Multi-Scale Landscape Character Assessment Framework for Vernacular Landscapes in High-Density Rural Chengdu Plain, China

Landscape Character Assessment (LCA) has struggled with scale mismatches and inadequate treatment of cultural expression when applied to high-density cultural landscapes in Asia. On the Chengdu Plain, Western Sichuan, China, remote sensing shows convergent settlement patterns across case sites, but fieldwork reveals substantial divergences in landscape character. We examined five cases representing different rural development models in the Chengdu metropolitan area. By integrating 10 m Sentinel-2 imagery and with systematic fieldwork (3200 photographs and 42 semi-structured interviews, July–August 2023), we constructed a framework that combines macro-scale spatial analysis with micro-scale field investigation. For macro-level quantification, six landscape pattern indices were adopted: number of patches (NP), patch density (PD), contagion index (CONTAG), aggregation index (AI), Shannon’s diversity index (SHDI), and Shannon’s evenness index (SHEI). The micro-level investigation followed a three-tier scheme (natural environment, settlement space, architectural details) to record vertical ecological communities, spatial expressions of cultural embeddedness, and visual landscape character. Indicator screening employed the KJ method and two rounds of Delphi consultation with ten experts; weights were then determined through the Analytic Hierarchy Process (AHP). Macro-level results display a clustered, low-fragmentation pattern (woodland AI = 97.48, water body AI = 99.40), anchored by a stable mosaic of Linpan, farmland, water bodies, and homesteads. Micro-level features include multi-strata vertical communities of trees, shrubs, grasses, and water, along with cultural embeddedness expressed through irrigation systems, farming patterns, and courtyard layouts. The VLEAS (Vernacular Landscape Elements Assessment System) framework encompasses three dimensions (natural, cultural, and visual) and comprises 12 indicators. The cultural dimension receives the highest weight (0.42), followed by natural (0.32) and visual (0.26) dimensions. Comparative analysis shows that the framework differentiates cases with similar macro-scale patterns but divergent micro-features, capturing differences that a purely macro-index benchmark misses, and it also reveals trade-offs among ecological integrity, cultural heritage, and visual quality. Sensitivity analysis displays that case rankings remain stable across four extreme weighting scenarios (cultural, ecological, visual, equal), with only one swap (Xingfu Pastoral Park and Nongke Village) under ecological priority and no rank change greater than one position, confirming that the results are not driven by any specific weight assignment. This approach extends the utility of LCA in high-density rural cultural landscapes and offers a practical tool for differentiated conservation and management, especially in tourism-influenced rural settings on the Chengdu Plain. Transferability to other regions would require recalibration of locally relevant indicators.