Social Media Image-Based Chromatic Characteristics of Biophilic Landscape: A Case Study of the Min River Urban Waterfront, Fuzhou

This study examines how the chromatic characteristics of the Min River urban waterfront are represented in publicly circulated social media images to support place-based biophilic landscape design. Dominant-color records were extracted through pixel-level filtering and per-image K-means clustering in CIELAB space, with image-level lighting-condition interpretation and record-level landscape-element labeling assisted by a multimodal large language model and subsequently reviewed and corrected by the author. Hue distributions and five record-proportion-weighted metrics of saturation, value, vividness, chromatic dissonance, and complexity were examined through an analytical framework integrating temporal scenarios, landscape elements, and lighting conditions. The results reveal a recurrent blue–orange orientation produced by the complementary positioning of multiple landscape elements rather than by any single category. Nighttime imagery showed the highest saturation but the lowest value, whereas dawn and dusk combined relatively high saturation and value and produced the highest vividness and chromatic dissonance. Transitional illumination brought built surfaces closer to natural elements in saturation–value space, while Ward hierarchical clustering identified Color-Affinity Groups that crossed temporal, lighting-condition, and landscape-element boundaries. These findings support a relational interpretation of biophilic color as a condition-dependent configuration rather than a fixed set of element-bound hues. Weighted representative palettes provide scenario-sensitive design references. However, the findings characterize publicly circulated visual representations of the waterfront rather than calibrated physical-color measurements or direct evidence of restorative effects.