太阳成8722(中国)有限公司-GREEN NO.1

标题: GIS-Based Emotional Computing: A Review of Quantitative Approaches to Measure the Emotion Layer of Human-Environment Relationships

作者: Huang, YJ (Huang, Yingjing); Fei, T (Fei, Teng); Kwan, MP (Kwan, Mei-Po); Kang, YH (Kang, Yuhao); Li, J (Li, Jun); Li, YZ (Li, Yizhuo); Li, X (Li, Xiang); Bian, M (Bian, Meng)

来源出版物: ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 卷: 9 期: 9 文献号: 551 DOI: 10.3390/ijgi9090551 出版年: SEP 2020

摘要: In recent years, with the growing accessibility of abundant contextual emotion information, which is benefited by the numerous georeferenced user-generated content and the maturity of artificial intelligence (AI)-based emotional computing technics, the emotion layer of human-environment relationship is proposed for enriching traditional methods of various related disciplines such as urban planning. This paper proposes the geographic information system (GIS)-based emotional computing concept, which is a novel framework for applying GIS methods to collective human emotion. The methodology presented in this paper consists of three key steps: (1) collecting georeferenced data containing emotion and environment information such as social media and official sites, (2) detecting emotions using AI-based emotional computing technics such as natural language processing (NLP) and computer vision (CV), and (3) visualizing and analyzing the spatiotemporal patterns with GIS tools. This methodology is a great synergy of multidisciplinary cutting-edge techniques, such as GIScience, sociology, and computer science. Moreover, it can effectively and deeply explore the connection between people and their surroundings with the help of GIS methods. Generally, the framework provides a standard workflow to calculate and analyze the new information layer for researchers, in which a measured human-centric perspective onto the environment is possible.

入藏号: WOS:000579994300001

语言: English

文献类型: Review

作者关键词: human-environment relationship; collective emotion; GIS-based emotional computing

地址: [Huang, Yingjing; Fei, Teng; Li, Jun; Li, Yizhuo] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430000, Peoples R China.

[Kwan, Mei-Po] Chinese Univ Hong Kong, Dept Geog & Resource Management, Shatin, Hong Kong, Peoples R China.

[Kwan, Mei-Po] Chinese Univ Hong Kong, Inst Space & Earth Informat Sci, Shatin, Hong Kong, Peoples R China.

[Kwan, Mei-Po] Univ Utrecht, Dept Human Geog & Spatial Planning, NL-3584 CB Utrecht, Netherlands.

[Kang, Yuhao] Univ Wisconsin, Dept Geog, Geospatial Data Sci Lab, Madison, WI 53706 USA.

[Li, Xiang] Informat Engn Univ, Inst Surveying & Mapping, Zhengzhou 450000, Peoples R China.

[Bian, Meng] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430000, Peoples R China.

通讯作者地址: Fei, T (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430000, Peoples R China.

电子邮件地址: huangyingjing@whu.edu.cn; feiteng@whu.edu.cn; mpkwan@cuhk.edu.hk; yuhao.kang@wisc.edu; leejun@whu.edu.cn; liyizhuo@whu.edu.cn; lixiangzzchxy@163.com; bian@whu.edu.cn

影响因子：2.239