Abstract
The structure of computational spatial analysis has mostly built on data lattices inherited from cartography, where visualization of information takes priority over analysis. In these framings, spatial relationships cannot easily be encoded into traditional data lattices. This hinders spatial analysis that emphasizes how interactions among spatial entities reflect mutual inter-relationships. This paper explores how graph theoretic principles can support spatiotemporal analysis by enabling assessment of spatial and temporal relationships in landscape monitoring.
| Original language | English |
|---|---|
| Pages (from-to) | 580-605 |
| Number of pages | 26 |
| Journal | International Journal of Geographical Information Science |
| Volume | 29 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 3 Apr 2015 |
| Externally published | Yes |
Keywords
- land use land cover change
- spatial analysis
- spatial data mining
- spatiotemporal data modelling
- visualization