Characterization of riparian zones in wallonia (belgium) from local to regional scale using aerial lidar data and photogrammetric DSM | Utilisation de données LiDAR et de MNS photogrammétrique pour la caractérisation des bandes riveraines en Wallonie (Belgique) de l'échelle locale à l'échelle régionale

English. peer reviewed

English. The present study proposes an innovative approach to automatically extract riparian zone characteristics in order to assess its quality, from pre-determined river management reaches (1-3 km long) to regional scale (ca. 13000 km for 1000 management sectors). The aim of this remotely sensed monitoring is to improve the river and riparian zone management and planning by providing some key information for river managers. The methodology was developed based on two watersheds covering approximately 500 km of river network (ca. 200 management sectors). The riparian zone quality is evaluated through various indicators of its ecological integrity (e.g. longitudinal continuity of riparian forest, mean vegetation height and relative standard deviation), hydromorphological quality and physical settings (e.g. flow channel extent, floodplain width, channel sinuosity). The physical characteristics of the riparian zone are mainly extracted from a high quality Digital Terrain Model (derived from ALS data) while the attributes of the riparian forest are derived from a « hybrid » Canopy Height Model (photogrammetric Digital Surface Model – LiDAR derived DTM). This first research is exclusively based on data which are available at the regional scale (170000 square km) to develop automated tools to implement the methodology to the whole Walloon river network (13000 km) before 2015 with an update frequency of 3 years (photogrammetric DSM survey frequency). Moreover, our approach is based on a photogrammetric Digital Surface Model which is derived from raw images of an orthophoto coverage. As most of European countries are regularly covered by orthophoto surveys, our approach is widely replicable in countries where a quality DTM is available.

Projet Imageau 2