Mapping Gross Domestic Product Distribution at 1 km Resolution across Thailand Using the Random Forest Area-to-Area Regression Kriging Model
文献类型：期刊论文
| 作者 | Jin, Yan4,5; Ge, Yong1,3; Fan, Haoyu4,5; Li, Zeshuo4,5; Liu, Yaojie2; Jia, Yan4,5 |
| 刊名 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
 |
| 出版日期 | 2023-12-01 |
| 卷号 | 12期号:12页码:24 |
| 关键词 | gridded GDP random forest area-to-area kriging Thailand |
| DOI | 10.3390/ijgi12120481 |
| 通讯作者 | Ge, Yong(gey@lreis.ac.cn) |
| 英文摘要 | Accurate spatial distribution of gridded gross domestic product (GDP) data is crucial for revealing regional disparities within administrative units, thus facilitating a deeper understanding of regional economic dynamics, industrial distribution, and urbanization trends. The existing GDP spatial models often rely on prediction residuals for model evaluation or utilize residual distribution to improve the final accuracy, frequently overlooking the modifiable areal unit problem within residual distribution. This paper introduces a hybrid downscaling model that combines random forest and area-to-area kriging to map gridded GDP. Employing Thailand as a case study, GDP distribution maps were generated at a 1 km spatial resolution for the year 2015 and compared with five alternative downscaling methods and an existing GDP product. The results demonstrate that the proposed approach yields higher accuracy and greater precision in detailing GDP distribution, as evidenced by the smallest mean absolute error and root mean squared error values, which stand at USD 256.458 and 699.348 ten million, respectively. Among the four different sets of auxiliary variables considered, one consistently exhibited a higher prediction accuracy. This particular set of auxiliary variables integrated classification-based variables, illustrating the advantages of incorporating such integrated variables into modeling while accounting for classification characteristics. |
| WOS关键词 | NIGHTTIME LIGHT DATA ; LAND-COVER DATA ; SATELLITE IMAGERY ; ECOSYSTEM SERVICES ; ECONOMIC-ACTIVITY ; GDP ; POPULATION ; VALUES ; LEVEL |
| 资助项目 | National Natural Science Foundation of China |
| WOS研究方向 | Computer Science ; Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:001130494100001 |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/201266]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Ge, Yong |
| 作者单位 | 1.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Nanjing Univ Informat Sci & Technol, Sch Geog Sci, Nanjing 210044, Peoples R China 3.Jiangxi Normal Univ, Key Lab Poyang Lake Wetland & Watershed Res, Minist Educ, Nanchang 330022, Peoples R China 4.Smart Hlth Big Data Anal & Locat Serv Engn Lab Jia, Nanjing 210023, Peoples R China 5.Nanjing Univ Posts & Telecommun, Sch Internet Things, Nanjing 210023, Peoples R China |
| 推荐引用方式 GB/T 7714 | Jin, Yan,Ge, Yong,Fan, Haoyu,et al. Mapping Gross Domestic Product Distribution at 1 km Resolution across Thailand Using the Random Forest Area-to-Area Regression Kriging Model[J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,2023,12(12):24. |
| APA | Jin, Yan,Ge, Yong,Fan, Haoyu,Li, Zeshuo,Liu, Yaojie,&Jia, Yan.(2023).Mapping Gross Domestic Product Distribution at 1 km Resolution across Thailand Using the Random Forest Area-to-Area Regression Kriging Model.ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION,12(12),24. |
| MLA | Jin, Yan,et al."Mapping Gross Domestic Product Distribution at 1 km Resolution across Thailand Using the Random Forest Area-to-Area Regression Kriging Model".ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 12.12(2023):24. |
入库方式： OAI收割
来源：地理科学与资源研究所
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