New framework for land surface temperature and emissivity inversion based on hyperspectral thermal infrared data
文献类型：期刊论文
| 作者 | Li, Xiujuan; Wu, Hua; Ni, Li; Zhang, Yuze; Jiang, Xiaoguang |
| 刊名 | INTERNATIONAL JOURNAL OF REMOTE SENSING
 |
| 出版日期 | 2023-06-03 |
| ISSN号 | 1366-5901 |
| DOI | 10.1080/01431161.2023.2216855 |
| 产权排序 | 1 |
| 文献子类 | Article ; Early Access |
| 英文摘要 | Hyperspectral thermal infrared (HTIR) data offers enormous potential for land surface temperature (LST) and emissivity (LSE) inversion. Methods to fully use a large amount of spectral information, while avoiding data redundancy, is constantly being explored. Therefore, a new framework for LST and LSE inversion using HTIR data is proposed in this study. First, the stepwise iteration method based on information content was used to select channels that were more sensitive to land surface information. Principal component analysis (PCA) and a two-step machine learning method were then used to retrieve the LST and LSE based on the selected channels. The findings demonstrate that the LST and spectra of the LSE can be obtained simultaneously based on the proposed framework. An LST inversion accuracy of 1.5K and an emissivity inversion accuracy of 0.017 can be achieved. However, an increase in the number of channels does not result in superior outcomes. Satisfactory inversion results can be obtained by selecting only 10-35 channels with the highest information content. In conclusion, this framework can be used to guide channel selection and land surface parameters inversion for HTIR sensors. |
| 学科主题 | Remote Sensing ; Imaging Science & Photographic Technology |
| WOS关键词 | NEURAL-NETWORK TECHNIQUE ; CHANNEL SELECTION ; RETRIEVAL ALGORITHM ; PARAMETERS ; SEPARATION ; WATER |
| WOS研究方向 | Remote Sensing ; Imaging Science & Photographic Technology |
| 出版者 | TAYLOR & FRANCIS LTD |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/193768]  |
| 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.Chinese Academy of Sciences 2.Institute of Geographic Sciences & Natural Resources Research, CAS 3.University of Chinese Academy of Sciences, CAS |
| 推荐引用方式 GB/T 7714 | Li, Xiujuan,Wu, Hua,Ni, Li,et al. New framework for land surface temperature and emissivity inversion based on hyperspectral thermal infrared data[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2023. |
| APA | Li, Xiujuan,Wu, Hua,Ni, Li,Zhang, Yuze,&Jiang, Xiaoguang.(2023).New framework for land surface temperature and emissivity inversion based on hyperspectral thermal infrared data.INTERNATIONAL JOURNAL OF REMOTE SENSING. |
| MLA | Li, Xiujuan,et al."New framework for land surface temperature and emissivity inversion based on hyperspectral thermal infrared data".INTERNATIONAL JOURNAL OF REMOTE SENSING (2023). |
入库方式： OAI收割
来源：地理科学与资源研究所
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