Multipurpose temporal GIS model for cadastral data management


Mango J., Claramunt C., Ngondo J., Zhang D., Xu D., Colak E., ...More

INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, vol.36, pp.1205-1230, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 36
  • Publication Date: 2022
  • Doi Number: 10.1080/13658816.2021.2009483
  • Journal Name: INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, Applied Science & Technology Source, CAB Abstracts, Computer & Applied Sciences, Geobase, INSPEC, Pollution Abstracts, Veterinary Science Database
  • Page Numbers: pp.1205-1230
  • Keywords: Temporal GIS models, temporal cadastral data changes, semantical cadastral data modelling, cadastre, SYSTEMS, DESIGN, TIME
  • Karadeniz Technical University Affiliated: Yes

Abstract

Past and current cadastral records are among the most valuable information that different countries need to solve land management and planning problems. However, many countries still face critical challenges in adopting modern temporal cadastral systems, including a sound integration of time constructs, efficient data integration and representation methods in the designed models. This research developed a new temporal GIS model to manage spatial and non-spatial temporal cadastral data, namely cadastral parcels, land-use and land-ownerships. Three-time dimensions defined by decision and valid and transaction times were formulated to qualify parcels data. A hybrid approach fusing on the Base State with Amendment and Space-Time Composite models is used to store significant parcel changes and their relationships in two interdependent sub-databases. We used administrative plot identifiers to associate with land use and ownership records, experiencing distinct temporal variations in the third sub-database within the same main repository. We experimented our model with data from Tanzania, and the results from queries demonstrate that the designed model can store all three temporal cadastral data and track their variations semantically and effectively. This model is very useful for storing cadastral parcels, reasons, events, and the transformed parcels' values to improve decision-making processes.