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GIS Algorithms
- Ningchuan Xiao - Ohio State University, USA
December 2015 | 336 pages | SAGE Publications Ltd
Geographic information systems (GIS) have become increasingly important in helping us understand complex social, economic, and natural dynamics where spatial components play a key role. The critical algorithms used in GIS, however, are notoriously difficult to both teach and understand, in part due to the lack of a coherent representation. GIS Algorithms attempts to address this problem by combining rigorous formal language with example case studies and student exercises.
Using Python code throughout, Xiao breaks the subject down into three fundamental areas:
Using Python code throughout, Xiao breaks the subject down into three fundamental areas:
- Geometric Algorithms
- Spatial Indexing
- Spatial Analysis and Modelling
Introduction
Part I. Geometric Algorithms
Basic Geometric Operations
Polygon Overlay
Part II. Spatial Indexing
Indexing
k-D Trees
Quadtrees
Indexing Lines and Polygons
Part III. Spatial Analysis and Modeling
Interpolation
Spatial Pattern and Analysis
Network Analysis
Spatial Optimization
Heuristic Search Algorithms
Xiao’s book is a must-have for any GIS programmers, from beginners to professionals. Its sample programs in Python provide a rich library for key GIS algorithms.
James J Parsons Professor and Chair, Department of Geography and Anthropology, Louisiana State University
This is a welcome book, which covers the major geographical algorithms for vector and point-based analyses, along with network travel analysis and optimal solution searches, in practical detail. Its concentration on applied Python examples is timely, and it is sure to be the go-to handbook for anyone wanting to build from-the-ground up GIS functions into Python software. In addition the algorithms are a good starting point for anyone looking to implement functions in other languages.
Senior Lecturer in GeoComputation and GIS, University of Leeds
