Python For ArcGIS

Capa
Springer, 16/01/2016 - 538 páginas
This book introduces Python scripting for geographic information science (GIS) workflow optimization using ArcGIS. It builds essential programming skills for automating GIS analysis. Over 200 sample Python scripts and 175 classroom-tested exercises reinforce the learning objectives. Readers will learn to: • Write and run Python in the ArcGIS Python Window, the PythonWin IDE, and the PyScripter IDE • Work with Python syntax and data types • Call ArcToolbox tools, batch process GIS datasets, and manipulate map documents using the arcpy package • Read and modify proprietary and ASCII text GIS data • Parse HTML web pages and KML datasets • Create Web pages and fetch GIS data from Web sources. • Build user-interfaces with the native Python file dialog toolkit or the ArcGIS Script tools and PyToolboxes Python for ArcGIS is designed as a primary textbook for advanced-level students in GIS. Researchers, government specialists and professionals working in GIS will also find this book useful as a reference.
 

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Índice

Introduction
1
Beginning Python
13
Basic Data Types Numbers and Strings
37
Basic Data Types Lists and Tuples
59
ArcGIS and Python
77
Calling Tools with Arcpy
95
Getting User Input
119
Controlling Flow
133
Error Handling
241
UserDefined Functions
261
UserDefined Modules
291
Reading and Writing with Cursors
309
Dictionaries
335
Reading and Writing Text Files
357
Working with HTML and KML
385
Classes
415

DecisionMaking and Describing Data
141
Repetition Looping for Geoprocessing
171
Batch Geoprocessing
187
Additional Looping Functions
209
Debugging
223
User Interfaces for File and Folder Selection
435
ArcGIS Python GUIs
449
Mapping Module
505
Index
531
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Laura G. Tateosian is a professor at the Center for Geospatial Analytics at North Carolina State University. She earned her B.A. in Mathematics from Towson University, her M.S. in Mathematics from the University of Oklahoma, and her Ph.D. in computer science from North Carolina State University. She has more than 8 years of experience teaching Python programming for GIS and receives outstanding teaching evaluations. In 2014, she received an award for her teaching at North Carolina State University. Her research involves geospatial data analysis, aesthetic geovisualization, eye-tracking for map and visualization design, and automatic narrative mapping with Python and ArcGIS. Her research has published in refereed conferences and journals, such as, Information Visualization, International Journal for Uncertainty Quantification, Transactions in GIS, ACM Transactions on Graphics, IEEE Transactions on Visualization and Computer Graphics, the proceedings of the International Symposium on Non-Photorealistic Animation and Rendering, the International Symposium on Applied Perception in Graphics and Visualization, and IEEE Computer Graphics & Applications (Visualization Viewpoints).

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