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...
Ausführliche Beschreibung
Autor*in: |
Hélène Bley Dalouman [verfasserIn] François Broust [verfasserIn] Annelise Tran [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2023 |
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Übergeordnetes Werk: |
In: Forests - MDPI AG, 2010, 14(2023), 2030, p 2030 |
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Übergeordnetes Werk: |
volume:14 ; year:2023 ; number:2030, p 2030 |
Links: |
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DOI / URN: |
10.3390/f14102030 |
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Katalog-ID: |
DOAJ093140053 |
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10.3390/f14102030 doi (DE-627)DOAJ093140053 (DE-599)DOAJca2d468b68af430cbb692362bd6813ea DE-627 ger DE-627 rakwb eng QK900-989 Hélène Bley Dalouman verfasserin aut 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 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <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. <i<Acacia mearnsii</i< invasive alien species remote sensing object-based classification confusion index GIS Plant ecology François Broust verfasserin aut Annelise Tran verfasserin aut In Forests MDPI AG, 2010 14(2023), 2030, p 2030 (DE-627)614095689 (DE-600)2527081-3 19994907 nnns volume:14 year:2023 number:2030, p 2030 https://doi.org/10.3390/f14102030 kostenfrei https://doaj.org/article/ca2d468b68af430cbb692362bd6813ea kostenfrei https://www.mdpi.com/1999-4907/14/10/2030 kostenfrei https://doaj.org/toc/1999-4907 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 2030, p 2030 |
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10.3390/f14102030 doi (DE-627)DOAJ093140053 (DE-599)DOAJca2d468b68af430cbb692362bd6813ea DE-627 ger DE-627 rakwb eng QK900-989 Hélène Bley Dalouman verfasserin aut 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 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <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. <i<Acacia mearnsii</i< invasive alien species remote sensing object-based classification confusion index GIS Plant ecology François Broust verfasserin aut Annelise Tran verfasserin aut In Forests MDPI AG, 2010 14(2023), 2030, p 2030 (DE-627)614095689 (DE-600)2527081-3 19994907 nnns volume:14 year:2023 number:2030, p 2030 https://doi.org/10.3390/f14102030 kostenfrei https://doaj.org/article/ca2d468b68af430cbb692362bd6813ea kostenfrei https://www.mdpi.com/1999-4907/14/10/2030 kostenfrei https://doaj.org/toc/1999-4907 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 2030, p 2030 |
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10.3390/f14102030 doi (DE-627)DOAJ093140053 (DE-599)DOAJca2d468b68af430cbb692362bd6813ea DE-627 ger DE-627 rakwb eng QK900-989 Hélène Bley Dalouman verfasserin aut 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 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <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. <i<Acacia mearnsii</i< invasive alien species remote sensing object-based classification confusion index GIS Plant ecology François Broust verfasserin aut Annelise Tran verfasserin aut In Forests MDPI AG, 2010 14(2023), 2030, p 2030 (DE-627)614095689 (DE-600)2527081-3 19994907 nnns volume:14 year:2023 number:2030, p 2030 https://doi.org/10.3390/f14102030 kostenfrei https://doaj.org/article/ca2d468b68af430cbb692362bd6813ea kostenfrei https://www.mdpi.com/1999-4907/14/10/2030 kostenfrei https://doaj.org/toc/1999-4907 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 2030, p 2030 |
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10.3390/f14102030 doi (DE-627)DOAJ093140053 (DE-599)DOAJca2d468b68af430cbb692362bd6813ea DE-627 ger DE-627 rakwb eng QK900-989 Hélène Bley Dalouman verfasserin aut 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 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <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. <i<Acacia mearnsii</i< invasive alien species remote sensing object-based classification confusion index GIS Plant ecology François Broust verfasserin aut Annelise Tran verfasserin aut In Forests MDPI AG, 2010 14(2023), 2030, p 2030 (DE-627)614095689 (DE-600)2527081-3 19994907 nnns volume:14 year:2023 number:2030, p 2030 https://doi.org/10.3390/f14102030 kostenfrei https://doaj.org/article/ca2d468b68af430cbb692362bd6813ea kostenfrei https://www.mdpi.com/1999-4907/14/10/2030 kostenfrei https://doaj.org/toc/1999-4907 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 2030, p 2030 |
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10.3390/f14102030 doi (DE-627)DOAJ093140053 (DE-599)DOAJca2d468b68af430cbb692362bd6813ea DE-627 ger DE-627 rakwb eng QK900-989 Hélène Bley Dalouman verfasserin aut 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 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <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. <i<Acacia mearnsii</i< invasive alien species remote sensing object-based classification confusion index GIS Plant ecology François Broust verfasserin aut Annelise Tran verfasserin aut In Forests MDPI AG, 2010 14(2023), 2030, p 2030 (DE-627)614095689 (DE-600)2527081-3 19994907 nnns volume:14 year:2023 number:2030, p 2030 https://doi.org/10.3390/f14102030 kostenfrei https://doaj.org/article/ca2d468b68af430cbb692362bd6813ea kostenfrei https://www.mdpi.com/1999-4907/14/10/2030 kostenfrei https://doaj.org/toc/1999-4907 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 14 2023 2030, p 2030 |
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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 |
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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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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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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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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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