标题: A Population Spatialization Model at the Building Scale Using Random Forest

作者: Wang, MQ (Wang, Mengqi); Wang, YL (Wang, Yinglin); Li, BZ (Li, Bozhao); Cai, ZL (Cai, Zhongliang); Kang, MJ (Kang, Mengjun)

来源出版物: REMOTE SENSING 卷: 14 期: 8 文献号: 1811 DOI: 10.3390/rs14081811 出版年: APR 2022

摘要: Population spatialization reveals the distribution and quantity of the population in geographic space with gridded population maps. Fine-scale population spatialization is essential for urbanization and disaster prevention. Previous approaches have used remotely sensed imagery to disaggregate census data, but this approach has limitations. For example, large-scale population censuses cannot be conducted in underdeveloped countries or regions, and remote sensing data lack semantic information indicating the different human activities occurring in a precise geographic location. Geospatial big data and machine learning provide new fine-scale population distribution mapping methods. In this paper, 30 features are extracted using easily accessible multisource geographic data. Then, a building-scale population estimation model is trained by a random forest (RF) regression algorithm. The results show that 91% of the buildings in Lin'an District have absolute error values of less than six compared with the actual population data. In a comparison with a multiple linear (ML) regression model, the mean absolute errors of the RF and ML models are 2.52 and 3.21, respectively, the root mean squared errors are 8.2 and 9.8, and the R-2 values are 0.44 and 0.18. The RF model performs better at building-scale population estimation using easily accessible multisource geographic data. Future work will improve the model accuracy in densely populated areas.

入藏号: WOS:000788060500001

语言: English

文献类型: Article

作者关键词: population spatialization; random forest model; building scale

地址: [Wang, Mengqi; Wang, Yinglin; Li, Bozhao; Cai, Zhongliang; Kang, Mengjun] Wuhan Univ, Sch Resource & Environm Sci, 129 Luoyu Rd, Wuhan 310029, Peoples R China.

[Kang, Mengjun] Beijing Key Lab Urban Spatial Informat Engn, Beijing 100045, Peoples R China.

通讯作者地址: Cai, ZL (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, 129 Luoyu Rd, Wuhan 310029, Peoples R China.

电子邮件地址: mqwang@whu.edu.cn; 2018282050148@whu.edu.cn; libozhao@whu.edu.cn; zlcai@whu.edu.cn; mengjunk@whu.edu.cn

影响因子：4.848