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Learning Geospatial Analysis with Python - Third Edition

Python programiranje Python programiranje

Learning Geospatial Analysis with Python - Third Edition

Autor: Joel Lawhead
Broj strana: 456
ISBN broj: 9781789959277
Izdavač: PACKT PUBLISHING PACKT PUBLISHING
Godina izdanja: 2019.

Pregleda (30 dana / ukupno): 63 / 63

                 
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  • Automate geospatial analysis workflows using Python
  • Code the simplest possible GIS in just 60 lines of Python
  • Create thematic maps with Python tools such as PyShp, OGR, and the Python Imaging Library
  • Understand the different formats that geospatial data comes in
  • Produce elevation contours using Python tools
  • Create flood inundation models
  • Apply geospatial analysis to real-time data tracking and storm chasing

Geospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. With this systematic guide, you'll get started with geographic information system (GIS) and remote sensing analysis using the latest features in Python. This book will take you through GIS techniques, geodatabases, geospatial raster data, and much more using the latest built-in tools and libraries in Python 3.7. You'll learn everything you need to know about using software packages or APIs and generic algorithms that can be used for different situations. Furthermore, you'll learn how to apply simple Python GIS geospatial processes to a variety of problems, and work with remote sensing data. By the end of the book, you'll be able to build a generic corporate system, which can be implemented in any organization to manage customer support requests and field support personnel.

  • Create GIS solutions using the new features introduced in Python 3.7
  • Explore a range of GIS tools and libraries such as PostGIS, QGIS, and PROJ
  • Learn to automate geospatial analysis workflows using Python and Jupyter

Table of contents

1 Learning about Geospatial Analysis with Python
Technical requirements
Geospatial analysis and our world
History of geospatial analysis
GIS
Remote sensing
Elevation data
Computer-aided drafting
Geospatial analysis and computer programming
The importance of geospatial analysis
GIS concepts
Remote sensing concepts
Common vector GIS concepts
Common raster data concepts
Creating the simplest possible Python GIS
Summary
Further reading

2 Learning Geospatial Data
Getting an overview of common data formats
Understanding data structures
Understanding spatial indexing
What are overviews?
What is metadata?
Understanding the file structure
Knowing the most widely used vector data types
Understanding raster data types
What is point cloud data?
What are web services?
Understanding geospatial databases
Summary
Further reading

3 The Geospatial Technology Landscape
Technical requirements
Understanding data access
Understanding computational geometry
Understanding desktop tools (including visualization)
Understanding metadata management
Summary
Further reading

4 Geospatial Python Toolbox
Technical requirements
Installing third-party Python modules
Python virtualenv
Conda
Installing GDAL
Python networking libraries for acquiring data
ZIP and TAR files
Python markup and tag-based parsers
Python JSON libraries
OGR
PyShp
dbfpy
Shapely
Fiona
ESRI shapefile
GDAL
NumPy
PIL
PNGCanvas
GeoPandas
PyMySQL
PyFPDF
Geospatial PDF
Rasterio
OSMnx
Jupyter
Conda
Summary
Further reading

5 Python and Geographic Information Systems
Technical requirements
Measuring distance
Calculating line direction
Understanding coordinate conversion
Understanding reprojection
Understanding coordinate format conversion
Calculating the area of a polygon
Editing shapefiles
Aggregating geometry
Creating images for visualization
Using GPS data
Geocoding
Multiprocessing
Summary

6 Python and Remote Sensing
Technical requirements
Swapping image bands
Creating histograms
Performing a histogram stretch
Clipping images
Classifying images
Extracting features from images
Understanding change detection
Summary
Further reading

7 Python and Elevation Data
Accessing ASCII Grid files
Creating a shaded relief
Creating elevation contours
Working with LIDAR data
Summary
Further reading

8 Advanced Geospatial Python Modeling
Technical requirements
Creating a normalized difference vegetative index
Creating a flood inundation model
Creating a color hillshade
Performing least cost path analysis
Converting the route to a shapefile
Routing along streets
Geolocating photos
Calculating satellite image cloud cover
Summary

9 Real-Time Data
Technical requirements
Limitations of real-time data
Using real-time data
Tracking vehicles
Storm chasing
Reports from the field
Summary

10 Putting It All Together
Technical requirements
Understanding a typical GPS report
Building a GPS reporting tool
Summary
Further reading

 

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