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Multitemporal Remote Sensing Based on an FVC Reference Period Using Sentinel-2 for Monitoring Eichhornia crassipes on a Mediterranean River

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Agrocampus Ouest, UMR Sol Agronomie Spatialisation (UMR SAS), P.O. Box 35042 Rennes, France
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Agrocampus Ouest, UMR Ecology and Ecosystem Health (UMR ESE), P.O. Box 35042 Rennes, France
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National Center for Remote Sensing, National Council for Scientific Research, P.O. Box 11- 8281, Riad El Solh, 1107 2260 Beirut, Lebanon
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Lebanese University, Faculty of Sciences (I), Rafic Hariri campus, P.O. Box 14-6573, Beirut, Lebanon
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Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(16), 1856; https://doi.org/10.3390/rs11161856
Received: 11 July 2019 / Revised: 5 August 2019 / Accepted: 6 August 2019 / Published: 9 August 2019
(This article belongs to the Special Issue Ecosystem Services with Remote Sensing)
Invasive aquatic plants are a serious global ecological and socio-economic problem because they can cause local extinction of native species and alter navigation and fishing. Eichhornia crassipes (water hyacinth) is a dangerous invasive floating plant that is widely distributed throughout the world. In Lebanon, it has spread since 2006 in the Al Kabir River. Remote sensing techniques have been widely developed to detect and monitor dynamics and extents of invasive plants such as water hyacinth over large areas. However, they become challenging to use in narrow areas such as the Al Kabir River and we developed a new image-analysis method to extract water hyacinth areas on the river. The method is based on a time series of a biophysical variable obtained from Sentinel-2 images. After defining a reference period between two growing cycles, we used the fractional vegetation cover (FVC) to estimate the water hyacinth surface area in the river. This method makes it possible to monitor water hyacinth development and estimate the total area it colonizes in the river corridor. This method can help ecologists and other stakeholders to map invasive plants in rivers and improve their control. View Full-Text
Keywords: Eichhornia crassipes; remote sensing; soil-adjusted vegetation index; FVC reference period; Sentinel-2; time series; Lebanon Eichhornia crassipes; remote sensing; soil-adjusted vegetation index; FVC reference period; Sentinel-2; time series; Lebanon
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Ghoussein, Y.; Nicolas, H.; Haury, J.; Fadel, A.; Pichelin, P.; Abou Hamdan, H.; Faour, G. Multitemporal Remote Sensing Based on an FVC Reference Period Using Sentinel-2 for Monitoring Eichhornia crassipes on a Mediterranean River. Remote Sens. 2019, 11, 1856.

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