Drought Analysis Using Digital Image Processing & Meteorological Data

Abstract

Meteorological drought is simple absence/deficit of rainfall from the normal. It is the least severe form of drought and is often identified by sunny days and hot weather. Importance of time scale when accessing different types of drought, meteorological drought depends on precipitation deficit and duration of period with precipitation deficit. This study demonstrates observed meteorological based drought indices such as Normalized Deviation (ND), De Martonne’s Index (I_A), Pluvothermic Quotient (PQ), Negative Moisture Index (NMI) and Standard Precipitation Index (SPI) values were interpolated to get the spatial pattern of meteorological based drought. Crop yield and production trend was plotted and an equivalent Normalized Difference Vegetation Index (NDVI) threshold was identified to get the agricultural drought risk in Jodhpur district, where the occurrence is high in Jodhpur district. Monthly rainfall data from six stations were used to derive the Standardized Precipitation Index (SPI). The Landsat-7 ETM+ and Landsat-5 TM satellite sensor data was used for calculating Brightness Temperature (BT), Land Surface Temperature (LST). BT was converted to the Vegetation Condition Index (VCI) and the Temperature Condition Index (TCI), which are useful indices for the estimation of vegetation health and drought monitoring. The analysis was carried out for a period of 21 years (1991–2011) and from the SPI analysis it is found that in 2002 all of the area under study was affected by drought with greater intensity, can be classified as extreme and severe drought conditions.