site is more suitable for the near

  8. Future Landing Capabilities of the Mars 2020 Entry, Descent, and Landing System

    NASA Astrophysics Data System (ADS)

    Kipp, K. A.; Hines, E. K.; Chen, A.

    2014-06-01

    This study examines landing site elevation capability as a function of landing season, for a future mission using the heritage MSL/Mars 2020 EDL system. Results are presented for a 1200kg landed mass with different parachute technology assumptions.

  9. 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.

  10. Assessing the trends and effects of environmental parameters on the behaviour of mercury in the lower atmosphere over cropped land over four seasons

    NASA Astrophysics Data System (ADS)

    Baya, A. P.; van Heyst, B.

    2010-09-01

    Mercury is released to the atmosphere from natural and anthropogenic sources. Due to its persistence in the atmosphere, mercury is subject to long range transport and is thus a pollutant of global concern. Mercury emitted to the atmosphere enters terrestrial and aquatic ecosystems which act as sinks but also as sources of previously emitted and deposited mercury when the accumulated mercury is emitted back to the atmosphere. Studying the factors and processes that influence the behaviour of mercury from terrestrial sources is thus important for a better understanding of the role of natural ecosystems in the mercury cycling and emission budget. A study was conducted over ten months (November 2006 to August 2007) at Elora, Ontario, Canada to measure gaseous elemental mercury (GEM), reactive gaseous mercury (RGM) and particulate bound mercury (HgP) as well as GEM fluxes over different ground cover spanning the four seasons typical of a temperate climate zone. GEM concentrations were measured using a mercury vapour analyzer (Tekran 2537A) while RGM and HgP were measured with the Tekran 1130/1135 speciation unit coupled to another mercury vapour analyzer. A micrometeorological approach was used for GEM flux determination using a continuous two-level sampling system for GEM concentration gradient measurement above the soil surface and crop canopy. The turbulent transfer coefficients were derived from meteorological parameters measured on site. A net GEM volatilization (6.31 ± 33.98 ng mM-2 hr-1, study average) to the atmosphere was observed. Average GEM concentrations and GEM fluxes showed significant seasonal differences and distinct diurnal patterns while no trends were observed for HgP or RGM. Highest GEM concentrations, recorded in late spring and fall, were due to meteorological changes such as increases in net radiation and air temperature in spring and lower atmospheric mixing height in fall. Highest GEM fluxes (18.1 ng m-2 hr-1, monthly average) were recorded in

  11. Assessing the trends and effects of environmental parameters on the behavior of mercury in the lower atmosphere over cropped land over four seasons

    NASA Astrophysics Data System (ADS)

    Baya, A. P.; van Heyst, B.

    2010-02-01

    Mercury is released to the atmosphere from natural and anthropogenic sources. Due to its persistence in the atmosphere, mercury is subject to long range transport and is thus a pollutant of global concern. The terrestrial ecosystem is an important atmospheric mercury sink as a significant portion of the mercury emitted can be accumulated on soil surfaces making terrestrial surfaces an important source of previously emitted and deposited mercury. Studying the factors and processes that influence the behavior of mercury from terrestrial sources is thus important for a better understanding of the role of natural ecosystems in the mercury cycling and emission budget. A one year study (July 2006-August 2007) was conducted at Elora, Ontario, Canada to measure total gaseous mercury (TGM), reactive gaseous mercury (RGM) and particulate bound mercury (HgP) as well as TGM fluxes over different ground cover spanning the four seasons typical of a temperate climate zone. TGM concentrations were measured using a mercury vapour analyzer (Tekran 2537A) while RGM and HgP were measured with the Tekran 1130/1135 speciation unit coupled to another mercury vapour analyzer. A micrometeorological approach was used for TGM flux determination using a continuous two-level sampling system for TGM concentration gradient measurement above the soil surface and crop canopy. The turbulent transfer coefficients were derived from meteorological parameters measured on site. A net TGM volatilization (6.31±33.98 ng m-2 h-1, annual average) to the atmosphere was observed during the study. Average TGM concentrations and TGM fluxes showed significant seasonal differences and distinct diurnal patterns while no trends were observed for HgP or RGM. Highest TGM concentrations recorded in late spring and fall were due to meteorological changes such as increases in net radiation and air temperature in spring and lower atmospheric mixing height in fall. Highest TGM fluxes (18.1 ng m-2 h-1, monthly average

  12. 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.

  13. Classification of satellite time series-derived land surface phenology focused on the northern Fertile Crescent

    NASA Astrophysics Data System (ADS)

    Bunker, Brian

    Land surface phenology describes events in a seasonal vegetation cycle and can be used in a variety of applications from predicting onset of future drought conditions, to revealing potential limits of historical dry farming, to guiding more accurate dating of archeological sites. Traditional methods of monitoring vegetation phenology use data collected in situ. However, vegetation health indices derived from satellite remote sensor data, such as the normalized difference vegetation index (NDVI), have been used as proxy for vegetation phenology due to their repeated acquisition and broad area coverage. Land surface phenology is accessible in the NDVI satellite record when images are processed to be intercomparable over time and temporally ordered to create a time series. This study utilized NDVI time series to classify areas of similar vegetation phenology in the northern Fertile Crescent, an area from the middle Mediterranean coast to southern/south-eastern Turkey to western Iran and northern Iraq. Phenological monitoring of the northern Fertile Crescent is critical due to the area's minimal water resources, susceptibility to drought, and understanding ancient historical reliance on precipitation for subsistence dry farming. Delineation of phenological classes provides areal and temporal synopsis of vegetation productivity time series. Phenological classes were developed from NDVI time series calculated from NOAA's Advanced Very High Resolution Radiometer (AVHRR) imagery with 8 × 8 km spatial resolution over twenty-five years, and by NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) with 250 × 250 m spatial resolution over twelve years. Both AVHRR and MODIS time series were subjected to data reduction techniques in spatial and temporal dimensions. Optimized ISODATA clusters were developed for both of these data reduction techniques in order to compare the effects of spatial versus temporal aggregation. Within the northern Fertile Crescent study area

  14. 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

  15. SeaShark and Starfish opertional data processing schemes for AVHRR and SeaWiFs

    NASA Astrophysics Data System (ADS)

    Flowerdew, R. J.; Corlyon, Anaa M.; Greer, W. A. D.; Newby, Steve J.; Winder, C. P.

    1997-02-01

    SeaShark is an operational software package for processing, archiving and cataloguing AVHRR and SeaWiFS data using an operator friendly GUI. Upon receipt of a customer order, it produces standard AVHRR data products, including Sea Surface Temperature (SST) and it has recently been modified to include SeaWiFS level 2 data processing. This uses an atmospheric correction scheme developed by the Plymouth Marine Laboratory, UK (PML) that builds upon the standard Gordon and Wang approach to be applicable over both case 1 and case 2 waters. Higher level products are then generated using PML algorithms, including chlorophyll a, a CZCS-type pigment, Kd, and suspended particulate matter. Outputs are in CEOS-compatible format. The software also produces fast delivery products (FDPs) of chlorophyll a and SST. These FDPs are combined in the StarFish software package to provide maps indicating potential location of phytoplankton and the preferred thermal environment of certain pelagic fish species. Fishing vessels may obtain these maps over Inmarsat, allowing them to achieve a greater efficiency hence lower cost.

  16. Comparison between AVHRR surface temperature data and in-situ weather station temperatures over the Greenland Ice Sheet

    NASA Astrophysics Data System (ADS)

    Rezvanbehbahani, S.; Csatho, B. M.; Comiso, J. C.; Babonis, G. S.

    2011-12-01

    Advanced Very-High Resolution Radiometer (AVHRR) images have been exhaustively used to measure surface temperature time series of the Greenland Ice sheet. The purpose of this study is to assess the accuracy of monthly average ice sheet surface temperatures, derived from thermal infrared AVHRR satellite imagery on a 6.25 km grid. In-situ temperature data sets are from the Greenland Collection Network (GC-Net). GC-Net stations comprise sensors monitoring air temperature at 1 and 2 meter above the snow surface, gathered at every 60 seconds and monthly averaged to match the AVHRR temporal resolution. Our preliminary results confirm the good agreement between satellite and in-situ temperature measurements reported by previous studies. However, some large discrepancies still exist. While AVHRR provides ice surface temperature, in-situ stations measure air temperatures at different elevations above the snow surface. Since most in-situ data on ice sheets are collected by Automatic Weather Station (AWS) instruments, it is important to characterize the difference between surface and air temperatures. Therefore, we compared and analyzed average monthly AVHRR ice surface temperatures using data collected in 2002. Differences between these temperatures correlate with in-situ temperatures and GC-Net station elevations, with increasing differences at lower elevations and higher temperatures. The Summit Station (3199 m above sea level) and the Swiss Camp (1176 m above sea level) results were compared as high altitude and low altitude stations for 2002, respectively. Our results show that AVHRR derived temperatures were 0.5°K warmer than AWS temperature at the Summit Station, while this difference was 2.8°K in the opposite direction for the Swiss Camp with surface temperatures being lower than air temperatures. The positive bias of 0.5°K at the high altitude Summit Station (surface warmer than air) is within the retrieval error of AVHRR temperatures and might be in part due to

  17. Sea ice motions in the central arctic ice central arctic pack ice as inferred from AVHRR imagery

    NASA Technical Reports Server (NTRS)

    Emery, William; Maslanik, James; Fowler, Charles

    1993-01-01

    Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoy data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Merging the remotely-sensed ice motions with SAR, AVHRR, OLS, and SSM/I imagery permits studies of ice processes over a range of space and time scales. A medium-resolution passive microwave sensor might be ideal for this purpose, but no such satellite will be available in the near future. Combinations of existing data types are thus likely to be our best bet for generating motion fields with a coverage and resolution best suited to climate studies. Principal objectives of this project are to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions.

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

    USGS Publications Warehouse

    Eldenshink, J.

    2006-01-01

    The U.S. Geological Survey (USGS) has developed a 16-year time series of vegetation condition information for the conterminous United States and, Alaska using 1 km Advanced Very High Resolution Radiometer (AVHRR) data. The AVHRR data have been processed using consistent methods that account for radiometric variability due to calibration uncertainty, the effects of the atmosphere on surface radiometric measurements obtained from wide field-of-view observations, and the geometric registration accuracy. The conterminous United States and Alaska data sets have an atmospheric correction for water vapor, ozone, and Rayleigh scattering and include a cloud mask derived using the Clouds from AVHRR (CLAVR) algorithm. In comparison with other AVHRR time series data sets, the conterminous United States and Alaska data are processed using similar techniques. The primary difference is that the conterminous United States and Alaska data are at 1 km resolution, while others are at 8 km resolution. The time series consists of weekly and biweekly maximum normalized difference vegetation index (NDVI) composites. ?? 2006 American Society for Photogrammetry and Remote Sensing.

  19. 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

  20. 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.

  1. Microwave Brightness Of Land Surfaces From Outer Space

    NASA Technical Reports Server (NTRS)

    Kerr, Yann H.; Njoku, Eni G.

    1991-01-01

    Mathematical model approximates microwave radiation emitted by land surfaces traveling to microwave radiometer in outer space. Applied to measurements made by Scanning Multichannel Microwave Radiometer (SMMR). Developed for interpretation of microwave imagery of Earth to obtain distributions of various chemical, physical, and biological characteristics across its surface. Intended primarily for use in mapping moisture content of soil and fraction of Earth covered by vegetation. Advanced Very-High-Resolution Radiometer (AVHRR), provides additional information on vegetative cover, thereby making possible retrieval of soil-moisture values from SMMR measurements. Possible to monitor changes of land surface during intervals of 5 to 10 years, providing significant data for mathematical models of evolution of climate.

  2. A Satellite Time Slots Climatology of the Urban Heat Island of Guadalajara Megacity in Mexico from NOAA ¡/AVHRR THERMAL Infrared Monitoring (TIR)

    NASA Astrophysics Data System (ADS)

    Galindo, I.

    2009-04-01

    The urban heat island (UHI) of the metropolitan area of the second megacity of Mexico, named Guadalajara in Mexico is studied using thermal infrared data (TIR) (10 £ l £ 12 mm) obtained from the Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA polar orbitters whose signals are received on real time at our ground station for the period 1996-2006. The TIR data are selected by means of a software, since they depend on natural causes (e.g., atmospheric transparency, surface temperature, spectral emissivity and topography) and observational (time and incidence angle of the satellite pass, season of the year, etc.). The above conditions have a variable contribution to the measurements which it can be so high that they simulate the temporal-space fluctuations considered as thermal anomalies. Using a Geographic Information System and spatial analysis techniques temperatures are obtained for diofferent times of the day (satellite slots) and dropped into a grid with a 2.5 km distance between points (latitude, longitude). The temperatures obtained for each satellite pass slot (four per day) are monthly averaged and the temperature anomalies are represented in thermal isolines for the study area. The temperature difference usually is larger at night than during the day, reaching a thermal gradient of 9 °C.

  3. Multilevel cloud retrieval using multispectral HIRS and AVHRR data: Nighttime oceanic analysis

    NASA Technical Reports Server (NTRS)

    Baum, Bryan A.; Arduini, Robert F.; Wielicki, Bruce A.; Minnis, Patrick; Tsay, Si-Chee

    1994-01-01

    A multispectral, multiresolution (MSMR) method is developed for analyzing scenes of overlapping cloud layers. The MSMR method is applied to data from the NOAA 11 advanced very high resolution radiometer (AVHRR) and the high-resolution infrared radiometer sounder (HIRS-2). The data are from a nighttime oceanic scene in which a semitransparent cirrus veil overlays a large-scale stratus cloud. Low-cloud and clear-sky radiances are determined using a spatial coherence technique. Middle to upper level cloud pressures and radiances are estimated from HIRS-2 15 micrometer CO2 band radiometric data. The MSMR method improves the interpretation of a nighttime, oceanic scene containing thin cirrus over a large-scale stratiform cloud. If, for example, the same scene is analyzed using only the AVHRR 10.8 micrometer channel, the accompanying retrieved cloud heights are found to be between the cirrus and stratus cloud heights and are incorrectly identified as midlevel altostratus clouds. Theoretical radiative transfer model results for both water droplet spheres and randomly oriented hexagonal ice crystals are compared to observed AVHRR brightness temperature differences (BTD) between the 3.7- and 10.8 micrometer channels (BTD(sup 34)) and between the 10.8- and 12- micrometer channels (BTD(sup 45)) to distinguish among the effects of cloud optical depth, particle size, and phase for both single-layer clouds and overlapping two-layer clouds. Theoretical BTD calculations are used to estimate the range of effective particle sizes for eac h cloud layer. The data for the cirrus in the case study region near Bermuda are consistent with theoretical results for relatively small randomly oriented hexagonal ice crystals. The observed BTD(sup 34) and BTD(sup 45) values are lower for the cirrus above a lower-level cloud than for single-level cirrus with no underlying cloud. In certain cases the BTD analysis provides a way to distinguish between clouds composed of supercooled water droplets

  4. 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…

  5. Performance evaluation of Landsat 8 TIRS and the NOAA/METOP AVHRR sensors for lake surface water temperature retrieval

    NASA Astrophysics Data System (ADS)

    Lieberherr, Gian; Bur, Patrick; Wunderle, Stefan

    2016-04-01

    Lake surface water temperature (LSWT) is an important driver of lake ecosystems and it has been identified as an indicator of climate change. In-situ data for European lake water temperatures are very heterogeneous in terms of spatio-temporal coverage and retrieval methods. Satellite derived long term LSWT time series, as derived for example from the AVHRR sensor (since early 80ies), can serve as a baseline when merging different data sets. Another important advantage of satellite based temperature measurement is the representation of spatial temperature distribution within a waterbody. Focusing on spatial temperature distribution, the coarse resolutions of older sensors (1.1km for AVHRR sensor) is a limiting factor. Thus, during this study, the performance of LSWT retrieval from the TIRS sensor on the Landsat 8 platform was evaluated. The TIRS sensor has a resolution of 100m which allows to see small spatial temperature gradients, and it also offers the possibility to retrieve LSWT from smaller lakes where it was not possible with the AVHRR sensor. The temperature retrieval method used for both sensors was an optimized split window approach with lake specific and sensor specific coefficients. To validate and to evaluate the performance of the retrievals, the LSWT derived from Landsat 8 TIRS and from AVHRR where compared to each other, and also to different in-situ measurements. The accuracy of the temperature retrieval with the Landsat 8 sensor is shown to be generally better than with the AVHRR sensor. This is due to the higher resolution of the TIRS sensor, leading to lower contamination rate for individual pixels.

  6. Vegetation dynamics using AVHRR/NDVI: Regional climate, carbon dioxide fertilization and crop yield relations

    NASA Astrophysics Data System (ADS)

    Lim, Chai Kyung

    Vegetation development is closely related to climate factors, and, therefore, it is important to understand how it responds to global climate changes. For the last two decades it has been possible to monitor vegetation development at continental or global scales utilizing remote sensing Normalized Difference Vegetation Index (NDVI) data. We have developed a frequency analysis method to investigate land's vegetation greenness change and its response to the El Nino Southern Oscillation (ENSO). We found an ENSO influence on a tropical forest, southern semi-deciduous forest and a northeastern mixed forest. Our analysis shows the annual trends in vegetation greenness respond more sensitively than averaging methods. Atmospheric CO2 increase is another concern for climate change, for which fertilization effect on land vegetation has been suggested. Atmospheric CO2 and NDVI have a seasonal pattern of negative correlation, which makes it difficult to discern any positive influence of CO2 on vegetation. We adopted the concept of the rate of change in atmospheric CO2 concentration and NDVI to overcome this set pattern, and to reveal undergoing fluctuations. We found evidence that suggests a CO2 fertilization effect in some arctic and sub arctic regions and northern and inland parts of the eastern humid temperate zones in North America. Although NDVI reveals the vegetation greenness only at a fixed time and location, we have transformed NDVI effectively to describe the vegetation growth dynamics in the form of a new index, Normalized Growth Index (NGI). Utilizing NGI, we found the vegetation growth during the growing season is highly negatively correlated with the initial minimum vegetation greenness. One needs to be careful when comparing Net Primary Production (NPP) using NDVI between different types of vegetation, because the same NDVI value can imply the existence of different biomass due to different Leaf Area Index (LAI). To overcome this difficulty we have developed

  7. Some practical aspects of lossless and nearly-lossless compression of AVHRR imagery

    NASA Technical Reports Server (NTRS)

    Hogan, David B.; Miller, Chris X.; Christensen, Than Lee; Moorti, Raj

    1994-01-01

    Compression of Advanced Very high Resolution Radiometers (AVHRR) imagery operating in a lossless or nearly-lossless mode is evaluated. Several practical issues are analyzed including: variability of compression over time and among channels, rate-smoothing buffer size, multi-spectral preprocessing of data, day/night handling, and impact on key operational data applications. This analysis is based on a DPCM algorithm employing the Universal Noiseless Coder, which is a candidate for inclusion in many future remote sensing systems. It is shown that compression rates of about 2:1 (daytime) can be achieved with modest buffer sizes (less than or equal to 2.5 Mbytes) and a relatively simple multi-spectral preprocessing step.

  8. BOREAS RSS-7 Regional LAI and FPAR Images From 10-Day AVHRR-LAC Composites

    NASA Technical Reports Server (NTRS)

    Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Chen, Jing; Cihlar, Josef

    2000-01-01

    The BOReal Ecosystem-Atmosphere Study Remote Sensing Science (BOREAS RSS-7) team collected various data sets to develop and validate an algorithm to allow the retrieval of the spatial distribution of Leaf Area Index (LAI) from remotely sensed images. Advanced Very High Resolution Radiometer (AVHRR) level-4c 10-day composite Normalized Difference Vegetation Index (NDVI) images produced at CCRS were used to produce images of LAI and the Fraction of Photosynthetically Active Radiation (FPAR) absorbed by plant canopies for the three summer IFCs in 1994 across the BOREAS region. The algorithms were developed based on ground measurements and Landsat Thematic Mapper (TM) images. The data are stored in binary image format files.

  9. Monitoring Weather Impact and Crop Yield from Noaa Avhrr Data in Argentina

    NASA Astrophysics Data System (ADS)

    Seiler, R. A.; Kogan, F.; Wei, Guo

    Satellite observations over the last two decades have contributed to improve the understanding of climate variations and the physical and biological relations of the environment. In this study the application of NOAA-AVHRR satellite data for monitoring weather conditions and corn yield in the main cropping area of Argentina was analyzed. The results have shown that images of VCI and TCI are an effective tool for monitoring regional weather conditions, droughts and their evolution, providing greater and on time spatial and temporal coverage than the one is possible from ground-based measurements. Corn yield developed models based on VCI and TCI can provide reliable and timely yield estimates of regional agricultural production. Yield estimates can be made about two months before harvesting

  10. Error correction of the Normalized Difference Vegetation Index and Brightness Temperature calculated from the AVHRR observations

    NASA Astrophysics Data System (ADS)

    Rahman, Mohammed Zahidur

    This thesis investigates Normalized Difference Vegetation Index (NDVI) and Brightness Temperature (BT) stability in the NOAA/NESDIS Global Vegetation Index (GVI) data during 1982-2003. This data was collected from five NOAA series satellites. We have proposed to apply Empirical distribution function (EDF) to improve the stability of the NDVI and BT data derived from the AVHRR sensor on NOAA polar orbiting satellite. The instability of data results from orbit degradation as well as the circuit drifts over the life or a satellite. Degradation of NDVI and BT over time and shifts of NDVI and BT between the satellites was estimated China data set, for it includes a wide variety or different ecosystems represented globally. It was found that data for the years 1988, 1992, 1993, 1994, 1995 and 2000 are not stable enough compared to other years because of satellite orbit drift, AVHRR sensor degradation, and also Mt Pinatubo volcanic eruption in 1992. We assume data from NOAA-7(1982, 1983), NOAA-9 (1985, 1986), NOAA-11(1989, 1990), NOAA-14(1996, 1997), and NOAA-16 (2001, 2002) to be standard because theses satellite's equator crossing time falls between 1330 and 1500. Data from this particular period of the day maximized the value of coefficients. The crux of the proposed correction procedure consists of dividing standard year's data sets into two subsets. The subset 1(standard data correction sets) is used for correcting unstable years and then corrected data for this years compared with the standard data in the subset 2 (standard data validation sets). In this dissertation, we apply EDF to correct this deficiency of data for the affected years. We normalize or correct data by the method of empirical distribution functions compared with the standard. Using these normalized values, we estimate new NDVI and BT time series which provides NDVI and BT data for these years that match in subset 2 that is used for data validation.

  11. An efficient contextual algorithm to detect subsurface fires with NOAA/AVHRR data

    SciTech Connect

    Gautam, R.S.; Singh, D.; Mittal, A.

    2008-07-15

    This paper deals with the potential application of National Oceanic and Atmospheric Administration (NOAA)/Advanced Very High Resolution Radiometer (AVHRR) data to detect subsurface fire (subsurface hotspots) by proposing an efficient contextual algorithm. Although few algorithms based on the fixed-thresholding approach have been proposed for subsurface hotspot detection, however, for each application, thresholds have to be specifically tuned to cope with unique environmental conditions. The main objective of this paper is to develop an instrument-independent adaptive method by which direct threshold or multithreshold can be avoided. The proposed contextual algorithm is helpful to monitor subsurface hotspots with operational satellite data, such as the Jharia region of India, without making any region-specific guess in thresholding. Novelty of the proposed work lies in the fact that once the algorithmic model is developed for the particular region of interest after optimizing the model parameters, there is no need to optimize those parameters again for further satellite images. Hence, the developed model can be used for optimized automated detection and monitoring of subsurface hotspots for future images of the particular region of interest. The algorithm is adaptive in nature and uses vegetation index and different NOAA/AVHRR channel's statistics to detect hotspots in the region of interest. The performance of the algorithm is assessed in terms of sensitivity and specificity and compared with other well-known thresholding, techniques such as Otsu's thresholding, entropy-based thresholding, and existing contextual algorithm proposed by Flasse and Ceccato. The proposed algorithm is found to give better hotspot detection accuracy with lesser false alarm rate.

  12. Phenology of forest-grassland transition zones in the Community Land Model

    NASA Astrophysics Data System (ADS)

    Dahlin, K.; Fisher, R. A.

    2013-12-01

    Forest-grassland transition zones (savannas, woodlands, wooded grasslands, and shrublands) are highly sensitive to climate and may already be changing due to warming, changes in precipitation patterns, and/or CO2 fertilization. Shifts between closed canopy forest and open grassland, as well as shifts in phenology, could have large impacts on the global carbon cycle, water balance, albedo, and on the humans and other animals that depend on these regions. From an earth system perspective these impacts may then feed back into the climate system and impact how, when, and where climate change occurs. Here we compare 29 years of monthly leaf area index (LAI) outputs from several offline versions of the Community Land Model (CLM), the land component of the Community Earth System Model, to LAI derived from the AVHRR NDVI3g product (LAI3g). Specifically, we focus on seasonal patterns in regions dominated by tropical broadleaved deciduous trees (T-BDT), broadleaved deciduous shrubs (BDS) and grasslands (C3 and C4) in CLM, all of which follow a 'stress deciduous' phenological algorithm. We consider and compare two versions of CLM (v. 4CN and v. 4.5BGC) to the satellite derived product. We found that both versions of CLM were able to capture seasonal variations in grasslands relatively well at the regional scale, but that the 'stress deciduous' phenology algorithm did not perform well in areas dominated by T-BDT or BDS. When we compared the performance of the models at single points we found slight improvements in CLM4.5BGC over CLM4CN, but generally that the magnitude of seasonality was too low in CLM as compared to the LAI3g satellite product. To explore the parameters within CLM that had the most leverage on seasonality of LAI, we used a Latin hypercube approach to vary values for critical soil water potential (threshold at which plants drop leaves), the critical number of days that soil water potential must be too low for leaves to drop, and the carbon allocation scheme

  13. 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.

  14. Analysis of trends in fused AVHRR and MODIS NDVI data for 1982-2006: Indication for a CO2 fertilization effect in global vegetation

    NASA Astrophysics Data System (ADS)

    Los, S. O.

    2013-04-01

    CO2 fertilization would be a large component of the land carbon sink. In the supporting information the RVI is used as a common standard to fuse MODIS and advanced very high resolution radiometer (AVHRR) NDVI data. This fusion compares well with SeaWiFS data.

  15. Development of an automated classification scheme for detection of polar stratospheric clouds over Antarctica using AVHRR imagery

    NASA Astrophysics Data System (ADS)

    Foschi, Patricia S.; Pagan, Kathy L.; Garcia, Oswaldo; Smith, Deborah K.; Gaines, Steven E.; Hipskind, R. Stephen

    1995-12-01

    Although polar stratospheric clouds (PSCs) are a critical component in the ozone depletion process, their timing, duration, geographic extent, and annual variability are not well understood. The goal of this study is the development of an automated classification scheme for detecting PSCs using NOAA AVHRR data. Visual interpretation, density slicing, and standard multispectral classification detect most optically thick PSCs, but only some thin PSCs. Two types of automated techniques for detecting thin PSCs are being investigated: namely, multispectral classification methods, including the use of texture and other imagederived features, and back-propagation neural networks, including the use of hyperspatial and hypertemporal data. UARS CLAES temperature and aerosol extinction coefficient data are being used as a verification dataset. If successful, this classification scheme will be used to process the entire record of AVHRR data in order to assemble a long-term PSC climatology.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. Condition of New Mexico rangelands derived from multi-year AVHRR imagery and associated spatial variables

    SciTech Connect

    Lancaster, J.; Wade, T.; Minor, T.

    1996-07-01

    The Desert Research Institute in cooperation with the Environmental Protection Agency Characterization Research Division, Las Vegas, has been evaluating indicators of rangeland health derived from remote sensing technology. The primary objective of this project was to determine the ability of multi-date remote sensing imagery to detect variation in vegetation productivity, as a potential indicator of ecosystem condition in the western U.S. The conterminous U.S. AVHRR biweekly composites were acquired from EROS Data Center for the six years 1989-1994. Normalized Difference Vegetation Index (NDVI) data for New Mexico were imported into a Geographical Information System. Using a digital vegetation map for the state, woodland and montane vegetation types were masked, leaving two grassland and four shrub-dominated vegetation classes. Average annual NDVI was calculated for each year, and a series of regression analysis were performed using 1989 as the reference year (independent variable), and each subsequent year as dependent variables. Outliers were identified as pixels two standard deviations from the calculated regression line, indicating 14 areas of change, three with lower productivity versus 1989, and 11 with higher productivity. Mining, military activity and irrigated agriculture were among the causes of change.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. AVHRR imagery used to identify hurricane damage in a forested wetland of Louisiana

    USGS Publications Warehouse

    Ramsey, Elijah W.; Chappell, D.K.; Baldwin, D.G.

    1997-01-01

    Certain events provide a unique opportunity to test the monitoring capability of AVHBR imagery. On 26 August 1992, Hurricane Andrew passed through Louisiana, impacting a large area of forested wetlands. One response to the widespread defoliation resulting from the hurricane impact was an abnormal bloom of new leaves and new growth in the underlying vegetation between September and October. To capture this atypical phenology, a time sequence of AVHRR images was transformed into a normalized difference vegetation index, NDVI, as an indicator of vegetation changes in the forest impacted by the passage of a hurricane. Using geographic information system functions, three sites in the impacted forest were vectorized as polygons, and the inclusive pixels were extracted for subsequent graphical and univariate statistical analysis. Temporal curves of mean NDVIs for the three sites for before, during, and after the hurricane passage, and aggregate curves of the impacted forest to an undisturbed forest, were compared. These comparisons corroborated the atypical phenology of the impacted forested wetland and directly related the cause to the hurricane passage.

  8. 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…

  9. 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 Chicho??n, Mexico. The volcanic cloud/atmosphere interactions in the first four days of this eruption were investigated by combining ultraviolet retrievals to estimate the mass of sulfur dioxide in the volcanic cloud [Krueger et al., 1995] with thermal infrared retrievals of the size, optical depth, and mass of fine-grained (1-10 ??m radius) volcanic ash [Wen and Rose, 1994]. Our study provides the first direct evidence of gravitational separation of ash from a stratospheric, gas-rich, plinian eruption column and documents the marked differences in residence times of volcanic ash and sulfur dioxide in volcanic clouds. The eruption column reached as high as 32 km [Carey and Sigurdsson, 1986] and was injected into an atmosphere with a strong wind shear, which allowed for an observation of the separation of sulfur dioxide and volcanic ash. The upper, more sulfur dioxide-rich part of the cloud was transported to the west in the stratosphere, while the fine-grained ash traveled to the south in the troposphere. The mass of sulfur dioxide released was estimated at 7.1 ?? 109 kg with the mass decreasing by approximately 4% 1 day after the peak. The mass of fine-grained volcanic ash detected was estimated at 6.5 ?? 109 kg, amounting to about 0.7% of the estimated mass of the ash which fell out in the mapped ash blanket close to the volcano. Over the following days, 98% of this remaining fine ash was removed from the volcanic cloud, and the effective radius of ash in the volcanic cloud decreased from about 8 ??m to about 4 ??m. Copyright 1999 by the American Geophysical Union.

  10. Operational surface UV radiation product from GOME-2 and AVHRR/3 data

    NASA Astrophysics Data System (ADS)

    Kujanpää, J.; Kalakoski, N.

    2015-10-01

    The surface ultraviolet (UV) radiation product, version 1.20, generated operationally in the framework of the Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M SAF) of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) is described. The product is based on the total ozone column derived from the measurements of the second Global Ozone Monitoring Experiment (GOME-2) instrument aboard EUMETSAT's polar orbiting meteorological operational (Metop) satellites. Cloud cover is taken into account by retrieving cloud optical depth from the channel 1 reflectance of the third Advanced Very High-Resolution Radiometer (AVHRR/3) instrument aboard both Metop in the morning orbit and Polar Orbiting Environmental Satellites (POES) of the National Oceanic and Atmospheric Administration (NOAA) in the afternoon orbit. In addition, more overpasses are used at high latitudes where the swaths of consecutive orbits overlap. The input satellite data are received from EUMETSAT's Multicast Distribution System (EUMETCast). The surface UV product includes daily maximum dose rates and integrated daily doses with different biological weighting functions, integrated ultraviolet B (UVB) and ultraviolet A (UVA) radiation, solar noon UV index and daily maximum photolysis frequencies of ozone and nitrogen dioxide at the surface level. The quantities are computed in a 0.5°×0.5° regular latitude-longitude grid and stored as daily files in the hierarchical data format (HDF5) within 2 weeks from sensing. The product files are archived in the O3M SAF distributed archive and can be ordered via the EUMETSAT Data Centre.

  11. 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.

  12. 25 CFR 170.123 - What are seasonal transportation routes?

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 25 Indians 1 2012-04-01 2011-04-01 true What are seasonal transportation routes? 170.123 Section 170.123 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAND AND WATER INDIAN RESERVATION... § 170.123 What are seasonal transportation routes? Seasonal transportation routes are...

  13. 25 CFR 170.123 - What are seasonal transportation routes?

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 25 Indians 1 2014-04-01 2014-04-01 false What are seasonal transportation routes? 170.123 Section 170.123 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAND AND WATER INDIAN RESERVATION... § 170.123 What are seasonal transportation routes? Seasonal transportation routes are...

  14. 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.

  15. Managing the Sneezing Season

    MedlinePlus

    ... Javascript on. Feature: Managing Allergies Managing the Sneezing Season Past Issues / Summer 2011 Table of Contents Seasonal ... Read More "Managing Allergies" Articles Managing the Sneezing Season / A Pollen Primer / Seasonal Allergies: Symptoms, Diagnosis, and ...

  16. 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.

  17. 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

  18. 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

  19. 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

  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. 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.

  2. Retrieval of aerosol optical properties over land using PMAp

    NASA Astrophysics Data System (ADS)

    Grzegorski, Michael; Munro, Rosemary; Lang, Ruediger; Poli, Gabriele; Holdak, Andriy

    2015-04-01

    The retrieval of aerosol optical properties is an important task for industry and climate forecasting. An ideal instrument should include observations with moderate spectral and high spatial resolutions for a wide range of wavelengths (from the UV to the TIR), measurements of the polarization state at different wavelengths and measurements of the same scene for different observation geometries. As such an ideal instrument is currently unavailable the usage of different instruments on one satellite platform is an alternative choice. Since February 2014, the Polar Multi sensor Aerosol product (PMAp) is delivered as operational GOME product to our customers. The algorithms retrieve aerosol optical properties over ocean (AOD, volcanic ash, aerosol type) using a multi-sensor approach (GOME, AVHRR, IASI). The next releases of PMAp will provide an extended set of aerosol and cloud properties which include AOD over land and an improved volcanic ash retrieval combining AVHRR and IASI. This presentation gives an overview on the existing product and the prototypes in development. The major focus is the discussion of the AOD retrieval over land implemented in the upcoming PMAp2 release. In addition, the results of our current validation studies (e.g. comparisons to AERONET, other satellite platforms and model data) are shown.

  3. Validation of current land cover maps utilizing astronaut acquired photography

    NASA Astrophysics Data System (ADS)

    Gebelein, Jennifer; Estes, John E.

    2000-01-01

    This investigation focuses on the potential use of astronaut acquired photography for the validation of current, land cover maps. More specifically, this study is directed at assessing the potential for the use of astronaut acquired photography to document and validate land cover change. Space Shuttle, astronaut acquired photography is employed to test the potential utility of data that may be acquired by astronauts employing the Window Observational Rack Facility (WORF) on International Space Station (ISS). The majority of astronaut acquired photography has been obtained under conditions similar to ISS operations in terms of both spectral as well as spatial resolution. Validation of land cover maps utilizing this type of imagery is being accomplished through a process of comparison among three different land cover classification legends created from the Eros Data Center (EDC) Land Characteristics Database. Our study area is a subregional scale portion of an Advanced Very High Resolution Radiometer (AVHRR) based global Land Characteristics Database. The goal of this research is to attempt to establish: 1. which legend derived for this area provides the highest overall accuracy for the land cover classes present: 2. which legend is best validated using astronaut acquired photography; and 3. which classes of these legends best lend themselves to validation with astronaut acquired photography. Preliminary results indicate that astronaut acquired photography can be employed to validate land cover maps and that results achieved using this imagery corresponds well to those achieved utilizing Landsat data. .

  4. 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.

  5. REVIEW: Accuracies of Global Land Cover Maps Checked against Fluxnet Sites

    NASA Astrophysics Data System (ADS)

    Gong, Peng

    2008-01-01

    Global land cover data products are key sources of information in understanding the complex interactions between human activities and global change. They play a critical role in improving performances of ecosystem, hydrological and atmospheric models. Three freely available global land cover products developed in the United States are popularly used by the scientific community. These include two global maps developed separately by the United States Geological Survey (USGS) and the University of Maryland (UMD) with NOAA Advanced Very High Resolution Radiometer (AVHRR) data, and one developed by Boston University with the EOS Moderate Resolution Imaging Spectroradiometer (MODIS) data. They are compared with known land cover types at 250 available Fluxnet sites around the world. The overall accuracies are 37%, 36% and 42%, respectively for the USGS, UMD and Boston global land cover maps. Some future global land cover mapping strategies are suggested.

  6. 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.

  7. Integration of high spatial resolution land cover maps to understand opposing trends in vegetation productivity: A case study for the Dry Chaco ecoregion of South America

    NASA Astrophysics Data System (ADS)

    Ehammer, A.; Fensholt, R.; Horion, S.; Tagesson, T.

    2013-12-01

    Time series analysis of coarse spatial resolution satellite images, especially AVHRR-NDVI data records, has been widely used to characterize long term vegetation dynamics at regional, continental and global scales. However, studies of greening and browning trends show contradictory results depending on input data sets or examined vegetation productivity metrics. Annual cycles of vegetation reflectance respond in a variety of ways to change in climate and/or human induced activities, which make the interpretation and validation of trends at global scale difficult. Integrating high spatial resolution land cover data for analysis can provide accurate evidence of change in land cover/use such as deforestation or expansion/reduction of agricultural land. To bridge scales between coarse resolution data and in-situ observations, this research aims to create multi-temporal, high resolution land cover maps. These maps should add an independent information layer to understand trends found in global earth observation records. To test the framework of this study, the Dry Chaco ecoregion, covering Northern Argentina, Eastern Bolivia and Western Paraguay, is explored as opposing trends are found for this region for the period 1982 to 2010. Not only are results based on yearly NDVI sums of the GIMMS (Global Inventory Modeling and Mapping Studies; 3g) and VIP (Vegetation Index and Phenology; version 2) datasets diverging, but also a comparison of the annual mean with the growing season small integral (both derived from GIMMS 3g) yields opposing trends. In this study we hypothesize that these differences in trends are related to land cover change and several researchers report deforestation in favor of industrial agriculture. Landsat images are used to create regional land cover maps. To overcome the problem of product availability and acquisition mismatch between years, an object-based classification approach based on multiple images per year is applied. First results are

  8. MSG/SEVIRI, NOAA/AVHRR and EOS/MODIS TIR observations during the Abruzzo 6 April 2009 earthquake (ML~ 5.8)

    NASA Astrophysics Data System (ADS)

    Genzano, Nicola; Corrado, Rosita; Filizzola, Carolina; Lacava, Teodosio; Lisi, Mariano; Marchese, Francesco; Mazzeo, Giuseppe; Paciello, Rossana; Pergola, Nicola; Tramutoli, Valerio

    2010-05-01

    Space-time fluctuations of Earth's emitted Thermal Infrared (TIR) radiation have been observed from satellite months to weeks before earthquakes occurrence. Different authors, in order to explain the appearance of anomalously high TIR records near the place and the time of earthquake occurrence, attributed their appearance to the increase of green-house gas (such as CO2, CH4, etc.) emission rates, to the modification of ground water regime and/or to the increase of convective heat flux. In this contest, an approach called Robust Satellite Techniques (RST) has been proposed in order to discriminate normal (i.e. related to the change of natural factor and/or observation conditions) TIR signal fluctuations from anomalous signal transient possibly associated to earthquake occurrence. In the past RST was already tested in the case of tens of earthquakes with a wide range of magnitudes (from 4.0 to 7.9) occurred in different continents and in various geo-tectonic setting (e.g. 1980 Irpinia-Basilicata earthquake; Izmit earthquake, 17 August 1999; Hector Mine earthquake, 16 October 1999, etc.). The RST analysis is based on a statistically definition of "TIR anomalies" and a suitable method for their identification even in very different local (e.g. related to atmosphere and/or surface) and observational (e.g. related to time/season, but also to solar and satellite zenithal angles) conditions, and has been always carried out by using a validation/confutation approach, to verify the presence/absence of anomalous space-time TIR transients in the presence/absence of seismic activity. In this work the same approach is applied to the case of Abruzzo 6 April 2009 event (ML=5.8) and compared with an identical analysis (confutation) performed in seismically unperturbed years. RST analysis was performed on a historical data set made of 30 years of contemporary observations done by 3 independent satellite systems (5 years of MSG/SEVIRI, 15 years of NOAA/AVHRR and 10 years of EOS

  9. Global patterns of vegetation fire seasonality

    NASA Astrophysics Data System (ADS)

    Benali, Akli; Mota, Bernardo; Pereira, Jose M. C.; Oom, Duarte; Carvalhais, Nuno

    2013-04-01

    Fires exhibit a strong seasonality throughout the year, which is driven by a combination of climatic factors, ignition sources and land management practices. Despite the significant contribution of fire to atmospheric composition, global biogeochemical cycles and the Earth system in general, seasonal fire activity has not been thoroughly characterized at the global scale so far. In this work we aim to classify and investigate the patterns of fire seasonality at the global scale. Active fire counts from the Moderate Resolution Imaging Spectrometer (MODIS) over the period 2002-2012 were aggregated to a spatial resolution of 0.5 degrees to derive the first global classification map of uni and bimodal fire seasons. We used circular statistics techniques to fit a single and a mixture of two von Mises distributions to the observed active fire counts in order to classify fire activity into uni- and bi-modal seasonal patterns. The seasonal model was determined using the Nash-Sutcliffe model efficiency index to select the best seasonal model explaining the fire activity observations. We combined annual and aggregated (2002-2012) active fire counts to produce a more detailed seasonality classification identifying the regions with unimodal and predominantly- frequently- and sporadically-bimodal seasonal patterns. We find that circa 25% of the global regions with relevant fire activity exhibited some type of bimodal fire seasonality. The most relevant clusters showing bimodal seasonality were found in northeastern regions of North America, and the southern areas of South America, as well as in Russia, Ukraine and Kazakhstan, northern India, and northeastern China. Around 40% of the bimodal regions were covered by croplands, twice as much as in unimodal areas, suggesting that most of the bimodal activity is related to land management practices. The interannual variability of the seasonal patterns is also investigated, in particular the changes in the magnitude of the main and

  10. A 30-Year Multi-Sensor Vegetation Index and Land Surface Phenology Data Record: Methods Challenges and Potentials

    NASA Astrophysics Data System (ADS)

    Didan, K.; Barreto-munoz, A.; Miura, T.; Tsend-Ayush, J.

    2013-12-01

    During the last five years the Vegetation Index and Phenology Lab. (vip.arizona.edu) embarked on an effort to process a global multi-sensor Earth Science Data Record of NDVI, EVI2, and land surface Phenology. Data from AVHRR, MODIS, and SPOT-VGT, covering the period 1981 to present, were processed into a seamless and sensor independent record using a suite of community algorithms for data filtering, across-sensor continuity, Vegetation Index (NDVI and EVI2), land surface Phenology, and spatial and temporal gap filling. Currently at Version 3.0 these ESDRs are suitable for the study of land surface vegetation dynamics, long term change and trends, anomalies, and can support various ecosystem and climate modeling efforts by providing key parameters. While adapting the various algorithms to processing this new data record many challenges emerged, ranging from excessive missing and poor quality data to complex and temporally dependent divergence across the various sensors making continuity quite difficult. The first step to addressing these challenges was the adoption of very strict and low tolerance to noise data filters, where the intrinsic input data quality is used along with the long term expected dynamic range to screen for outliers and poor quality. A sophisticated and explicit per-pixel and seasonally dependent across-sensor translation algorithm was developed to address the continuity more properly. To generate the land surface phenology we adapted various community algorithms to work with and take advantage of this new record. Both the standard MODIS Vegetation dynamic algorithm and an in-house homogeneous cluster algorithm were applied to the data. We've also completed a spatially and temporally explicit error and uncertainty characterization of this record. Results indicate a VI error in the range of 5-10% VI units and a 5-40 days error in the date dependent phenology parameters, with an average error of 15 days. This VIP record accounts now for more than

  11. 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.

  12. 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

  13. 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.

  14. 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

  15. 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

  16. Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982-2010.

    PubMed

    Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

    2014-05-01

    Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and GSL varied considerably during 1982-2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

  17. Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982-2010.

    PubMed

    Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

    2014-05-01

    Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and GSL varied considerably during 1982-2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

  18. Seasonal greening in grasslands

    NASA Astrophysics Data System (ADS)

    Orescanin, Biljana

    Grasslands cover about one quarter of the Earth's land and are currently considered to act as carbon sinks, taking up an estimated 0.5 Gt C per year. Thus, robust understanding of the grassland biome (e.g. representation of seasonal cycle of plant growth and the amount of green mass, often referred to as phenology, in global carbon models) plays a key role in understanding and predicting the global carbon cycle. The focus of this research is on improvement of a grassland biome representation in a biosphere model, which sometimes fails to correctly represent the phenology of vegetation. For this purpose, as a part of Simple Biosphere model (SiB3), a phenology model is tested and improved to provide more realistic representation of plant growth dependence on available moisture, which along with temperature and light controls plant growth. The new methodology employs integrated soil moisture in plant growth simulation. This new representation addresses the nature of the plants to use their root system to access the water supply. At same time it represents the plant's moisture recourses more accurately than the currently used vapor pressure method, which in grasslands is often non-correlated with soil conditions. The new technique has been developed and tested on data from the Skukuza flux tower site in South Africa and evaluated at 6 different flux tower sites around the world covering a variety of climate conditions. The technique is relatively easy and inexpensive to implement into the existing model providing excellent results capturing both the onset of green season and greening cycle at all locations. Although the method is developed for grasslands biome its representation of natural plant processes provides a good potential for its global use.

  19. Assessing the consequence of land use change on agricultural productivity in China

    NASA Astrophysics Data System (ADS)

    Yan, Huimin; Liu, Jiyuan; Huang, He Qing; Tao, Bo; Cao, Mingkui

    2009-05-01

    China's cultivated land has been undergoing dramatic changes along with its rapidly growing economy and population. The impacts of land use transformation on food production at the national scale, however, have been poorly understood due to the lack of detailed spatially explicit agricultural productivity information on cropland change and crop productivity. This study evaluates the effect of the cropland transformation on agricultural productivity by combining the land use data of China for the period of 1990-2000 from TM images and a satellite-based NPP (net primary production) model driven with NOAA/AVHRR data. The cropland area of China has a net increase of 2.79 Mha in the study period, which causes a slightly increased agricultural productivity (6.96 Mt C) at the national level. Although the newly cultivated lands compensated for the loss from urban expansion, but the contribution to production is insignificant because of the low productivity. The decrease in crop production resulting from urban expansion is about twice of that from abandonment of arable lands to forests and grasslands. The productivity of arable lands occupied by urban expansion was 80% higher than that of the newly cultivated lands in the regions with unfavorable natural conditions. Significance of cropland transformation impacts is spatially diverse with the differences in land use change intensity and land productivity across China. The increase in arable land area and yet decline in land quality may reduce the production potential and sustainability of China's agro-ecosystems.

  20. 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.

  1. 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.

  2. Study to assess the importance of errors introduced by applying NOAA 6 and NOAA 7 AVHRR data as an estimator of vegetative vigor: Feasibility study of data normalization

    NASA Technical Reports Server (NTRS)

    Duggin, M. J. (Principal Investigator); Piwinski, D.

    1982-01-01

    The use of NOAA AVHRR data to map and monitor vegetation types and conditions in near real-time can be enhanced by using a portion of each GAC image that is larger than the central 25% now considered. Enlargement of the cloud free image data set can permit development of a series of algorithms for correcting imagery for ground reflectance and for atmospheric scattering anisotropy within certain accuracy limits. Empirical correction algorithms used to normalize digital radiance or VIN data must contain factors for growth stage and for instrument spectral response. While it is not possible to correct for random fluctuations in target radiance, it is possible to estimate the necessary radiance difference between targets in order to provide target discrimination and quantification within predetermined limits of accuracy. A major difficulty lies in the lack of documentation of preprocessing algorithms used on AVHRR digital data.

  3. 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.

  4. Quantification of Surface Suspended Sediments along a River Dominated Coast with NOAA AVHRR and SeaWiFS Measurements: Louisiana, USA

    NASA Technical Reports Server (NTRS)

    Myint, S. W.; Walker, N. D.

    2002-01-01

    The ability to quantify suspended sediment concentrations accurately over both time and space using satellite data has been a goal of many environmental researchers over the past few decades This study utilizes data acquired by the NOAA Advanced Very High Resolution Radiometer (AVHRR) and the Orbview-2 Sea-viewing wide field-of-view (SeaWiFS) ocean colour sensor, coupled with field measurements to develop statistical models for the estimation of near-surface suspended sediment and suspended solids "Ground truth" water samples were obtained via helicopter, small boat and automatic water sampler within a few hours of satellite overpasses The NOAA AVHRR atmospheric correction was modified for the high levels of turbidity along the Louisiana coast. Models were developed based on the field measurements and reflectance/radiance measurements in the visible and near infrared Channels of NOAA-14 and Orbview-2 SeaWiFS. The best models for predicting surface suspended sediment concentrations were obtained with a NOAA AVHRR Channel 1 (580-680nm) cubic model, Channel 2 (725-1100 nm) linear mod$ and SeaWiFs Channel 6 (660-68Onm) power modeL The suspended sediment models developed using SeaWiFS Channel 5 (545-565 nm) were inferior, a result that we attribute mainly to the atmospheric correction technique, the shallow depth of the water samples and absorption effects from non-sediment water constituents.

  5. 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.

  6. 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.

  7. Dry season streamflow persistence in seasonal climates

    NASA Astrophysics Data System (ADS)

    Dralle, David N.; Karst, Nathaniel J.; Thompson, Sally E.

    2016-01-01

    Seasonally dry ecosystems exhibit periods of high water availability followed by extended intervals during which rainfall is negligible and streamflows decline. Eventually, such declining flows will fall below the minimum values required to support ecosystem functions or services. The time at which dry season flows drop below these minimum values (Q*), relative to the start of the dry season, is termed the "persistence time" (). The persistence time determines how long seasonal streams can support various human or ecological functions during the dry season. In this study, we extended recent work in the stochastic hydrology of seasonally dry climates to develop an analytical model for the probability distribution function (PDF) of the persistence time. The proposed model accurately captures the mean of the persistence time distribution, but underestimates its variance. We demonstrate that this underestimation arises in part due to correlation between the parameters used to describe the dry season recession, but that this correlation can be removed by rescaling the flow variables. The mean persistence time predictions form one example of the broader class of streamflow statistics known as crossing properties, which could feasibly be combined with simple ecological models to form a basis for rapid risk assessment under different climate or management scenarios.

  8. 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.

  9. 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…

  10. 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…

  11. Land Application.

    ERIC Educational Resources Information Center

    Reynolds, James H.

    1978-01-01

    Presents a literature review of wastewater land application, covering publications of 1976-77. This review covers areas such as the history, development, philosophy, design, models, and case studies of land application. A list of 41 references is also presented. (HM)

  12. Global and regional trends of aerosol optical depth over land and ocean using SeaWiFS measurements from 1997 to 2010

    NASA Astrophysics Data System (ADS)

    Hsu, N. C.; Gautam, R.; Sayer, A. M.; Bettenhausen, C.; Li, C.; Jeong, M. J.; Tsay, S.-C.; Holben, B. N.

    2012-09-01

    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, 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-yr mission. Our correlation analysis between climatic indices (such as ENSO) and AOD suggests strong relationships for Saharan dust export as well as biomass-burning activity in the tropics, associated with large-scale feedbacks. The results also 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 regional scales, distinct tendencies are found for different regions associated with natural and anthropogenic aerosol emission and transport. 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.

  13. 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.

  14. Retrieval of red spectral albedo and bidirectional reflectance using AVHRR HRPT and GOES satellite observations of the New England region

    NASA Astrophysics Data System (ADS)

    D'Entremont, Robert P.; Schaaf, Crystal Barker; Lucht, Wolfgang; Strahler, Alan H.

    1999-03-01

    As a prototyping exercise for the moderate-resolution imaging spectroradiometer (MODIS) albedo/BRDF product, we demonstrate the retrieval of bidirectional reflectance distribution functions (BRDFs) and red spectral albedo measures for the New England region, United States, from merged AVHRR and GOES radiances at a 1 km2 (nominal) spatial scale. These data were acquired during a 25-day period in early fall 1995. The spatial pattern of BRDF retrievals shows that urban, suburban, and interurban regions exhibit directional scattering that is well modeled by the geometric optics of shadow casting. The directional reflectance of more continuous forest areas is better described by volume-scattering mechanisms. Spectral albedos are larger in urban and suburban areas than in forested regions, as might be expected from the strong absorption of leaves in the red wave band. The red spectral albedo generally increases with solar zenith angle, as has been noted in ground measurements of broadband albedo. A number of technical limitations discussed constrain the absolute accuracy of retrieved albedos presented here, although the spatial patterns of albedo and the consistency of the BRDF shapes inspire confidence. These limitations will largely be overcome with application of our algorithm to data from the MODIS and MISR instruments on the EOS AM-1 platform.

  15. 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.

  16. 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.

  17. 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

  18. Application study on drought monitoring with time-series NOAA/AVHRR data

    NASA Astrophysics Data System (ADS)

    Zhu, Xiaoxiang; Zhao, Bolin; Zhu, Yuanjing; Zhang, Wenjian; Zhang, Yeping; Liu, Ruixia

    2006-12-01

    In this paper, 30 years conventional data of China are processed, the anomaly of precipitation, land surface temperature and air temperature are calculated and their relations are analyzed by using regressive statistics analysis and Singular Value Decomposition (SVD). The result shows that precipitation anomaly has a good negative correlation to both surface temperature anomaly and air temperature anomaly. Moreover, 20 years satellite brightness temperature anomaly and the same period precipitation anomaly are also calculated and analyzed; the similar result is obtained. It indicates that brightness temperature anomaly is an important factor for drought monitoring by using remote sensing data. Moreover, compared with historic data, the change of Normalized Difference Vegetation Index (NDVI) is another factor for drought monitoring. Drought index is formed by these two factors normalization and mean in weight. This remote sensing method on drought was used to some experiments and the results show that the drought distribution on space is very similar, compared with conventional drought index. Now this method is being used in operational system on drought monitoring in National Satellite Meteorological Center (NSMC), China meteorology administration (CMA).

  19. 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

  20. 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.

  1. Seasonality of Tuberculosis

    PubMed Central

    Fares, Auda

    2011-01-01

    Objectives: This study was designed to review previous studies and analyse the current knowledge and controversies related to seasonal variability of tuberculosis (TB) to examine whether TB has an annual seasonal pattern. Study Design and Methods: Systematic review of peer reviewed studies identified through literature searches using online databases belonging to PubMed and the Cochrane library with key words “Tuberculosis, Seasonal influence” and “Tuberculosis, Seasonal variation”. The search was restricted to articles published in English. The references of the identified papers for further relevant publications were also reviewed. Results: Twelve studies conducted between the period 1971 and 2006 from 11 countries/regions around the world (South Western Cameroon, South Africa, India, Hong Kong, Japan, Kuwait, Spain, UK, Ireland, Russia, and Mongolia) were reviewed. A seasonal pattern of tuberculosis with a mostly predominant peak is seen during the spring and summer seasons in all of the countries (except South Western Cameroon and Russia). Conclusions: The observation of seasonality leads to assume that the risk of transmission of M. tuberculosis does appear to be the greatest during winter months. Vitamin D level variability, indoor activities, seasonal change in immune function, and delays in the diagnosis and treatment of tuberculosis are potential stimuli of seasonal tuberculosis disease. Additionally, seasonal variation in food availability and food intake, age, and sex are important factors which can play a role in the tuberculosis notification variability. Prospective studies regarding this topic and other related subjects are highly recommended. PMID:21572609

  2. Improvements in AVHRR Daytime Cloud Detection Over the ARM NSA Site

    NASA Technical Reports Server (NTRS)

    Chakrapani, V.; Spangenberg, D. A.; Doelling, D. R.; Minnis, P.; Trepte, Q. Z.; Arduini, R. F.

    2001-01-01

    Clouds play an important role in the radiation budget over Arctic and Antarctic. Because of limited surface observing capabilities, it is necessary to detect clouds over large areas using satellite imagery. At low and mid-latitudes, satellite-observed visible (VIS; 0.65 micrometers) and infrared (IR; 11 micrometers) radiance data are used to derive cloud fraction, temperature, and optical depth. However, the extreme variability in the VIS surface albedo makes the detection of clouds from satellite a difficult process in polar regions. The IR data often show that the surface is nearly the same temperature or even colder than clouds, further complicating cloud detection. Also, the boundary layer can have large areas of haze, thin fog, or diamond dust that are not seen in standard satellite imagery. Other spectral radiances measured by satellite imagers provide additional information that can be used to more accurately discriminate clouds from snow and ice. Most techniques currently use a fixed reflectance or temperature threshold to decide between clouds and clear snow. Using a subjective approach, Minnis et al. (2001) found that the clear snow radiance signatures vary as a function of viewing and illumination conditions as well as snow condition. To routinely process satellite imagery over polar regions with an automated algorithm, it is necessary to account for this angular variability and the change in the background reflectance as snow melts, vegetation grows over land, and melt ponds form on pack ice. This paper documents the initial satellite-based cloud product over the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site at Barrow for use by the modeling community. Cloud amount and height are determined subjectively using an adaptation of the methodology of Minnis et al. (2001) and the radiation fields arc determined following the methods of Doelling et al. (2001) as applied to data taken during the Surface Heat and Energy Budget of the

  3. A New Hybrid Method for Remote Sensing Time Series Reconstruction in Support of Land Surface Phenology

    NASA Astrophysics Data System (ADS)

    Barreto-Munoz, A.; Didan, K.; Riveracamacho, J.; Yitayew, M.

    2010-12-01

    Remote sensing vegetation indices (NDVI, EVI, and EVI2) are proxies for studying vegetation states and enable the effective and consistent monitoring of global vegetation. Records of daily global satellite images are available from the last three decades, however, the presence of clouds, aerosols, variable viewing geometry and less than ideal processing techniques makes it difficult to obtain high quality data every time; resulting in incomplete daily coverage (80% of the data is either missing or useless sometimes). In order to improve the temporal frequency and coverage, gap fill techniques are usually employed. There are several methods that are mostly based on the use of complex Fourier Transform (TF) functions, Gaussian fitting models, or simple compositing techniques. The first two methods are extremely CPU and memory intensive and the results tend to be biased towards the periods of time when data is available . The composite-method sacrifices the temporal frequency in order to achieve higher quality data over longer periods of time by combining several images into one to insure the elimination of problematic data Long composite period interval tend to inhibit proper change detection during periods of rapid change and periods of land cover disturbance. Because this method is based on maximizing the vegetation index value during the composite period, longer composite interval will shift the start of season towards later dates, the end of season towards earlier dates, and consequently shorter growing season. These slight errors and uncertainties interfere with accurate change detection as they add a level of uncertainty to the estimated Phenology parameters. In this research we’re developing a new technique that aims at producing consistently high quality vegetation index data, while preserving adequate temporal resolution to support accurate phenological studies. This method involves finding the optimum number of days for compositing and then using an

  4. Characteristics of seasonal vegetation cover in the conterminous USA

    USGS Publications Warehouse

    Gallo, Kevin P.; Reed, Bradley C.; Owen, editors, Timothy W.; Adegoke, Jimmy O.

    2005-01-01

    A data set of the fractional green vegetation cover (FGREEN) for the Conterminous USA was evaluated for regional and seasonal variation. The value of FGREEN was derived monthly for the three most dominant land cover classes per 20 km by 20 km grid cell within the study area. At this grid cell resolution (comprised of 400 1-km pixels), 97 percent of the grid cells included three or fewer land cover classes. FGREEN was found to vary regionally due to local land cover and climate variations. FGREEN was found significantly different between one or more of the land cover classes, for one or more months, in 58 percent of the grid cells included in the study. Monthly FGREEN values for the land cover classes vary sufficiently between the land cover classes to warrant monthly FGREEN data for each of the one to three most dominant land cover classes per grid cell.

  5. Specificity of use of the data of remote sensing AVHRR and MODIS in tasks of detecting of fires

    NASA Astrophysics Data System (ADS)

    Moiseev, Eugene E.; Lapukhov, Sergey A.; Glushkova, Nadezhda V.; Dobretsov, Nicolay N.

    2004-02-01

    In 1998 it has been organized the service which uses remote sensing data (RSD) processing techniques for monitoring and prediction of the fire situation on the basis of the West-Siberian Regional Centre of Reception and Data processing (WS RCRDP), at the participation of the Novosibirsk Regional Center of Geoinformation Technologies (NRCGIT SB RAS). Accuracy of referencing for the Novosibirsk region is up to 1 pixel (satellite NOAA-14, sensor AVHRR, space resolution is 1 km). Thin plate spline is used for received NOAA images georeference correction. Currently the data of the MODIS sensor from the Terra satellite is accessible. A hot spot coordinates determination accuracy on images received after the geometrical correction is less than one pixel (up to 1 km) and in the case of higher resolution channels utilization is less than one quarter of the pixel (up to 250m). A whole system of the forest fires monitoring consists of two independent parts: "component of RSD processing" and "GIS-component." The "component of RSD processing" performs: data reprocessing (calibration, image georeferencing) and hotspots detection. The "GIS-component" is intended for secondary data processing. The input data is analyzed by the overlay analysis of the fire seats geometry. Formation of reports and processing results archiving are also performed. End users derive data not in physical coordinates "latitude-longitude," but in their standard forest management system nomenclature -- "Forestry - forest area - wood block." This lightens utilization of the derived result of the processing by forest-guards. It is also planned to develop the module which performs an estimation of the damage, inflicted by forest fires.

  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. 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.

  8. 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.

  9. Seasonality and dietary requirements: will eating seasonal food contribute to health and environmental sustainability?

    PubMed

    Macdiarmid, Jennie I

    2014-08-01

    Eating more seasonal food is one proposal for moving towards more sustainable consumption patterns, based on the assumption that it could reduce the environmental impact of the diet. The aim of the present paper is to consider the implications of eating seasonal food on the different elements of sustainability (i.e. health, economics, society), not just the environment. Seasonality can be defined as either globally seasonal (i.e. produced in the natural production season but consumed anywhere in the world) or locally seasonal (i.e. produced in the natural production season and consumed within the same climatic zone). The environmental, health, economic and societal impact varies by the definition used. Global seasonality has the nutritional benefit of providing a more varied and consistent supply of fresh produce year round, but this increases demand for foods that in turn can have a high environmental cost in the country of production (e.g. water stress, land use change with loss of biodiversity). Greenhouse gas emissions of globally seasonal food are not necessarily higher than food produced locally as it depends more on the production system used than transportation. Eating more seasonal food, however, is only one element of a sustainable diet and should not overshadow some of the potentially more difficult dietary behaviours to change that could have greater environmental and health benefits (e.g. reducing overconsumption or meat consumption). For future guidelines for sustainable diets to be realistic they will need to take into account modern lifestyles, cultural and social expectations in the current food environment. PMID:25027288

  10. 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…

  11. True Color Earth Data Set Includes Seasonal Dynamics

    NASA Astrophysics Data System (ADS)

    Stöckli, Reto; Vermote, Eric; Saleous, Nazmi; Simmon, Robert; Herring, David

    2006-01-01

    Space exploration has changed our visual perception of planet Earth. In the 1950s, satellites revolutionized weather forecasting. Astronaut photography in the early 1970s showed us the Earth in color, the so-called `Blue Marble' (Figure 1, left). Since 1972, satellite sensors have been acquiring atmosphere, land, ice, and ocean data with increasing spectral and spatial resolution. Satellite remote sensing systems such as the NASA Earth Observing System (EOS) help us to understand and monitor Earth's physical, chemical, and biological processes [Running et al., 1999]. The false-color Earth image shown in the center of Figure 1, named Blue Marble, was created in 2000 with data from the Advanced Very High Resolution Radiometer (AVHRR), the Geostationary Operational Environmental Satellite (GOES 8), and the Sea viewing Wide Field-of-view Sensor (SeaWiFS). New sensors such as the Moderate-Resolution Imaging Spectroradiometer (MODIS), aboard NASA Terra and Aqua satellites, allow the derivation of a wide range of geophysical parameters from measured radiances of a single sensor.

  12. 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.

  13. Adaptation to seasonality and the winter freeze.

    PubMed

    Preston, Jill C; Sandve, Simen R

    2013-01-01

    Flowering plants initially diversified during the Mesozoic era at least 140 million years ago in regions of the world where temperate seasonal environments were not encountered. Since then several cooling events resulted in the contraction of warm and wet environments and the establishment of novel temperate zones in both hemispheres. In response, less than half of modern angiosperm families have members that evolved specific adaptations to cold seasonal climates, including cold acclimation, freezing tolerance, endodormancy, and vernalization responsiveness. Despite compelling evidence for multiple independent origins, the level of genetic constraint on the evolution of adaptations to seasonal cold is not well understood. However, the recent increase in molecular genetic studies examining the response of model and crop species to seasonal cold offers new insight into the evolutionary lability of these traits. This insight has major implications for our understanding of complex trait evolution, and the potential role of local adaptation in response to past and future climate change. In this review, we discuss the biochemical, morphological, and developmental basis of adaptations to seasonal cold, and synthesize recent literature on the genetic basis of these traits in a phylogenomic context. We find evidence for multiple genetic links between distinct physiological responses to cold, possibly reinforcing the coordinated expression of these traits. Furthermore, repeated recruitment of the same or similar ancestral pathways suggests that land plants might be somewhat pre-adapted to dealing with temperature stress, perhaps making inducible cold traits relatively easy to evolve.

  14. 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.

  15. An Integrated Approach (TRMM, MODIS, AVHRR, and Rain Gauge) for Assessment of Precipitation in Arid Areas: A Case Study from the Eastern Desert of Egypt

    NASA Astrophysics Data System (ADS)

    Milewski, A.; Sultan, M.; Becker, R.; Abdeldayem, A. W.

    2005-05-01

    Water shortages are major obstacles to sustainable development and a cause for poverty in arid and semiarid countries. In these domains often the case, the appropriate systems (precipitation networks) that are needed to estimate precipitation on a regional scale are absent. We developed an integrated methodology to address this problem using data sets that are available on a global scale. We developed an integrated approach to improve estimates of renewable water resources. The approach utilizes the following data sets (1) TRMM-3B42V6 to extract 3-hourly precipitation data, (2) daily AVHRR data for soil moisture and NDVI measurements, (3) METEOSAT-7 for monitoring cloud movement, and (4) rain gauge data for ground truthing. Our approach entails identifying rain storm events from TRMM data. Following the identification of the events, we verify the individual events by examining the cloud patterns, examining the temporal variations in NDVI and soil moisture, and through comparisons with rain gauge data. For the year 1998, we examined in a GIS environment the following: TRMM scenes (2920 scenes), AVHRR data (365 scenes), METEOSAT (8760 scenes), and available rain gauge data. Findings indicate: (1) A general correspondence between TRMM data and rain gauge data, (2) A progressive increase in NDVI measurements following precipitation (peak after ~10 days), and (3) instantaneous increase in soil moisture. A similar (yet with a more restricted data set) exercise was conducted in year 1994, where a major flood occurred.

  16. 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.

  17. 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

  18. 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.

  19. Dynamics of the Chesapeake Bay outflow plume: Realistic plume simulation and its seasonal and interannual variability

    NASA Astrophysics Data System (ADS)

    Jiang, Long; Xia, Meng

    2016-02-01

    The three-dimensional unstructured-grid Finite Volume Coastal Ocean Model (FVCOM) was implemented for Chesapeake Bay and its adjacent coastal ocean to delineate the realistic Chesapeake Bay outflow plume (CBOP) as well as its seasonal and interannual variability. Applying the appropriate horizontal and vertical resolution, the model exhibited relatively high skill in matching the observational water level, temperature, and salinity from 2003 to 2012. The simulated surface plume structure was verified by comparing output to the HF radar current measurements, earlier field observations, and the MODIS and AVHRR satellite imagery. According to the orientation, shape, and size of the CBOP from both model snapshots and satellite images, five types of real-time plume behavior were detected, which implied strong regulation by wind and river discharge. In addition to the episodic plume modulation, horizontal and vertical structure of the CBOP exhibited variations on seasonal and interannual temporal scales. Seasonally, river discharge with a 1 month lag was primarily responsible for the surface plume area variation, while the plume thickness was mainly correlated to wind magnitude. On the interannual scale, river discharge was the predominant source of variability in both surface plume area and depth; however, the southerly winds also influenced the offshore plume depth. In addition, large-scale climate variability, such as the North Atlantic Oscillation, could potentially affect the plume signature in the long term by altering wind and upwelling dynamics, underlining the need to understand the impacts of climate change on buoyant plumes, such as the CBOP.

  20. 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...

  1. 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

  2. Sorting Out Seasonal Allergies

    MedlinePlus

    ... Back to Health Library Sorting Out Seasonal Allergies Sneezing, runny nose, nasal congestion. Symptoms of the common ... simple preventive measures, you can help reduce your sneezing, coughing and general stuffiness, according to Pamela A. ...

  3. 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.

  4. Improving distributed hydrologic modeling and global land cover data

    NASA Astrophysics Data System (ADS)

    Broxton, Patrick

    -added Land Cover products (land cover type and maximum green vegetation fraction; MGVF) are developed and evaluated. The new products are good successors to current generation land cover products that are used in global models (many of which rely on 20 year old AVHRR land cover data from a single year) because they are based on 10 years of recent MODIS data. There is substantial spurious interannual variability in the MODIS land cover type data, and the MGVF product can vary substantially from year to year depending on climate conditions, suggesting the importance of using climatologies for land cover data. The new land cover type climatology also agrees better with validation sites, and the MGVF climatology is more consistent with other measures of vegetation (e.g. Leaf Area Index) than the older land cover data.

  5. Past climate and land cover change impacts on streamflow in upper Yellow River Basin, China

    NASA Astrophysics Data System (ADS)

    Cuo, L.

    2011-12-01

    Upper Yellow River Basin is located in the northern Tibetan Plateau. More than half of the annual total yield of the entire Yellow River is contributed from the Upper Yellow River Basin. Like the other part of the world, upper Yellow River Basin has been experiencing climate change. Also, sponsored by China Central Government, local Provincial government launched "Returning Farm Land and Grazing Land to Grasses and Forests" in 2000 and "Three Rivers' Source Region Environmental Protection Project" in 2005 to conserve ecosystem in the source region of the Yellow River. Understanding climate and land cover change impacts on the streamflow in the upper Yellow River Basin is essential for local and downstream ecosystems. This study utilized a large scale hydrology model - Variable Infiltration Capacity model to investigate both climate and land cover change impacts on the streamflow in the upper Yellow River Basin. Past 50-year of climate data, and 1994 and 2004 land cover data obtained from NOAA AVHRR and MODIS satellites were used in the study. 1994 and 2004 were the years before and after the execution of environmental protection programs. The investigation revealed that warmer climate has resulted in lower annual total streamflow, higher spring peak but lower summer flow. After launching the ecosystem conservation programs, streamflow has decreased. In the source region of the Yellow River, climate change impact dominates over land cover change impact.

  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. Variability of the seasonally integrated normalized difference vegetation index across the north slope of Alaska in the 1990s

    USGS Publications Warehouse

    Stow, D.; Daeschner, S.; Hope, A.; Douglas, D.; Petersen, A.; Myneni, R.; Zhou, L.; Oechel, W.

    2003-01-01

    The interannual variability and trend of above-ground photosynthetic activity of Arctic tundra vegetation in the 1990s is examined for the north slope region of Alaska, based on the seasonally integrated normalized difference vegetation index (SINDVI) derived from local area coverage (LAC) National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data. Smaller SINDVI values occurred during the three years (1992-1994) following the volcanic eruption of Mt Pinatubo. Even after implementing corrections for this stratospheric aerosol effect and adjusting for changes in radiometric calibration coefficients, an apparent increasing trend of SINDVI in the 1990s is evident for the entire north slope. The most pronounced increase was observed for the foothills physiographical province.

  8. Seasonal sediment and nutrient transport patterns.

    PubMed

    Moriasi, D N; Guzman, J A; Steiner, J L; Starks, P J; Garbrecht, J D

    2014-07-01

    It is essential to understand sediment and nutrient sources and their spatial and temporal patterns to design effective mitigation strategies. However, long-term data sets to determine sediment and nutrient loadings are scarce and expensive to collect. The goal of this study was to determine seasonal patterns of suspended sediment (SS), total N (TN), and total P (TP) concentrations and loadings for three USGS gauge sites located at the Fort Cobb Reservoir Experimental watershed (FCREW) located in southwestern Oklahoma. Measured instantaneous discharge, SS, TN, and TP concentration data were used to develop lognormal water quality-discharge relationships. The water quality-discharge relationships were used to generate estimated seasonal concentrations and loads based on hourly or 30-min interval discharge. The estimated concentrations and loads were used to determine seasonal patterns for SS, TN, and TP relative to the respective state water quality criteria. Decreasing and increasing monotonic trends were observed for the seasonal time series loads for all three sites, but they were insignificant based on the Spearman test (α = 0.05). The largest loads were estimated during the wet springs and summers. The study SS, TN, and TP target concentrations were exceeded in one season or another. The study results showed that the priority locations to implement the TN and TP conservation practices were the Lake Creek and Willow Creek subwatersheds during the winter and spring seasons. Common practices to mitigate nutrients and suspended sediments include nutrient management, no-till, conversion of cultivated land to pasture, riparian buffers, and animal exclusion.

  9. Seasonal sediment and nutrient transport patterns.

    PubMed

    Moriasi, D N; Guzman, J A; Steiner, J L; Starks, P J; Garbrecht, J D

    2014-07-01

    It is essential to understand sediment and nutrient sources and their spatial and temporal patterns to design effective mitigation strategies. However, long-term data sets to determine sediment and nutrient loadings are scarce and expensive to collect. The goal of this study was to determine seasonal patterns of suspended sediment (SS), total N (TN), and total P (TP) concentrations and loadings for three USGS gauge sites located at the Fort Cobb Reservoir Experimental watershed (FCREW) located in southwestern Oklahoma. Measured instantaneous discharge, SS, TN, and TP concentration data were used to develop lognormal water quality-discharge relationships. The water quality-discharge relationships were used to generate estimated seasonal concentrations and loads based on hourly or 30-min interval discharge. The estimated concentrations and loads were used to determine seasonal patterns for SS, TN, and TP relative to the respective state water quality criteria. Decreasing and increasing monotonic trends were observed for the seasonal time series loads for all three sites, but they were insignificant based on the Spearman test (α = 0.05). The largest loads were estimated during the wet springs and summers. The study SS, TN, and TP target concentrations were exceeded in one season or another. The study results showed that the priority locations to implement the TN and TP conservation practices were the Lake Creek and Willow Creek subwatersheds during the winter and spring seasons. Common practices to mitigate nutrients and suspended sediments include nutrient management, no-till, conversion of cultivated land to pasture, riparian buffers, and animal exclusion. PMID:25603081

  10. [Variability of vegetation growth season in different latitudinal zones of North China: a monitoring by NOAA NDVI and MSAVI].

    PubMed

    Wang, Hong; Li, Xiaobing; Han, Ruibo; Ge, Yongqin

    2006-12-01

    In this study, North China was latitudinally divided into five zones, i.e., 32 degrees - 36 degrees N (Zone I), 36 degrees - 40 degrees N (Zone II), 40 degrees - 44 degrees N (Zone III), 44 degrees - 48 degrees N (Zone IV) and 48 degrees - 52 degrees N (Zone V), and the NOAA/ AVHRR NDVI and MSAVI time-series images from 1982 to 1999 were smoothed with Savitzky-Golay filter algorithm. Based on the EOF analysis, the principal components of NDVI and MSAVI for the vegetations in different latitudinal zones of North China were extracted, the annual beginning and ending dates and the length of growth season in 1982 - 1999 were estimated, and the related parameters were linearly fitted, aimed to analyze the variability of vegetation growth season. The results showed that the beginning date of the growth season in different zones tended to be advanced, while the ending date tended to be postponed with increasing latitude. The length of the growth season was also prolonged, with the prolonging time exceeded 10 days.

  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 Brazilian state with the highest deforestation rate. Land use/land cover (LU/LC) changes have been reported to occur over large areas in this state due to the introduction of large-scale mechanized agriculture, extensive cattle ranching and uncontrolled slash-and-burn cultivation since the 1980s. In this study, we specifically aim at doing more detailed analysis for the causes of deforestation and savannization in this area, with special attention to agriculture and cattle ranching industry at the municipal district level in this state. Using GIS techniques and remotely-sensed NOAA/AVHRR data, we created 5-year Digital Vegetation Model Maps characterizing LU/LC features for every five years during the 1981-2001 periods using the PCA first components of the NOAA/AVHRR multi-spectral data. Our results make it clear that: (1) LU/LC changes among the phases are of the following 3 major types: degradation, recovery or transition; (2) The changes in LU/LC features are concomitant with the advance of cattle ranching and corn production activities toward the northern parts of the state, and with the expansion of soybean production in the central and western Mato Grosso; (3) Most of the agro-pastoral business are found in the southern Mato Grosso where about 46% of the state's deforestation during the 1981-2001 period occurred; (4) Rates of vegetation change are larger over non-inhabited areas (56%), especially in the north, than over the populated zones in the south (42%). Moreover, this work sheds some new light on the patterns of the changes in LU/LC features (deforestation and savannization) for each municipal district of Mato Grosso. In general, the following activities

  12. In Brief: Studying seasonal changes in wildlife

    NASA Astrophysics Data System (ADS)

    Showstack, Randy

    2008-12-01

    A new Wildlife Phenology Program is enlisting professional and citizen scientists to monitor and record seasonal wildlife events to help U.S. land managers understand and respond to climatic and other environmental changes. The Wildlife Society and the USA National Phenology Network (USA-NPN) announced the program on 2 December as the second phase in the network's phenology monitoring efforts; a plant phenology monitoring initiative began in 2007. Phenology is the study of seasonal timing of plant and animal life-cycle events, including migration, hibernation, and the leafing and fruiting of plants. Changes in the timing of such events are among the most sensitive biological responses to climate change. With spring events occurring earlier than previously in many regions of the world, some time-sensitive biological relationships are being disrupted.

  13. Seasonality of volcanic eruptions

    NASA Astrophysics Data System (ADS)

    Mason, B. G.; Pyle, D. M.; Dade, W. B.; Jupp, T.

    2004-04-01

    An analysis of volcanic activity during the last three hundred years reveals that volcanic eruptions exhibit seasonality to a statistically significant degree. This remarkable pattern is observed primarily along the Pacific "Ring of Fire" and locally at some individual volcanoes. Globally, seasonal fluctuations amount to 18% of the historical average monthly eruption rate. In some regions, seasonal fluctuations amount to as much as 50% of the average eruption rate. Seasonality principally reflects the temporal distribution of the smaller, dated eruptions (volcanic explosivity index of 0-2) that dominate the eruption catalog. We suggest that the pattern of seasonality correlates with the annual Earth surface deformation that accompanies the movement of surface water mass during the annual hydrological cycle and illustrate this with respect to global models of surface deformation and regional measurements of annual sea level change. For example, seasonal peaks in the eruption rate of volcanoes in Central America, the Alaskan Peninsula, and Kamchatka coincide with periods of falling regional sea level. In Melanesia, in contrast, peak numbers of volcanic eruptions occur during months of maximal regional sea level and falling regional atmospheric pressure. We suggest that the well-documented slow deformation of Earth's surface that accompanies the annual movements of water mass from oceans to continents acts to impose a fluctuating boundary condition on volcanoes, such that volcanic eruptions tend to be concentrated during periods of local or regional surface change rather than simply being distributed randomly throughout the year. Our findings have important ramifications for volcanic risk assessment and volcanoclimate feedback mechanisms.

  14. 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.

  15. An atlas of monthly mean distributions of SSMI surface wind speed, ARGOS buoy drift, AVHRR/2 sea surface temperature, and ECMWF surface wind components during 1991

    NASA Technical Reports Server (NTRS)

    Halpern, D.; Knauss, W.; Brown, O.; Wentz, F.

    1993-01-01

    The following monthly mean global distributions for 1991 are presented with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the advanced very high resolution radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) spacecraft; Cartesian components of free-drifting buoys which are tracked by the ARGOS navigation system on NOAA satellites; and Cartesian components of the 10-m height wind vector computed by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of monthly mean value, sampling distribution, and standard deviation value are displayed. Annual mean distributions are displayed.

  16. An atlas of monthly mean distributions of SSMI surface wind speed, ARGOS buoy drift, AVHRR/2 sea surface temperature, and ECMWF surface wind components during 1990

    NASA Technical Reports Server (NTRS)

    Halpern, D.; Knauss, W.; Brown, O.; Wentz, F.

    1993-01-01

    The following monthly mean global distributions for 1990 are proposed with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States (US) Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the advanced very high resolution radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) spacecraft; Cartesian components of free drifting buoys which are tracked by the ARGOS navigation system on NOAA satellites; and Cartesian components on the 10-m height wind vector computed by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of monthly mean value, sampling distribution, and standard deviation values are displayed. Annual mean distributions are displayed.

  17. A study on the Abruzzo 6 April 2009 earthquake by applying the RST approach to 15 years of AVHRR TIR observations

    NASA Astrophysics Data System (ADS)

    Lisi, M.; Filizzola, C.; Genzano, N.; Grimaldi, C. S. L.; Lacava, T.; Marchese, F.; Mazzeo, G.; Pergola, N.; Tramutoli, V.

    2010-02-01

    A self adaptive approach (RST, Robust Satellite Technique) has been proposed as a suitable tool for satellite TIR surveys in seismically active regions devoted to detect and monitor thermal anomalies possibly related to earthquake occurrence. In this work, RST approach has been applied to 15 years of AVHRR (Advanced Very High Resolution Radiometer) thermal infrared observations in order to study the 6 April 2009 Abruzzo earthquake. Preliminary results show clear differences in TIR anomalies occurrence during the periods used for validation (15 March-15 April 2009) and the one (15 March-15 April 2008) without earthquakes with ML≥4.5, used for confutation purposes. Quite clear TIR anomalies appears also to mark main tectonic lineaments during the preparatory phases of others, low magnitude(3.9

  18. What is the potential predictability of seasonal floods and droughts?

    SciTech Connect

    Phillips, T.J.

    1996-05-01

    The potential predictability (PP) of seasonal anomalies in continental hydrology may be thought of as the upper bound in forecast accuracy to be expected when the state of the oceans is known perfectly. We assume that the PP of the seasonal anomalies of continental hydrology is related to their degree of reproducibility in the presence of identical ocean boundary conditions across a number of simulations. In this study, the PP of seasonal anomalies in surface hydrological variables is estimated from an ensemble of 6 decadal integration of the ECMWF global atmospheric model coupled to a land-surface scheme which includes interception and transpiration by a simple vegetation canopy. Identical observed (AMIP) monthly sea surface temperatures are specified in each simulation, while the initial condition of the atmosphere and land surface are allowed to vary.

  19. The international geosphere biosphere programme data and information system global land cover data set (DIScover)

    USGS Publications Warehouse

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

    1997-01-01

    The International Geosphere Biosphere Programme Data and Information System (IGBP-DIS), through the mapping expertise of the U.S. Geological Survey and the European Commission's Joint Research Centre, recently guided the completion of a 1-km resolution global land cover data set from advanced very high resolution radiometer (AVHRR) data. The 1-km resolution land cover product, 'DISCover,' was based on monthly normalized difference vegetation index composites from 1992 and 1993. The development of DISCover was coordinated by the IGBP-DIS Land Cover Working Group as part of the IGBP-DIS Focus 1 activity. DISCover is a 17-class land cover data set based on the scientific requirements of IGBP elements. The mapping used unsupervised classification and postclassification refinement using ancillary data. The development of this data set was motivated by the need for global land cover data with higher spatial resolution, improved temporal specificity, and known classification accuracy. The completed DISCover data set will soon be validated to determine the accuracy of the global classification.

  20. Seasonal Change Investigations

    ERIC Educational Resources Information Center

    Smith, Wendy

    2009-01-01

    The author describes how the yearlong Investigating Seasonal Change at North Ponds project enabled third-grade students to take on the role of environmental scientists, recording and analyzing environmental data from ponds near their school. The students used an array of technological tools to explore and report on the causes and effects of…

  1. Weatherwords: The Hurricane Season.

    ERIC Educational Resources Information Center

    Buckley, Jim

    1991-01-01

    Information and anecdotes are provided for the following topics: the typical length of the hurricane season for the North Atlantic, Caribbean, and Gulf of Mexico; specifics related to the practice of naming hurricanes; and categorical details related to the Saffir/Simpson scale for rating hurricane magnitude. (JJK)

  2. Assessing hurricane season

    NASA Astrophysics Data System (ADS)

    Showstack, Randy

    2011-12-01

    With the official conclusion of the Atlantic hurricane season on 29 November, Irene was the only hurricane to strike the United States this year and the first one since Hurricane Ike made landfall in Texas in 2008, according to the National Oceanic and Atmospheric Administration (NOAA). Irene “broke the ‘hurricane amnesia’ that can develop when so much time lapses between landfalling storms,” indicated Jack Hayes, director of NOAA's National Weather Service. “This season is a reminder that storms can hit any part of our coast and that all regions need to be prepared each and every season.” During the season, there were 19 tropical storms, including 7 that became hurricanes; 3 of those were major hurricanes, of category 3 or above. The activity level was in line with NOAA predictions. The agency stated that Hurricane Irene was an example of improved accuracy in forecasting storm tracks: NOAA National Hurricane Center had accurately predicted the hurricane's landfall in North Carolina and its path northward more than 4 days in advance.

  3. Seasonal Influenza: An Overview

    ERIC Educational Resources Information Center

    Li, Christina; Freedman, Marian

    2009-01-01

    Seasonal influenza is a major cause of morbidity and mortality in the United States. It also has major social and economic consequences in the form of high rates of absenteeism from school and work as well as significant treatment and hospitalization costs. In fact, annual influenza epidemics and the resulting deaths and lost days of productivity…

  4. Arid Lands Biofuel

    NASA Astrophysics Data System (ADS)

    Neupane, B. P.

    2013-05-01

    Dependence on imported petroleum, as well as consequences from burning fossil fuels, has increased the demand for biofuel sources in the United States. Competition between food crops and biofuel crops has been an increasing concern, however, since it has the potential to raise prices for US beef and grain products due to land and resource competition. Biofuel crops that can be grown on land not suitable for food crops are thus attractive, but also need to produce biofuels in a financially sustainable manner. In the intermountain west of Nevada, biofuel crops need to survive on low-organic soils with limited precipitation when grown in areas that are not competing with food and feed. The plants must also yield an oil content sufficiently high to allow economically viable fuel production, including growing and harvesting the crop as well as converting the hydrocarbons into a liquid fuel. Gumweed (Grindelia squarrosa) currently appears to satisfy all of these requirements and is commonly observed throughout the west. The plant favors dry, sandy soils and is most commonly found on roadsides and other freshly disturbed land. A warm season biennial, the gumweed plant is part of the sunflower family and normally grows 2-4 feet high with numerous yellow flowers and curly leaves. The gumweed plant contains a large store of diterpene resins—most abundantly grindelic acid— similar to the saps found on pine trees that are used to make inks and adhesives. The dry weight harvest on the experimental field is 5130 lbs/acre. Whole plant biomass yields between 11-15% (average 13%) biocrude when subjected to acetone extraction whereas the buds alone contains up to a maximum of 35% biocrude when harvested in 'white milky' stage. The extract is then converted to basic form (sodium grindelate) followed by extraction of nonpolar constituents (mostly terpenes) with hexane and extracted back to ethyl acetate in acidified condition. Ethyl acetate is removed under vacuum to leave a dark

  5. Determining Land System Sustainability through a Land Architecture Approach: Example of Southern Yucatán (Invited)

    NASA Astrophysics Data System (ADS)

    Turner, B. L., II

    2009-12-01

    Sustainable land systems involve an array of tradeoffs, not only among ecosystem services, but between those services and human outcomes. These tradeoffs are affected by the architecture of the land system—the kind, size, pattern, and distribution of land uses and covers. Working towards a model capable of handling a full array of ecosystem services and human outcomes, the concept of land architecture is illustrated through a simplified land system in the seasonal tropical forests of the southern Yucatán where sustainability is sought through the competing goals of forest conservation-preservation and agricultural development, both cultivation and ranching. Land architecture and tradeoff impacts are compared between two communities emphasizing, respectfully, forest conservation-preservation and agriculture. The role of spatial scale is also illustrated. Vulnerability and resilience assessments of land systems should be enhanced through a land architecture approach.

  6. 26 CFR 1.175-4 - Definition of “land used in farming.”

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... before or at the same time as, the taxpayer makes the expenditures for soil or water conservation or for the prevention of the erosion of land. The taxpayer will be considered to have used the land in... land is idle because of the season, A makes certain soil and water conservation expenditures on...

  7. 26 CFR 1.175-4 - Definition of “land used in farming.”

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... before or at the same time as, the taxpayer makes the expenditures for soil or water conservation or for the prevention of the erosion of land. The taxpayer will be considered to have used the land in... land is idle because of the season, A makes certain soil and water conservation expenditures on...

  8. 26 CFR 1.175-4 - Definition of “land used in farming.”

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... before or at the same time as, the taxpayer makes the expenditures for soil or water conservation or for the prevention of the erosion of land. The taxpayer will be considered to have used the land in... land is idle because of the season, A makes certain soil and water conservation expenditures on...

  9. 26 CFR 1.175-4 - Definition of “land used in farming.”

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... before or at the same time as, the taxpayer makes the expenditures for soil or water conservation or for the prevention of the erosion of land. The taxpayer will be considered to have used the land in... land is idle because of the season, A makes certain soil and water conservation expenditures on...

  10. Viewing Seasonality in 8 Megacities at 4 Microns

    NASA Astrophysics Data System (ADS)

    Tomaszewska, M. A.; Kovalskyy, V.; Small, C.; Henebry, G. M.

    2013-12-01

    The middle infrared (MIR) spectral region, between 3 and 5 microns, offers a different perspective on cities. The MIR is the mixing zone of both emitted terrestrial radiation and reflected solar radiation. The relatively long wavelengths enable views of surfaces often obscured by anthropogenic haze. Green vegetation appears very dark in the MIR due to high absorption by leaf water. In contrast, building, roofing, and paving materials reflect much MIR and exposed soils and dried vegetation reflect even more. Thus, physics dictates a strong expression of seasonality in the MIR. But is there sufficient signal in the MIR to merit it as a complementary approach for characterizing urbanized areas and monitoring their dynamics? We have explored this question in a research effort that links two NASA Interdisciplinary Science projects on the effect of cities on the environment. We focused on 8 global megacities: Beijing, Cairo, Istanbul, Mexico, Moscow, Nairobi, New Delhi, and São Paulo. We used Level 1B calibrated radiance data from band 23 (~4 microns) of the Aqua MODIS during ascending passes in 2010. These 1 km data were processed to reduce cloud cover using monthly maximum value compositing into four sensor view zenith angle (VZA) classes: 0land covers: urban, agriculture, and 'natural' which included forest, savanna, or desert depending on the city. The seasonal patterns of MIR radiance varied, as expected, by latitude, with very strong seasonality effects at higher latitudes (Beijing, Cairo, Istanbul, Moscow), and lesser to minimal seasonal signals evident in the tropics (Mexico City, Nairobi, São Paulo). The monsoon imposed strong MIR seasonality in New Delhi. The strength of the seasonality was modulated by the VZA with smaller VZAs (<30°) showing higher signal-to-noise ratio (SNR) than larger VZAs (>30°). SNR was higher in the summer

  11. Seasonal aggression independent of seasonal testosterone in wood rats.

    PubMed Central

    Caldwell, G S; Glickman, S E; Smith, E R

    1984-01-01

    Levels of inter-male aggression, both in laboratory encounters and in the field, rise dramatically during the breeding season, closely paralleling the seasonal rise in testosterone. However, post-pubertally castrated males also show the dramatic seasonal rise in aggression in laboratory encounters with castrated opponents and show no decrement in fighting ability when paired with intact opponents, clearly demonstrating the independence of seasonal aggression from the proximate modulating effects of testosterone in wood rats. PMID:6591190

  12. Seasonal influenza: an overview.

    PubMed

    Li, Christina; Freedman, Marian

    2009-02-01

    Seasonal influenza is a major cause of morbidity and mortality in the United States. It also has major social and economic consequences in the form of high rates of absenteeism from school and work as well as significant treatment and hospitalization costs. In fact, annual influenza epidemics and the resulting deaths and lost days of productivity are estimated to cost US$10.4 billion in direct medical expenses and US$16.4 billion in lost potential earnings. Given the enormous burden of seasonal influenza and the important role that school-age children play in the cycle of disease, school nurses need to be knowledgeable about all aspects of this condition, including its clinical course and how it is transmitted; the range of options for preventing and treating the disease; and steps that can be taken to improve the rates of immunization against influenza. School nurses also can help by making sure that they themselves are vaccinated in a timely manner.

  13. A comparison of the IGBP DISCover and University of Maryland 1 km global land cover products

    USGS Publications Warehouse

    Hansen, M.C.; Reed, B.

    2000-01-01

    Two global 1 km land cover data sets derived from 1992-1993 Advanced Very High Resolution Radiometer (AVHRR) data are currently available, the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) DISCover and the University of Maryland (UMd) 1 km land cover maps. This paper makes a preliminary comparison of the methodologies and results of the two products. The DISCover methodology employed an unsupervised clustering classification scheme on a per-continent basis using 12 monthly maximum NDVI composites as inputs. The UMd approach employed a supervised classification tree method in which temporal metrics derived from all AVHRR bands and the NDVI were used to predict class membership across the entire globe. The DISCover map uses the IGBP classification scheme, while the UMd map employs a modified IGBP scheme minus the classes of permanent wetlands, cropland/natural vegetation mosaic and ice and snow. Global area totals of aggregated vegetation types are very similar and have a per-pixel agreement of 74%. For tall versus short/no vegetation, the per-pixel agreement is 84%. For broad vegetation types, core areas map similarly, while transition zones around core areas differ significantly. This results in high regional variability between the maps. Individual class agreement between the two 1 km maps is 49%. Comparison of the maps at a nominal 0.5 resolution with two global ground-based maps shows an improvement of thematic concurrency of 46% when viewing average class agreement. The absence of the cropland mosaic class creates a difficulty in comparing the maps, due to its significant extent in the DISCover map. The DISCover map, in general, has more forest, while the UMd map has considerably more area in the intermediate tree cover classes of woody savanna/ woodland and savanna/wooded grassland.

  14. On Landing Gear Stresses

    NASA Technical Reports Server (NTRS)

    Gentric, A.

    1956-01-01

    Information on landing gear stresses is presented on the following: vibratory phenomena, tangential forces applied to landing gear, fore and aft oscillations of landing gears, examples of fatigue failures, vibration calculations, and improvement of existing test equipment.

  15. Responses of Seasonal Precipitation Intensity to Global Warming

    NASA Astrophysics Data System (ADS)

    Lan, Chia-Wei; Lo, Min-Hui; Chou, Chia

    2016-04-01

    Under global warming, the water vapor increases with rising temperature at the rate of 7%/K. Most previous studies focus on the spatial differences of precipitation and suggest that wet regions become wetter and dry regions become drier. Our recent studies show a temporal disparity of global precipitation, which the wet season becomes wetter and dry season becomes drier; therefore, the annual range increases. However, such changes in the annual range are not homogeneous globally, and in fact, the drier trend over the ocean is much larger than that over the land, where the dry season does not become drier. Such precipitation change over land is likely because of decreased omega at 500hPa (more upward motion) in the reanalysis datasets from 1980 to 2013. The trends of vertical velocity and moist static energy profile over the increased precipitation regions become more unstable. The instability is most likely attributed to the change in specific humility below 400hPa. Further, we will use Coupled Model Intercomparison Project Phase 5 (CMIP5) archives to investigate whether the precipitation responses in dry season are different between the ocean and land under global warming.

  16. Seasonal water storage and delayed evapotranspiration across continents: Patterns and drivers

    NASA Astrophysics Data System (ADS)

    Kuppel, Sylvain; Fan, Ying; Jobbagy, Esteban

    2016-04-01

    Storage and delayed evapotranspiration (ET) of precipitation (P) inputs by land ecosystems is critical regulating the timing and stability of plant production and the multiple ecological and economic processes that it supports. The extent to which actual ET (AET) can decouple from P inputs depends on the ecohydrologic system capacity to store water. This decoupling and its associated storage requirement can be particularly relevant at the seasonal scale in regions where, for instance, rainfalls are highly seasonal and/or P and potential ET (PET) are seasonally out of phase. Focusing on the 2003-2010 period, we explore, first, where on Earth this decoupling is likely to occur from a climate perspective by assessing the magnitude and duration of the expected seasonal land water transfers. These climate-based predictions are then compared with independent evidence derived from satellite observations of vegetation activity (MODIS) and water storage (GRACE), together with datasets of terrain attributes. We assess how land surface processes alter the "potential" seasonal hydrologic buffer provided by the local climatic conditions, in terms of volume and residence time. This analysis helps outlining the expected seasonal response of the land water cycle in the frame of likely climate and land use changes.

  17. The Role of Suomi NPP VIIRS Data in Land Science and Applications.

    NASA Astrophysics Data System (ADS)

    Justice, C. O.; Csiszar, I. A.; Roman, M. O.; Vermote, E.

    2014-12-01

    The current Suomi-NPP mission was designed as a bridging mission to the Joint Polar Satellite System (JPSS) next-generation, operational satellites. The VIIRS instrument on-board Suomi-NPP provides continuity with NASA's Earth Observing System Moderate-resolution Imaging Spectroradiometer (MODIS) observations and a much-needed replacement of the long-serving, operational NOAA Advanced Very High Resolution Radiometer (AVHRR) system, to meet the expanding needs of Earth Science and Applications of Societal Benefit. Post-launch evaluation has proven the instrument to be excellent for land observations and capable of providing measurement continuity with MODIS. This provides a critical contribution to the scientific study of global change. Several regions of the World are undergoing rapid land transformations, driven by economic development and population growth. In addition, changes in climate conditions are resulting in ecosystem responses and changes in land cover and land use. Long-term, systematic observations of the global land surface at coarse resolution enable detection, monitoring and characterization of such changes to the land surface. A suite of Land environmental data records (EDRs) from the VIIRS, are being developed by NOAA to meet operational data needs, primarily for the National Weather Service (e.g., Albedo, Land Surface Temperature, Fractional Vegetation Cover, Surface Type, Snow and Ice Monitoring). Scientists funded by NOAA and NASA, have been evaluating and validating these products. Based on these evaluations, NASA is embarking on a program to develop enhanced and additional products to provide continuity with MODIS to meet the needs of the global change science community. In addition, and as with MODIS, data from the VIIRS can be used as input to a number of practical applications of societal benefit and the associated decision support systems. For example, progress with VIIRS data is being made in the areas of fire and agricultural monitoring

  18. Development of high resolution land surface parameters for the Community Land Model

    NASA Astrophysics Data System (ADS)

    Ke, Y.; Leung, L. R.; Huang, M.; Coleman, A. M.; Li, H.; Wigmosta, M. S.

    2012-06-01

    There is a growing need for high-resolution land surface parameters as land surface models are being applied at increasingly higher spatial resolution offline as well as in regional and global models. The default land surface parameters for the most recent version of the Community Land Model (i.e. CLM 4.0) are at 0.5° or coarser resolutions, released with the model from the National Center for Atmospheric Research (NCAR). Plant Functional Types (PFTs), vegetation properties such as Leaf Area Index (LAI), Stem Area Index (SAI), and non-vegetated land covers were developed using remotely-sensed datasets retrieved in late 1990's and the beginning of this century. In this study, we developed new land surface parameters for CLM 4.0, specifically PFTs, LAI, SAI and non-vegetated land cover composition, at 0.05° resolution globally based on the most recent MODIS land cover and improved MODIS LAI products. Compared to the current CLM 4.0 parameters, the new parameters produced a decreased coverage by bare soil and trees, but an increased coverage by shrub, grass, and cropland. The new parameters result in a decrease in global seasonal LAI, with the biggest decrease in boreal forests; however, the new parameters also show a large increase in LAI in tropical forest. Differences between the new and the current parameters are mainly caused by changes in the sources of remotely sensed data and the representation of land cover in the source data. The new high-resolution land surface parameters have been used in a coupled land-atmosphere model (WRF-CLM) applied to the western US to demonstrate their use in high-resolution modeling. Future work will include global offline CLMsimulations to examine the impacts of source data resolution and subsequent land parameter changes on simulated land surface processes.

  19. Potential and challenges of NDVI-based studies for detecting and monitoring land degradation and rehabilitation (Invited)

    NASA Astrophysics Data System (ADS)

    Herrmann, S. M.

    2009-12-01

    Providing the longest record of a continuous and consistently processed indicator of green vegetation, the Normalized Difference Vegetation Index (NDVI) from the AVHRR sensor has formed the basis of many scientific studies and applied vegetation monitoring programs. Positive NDVI trends since 1982 have suggested increases in biomass across the Sahel, paralleled by, and in some places even exceeding, increases in rainfall. Interpretation of the observed trends with respect to processes of land degradation and land rehabilitation, however, remains challenging at the coarse spatial resolution of this dataset. Attempts to better exploit the information content of the NDVI for obtaining a more detailed understanding of vegetation - rainfall relationships and the role of land management include: (1) analyzing finer resolution NDVI and gridded rainfall datasets which better match the scales at which land degradation and rehabilitation take place, (2) deriving vegetation phenological metrics from annual NDVI curves and assessing their sensitivities to rainfall metrics in order to distinguish between faster metrics driven primarily by rainfall variability and slower metrics potentially indicative of land cover changes, and (3) stratifying the study area by land cover and known management regimes. Findings from a 5x5 degree Sahelian-Soudanian study site covering parts of Burkina Faso and Mali illustrate potential and challenges of these approaches related to the complexity of cause-and-effect relationships that govern vegetation dynamics and to the need of reconciling the scales of analysis dictated by available NDVI datasets with those ideally required by the management questions at hand.

  20. Advanced Very High Resolution Radiometer (AVHRR) data evaluation for use in monitoring vegetation. Volume 1: Channels 1 and 2

    NASA Technical Reports Server (NTRS)

    Horvath, N. C.; Gray, T. I.; Mccrary, D. G. (Principal Investigator)

    1982-01-01

    Data from the National Oceanic and Atmospheric Administration satellite system (NOAA-6 satellite) were analyzed to study their nonmeteorological uses. A file of charts, graphs, and tables was created form the products generated. It was found that the most useful data lie between pixel numbers 400 and 2000 on a given scan line. The analysis of the generated products indicates that the Gray-McCrary Index can discern vegetation and associated daily and seasonal changes. The solar zenith-angle correction used in previous studies was found to be a useful adjustment to the index. The METSAT system seems best suited for providing large-area analyses of surface features on a daily basis.

  1. The Response of African Land Surface Phenology to Large Scale Climate Oscillations

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

    Variations in agricultural production due to rainfall and temperature fluctuations are a primary cause of food insecurity on the African continent. Analysis of changes in phenology can provide quantitative information on the effect of climate variability on growing seasons in agricultural regions. Using a robust statistical methodology, we describe the relationship between phenology metrics derived from the 26 year AVHRR NDVI record and the North Atlantic Oscillation index (NAO), the Indian Ocean Dipole (IOD), the Pacific Decadal Oscillation (PDO), and the Multivariate ENSO Index (MEI). We map the most significant positive and negative correlation for the four climate indices in Eastern, Western and Southern Africa between two phenological metrics and the climate indices. Our objective is to provide evidence of whether climate variability captured in the four indices has had a significant impact on the vegetative productivity of Africa during the past quarter century. We found that the start of season and cumulative NDVI were significantly affected by large scale variations in climate. The particular climate index and the timing showing highest correlation depended heavily on the region examined. In Western Africa the cumulative NDVI correlates with PDO in September-November. In Eastern Africa the start of the June-October season strongly correlates with PDO in March-May, while the PDO in December-February correlates with the start of the February-June season. The cumulative NDVI over this last season relates to the MEI of March-May. For Southern Africa, high correlations exist between SOS and NAO of September-November, and cumulative NDVI and MEI of March-May. The research shows that climate indices can be used to anticipate late start and variable vigor in the growing season of sensitive agricultural regions in Africa.

  2. Simulated effects of cropland expansion on seasonal temperatures over China

    NASA Astrophysics Data System (ADS)

    Xiong, Zhe

    Human activities result in deforestation, expansion of cropland, grassland degradation, urbanization and other large-scale land use/cover change; among these, cropland expansion is one of the most important processes. To understand the effects of cropland expansion on seasonal temperatures over China, two 21-year simulations (spanning January 1, 1980-December 31, 2000), using the Regional Integrated Environmental Model System (RIEMS 2.0), were performed. The two simulations comprised current realistic land use/cover patterns and the previous vegetation cover without crop expansion, to investigate the impact of crop expansion on seasonal temperatures over China. The results showed that due to cropland expansion: (1) the most obvious changes occurred in the maximum temperatures, followed by the mean surface air temperatures, and the minimum temperatures were the least affected; (2) the summer mean maximum temperatures decreased in most parts of eastern China, and the temperatures changed significantly in most parts of northeast China, north China and central China (p < 0.05); (3) the surface air temperatures, maximum temperatures and minimum temperatures in summer decreased in the different regions by between -0.03 and -0.76 °C (the greatest temperature changes occurred in southwest China, and the smallest were in northeast China); (4) the net radiation flux and latent heat flux increased, while the sensible flux decreased, when semi-desert vegetation was replaced by dry land crops, in both summer and winter seasons, and the converse occurred when irrigated crops were replaced by dry land crops. In addition, the net radiation flux and sensible heat flux decreased, and the latent heat flux increased when short grass and tall grass were replaced dry land crops, as well as when dry land crops were replaced by irrigated crops.

  3. The Making of National Seasonal Wildfire Outlooks

    NASA Astrophysics Data System (ADS)

    Garfin, G. M.; Brown, T. J.

    2015-12-01

    Bridging the gap between research-based experiments and fully operational products has been likened to crossing the valley of death. In this talk, we document the development of pre-season fire potential outlooks, informed by seasonal climate predictions, through a long-term collaboration between NOAA RISA teams, the Program for Climate, Ecosystem and Fire Applications (Desert Research Institute), the National Interagency Fire Center's Predictive Services program and multiple collaborators. To transition experimental outlooks into a sustained, monthly operational product, we co-developed a temporary institution, the National Seasonal Assessment Workshops, as a platform for cross-disciplinary knowledge exchange, training, and experimentation in consensus forecast processes and product development. In our retrospective evaluation of the process, we identified several factors that supported the transition from research to operations. These include: the development of new institutions; focus on a geographic scale commensurate with the needs of federal and state land management agencies; participatory and deliberative engagements; cooperation by many partners with perspectives on the connections between climate and wildland fire management; and iterative engagement sustained by funding and human resource commitments from the key partners. Through co-production of the outlooks and the institution, we created a cross-disciplinary community of practice, thus, increasing the capacity of fire management practitioners to use climate information in decision making. This experiment in developing a collaborative climate service was not an unqualified success. For example, while practitioners almost always *consult* official probabilistic climate forecasts, based on the output from dynamical and statistical models, they sometimes *act* on information from self-constructed forecasts, based on analysis of analogue years. We recommend research to further examine the distribution and

  4. High Resolution Land Surface Modeling with the next generation Land Data Assimilation Systems

    NASA Astrophysics Data System (ADS)

    Kumar, S. V.; Eylander, J.; Peters-Lidard, C.

    2005-12-01

    Knowledge of land surface processes is important to many real-world applications such as agricultural production, water resources management, and flood predication. The Air Force Weather Agency (AFWA) has provided the USDA and other customers global soil moisture and temperature data for the past 30 years using the agrometeorological data assimilation model (now called AGRMET), merging atmospheric data. Further, accurate initialization of land surface conditions has been shown to greatly influence and improve weather forecast model and seasonal-to-interannual climate predictions. The AFWA AGRMET model exploits real time precipitation observations and analyses, global forecast model and satellite data to generate global estimates of soil moisture, soil temperature and other land surface states at 48km spatial resolution. However, to truly address the land surface initialization and climate prediction problem, and to mitigate the errors introduced by the differences in spatial scales of models, representations of land surface conditions need to be developed at the same fine scales such as that of cloud resolving models. NASA's Goddard Space Flight Center has developed an offline land data assimilation system known as the Land Information System (LIS) capable of modeling land atmosphere interactions at spatial resolutions as fine as 1km. LIS provides a software architecture that integrates the use of the state of the art land surface models, data assimilation techniques, and high performance computing and data management tools. LIS also employs many high resolution surface parameters such as the NASA Earth Observing System (EOS)-era products. In this study we describe the development of a next generation high resolution land surface modeling and data assimilation system, combining the capabilities of LIS and AGRMET. We investigate the influence of high resolution land surface data and observations on the land surface conditions by comparing with the operational AGRMET

  5. Assessing the use of global land cover data for guiding large area population distribution modelling.

    PubMed

    Linard, Catherine; Gilbert, Marius; Tatem, Andrew J

    2011-10-01

    Gridded population distribution data are finding increasing use in a wide range of fields, including resource allocation, disease burden estimation and climate change impact assessment. Land cover information can be used in combination with detailed settlement extents to redistribute aggregated census counts to improve the accuracy of national-scale gridded population data. In East Africa, such analyses have been done using regional land cover data, thus restricting application of the approach to this region. If gridded population data are to be improved across Africa, an alternative, consistent and comparable source of land cover data is required. Here these analyses were repeated for Kenya using four continent-wide land cover datasets combined with detailed settlement extents and accuracies were assessed against detailed census data. The aim was to identify the large area land cover dataset that, combined with detailed settlement extents, produce the most accurate population distribution data. The effectiveness of the population distribution modelling procedures in the absence of high resolution census data was evaluated, as was the extrapolation ability of population densities between different regions. Results showed that the use of the GlobCover dataset refined with detailed settlement extents provided significantly more accurate gridded population data compared to the use of refined AVHRR-derived, MODIS-derived and GLC2000 land cover datasets. This study supports the hypothesis that land cover information is important for improving population distribution model accuracies, particularly in countries where only coarse resolution census data are available. Obtaining high resolution census data must however remain the priority. With its higher spatial resolution and its more recent data acquisition, the GlobCover dataset was found as the most valuable resource to use in combination with detailed settlement extents for the production of gridded population datasets

  6. Fire Monitoring - The use of medium resolution satellites (AVHRR, MODIS, TET) for long time series processing and the implementation in User Driven Applications and Services

    NASA Astrophysics Data System (ADS)

    Fuchs, E.-M.; Stein, E.; Strunz, G.; Strobl, C.; Frey, C.

    2015-04-01

    This paper introduces fire monitoring works of two different projects, namely TIMELINE (TIMe Series Processing of Medium Resolution Earth Observation Data assessing Long -Term Dynamics In our Natural Environment) and PHAROS (Project on a Multi-Hazard Open Platform for Satellite Based Downstream Services). It describes the evolution from algorithm development from in applied research to the implementation in user driven applications and systems. Concerning TIMELINE, the focus of the work lies on hot spot detection. A detailed description of the choice of a suitable algorithm (round robin approach) will be given. Moreover, strengths and weaknesses of the AVHRR sensor for hot spot detection, a literature review, the study areas and the selected approach will be highlighted. The evaluation showed that the contextual algorithm performed best, and will therefore be used for final implementation. Concerning the PHAROS project, the key aspect is on the use of satellite-based information to provide valuable support to all phases of disaster management. The project focuses on developing a pre-operational sustainable service platform that integrates space-based EO (Earth Observation), terrestrial sensors and communication and navigation assets to enhance the availability of services and products following a multi-hazard approach.

  7. [Relationship Between Agricultural Land and Water Quality of Inflow River in Erhai Lake Basin].

    PubMed

    Pang, Yan; Xiang, Song; Chu, Zhao-sheng; Xue, Li-qiang; Ye, Bi-bi

    2015-11-01

    We studied the relationship between agricultural land and water quality of inflow river in Erhai Lake Basin, by means of spatial and statistical analysis, from the perspective of comprehensive agricultural land and the area percentage of different types of agricultural land. The obtained results indicated that inflow water quality showed a significant spatial difference, the inflow TP pollution in the western inflow rivers of Erhai Basin was serious. The major pollution indicators in the northern and southern inflow rivers (except for D3) were organic matter and nitrogen. The area percentage of agricultural land had a significantly indicative effect on the water quality of inflow river. The area percentage of comprehensive agricultural land negatively correlated with permanganate index, NH4(+) -N, TN and TP contents in wet season, the correlation coefficients were - 0.859, - 0.565, - 0.693, - 0.181. It negatively correlated with permanganate index and NH4(+) -N content in dry season, the correlation coefficients were - 0.384, - 0.328. It had positive relationships with and TN, TP content in dry season, the correlation coefficients were 0.221 and 0.146. The area percentage of different types of agricultural land had an obviously indicative effect on the inflow water quality. Farmland positively correlated with TN and TP contents both in wet and dry seasons. The correlation coefficients between farmland and TN, TP were 0.252, 0.581 in rainy season and were 0.149, 0.511 in dry season. It had positive and negative relationships with permanganate index, NH4(+) -N content in wet season and dry season, respectively. The correlation coef