City landscapes viewed through home windows influence quality of life, yet perceptions of actual window views at the urban scale remain understudied. This study presents an approach for large-scale mapping of perceptions using 12,334 window view images (WVIs) collected from actual residential properties listed on real estate platforms in Wuhan, China, representing a rarely explored form of urban view imagery that offers advantages over the rendered or simulated window views commonly examined in previous studies. Through a non-immersive virtual reality platform, we collected 27,477 pairwise comparisons across six perceptual dimensions (e.g.\ Vivid) from 304 participants based on 499 WVIs. A hybrid neural network model was trained to predict human perceptions of all crowdsourced WVIs and map their spatial distribution. Results reveal significant spatial autocorrelation with distinct hot and cold spots across the whole city. Floor level strongly influences human perceptions: while higher floors offer more preferred and extensive window views, lower-floor windows provide residents with quiet and vivid views. An inference model further shows that window view composition matters considerably: high ratios of sky, trees, and low-rise buildings enhance people's preferences and perceptions of vividness, whereas high ratios of high-rise buildings increase perceptions of monotony and oppression. Importantly, these effects are non-linear: the excessive presence of certain elements can alter their impact on human perception. This work advances urban-scale understanding of residents' visual experiences and provides evidence-based guidance for human-centric urban planning and real estate to optimise visual landscapes from windows.

翻译：透过住宅窗户所见的城市景观影响生活质量，然而城市尺度下真实窗景的感知研究仍显不足。本研究提出了一种大规模感知映射方法，利用从中国武汉市房地产平台采集的12,334张真实住宅窗景图像（WVIs），这是一种鲜少被探索的城市景观影像形式，相较于以往研究中常见的渲染或模拟窗景更具优势。通过非沉浸式虚拟现实平台，我们基于499张WVIs收集了304名参与者在六个感知维度（如生动性）上的27,477组两两比较数据。训练混合神经网络模型以预测所有众包WVIs的人类感知并绘制其空间分布。结果表明，全城范围内存在显著的空间自相关，呈现分明的高值聚集区与低值聚集区。楼层高度显著影响人类感知：较高楼层虽能提供更广阔且更受青睐的窗景，但低楼层窗户能为居民带来静谧与生动的视觉体验。推理模型进一步揭示窗景构成具有重要影响：天空、树木与低层建筑的高占比能提升人们对窗景的偏好与生动感知，而高层建筑的高占比则会增强单调与压抑感。值得注意的是，这些影响呈现非线性特征：特定要素的过度存在会改变其对人类感知的作用方向。本研究推进了城市尺度居民视觉体验的认知，为以人为本的城市规划与房地产行业优化窗口视觉景观提供了循证指导。