Abstract
Cadastre-based temporal land use modeling with python
Envision! Book of Accepted Abstracts
Annual Conference of the Association of Collegiate Schools of Planning (ACSP), 52nd (Salt Lake City, United States, 13-Oct-2011–16-Oct-2011)
2011
Abstract
Time series data can be used to better understand the past. An improved understanding of the past can, in turn, can enhance our ability to plan for the future. The purpose of this research is to explore a low-cost technique for developing high resolution temporal land-use data. An often overlooked source for high resolution temporal data on land use is local government cadastral data. Compared with remotely sensed data, cadastral data are often of a greater resolution, more temporally continuous, and exist for a longer time period. Cadastral data are widely available and often contain the attributes needed for the temporal modeling of land use, most commonly a date of construction associated with the structures within a parcel.
Details
- Title
- Cadastre-based temporal land use modeling with python
- Authors
- Scott Lieske (Author) - University of Wyoming, United States
- Publication details
- Envision! Book of Accepted Abstracts
- Conference details
- Annual Conference of the Association of Collegiate Schools of Planning (ACSP), 52nd (Salt Lake City, United States, 13-Oct-2011–16-Oct-2011)
- Date published
- 2011
- Organisation Unit
- School of Social Sciences - Legacy; University of the Sunshine Coast, Queensland; Sustainability Research Cluster
- Language
- English
- Record Identifier
- 99450141802621
- Output Type
- Abstract
Metrics
5 File views/ downloads
379 Record Views