Satellite Imagery Analysis in Python Part III: Land Surface Temperature and The National Land Cover Database (NLCD)

The third entry of the satellite imagery analysis in Python uses land surface temperature (LST) as the data variable along with land cover information from the national (U.S.) database. The land cover information will allow us to create a relationship between land cover type and its respective heating (or cooling) contribution to the earth’s surface. Land cover is used in many applications ranging from algorithm development to military applications and crop surveying, not to mention applications in water management and drought awareness.