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Python Geospatial Analysis Cookbook

Python Geospatial Analysis Cookbook

By : Diener
4.4 (5)
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Python Geospatial Analysis Cookbook

Python Geospatial Analysis Cookbook

4.4 (5)
By: Diener

Overview of this book

Geospatial development links your data to places on the Earth’s surface. Its analysis is used in almost every industry to answer location type questions. Combined with the power of the Python programming language, which is becoming the de facto spatial scripting choice for developers and analysts worldwide, this technology will help you to solve real-world spatial problems. This book begins by tackling the installation of the necessary software dependencies and libraries needed to perform spatial analysis with Python. From there, the next logical step is to prepare our data for analysis; we will do this by building up our tool box to deal with data preparation, transformations, and projections. Now that our data is ready for analysis, we will tackle the most common analysis methods for vector and raster data. To check or validate our results, we will explore how to use topology checks to ensure top-quality results. This is followed with network routing analysis focused on constructing indoor routes within buildings, over different levels. Finally, we put several recipes together in a GeoDjango web application that demonstrates a working indoor routing spatial analysis application. The round trip will provide you all the pieces you need to accomplish your own spatial analysis application to suit your requirements.
Table of Contents (15 chapters)
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12
A. Other Geospatial Python Libraries
13
B. Mapping Icon Libraries
14
Index

Creating an indoor route from room to room

Routing from room A to room B in an indoor routing web application over multiple floors with routing types brings together all our work up to this point. We will import some room data and utilize our network to then allow a user to select a room, route from one room to the next, and select a type of route.

Creating an indoor route from room to room

Getting ready

We need to import a set of room polygons for both the first and second floor as follows:

  1. Import a Shapefile of the first floor room polygons as follows:
    ogr2ogr -a_srs EPSG:3857 -lco "SCHEMA=geodata" -lco "COLUMN_TYPES=name=varchar,room_num=integer,floor=integer" -nlt POLYGON -nln ch11_e01_roomdata -f PostgreSQL "PG:host=localhost port=5432 user=saturn dbname=py_geoan_cb password=secret" e01_room_data.shp
    
  2. Import a Shapefile of the second floor room polygons as follows:
    ogr2ogr -a_srs EPSG:3857 -lco "SCHEMA=geodata" -lco "COLUMN_TYPES=name=varchar,room_num=integer,floor=integer" -nlt POLYGON...

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