Research on the habitats protected by the European Union's Habitats Directive (HD) has increased rapidly since its adoption in 1992. However, the methods and tools used to assess their conservation ...status are varied. In this context, we reviewed and summarized the scientific literature related to the coastal Natura 2000 habitats to list and sort parameters used to assess and map their conservation status. We found 225 papers that specifically focused on the assessment of conservation status of coastal habitats. An analysis of the papers was conducted based on the four parameters (“Range”, “Area”, “structure and functions”, “Future prospects”) specified in the guidelines. Results highlight knowledge gaps regarding the availability of data and methods that measure the “Range”, “Area”, “Structure and functions” and “Future prospects”. Most of the papers focused on coastal dunes and were located in the Mediterranean biogeographic region. Therefore, the process of assessing the conservation status of coastal habitats remains complicated to implement because methodological approaches are mainly dominated by expert statements. Moreover, all the procedures of the HD are carried out within each member country and the final assessments are often the synthesis of these partial assessments. However, the multiscalar approach and the use of innovative technologies (databases, remote sensing) can be particularly relevant to develop replicable approaches and facilitate monitoring and the implementation of management measures.
•The implementation of HD remains complicated today to assess and monitor the conservation status.•Methodological disparities exist between coastal habitats, between countries and between biogeographic regions.•Currently, methodological approaches remain mainly based on expert judgements.•Recent and innovative methods for automatic and objective modelling can help to assess habitat range and area.•Concerted and multiscalar approaches can help to improve knowledge on structure, functions and future prospects.
Mapping natural habitats remains challenging, especially at a national scale. Although new open‐access variables for vegetation and its environment and increased spatial resolution derived from ...satellite remote sensing data are available at the global scale, the relevance of these new variables for fine‐grained mapping of natural habitats at a national scale remains underexplored. This study aimed to map the fine‐grained pattern of four heathland habitats throughout France (550 000 km2). Environmental (bioclimatic, soil and topographic) and spectral (vegetation) variables derived from MODerate resolution Imaging Spectroradiometer, Advanced Spaceborne Thermal Emission and Reflection Radiometer, and Sentinel‐2 satellite data were analyzed using the MaxEnt classifier. Open‐access field databases were used to calibrate and validate the classification, based on the threshold‐independent area under the curve (AUC) index and the conventional F1‐score. For each heathland habitat, potential and actual areas were mapped using environmental and spectral variables, respectively. The results showed high classification accuracy for potential (AUC 0.92–0.99) and actual (AUC 0.88–0.99) suitability maps of the four heathland habitats. Visual interpretation of maps of the probability of occurrence indicated that the fine‐grained distribution of heathland habitat was detected satisfactorily. However, although the accuracy of the crisp map of combined classifications of actual heathland habitats was high (overall accuracy 0.72), estimated producer's accuracies in terms of proportion of area were low (<0.25). This study provides the first fine‐grained pattern maps of heathland habitats at a national scale, thus highlighting the value of combining environmental and spectral variables derived from open‐remote sensing data and open‐source field databases. These suitability maps could support the identification of heathland habitats in the framework of national conservation policies.
Mapping natural habitats remains challenging, especially at the national scale. Here, we mapped the fine‐grained pattern of four heathland habitats throughout France (550 000 km2) using open‐source remote sensing data, including Sentinel‐2 time series. This study provides the first fine‐grained map of heathland habitats at a national scale, highlighting the value of combining environmental and vegetation variables. This map will support the monitoring and evaluation of the conservation status of natural habitats.
Mapping plant communities, which is essential to assess the conservation status of natural habitats, is currently based mainly on time-consuming field surveys without the use of satellite data. ...However, free image time-series with high spatial and temporal resolution have been available since 2015. This study assessed the contribution of Sentinel-2 time-series images to mapping the spatial distribution of 18 plant communities within a Natura 2000 site (1978 ha) located on the Mediterranean biogeographical region (Corsica, France). The method was based on random forest modeling of six Sentinel-2 images acquired from 26 February to 24 October 2017, which were calibrated and validated using a field vegetation map. The results showed that the 18 plant communities were modeled correctly, with 72% overall accuracy. The uncertainty map associated with the model indicated areas that required additional field observations.
Decadal time-series derived from satellite observations are useful for discriminating crops and identifying crop succession at national and regional scales. However, use of these data for crop ...modeling is challenged by the presence of mixed pixels due to the coarse spatial resolution of these data, which influences model accuracy, and the scarcity of field data over the decadal period necessary to calibrate and validate the model. For this data article, cloud-free satellite “Vegetation Indices 16-Day Global 250 m” Terra (MOD13Q1) and Aqua (MYD13Q1) products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), as well as the Land Parcel Information System (LPIS) vector field data, were collected throughout France for the 12-year period from 2006 to the end of 2017. A GIS workflow was developed using R software to combine the MOD13Q1 and MYD13Q1 products, and then to select “pure” MODIS pixels located within single-crop parcels over the entire period. As a result, a dataset for 21,129 reference plots (corresponding to “pure” pixels) was generated that contained a spectral time-series (red band, near-infrared band, Normalized Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI)) and the associated annual crop type with an 8-day time step over the period. This dataset can be used to develop new classification methods based on time-series analysis using deep learning, and to monitor and predict crop succession.
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.
Semi-natural grasslands are perennial ecosystems and an important part of agricultural landscapes that are threatened by urbanization and agricultural intensification. However, implementing national ...grassland conservation policies remains challenging because their inventory, based on short-term observation, rarely discriminate semi-natural permanent from temporary grasslands. This study aims to map grassland frequency at a national scale over a long period using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m satellite time-series. A three-step method was applied to the entire area of metropolitan France (543,940 km²). First, land-use and land-cover maps—including grasslands—were produced for each year from 2006–2017 using the random forest classification of MOD13Q1 and MYD13Q1 products, which were calibrated and validated using field observations. Second, grassland frequency from 2006–2017 was calculated by combining the 12 annual maps. Third, sub-pixel analysis was performed using a reference layer with 20 m spatial resolution to quantify percentages of land-use and land-cover classes within MODIS pixels classified as grassland. Results indicate that grasslands were accurately modeled from 2006–2017 (F1-score 0.89–0.93). Nonetheless, modeling accuracy varied among biogeographical regions, with F1-score values that were very high for Continental (0.94 ± 0.01) and Atlantic (0.90 ± 0.02) regions, high for Alpine regions (0.86 ± 0.04) but moderate for Mediterranean regions (0.62 ± 0.10). The grassland frequency map for 2006–2017 at 250 m spatial resolution provides an unprecedented view of stable grassland patterns in agricultural areas compared to existing national and European GIS layers. Sub-pixel analysis showed that areas modeled as grasslands corresponded to grassland-dominant areas (60%–94%). This unique long-term and national monitoring of grasslands generates new opportunities for semi-natural grassland inventorying and agro-ecological management.
While fine-scale maps of vegetation alliances are required for conservation, their distribution is usually known at broad scales. Open-access field and spatial data are increasingly available ...worldwide, but their contribution to modelling vegetation alliances remains to be assessed. This study aimed to map the suitability area of six heath alliances distributed along ecological gradients throughout France. We used 20 broad and local variables derived from WorldClim, the European Union DEM, SoilGrids, and the Global Wind and Solar Atlases that describe bioclimatic and environmental conditions. For each alliance, two nested MaxEnt models were calibrated and validated using archive field data: one at a broad scale (1000 × 1000 m) to define its bioclimatic area, and the second at a local scale (25 × 25 m) to predict its environmental area. The results showed complementarity of the variables used to discriminate the alliances, and the accuracy of spatial modelling at broad (AUC = 0.83-0.99) and local scales (AUC = 0.91-0.99). They also highlighted the gradients of continentality and temperature that differentiate the alliances. These new maps provide additional knowledge about alliance distribution areas and could support natural vegetation conservation at a national scale.
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