Tuesday, September 8, 2015

Geo-processing with Python Books to read

Here I present to you some quality books to learn Geospatial Technology in Python programming language.

What is Geospatial Technology?
Geospatial technology (also known as Geomatics or geomatics engineering, or geomatic engineering, géomatique in French) is the discipline of gathering, storing, processing, and delivering geographic information, or spatially referenced information. In other words, it "consists of products, services and tools involved in the collection, integration and management of geographic data".

Geospatial technology refers to equipment used in visualization, measurement, and analysis of earth's features, typically involving such systems as GPS (global positioning systems), GIS (geographical information systems), and RS (remote sensing).

Fundamentals of this technology include: Geodesy, Geodynamics, Land Surveying, Cartography, and History

Application areas include:
    Aeromagnetic surveys
    Airborne geophysics
    Air navigation services
    Archaeological excavation and survey for GIS applications
    Coastal zone management and mapping
    Disaster informatics for disaster risk reduction and response
    The environment
    Infrastructure management
    Land management and reform
    Natural resource monitoring and development
    Seismic Interpretation
    Subdivision planning
    Urban planning
    Resource Management
    Climate Change/Environmental Monitoring
Source: https://en.wikipedia.org/wiki/Geomatics

Ok, here are some books to learning Python programming as applicable to the field of Geospatial Technology;-

Python Geospatial Development - Second Edition Eric Westra (2013), 508 pages
The author directly attack treatment modules withGDAL (OSGeo), Shapely, Mapnik, Django / GeoDjango (shapefiles, spatial databases, OpenStreetMap, webmapping). The focus is on the Mapnik module and the creation of a complete application with Django / GeoDjango.
    Chapter 1: Geospatial Development Using Python
    Chapter 2: GIS
    Chapter 3: Python Libraries for Geospatial Development
    Chapter 4: Sources of Geospatial Data
    Chapter 5: Working with Ceospatial Data in Python
    Chapter 6: GIS in the Database
    Chapter 7: Working with Spatial Data
    Chapter8 : Using Python and Mapnik to Generate Maps
    Chapter 9: Putting It All Together - a Complete Mapping System
    Chapter 10: ShapeEditor - Implementing List View, Import, and Export
    Chapter 11: ShapeEditor - Selecting and Editing Features

Learning Geospatial Analysis with Python Joel Lawhead (2013), 364 pages
Joel Lawhead is the creator of the module PyShpand blog GeospatialPython. All aspects are addressed. His book is a real mine of information: most geospatial modules are processed (installation on Linux, Mac OS X, Windows, principles of use) with a multitude of practical examples in all fields.
    Chapter 1: Learning Geospatial Analysis with Python
    Chapter 2: Geospatial Data
    Chapter 3: The Geospatial Technology Landscape
    Chapter 4: Geospatial Python Toolbox
    Chapter 5: Python and Geographic Information Systems
    Chapter 6: Python and Remote Sensing
    Chapter 7: Python and Elevation Data
    Chapter 8 : Advanced Geospatial Modeling Python
    Chapter 9: Real-Time Data
    Chapter 10: Putting lt All Together
Geoprocessing with Python Chris Garrard
Also noteworthy are the book Geoprocessing with Python Chris Garrard (in press), 400 pages devoted to treatment with the module GDAL (OSGeo) and is a continuation of his university course online  Geoprocessing with Python using Open Source GIS to UtahState University / GIS Laboratory already quoted on the Portal (thank youThomasG77).
  1: Introduction 
  2: Python basics 
  3: Representing the world have shapes: points, lines, and polygons 
  4: Reading vector data with OGR
  5: Writing vector data with OGR
  6: Filtering data with OCR
  7: Manipulating geometries with OGR
  8: Using spatial reference systems
  9: Representing the world as a set of numbers
10: Reading and writing raster data
11: Working with raster data
12: Analyzing raster data: NumPy
13: Visualizing data with Matplotlib

PyQGIS - The PyQGIS Programmer's Guide Gary Sherman (2014), 197 pages

A remark is necessary, if you only want to learn to create a plugin, these books are not for you. They deal mainly with the characteristics of PyQGIS and understandings with practical examples (the plugin is discussed briefly). They thus fills in part the shortcomings of the official documentation.However, they are difficult to address if you do not have some preliminary concepts of Python.
Python Basics
Setting UpYour Development Tools
The QGIS / Python Ecosystem
Navigating the QGIS API
Using the Console
Running Scripts
Tips and Techniques
Extending the API
Writing Piugins
Creating a Workflow Development
Writing a Standalone Application

Building Mapping Applications with QGIS Erik Westra (2014), 264 pages
Like the previous, it addresses all practical aspects of PyQGIS but expounds a little on creating plugins and creating standalone applications.
    Chapter 1: Getting Started with QGIS
    Chapter 2: The QCIS Python Console
    Chapter 3: Learning the QCIS Python API
    Chapter 4: Creating QGIS Plugins
    Chapter 5: Using QGIS in External Application
    Chapter 6: Mastering the QGIS Python API
    Chapter 7: Selecting and Editing Features in a PyQGIS Application
    Chapter 8: Building a Complete Application Mapping using Python and QGIS
    Chapter 9: Completing the Application ForestTrails

QGIS Python Programming Cookbook Joel Lawhead (2015), 340 pages

This book is the counterpart of Learning Geospatial Analysis with Python, it's a real treasure trove of tips and practical tips to achieve with PyQGIS in all areas. (since script debugging to full membership cards) rather than a simple introduction to the API.
    Chapter 1: Automating QCIS
    Chapter 2: Querying Vector Data
    Chapter 3: Editing Vector Data
    Chapter 4: Using Raster Data
    Chapter 5: Creating Dynamic Maps
    Chapter 6: Composing Static Maps
    Chapter 7: Interacting with the User
    Chapter 8: QGIS Workflows
    Chapter 9: Other Tips and Tricks

Learning QGIS - Second Edition (2014, 150 pages)
Anita Graser noted in the second edition of her book offers a small introduction to PyQGIS (18 pages)
    Chapter 6: Extending QGIS with Pvthon
       Getting to know the console Pvthon
        Creating custom geoprocessing scripts using Python
        Developing your first plugin

Here are other worthy to note especially with the ArcGIS user (ArcGIS ArcPy)
A Primer for ArcGIS Python Nathan Jennings (2011), 462 pages
A Primer for ArcGIS Python: Workbook I and A Primer for ArcGIS Python: Workbook II   (2015, the Worbook III is in press)
Python Scripting for ArcGIS   to Paul A. Zandbergen (2013, 2015)
Programming with ArcGIS 10.1 Python CookbookEric Pimpler (2013), 304 pages
GIS Tutorial for Python Scripting of David W. Allen (2014), 284 pages
ArcPy and ArcGIS - Geospatial Analysis with Python Silas Toms (2015), 224 pages

Some other ebooks to read as far as GIS mapping and Spatial Programming in Python and SQL is concerned are listed below:-

~ The PyQGIS Programmer's Guide
~ Mastering QGIS
~ The Geospatial Desktop
~ Geospatial Power Tools
~ Qgis Map Design
~ Learning QGIS
~ An Introduction to R for Spatial Analysis and Mapping
~ PostGIS in Action
~ Building Mapping Applications with QGIS
~ QGIS by Example
~ QGIS Python Programming Cookbook
~ Geoprocessing with Python

Happy reading.

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