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.

Thermal terrain modeling of spatial objects, a tool for environmental and climatic change assessment.

The aim of the current research effort is to include biophysical multi-temporal data and more specifically land surface temperature (LST) in the terrain modeling process that traditionally was based only on digital elevation data processing. The terrain partition framework (spatial objects) is defined by the borderlines of prefecture authorities of Greece. Each object is represented by a set of attributes derived from the digital elevation data, and objects are organized into clusters on the basis of their terrain dependent representation. Finally, the terrain is segmented to regions on the basis of the multi-temporal LST data, each region presenting a different thermal signature. The thermal regions are used in the spatial objects parametric representation and a new index is devised (LST climatic index) expressing the biophysical suitability of spatial objects at moderate resolution scale.

The terrain signatures of administrative units: a tool for environmental assessment.

The quantification of knowledge related to the terrain and the landuse/landcover of administrative units in Southern Greece (Peloponnesus) is performed from the CGIAR-CSI SRTM digital elevation model and the CORINE landuse/landcover database. Each administrative unit is parametrically represented by a set of attributes related to its relief. Administrative units are classified on the basis of K-means cluster analysis in an attempt to see how they are organized into groups and cluster derived geometric signatures are defined. Finally each cluster is parametrically represented on the basis of the occurrence of the Corine landuse/landcover classes included and thus, landcover signatures are derived. The geometric and the landuse/landcover signatures revealed a terrain dependent landuse/landcover organization that was used in the assessment of the forest fires impact at moderate resolution scale.