Integrating Computer Vision and GIS for Large-Scale Morphological Mapping and Driving Force Analysis of Vernacular Courtyard Dwellings
Changsha University of Science and Technology · Hunan University
Abstract
This study develops and applies an integrated methodology that combines deep learning-based computer vision and spatial statistics to automate the large-scale identification and analysis of morphological features in vernacular courtyard dwellings. Focusing on Liangshuaixiu dwellings in Wu’an, southern Hebei, we trained an HRNetV2 semantic segmentation model on high-resolution satellite imagery to identify and extract contours for 134,280 courtyard spaces. Core morphological parameters (area, orientation) were calculated and analyzed using GIS spatial statistics and the geographic detector model. The results show that (1) the computer vision pipeline achieved efficient recognition with satisfactory accuracy…
Citation impact
- FWCI
- 46.07
- Percentile
- 99%
- References
- 53
Authors
6Topics & keywords
- Vernacular
- Segmentation
- Spatial analysis
- Geographic information system
- Orientation (vector space)
- Thematic map
- Climate action