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Kishan Singh Rawat Anil Kumar Mishra Rakesh Kumar Jitendra Singh

Abstract

This study describes the Vegetation Condition Index in the near-real-time with help of SPOT based Normalized Difference Vegetation Index (NDVI) for Agro climatic-region of India and gave the development pattern in last six year (2002-2007) over the study area of India using decadal time data set from SPOT satellite sensor for 2002-2007 time periods. The each Agro-climatic region of study, 1°x1° degree in area, part of India agro-climate regions, has been taken for analysis using remote sensing and Geographical Information System (RS and GIS)
methods, SPOT satellite sensor NDVI data, and from processed data set (geo-referenced data set), cut out 1°x1° degree of area by preparing a layers representing Agro-climatic region of India as base mapping units (BMU),The results indicated that NDVI index is only water stress over vegetation while VCI is an appropriate index for vegetation pattern monitoring over study area. As satellite observations provide better spatial and temporal coverage, the VCI based system will provide efficient tools for management of the improvement of agricultural planning. This system will serve as a prototype in the other parts of the world where ground observations are limited or not available.

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Keywords

Droughts, Drought indices, Drought severity, Remote sensing, Vegetation condition index

References
Burgan, R. E., Hartford R. A. and Eidenshink J. C. (1996). Using NDVI to assess departure from average greenness and its relation to fire business. Gen. Tech. Rep. INT-GTR- 333. Ogden, UT: US Department of Agriculture, Forest Service, Intermountain Research Station. pp 8.
Burgan, R. E.and Hartford, R. A. (1993). Monitoring vegetation greenness with satellite data. Gen. Tech. Rep. INT-297. Ogden, UT: US Department of Agriculture, Forest Service, Intermountain Research Station. pp 13.
Hardin, G. (1986). Cultural carrying capacity: A biological approach to human problems. Biological Science, 36:599-606.
Immerzeel,W.W., Quiroz, R. A. and Dejong, S. M. (2005). Understanding precipitation patterns and land use interaction in Tibet using harmonic analysis of SPOT VGTS10 NDVI time series. International Journal of Remote Sensing, 1-15
John, G., Yuan, D., Lunetta, R.S. and Elvidge, C.D. (1998). A change detection experiment using vegetation indices. Photogrammetric Engineering and Remote Sensing, 62:143-150.
Karabulut, M. (2003). An Examination of Relationships Between Vegetation and Rainfall Using Maximum Value Composite AVHRR-NDVI Data, Research Article.
Kogan, F. N. (1997). Drought of the late 1980s in the United States as derived from NOAA polar orbiting satellite data. Bulletin of the American Meteological Society, 76: 655-668.
Kogan, F.N. (1990). Remote sensing of weather impacts on vegetation in non-homogeneous areas. International Journal of Remote Sensing, 11:1405–1419.
Liu, W.T. and Kogan, F.N. (1996). Monitoring regional drought using Vegetation Condition Index. International Journal of Remote Sensing, 17: 2761–2782.
Malik, R. N. and Husain, S.Z. (2008). Linking remote sensing and ecological vegetation Communities: a multivariate approach. Pakistan Journal of Botany, 40: 337-349.
Malingreau, J.P. and Belward, S.B. (1992). Scale consideration in vegetation monitoring using AVHRR data. International Journal of Remote Sensing, 13: 2289-2307.
Peters, A. J., Walter-Shea, E. A., Ji, L., Vina, A., Hayes, M, and Svoboda, M.D. (2002). Drought monitoring with NDVIbased standardized vegetation index. Photogrammetric Engineering and Remote Sensing, 68: 71-76.
Reed, B.C., Brown, J.F., Vanderzee, D., Loveland, T.R., Merchant, J.W. and Ohlen, D.O. (1994). Measuring phenological variability from satellite imagery. Journal of Vegetation Sciences, 5: 703-714.
Sarkar, S. and Kafatos, M. (2004). Interannual variability of vegetation over the Indian sub-continent and its relation to the different meteorological parameters. Remote Sensing of Environment, 90: 268–280.
Shilong, P., Jingyun, F., Wei, J., Qinghua, G., Jinhu, K. and Shu, T.(2004), Variation in a satellite-based vegetation index in relation to climate in China. Journal of Vegetation Science, 15: 219-226.
Shin S. H. (2005). Applicability of Multi-temporal NDVI based Drought Index for Drought Monitoring of Korea Peninsula. Inha University Master Paper.
Shin, S.C. and Kim, C. J. (2003). Application of Normalized Difference Vegetation Index for Drought Detection in Korea, Korea Water Resources Association. 36: 839-849. http://edcimswww.cr.usgs.gov/pub/imswelcome/index.html (EOS Data Gate Way).
Vicente Serrano, S.M. (2007). Evaluating the impact of drought using remote sensing in a Mediterranean, semi-arid region. Natural Hazards, 40: 173–208.
Yang, W., Yang, L. and Merchant, J.W. (1997). An assessment of AVHRR/NDVI ecoclimatological relations in Nebraska, U.S.A. Remote Sensing of Environment, 18: 2161-2180.
Yang, W.L. and Merchant, J.M. (1998). An assessment of AVHRR/NDVI ecoclimatological relations in Nebraska. U.S.A. International Journal of Remote Sensing, 18: 2161-2180.
Zhou, L. M., Tucker, C. J., Kaufmann, R. K., Slayback, D., Shabanov, N. V. and Myneni, R. B. (2001). Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. Journal of Geophysical Research, 106: 20069-20083.
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How to Cite
Rawat, K. S., Mishra, A. K., Kumar, R., & Singh, J. (2012). Vegetation condition index pattern (2002-2007) over Indian agro-climate regions, using of GIS and SPOT sensor NDVI data. Journal of Applied and Natural Science, 4(2), 214–219. https://doi.org/10.31018/jans.v4i2.252
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