Automating geoprocessing tasks to create city wide layers

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dc.contributor.authorTruong, Renna
dc.date.accessioned2019-03-04T17:34:27Z
dc.date.available2019-03-04T17:34:27Z
dc.date.issued2019-03-04
dc.description.abstractAnnually, 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.en_US
dc.identifier.citationTruong, R. (2019). Automating geoprocessing tasks to create city wide layers, Women in Data Science at University of Calgary, Calgary, March 4, 2019.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/36156
dc.identifier.urihttp://hdl.handle.net/1880/109927
dc.language.isoengen_US
dc.publisher.facultyLibraries and Cultural Resourcesen_US
dc.publisher.institutionUniversity of Calgaryen_US
dc.rightsUnless otherwise indicated, this material is protected by copyright and has been made available with authorization from the copyright owner. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectArcPyen_US
dc.subjectArcGISen_US
dc.subjectPythonen_US
dc.titleAutomating geoprocessing tasks to create city wide layersen_US
dc.typeconference posteren_US

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