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Comparative analysis of water hyacinth dynamics in North Bolgoda Lake, Sri Lanka: a classification based on high-resolution aerial imagery and satellite-imagery

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dc.contributor.author Dawalagala, HS
dc.contributor.author Radampola, A
dc.contributor.author Gowsigan, PT
dc.contributor.author Chaminda, SP
dc.contributor.author Dassanayake, SM
dc.contributor.author Jayawardena, CL
dc.date.accessioned 2023-12-18T09:12:22Z
dc.date.available 2023-12-18T09:12:22Z
dc.date.issued 2023-08-28
dc.identifier.citation Dawalagala, H.S., Radampola, A., Gowsigan, P.T., Chaminda, S.P., Dassanayake, S.M., & Jayawardena, C.L. (2023). Comparative analysis of water hyacinth dynamics in North Bolgoda Lake, Sri Lanka: a classification based on high-resolution aerial imagery and satellite-imagery. In C.L. Jayawardena (Ed.), International Symposium on Earth Resources Management & Environment – ISERME 2023: Proceedings of the 7th international Symposium on Earth Resources Management & Environment (pp.78). Department of Earth Resources Engineering, University of Moratuwa. https://doi.org/10.31705/ISERME.2023.16
dc.identifier.uri http://dl.lib.uom.lk/handle/123/21960
dc.description.abstract Water hyacinth (WH) is an invasive aquatic plant that has established its presence in tropical and subtropical regions around the globe. Its widespread existence has resulted in societal, economic, and ecological impacts that are mostly intolerable. Understanding and monitoring the spatial and seasonal dynamics of WH in the respective environments could provide insights to mitigate its environmental impact. This study attempts to identify seasonal patterns of WH within north Bolgoda Lake over four years (2019-2022). The methodology includes a pixel-based random forest (RF) classification utilising five distinct spectral indices in conjunction with raw Sentinel-2 spectral bands, operationalised through the Google Earth Engine (GEE) platform. The aerial imageries were classified using Esri ArcGIS Pro software. The outcomes of this study indicate an increase of WH proliferation during the wet season (May-November) over the dry season (December- April) with an overall accuracy of 82% for aerial imagery and 98% for satellite imagery. Data fusion techniques are proposed to overcome the limitations of employing two different forms of remote sensing data individually. Despite the challenges, this study reveals important insights into the scalability of input data to specific requirements and under restricted conditions. en_US
dc.language.iso en en_US
dc.publisher Department of Earth Resources Engineering en_US
dc.subject Image analysis en_US
dc.subject Invasive plants en_US
dc.subject Multi-spectral data en_US
dc.subject Random forest classification en_US
dc.title Comparative analysis of water hyacinth dynamics in North Bolgoda Lake, Sri Lanka: a classification based on high-resolution aerial imagery and satellite-imagery en_US
dc.type Conference-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.department Department of Earth Resources Engineering en_US
dc.identifier.year 2023 en_US
dc.identifier.conference International Symposium on Earth Resources Management & Environment - ISERME 2023 en_US
dc.identifier.place Colombo en_US
dc.identifier.pgnos pp. 78 en_US
dc.identifier.proceeding Proceedings of the 7th International Symposium on Earth Resources Management & Environment en_US
dc.identifier.email chulanthaj@uom.lk en_US
dc.identifier.doi https://doi.org/10.31705/ISERME.2023.16 en_US


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