Combining Remote Sensing and a Geographic Information System to Map and Assess the Accessibility of Invasive Alien Species Forest Stands: Case of <i<Acacia mearnsii</i< on Reunion Island

<i<Acacia mearnsii</i<, an invasive alien species, is the main resource identified for the energy transition initiated on Reunion Island. It is, therefore, critical to identify the existent forest stands within the island’s large tropical forest area and to determine which of these stand...
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Autor*in:	Hélène Bley Dalouman [verfasserIn] François Broust [verfasserIn] Annelise Tran [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	invasive alien species remote sensing object-based classification confusion index GIS

Übergeordnetes Werk:	In: Forests - MDPI AG, 2010, 14(2023), 2030, p 2030
Übergeordnetes Werk:	volume:14 ; year:2023 ; number:2030, p 2030

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/f14102030

Katalog-ID:	DOAJ093140053

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callnumber-first	Q - Science
author	Hélène Bley Dalouman
spellingShingle	Hélène Bley Dalouman misc QK900-989 misc <i<Acacia mearnsii</i< misc invasive alien species misc remote sensing misc object-based classification misc confusion index misc GIS misc Plant ecology Combining Remote Sensing and a Geographic Information System to Map and Assess the Accessibility of Invasive Alien Species Forest Stands: Case of <i<Acacia mearnsii</i< on Reunion Island
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topic_title	QK900-989 Combining Remote Sensing and a Geographic Information System to Map and Assess the Accessibility of Invasive Alien Species Forest Stands: Case of <i<Acacia mearnsii</i< on Reunion Island <i<Acacia mearnsii</i< invasive alien species remote sensing object-based classification confusion index GIS
topic	misc QK900-989 misc <i<Acacia mearnsii</i< misc invasive alien species misc remote sensing misc object-based classification misc confusion index misc GIS misc Plant ecology
topic_unstemmed	misc QK900-989 misc <i<Acacia mearnsii</i< misc invasive alien species misc remote sensing misc object-based classification misc confusion index misc GIS misc Plant ecology
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title	Combining Remote Sensing and a Geographic Information System to Map and Assess the Accessibility of Invasive Alien Species Forest Stands: Case of <i<Acacia mearnsii</i< on Reunion Island
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title_full	Combining Remote Sensing and a Geographic Information System to Map and Assess the Accessibility of Invasive Alien Species Forest Stands: Case of <i<Acacia mearnsii</i< on Reunion Island
author_sort	Hélène Bley Dalouman
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author_browse	Hélène Bley Dalouman François Broust Annelise Tran
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author-letter	Hélène Bley Dalouman
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title_sort	combining remote sensing and a geographic information system to map and assess the accessibility of invasive alien species forest stands: case of <i<acacia mearnsii</i< on reunion island
callnumber	QK900-989
title_auth	Combining Remote Sensing and a Geographic Information System to Map and Assess the Accessibility of Invasive Alien Species Forest Stands: Case of <i<Acacia mearnsii</i< on Reunion Island
abstract	<i<Acacia mearnsii</i<, an invasive alien species, is the main resource identified for the energy transition initiated on Reunion Island. It is, therefore, critical to identify the existent forest stands within the island’s large tropical forest area and to determine which of these stands are accessible for logging operations. In this study, a very high-spatial-resolution image was used to map forest (<i<Acacia mearnsii</i<, <i<Acacia heterophylla</i<, <i<Cryptomeria japonica</i<) and non-forest land cover. To identify the accessible forest stands, we developed a geographic information system (GIS) processing chain, accounting for barriers, the distribution of slopes, and the location of forest roads. User-defined parameters, such as the slope threshold and maximal distance to forest roads, allow different scenarios to be explored. The classification yields an overall accuracy of 88% and a Kappa index of 0.86 and highlights the areas occupied by the different types of Acacia. By applying the GIS processing chain for a standard scenario, the results show that only 19% of the initial study area of 637 ha of <i<Acacia mearnsii</i< patches is suitable for exploitation. In conclusion, our results demonstrate how remote sensing (RS) and GIS can be combined to provide valuable tools for forest managers to design management plans for invasive alien forest species.
abstractGer	<i<Acacia mearnsii</i<, an invasive alien species, is the main resource identified for the energy transition initiated on Reunion Island. It is, therefore, critical to identify the existent forest stands within the island’s large tropical forest area and to determine which of these stands are accessible for logging operations. In this study, a very high-spatial-resolution image was used to map forest (<i<Acacia mearnsii</i<, <i<Acacia heterophylla</i<, <i<Cryptomeria japonica</i<) and non-forest land cover. To identify the accessible forest stands, we developed a geographic information system (GIS) processing chain, accounting for barriers, the distribution of slopes, and the location of forest roads. User-defined parameters, such as the slope threshold and maximal distance to forest roads, allow different scenarios to be explored. The classification yields an overall accuracy of 88% and a Kappa index of 0.86 and highlights the areas occupied by the different types of Acacia. By applying the GIS processing chain for a standard scenario, the results show that only 19% of the initial study area of 637 ha of <i<Acacia mearnsii</i< patches is suitable for exploitation. In conclusion, our results demonstrate how remote sensing (RS) and GIS can be combined to provide valuable tools for forest managers to design management plans for invasive alien forest species.
abstract_unstemmed	<i<Acacia mearnsii</i<, an invasive alien species, is the main resource identified for the energy transition initiated on Reunion Island. It is, therefore, critical to identify the existent forest stands within the island’s large tropical forest area and to determine which of these stands are accessible for logging operations. In this study, a very high-spatial-resolution image was used to map forest (<i<Acacia mearnsii</i<, <i<Acacia heterophylla</i<, <i<Cryptomeria japonica</i<) and non-forest land cover. To identify the accessible forest stands, we developed a geographic information system (GIS) processing chain, accounting for barriers, the distribution of slopes, and the location of forest roads. User-defined parameters, such as the slope threshold and maximal distance to forest roads, allow different scenarios to be explored. The classification yields an overall accuracy of 88% and a Kappa index of 0.86 and highlights the areas occupied by the different types of Acacia. By applying the GIS processing chain for a standard scenario, the results show that only 19% of the initial study area of 637 ha of <i<Acacia mearnsii</i< patches is suitable for exploitation. In conclusion, our results demonstrate how remote sensing (RS) and GIS can be combined to provide valuable tools for forest managers to design management plans for invasive alien forest species.
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container_issue	2030, p 2030
title_short	Combining Remote Sensing and a Geographic Information System to Map and Assess the Accessibility of Invasive Alien Species Forest Stands: Case of <i<Acacia mearnsii</i< on Reunion Island
url	https://doi.org/10.3390/f14102030 https://doaj.org/article/ca2d468b68af430cbb692362bd6813ea https://www.mdpi.com/1999-4907/14/10/2030 https://doaj.org/toc/1999-4907
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up_date	2024-07-03T15:30:59.913Z
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Combining Remote Sensing and a Geographic Information System to Map and Assess the Accessibility of Invasive Alien Species Forest Stands: Case of <i<Acacia mearnsii</i< on Reunion Island

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