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Python for geospatial data analysis : theory, tools, and practice for location intelligence
- Author / Creator
- Available as
- Online
Details
- Creator
- Bonny P. McClain
- Format
- Books
- Language
- English
- Contributors
- Publication
-
- Sebastopol : O'Reilly Media, Inc., 2022
- Physical Details
-
- 1 online resource (282 pages)
- data file
- ISBNs
- 9781098104795, 9781098104788, 1098104781, 1098104765, 9781098104764
- OCLC
- on1348493378
- Cover -- Copyright -- Table of Contents -- Preface -- Why Python? -- How This Book Works -- Who Is This Book For? -- A Few Tips on Tooling -- Finding Your Way -- Conventions Used in This Book -- Using Code Examples -- O'Reilly Online Learning -- How to Contact Us -- Acknowledgments -- Chapter 1. Introduction to Geospatial Analytics -- Democratizing Data -- Asking Data Questions -- A Conceptual Framework for Spatial Data Science -- Map Projections -- Vector Data: Places as Objects -- Raster Data: Understanding Spatial Relationships -- Evaluating and Selecting Datasets -- Summary
- Chapter 2. Essential Facilities for Spatial Analysis -- Exploring Spatial Data in QGIS -- Installing QGIS -- Adding Basemaps to QGIS -- Exploring Data Resources -- Visualizing Environmental Complaints in New York City -- Uploading Data to QGIS -- Setting the Project CRS -- Using the Query Editor to Filter Data -- Visualizing Population Data -- The QGIS Python Console -- Loading a Raster Layer -- Redlining: Mapping Inequalities -- Summary -- Chapter 3. QGIS: Exploring PyQGIS and Native Algorithms for Spatial Analytics -- Exploring the QGIS Workspace: Tree Cover and Inequality in San Francisco
- The Python Plug-in -- Accessing the Data -- Working with Layer Panels -- Addressing the Research Question -- Web Feature Service: Identifying Environmental Threats in Massachusetts -- Accessing the Data -- Discovering Attributes -- Working with Iterators -- Layer Styling -- Using Processing Algorithms in the Python Console -- Working with Algorithms -- Extract by Expression -- Buffer -- Extract by Location -- Summary -- Chapter 4. Geospatial Analytics in the Cloud: Google Earth Engine and Other Tools -- Google Earth Engine Setup -- Using the GEE Console and geemap -- Creating a Conda Environment
- Opening the Jupyter Notebook -- Installing geemap and Other Packages -- Navigating geemap -- Layers and Tools -- Basemaps -- Exploring the Landsat 9 Image Collection -- Working with Spectral Bands -- The National Land Cover Database Basemap -- Accessing the Data -- Building a Custom Legend -- Leafmap: An Alternative to Google Earth Engine -- Summary -- Chapter 5. OpenStreetMap: Accessing Geospatial Data with OSMnx -- A Conceptual Model of OpenStreetMap -- Tags -- Multidigraphs -- Installing OSMnx -- Choosing a Location -- Understanding Arguments and Parameters -- Calculating Travel Times
- Basic Statistical Measures in OSMnx -- Circuity -- Network Analysis: Circuity in Paris, France -- Betweenness Centrality -- Network Types -- Customizing Your Neighborhood Maps -- Geometries from Place -- Geometries from Address -- Working with QuickOSM in QGIS -- Summary -- Chapter 6. The ArcGIS Python API -- Setup -- Modules Available in the ArcGIS Python API -- Installing ArcGIS Pro -- Setting Up Your Environment -- Installing Packages -- Connecting to the ArcGIS Python API -- Connecting to ArcGIS Online as an Anonymous User -- Connecting to an ArcGIS User Account with Credentials -- Exploring Imagery Layers: Urban Heat Island Maps