地球信息科学学报 ›› 2022, Vol. 24 ›› Issue (10): 2045-2057.doi: 10.12082/dqxxkx.2022.210712
刘智谦1(), 吕建军1, 姚尧1,2,*(
), 张嘉琪1, 寇世浩1, 关庆锋1
收稿日期:
2021-11-05
修回日期:
2022-01-20
出版日期:
2022-10-25
发布日期:
2022-12-25
通讯作者:
*姚尧(1987— ),男,广东梅州人,博士,副教授,研究方向为空间大数据和城市计算。E-mail: yaoy@cug.edu.cn作者简介:
刘智谦(1997— ),男,四川达州人,硕士生,研究方向为城市计算和空间分析。E-mail: liuzhiqian@cug.edu.cn
基金资助:
LIU Zhiqian1(), LV Jianjun1, YAO Yao1,2,*(
), ZHANG Jiaqi1, KOU Shihao1, GUAN Qingfeng1
Received:
2021-11-05
Revised:
2022-01-20
Online:
2022-10-25
Published:
2022-12-25
Contact:
YAO Yao
Supported by:
摘要:
理解城市环境对人类感知的影响,对城市合理规划及布局具有重要的人文参考价值。城市环境是一个动态变化的复杂系统,具有空间异质性的特点。由于研究方法的限制,在复杂的城市环境中,以往基于街景图像的城市感知研究难以全面精细地分析环境关键要素对人类感知的影响。本研究以武汉市中心为研究区,首先利用全卷积神经网络将街景图像分割为城市地物类型,耦合感知打分数据和随机森林算法建立6类城市感知模型;然后基于沙普利值方法分解在随机森林模型中各类城市地物对人类感知的影响,并识别城市环境关键要素;最后结合分解结果,探究在非线性模型中沙普利值方法的适用性和优势。结果表明:沙普利值方法能够有效考虑环境异质性,精确地定量表示在不同场景中各类地物对人类感知的影响;城市高楼、天空、绿地空间是对人类感知影响最大的3类地物,且地物的体积和分布与其对人类感知的影响有关,图像占比大、分布连续的地物对人类感知的影响比图像占比小、分布离散的地物对人类感知的影响大;受城市环境空间异质性的影响,主要地物类型对各类感知的影响程度和形式有显著不同;高楼与人类感知为非线性关系,且具有明显的单调递增或递减的形式;绿地空间与积极感知呈非线性关系,与消极感知呈线性递减的关系。基于可解释性方法,本研究主要分析城市环境关键要素对人类感知的影响特点,探究了城市感知模型中的可解释性问题,能够为城市感知相关研究提供方法参考和理论依据,同时也可为城市规划和景观设计提供参考。
刘智谦, 吕建军, 姚尧, 张嘉琪, 寇世浩, 关庆锋. 基于街景图像的可解释性城市感知模型研究方法[J]. 地球信息科学学报, 2022, 24(10): 2045-2057.DOI:10.12082/dqxxkx.2022.210712
LIU Zhiqian, LV Jianjun, YAO Yao, ZHANG Jiaqi, KOU Shihao, GUAN Qingfeng. Research Method of Interpretable Urban Perception Model based on Street View Imagery[J]. Journal of Geo-information Science, 2022, 24(10): 2045-2057.DOI:10.12082/dqxxkx.2022.210712
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