Estimation of Seasonal Dynamics of Pasture and Crop Productivity in Kazakhstan Using NOAA/AVHRR Data

Authors

Anatoly A. Gitelson, University of Nebraska - LincolnFollow
Felix Kogan, National Environmental Satellite Data and Information Service, National Oceanic and Atmospheric AdministrationFollow
Lev Spivak, Institute for Space Research, Academy of Sciences, Kazakhstan
Edige Zakarin, Institute for Space Research, Academy of Sciences, Kazakhstan
Lubov Lebed, National Meteorological Administration, Kazakhstan

Document Type

Article

Date of this Version

1996

Comments

Published in the Proceedings of the Geoscience and Remote Sensing Symposium, 1996. IGARSS '96: Remote Sensing for a Sustainable Future. DOI: 10.1109/IGARSS.1996.516293. Copyright 1996, IEEE. Used by permission. Pages 209-211, volume 1.

Abstract

Recently, NOAA developed the AVHRR-based Vegetation Condition Index (VCI) for drought monitoring. This index was used for estimating pasture and crop productivity in Kazakhstan. The results of VCI-derived vegetation conditions were compared with vegetation density, biomass and reflectance measured in different climatic and ecological zones with elevation from 200 to 700 m and a large range of the NDVI variation (over space and season) from 0.05 to 0.47. An estimation error of AVHRR-derived vegetation density was less than 16 per cent. First time it was shown that the VCI-derived vegetation condition data can be effectively used for quantitative assessments of both vegetation state and productivity (density and biomass) over large areas.