Anita Graser – författare

In Detail

QGIS is a user friendly open source geographic information system (GIS) that runs on Linux, Unix, Mac OSX, and Windows. The popularity of open source geographic information systems and QGIS in particular has been growing rapidly over the last few years. More and more companies and institutions are adopting QGIS and even switching to QGIS as their main GIS.

Learning QGIS 2.0 is a practical, hands-on guide that provides you with clear, step-by-step exercises that will help you to apply your GIS knowledge to QGIS. Containing a number of clear, practical exercises, this book will introduce you to working with QGIS, quickly and painlessly. If you want to take advantage of the wide range of functionalities that QGIS offers, then this is the book for you.

This book takes you from installing and configuring QGIS, through handling spatial data to creating great maps. You will learn how to load and visualize existing spatial data and how to create data from scratch. You will perform common geoprocessing and spatial analysis tasks and automate them. We will cover how to achieve great cartographic output and print maps. You will learn everything you need to know to handle spatial data management, processing, and visualization tasks in QGIS.

Approach

A short book with a lot of hands-on examples to help you learn in a practical way.

Who this book is for

This book is great for users, developers, and consultants who know the basic functions and processes of a GIS but want to know how to use QGIS to achieve the results they are used to a full-fledged GIS.

Geocomputation with Python is a comprehensive resource for working with geographic data with the most popular programming language in the world. The book gives an overview of Python''s capabilities for spatial data analysis, as well as dozens of worked-through examples covering the entire range of standard GIS operations. A unique selling point of the book is its cohesive and joined-up coverage of both vector and raster geographic data models and consistent learning curve. This book is an excellent starting point for those new to working with geographic data with Python, making it ideal for students and practitioners beginning their journey with Python.

Key features:

Another unique feature is that this book is part of a wider community. Geocomputation with Python is a sister project of Geocomputation with R (Lovelace, Nowosad, and Muenchow 2019), a book on geographic data analysis, visualization, and modeling using the R programming language that has numerous contributors and an active community.

The book teaches how to import, process, examine, transform, compute, and export spatial vector and raster datasets with Python, the most widely used language for data science and many other domains. Reading the book and running the reproducible code chunks within will make you a proficient user of key packages in the ecosystem, including shapely, geopandas, and rasterio. The book also demonstrates how to make use of dozens of additional packages for a wide range of tasks, from interactive map making to terrain modeling. Geocomputation with Python provides a firm foundation for more advanced topics, including spatial statistics, machine learning involving spatial data, and spatial network analysis, and a gateway into the vibrant and supportive community developing geographic tools in Python and beyond.

Geocomputation with Python is a comprehensive resource for working with geographic data with the most popular programming language in the world. The book gives an overview of Python''s capabilities for spatial data analysis, as well as dozens of worked-through examples covering the entire range of standard GIS operations. A unique selling point of the book is its cohesive and joined-up coverage of both vector and raster geographic data models and consistent learning curve. This book is an excellent starting point for those new to working with geographic data with Python, making it ideal for students and practitioners beginning their journey with Python.

Key features:

Another unique feature is that this book is part of a wider community. Geocomputation with Python is a sister project of Geocomputation with R (Lovelace, Nowosad, and Muenchow 2019), a book on geographic data analysis, visualization, and modeling using the R programming language that has numerous contributors and an active community.

The book teaches how to import, process, examine, transform, compute, and export spatial vector and raster datasets with Python, the most widely used language for data science and many other domains. Reading the book and running the reproducible code chunks within will make you a proficient user of key packages in the ecosystem, including shapely, geopandas, and rasterio. The book also demonstrates how to make use of dozens of additional packages for a wide range of tasks, from interactive map making to terrain modeling. Geocomputation with Python provides a firm foundation for more advanced topics, including spatial statistics, machine learning involving spatial data, and spatial network analysis, and a gateway into the vibrant and supportive community developing geographic tools in Python and beyond.

Become a QGIS power user and master QGIS data management, visualization, and spatial analysis techniques

Key Features

Book Description

What you will learn

Who this book is for

If you are an intermediate GIS user, with either previous experience in QGIS or any other GIS application, this is the book for you. The recipes can be used to learn more advanced techniques in QGIS or to replicate the functionalities equivalent to other GIS platforms. This book assumes that you already have a working QGIS system in place.

The latest guide to using QGIS 2.14 to create great maps and perform geoprocessing tasks with ease

About This Book

Who This Book Is For

This book is great for users, developers, and consultants who know the basic functions and processes of GIS and want to learn to use QGIS to analyze geospatial data and create rich mapping applications. If you want to take advantage of the wide range of functionalities that QGIS offers, then this is the book for you.

What You Will Learn

In Detail

QGIS is a user-friendly open source geographic information system (GIS) that runs on Linux, Unix, Mac OS X, and Windows. The popularity of open source geographic information systems and QGIS in particular has been growing rapidly over the last few years.

Learning QGIS Third Edition is a practical, hands-on guide updated for QGIS 2.14 that provides you with clear, step-by-step exercises to help you apply your GIS knowledge to QGIS. Through clear, practical exercises, this book will introduce you to working with QGIS quickly and painlessly.

This book takes you from installing and configuring QGIS to handling spatial data to creating great maps. You will learn how to load and visualize existing spatial data and create data from scratch. You will get to know important plugins, perform common geoprocessing and spatial analysis tasks and automate them with Processing.

We will cover how to achieve great cartographic output and print maps. Finally, you will learn how to extend QGIS using Python and even create your own plugin.

Style and approach

A step by step approach to explain concepts of Geospatial map with the help of real life examples