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

Matching the rest of the criteria


We have two additional tasks to complete in order to match the common preferences of our customers. If you do not remember the exact preferences, here they are again:

  • They should be less than 500 meters away from a park with a playground
  • They should be less than 500 meters away from a restaurant
  • They should be less than 500 meters away from a bar or a pub
  • There should be at least two markets within their 500 meters vicinity

The first three criteria can be easily matched building on the queries of the previous section. We only have to create three CTE tables or subqueries; one for the parks with playgrounds in their 200 meters vicinity, one for the restaurants, and one for the bars and pubs. After that, we only have to match our houses by using distance checks. Such a query can be formulated as follows:

    WITH parks_with_playgrounds AS (
     SELECT ST_Collect(l.geom) AS geom FROM spatial.landuse l,
     spatial.pois p
     WHERE l.fclass = 'park' AND p.fclass...