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| Principles and methods of scaling geospatial Earth science data | |
Ge, Yong1,2 ; Jin, Yan3,4; Stein, Alfred5; Chen, Yuehong6; Wang, Jianghao1; Wang, Jinfeng1; Cheng, Qiuming7; Bai, Hexiang8; Liu, Mengxiao1,2; Atkinson, Peter M.9
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| 2019-10-01 | |
| Source Publication | EARTH-SCIENCE REVIEWS (IF:9.724[JCR-2019],10.973[5-Year]) |
| ISSN | 0012-8252 |
| Volume | 197Pages:17 |
| Abstract | The properties of geographical phenomena vary with changes in the scale of measurement. The information observed at one scale often cannot be directly used as information at another scale. Scaling addresses these changes in properties in relation to the scale of measurement, and plays an important role in Earth sciences by providing information at the scale of interest, which may be required for a range of applications, and may be useful for inferring geographical patterns and processes. This paper presents a review of geospatial scaling methods for Earth science data. Based on spatial properties, we propose a methodological framework for scaling addressing upscaling, downscaling and side-scaling. This framework combines scale-independent and scale-dependent properties of geographical variables. It allows treatment of the varying spatial heterogeneity of geographical phenomena, combines spatial autocorrelation and heterogeneity, addresses scale-independent and scale-dependent factors, explores changes in information, incorporates geospatial Earth surface processes and uncertainties, and identifies the optimal scale(s) of models. This study shows that the classification of scaling methods according to various heterogeneities has great potential utility as an underpinning conceptual basis for advances in many Earth science research domains. |
| Keyword | Scaling Change-of-support Autocorrelation Heterogeneity |
| WOS Keyword | HOPFIELD NEURAL-NETWORK ; REMOTELY-SENSED IMAGERY ; LAND DATA ASSIMILATION ; PIXEL MAPPING METHOD ; MARKOV RANDOM-FIELD ; SOIL-MOISTURE ; CLIMATE-CHANGE ; GEOSTATISTICAL APPROACH ; DOWNSCALING METHOD ; HYDRAULIC CONDUCTIVITY |
| DOI | 10.1016/j.earscirev.2019.102897 |
| Indexed By | SCI |
| Language | 英语 |
| WOS Research Area | Geology |
| WOS Subject | Geosciences, Multidisciplinary |
| WOS ID | WOS:000497253500004 |
| Funding Project | National Natural Science Foundation for Distinguished Young Scholars of China[41725006] ; National Natural Science Foundation of China[41531174] ; National Natural Science Foundation of China[41531179] |
| Funding Organization | National Natural Science Foundation for Distinguished Young Scholars of China ; National Natural Science Foundation of China |
| Publisher | ELSEVIER |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.igsnrr.ac.cn/handle/311030/130319 |
| Collection | 资源与环境信息系统国家重点实验室_外文论文 |
| Affiliation | 1.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Nanjing Univ Posts & Telecommun, Sch Geog & Biol Informat, Nanjing 210023, Jiangsu, Peoples R China 4.Smart Hlth Big Data Anal & Locat Serv Engn Lab Ji, Nanjing 210023, Jiangsu, Peoples R China 5.Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, NL-7500 AE Enschede, Netherlands 6.Hohai Univ, Sch Earth Sci & Engn, Nanjing 210098, Jiangsu, Peoples R China 7.China Univ Geosci, State Key Lab Geol Proc & Mineral Resources, Beijing 100083, Peoples R China 8.Shanxi Univ, Sch Comp & Informat Technol, Taiyuan 030006, Shanxi, Peoples R China 9.Univ Lancaster, Lancaster Environm Ctr, Fac Sci & Technol, Lancaster LA1 4YR, England |
| Recommended Citation GB/T 7714 | Ge, Yong,Jin, Yan,Stein, Alfred,et al. Principles and methods of scaling geospatial Earth science data[J]. EARTH-SCIENCE REVIEWS,2019,197:17. |
| APA | Ge, Yong.,Jin, Yan.,Stein, Alfred.,Chen, Yuehong.,Wang, Jianghao.,...&Atkinson, Peter M..(2019).Principles and methods of scaling geospatial Earth science data.EARTH-SCIENCE REVIEWS,197,17. |
| MLA | Ge, Yong,et al."Principles and methods of scaling geospatial Earth science data".EARTH-SCIENCE REVIEWS 197(2019):17. |
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| Ge-2019-Principles a（3537KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Download | |
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