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Using community detection for spatial networks
- Source :
- CF
- Publication Year :
- 2019
- Publisher :
- ACM, 2019.
-
Abstract
- This paper describes the use of graph analysis for spatial networks. The use of community detection algorithms for detecting communities- groups of similar objects within networks of land cover objects to determine the land use is evaluated. Land cover to land use transformation requires some knowledge to merge land cover objects. Community detection algorithms merge objects of the formed spatial network into communities. Community detection algorithms are efficient analysis tool for spatial graphs and can identify land use communities but with different characteristics, although spatial networks with topological relationships between objects can cause some problems.
- Subjects :
- Power graph analysis
0303 health sciences
Land use
Computer science
0211 other engineering and technologies
02 engineering and technology
Land cover
computer.software_genre
03 medical and health sciences
Spatial network
Data mining
Merge (version control)
computer
030304 developmental biology
021101 geological & geomatics engineering
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Proceedings of the 16th ACM International Conference on Computing Frontiers
- Accession number :
- edsair.doi...........890f37415cfe1ad863df8e14de0d67b9
- Full Text :
- https://doi.org/10.1145/3310273.3323429