Exploring the Spatial Coupling Between Visual and Ecological Sensitivity: A Cross-Modal Approach Using Deep Learning in Tianjin’s Central Urban Area

Zhihao Kang, Chenfeng Xu, Yang Gu, Lunsai Wu, Zhiqiu He, Xiaoxu Heng, Xiaofei Wang and Yike Hu ()
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Zhihao Kang: The School of Architecture, Tianjin University, Tianjin 300072, China
Chenfeng Xu: The School of Architecture, Tianjin University, Tianjin 300072, China
Yang Gu: The School of Architecture, Tianjin University, Tianjin 300072, China
Lunsai Wu: The School of Architecture, Tianjin University, Tianjin 300072, China
Zhiqiu He: Tianjin Xinjian Construction Co., Ltd., Tianjin 300220, China
Xiaoxu Heng: Tianjin Port Bonded Zone Urban Renewal Investment and Construction Group, Tianjin 300450, China
Xiaofei Wang: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Yike Hu: The School of Architecture, Tianjin University, Tianjin 300072, China

Land, 2025, vol. 14, issue 11, 1-25

Abstract: Amid rapid urbanization, Chinese cities face mounting ecological pressure, making it critical to balance environmental protection with public well-being. As visual perception accounts for over 80% of environmental information acquisition, it plays a key role in shaping experiences and evaluations of ecological space. However, current ecological planning often overlooks public perception, leading to increasing mismatches between ecological conditions and spatial experiences. While previous studies have attempted to introduce public perspectives, a systematic framework for analyzing the spatial relationship between ecological and visual sensitivity remains lacking. This study takes 56,210 street-level points in Tianjin’s central urban area to construct a coordinated analysis framework of ecological and perceptual sensitivity. Visual sensitivity is derived from social media sentiment analysis (via GPT-4o) and street-view image semantic features extracted using the ADE20K semantic segmentation model, and subsequently processed through a Multilayer Perceptron (MLP) model. Ecological sensitivity is calculated using the Analytic Hierarchy Process (AHP)—based model integrating elevation, slope, normalized difference vegetation index (NDVI), land use, and nighttime light data. A coupling coordination model and bivariate Moran’s I are employed to examine spatial synergy and mismatches between the two dimensions. Results indicate that while 72.82% of points show good coupling, spatial mismatches are widespread. The dominant types include “HL” (high visual–low ecological) areas (e.g., Wudadao) with high visual attention but low ecological resilience, and “LH” (low visual–high ecological) areas (e.g., Huaiyuanli) with strong ecological value but low public perception. This study provides a systematic path for analyzing the spatial divergence between ecological and perceptual sensitivity, offering insights into ecological landscape optimization and perception-driven street design.

Keywords: ecological sensitivity; street view image analysis; social media data; visual perception; urbanization; ecological security pattern (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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