Drought Analysis Using Digital Image Processing & Meteorological Data

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