Learn the core concepts of geospatial data analysis for building actionable and insightful GIS applications
Key Features
• Create GIS solutions using the new features introduced in Python 3.7
• Explore a range of GIS tools and libraries such as PostGIS, QGIS, and PROJ
• Learn to automate geospatial analysis workflows using Python and Jupyter
Book Description
Geospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. With this systematic guide, you'll get started with geographic information system (GIS) and remote sensing analysis using the latest features in Python.
This book will take you through GIS techniques, geodatabases, geospatial raster data, and much more using the latest built-in tools and libraries in Python 3.7. You'll learn everything you need to know about using software packages or APIs and generic algorithms that can be used for different situations. Furthermore, you'll learn how to apply simple Python GIS geospatial processes to a variety of problems, and work with remote sensing data.
By the end of the book, you'll be able to build a generic corporate system, which can be implemented in any organization to manage customer support requests and field support personnel.
What you will learn
• Automate geospatial analysis workflows using Python
• Code the simplest possible GIS in just 60 lines of Python
• Create thematic maps with Python tools such as PyShp, OGR, and the Python Imaging Library
• Understand the different formats that geospatial data comes in
• Produce elevation contours using Python tools
• Create flood inundation models
• Apply geospatial analysis to real-time data tracking and storm chasing
Who this book is for
This book is for Python developers, researchers, or analysts who want to perform geospatial modeling and GIS analysis with Python. Basic knowledge of digital mapping and analysis using Python or other scripting languages will be helpful.
Author(s): Joel Lawhead
Edition: 3
Publisher: Packt Publishing
Year: 2019
Language: English
Commentary: True PDF
Pages: 456
City: Birmingham, UK
Tags: Python; Data Visualization; PostGIS; Graph Algorithms; Geospatial Data; GPS Tracking; Geographic Information Systems; QGIS; Remote Sensing; Multiprocessing; LiDAR Sensor; Computational Geometry; PROJ
1. Learning about Geospatial Analysis with Python
2. Learning Geospatial Data
3. The Geospatial Technology Landscape
4. Geospatial Python Toolbox
5. Python and Geographic Information Systems
6. Python and Remote Sensing
7. Python and Elevation Data
8. Advanced Geospatial Python Modeling
9. Real-Time Data
10. Putting It All Together