October 2013
Beginner to intermediate
364 pages
8h 8m
English
Content preview from Learning Geospatial Analysis with PythonBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Chapter 2. Geospatial Data
The most challenging aspect of geospatial analysis is the data. Geospatial data includes dozens of file formats and database structures already and continues to evolve and grow to include new types of data and standards. Additionally almost any file format can technically contain geospatial information simply by adding a location. As a geospatial analyst you may frequently encounter the following general data types:
- Spreadsheets and comma or tab-delimited files (CSV files)
- Geo-tagged photos
- Lightweight binary points, lines, and polygons
- Multigigabyte satellite or aerial images
- Elevation data such as grids, point clouds, or integer-based images
- XML files
- JSON files
- Databases (both servers and file databases)
Each format contains ...
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