Dr. Ayyemperumal Thillai Jeyaseelan Profile

Dr. Ayyemperumal Thillai Jeyaseelan

at National Remote Sensing Agency

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Publications (1)

Proceedings Article | 12 December 2006 Paper

Evaluation of GVI-based indices for drought early warning in India

A. Jeyaseelan, Felix Kogan

Proceedings Volume 6412, 64120S (2006) https://doi.org/10.1117/12.693929

KEYWORDS: Vegetation, Satellites, Agriculture, Remote sensing, Atmospheric monitoring, Databases, Spatial resolution, Clouds, Solar radiation, Decision support systems

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Drought is the major disaster, which occurs in some part of India every year due to monsoon variability. India has established satellite based National Agricultural Drought Assessment and Monitoring System (NADAMS), at National Remote Sensing Agency, Department of Space since 1987. NADAMS provides near real time monitoring and early warning of drought conditions at National level using NOAA AVHRR and at regional level using IRS WiFS and AWiFS data. ISRO-NASA-NOAA science cooperation project has been initiated during 2005 for development of satellite based decision support drought monitor system in India. Initially, the evaluation of GVI based indices for drought early warning in India was taken up. The study was carried out over five small regions each covering part of a district and over five large regions each covering few districts in each state of Gujarat, Maharashtra and Rajasthan states and the result of the study is presented in this paper. The weekly GVI based indices such as Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI) for the period from 1991-2004 over 5 small regions covering part of districts namely Banaskantha district of Gujarat state to represent Bajra crop, Surendra nagar district of Gujarat state to represent Cotton crop, Nasik district of Maharashtra to represent Bajra crop, Bhandara district to represent Rice crop and Akola district of Maharastra to represent Jowar crop was selected. The weekly GVI based indices over 5 large regions with larger database from 1981 to 2004 covering few districts of Rajasthan state to represent winter wheat and few districts of Maharashtra state to represent Jowar, Rice and Cotton crops were selected. The comparison of seasonal average VCI, TCI and VHI with the corresponding crops yield over 5 small regions indicate better regression coefficient for VHI than VCI or TCI. The comparison over 5 large regions covering larger data base from 1982-2004 indicate better regression coefficient for VCI than VHI or TCI. Results of the study suggests over smaller region, the VCI and TCI combined VHI indices relates better with crop yields, whereas over larger region, the VCI itself relates better with crop yields than with TCI or the VCI and TCI combined VHI.

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