{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T15:01:22Z","timestamp":1779116482313,"version":"3.51.4"},"reference-count":74,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2020,12,9]],"date-time":"2020-12-09T00:00:00Z","timestamp":1607472000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fitzpatrick Institute of African Ornithology, DST\u2010NRF Centre of Excellence, University of Cape Town, Rondebosch, South Africa.","award":["TTK180413320613"],"award-info":[{"award-number":["TTK180413320613"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Diverse freshwater biological communities are threatened by invasive aquatic alien plant (IAAP) invasions and consequently, cost countries millions to manage. The effective management of these IAAP invasions necessitates their frequent and reliable monitoring across a broad extent and over a long-term. Here, we introduce and apply a monitoring approach that meet these criteria and is based on a three-stage hierarchical classification to firstly detect water, then aquatic vegetation and finally water hyacinth (Pontederia crassipes, previously Eichhornia crassipes), the most damaging IAAP species within many regions of the world. Our approach circumvents many challenges that restricted previous satellite-based water hyacinth monitoring attempts to smaller study areas. The method is executable on Google Earth Engine (GEE) extemporaneously and utilizes free, medium resolution (10\u201330 m) multispectral Earth Observation (EO) data from either Landsat-8 or Sentinel-2. The automated workflow employs a novel simple thresholding approach to obtain reliable boundaries for open-water, which are then used to limit the area for aquatic vegetation detection. Subsequently, a random forest modelling approach is used to discriminate water hyacinth from other detected aquatic vegetation using the eight most important variables. This study represents the first national scale EO-derived water hyacinth distribution map. Based on our model, it is estimated that this pervasive IAAP covered 417.74 km2 across South Africa in 2013. Additionally, we show encouraging results for utilizing the automatically derived aquatic vegetation masks to fit and evaluate a convolutional neural network-based semantic segmentation model, removing the need for detection of surface water extents that may not always be available at the required spatio-temporal resolution or accuracy. The water hyacinth species discrimination has a 0.80, or greater, overall accuracy (0.93), F1-score (0.87) and Matthews correlation coefficient (0.80) based on 98 widely distributed field sites across South Africa. The results suggest that the introduced workflow is suitable for monitoring changes in the extent of open water, aquatic vegetation, and water hyacinth for individual waterbodies or across national extents. The GEE code can be accessed here.<\/jats:p>","DOI":"10.3390\/rs12244021","type":"journal-article","created":{"date-parts":[[2020,12,9]],"date-time":"2020-12-09T09:17:58Z","timestamp":1607505478000},"page":"4021","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":60,"title":["A Remote Sensing Method to Monitor Water, Aquatic Vegetation, and Invasive Water Hyacinth at National Extents"],"prefix":"10.3390","volume":"12","author":[{"given":"Geethen","family":"Singh","sequence":"first","affiliation":[{"name":"School of Animal, Plant &amp; Environmental Sciences, University of the Witwatersrand, Johannesburg 2000, South Africa"},{"name":"DST-NRF Centre of Excellence, Fitzpatrick Institute of African Ornithology, University of Cape Town, Rondebosch 7701, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2345-7017","authenticated-orcid":false,"given":"Chevonne","family":"Reynolds","sequence":"additional","affiliation":[{"name":"School of Animal, Plant &amp; Environmental Sciences, University of the Witwatersrand, Johannesburg 2000, South Africa"},{"name":"DST-NRF Centre of Excellence, Fitzpatrick Institute of African Ornithology, University of Cape Town, Rondebosch 7701, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5155-2599","authenticated-orcid":false,"given":"Marcus","family":"Byrne","sequence":"additional","affiliation":[{"name":"School of Animal, Plant &amp; Environmental Sciences, University of the Witwatersrand, Johannesburg 2000, South Africa"},{"name":"DST-NRF Centre of Excellence for Invasion Biology, School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Johannesburg 2000, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0284-4114","authenticated-orcid":false,"given":"Benjamin","family":"Rosman","sequence":"additional","affiliation":[{"name":"School of Computer Science &amp; Applied Mathematics, University of the Witwatersrand, Johannesburg 2000, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1899\/08-171.1","article-title":"Freshwater Biodiversity Conservation: Recent Progress and Future Challenges","volume":"29","author":"Strayer","year":"2010","journal-title":"J. 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