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Practical GIS

Practical GIS

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Practical GIS

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 (15 chapters)
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1
Appendix

Summary

In this chapter, we discussed PostgreSQL's structure, its objects, and how PostGIS sits on the RDBMS. We also learned some of the architectural specialities of PostGIS. We came closer to fully understanding RDBMSs, what we should look out for when we use them, and how we can effectively create queries in them. Although we used pgAdmin, we also learned some useful expressions, which can be used directly in PostgreSQL's CLI. It will come in handy when you have to configure a PostgreSQL or PostGIS instance on a remote server only accessible through SSH.

In the next chapter, we will dive into geospatial analysis, and see how we can produce meaningful results from our raw data. We will set up a scenario where we are real estate agents serving a customer with very specific needs. To find out the best spots matching the given criteria, we will use various geoalgorithms...

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Practical GIS
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