The accuracy of temperature & humidity prediction directly affects indoor environmental control, and current predictions mainly focus on time modeling, lacking spatiotemporal modeling based prediction
For political and administrative governance of land-use decisions, high-resolution and reliable spatial models are required over large areas and for various time horizons. We present a process-centere
The data source contains the data set, feature rasters, R scripts, model outputs of Wildfire likelihood mapping of Sikkim Himalaya using ML methods like GLM, SVM, GBM and RF.
