Landscape character change in mountain traditional villages is difficult to assess from a single perspective because roof-material replacement, material–color deviation, and visual exposure vary under complex terrain and settlement configurations. This study develops a multi-source UAV framework for reproducible, spatially explicit assessment of courtyard-scale visual–material integrity (CI), a spatially observable component of landscape character integrity. Using 749 courtyards in nine nationally designated traditional villages in Shangluo, China, the framework integrates UAV orthophotos, 3D mesh models, and point-cloud data to derive material penetration rate (PR), material–color conflict (CC), and standardized visual exposure (VC). PR and CC represent baseline material–color loss, whereas VC is incorporated as an exposure-amplification condition. Formulastructure sensitivity analysis against blinded ratings of 50 sampled courtyards showed that the proposed formulation had the highest rank consistency with expert judgments (Spearman’s ρ = 0.949). The frozen framework also showed a strong association with blinded professional ratings in geographically independent Longnan villages (ρ = 0.912, p < 0.001). XGBoost–SHAP identified courtyard impervious-surface ratio, primary material, and roof form as the leading model-associated predictors of CI variation. The framework supports courtyard-scale CI assessment, priority screening, and repeat-survey reassessment under comparable acquisition conditions.

A Multi-Source UAV Framework for Courtyard-Scale Visual–Material Integrity Assessment in Mountain Traditional Villages

barbara galli;Hao Jing;
2026-01-01

Abstract

Landscape character change in mountain traditional villages is difficult to assess from a single perspective because roof-material replacement, material–color deviation, and visual exposure vary under complex terrain and settlement configurations. This study develops a multi-source UAV framework for reproducible, spatially explicit assessment of courtyard-scale visual–material integrity (CI), a spatially observable component of landscape character integrity. Using 749 courtyards in nine nationally designated traditional villages in Shangluo, China, the framework integrates UAV orthophotos, 3D mesh models, and point-cloud data to derive material penetration rate (PR), material–color conflict (CC), and standardized visual exposure (VC). PR and CC represent baseline material–color loss, whereas VC is incorporated as an exposure-amplification condition. Formulastructure sensitivity analysis against blinded ratings of 50 sampled courtyards showed that the proposed formulation had the highest rank consistency with expert judgments (Spearman’s ρ = 0.949). The frozen framework also showed a strong association with blinded professional ratings in geographically independent Longnan villages (ρ = 0.912, p < 0.001). XGBoost–SHAP identified courtyard impervious-surface ratio, primary material, and roof form as the leading model-associated predictors of CI variation. The framework supports courtyard-scale CI assessment, priority screening, and repeat-survey reassessment under comparable acquisition conditions.
2026
UAV remote sensing; visual–material integrity; landscape character; roof-material recognition; pedestrian viewshed; mountain traditional villages
File in questo prodotto:
File Dimensione Formato  
remotesensing-18-03067.pdf

Accesso riservato

Dimensione 2.62 MB
Formato Adobe PDF
2.62 MB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1326126
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
  • OpenAlex 0
social impact