Mapping the functional dimension of vegetation series in the Mediterranean region using multitemporal MODIS data
Monitoring the structural and functional dimensions of natural vegetation is a critical issue to ensure effective management of biodiversity. While coarse-resolution satellite image time-series have been used extensively to monitor vegetation physiognomies, their potential to describe plant species...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2020-01-01
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| Series: | GIScience & Remote Sensing |
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| Online Access: | http://dx.doi.org/10.1080/15481603.2019.1662167 |
| _version_ | 1827811802571866112 |
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| author | Sébastien Rapinel Clémence Rozo Pauline Delbosc Damien Arvor Alban Thomas Jan-Bernard Bouzillé Frédéric Bioret Laurence Hubert-Moy |
| author_facet | Sébastien Rapinel Clémence Rozo Pauline Delbosc Damien Arvor Alban Thomas Jan-Bernard Bouzillé Frédéric Bioret Laurence Hubert-Moy |
| author_sort | Sébastien Rapinel |
| collection | DOAJ |
| description | Monitoring the structural and functional dimensions of natural vegetation is a critical issue to ensure effective management of biodiversity. While coarse-resolution satellite image time-series have been used extensively to monitor vegetation physiognomies, their potential to describe plant species composition remains understudied. The objective of this study is to assess the potential of annual time-series of MODIS images to discriminate combinations of plant communities, called “vegetation series,” and characterize their structural and functional dimensions at the landscape scale. Twelve vegetation series were mapped in a 16 574 ha study area in a Mediterranean context located in Corsica (France). First, the structural dimension of vegetation series was examined using a random forest (RF) model calibrated with a reference field map to (i) measure the importance of each MODIS image in discriminating vegetation series; (ii) quantify the influence of the number of dates on model accuracy; and (iii) map the vegetation series with the optimal subset of MODIS images. Second, the functional dimension of vegetation series was analyzed by ordinating three functional indices through principal component analysis. These indices were the annual sum of normalized difference vegetation index (NDVI), the annual amplitude of NDVI, and the date of maximum NDVI, considered as a proxy for annual primary production, seasonality of carbon fluxes, and vegetation phenology, respectively. Results showed that (i) vegetation series were mapped accurately (median Kappa index 0.70, median overall accuracy 0.76), preferably using images acquired from February to August; (ii) at least 10 MODIS images were required to achieve sufficient accuracy; and (iii) a functional gradient was detected, ranging from high annual net primary production with low seasonality of carbon fluxes and early phenology in Mediterranean vegetation series to low annual net primary production with high seasonality of carbon fluxes and late phenology in alpine vegetation series. |
| first_indexed | 2024-03-11T23:09:47Z |
| format | Article |
| id | doaj.art-cc3a4da0afc349e9af332c51e8428918 |
| institution | Directory Open Access Journal |
| issn | 1548-1603 1943-7226 |
| language | English |
| last_indexed | 2024-03-11T23:09:47Z |
| publishDate | 2020-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | GIScience & Remote Sensing |
| spelling | doaj.art-cc3a4da0afc349e9af332c51e84289182023-09-21T12:34:15ZengTaylor & Francis GroupGIScience & Remote Sensing1548-16031943-72262020-01-01571607310.1080/15481603.2019.16621671662167Mapping the functional dimension of vegetation series in the Mediterranean region using multitemporal MODIS dataSébastien Rapinel0Clémence Rozo1Pauline Delbosc2Damien Arvor3Alban Thomas4Jan-Bernard Bouzillé5Frédéric Bioret6Laurence Hubert-Moy7Université de Rennes, LETG, UMR 6554 CNRSUniversité de Rennes, LETG, UMR 6554 CNRSUniversité de Bretagne Occidentale UFR Sciences et Techniques, Institut de GéoarchitectureUniversité de Rennes, LETG, UMR 6554 CNRSUniversité de Rennes, LETG, UMR 6554 CNRSUniversité de Rennes, ECOBIO UMR 6553 CNRSUniversité de Bretagne Occidentale UFR Sciences et Techniques, Institut de GéoarchitectureUniversité de Rennes, LETG, UMR 6554 CNRSMonitoring the structural and functional dimensions of natural vegetation is a critical issue to ensure effective management of biodiversity. While coarse-resolution satellite image time-series have been used extensively to monitor vegetation physiognomies, their potential to describe plant species composition remains understudied. The objective of this study is to assess the potential of annual time-series of MODIS images to discriminate combinations of plant communities, called “vegetation series,” and characterize their structural and functional dimensions at the landscape scale. Twelve vegetation series were mapped in a 16 574 ha study area in a Mediterranean context located in Corsica (France). First, the structural dimension of vegetation series was examined using a random forest (RF) model calibrated with a reference field map to (i) measure the importance of each MODIS image in discriminating vegetation series; (ii) quantify the influence of the number of dates on model accuracy; and (iii) map the vegetation series with the optimal subset of MODIS images. Second, the functional dimension of vegetation series was analyzed by ordinating three functional indices through principal component analysis. These indices were the annual sum of normalized difference vegetation index (NDVI), the annual amplitude of NDVI, and the date of maximum NDVI, considered as a proxy for annual primary production, seasonality of carbon fluxes, and vegetation phenology, respectively. Results showed that (i) vegetation series were mapped accurately (median Kappa index 0.70, median overall accuracy 0.76), preferably using images acquired from February to August; (ii) at least 10 MODIS images were required to achieve sufficient accuracy; and (iii) a functional gradient was detected, ranging from high annual net primary production with low seasonality of carbon fluxes and early phenology in Mediterranean vegetation series to low annual net primary production with high seasonality of carbon fluxes and late phenology in alpine vegetation series.http://dx.doi.org/10.1080/15481603.2019.1662167corsicasigmetumhabitats directiverandom forestecosystem functioning |
| spellingShingle | Sébastien Rapinel Clémence Rozo Pauline Delbosc Damien Arvor Alban Thomas Jan-Bernard Bouzillé Frédéric Bioret Laurence Hubert-Moy Mapping the functional dimension of vegetation series in the Mediterranean region using multitemporal MODIS data GIScience & Remote Sensing corsica sigmetum habitats directive random forest ecosystem functioning |
| title | Mapping the functional dimension of vegetation series in the Mediterranean region using multitemporal MODIS data |
| title_full | Mapping the functional dimension of vegetation series in the Mediterranean region using multitemporal MODIS data |
| title_fullStr | Mapping the functional dimension of vegetation series in the Mediterranean region using multitemporal MODIS data |
| title_full_unstemmed | Mapping the functional dimension of vegetation series in the Mediterranean region using multitemporal MODIS data |
| title_short | Mapping the functional dimension of vegetation series in the Mediterranean region using multitemporal MODIS data |
| title_sort | mapping the functional dimension of vegetation series in the mediterranean region using multitemporal modis data |
| topic | corsica sigmetum habitats directive random forest ecosystem functioning |
| url | http://dx.doi.org/10.1080/15481603.2019.1662167 |
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