Thermal anomaly mapping from night MODIS imagery of USA, a tool for environmental assessment

A method is presented for elevation, latitude and longitude decorrelation stretch of multi-temporal MODIS MYD11C3 imagery (monthly average night land surface temperature (LST) across USA and Mexico). Multiple linear regression analysis of principal components images (PCAs) quantifies the variance explained by elevation (H), latitude (LAT), and longitude (LON). The multi-temporal LST imagery is reconstructed from the residual images and selected PCAs by taking into account the portion of variance that is not related to H, LAT, LON. The reconstructed imagery presents the magnitude the standardized LST value per pixel deviates from the H, LAT, LON predicted. LST anomaly is defined as a region that presents either positive or negative reconstructed LST value. The environmental assessment of USA indicated that only for the 25 % of the study area (Mississippi drainage basin), the LST is predicted by the H, LAT, LON. Regions with milled climatic pattern were identified in the West Coast while the coldest climatic pattern is observed for Mid USA. Positive season invariant LST anomalies are identified in SW (Arizona, Sierra Nevada, etc.) and NE USA.