Introduction to model-based resource potential mapping in a GIS environment: rationale, concepts, components, inputs, and outputs. Spatial data analysis in GIS: Spatial data models and management, elements of geoprocessing spatial query and conditional evaluation, reclassification, distance and density estimations, transformations, interpolation and neighbourhood operations, map algebra and mathematical operations, map overlay. Selection of model inputs: quantification of spatial associations, exploratory spatial data analysis, hypothesis testing, generating derivative input map layers. Model-based integration of input spatial data: knowledge-driven, data-driven, and hybrid models, linear and non-linear models - Fuzzy, Bayesian probabilistic, neural network and neurofuzzy.Validation, interpretation and evaluation of output resource potential maps.
Information related to PhD interviews and message from Head, CSRE
Posted on April 22, 2024
PhD Topics for Autumn Semester (July - Dec. 2024)
Posted on March 21, 2024
Applications for PhD 2024-2025 Autumn Semester (July - Dec. )
Posted on April 2,2024
M.Tech. interviews will he held on 16 and 17 May 2024.
Posted on April 2,2024