GISC 4480K - Geospatial Modeling

This course covers advanced geospatial modeling for decision support towards real-world issues. The course focuses on advanced data mining for spatial data analysis and simulation. Instruction concentrates on the concepts of data modeling (statistical multivariate approach) with data visualizing, preprocessing, cleaning, compiling, trend-analyzing, and final analysis process followed in data mining approaches. Artificial neural networks (ANN) will be taught comprehensively to model spatial input data for projected/simulated output data developed for spatial decision support. Back propagation neural network (BPNN), Radial Basis Function Network (RBFN), Self-organizing Map (SOM), and Learning Vector Quantization (LVQ) ANN modeling approaches will be used for developing relationships between geospatial data and real world environmental phenomena for management decision support system development. Students will work on several case studies involving environmental issues.

Prerequisite/Corequisite:
Prerequisite: GISC 4470K

Hours:
3