The Enhanced NOAA Global Land Dataset from the Advanced Very High Resolution Radiometer

The Enhanced NOAA Global Land Dataset from the Advanced Very High Resolution Radiometer Global mapped data of reflected radiation in the visible (0.63 m) and near-infrared (0.85 m) wavebands of the Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration satellites have been collected as the global vegetation index (GVI) dataset since 1982. Its primary objective has been vegetation studies (hence its title) using the normalized difference vegetation index (NDVI) calculated from the visible and near-IR data. The second-generation GVI, which started in April 1985, has also included brightness temperatures in the thermal IR (11 and 12 m) and the associated observationillumination geometry. This multiyear, multispectral, multisatellite dataset is a unique tool for global land studies. At the same time, it raises challenging remote sensing and data management problems with respect to uniformity in time, enhancement of signal-to-noise ratio, retrieval of geophysical parameters from satellite radiances, and large data volumes. The authors explored a four-level generic structure for processing AVHRR datathe first two levels being remote sensing oriented and the other two directed at environmental studiesand will describe the present status of each level. The uniformity of GVI data was improved by applying an updated calibration, and noise was reduced by applying a more accurate cloud-screening procedure. In addition to the enhanced weekly data (recalibrated with appended quality/cloud flags), the available land environmental products include monthly 0.15-resolution global maps of top-of-theatmosphere visible and near-IR reflectances, NDVI, brightness temperatures, and a precipitable water index for April 1985September 1994. For the first time, a 5-yr monthly climatology (means and standard deviations) of each quantity was produced. These products show strong potential for detecting and analyzing largescale spatial and seasonal land variability. The data can also be used for educational purposes to illustrate the annual global dynamics of vegetation cover, albedo, temperature, and water vapor. Development of the GVI data product contributes to the activities of the International GeosphereBiosphere Programme and Global Energy and Water Cycle Experiment and, in particular, to the International Satellite Land Surface Climatology Project. Monthly standardized anomalies of the GVI variables have been calculated for April 1985present and are routinely produced on UNIX workstations, thus providing a prototype land monitoring system. Standardized anomalies clearly indicate that strong signals at the land surface, such as droughts and floods and their teleconnections with such global environmental phenomena as El NioSouthern Oscillation, can be detected and analyzed. The monitoring of relatively small year-to-year variability is, however, contingent on the removal of residual trends/noise in GVI data, which are of the order of the analyzed effects. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bulletin of the American Meteorological Society American Meteorological Society

The Enhanced NOAA Global Land Dataset from the Advanced Very High Resolution Radiometer

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0477
D.O.I.
10.1175/1520-0477(1995)076<1141:TENGLD>2.0.CO;2
Publisher site
See Article on Publisher Site

Abstract

Global mapped data of reflected radiation in the visible (0.63 m) and near-infrared (0.85 m) wavebands of the Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration satellites have been collected as the global vegetation index (GVI) dataset since 1982. Its primary objective has been vegetation studies (hence its title) using the normalized difference vegetation index (NDVI) calculated from the visible and near-IR data. The second-generation GVI, which started in April 1985, has also included brightness temperatures in the thermal IR (11 and 12 m) and the associated observationillumination geometry. This multiyear, multispectral, multisatellite dataset is a unique tool for global land studies. At the same time, it raises challenging remote sensing and data management problems with respect to uniformity in time, enhancement of signal-to-noise ratio, retrieval of geophysical parameters from satellite radiances, and large data volumes. The authors explored a four-level generic structure for processing AVHRR datathe first two levels being remote sensing oriented and the other two directed at environmental studiesand will describe the present status of each level. The uniformity of GVI data was improved by applying an updated calibration, and noise was reduced by applying a more accurate cloud-screening procedure. In addition to the enhanced weekly data (recalibrated with appended quality/cloud flags), the available land environmental products include monthly 0.15-resolution global maps of top-of-theatmosphere visible and near-IR reflectances, NDVI, brightness temperatures, and a precipitable water index for April 1985September 1994. For the first time, a 5-yr monthly climatology (means and standard deviations) of each quantity was produced. These products show strong potential for detecting and analyzing largescale spatial and seasonal land variability. The data can also be used for educational purposes to illustrate the annual global dynamics of vegetation cover, albedo, temperature, and water vapor. Development of the GVI data product contributes to the activities of the International GeosphereBiosphere Programme and Global Energy and Water Cycle Experiment and, in particular, to the International Satellite Land Surface Climatology Project. Monthly standardized anomalies of the GVI variables have been calculated for April 1985present and are routinely produced on UNIX workstations, thus providing a prototype land monitoring system. Standardized anomalies clearly indicate that strong signals at the land surface, such as droughts and floods and their teleconnections with such global environmental phenomena as El NioSouthern Oscillation, can be detected and analyzed. The monitoring of relatively small year-to-year variability is, however, contingent on the removal of residual trends/noise in GVI data, which are of the order of the analyzed effects.

Journal

Bulletin of the American Meteorological SocietyAmerican Meteorological Society

Published: Jul 20, 1995

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