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dc.contributor.authorSimpson, Morgan Daviden_UK
dc.contributor.authorAkbari, Vahiden_UK
dc.contributor.authorMarino, Armandoen_UK
dc.contributor.authorPrabhu, G Nagendraen_UK
dc.contributor.authorBhowmik, Deepayanen_UK
dc.contributor.authorRupavatharam, Srikanthen_UK
dc.contributor.authorDatta, Avirajen_UK
dc.contributor.authorKleczkowski, Adamen_UK
dc.contributor.authorSujeetha, J Alice R Pen_UK
dc.contributor.authorGunjotikar Anantrao, Girishen_UK
dc.contributor.authorKampurath Poduvattil, Vidhuen_UK
dc.contributor.authorKumar, Sauraven_UK
dc.contributor.authorMaharaj, Savitrien_UK
dc.contributor.authorHunter, Peter Den_UK
dc.description.abstractWater hyacinth (Pontederia crassipes, also known as Eichhornia crassipes) is a highly invasive aquatic macrophyte species, indigenous to Amazonia, Brazil and tropical South America. It was introduced to India in 1896 and has now become an environmental and social challenge throughout the country in community ponds, freshwater lakes, irrigation channels, rivers and most other surface waterbodies. Considering its large speed of propagation on the water surface under conducive conditions and the adverse impact the infesting weed has, constant monitoring is needed to aid civic bodies, governments and policy makers involved in remedial measures. The synoptic coverage provided by satellite imaging and other remote sensing practices make it convenient to find a solution using this type of data. While there is an established background for the practice of remote sensing in the detection of aquatic plants, the use of Synthetic Aperture Radar (SAR) has yet to be fully exploited in the detection of water hyacinth. This research focusses on detecting water hyacinth within Vembanad Lake, Kuttanad, India. Here, results show that the monitoring of water hyacinth has proven to be possible using Sentinel-1 SAR data. A quantitative analysis of detection performance is presented using traditional and state-of-the-art change detectors. Analysis of these more powerful detectors showed true positive detection ratings of ~95% with 0.1% false alarm, showing significantly greater positive detection ratings when compared to the more traditional detectors. We are therefore confident that water hyacinth can be monitored using SAR data provided the extent of the infestation is significantly larger than the resolution cell (bigger than a quarter of a hectare).en_UK
dc.relationSimpson MD, Akbari V, Marino A, Prabhu GN, Bhowmik D, Rupavatharam S, Datta A, Kleczkowski A, Sujeetha JARP, Gunjotikar Anantrao G, Kampurath Poduvattil V, Kumar S, Maharaj S & Hunter PD (2022) Detecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imagery. Remote Sensing, 14 (12), Art. No.: 2845.
dc.rights© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
dc.subjectwater hyacinthen_UK
dc.subjectchange detectionen_UK
dc.titleDetecting Water Hyacinth Infestation in Kuttanad, India, Using Dual-Pol Sentinel-1 SAR Imageryen_UK
dc.typeJournal Articleen_UK
dc.citation.jtitleRemote Sensingen_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderEuropean Space Agencyen_UK
dc.contributor.funderRoyal Academy of Engineeringen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationUniversity of Keralaen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationInternational Crops Research Institute for the Semi-Arid Tropicsen_UK
dc.contributor.affiliationInternational Crops Research Institute for the Semi-Arid Tropicsen_UK
dc.contributor.affiliationUniversity of Strathclydeen_UK
dc.contributor.affiliationNational Institute of Plant Health Management (India)en_UK
dc.contributor.affiliationNational Institute of Plant Health Management (India)en_UK
dc.contributor.affiliationNational Institute of Plant Health Management (India)en_UK
dc.contributor.affiliationCSIR Water Research Instituteen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.relation.funderprojectMultimodal data analysis for monitoring invasive aquatic weeds in Indiaen_UK
rioxxterms.typeJournal Article/Reviewen_UK
local.rioxx.authorSimpson, Morgan David|0000-0003-3004-4517en_UK
local.rioxx.authorAkbari, Vahid|0000-0002-9621-8180en_UK
local.rioxx.authorMarino, Armando|0000-0002-4531-3102en_UK
local.rioxx.authorPrabhu, G Nagendra|en_UK
local.rioxx.authorBhowmik, Deepayan|0000-0003-1762-1578en_UK
local.rioxx.authorRupavatharam, Srikanth|en_UK
local.rioxx.authorDatta, Aviraj|en_UK
local.rioxx.authorKleczkowski, Adam|en_UK
local.rioxx.authorSujeetha, J Alice R P|en_UK
local.rioxx.authorGunjotikar Anantrao, Girish|en_UK
local.rioxx.authorKampurath Poduvattil, Vidhu|en_UK
local.rioxx.authorKumar, Saurav|en_UK
local.rioxx.authorMaharaj, Savitri|0000-0002-0674-6044en_UK
local.rioxx.authorHunter, Peter D|0000-0001-7269-795Xen_UK
local.rioxx.projectFF\1920\1\37|Royal Academy of Engineering|
Appears in Collections:Biological and Environmental Sciences Journal Articles

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