{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T15:13:35Z","timestamp":1787238815967,"version":"build-2736575974"},"reference-count":10,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2019,9,19]],"date-time":"2019-09-19T00:00:00Z","timestamp":1568851200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The importance of monitoring, preserving, and, where needed, improving the quality of water resources in the open ocean, coastal regions, estuaries, and inland water bodies cannot be overstated [...]<\/jats:p>","DOI":"10.3390\/rs11182178","type":"journal-article","created":{"date-parts":[[2019,9,19]],"date-time":"2019-09-19T03:40:06Z","timestamp":1568864406000},"page":"2178","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Editorial for the Special Issue \u201cRemote Sensing of Water Quality\u201d"],"prefix":"10.3390","volume":"11","author":[{"given":"Wesley J.","family":"Moses","sequence":"first","affiliation":[{"name":"U.S. Naval Research Laboratory, Remote Sensing Division, Coastal and Ocean Remote Sensing Branch, 4555 Overlook Ave SW, Washington, DC 20375, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4940-5987","authenticated-orcid":false,"given":"W. David","family":"Miller","sequence":"additional","affiliation":[{"name":"U.S. Naval Research Laboratory, Remote Sensing Division, Coastal and Ocean Remote Sensing Branch, 4555 Overlook Ave SW, Washington, DC 20375, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Huang, C., Jiang, Q., Yao, L., Li, Y., Yang, H., Huang, T., and Zhang, M. (2017). Spatiotemporal Variation in Particulate Organic Carbon Based on Long-Term MODIS Observations in Taihu Lake, China. Remote Sens., 9.","DOI":"10.3390\/rs9060624"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Lobo, F., Costa, M., Novo, E., and Telmer, K. (2017). Effects of Small-Scale Gold Mining Tailings on the Underwater Light Field in the Tapaj\u00f3s River Basin, Brazilian Amazon. Remote Sens., 9.","DOI":"10.3390\/rs9080861"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Carswell, T., Costa, M., Young, E., Komick, N., Gower, J., and Sweeting, R. (2017). Evaluation of MODIS-Aqua Atmospheric Correction and Chlorophyll Products of Western North American Coastal Waters Based on 13 Years of Data. Remote Sens., 9.","DOI":"10.3390\/rs9101063"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Toming, K., Kutser, T., Uiboupin, R., Arikas, A., Vahter, K., and Paavel, B. (2017). Mapping Water Quality Parameters with Sentinel-3 Ocean and Land Colour Instrument imagery in the Baltic Sea. Remote Sens., 9.","DOI":"10.3390\/rs9101070"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Robert, E., Kergoat, L., Soumaguel, N., Merlet, S., Martinez, J., Diawara, M., and Grippa, M. (2017). Analysis of Suspended Particulate Matter and Its Drivers in Sahelian Ponds and Lakes by Remote Sensing (Landsat and MODIS): Gourma Region, Mali. Remote Sens., 9.","DOI":"10.3390\/rs9121272"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Renosh, P., Jourdin, F., Charantonis, A., Yala, K., Rivier, A., Badran, F., Thiria, S., Guillou, N., Leckler, F., and Gohin, F. (2017). Construction of Multi-Year Time-Series Profiles of Suspended Particulate Inorganic Matter Concentrations Using Machine Learning Approach. Remote Sens., 9.","DOI":"10.3390\/rs9121320"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"G\u00f6ritz, A., Berger, S., Gege, P., Grossart, H., Nejstgaard, J., Riedel, S., R\u00f6ttgers, R., and Utschig, C. (2018). Retrieval of Water Constituents from Hyperspectral In-Situ Measurements under Variable Cloud Cover\u2014A Case Study at Lake Stechlin (Germany). Remote Sens., 10.","DOI":"10.3390\/rs10020181"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"McCarthy, M., Otis, D., M\u00e9ndez-L\u00e1zaro, P., and Muller-Karger, F. (2018). Water Quality Drivers in 11 Gulf of Mexico Estuaries. Remote Sens., 10.","DOI":"10.3390\/rs10020255"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Kratzer, S., and Moore, G. (2018). Inherent Optical Properties of the Baltic Sea in Comparison to Other Seas and Oceans. Remote Sens., 10.","DOI":"10.3390\/rs10030418"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Pahlevan, N., Balasubramanian, S., Sarkar, S., and Franz, B. (2018). Toward Long-Term Aquatic Science Products from Heritage Landsat Missions. Remote Sens., 10.","DOI":"10.3390\/rs10091337"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/18\/2178\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:21:39Z","timestamp":1760188899000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/18\/2178"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,19]]},"references-count":10,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2019,9]]}},"alternative-id":["rs11182178"],"URL":"https:\/\/doi.org\/10.3390\/rs11182178","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,9,19]]}}}