A 5 m dataset of digital terrain model derivatives across mainland France.

A dataset of three digital terrain model (DTM) derivatives was produced at 5 m spatial resolution across mainland France. This dataset includes (i) a topographic wetness index (TWI) that characterizes potential soil wetness as a function of the contributing area and local slope, (ii) a multi-scale topographic position color composite (MTPCC) that describes the position of a pixel relative to its neighborhood at three spatial scales, and (iii) a vertical distance to channel network index (VDCNI) that expresses the vertical height between the elevation of a pixel and the nearest channel. These three raster layers were derived from the French national airborne DTM at 5 m spatial resolution and the vector layer of the channel network of the national hydrological database.

Natural grasslands across mainland France: A dataset including a 10 m raster and ground reference points.

The data provided here include the first 10 m raster of natural grasslands across mainland France and related ground reference points. The latter consist of 1770 field observations that describe natural and artificial grasslands from respectively a compilation of hundreds of field-based vegetation maps and the European Union Land Parcel Identification System (LPIS). Based on analysis of aerial images, ground reference points were manually extracted from grassland polygons of the field-based vegetation maps and the LPIS within herbaceous areas larger than 30 × 30 m.

National wetland mapping using remote-sensing-derived environmental variables, archive field data, and artificial intelligence.

While wetland ecosystem services are widely recognized, the lack of fine-scale national inventories prevents successful implementation of conservation policies. Wetlands are difficult to map due to their complex fine-grained spatial pattern and fuzzy boundaries. However, the increasing amount of open high-spatial-resolution remote sensing data and accurately georeferenced field data archives, as well as progress in artificial intelligence (AI), provide opportunities for fine-scale national wetland mapping.

Field dataset of punctual observations of soil properties and vegetation types distributed along soil moisture gradients in France.

The interface between wetlands and uplands is characterized by gradients in hydrological, soil and biological components. Consequently, the exact spatial distribution of this transitional area is not well known because it often occurs as a fuzzy moisture gradient. However, ecological assessment and conservation require mapping and characterizing this interface to better understand and model biotic and abiotic interactions between wetlands and uplands.

Bioclimatic dataset of Metropolitan France under current conditions derived from the WorldClim model.

Several studies have shown that adequate bioclimatic information is of major importance for mapping ecological niches or for modelling the distribution ranges of species and communities, particularly from a climate change perspective [1,2]. However, in France, there are few data sources that provide consistent information, available data being produced at low spatial resolution and based on classification systems that are not suitable for mapping French ecological systems. This paper presents bioclimatic maps produced on Metropolitan France and based on the Worldwide Bioclimatic Classification System, which are called Global Bioclimatics [3].

Time-series spectral dataset for croplands in France (2006-2017).

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.

Mapping wetland functions using Earth observation data and multi-criteria analysis.

Wetland functional assessment is commonly conducted based on field observations, and thus, is generally limited to small areas. However, there is often a need for wetland managers to obtain information on wetland functional performance over larger areas. For this purpose, we are proposing a new field-based functional assessment procedure in which wetland functions are evaluated and classified into hydrogeomorphic units according to a multi-criteria analysis approach.

Identification and mapping of natural vegetation on a coastal site using a Worldview-2 satellite image.

Identification and mapping of natural vegetation are major issues for biodiversity management and conservation. Remotely sensed data with very high spatial resolution are currently used to study vegetation, but most satellite sensors are limited to four spectral bands, which is insufficient to identify some natural vegetation formations. The study objectives are to discriminate natural vegetation and identify natural vegetation formations using a Worldview-2 satellite image.