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Mapping the functional dimension of vegetation series in the Mediterranean region using multitemporal MODIS data
Authors:Sébastien Rapinel  Clémence Rozo  Pauline Delbosc  Damien Arvor  Alban Thomas  Jan-Bernard Bouzillé
Institution:1. Université de Rennes, LETG, UMR 6554 CNRS, Rennes, Francesebastienrapinel@gmail.comORCID Iconhttps://orcid.org/0000-0002-4250-5360;3. Université de Rennes, LETG, UMR 6554 CNRS, Rennes, France;4. EA 7462 Géoarchitecture, Université de Bretagne Occidentale UFR Sciences et Techniques, Institut de Géoarchitecture, Brest, France;5. Université de Rennes, LETG, UMR 6554 CNRS, Rennes, FranceORCID Iconhttps://orcid.org/0000-0002-3017-9625;6. , Université de Rennes, ECOBIO UMR 6553 CNRS, Rennes, France
Abstract:ABSTRACT

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.
Keywords:Corsica  sigmetum  Habitats Directive  random forest  ecosystem functioning
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