Real time drought monitoring using Remote Sensing approaches A Case Study: Western desert of Kharga and Dakhla Regions

A new drought index was developed using Soil moisture(SM) and Land Surface temperature (LST) reflectance data, which deduced from Landsat images, called (LST/SM). This new index was examined beside other effective existing drought index named:Perpendicular Drought Index (PDI), which consider as useful indicator for monitoring drought condition. These indices were applied on the middle of western desert of Egypt (Kharga and Dakhla regions) as study areas. Red, blue, and near-infrared wavelengths of landsat 8 (2014) and TM 5(2003) images were preprocessed: First georegisted then converted to TOA Reflectance for SM, PDI indices determination Thermal infrared bands were processed using different algorithms to deduce LST data. 800 random points were well distributed on each resulted index raster image to analyze the drought condition. The results demonstrated that for Kharga region: the mean value for LST/SM index was slightly increased from 16.770 in 2003 to 16.807 in 2014, and for PDI index, the mean value increase from 0.583 in 2003, to 0.6171 in 2014. For Dakhla region:mean value of LST/SM index increase from 17.589 in 2003 to 20.820 in 2014, while for PDI index, the mean value increase from 0.5676 in 2003 to 0.6021 in 2014. Standard deviation (SD) for LST/SM index were increased from 2.5933 in 2003 to 2.9775 in 2014 for Kharga region, and SD increase from 2.9996 in 2003 to 3.0756 in 2014 for Dakhla region. Analyzing the drought indices proof significant correlation between LST/SM, PDI(r =.457). The results proof slightly increasing in drought condition in the two study areas and this was agree with other previous field study. Finally These indices LST/SM and PDI have the potential to provide a effective, simple and real time monitoring method in the remote estimation of drought phenomena.