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.