Introduction to GIS Programming and Fundamentals with Python and ArcGIS®


Book Description

Combining GIS concepts and fundamental spatial thinking methodology with real programming examples, this book introduces popular Python-based tools and their application to solving real-world problems. It elucidates the programming constructs of Python with its high-level toolkits and demonstrates its integration with ArcGIS Theory. Filled with hands-on computer exercises in a logical learning workflow this book promotes increased interactivity between instructors and students while also benefiting professionals in the field with vital knowledge to sharpen their programming skills. Readers receive expert guidance on modules, package management, and handling shapefile formats needed to build their own mini-GIS. Comprehensive and engaging commentary, robust contents, accompanying datasets, and classroom-tested exercises are all housed here to permit users to become competitive in the GIS/IT job market and industry.




A Python Primer for ArcGIS(r)


Book Description

A Python Primer for ArcGIS(r) Workbook I (1 of 3) The automation of geoprocessing tasks is a common practice among GIS professionals. Python is the standard programming language for ArcGIS and other fields such as remote sensing, GPS, spatial modeling, and statistical analysis. A Python Primer for ArcGIS(r) Workbook series combines fundamental Python programming structures to help professionals automate common geoprocessing functions. Thorough explanations of programming concepts are included along with user-friendly demonstrations that enable readers to develop programs on their own. In addition, chapters contain exercises and questions that aid in the application of each chapter's highlighted principles. Workbook I provides a practical introduction using Python for ArcGIS geoprocessing. Readers will learn some Python basics ending with writing a simple geoprocessing script. Workbook II contains coding strategies for common GIS tasks and processes. Workbook III completes the Workbook series by focusing on Python functions, creating custom Python script tools, Python Add-ins, and script automation. Workbook II can be ordered here:https://www.createspace.com/5215222 Workbook III can be ordered here:https://www.createspace.com/6279064 Follow for changes, updates, and new material: Blog: http://education.urbandalespatial.com/ Twitter: https://twitter.com/urbandalegis




Python Scripting for ArcGIS Pro


Book Description

Unlock the power of Python in ArcGIS Pro with Python Scripting for ArcGIS Pro, the definitive, easy-to-follow guide to writing Python code with spatial data in ArcGIS Pro.




Python Scripting for Arcgis Pro


Book Description

Python Scripting for ArcGIS Pro is the definitive, easy-to-follow guide to writing useful Python code with spatial data in ArcGIS Pro, whether you're new to programming or not.




Geocomputation with R


Book Description

Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you up-to-speed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to real-world problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems, including representing and modeling transport systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/. Dr. Robin Lovelace is a University Academic Fellow at the University of Leeds, where he has taught R for geographic research over many years, with a focus on transport systems. Dr. Jakub Nowosad is an Assistant Professor in the Department of Geoinformation at the Adam Mickiewicz University in Poznan, where his focus is on the analysis of large datasets to understand environmental processes. Dr. Jannes Muenchow is a Postdoctoral Researcher in the GIScience Department at the University of Jena, where he develops and teaches a range of geographic methods, with a focus on ecological modeling, statistical geocomputing, and predictive mapping. All three are active developers and work on a number of R packages, including stplanr, sabre, and RQGIS.




A Python Primer for ArcGIS(r)


Book Description

A Python Primer for ArcGIS(r) Workbook III (3 of 3) The automation of geoprocessing tasks is a common practice among GIS professionals. Python is the standard programming language for ArcGIS and other fields such as remote sensing, GPS, spatial modeling, and statistical analysis. A Python Primer for ArcGIS(r) Workbook series combines fundamental Python programming structures to help professionals automate common geoprocessing functions. Thorough explanations of programming concepts are included along with user-friendly demonstrations that enable readers to develop programs on their own. In addition, chapters contain exercises and questions that aid in the application of each chapter's highlighted principles. Workbook III completes the Workbook series by focusing on Python functions, creating custom Python script tools, Python Add-ins, and script automation. Workbook I provides a practical introduction using Python for ArcGIS geoprocessing. Readers will learn some Python basics ending with writing a simple geoprocessing script. Workbook II contains coding strategies for common GIS tasks and processes. Workbook I can be ordered here: https://www.createspace.com/5205001 Workbook II can be ordered here:https://www.createspace.com/5215222 Follow for changes, updates, and new material: Blog: http://education.urbandalespatial.com/ Twitter: https://twitter.com/urbandalegis




Python Scripting for ArcGIS


Book Description

"Python Scripting for ArcGIS is a guide to help experienced users of ArcGIS for Desktop get started with Python scripting. This book teaches how to write Python code that works with spatial data to automate geoprocessing tasks in ArcGIS. Readers can thuslearn the skill set needed to create custom tools. Key topics in this book include Python language fundamentals, automating geoprocessing tasks,exploring and manipulating spatial data, working with geometries and rasters, map scripting, debugging and error handling, creating functions and classes, and creating and sharing script tools"--




A Geographer's Guide to Computing Fundamentals


Book Description

This upper-undergraduate textbook teaches students programming in GIS using a mix of computer science theory and hands-on activities, with the aim of empowering students to understand fundamentals and apply their knowledge beyond the specific examples in the book. Each of the book’s twenty-one chapters integrates instructional material with exercises in ArcGIS Pro. In doing so, this book combines the strengths of workbooks and theoretical textbooks to provide a holistic and comprehensive text. Each chapter concludes with an unguided task that ensures students have learned the broader principles explained therein. In addition to its unique format, the book covers oft-neglected topics such as debugging, creating a program from scratch, and managing metadata. Section I starts with the principles of scripting and programming with Python. Section II introduces the ArcPy module and elements specific to ArcGIS Pro. This section focuses on data structures, and how they are used and implemented within Python. Section III uses the topic of algorithms to guide the student through creating tools to add functionality to ArcGIS Pro. The last section, Section IV, builds upon section III to guide the student to developing and sharing projects and Python packages to include external open-source code and share the Python code as an open-source package. This text will prepare students for a long-term ability to do GIS programming, whether in industry or academic research. This comes from the author’s observations of students who have learned GIS programming in one platform, such as VBA in ArcMap, struggle to apply that knowledge to a new platform, such as Python in ArcGIS Pro, because the content was presented too closely with a specific platform. The integration of exercises with conceptual content, along with the choice of chapter content, serves this goal of preparing students for working in a dynamic, rapidly changing technology field.




A Python Primer for ArcGIS(r)


Book Description

"The automation of geoprocessing tasks is a common practice among GIS professionals. Python is the standard programming language for ArcGIS and other fields such as remote sensing, GPS, spatial modeling, and statistical analysis. A Python Primer for ArcGIS® Workbook series combines fundamental Python programming structures to help professionals automate common geoprocessing functions. Thorough explanations of programming concepts are included along with user-friendly demonstrations that enable readers to develop programs on their own. In addition, chapters contain exercises and questions that aid in the application of each chapter's highlighted principles. These workbooks provides a practical approach to a board range of programming skills using ArcGIS for geoprocessing and map production in the work place."--p. [4] of cover.




Geoprocessing with Python


Book Description

Summary Geoprocessing with Python teaches you how to use the Python programming language, along with free and open source tools, to read, write, and process geospatial data. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology This book is about the science of reading, analyzing, and presenting geospatial data programmatically, using Python. Thanks to dozens of open source Python libraries and tools, you can take on professional geoprocessing tasks without investing in expensive proprietary packages like ArcGIS and MapInfo. The book shows you how. About the Book Geoprocessing with Python teaches you how to access available datasets to make maps or perform your own analyses using free tools like the GDAL, NumPy, and matplotlib Python modules. Through lots of hands-on examples, you’ll master core practices like handling multiple vector file formats, editing geometries, applying spatial and attribute filters, working with projections, and performing basic analyses on vector data. The book also covers how to manipulate, resample, and analyze raster data, such as aerial photographs and digital elevation models. What's Inside Geoprocessing from the ground up Read, write, process, and analyze raster data Visualize data with matplotlib Write custom geoprocessing tools Three additional appendixes available online About the Reader To read this book all you need is a basic knowledge of Python or a similar programming language. About the Author Chris Garrard works as a developer for Utah State University and teaches a graduate course on Python programming for GIS. Table of Contents Introduction Python basics Reading and writing vector data Working with different vector file formats Filtering data with OGR Manipulating geometries with OGR Vector analysis with OGR Using spatial reference systems Reading and writing raster data Working with raster data Map algebra with NumPy and SciPy Map classification Visualizing data Appendixes A - Installation B - References C - OGR - online only D - OSR - online only E - GDAL - online only