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Geospatial development by example with Python : build your first interactive map and build location-aware applications using cutting-edge examples in Python /
Build your first interactive map and build location-aware applications using cutting-edge examples in PythonAbout This Book Learn the full geo-processing workflow using Python with open source packages Create press-quality styled maps and data visualization with high-level and reusable code Process...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham, UK :
Packt Publishing,
January 2016.
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| Colección: | Community experience distilled.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover
- Copyright
- Credits
- About the Author
- About the Reviewers
- www.PacktPub.com
- Table of Contents
- Preface
- Chapter 1: Preparing the Work Environment
- Installing Python
- Windows
- Ubuntu Linux
- Python packages and package manager
- The repository of Python packages for Windows
- Installing packages and required software
- OpenCV
- Windows
- Ubuntu Linux
- Installing NumPy
- Windows
- Ubuntu Linux
- Installing GDAL and OGR
- Windows
- Ubuntu Linux
- Installing Mapnik
- Windows
- Ubuntu Linux
- Installing Shapely
- Windows
- Ubuntu Linux
- Installing other packages directly from pip
- Windows
- Ubuntu Linux
- Installing an IDE
- Windows
- Linux
- Creating the book project
- Programming and running your first example
- Transforming the coordinate system and calculating the area of all countries
- Sort the countries by area size
- Summary
- Chapter 2: The Geocaching App
- Building the basic application structure
- Creating the application tree structure
- Functions and methods
- Documenting your code
- Creating the application entry point
- Downloading geocaching data
- Geocaching data sources
- Fetching information from a REST API
- Downloading data from a URL
- Downloading data manually
- Opening the file and getting its contents
- Preparing the content for analysis
- Combining functions into an application
- Setting your current location
- Finding the closest point
- Summary
- Chapter 3: Combining Multiple Data Sources
- Representing geographic data
- Representing geometries
- Making data homogeneous
- The concept of abstraction
- Abstracting the geocache point
- Abstracting geocaching data
- Importing geocaching data
- Reading GPX attributes
- Returning the homogeneous data
- Converting the data into Geocache objects
- Merging multiple sources of data.
- Integrating new functionality into the application
- Summary
- Chapter 4: Improving the App Search Capabilities
- Working with polygons
- Knowing well-known text
- Using Shapely to handle geometries
- Importing polygons
- Getting the attributes' values
- Importing lines
- Converting the spatial reference system and units
- Geometry relationships
- Touches
- Crosses
- Contains
- Within
- Equals or almost equals
- Intersects
- Disjoint
- Filtering by attributes and relations
- Filtering by multiple attributes
- Chaining filters
- Integrating with the app
- Summary
- Chapter 5: Making Maps
- Knowing Mapnik
- Making a map with pure Python
- Making a map with a style sheet
- Creating utility functions to generate maps
- Changing the data source at runtime
- Automatically previewing the map
- Styling maps
- Map style
- Polygon style
- Line styles
- Text styles
- Adding layers to the map
- Point styles
- Using Python objects as a source of data
- Exporting geo objects
- Creating the Map Maker app
- Using PythonDatasource
- Using the app with filtering
- Summary
- Chapter 6: Working with Remote Sensing Images
- Understanding how images are represented
- Opening images with OpenCV
- Knowing numerical types
- Processing remote sensing images and data
- Mosaicking images
- Adjusting the values of the images
- Cropping an image
- Creating a shaded relief image
- Building an image processing pipeline
- Creating a RasterData class
- Summary
- Chapter 7: Extract Information from Raster Data
- Getting the basic statistics
- Preparing the data
- Printing simple information
- Formatting the output information
- Calculating quartiles, histograms, and other statistics
- Making statistics a lazy property
- Creating color classified images
- Choosing the right colors for a map
- Blending images.
- Showing statistics with colors
- Using the histogram to colorize the image
- Summary
- Chapter 8: Data Miner App
- Measuring execution time
- Code profiling
- Storing information on a database
- Creating an Object Relational Mapping
- Preparing the environment
- Changing our models
- Customizing a manager
- Generating the tables and importing data
- Filtering the data
- Importing massive amount of data
- Optimizing database inserts
- Optimizing data parsing
- Importing OpenStreetMap points of interest
- Removing the test data
- Populating the database with real data
- Searching for data and crossing information
- Filtering using boundaries
- Summary
- Chapter 9: Processing Big Images
- Working with satellite images
- Getting Landsat 8 images
- Memory and images
- Processing images in chunks
- Using GDAL to open images
- Iterating through the whole image
- Creating image compositions
- True color compositions
- Processing specific regions
- False color compositions
- Summary
- Chapter 10: Parallel Processing
- Multiprocessing basics
- Block iteration
- Improving the image resolution
- Image resampling
- Pan sharpening
- Summary
- Index.