Applied and Natural Science Foundation
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Journal of Applied and Natural Science
An International Journal | Print ISSN: 0974-9411 | Online ISSN: 2231-5209
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Journal of Applied and Natural Science 4(2):214-219(2012)
Vegetation condition index pattern (2002-2007) over Indian agro-climate regions, using of GIS and SPOT sensor NDVI data
Kishan Singh Rawat, Anil Kumar Mishra, Rakesh Kumar and Jitendra Singh
1Water Technology Centre, Indian Agriculture Research Institute, New Delhi-110012, INDIA 2Division of Agricultural Physics, Indian Agriculture Research Institute, New Delhi-110012, INDIA *Corresponding author.E-mail: Received: April 24, 2012; Revised received: June 28, 2012; Accepted: September 14, 2012
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.

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