| 论文题目： | Spatial sampling, data models, spatial scale and ontologies: Interpreting spatial statistics and machine learning applied to satellite optical remote sensing |
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| 第一作者： | Atkinson Peter M., Stein A., Jeganathan C. |
| 联系作者： | |
| 发表年度： | 2022 |
| 摘 要： | This paper summarizes the development and application of spatial statistical models in satellite optical remote sensing. The paper focuses on the development of a conceptual model that includes the measurement and sampling processes inherent in remote sensing. We organized this paper into five main sections: introducing the basis of remote sensing, including measurement and sampling; spatial variation, including variation through the object-based data model; advances in spatial statistical modelling; machine learning and explainable AI; a hierarchical ontological model of the nature of remotely sensed scenes. The paper finishes with a summary. We conclude that optical remote sensing provides an important source of data and information for the development of spatial statistical techniques that, in turn, serve as powerful tools to obtain important information from the images. (c) 2022 The Authors. Published by Elsevier B.V. This is an open (http://creativecommons.org/licenses/by/4.0/). |
| 英文摘要： | |
| 刊物名称： | SPATIAL STATISTICS |
| 全文链接： | |
| 论文类别： | SCI |
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