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Spatially Explicit Mapping of Historical Population Density with Random Forest Regression: A Case Study of Gansu Province, China, in 1820 and 2000

文献类型：期刊论文

作者Wang, Fahao2,5; Lu, Weidong1; Zheng, Jingyun2,3; Li, Shicheng4; Zhang, Xuezhen2,3
刊名SUSTAINABILITY
出版日期2020-02-01
卷号12期号:3页码:16
关键词historical period random forest regression model population density prediction Gansu Province
DOI10.3390/su12031231
通讯作者Zhang, Xuezhen(xzzhang@igsnrr.ac.cn)
英文摘要This study established a random forest regression model (RFRM) using terrain factors, climatic and river factors, distances to the capitals of provinces, prefectures (Fu, in Chinese Pinyin), and counties as independent variables to predict the population density. Then, using the RFRM, we explicitly reconstructed the spatial distribution of the population density of Gansu Province, China, in 1820 and 2000, at a resolution of 10 by 10 km. By comparing the explicit reconstruction with census data at the township level from 2000, we found that the RFRM-based approach mostly reproduced the spatial variability in the population density, with a determination coefficient (R-2) of 0.82, a positive reduction of error (RE, 0.72) and a coefficient of efficiency (CE) of 0.65. The RFRM-based reconstructions show that the population of Gansu Province in 1820 was mostly distributed in the Lanzhou, Gongchang, Pingliang, Qinzhou, Qingyang, and Ningxia prefecture. The macro-spatial pattern of the population density in 2000 kept approximately similar with that in 1820. However, fine differences could be found. The 79.92% of the population growth of Gansu Province from 1820 to 2000 occurred in areas lower than 2500 m. As a result, the population weighting in the areas above 2500 m was similar to 9% in 1820 while it was greater than 14% in 2000. Moreover, in comparison to 1820, the population density intensified in Lanzhou, Xining, Yinchuan, Baiyin, Linxia, and Tianshui, while it weakened in Gongchang, Qingyang, Ganzhou, and Suzhou.
WOS关键词INTERPOLATION METHODS ; QILIAN MOUNTAINS ; HUMAN SETTLEMENT ; RELIEF DEGREE ; LAND-SURFACE ; RECONSTRUCTION ; CLIMATE ; IMAGERY ; CARBON ; PERIOD
资助项目Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19040101] ; National Key Research and Development Program of China[2017YFA0603300] ; Key Research Program from CAS[QYZDB-SSW-DQC005] ; Key Research Program from CAS[ZDRW-ZS-2017-4]
WOS研究方向Science & Technology - Other Topics ; Environmental Sciences & Ecology
语种英语
WOS记录号WOS:000524899604012
出版者MDPI
资助机构Strategic Priority Research Program of the Chinese Academy of Sciences ; National Key Research and Development Program of China ; Key Research Program from CAS
源URL[http://ir.igsnrr.ac.cn/handle/311030/133811]  
专题中国科学院地理科学与资源研究所
通讯作者Zhang, Xuezhen
作者单位1.Fudan Univ, Ctr Hist Geog Studies, Shanghai 200433, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China
3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
4.China Univ Geosci, Sch Publ Adm, Dept Land Resource Management, Wuhan 430074, Peoples R China
5.Shandong Normal Univ, Coll Geog & Environm, Jinan 250358, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Fahao,Lu, Weidong,Zheng, Jingyun,et al. Spatially Explicit Mapping of Historical Population Density with Random Forest Regression: A Case Study of Gansu Province, China, in 1820 and 2000[J]. SUSTAINABILITY,2020,12(3):16.
APA Wang, Fahao,Lu, Weidong,Zheng, Jingyun,Li, Shicheng,&Zhang, Xuezhen.(2020).Spatially Explicit Mapping of Historical Population Density with Random Forest Regression: A Case Study of Gansu Province, China, in 1820 and 2000.SUSTAINABILITY,12(3),16.
MLA Wang, Fahao,et al."Spatially Explicit Mapping of Historical Population Density with Random Forest Regression: A Case Study of Gansu Province, China, in 1820 and 2000".SUSTAINABILITY 12.3(2020):16.

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来源：地理科学与资源研究所

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