MRSEILA: A modified remote sensing ecological index using local adaptability for enhancing ecological environment quality assessment
文献类型：期刊论文
| 作者 | Guo, Yingzhang1,2; Zhan, Mingjin3; Xu, Hanzeyu4,5,6,12; Li, Xiao7,8; Fang, Junjun9,10; Zhou, Xingchen2,11; Lin, Dan1; Chen, Wenhui2,12 |
| 刊名 | ECOLOGICAL INFORMATICS
 |
| 出版日期 | 2025-12-01 |
| 卷号 | 90页码:103238 |
| 关键词 | Ecological environment quality (EEQ) Remote sensing ecological index (RSEI) Moving window Principal component analysis (PCA) Eigenvector direction |
| ISSN号 | 1574-9541 |
| DOI | 10.1016/j.ecoinf.2025.103238 |
| 产权排序 | 9 |
| 文献子类 | Article |
| 英文摘要 | The Remote Sensing Ecological Index (RSEI) has been widely applied in ecological environment quality (EEQ) assessments by integrating multiple environmental factors. To enhance RSEI's ability to capture local ecological variations, a locally adapted version (RSEILA) was designed and widely adopted using moving windows. However, the randomness in eigenvector directions generated by principal component analysis (PCA) can introduce bias, affecting the accuracy of RSEILA's assessment. To enhance the effectiveness of RSEILA in EEQ, we propose a modified RSEILA model (MRSEILA) implemented on the Google Earth Engine (GEE) platform, consisting of three components: (1) optimization of moving window sizes tailored to each target region; (2) automatic recognition and correction of PCA-induced eigenvector direction inconsistencies; and (3) refinement of PCA computation within each circular window to improve the accuracy of EEQ evaluations. We validated MRSEILA using Landsat Collection 2 Level-2 surface reflectance data and compared its performance with RSEILA across four typical areas in China. The results showed that, compared to RSEILA, MRSEILA consistently produces aligned eigenvector directions and more accurate EEQ assessments that better reflect actual land surface conditions across all four testing areas, making it an effective tool for regional and large-scale ecological monitoring. |
| URL标识 | 查看原文 |
| WOS关键词 | PERFORMANCE |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001508186000001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/214499]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Xu, Hanzeyu; Chen, Wenhui |
| 作者单位 | 1.Fujian Mapping Inst, Fuzhou 350001, Peoples R China; 2.Fujian Normal Univ, Sch Geog Sci, Sch Carbon Neutral Future Technol, Fuzhou 350117, Peoples R China; 3.Jiangxi Vocat & Tech Coll Informat Applicat, Nanchang 330043, Peoples R China; 4.Yangzhou Univ, Agr Coll, Jiangsu Key Lab Crop Genet & Physiol, Jiangsu Key Lab Crop Cultivat & Physiol, Yangzhou 225009, Peoples R China; 5.Yangzhou Univ, Jiangsu Coinnovat Ctr Modern Prod Technol Grain Cr, Yangzhou 225009, Peoples R China; 6.Yangzhou Univ, Res Inst Smart Agr, Yangzhou 225009, Peoples R China; 7.Univ Oxford, Transport Studies Unit, Oxford OX1 3QY, England; 8.Univ Oxford, Linacre Coll, Oxford OX1 3JA, England; 9.Chinese Acad Sci, State Key Lab Resource & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 10.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Guo, Yingzhang,Zhan, Mingjin,Xu, Hanzeyu,et al. MRSEILA: A modified remote sensing ecological index using local adaptability for enhancing ecological environment quality assessment[J]. ECOLOGICAL INFORMATICS,2025,90:103238. |
| APA | Guo, Yingzhang.,Zhan, Mingjin.,Xu, Hanzeyu.,Li, Xiao.,Fang, Junjun.,...&Chen, Wenhui.(2025).MRSEILA: A modified remote sensing ecological index using local adaptability for enhancing ecological environment quality assessment.ECOLOGICAL INFORMATICS,90,103238. |
| MLA | Guo, Yingzhang,et al."MRSEILA: A modified remote sensing ecological index using local adaptability for enhancing ecological environment quality assessment".ECOLOGICAL INFORMATICS 90(2025):103238. |
入库方式： OAI收割
来源：地理科学与资源研究所
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