Observational modeling study demonstrates that microclimate regulation and waterfront openness enhance visitor comfort and stay duration, indicating key pathways for adaptive coastal design.
Understanding the interaction between environmental conditions and human behavioral responses is essential for developing adaptive and intelligent public-service infrastructures in complex coastal environments. This study proposes an integrated evaluation–coupling framework for climate-adaptive perception and behavior-aware optimization based on a coastal service hub in Haikou, China. A multi-source environmental sensing and assessment system is first established by integrating spatial attributes, microclimate characteristics, environmental perception indicators, and user behavioral observations. The relative importance of environmental variables is quantified using the Analytic Hierarchy Process (AHP), while Structural Equation Modeling (SEM) is employed to investigate the coupling mechanisms between environmental stimuli, perceptual responses, and behavioral outcomes. Experimental analysis demonstrates that viewscape coverage, waterfront openness, and microclimate regulation are the dominant factors influencing spatial performance and user engagement. The results further reveal significant perception-mediated pathways in which climate-adaptive environmental conditions enhance user comfort and prolong stay duration, while cultural expressiveness improves revisit intention through strengthened place identity. Based on the identified coupling relationships, a climate-adaptive and behavior-guided optimization framework is developed to support intelligent environmental regulation and adaptive spatial decision-making. The proposed methodology provides an effective approach for environmental signal representation, multi-source information fusion, behavioral response modeling, and adaptive optimization in smart coastal infrastructures, with potential applications in intelligent sensing, human-centric environmental systems, and next-generation adaptive service environments.
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Yuan et al. (2026) studied this question.
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