Iterative selective spatial variance reduction of MYD11A2 LST data

The aim of this research effort is to develop a method that will allow to map and evaluate thermal anomalies in SW USA from the MYD11A2 night land surface temperature (LST) imagery being available for the year 2014, that present higher spatial (1 km) and temporal (46 images per year) resolution than the MYD11C3 LST data (12 images per year at 5.6 km spatial resolution). The fact that is MYD11A2 LST imagery is projected to a rectangular grid did not affect the X, Y and elevation (H) spatial decorrelation stretch. Principal component analysis and linear regression models isolated and removed the X, Y, H (spatial) dependent variance included in the data while metrics devised verified the selective spatial variance reduction. The reconstructed 46 LST images represent the amount the LST deviates from the X, Y and H predicted for the year 2014. The thematic information content of the reconstructed LST images is verified by cluster analysis and mapped the spatial extend and the temporal variability of thermal anomalies within the study area. The positive thermal anomaly clusters are spatially arranged mainly west of Sierra Nevada in Great Basin Section where extensional tectonics create a series of titled elongated mountain blocks along the N to S direction in between basins bounded by normal faults, while the negative thermal anomaly clusters are spatially arranged along the coastal region, further north and in the western region far from the tilted mountain tectonic blocks of the Great Basin Section. The spatial maps that define regions with (positive or negative) thermal anomalies and distinct mean land response could assist landcover studies and support urban and rural planning in the context of emerging climatic change.