Book Image

Practical GIS

Book Image

Practical GIS

Overview of this book

The most commonly used GIS tools automate tasks that were historically done manually—compiling new maps by overlaying one on top of the other or physically cutting maps into pieces representing specific study areas, changing their projection, and getting meaningful results from the various layers by applying mathematical functions and operations. This book is an easy-to-follow guide to use the most matured open source GIS tools for these tasks. We’ll start by setting up the environment for the tools we use in the book. Then you will learn how to work with QGIS in order to generate useful spatial data. You will get to know the basics of queries, data management, and geoprocessing. After that, you will start to practice your knowledge on real-world examples. We will solve various types of geospatial analyses with various methods. We will start with basic GIS problems by imitating the work of an enthusiastic real estate agent, and continue with more advanced, but typical tasks by solving a decision problem. Finally, you will find out how to publish your data (and results) on the web. We will publish our data with QGIS Server and GeoServer, and create a basic web map with the API of the lightweight Leaflet web mapping library.
Table of Contents (22 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface
14
Appendix

Raster analysis


Unlike our previous analysis, now that we do not have input points or areas to choose from, we have to delimit those areas based on different criteria. That alone raises the idea of using rasters. Additionally, this time we not only have Boolean criteria (inside or outside), but also have some continuous preferences (closer, or farther, the better). This factor calls for raster analysis. In raster analysis, we can consider almost the same classification as in vector analysis:

  • Overlay analysis: Masking a raster layer with a binary mask layer. Where the binary mask layer has a zero value, we drop the value of the other raster layer, or set it to zero.
  • Proximity analysis: Analyzing the distance between features or cells, and creating a raster map from the results. The raster map can contain real-world distances (Appendix 1.12) or raster distances (number of cells) from features or non-null cells in the input vector or raster map.
  • Neighborhood analysis: Analyzing the neighborhood...