With the increasing use of map-based web sites and spatially aware devices and applications, geospatial development is a rapidly growing area. As a Python developer, you can't afford to be left behind. In today's location-aware world, every Python developer can benefit from understanding geospatial concepts and development techniques.
Working with geospatial data can get complicated because you are dealing with mathematical models of the earth's surface. Since Python is a powerful programming language with many high-level toolkits, it is ideally suited to geospatial development. This book will familiarize you with the Python tools required for geospatial development. It walks you through the key geospatial concepts of location, distance, units, projections, datums, and geospatial data formats. We will then examine a number of Python libraries and use these with freely available geospatial data to accomplish a variety of tasks. The book provides an in-depth look at storing spatial data in a database and how you can use spatial databases as tools to solve a range of geospatial problems.
It goes into the details of generating maps using the Mapnik map-rendering toolkit and helps you build a sophisticated web-based geospatial map-editing application using GeoDjango, Mapnik, and PostGIS. By the end of the book, you will be able to integrate spatial features into your applications and build complete mapping applications from scratch.
This book is a hands-on tutorial, teaching you how to access, manipulate, and display geospatial data efficiently using a range of Python tools for GIS development.
Chapter 1, Geospatial Development Using Python, provides an overview of the Python programming language and the concepts behind geospatial development. Major use cases of geospatial development and recent and upcoming developments in the field are also covered.
Chapter 2, GIS, introduces the core concepts of location, distance, units, projections, shapes, datums, and geospatial data formats, before discussing the process of working with geospatial data by hand.
Chapter 3, Python Libraries for Geospatial Development, explores the major Python libraries available for geospatial development, including the available features, how to install them, the major concepts you need to understand about the libraries, and how they can be used.
Chapter 4, Sources of Geospatial Data, investigates the major sources of freely available geospatial data, what information is available, the data format used, and how to import the data once you have downloaded it.
Chapter 5, Working with Geospatial Data in Python, uses the libraries introduced earlier to perform various tasks using geospatial data, including changing projections, importing and exporting data, converting and standardizing units of geometry and distance, and performing geospatial calculations.
Chapter 6, Spatial Databases, introduces the concepts behind spatial databases before looking in detail at the PostGIS spatially enabled database and how to install and use it from a Python program.
Chapter 7, Using Python and Mapnik to Produce Maps, provides a detailed look at the Mapnik map-generation toolkit and how to use it to produce a variety of maps.
Chapter 8, Working with Spatial Data, works through the design and implementation of a complete geospatial application called DISTAL, using freely available geospatial data stored in a spatial database.
Chapter 9, Improving the DISTAL Application, improves the application written in the previous chapter to solve various usability and performance issues.
Chapter 10, Tools for Web-based Geospatial Development, examines the concepts of web application frameworks, web services, JavaScript UI libraries, and slippy maps. It introduces a number of standard web protocols used by geospatial applications and finishes with a survey of the tools and techniques that will be used to build the complete mapping application in the final three chapters of this book.
Chapter 11, Putting it all Together – a Complete Mapping Application, introduces ShapeEditor, a complete and sophisticated web application built using PostGIS, Mapnik, and GeoDjango. We start by designing the overall application, and we then build the ShapeEditor's database models.
Chapter 12, ShapeEditor – Importing and Exporting Shapefiles, continues with the implementation of the ShapeEditor system, concentrating on displaying a list of imported shapefiles, along with logic for importing and exporting shapefiles via a web browser.
Chapter 13, ShapeEditor – Selecting and Editing Features, concludes the implementation of the ShapeEditor, adding logic to let the user select and edit features within an imported shapefile. This involves the creation of a custom tile map server and the use of the OpenLayers JavaScript library to display and interact with geospatial data.
The third edition of this book has been extended to support Python 3, though you can continue to use Python 2 if you wish to. You will also need to download and install the following tools and libraries, though full instructions are given in the relevant sections of this book:
GDAL/OGR
GEOS
Shapely
Proj
pyproj
PostgreSQL
PostGIS
pyscopg2
Mapnik
Django
This book is aimed at experienced Python developers who want to get up to speed with open source geospatial tools and techniques in order to build their own geospatial applications or integrate geospatial technology into their existing Python programs.
In this book, you will find a number of styles of text that distinguish between different kinds of information. Here are some examples of these styles, and an explanation of their meaning.
Code words in text are shown as follows: "The dataset, an instance of gdal.Dataset, represents a file containing raster-format data."
A block of code is set as follows:
import pyproj
lat1,long1 = (37.8101274,-122.4104622)
lat2,long2 = (37.80237485,-122.405832766082)
geod = pyproj.Geod(ellps="WGS84")
angle1,angle2,distance = geod.inv(long1, lat1, long2, lat2)
print("Distance is {:0.2f} meters".format(distance))When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
for value in values:
if value != band.GetNoDataValue():
try:
histogram[value] += 1
except KeyError:
histogram[value] = 1Any command-line input or output is written as follows:
% python calcBoundingBoxes.py Afghanistan (AFG) lat=29.4061..38.4721, long=60.5042..74.9157 Albania (ALB) lat=39.6447..42.6619, long=19.2825..21.0542 Algeria (DZA) lat=18.9764..37.0914, long=-8.6672..11.9865 ...
New terms and important words are shown in bold. Words that you see on the screen, in menus or dialog boxes for example, appear in the text like this: "Click on the Download Domestic Names hyperlink".
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