Xiran Zhou, Jiawei Chen, Todd E. Rakstad, M. Ploughe, P. Tang
{"title":"基于高分辨率遥感数据的城市渠系水体叶绿素估算","authors":"Xiran Zhou, Jiawei Chen, Todd E. Rakstad, M. Ploughe, P. Tang","doi":"10.1109/lgrs.2020.3011074","DOIUrl":null,"url":null,"abstract":"Water quality, which is a key concern associated with large-scale canal operation and management, is vulnerable to the influences from short-term weather variations and artificial activities. Chlorophyll is one of the key indicators to measure the water quality and usability for drinking and irrigation in the canal system. However, previous research designed the state-of-the-art algorithms regarding water chlorophyll estimation using medium-resolution remote sensing data (e.g., Landsat), which has insufficient resolution to capture canals that are usually narrower than one pixel in such data. High-resolution imageries covering the whole canal network might include only either visible wavebands (i.e., red, green, blue bands) or cost thousands of dollars for an effective investigation on real-time water chlorophyll monitoring. Thus, the strategy designed for water chlorophyll analysis in a canal should consider an appropriate tradeoff among spatial resolution, the spectrum helpful for chlorophyll detection, and the financial burden. This letter presents our efforts on identifying and assessing the extent of the Planet data for measuring chlorophyll degree of canal waters. The experiments show that although Planet can represent the relative variation in water chlorophyll concentration, new algorithms are still necessary for accurate results regarding water chlorophyll variations in a canal system.","PeriodicalId":13046,"journal":{"name":"IEEE Geoscience and Remote Sensing Letters","volume":"18 1","pages":"1876-1880"},"PeriodicalIF":4.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/lgrs.2020.3011074","citationCount":"1","resultStr":"{\"title\":\"Water Chlorophyll Estimation in an Urban Canal System With High-Resolution Remote Sensing Data\",\"authors\":\"Xiran Zhou, Jiawei Chen, Todd E. Rakstad, M. Ploughe, P. Tang\",\"doi\":\"10.1109/lgrs.2020.3011074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Water quality, which is a key concern associated with large-scale canal operation and management, is vulnerable to the influences from short-term weather variations and artificial activities. Chlorophyll is one of the key indicators to measure the water quality and usability for drinking and irrigation in the canal system. However, previous research designed the state-of-the-art algorithms regarding water chlorophyll estimation using medium-resolution remote sensing data (e.g., Landsat), which has insufficient resolution to capture canals that are usually narrower than one pixel in such data. High-resolution imageries covering the whole canal network might include only either visible wavebands (i.e., red, green, blue bands) or cost thousands of dollars for an effective investigation on real-time water chlorophyll monitoring. Thus, the strategy designed for water chlorophyll analysis in a canal should consider an appropriate tradeoff among spatial resolution, the spectrum helpful for chlorophyll detection, and the financial burden. This letter presents our efforts on identifying and assessing the extent of the Planet data for measuring chlorophyll degree of canal waters. The experiments show that although Planet can represent the relative variation in water chlorophyll concentration, new algorithms are still necessary for accurate results regarding water chlorophyll variations in a canal system.\",\"PeriodicalId\":13046,\"journal\":{\"name\":\"IEEE Geoscience and Remote Sensing Letters\",\"volume\":\"18 1\",\"pages\":\"1876-1880\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/lgrs.2020.3011074\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Geoscience and Remote Sensing Letters\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1109/lgrs.2020.3011074\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Geoscience and Remote Sensing Letters","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1109/lgrs.2020.3011074","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Water Chlorophyll Estimation in an Urban Canal System With High-Resolution Remote Sensing Data
Water quality, which is a key concern associated with large-scale canal operation and management, is vulnerable to the influences from short-term weather variations and artificial activities. Chlorophyll is one of the key indicators to measure the water quality and usability for drinking and irrigation in the canal system. However, previous research designed the state-of-the-art algorithms regarding water chlorophyll estimation using medium-resolution remote sensing data (e.g., Landsat), which has insufficient resolution to capture canals that are usually narrower than one pixel in such data. High-resolution imageries covering the whole canal network might include only either visible wavebands (i.e., red, green, blue bands) or cost thousands of dollars for an effective investigation on real-time water chlorophyll monitoring. Thus, the strategy designed for water chlorophyll analysis in a canal should consider an appropriate tradeoff among spatial resolution, the spectrum helpful for chlorophyll detection, and the financial burden. This letter presents our efforts on identifying and assessing the extent of the Planet data for measuring chlorophyll degree of canal waters. The experiments show that although Planet can represent the relative variation in water chlorophyll concentration, new algorithms are still necessary for accurate results regarding water chlorophyll variations in a canal system.
期刊介绍:
IEEE Geoscience and Remote Sensing Letters (GRSL) is a monthly publication for short papers (maximum length 5 pages) addressing new ideas and formative concepts in remote sensing as well as important new and timely results and concepts. Papers should relate to the theory, concepts and techniques of science and engineering as applied to sensing the earth, oceans, atmosphere, and space, and the processing, interpretation, and dissemination of this information. The technical content of papers must be both new and significant. Experimental data must be complete and include sufficient description of experimental apparatus, methods, and relevant experimental conditions. GRSL encourages the incorporation of "extended objects" or "multimedia" such as animations to enhance the shorter papers.