{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T06:53:07Z","timestamp":1768287187514,"version":"3.49.0"},"reference-count":37,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2022,12,10]],"date-time":"2022-12-10T00:00:00Z","timestamp":1670630400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"POCI-FEDER","award":["POCI-01-0247-FEDER-070123"],"award-info":[{"award-number":["POCI-01-0247-FEDER-070123"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Plants"],"abstract":"<jats:p>Monitoring invasive plant species is a crucial task to assess their presence in affected ecosystems. However, it is a laborious and complex task as it requires vast surface areas, with difficult access, to be surveyed. Remotely sensed data can be a great contribution to such operations, especially for clearly visible and predominant species. In the scope of this study, water hyacinth (Eichhornia crassipes) was monitored in the Lower Mondego region (Portugal). For this purpose, Sentinel-2 satellite data were explored enabling us to follow spatial patterns in three water channels from 2018 to 2021. By applying a straightforward and effective methodology, it was possible to estimate areas that could contain water hyacinth and to obtain the total surface area occupied by this invasive species. The normalized difference vegetation index (NDVI) was used for this purpose. It was verified that the occupation of this invasive species over the study area exponentially increases from May to October. However, this increase was not verified in 2021, which could be a consequence of the adopted mitigation measures. To provide the results of this study, the methodology was applied through a semi-automatic geographic information system (GIS) application. This tool enables researchers and ecologists to apply the same approach in monitoring water hyacinth or any other invasive plant species in similar or different contexts. This methodology proved to be more effective than machine learning approaches when applied to multispectral data acquired with an unmanned aerial vehicle. In fact, a global accuracy greater than 97% was achieved using the NDVI-based approach, versus 93% when using the machine learning approach (above 93%).<\/jats:p>","DOI":"10.3390\/plants11243465","type":"journal-article","created":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T03:36:09Z","timestamp":1670816169000},"page":"3465","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Spatio-Temporal Water Hyacinth Monitoring in the Lower Mondego (Portugal) Using Remote Sensing Data"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7570-9773","authenticated-orcid":false,"given":"Lu\u00eds","family":"P\u00e1dua","sequence":"first","affiliation":[{"name":"Centre for the Research and Technology of Agro-Environmental and Biological Sciences, University of Tr\u00e1s-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal"},{"name":"Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production, University of Tr\u00e1s-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7537-6606","authenticated-orcid":false,"given":"Lia","family":"Duarte","sequence":"additional","affiliation":[{"name":"Institute of Earth Sciences, FCUP Pole, Rua do Campo Alegre, 4169-007 Porto, Portugal"},{"name":"Department of Geosciences, Environment and Spatial Planning, FCUP, 4169-007 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4966-2227","authenticated-orcid":false,"given":"Ana M.","family":"Ant\u00e3o-Geraldes","sequence":"additional","affiliation":[{"name":"Centro de Investiga\u00e7\u00e3o de Montanha (CIMO), Instituto Polit\u00e9cnico de Bragan\u00e7a Campus de Santa Apol\u00f3nia, 5300-253 Bragan\u00e7a, Portugal"},{"name":"Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, Campus de Santa Apol\u00f3nia, 5300-253 Bragan\u00e7a, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4533-930X","authenticated-orcid":false,"given":"Joaquim J.","family":"Sousa","sequence":"additional","affiliation":[{"name":"Engineering Department, School of Science and Technology, University of Tr\u00e1s-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal"},{"name":"Centre for Robotics in Industry and Intelligent Systems (CRIIS), INESC Technology and Science (INESC-TEC), 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0647-8892","authenticated-orcid":false,"given":"Jo\u00e3o Paulo","family":"Castro","sequence":"additional","affiliation":[{"name":"Centro de Investiga\u00e7\u00e3o de Montanha (CIMO), Instituto Polit\u00e9cnico de Bragan\u00e7a Campus de Santa Apol\u00f3nia, 5300-253 Bragan\u00e7a, Portugal"},{"name":"Laborat\u00f3rio Associado para a Sustentabilidade e Tecnologia em Regi\u00f5es de Montanha (SusTEC), Instituto Polit\u00e9cnico de Bragan\u00e7a, Campus de Santa Apol\u00f3nia, 5300-253 Bragan\u00e7a, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,10]]},"reference":[{"key":"ref_1","unstructured":"Lowe, S., Browne, M., Boudjelas, S., and De Poorter, M. 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