This document discusses spatial analysis and modeling in a geographical information system. It defines spatial analysis as gaining an understanding of patterns and processes underlying geographic features in order to make better decisions and understand phenomena. The document outlines four types of spatial analysis: spatial data manipulation, spatial data analysis, spatial statistical analysis, and spatial modeling. It also describes different vector and raster spatial analysis techniques, such as clipping, overlaying, buffering, and slope/aspect calculations. Spatial modeling is defined as using models to predict spatial outcomes and enable "what if" analyses.

1. SPATIAL ANALYSIS AND MODELING
(GEOGRAPHICAL INFORMATION
SYSTEM)
UNIT – IV
Dr. Rambabu Palaka, Professor, BVRITMar. 2019

2. Spatial Analysis
Most GIS systems are for the purpose of representing and describing features of
the real world. Spatial databases perform this function
 Points, lines, polygons concepts for representation
 Coordinate systems as fundamental properties of spatial data
 geographic file formats for storage
Spatial Analysis involves gaining an understanding of the patterns, and
associated cause and effect processes, underlying the features which have been
described in order to
 Make better decisions
 Understand the phenomena as a goal in itself

3. Spatial Analysis
Types of Spatial Analysis:
1. Spatial data manipulation:
Classic GIS capabilities - Spatial queries & measurement, buffering, map layer
overlay
2. Spatial data analysis:
Descriptive and exploratory, Visualization through data manipulation and mapping
3. Spatial statistical analysis:
Hypothesis testing; Are data “to be expected” or are they “unexpected” relative to
some statistical model, usually of a random process
4. Spatial modeling:
Prediction, Constructing models (of processes) to predict spatial outcomes
(patterns) What if analyses

4. Spatial Analysis
Types of Spatial Analysis:
1. Vector Spatial Analysis - Extracting portions of data is an effective means of isolating specific areas for
further processing or data analysis
a) Extraction
i. Clip
ii. Split
iii. Select
iv. Erase
b) Overlay
i. Point-in-Polygon
ii. Line-in-Polygon
iii. Polygon-in-Polygon
c) Proximity
i. Buffer
ii. Near
iii. Point Distance

5. Spatial Analysis
2. Raster Spatial Analysis
a) Surface Analysis
a) Slope
b) Aspect
c) Contour
d) Hill Shade
e) Viewshed
b) Local Functions and Statistics
c) Neighborhood Functions and Statistics
d) Zonal Functions
a) Distance
b) Straight-line
c) Shortest path

6. Spatial Data Criteria: Spatial Analysis Functions
Spatial Analysis

28. Spatial Modeling