| Cadastral and Urban Maps Enrichments Using Smart Spatial Data Fusion |
| Paper ID : 1116-GEOSPATIAL (R5) |
| Authors: |
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Alireza Hajiheidari *1, Mahmoud Reza Delavar2, Abbas Rajabifard3 1Geo-Spatial Information Department School of Surveying and Geospatial Eng., College of Engineering, University of Tehran, Tehran, Iran 2Center of Excellence in Geomatic Eng. in Disaster Management, School of Surveying and Geospatial Eng., College of Engineering, University of Tehran 3Centre for Spatial Data Infrastructures and Land Administration, Department of Infrastructure Engineering, University of Melbourne, Victoria, Australia |
| Abstract: |
| Cadastral and urban map enrichment/upgrading is an essential requirement for smart urban management. The high pace of development and change in megacities can cause different challenges for urban organizations to reproduce their maps based on their need. New urban management aims and plans need new cadastral and urban maps with different standards and elements which may have existed in the other urban organization. Producing an original map or checking the maps of different organizations visually in a megacity is very costly and time-consuming. These challenges require an advanced integration approach to overcome them. Therefore, enriching maps with concerned organizations' maps and intelligent and automatically identifying as well as applying the changes in urban and cadastral maps will save time and cost for informed urban decision-making. This paper has employed the data of the third zone of the District six of the Municipality of Tehran, the capital of Iran, and identifies changes in the parcel’s geometry of the cadastre maps in comparison with the recently produced maps of the municipality of Tehran. After pre-processing the data, some spatial and attribute information are added to each feature, and the land parcels are enriched. By matching the algorithm and comparing the parcels geometry and attributes, suspicious parcels are identified by the logistic regression algorithm. The Accuracy and F1-Score of this model were 0.845 and 0.780, respectively. Finally, the suspicious parcels are checked and the parcels are located, deleted, merged, splitted and geometrically modified in the base map and the base map is enriched. This paper has successfully proposed a new framework for cadastral and urban map enrichment intelligently. |
| Keywords: |
| Digital Cadastre, Cadastral and Urban Maps Intelligent Enrichment, Spatial data upgrading, Spatial Data Fusion, Geospatial Data Sharing, Urban Management, Spatial Data Infrastructure. |
| Status : Paper Accepted (Oral Presentation) |
