ASSOCIATION RULE MINING ON METROLOGICAL AND REMOTE SENSING DATA WITH WEKA TOOL

Drought is one of the major environmental disasters in many parts of the world. There are several possibilities of drought monitoring based on ground measurements, hydrological, climatologically and Remote Sensing data. Drought indices that derived by meteorological data and Remote Sensing data have coarse spatial and temporal resolution. Because of the spatial and temporal variability and multiple impacts of droughts, we need to improve the tools and data available for mapping and monitoring this phenomenon on all scales. In this paper we present discovering knowledge by association rules from metrological and Remote Sensing data and we have also used descriptive modeling. For calculating drought taking metrological data which is extract from metrological department of Pune at Maharastra (India) and Remote Sensing data is extract from National Aeronautics and Space Administration (NASA).