Book Image

Mastering QGIS - Second Edition

By : Kurt Menke, GISP, Paolo Corti, Richard Smith Jr., GISP, Luigi Pirelli, John Van Hoesen, GISP
Book Image

Mastering QGIS - Second Edition

By: Kurt Menke, GISP, Paolo Corti, Richard Smith Jr., GISP, Luigi Pirelli, John Van Hoesen, GISP

Overview of this book

QGIS is an open source solution to GIS. It is widely used by GIS professionals all over the world. It is the leading alternative to the proprietary GIS software. Although QGIS is described as intuitive, it is also by default complex. Knowing which tools to use and how to apply them is essential to producing valuable deliverables on time. Starting with a refresher on the QGIS basics, this book will take you all the way through to creating your first custom QGIS plugin. From the refresher, we will recap how to create, populate, and manage a spatial database. You’ll also walk through styling GIS data, from creating custom symbols and color ramps to using blending modes. In the next section, you will discover how to prepare vector, heat maps, and create live layer effects, labeling, and raster data for processing. You’ll also discover advanced data creation and editing techniques. The last third of the book covers the more technical aspects of QGIS such as using LAStools and GRASS GIS’s integration with the Processing Toolbox, how to automate workflows with batch processing, and how to create graphical models. Finally, you will see how to create and run Python data processing scripts and write your own QGIS plugin with pyqgis. By the end of the book, you will understand how to work with all the aspects of QGIS, and will be ready to use it for any type of GIS work.
Table of Contents (19 chapters)
Mastering QGIS - Second Edition
Credits
Foreword
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Summary


This chapter provided an overview of the structure within the Processing Toolbox and an introduction to the variety of advanced spatial analysis tools than can be accessed through the toolbox. You specifically learned how to create a shaded relief map, calculate the least-cost path, evaluate a viewshed, reclassify raster layers, query and combine raster layers, and calculate raster statistics using GRASS algorithms. You then learned how to crop raster layers using a polygon mask and reclassify, query, and combine raster layers using SAGA algorithms. You learned how to delineate a watershed and extract a vector stream network from a DEM using TauDEM algorithms. We explored the integration of spatial statistics using R packages to identify characteristics of landscape features. And in our last exercise, we explored how to visualize, convert and produce surfaces from LIDAR data using LAStools and Fusion. Perhaps most importantly, we saw how interoperable the native QGIS tools are with...