A comprehensive review of remote sensing in wetland classification and mapping
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908328100102144 |
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| author | Yuan, Shuai Liang, Xiangan Lin, Tianwu Chen, Shuang Liu, Rui Wang, Jie Zhang, Hongsheng Gong, Peng |
| author_facet | Yuan, Shuai Liang, Xiangan Lin, Tianwu Chen, Shuang Liu, Rui Wang, Jie Zhang, Hongsheng Gong, Peng |
| contents | Wetlands constitute critical ecosystems that support both biodiversity and human well-being; however, they have experienced a significant decline since the 20th century. Back in the 1970s, researchers began to employ remote sensing technologies for wetland classification and mapping to elucidate the extent and variations of wetlands. Although some review articles summarized the development of this field, there is a lack of a thorough and in-depth understanding of wetland classification and mapping: (1) the scientific importance of wetlands, (2) major data, methods used in wetland classification and mapping, (3) driving factors of wetland changes, (4) current research paradigm and limitations, (5) challenges and opportunities in wetland classification and mapping under the context of technological innovation and global environmental change. In this review, we aim to provide a comprehensive perspective and new insights into wetland classification and mapping for readers to answer these questions. First, we conduct a meta-analysis of over 1,200 papers, encompassing wetland types, methods, sensor types, and study sites, examining prevailing trends in wetland classification and mapping. Next, we review and synthesize the wetland features and existing data and methods in wetland classification and mapping. We also summarize typical wetland mapping products and explore the intrinsic driving factors of wetland changes across multiple spatial and temporal scales. Finally, we discuss current limitations and propose future directions in response to global environmental change and technological innovation. This review consolidates our understanding of wetland remote sensing and offers scientific recommendations that foster transformative progress in wetland science. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_10842 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A comprehensive review of remote sensing in wetland classification and mapping Yuan, Shuai Liang, Xiangan Lin, Tianwu Chen, Shuang Liu, Rui Wang, Jie Zhang, Hongsheng Gong, Peng Computer Vision and Pattern Recognition Image and Video Processing Wetlands constitute critical ecosystems that support both biodiversity and human well-being; however, they have experienced a significant decline since the 20th century. Back in the 1970s, researchers began to employ remote sensing technologies for wetland classification and mapping to elucidate the extent and variations of wetlands. Although some review articles summarized the development of this field, there is a lack of a thorough and in-depth understanding of wetland classification and mapping: (1) the scientific importance of wetlands, (2) major data, methods used in wetland classification and mapping, (3) driving factors of wetland changes, (4) current research paradigm and limitations, (5) challenges and opportunities in wetland classification and mapping under the context of technological innovation and global environmental change. In this review, we aim to provide a comprehensive perspective and new insights into wetland classification and mapping for readers to answer these questions. First, we conduct a meta-analysis of over 1,200 papers, encompassing wetland types, methods, sensor types, and study sites, examining prevailing trends in wetland classification and mapping. Next, we review and synthesize the wetland features and existing data and methods in wetland classification and mapping. We also summarize typical wetland mapping products and explore the intrinsic driving factors of wetland changes across multiple spatial and temporal scales. Finally, we discuss current limitations and propose future directions in response to global environmental change and technological innovation. This review consolidates our understanding of wetland remote sensing and offers scientific recommendations that foster transformative progress in wetland science. |
| title | A comprehensive review of remote sensing in wetland classification and mapping |
| topic | Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2504.10842 |