Automating geoprocessing tasks to create city wide layers
Date
2019-03-04
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Abstract
Annually, Spatial and Numeric Data Services (SANDS) receives 434 Digital Aerial Survey (DAS) datasets, in AutoCAD format, from the City of Calgary. Each dataset covers an Alberta Township System (ATS) section (Figure 1) and is made up of five layers containing “surface features and topography” information “derived from 1:5000 aerial photos”1.
University of Calgary students regularly utilize these files in their research, however, in some cases they are looking for specific features covering an area much larger than an ATS section and in a more geographic information system (GIS) friendly format. To derive city wide products, from the DAS files, required reiterating through numerous geoprocessing operations. These repetitive and time consuming tasks were automated and accomplished within a day, using Python and ArcPy, instead of weeks if executed manually. The next section details the steps that were taken to create the outputs.
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ArcPy, ArcGIS, Python
Citation
Truong, R. (2019). Automating geoprocessing tasks to create city wide layers, Women in Data Science at University of Calgary, Calgary, March 4, 2019.