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Python geospatial analysis essentials : process, analyze, and display geospatial data using Python libraries and related tools /

If you are an experienced Python developer and wish to get up-to-speed with geospatial programming, then this book is for you. While familiarity with installing third-party Python libraries would be an advantage, no prior knowledge of geospatial programming is required.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Westra, Erik (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing, 2015.
Colección:Community experience distilled.
Temas:
Acceso en línea:Texto completo

MARC

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049 |a UAMI 
100 1 |a Westra, Erik,  |e author. 
245 1 0 |a Python geospatial analysis essentials :  |b process, analyze, and display geospatial data using Python libraries and related tools /  |c Erik Westra. 
246 3 0 |a Process, analyze, and display geospatial data using Python libraries and related tools 
264 1 |a Birmingham, UK :  |b Packt Publishing,  |c 2015. 
300 |a 1 online resource (1 volume) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Community experience distilled 
588 0 |a Online resource; title from cover (Safari, viewed July 6, 2015). 
500 |a Includes index. 
505 0 |a Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Geospatial Analysis and Techniques; About geospatial analysis; Understanding geospatial data; Setting up your Python installation; Installing GDAL; Installing Shapely; Obtaining some geospatial data; Unlocking the shapefile; Analyzing the data; A program to identify neighboring countries; Summary; Chapter 2: Geospatial Data; Geospatial data quality; Types of geospatial data; Shapefiles; Well-known text; Well-known binary; Spatial databases; Geospatial microformats. 
505 8 |a GeoJSONGML; Digital elevation models; Raster basemaps; Multiband raster files; Sources of freely available geospatial data; Natural Earth Data; OpenStreetMap; US Census Bureau; World Borders Dataset; GLOBE; National Elevation Dataset; Reading and writing geospatial data using Python; Reading vector data; Writing vector data; Reading raster data; Writing raster data; Dealing with spatial reference systems; WGS84; Universal Transverse Mercator; Describing spatial reference systems; Transforming coordinates; Calculating lengths and areas; Geospatial data errors and how to fix them; Points. 
505 8 |a LineStringsLinear Rings; Polygons; MultiPolygons; Fixing invalid geometries; Summary; Chapter 3: Spatial Databases; Spatial database concepts; Installing a spatial database; Installing PostgreSQL; Installing PostGIS; Installing psycopg2; Accessing PostGIS from Python; Setting up a spatial database; Importing spatial data; Querying spatial data; Manipulating spatial data; Exporting spatial data; Summary; Chapter 4: Creating Maps; Introducing Mapnik; Installing Mapnik; A taste of Mapnik; Building a map; Styling a map; Learning Mapnik; Datasources; Symbolizers; PointSymbolizer; LineSymbolizer. 
505 8 |a PolygonSymbolizerTextSymbolizer; RasterSymbolizer; Map rendering; A working example; Next steps; Summary; Chapter 5: Analyzing Geospatial Data; Libraries for spatial analysis; PyProj; NetworkX; Spatial analysis recipes; Calculating and comparing coordinates; Calculating lengths; Calculating areas; Calculating shortest paths; Summary; Chapter 6: Building a Complete Geospatial Analysis System; Matching GPS data against a map; An overview of the GPS Heatmap system; Obtaining the necessary data; Obtaining GPS data; Downloading the road data; Implementing the GPS Heatmap system. 
505 8 |a Initializing the databaseImporting the road data; Splitting the road data into segments; Constructing a network of directed road segments; Implementing the map-matching algorithm; Generating the GPS Heatmap; Further improvements; Summary; Index. 
520 |a If you are an experienced Python developer and wish to get up-to-speed with geospatial programming, then this book is for you. While familiarity with installing third-party Python libraries would be an advantage, no prior knowledge of geospatial programming is required. 
546 |a English. 
590 |a Knovel  |b ACADEMIC - Earth Sciences 
650 0 |a Python (Computer program language) 
650 0 |a Geospatial data. 
650 6 |a Python (Langage de programmation) 
650 6 |a Données géospatiales. 
650 7 |a Geospatial data.  |2 fast  |0 (OCoLC)fst01741194 
650 7 |a Python (Computer program language)  |2 fast  |0 (OCoLC)fst01084736 
776 0 8 |i Print version:  |a Westra, Erik.  |t Python geospatial analysis essentials : process, analyze, and display geospatial data using Python libraries and related tools.  |d Birmingham, England : Packt Publishing Ltd, ©2015  |h ix, 178 pages  |k Community experience distilled.  |z 9781782174516 
830 0 |a Community experience distilled. 
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