Spatiotemporal and multi-sensor analysis of surface temperature, NDVI, and precipitation using google earth engine cloud computing platform

Vegetation, precipitation, and surface temperature are three important elements of the environment. By increasing concerns about climate change global warming, monitoring vegetation dynamics considered to be crucial. In this study, cross-relationship between vegetation, temperature, their fluctuations over past 21 years evaluated. Day time LST from Terra sensor MODIS, nir red bands Landsat 7 ETM+ 8 OLI, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) used in research. Data were evaluated processed using google earth engine cloud processing platform. According results, it was concluded that correlations annual average normalized difference index precipitation not significant. Evaluation cross-seasonal exhibited availability strong significant correlation a value r2 = 0.82 thickness during spring summer, especially April August. Moreover, exposed an inverse NDVI values r2= 0.776 0.68 respectively, these relationships highly results declined sharply particular years, decrease occurred due insufficient rainfalls.