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Home > Programming > Geospatial Analysis > ArcGIS Blueprints
ArcGIS Blueprints
ArcGIS Blueprints

ArcGIS Blueprints: Explore the robust features of Python to create real-world ArcGIS applications through exciting, hands-on projects

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ArcGIS Blueprints

Chapter 2. Tracking Elk Migration Patterns with GPS and ArcPy

In this chapter, we're going to build an application that imports a CSV file containing Global Positioning System (GPS) locations that depict elk migration patterns into a feature class that will be time-enabled to display migration patterns over time and space. We'll use the ArcPy data access (arcpy.da) module and the Python csv module to read the file containing GPS locations, and write the data to a new feature class. Next, we'll use the ArcPy mapping (archy.mapping) module to make the output feature class time-enabled, and then visualize the migration patterns of the elk over time and space. The application will be built as an ArcGIS Python Toolbox in much the same way as what we did in Chapter 1, Extracting Wildfire Data from an ArcGIS Server Map Service with the ArcGIS REST API.

In this chapter, we will cover the following topics:

  • ArcGIS Desktop Python toolboxes
  • Reading CSV files with the Python csv...

Design

Let's spend a little time going over the design of what we're going to build in this chapter. This application, like the one we built in the Chapter 1, Extracting Wildfire Data from an ArcGIS Server Map Service with the ArcGIS REST API, will include the creation of an ArcGIS Desktop Python Toolbox. The toolbox, MigrationPatterns.pyt, will include two tools: ImportCollarData and VisualizeMigration. The ImportCollarData tool will import GPS data from a collar that was attached to an elk in northern California. The GPS data will have been extracted to a comma-delimited text file (csv format), that will be read using the Python csv module and then imported into a local feature class stored in a file geodatabase using the arcpy.da which is a data access module. We'll then need to do a little manual work inside ArcMap. First, we'll make the feature class that was created as a result of the ImportCollarData tool time-enabled, and then we'll save the time-enabled...

Creating migration patterns for Python toolbox

Just like we did in the first chapter of the book, we'll build an ArcGIS Python Toolbox to hold the code for our application. I won't walk you through every single step like I did in the first chapter, but I will provide some general guidelines instead. If needed, refer to the first chapter for the specifics of how to create an ArcGIS Python Toolbox.

The Python toolboxes encapsulate everything in one place: parameters, validation code, and source code. A Python Toolbox functions like any other toolbox in ArcToolbox, but it is created entirely in Python and has a file extension of .pyt. As you learned in the last chapter, it is created programmatically as a class named Toolbox.

The following steps will help you to create migration patterns for Python toolbox:

  1. Open ArcCatalog. You can create a Python Toolbox in a folder by right-clicking on the folder and navigating to New | Python Toolbox. In ArcCatalog, there is a folder called Toolboxes...

Creating the Import Collar Data tool

The following steps will help you to create Import Collar Data tool:

  1. Right-click on MigrationPatterns.pyt and select Edit. This will open your development environment, as shown in the following screenshot. Your environment will vary depending upon the editor that you defined in Chapter 1, Extracting Real-Time Wildfire Data from ArcGIS Server with the ArcGIS REST API:
    Creating the Import Collar Data tool
  2. Remember that you will not be changing the name of the class, which is Toolbox. However, you will rename the Tool class to reflect the name of the tool you want to create.
  3. Find the class named Tool in your code and change the name of this tool to ImportCollarData, and set the label and description properties:
    class ImportCollarData(object):
    def __init__(self):
        """Define the tool (tool name is the name of the class)."""
        self.label = "Import Collar Data"
        self.description = "Import Elk Collar Data"
        self.canRunInBackground...

Reading data from the CSV file and writing to the feature class

The following steps will help you to read and write data from CSV file to a write to feature class:

  1. The main work of a tool is done inside the execute() method. This is where the geoprocessing of the tool takes place. The execute() method, as shown in the following code, can accept a number of arguments, including the tools self, parameters, and messages:
    def execute(self, parameters, messages):
      """The source code of the tool."""
      return
  2. To access the parameter values that are passed into the tool, you can use the valueAsText() method. Add the following code to access the parameter values that will be passed into your tool. Remember from a previous step that the first parameter will contain a reference to a CSV file that will be imported and the second parameter is the output feature class where the data will be written:
    def execute(self, parameters, messages):
    inputCSV = parameters...

Making the data frame and layer time-enabled

In this section, you will learn how to make a layer and data frame time-enabled. You will then add a tool to the Migration Patterns toolbox that cycles through the time range for the layer and exports a PDF map showing the movement of the elk over time and space:

  1. If necessary, open C:\ArcGIS_Blueprint_Python\ch2\ElkMigration.mxd in ArcMap.
  2. First, we'll symbolize the features so that we display them differently for wet and dry seasons. Right-click on the Betsy feature class and select Properties.
  3. Click on the Symbology tab and then define the symbology, as shown in the following screenshot:
    Making the data frame and layer time-enabled
  4. Now, select the Time tab, as shown in the following screenshot:
    Making the data frame and layer time-enabled
  5. Enable the time for the layer by clicking on the Enable time for this layer checkbox.
  6. Define Layer Time Extent by clicking on the Calculate button.
  7. Under Time properties, select Each feature has a single time field for Layer Time. Select the date field for Time Field. Define a Time Step Interval...

Design

Let's spend a little time going over the design of what we're going to build in this chapter. This application, like the one we built in the Chapter 1, Extracting Wildfire Data from an ArcGIS Server Map Service with the ArcGIS REST API, will include the creation of an ArcGIS Desktop Python Toolbox. The toolbox, MigrationPatterns.pyt, will include two tools: ImportCollarData and VisualizeMigration. The ImportCollarData tool will import GPS data from a collar that was attached to an elk in northern California. The GPS data will have been extracted to a comma-delimited text file (csv format), that will be read using the Python csv module and then imported into a local feature class stored in a file geodatabase using the arcpy.da which is a data access module. We'll then need to do a little manual work inside ArcMap. First, we'll make the feature class that was created as a result of the ImportCollarData tool time-enabled, and then we'll save the time-enabled data in a map document file...

Creating migration patterns for Python toolbox

Just like we did in the first chapter of the book, we'll build an ArcGIS Python Toolbox to hold the code for our application. I won't walk you through every single step like I did in the first chapter, but I will provide some general guidelines instead. If needed, refer to the first chapter for the specifics of how to create an ArcGIS Python Toolbox.

The Python toolboxes encapsulate everything in one place: parameters, validation code, and source code. A Python Toolbox functions like any other toolbox in ArcToolbox, but it is created entirely in Python and has a file extension of .pyt. As you learned in the last chapter, it is created programmatically as a class named Toolbox.

The following steps will help you to create migration patterns for Python toolbox:

  1. Open ArcCatalog. You can create a Python Toolbox in a folder by right-clicking on the folder and navigating to New | Python Toolbox. In ArcCatalog, there is a folder called Toolboxes; inside...

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Page 1 of 8

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Key benefits

  • Get to grips with the big world of Python add-ins and wxPython in GUI development to implement their features in your application
  • Integrate advanced Python libraries, ArcPy mapping, and data access module techniques to develop a mapping application
  • Construct a top-notch intermediate-to-advanced project by accessing ArcGIS Server and ArcGIS Online resources through the ArcGIS REST API using a project-based approach

Description

This book is an immersive guide to take your ArcGIS Desktop application development skills to the next level It starts off by providing detailed description and examples of how to create ArcGIS Desktop Python toolboxes that will serve as containers for many of the applications that you will build. We provide several practical projects that involve building a local area/community map and extracting wildfire data. You will then learn how to build tools that can access data from ArcGIS Server using the ArcGIS REST API. Furthermore, we deal with the integration of additional open source Python libraries into your applications, which will help you chart and graph advanced GUI development; read and write JSON, CSV, and XML format data sources; write outputs to Google Earth Pro, and more. Along the way, you will be introduced to advanced ArcPy Mapping and ArcPy Data Access module techniques and use data-driven Pages to automate the creation of map books. Finally, you will learn advanced techniques to work with video and social media feeds. By the end of the book, you will have your own desktop application without having spent too much time learning sophisticated theory.

Who is this book for?

If you have prior experience building simple apps with ArcGIS and now have a fancy for developing a more challenging and complex desktop application in ArcGIS, then this book is ideal for you.

What you will learn

  • Automate the creation of creative output data visualizations including maps, charts, and graphs
  • Explore ways to use the ArcPy Mapping module and Data-driven Pages to automate the creation of map books in your own project
  • Develop applications that use the Plotly platform and library to create stunning charts and graphs that can be integrated into ArcGIS Desktop
  • Build tools that access REST services and download data to a local geodatabase Design, build, and integrate advanced GUIs with wxPython and ArcGIS Desktop in ArcGIS
  • Get clued up about constructing applications that export data to Google Earth Pro to automate time-consuming complex processes
  • Maximize the access of ArcGIS Server and ArcGIS Online using the ArcGIS REST API with Python

Product Details

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Publication date : Dec 22, 2015
Length: 378 pages
Edition : 1st
Language : English
ISBN-13 : 9781785283628
Vendor :
ESRI
Category :
Programming
Languages :
Python
Concepts :
Geospatial Analysis
Tools :
ArcGIS

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Publication date : Dec 22, 2015
Length: 378 pages
Edition : 1st
Language : English
ISBN-13 : 9781785283628
Vendor :
ESRI
Category :
Programming
Languages :
Python
Concepts :
Geospatial Analysis
Tools :
ArcGIS

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Table of Contents

12 Chapters
1. Extracting Real-Time Wildfire Data from ArcGIS Server with the ArcGIS REST API Chevron down icon Chevron up icon
1. Extracting Real-Time Wildfire Data from ArcGIS Server with the ArcGIS REST API
Design
Creating the ArcGIS Desktop Python Toolbox
Populating the feature class
Summary
2. Tracking Elk Migration Patterns with GPS and ArcPy Chevron down icon Chevron up icon
2. Tracking Elk Migration Patterns with GPS and ArcPy
Design
Creating migration patterns for Python toolbox
Creating the Import Collar Data tool
Reading data from the CSV file and writing to the feature class
Making the data frame and layer time-enabled
Coding the VisualizeMigration tool
Summary
3. Automating the Production of Map Books with Data Driven Pages and ArcPy Chevron down icon Chevron up icon
3. Automating the Production of Map Books with Data Driven Pages and ArcPy
Design
Setting up the Data Frame
Creating the Grid Index Features
Enabling Data Driven Pages
Creating the Locator Map
Adding dynamic text to the layout
Exporting the map series with ArcPy mapping
Summary
4. Analyzing Crime Patterns with ArcGIS Desktop, ArcPy, and Plotly(Part 1) Chevron down icon Chevron up icon
4. Analyzing Crime Patterns with ArcGIS Desktop, ArcPy, and Plotly(Part 1)
Design
Creating the Import Records tool
Creating the Aggregate Crimes tool
Building the Create Map tool
Performing Spatial Statistical Analysis
Summary
5. Analyzing Crime Patterns with ArcGIS Desktop, ArcPy, and Plotly(Part 2) Chevron down icon Chevron up icon
5. Analyzing Crime Patterns with ArcGIS Desktop, ArcPy, and Plotly(Part 2)
Design
Getting to know Plotly
Creating the Neighborhood Bar Chart tool
Creating the Create Line Plot tool
Creating the output
Summary
6. Viewing and Querying Parcel Data Chevron down icon Chevron up icon
6. Viewing and Querying Parcel Data
Design
Creating a user interface with wxPython
Creating the ArcGIS Python add-in
Summary
7. Using Python with the ArcGIS REST API and the GeoEnrichment Service for Retail Site Selection Chevron down icon Chevron up icon
7. Using Python with the ArcGIS REST API and the GeoEnrichment Service for Retail Site Selection
Design
Creating the Census Block Group selection tool
Creating the Define Potential Stores tool
Creating the Enrich Potential Stores tool
Summary
8. Supporting Search and Rescue Operations with ArcPy, Python Add-Ins, and simplekml Chevron down icon Chevron up icon
8. Supporting Search and Rescue Operations with ArcPy, Python Add-Ins, and simplekml
Design
Creating the Last Known Position tool
Creating the Search Area Buffers tool
Creating the Search Sector tool
Creating the Convert to Google Earth tool
Summary
9. Real-Time Twitter Mapping with Tweepy, ArcPy, and the Twitter API Chevron down icon Chevron up icon
9. Real-Time Twitter Mapping with Tweepy, ArcPy, and the Twitter API
Design
Extracting Tweet geographic coordinates with tweepy
Scheduling the script
Creating the heatmap
Summary
10. Integrating Smartphone Photos with ArcGIS Desktop and ArcGIS Online Chevron down icon Chevron up icon
10. Integrating Smartphone Photos with ArcGIS Desktop and ArcGIS Online
Design
Taking photos
Converting iPhone photos to a feature class
Creating a Web Map
Summary
A. Overview of Python Libraries for ArcGIS Chevron down icon Chevron up icon
A. Overview of Python Libraries for ArcGIS
Overview of Arcpy
Overview of the ArcPy mapping module
Overview of the Arcpy data access module
An overview of the ArcGIS REST API
Conclusion
Index Chevron down icon Chevron up icon
Index

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A great resource that focuses on creating add-ins and Python toolboxes in ArcMap. A great bonus are a set of freely available Python packages that can be used to extend ArcMap so that you can interact with the ArcGIS REST API, among others. For intermediate and advanced arcpy users.
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About the author

Profile icon Eric Pimpler
Eric Pimpler
Eric Pimpler is the founder and owner of GeoSpatial Training Services and has over 20 years of experience in implementing and teaching GIS solutions using Esri, Google Earth/Maps, and open source technology. Currently, he focuses on ArcGIS scripting with Python and the development of custom ArcGIS Server web and mobile applications using JavaScript. He is the author of Programming ArcGIS 10.1 with Python Cookbook. Eric has a bachelor's degree in geography from Texas A&M University and a master's degree in applied geography with a specification in GIS from Texas State University.
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