Integrating Computer Vision and GIS for Large-Scale Morphological Mapping and Driving Force Analysis of Vernacular Courtyard Dwellings
Lihua Liang; Xiaodong Li; Shutong Liu; Zhenhao Guo; Shuo Tang; Baohua Wen · 2026 · Buildings
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
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 mode
Abstract by Lihua Liang; Xiaodong Li; Shutong Liu; Zhenhao Guo; Shuo Tang; Baohua Wen, Buildings (2026) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.3390/buildings16061118