Monitoring of Drought using Satellite Data

Abstract

Droughts are considered to be one of the major natural hazards causing destructive impact on the environment as well as the economy of countries throughout the world. Drought being attributed to weather conditions cannot be monitored by weather data alone, strictly because these data are most likely to be ill-timed, infrequent and incomplete. Low rainfall has mainly caused droughts and subsequently reduction in agricultural production. Impacts of droughts constitute environmental destruction, economic damage human suffering and loss of lives. Droughts have been a recurring feature of the Indian climate therefore study of historical droughts may help in the delineation of major areas facing drought risk and thereby management plans can be formulated by the government authorities to cope with the disastrous effects of this hazard. In recent years, Remote Sensing (RS) and Geographic Information System (GIS) have played a remarkable role in assessment of various types of hazards either natural or man-made. This paper emphasize upon the use of RS and GIS in the field of drought risk evaluation. The study area taken is a part of the Jamnagar district of Gujrat between latitude 22 0 19 �46 �� N to 22 0 46 �01 �� N and longitude 70 0 20 �56 �� E to 70 0 47 �34 �� E. The study was conducted with satellite images of year 1977, 1990 and 1999. Data used for drought monitoring has been acquired from the following two sources, NDVI obtained from satellite sources and rainfall obtained from ground rainfall stations record. In this paper an attempt has been made to identify and extract drought risk areas encountering agricultural and meteorological drought by using the Normalized Difference Vegetation Index (NDVI) obtained from the LANDSAT images. The NDVI images generated from LANDSAT data were used to examine large scale drought patterns and their climatic impact on vegetation. NDVI values reflect the different geographical conditions quite well. The NDVI and rainfall was found to be highly correlated. It is therefore concluded that temporal variations of NDVI are convincingly associated with precipitation.