{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T16:41:22Z","timestamp":1781368882924,"version":"3.54.1"},"reference-count":91,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,6,15]],"date-time":"2021-06-15T00:00:00Z","timestamp":1623715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003141","name":"Consejo Nacional de Ciencia y Tecnolog\u00eda","doi-asserted-by":"publisher","award":["678957"],"award-info":[{"award-number":["678957"]}],"id":[{"id":"10.13039\/501100003141","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Remote Sensing, as a driver for water management decisions, needs further integration with monitoring water quality programs, especially in developing countries. Moreover, usage of remote sensing approaches has not been broadly applied in monitoring routines. Therefore, it is necessary to assess the efficacy of available sensors to complement the often limited field measurements from such programs and build models that support monitoring tasks. Here, we integrate field measurements (2013\u20132019) from the Mexican national water quality monitoring system (RNMCA) with data from Landsat-8 OLI, Sentinel-3 OLCI, and Sentinel-2 MSI to train an extreme learning machine (ELM), a support vector regression (SVR) and a linear regression (LR) for estimating Chlorophyll-a (Chl-a), Turbidity, Total Suspended Matter (TSM) and Secchi Disk Depth (SDD). Additionally, OLCI Level-2 Products for Chl-a and TSM are compared against the RNMCA data. We observed that OLCI Level-2 Products are poorly correlated with the RNMCA data and it is not feasible to rely only on them to support monitoring operations. However, OLCI atmospherically corrected data is useful to develop accurate models using an ELM, particularly for Turbidity (R2 = 0.7). We conclude that remote sensing is useful to support monitoring systems tasks, and its progressive integration will improve the quality of water quality monitoring programs.<\/jats:p>","DOI":"10.3390\/s21124118","type":"journal-article","created":{"date-parts":[[2021,6,15]],"date-time":"2021-06-15T21:24:29Z","timestamp":1623792269000},"page":"4118","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":66,"title":["Integration of Remote Sensing and Mexican Water Quality Monitoring System Using an Extreme Learning Machine"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8151-8631","authenticated-orcid":false,"given":"Leonardo F.","family":"Arias-Rodriguez","sequence":"first","affiliation":[{"name":"Chair of Hydrology and River Basin Management, Technical University of Munich, 80333 Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zheng","family":"Duan","sequence":"additional","affiliation":[{"name":"Department of Physical Geography and Ecosystem Science, Lund University, S-223 62 Lund, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2467-1031","authenticated-orcid":false,"given":"Jos\u00e9 de Jes\u00fas","family":"D\u00edaz-Torres","sequence":"additional","affiliation":[{"name":"Center for Research and Assistance in Technology and Design of the State of Jalisco, Colinas de la Normal, 44270 Guadalajara, Jalisco, Mexico"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M\u00f3nica","family":"Basilio Hazas","sequence":"additional","affiliation":[{"name":"Chair of Hydrology and River Basin Management, Technical University of Munich, 80333 Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6313-0230","authenticated-orcid":false,"given":"Jingshui","family":"Huang","sequence":"additional","affiliation":[{"name":"Chair of Hydrology and River Basin Management, Technical University of Munich, 80333 Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bapitha Udhaya","family":"Kumar","sequence":"additional","affiliation":[{"name":"Chair of Hydrology and River Basin Management, Technical University of Munich, 80333 Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ye","family":"Tuo","sequence":"additional","affiliation":[{"name":"Chair of Hydrology and River Basin Management, Technical University of Munich, 80333 Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4620-575X","authenticated-orcid":false,"given":"Markus","family":"Disse","sequence":"additional","affiliation":[{"name":"Chair of Hydrology and River Basin Management, Technical University of Munich, 80333 Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,15]]},"reference":[{"key":"ref_1","unstructured":"Morris, B.L., Lawrence, A.R., Chilton, P.J., Adams, B., Calow, R., and Klinck, B.A. (2003). 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