Purchase
Hardcover
ISBN:
9781446274323
Available from
January 0001
Description
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
Contents
Introduction
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
Additional materials
Description
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
Contents
Introduction
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
Additional materials
Reviews
November 2015 | 336 pages | Sage UK
| Format | Published Date | ISBN | Price |
|---|---|---|---|
| Hardcover | 31/03/2026 | 9781446274323 | $217.00 |
| Paperback | 31/03/2026 | 9781446274330 | $126.00 |
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
Table Of Contents:
- 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
Recent Product Reviews:
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.
Fahui Wang, 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.
Andrew Evans, Senior Lecturer in GeoComputation and GIS, University of Leeds