Mastering Geospatial analysis with Python : explore GIS processing and learn to work with GeoDjango, CARTOframes and MapboxGL-Jupyter / Paul Crickard, Eric van Rees, Silas Toms.

Format:

Book

Author/Creator:

Crickard, Paul, author.

Rees, Eric van, author.

Toms, Silas, author.

Language:

English

Subjects (All):

Geographic information systems--Computer programs.

Geographic information systems.

Geodatabases--Computer programs.

Geodatabases.

Physical Description:

1 online resource (431 pages)

Edition:

1st ed.

Place of Publication:

Birmingham ; Mumbai : Packt, [2018]

Biography/History:

Toms Silas: Silas Toms is a long-time geospatial professional and author who has previously published ArcPy and ArcGIS and Mastering Geospatial Analysis with Python. His career highlights include developing the real-time common operational picture used at Super Bowl 50, building geospatial software for autonomous cars, designing computer vision for next-gen insurance, and developing mapping systems for Zillow. He now works at Volta Charging, predicting the future of electric vehicle adoption and electric charging infrastructure. Crickard Paul: Paul Crickard authored a book on the Leaflet JavaScript module. He has been programming for over 15 years and has focused on GIS and geospatial programming for 7 years. He spent 3 years working as a planner at an architecture firm, where he combined GIS with Building Information Modeling (BIM) and CAD. Currently, he is the CIO at the 2nd Judicial District Attorney's Office in New Mexico. van Rees Eric: Eric van Rees was first introduced to Geographical Information Systems (GIS) when studying Human Geography in the Netherlands. For 9 years, he was the editor-in-chief of GeoInformatics, an international GIS, surveying, and mapping publication and a contributing editor of GIS Magazine. During that tenure, he visited many geospatial user conferences, trade fairs, and industry meetings. He focuses on producing technical content, such as software tutorials, tech blogs, and innovative new use cases in the mapping industry.

Summary:

Python comes with many libraries and tools that help you work on geoprocessing tasks without investing in expensive tools. This book introduces you to new libraries that perform geospatial and statistical analysis and data management. It uses examples that explain how Python v3 differs from v2, and solve age-old problems in geospatial analysis.

Contents:

Cover

Copyright and Credits

Packt Upsell

Contributors

Table of Contents

Preface

Chapter 1: Package Installation and Management

Introducing Anaconda

Installing Python using Anaconda

Running a Jupyter Notebook

Running a Notebook

Creating a new Notebook

Adding code

Managing Python packages

Managing packages with Anaconda Navigator

Online searching for packages using Anaconda Cloud

Managing Python packages with conda

Managing Python packages using pip

Upgrading and uninstalling the package with pip

Python virtual environments

Virtual environments using Anaconda

Managing environments with conda

Virtual environments using virtualenv

Summary

Chapter 2: Introduction to Geospatial Code Libraries

Geospatial Data Abstraction Library (GDAL) and the OGR Simple Features Library

Installing GDAL

Installing GDAL using Anaconda3

Installing GDAL using conda

Installing GDAL using pip

Installing a second GDAL version using pip

Other recommended GDAL resources

GEOS

Installing GEOS

Shapely

Installing Shapely

Fiona

Installing Fiona

Python shapefile library (pyshp)

Installing pyshp

pyproj

Installing pyproj

Rasterio

Rasterio dependencies

Installation of Rasterio

GeoPandas

GeoPandas installation

GeoPandas dependencies

How it all works together

Chapter 3: Introduction to Geospatial Databases

Installing PostgreSQL and PostGIS on Windows

Installing PostgreSQL and PostGIS on Mac

Working with PostgreSQL and PostGIS using Python

Connecting to PostgreSQL using psycopg2

Installing psycopg2

Connecting to the database and creating a table

Adding data to the table

Querying the data

Changing the CRS

Buffer

Distance and near

Lines in the database

Length of a line.

Intersecting lines

Polygons in the database

Point in polygon

Chapter 4: Data Types, Storage, and Conversion

Raster and vector data

Shapefiles

GeoJSON

KML

GeoPackage

Raster data formats

Reading and writing vector data with GeoPandas

Reading and writing vector data with OGR

Reading and writing raster data with Rasterio

Reading and writing raster data using GDAL

Chapter 5: Vector Data Analysis

OGR Simple Features Library

OGR batch commands

ogrmerge

The OGR library and Python bindings

OGR's main modules and classes

Creating polygon geometry with OGR

Creating polygon geometry from GeoJSON

Basic geometric operations

Writing polygon data to a newly created shapefile

Using a spatial filter to select features

Shapely and Fiona

Shapely objects and classes

Shapely methods for geospatial analysis

Fiona's data model

Creating geometries with Shapely

Applying geometrical methods with Shapely

Reading JSON geometries with Shapely

Reading data with Fiona

Accessing vector geometry in shapefiles using Shapely and Fiona

Geospatial analysis with GeoPandas

Selecting and plotting geometry data with GeoPandas and Matplotlib

Mapping wildfire data with GeoPandas

Why data inspection matters

Chapter 6: Raster Data Processing

Raster operations using GDAL

Using the GDAL library to load and query rasters

Using GDAL to create rasters

Raster operations using PostgreSQL

Loading rasters into PostgreSQL

Performing queries on rasters using PostgreSQL

Querying raster metadata

Queries returning geometry

Queries returning values

Chapter 7: Geoprocessing with Geodatabases

A crime dashboard

Building a crime database

Creating the tables

Populating the data

Mapping queries.

Incidents by date

Incidents in a polygon

Buffers

Nearest neighbor

Interactive widgets

Charts

Triggers

Chapter 8: Automating QGIS Analysis

Working in the Python console

Loading layers

Processing a layer

Layer properties

Feature properties

Drawing a layer from PostGIS

Drawing points

Drawing polygons from PostGIS

Adding, editing, and deleting features

Adding features to an existing layer

Deleting features from an existing layer

Editing features from an existing layer

Selecting features using expressions

Using toolboxes in Python

Writing custom toolboxes

Chapter 9: ArcGIS API for Python and ArcGIS Online

Introducing the ArcGIS API for Python and ArcGIS Online

A Pythonic web API

Installing the API

Testing the API

Troubleshooting

Authenticating your Esri user accounts

Different Esri user accounts

Different modules of the ArcGIS API for Python

Exercise 1 - importing the API and using the map widget

Creating a personalized ArcGIS Online account

Exercise 2 - searching, displaying, and describing geospatial content

Exercise 3 - working with raster data and the API's geoprocessing functions

Chapter 10: Geoprocessing with a GPU Database

Cloud geodatabase solutions

Big data processing

MapD architecture

Cloud versus local versus combined

Creating a MapD instance in the cloud

Finding the AMI

Opening an AWS account

Creating a key pair

Launching an instance

Picking a version

Searching for an instance

Setting up a security group

Immerse environment

Logging in to Immerse

Default dashboards

NYC taxi dataset

Importing a CSV

Creating a chart

Selections with the SQL EDITOR

Use geospatial data

Connecting to the database using a terminal

PuTTYgen.

Connection configuration

Using the private key

Installing pymapd

The conda install command

The pip install command

Creating a connection

User and password

Data cursor

Creating a table

Insert statements

Using Apache Arrow to load data

Contains queries

Other available spatial SQL commands

Chapter 11: Flask and GeoAlchemy2

Flask and its component modules

Setup

Installing modules using pip

Installing Flask using pip

Installing Flask-SQLAlchemy via pip

Installing GeoAlchemy2 using pip

Installing Flask-WTForms and WTForms using pip

Installing psycopg2 using pip

Installing SQLAlchemy-Utils using pip

Installing pyshapefile (or pyshp) using pip

Installing pygeoif using pip

Writing a Flask application

Downloading the data from a data source

County, district, state, and arena shapefiles

Creating the database and data tables

Adding the PostGIS extension tables to the new database

Defining the database tables

The declarative base

Database table model classes

Table properties

Inserting data into the new data tables

Importing the required modules

Locating and reading the shapefiles

Accessing shapefile data

Using queries

Components of the Flask application

Folder structure and the controller object

Models

Forms

Views

Dissecting the view

Using forms

Evaluating the request method

POST requests

Spatial queries

Relationship query

The web map template

Running the web application locally

Chapter 12: GeoDjango

Installing and configuring Django and GeoDjango

Steps from Django to GeoDjango

Installing Django

Installing PostGIS and psycopg2

Creating the database

GDAL/OGR

Modifying Windows environment variables

Creating a project and application.

Command-line argument - startproject

What is created by startproject?

Creating an application using manage.py

What is created by manage.py

Configuring settings.py

Adding a new database connection

Adding new installed apps

Creating the application

manage.py

Generating data models

Multipolygons

Database migrations

makemigrations

sqlmigrate

migrate

LayerMapping

Running the layer mapping

Administrative panel

GeoDjango administrative panel

admin.py

createsuperuser

runserver

URLs

URL patterns

Required folders and files

forms.py

templates folder

Writing views

index view

queryarena function

arena view

Running the application

Chapter 13: Geospatial REST API

Writing a REST API in Python

REST

JSON

Python for REST API

Flask

REST modules

Other frameworks

Variables in Flask URLs

Number converters

Other data converters

Request methods

GET

POST

Other available request methods

PUT

DELETE

The REST API application

Application components

Application folder and file structure

app.py

__init__.py

The database

models.py

Importing required modules

Declaring the session

Declaring the models

views.py

Importing modules

Base URL

Arenas

Getting all arenas

Getting arenas by ID

Getting arenas by name

A geospatial query

States

Getting all states

Getting a state by ID

Getting a state by name

Getting arenas by state

Counties

Getting a county by ID

Getting a county by name

Districts

Getting all districts

Getting a district by ID

Getting a district by name

API POST endpoints

New arenas

The view function

The addarena.html head

The addarena.html script

The addarena.html form.

Sending a POST request using the requests library.

Notes:

Description based on print version record.

ISBN:

9781788293334

1788293339

OCLC:

1035516325