Multiscale Entropy-Based Surface Complexity Analysis for Land Cover Image Semantic Segmentation
文献类型：期刊论文
| 作者 | Li, Lianfa3; Zhu, Zhiping3; Wang, Chengyi1,3 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023-04-01 |
| 卷号 | 15期号:8页码:2192 |
| 关键词 | remote sensing land use land cover surface complexity sampling bias stratification samples deep learning constrained optimization semantic segmentation |
| DOI | 10.3390/rs15082192 |
| 文献子类 | Article |
| 英文摘要 | Recognizing and classifying natural or artificial geo-objects under complex geo-scenes using remotely sensed data remains a significant challenge due to the heterogeneity in their spatial distribution and sampling bias. In this study, we propose a deep learning method of surface complexity analysis based on multiscale entropy. This method can be used to reduce sampling bias and preserve entropy-based invariance in learning for the semantic segmentation of land use and land cover (LULC) images. Our quantitative models effectively identified and extracted local surface complexity scores, demonstrating their broad applicability. We tested our method using the Gaofen-2 image dataset in mainland China and accurately estimated multiscale complexity. A downstream evaluation revealed that our approach achieved similar or better performance compared to several representative state-of-the-art deep learning methods. This highlights the innovative and significant contribution of our entropy-based complexity analysis and its applicability in improving LULC semantic segmentations through optimal stratified sampling and constrained optimization, which can also potentially be used to enhance semantic segmentation under complex geo-scenes using other machine learning methods. |
| 学科主题 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS关键词 | CLASSIFICATION ; NETWORK |
| 语种 | 英语 |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/193499]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Aerosp Informat Res Inst, Natl Engn Res Ctr Geomatics, Datun Rd, Beijing 100101, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Datun Rd, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Lianfa,Zhu, Zhiping,Wang, Chengyi. Multiscale Entropy-Based Surface Complexity Analysis for Land Cover Image Semantic Segmentation[J]. REMOTE SENSING,2023,15(8):2192. |
| APA | Li, Lianfa,Zhu, Zhiping,&Wang, Chengyi.(2023).Multiscale Entropy-Based Surface Complexity Analysis for Land Cover Image Semantic Segmentation.REMOTE SENSING,15(8),2192. |
| MLA | Li, Lianfa,et al."Multiscale Entropy-Based Surface Complexity Analysis for Land Cover Image Semantic Segmentation".REMOTE SENSING 15.8(2023):2192. |
入库方式： OAI收割
来源：地理科学与资源研究所
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