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

3 Citations (Scopus)

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 - Jan 1 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

Fingerprint

Advanced very high resolution radiometers (AVHRR)
AVHRR
Crops
pasture
Productivity
productivity
crop
vegetation
Biomass
Drought
biomass
NDVI
Error analysis
reflectance
drought
index
Monitoring
monitoring

ASJC Scopus subject areas

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

Cite this

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, .

Estimation of seasonal dynamics of pasture and crop productivity in Kazakhstan using NOAA/AVHRR data. / Gitelson, Anatoly; Kogan, Felix; Spivak, Lev; Zakarin, Edige; Lebed, Lubov.

1996. 209-211 Paper presented at Proceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4), Lincoln, NE, USA, .

Research output: Contribution to conferencePaper

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', Paper presented at Proceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4), Lincoln, NE, USA, 5/28/96 - 5/31/96 pp. 209-211.
Gitelson A, Kogan F, Spivak L, Zakarin E, Lebed L. Estimation of seasonal dynamics of pasture and crop productivity in Kazakhstan using NOAA/AVHRR data. 1996. Paper presented at Proceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4), Lincoln, NE, USA, .
Gitelson, Anatoly ; Kogan, Felix ; Spivak, Lev ; Zakarin, Edige ; Lebed, Lubov. / Estimation of seasonal dynamics of pasture and crop productivity in Kazakhstan using NOAA/AVHRR data. Paper presented at Proceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4), Lincoln, NE, USA, .3 p.
@conference{7d1b6eb2d3d5418ea936a233556a38db,
title = "Estimation of seasonal dynamics of pasture and crop productivity in Kazakhstan using NOAA/AVHRR data",
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.",
author = "Anatoly Gitelson and Felix Kogan and Lev Spivak and Edige Zakarin and Lubov Lebed",
year = "1996",
month = "1",
day = "1",
language = "English (US)",
pages = "209--211",
note = "Proceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4) ; Conference date: 28-05-1996 Through 31-05-1996",

}

TY - CONF

T1 - Estimation of seasonal dynamics of pasture and crop productivity in Kazakhstan using NOAA/AVHRR data

AU - Gitelson, Anatoly

AU - Kogan, Felix

AU - Spivak, Lev

AU - Zakarin, Edige

AU - Lebed, Lubov

PY - 1996/1/1

Y1 - 1996/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0029721017&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0029721017&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0029721017

SP - 209

EP - 211

ER -