{"title":"Water quality indication of spectral probability distribution (SPD): correlation between SPD and Forel-Ule index in closed, connected water bodies","authors":"Zhixuan Zhou, Weining Zhu","doi":"10.1080/2150704x.2023.2261150","DOIUrl":null,"url":null,"abstract":"ABSTRACTThe spectral probability distributions (SPD) of water bodies in satellite images have demonstrated the potential for indicating the geographical and environmental features of their watersheds. This implies that SPDs also have the potential for indicating water quality features, but so far there have been no further studies on their correlations. In this study, 690 SPDs of global closed connected water bodies, mainly including lakes and reservoirs, were extracted from Landsat-8 images. These SPDs were classified into seven types, and the entropy of each SPD diagram was calculated. The correlation between the SPD diagram’s entropy and Forel-Ule index (FUI) is relatively good with R2 = 0.5651 – indicating that water bodies with better water quality are usually found to have smaller entropy in their SPD diagrams. This study demonstrates that SPD is a good indicator for not only the aquatic environment but also water quality monitoring.KEYWORDS: Forel-Ule index (FUI)spectral probability distribution (SPD)Landsat-8remote sensingwater quality AcknowledgmentsThis research was funded by the National Natural Science Foundation of China (No. 41971373) and the Science Foundation of Donghai Laboratory (No. DH-2022KF01009).Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe work was supported by the National Natural Science Foundation of China [41971373]; Science Foundation of Donghai Laboratory [DH-2022KF01009].","PeriodicalId":49132,"journal":{"name":"Remote Sensing Letters","volume":"44 1","pages":"0"},"PeriodicalIF":1.4000,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/2150704x.2023.2261150","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACTThe spectral probability distributions (SPD) of water bodies in satellite images have demonstrated the potential for indicating the geographical and environmental features of their watersheds. This implies that SPDs also have the potential for indicating water quality features, but so far there have been no further studies on their correlations. In this study, 690 SPDs of global closed connected water bodies, mainly including lakes and reservoirs, were extracted from Landsat-8 images. These SPDs were classified into seven types, and the entropy of each SPD diagram was calculated. The correlation between the SPD diagram’s entropy and Forel-Ule index (FUI) is relatively good with R2 = 0.5651 – indicating that water bodies with better water quality are usually found to have smaller entropy in their SPD diagrams. This study demonstrates that SPD is a good indicator for not only the aquatic environment but also water quality monitoring.KEYWORDS: Forel-Ule index (FUI)spectral probability distribution (SPD)Landsat-8remote sensingwater quality AcknowledgmentsThis research was funded by the National Natural Science Foundation of China (No. 41971373) and the Science Foundation of Donghai Laboratory (No. DH-2022KF01009).Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe work was supported by the National Natural Science Foundation of China [41971373]; Science Foundation of Donghai Laboratory [DH-2022KF01009].
期刊介绍:
Remote Sensing Letters is a peer-reviewed international journal committed to the rapid publication of articles advancing the science and technology of remote sensing as well as its applications. The journal originates from a successful section, of the same name, contained in the International Journal of Remote Sensing from 1983 –2009. Articles may address any aspect of remote sensing of relevance to the journal’s readership, including – but not limited to – developments in sensor technology, advances in image processing and Earth-orientated applications, whether terrestrial, oceanic or atmospheric. Articles should make a positive impact on the subject by either contributing new and original information or through provision of theoretical, methodological or commentary material that acts to strengthen the subject.