Classification of Crops and Crop Rotation Using Remote Sensing and GIS-Based Approach: A Case Study of Doddakawalande Hobli, Nanjangudu Taluk

Abstract

Information about agricultural activities and spatial land use data is one of the key input parameter for the agricultural modelling. To access and manage crop information accurately, crop rotation and production risk reduction is additionally needed. Production risk can be reduced by adopting is related to multiple interaction between phenological information and crops management techniques. We address these issues by integrating remote sensing (RS) and Geographical Information System through three different methods (1). Differentiation of major crop types on an annual basis using village database, (2). Classification of RS data for a time periods (May to December), which are able to differentiate the certain stages of crops and (3). Combination of multispectral multi-temporal classification results in a sequential way for analysis strategy. Crop mapping for three different seasons were mapped for three consecutive years (2016–2018) by smoothing and integrating into a single vector layer for mapping of crop rotations. The use of phonological database in our classification method shows an improvement in a classification results. The obtained database shows information about the crop rotation which is extremely heterogeneous and contains large amount of crop sequences.