Course

Syllabus

Geospatial Analysis: foundations for analysis of continuous and discrete phenomena. GIS data Models and visualization. Geodatabase and attribute table handling. Spatial Statistical Models and GIS Model Builder. Analysis and modeling with map algebra.  

Point Pattern Analysis. Neighborhood operations and buffers. Spatial interpolation and approximation (gridding): Thessian polygon, TIN, Kriging, variogram calculation and interpretation.  

Raster distance calculation: cost surfaces, Euclidean and least cost path; Multi-criteria decision making (MCDM). Application of MCDM in different sectors. Network model and spatial optimization model. Site suitability modeling. 

Contribution of geospatial tech in different industrial and govt projects and their economic impact. Legal and policy aspects. Guest lectures: sharing of real time applications from invited talks.  

Proximal sensing and measurements of geospatial phenomenon by instrumentations like Spectroradiometer for hyperspectral based analysis, optical and lidar drone for geomorphological analysis, ERT & GPR for geophysical analysis, etc. 

Data standardization and access in the context of WMS (Web Map Service), WFS (Web Feature Service), and cloud computing. Standardized protocols to access and share geospatial data. Cloud infrastructure management for storage and processing.  

Note : software flexibility (ARCGIS/QGIS) 

Skills acquired : Experience on working with geospatial data for societal benefit using GIS software 

Course Outcomes  

CO1 : Explore different geospatial data types and statistical methods  

CO2: Apply GIS techniques in GIS software and model builder development (ArcGIS/Q-GIS) 

CO3: Perform point pattern analysis and spatial interpolation 

CO4: Understand Geospatial multi-criteria decision making and site suitability analysis 

CO5: Perform AI-based geospatial analysis 

CO6: Utilise proximal sensing instruments and measurements 

1. Reddy, GP Obi. “Spatial Data Management, Analysis, and Modeling in GIS: Principles and Applications.” Geospatial Technologies in Land Resources Mapping, Monitoring and Management. Springer, Cham, 2018. 127-142. 
2. Abdelbaki, Chérifa, et al. “Contribution of GIS and Hydraulic Modeling to the Management of Water Distribution Network.” Geospatial Challenges in the 21st Century. Springer, Cham, 2019. 125-150. 
3. Kumar, Pavan, et al., eds. Applications and Challenges of Geospatial Technology: Potential and Future Trends. Springer, 2018.