Introduction to GIS Programming and Fundamentals with Python and ArcGIS
This book is a comprehensive guide that delves into the world of Geographic Information Systems (GIS) programming, centered around Python and ArcGIS. The book is thoughtfully structured into four distinct sections, each building upon the previous one, with the ultimate goal of providing readers with a strong foundation in GIS programming.
Section I: Getting Started
Chapters 1 and 2 serve as an introduction to the core concepts of GIS programming. Chapter 1 sets the stage by familiarizing readers with the world of computers, computer programming, and the critical role of GIS. It also introduces the Unified Markup Language (UML) for capturing GIS models through practical Python programming. In Chapter 2, readers dive into the essential domain of object-oriented programming, complete with examples showcasing basic GIS vector data types such as Point, Polyline, and Polygon.
Section II: Python for GIS Programming
This section, comprising Chapters 3 through 8, is dedicated to Python programming. Here, readers will gain an in-depth understanding of Python, which is the integral programming language for ArcGIS. The topics covered include Python syntax, operators, control structures, file input/output, and exception handling. Additionally, the section focuses on developing a Mini-GIS application, offering hands-on experience while exploring fundamental GIS concepts.
Section III: Advanced GIS Algorithms
Chapters 9 through 12 transition into more advanced GIS programming topics. Readers learn how to use Python and ArcPy to harness the power of ArcGIS. Topics in this section include automating tools, accessing and describing data, and troubleshooting errors. Additionally, readers get to explore raster data algorithms, network data algorithms, and the representation of 3D data.
Section IV: Optimization and Advanced Topics
The final section, comprising Chapters 13 and 14, takes readers further into the world of GIS programming. It introduces performance optimization techniques, covering topics like storage access and management, parallel processing, multithreading, and spatial indexing. The knowledge gained throughout the book is applied to optimize the Mini-GIS application. Chapter 14 delves into advanced topics, such as GIS algorithms and modeling, spatial data structures, distributed GIS, and spatiotemporal thinking.
This book offers a structured and hands-on approach to learning GIS programming using Python and ArcGIS. It's an excellent resource for individuals looking to build a solid foundation in this field. Whether you're pursuing ESRI training, GIS programming courses, or aiming for GIS certifications, this book equips you with the knowledge and practical skills necessary to succeed. With a focus on geospatial analysis in Python and a comprehensive understanding of ArcGIS, readers will find themselves well-prepared to excel in the world of GIS programming.