This repo contains , the project that I worked on during Summers 2016 at Bhaskaracharya Institute For Space Applications and Geo-Informatics. Project Objective : Prediction of Land Use and Land Cover Tools Used : QGIS , Python3 Description : The algorithm uses basic linear regression to Predict "Vegetation , Soil , Water , BuildUp" in any given year in future , given its trained properly Each Training set uses 2 training images's data features and their repective years. The feature vector contains features namely 1. Vegetation (of Year1) 2. Water (of Year 1) 3. Soil ( of Yeaar 1) 4. BuildUp(of Year 1) 5. TimeGap between 2 images who's data has been provide (i.e Year2-Year1) Results vector(of traing set) will include : 1. Vegetation (of Year2) 2. Water (of Year 2) 3. Soil ( of Yeaar 2) 4. BuildUp(of Year 2) PreProcessing : this is where you'll have to use QGIS for semi automatic classification to get the features required above and put them into files. You can read about the same in a short tutorial given in the link given below http://semiautomaticclassificationmanual-v4.readthedocs.io/en/latest/Tutorials.html#data