Difference between revisions of "Spatial Analysis"
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Spatial analysis involves utilizing geographical information to create descriptive and informative outputs. These can be maps or other images and/or statistical data such as distances to other points, boundaries, roads or public services. The development world is rapidly expanding its capacity to access and analyze spatial data ranging from [http://pubdocs.worldbank.org/en/395241501768694367/KePSIE-Methodology-Note.pdf market clustering] to [http://www.worldbank.org/en/topic/sustainabledevelopment/brief/earth-observation-for-development satellite imagery] to agricultural plot mapping in SurveyCTO, the ability to process this data is also improving quickly. | Spatial analysis involves utilizing geographical information to create descriptive and informative outputs. These can be maps or other images and/or statistical data such as distances to other points, boundaries, roads or public services. The development world is rapidly expanding its capacity to access and analyze spatial data ranging from [http://pubdocs.worldbank.org/en/395241501768694367/KePSIE-Methodology-Note.pdf market clustering] to [http://www.worldbank.org/en/topic/sustainabledevelopment/brief/earth-observation-for-development satellite imagery] to agricultural plot mapping in SurveyCTO, the ability to process this data is also improving quickly. | ||
==Interactive Spatial Analysis Tools== | |||
Historically, spatial analysis tools have been challenging to code in a reproducible way, due to proprietary software systems with little extensibility. ArcGIS is a prime example of this, as the default implementation can only be coded reproducibly using [https://libraries.mit.edu/files/gis/PythonProgrammingforArcgis.pdf Python]. The open-source equivalent [http://qgis.org/en/site/ QGIS] has [http://www.qgistutorials.com/en/docs/getting_started_with_pyqgis.html similar limitations]. Both are useful for exploring spatial data | |||
==Reproducible Coding for Spatial Analysis== | |||
==Cloud Computing for Spatial Analysis== | |||
==Resources== | |||
Revision as of 15:36, 9 November 2017
Introduction
Spatial analysis involves utilizing geographical information to create descriptive and informative outputs. These can be maps or other images and/or statistical data such as distances to other points, boundaries, roads or public services. The development world is rapidly expanding its capacity to access and analyze spatial data ranging from market clustering to satellite imagery to agricultural plot mapping in SurveyCTO, the ability to process this data is also improving quickly.
Interactive Spatial Analysis Tools
Historically, spatial analysis tools have been challenging to code in a reproducible way, due to proprietary software systems with little extensibility. ArcGIS is a prime example of this, as the default implementation can only be coded reproducibly using Python. The open-source equivalent QGIS has similar limitations. Both are useful for exploring spatial data