A detection method for multi-type earth's surface anomalies based on multi-dimensional feature space
| Autor: | Haishuo Wei, Kun Jia, Qiao Wang, Biao Cao, Jianbo Qi, Wenzhi Zhao, Kai Yan, Guoqiang Wang, Baolin Xue, Xing Yan |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | International Journal of Digital Earth, Vol 17, Iss 1 (2024) |
| Druh dokumentu: | article |
| ISSN: | 17538947 1753-8955 1753-8947 |
| DOI: | 10.1080/17538947.2024.2398054 |
| Popis: | On-orbit processing is an important research direction in the real-time remote sensing detection of earth's surface anomalies (ESSA). However, existing methods cannot comprehensively utilize multi-dimensional remote sensing characteristics to detect multi-type ESSA simultaneously. Meanwhile, it is difficult to realize the comprehensive utilization of multi-dimensional remote sensing characteristics for the limited storage and computing resources on satellites. Therefore, this study proposed a detection method for multi-type ESSA based on multi-dimensional feature space. The proposed method first selected the remote sensing characteristics reflecting the basic earth's surface elements to construct a multi-dimensional feature space and proposed two comprehensive remote sensing characteristics. Then, these characteristics were used to build a prior knowledge base reflecting the normal earth's surface conditions. Finally, by comparing the real-time acquired data and prior knowledge base, this study completed ESSA detection. The validation results indicated that the proposed method can effectively detect multi-type ESSA with an accuracy of over 85%. Moreover, the proposed method simplifies the large and complex ESSA remote sensing characteristic system, which greatly reduces the complexity of ESSA detection methods and increases the possibility of on-orbit processing. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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