Estimation of seasonal dynamics of pasture and crop productivity in Kazakhstan using NOAA/AVHRR data

Anatoly Gitelson, Felix Kogan, Lev Spivak, Edige Zakarin, Lubov Lebed

Research output: Contribution to conferencePaper

5 Scopus citations

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.

Original languageEnglish (US)
Pages209-211
Number of pages3
StatePublished - 1996
EventProceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4) - Lincoln, NE, USA
Duration: May 28 1996May 31 1996

Other

OtherProceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4)
CityLincoln, NE, USA
Period5/28/965/31/96

ASJC Scopus subject areas

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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    Gitelson, A., Kogan, F., Spivak, L., Zakarin, E., & Lebed, L. (1996). Estimation of seasonal dynamics of pasture and crop productivity in Kazakhstan using NOAA/AVHRR data. 209-211. Paper presented at Proceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4), Lincoln, NE, USA, .