Jean Nabucet

Detection and Characterization of Hedgerows Using TerraSAR-X Imagery

Whilst most hedgerow functions depend upon hedgerow structure and hedgerow network patterns, in many ecological studies information on the fragmentation of hedgerows network and canopy structure is often retrieved in the field in small areas using accurate ground surveys and estimated over landscapes in a semi-quantitative manner. This paper explores the use of radar SAR imagery to (i) detect hedgerow networks; and (ii) describe the hedgerow canopy heterogeneity using TerraSAR-X imagery. The extraction of hedgerow networks was achieved using an object-oriented method using two polarimetric parameters: the Single Bounce and the Shannon Entropy derived from one TerraSAR-X image. The hedgerow canopy heterogeneity estimated from field measurements was compared with two backscattering coefficients and three polarimetric parameters derived from the same image. The results show that the hedgerow network and its fragmentation can be identified with a very good accuracy (Kappa index: 0.92). This study also reveals the high correlation between one polarimetric parameter, the Shannon entropy, and the canopy fragmentation measured in the field. Therefore, VHSR radar images can both precisely detect the presence of wooded hedgerow networks and characterize their structure, which cannot be achieved with optical images.

Functional connectivity in replicated urban landscapes in the land snail (Cornu aspersum)

Urban areas are highly fragmented and thereby exert strong constraints on individual dispersal. Despite this, some species manage to persist in urban areas, such as the garden snail, Cornu aspersum, which is common in cityscapes despite its low mobility. Using landscape genetic approaches, we combined study area replication and multiscale analysis to determine how landscape composition, configuration and connectivity influence snail dispersal across urban areas. At the overall landscape scale, areas with a high percentage of roads decreased genetic differentiation between populations. At the population scale, genetic differentiation was positively linked with building surface, the proportion of borders where wooded patches and roads appeared side by side and the proportion of borders combining wooded patches and other impervious areas. Analyses based on pairwise genetic distances validated the isolation‐by‐distance and isolation‐by‐resistance models for this land snail, with an equal fit to least‐cost paths and circuit‐theory‐based models. Each of the 12 landscapes analysed separately yielded specific relations to environmental features, whereas analyses integrating all replicates highlighted general common effects. Our results suggest that urban transport infrastructures facilitate passive snail dispersal. At a local scale, corresponding to active dispersal, unfavourable habitats (wooded and impervious areas) isolate populations. This work upholds the use of replicated landscapes to increase the generalizability of landscape genetics results and shows how multiscale analyses provide insight into scale‐dependent processes.

Evaluation of bispectral LIDAR data for urban vegetation mapping

Because of the large increase of urban population in the last decades, the question of sustainable development in urban areas is crucial. In this context, vegetation plays a significant role in urban planning, environmental protecting, and sustainable development policy making, heating and cooling requirements of buildings, displacement of animals dispersion, concentration of pollutants, and well-being. In numerous cities, vegetation is limited to public areas using GPS surveys or aerial remote sensing data. Recently, very high-resolution sensors as Light Detection and Ranging (LiDAR) data have permitted significant improvements in vegetation mapping in urban areas. This paper presents an evaluation of a new generation of airborne LIDAR bi-spectral discrete point (Optech titan) for mapping and characterizing urban vegetation. The methodology is based on a four-step approach: 1) the analysis of the quality of data in order to estimate noise between the green and near-infrared LIDAR point clouds; 2) this enables to remove the topographic effects and 3) a first classification, devoted to the elimination of the non-vegetation class, is performed based on the intensity value of the two channels; finally, in 4), the tree coverage is classified into seven categories of strata combination. To this end specific descriptors related to the organization of the point clouds are used. These first results show that compared to monospectral LiDAR data, bi-spectral LiDAR enables to improve significantly both the extraction and the characterization of urban objects. This reveals new perspectives for mapping and characterizing urban patterns and other complex structures.

Green and blue belt networks: Mapping connectivity areas at a regional scale using medium and high spatial resolution satellite images

The distribution of ecosystem sites, their connectivity and their evolution are key links between ecology and society, as these landscape patterns determine the regional sustainability for biodiversity and are subject to human interventions. While little attention has been paid to procedures for mapping connectivity among numerous “natural” landscape elements over large areas, the principal objective of this study was to map ecological corridors at a regional scale using remotely sensed data. To achieve this goal, we developed an approach including three stages: first, permanent “natural” landscape elements were identified from Landsat TM images; second, permanent grassland connected to these elements was extracted from a multitemporal series of MODIS images and aggregated to them; third, connectivity was depicted by least-cost modeling. The regional connectivity map can be analyzed at a regional scale to highlight large corridors, but also at a local scale to determine areas for conservation intervention.

Urban vegetation extraction with multi-angular Pléiades images

Vegetation is essential in urban environments since it provides significant services in terms of health, heat, property value, ecology … As part of the European Union Biodiversity Strategy Plan for 2020, the protection and development of green-infrastructures is strengthened in urban areas. In order to evaluate and monitor the quality of the green infra-structures, this article investigates contributions of Pléiades multi-angular images to extract and characterize low and high urban vegetation. From such images one can extract both spectral and elevation information from optical images. Our method is composed of 3 main steps: (1) the computation of a normalized Digital Surface Model from the multi-angular images; (2) Extraction of spectral and contextual features; (3) a classification of vegetation classes (tree and grass) performed with a random forest classifier. Results performed in the city of Rennes in France show the ability of multi-angular images to extract DEM in urban area despite building height. It also highlights its importance and its complementarity with contextual information to extract urban vegetation.

Infrastructures de données géographiques et observatoires de recherche en environnement - Un exemple de mise en œuvre

Cet article decrit une Infrastructure de Donnees Geographiques (Indigeo) elaboree dans un cadre academique associant un laboratoire de recherche et plusieurs observatoires en environnement. La methode Agile utilisee conduit a une solution exploitant des outils libres, et reposant sur un catalogue de metadonnees et un serveur de donnees georeferencees, adosses a un portail web disposant de deux visualiseurs cartographiques dont l’un (geoCMS) prend en charge la dimension temporelle des donnees. Conformement aux recommandations de l’Open Science, Indigeo met actuellement a disposition en acces libre plus de 500 couches d’informations et leurs metadonnees et permet la co-visualisation des donnees d’une quinzaine d’IDG generalistes ou thematiques interoperables. Elle offre aussi une plus-value pour l’analyse de donnees spatio-temporelles. Neanmoins si Indigeo rend actuellement plusieurs services de stockage, d’analyse, de partage et de porter a connaissances de l’information geographique scientifique, elle demeure sous-utilisee en termes d’alimentation du catalogue et de diffusion. Les perspectives d’evolution d’Indigeo sont discutees afin de contrecarrer sa sous-utilisation et son relatif isolement vis-a-vis des IDG institutionnelles et des infrastructures de recherche en environnement

Extraction of urban vegetation with Pleiades multiangular images

Vegetation is essential in urban environments since it provides significant services in terms of health, heat, property value, ecology ... As part of the European Union Biodiversity Strategy Plan for 2020, the protection and development of green-infrastructures is strengthened in urban areas. In order to evaluate and monitor the quality of the green infra-structures, this article investigates contributions of Pléiades multi-angular images to extract and characterize low and high urban vegetation. From such images one can extract both spectral and elevation information from optical images. Our method is composed of 3 main steps : (1) the computation of a normalized Digital Surface Model from the multi-angular images ; (2) Extraction of spectral and contextual features ; (3) a classification of vegetation classes (tree and grass) performed with a random forest classifier. Results performed in the city of Rennes in France show the ability of multi-angular images to extract DEM in urban area despite building height. It also highlights its importance and its complementarity with contextual information to extract urban vegetation.