Gis And Spatial Statistics
GIS and Spatial Statistics
Unit 1. GIS
GIS concepts: GIS definitions, GIS applications in urban planning and environmental management, GIS software.
- Representing geographic features: Primitive elements (point, line, and polygon); vector data structures; raster data structures; layers.
- Spatial data and sources: data definition, types, format, standard, conversion, precision and accuracy.
- Data entry and preparation: creating and editing features and attributes, data cleaning, topology, GPS data collection, recording and integration, data quality.
- Map projections and transformation, geo-referencing of data.
- Practicals: Introduction ArcGIS GIS (ArcMap, ArcCatalog, ArcToolbox), Open source GIS softwares
Unit 2: Spatial statistics
Introduction to spatial statistics: point level models, areal (lattice) models, spatial point processes
- Estimation and modelling of spatial correlations: estimating variogram, fitting parametric models (matern class), maximum likelihood estimation, restricted maximum likelihood
- Spatial prediction and Interpolation (kriging): spatial regression, kriging, frequentist corrections for unknown covariance structure, model misspecification in kriging