|Abstract||The spatial technology represent a major asset in the carried out programmes about prevention of natural hazards. Part of them are already considered as available in operational conditions, namely the
optical satellite imagery (Scanvic et al, 1992), but also the use of digital elevation model (DEM). But it turns out that those data are sometimes difficult to be gathered in every point of the world depending on environmental conditions. |
launches of the European ERS-1 radar, the Japanese JERS-1 sensors, and more recently the Canadian RADARSAT provide Earth scientists with orbital synthetic aperture radar (SAR) data with global coverage. Because these active microwave imaging systems
acquire data of fundamentally different natures in comparison with the passive remote sensing systems, they are expected to generate a complementarity wealth of information to geoscientists.
RADARSAT viewsthe world at a wavelength (C-band, 5 cm)
where the backscatter amplitude depends on surface interaction. In fact, surface roughness, vegetation cover and moisture content of the near-surface layers of the ground play an major role in modulating the signal. Furthermore, the RADARSAT many
beam modes offer a variety of image-terrain configurations of a given location that are very different in terms of geometry and radiometry. Since SAR imagery mimics very well the land shapes and the topography due to its strong sensitivity to the
relief, the foreshortening with steep look angles and the shadowing with shallow look angles generating different radiometric effects (backscatter) can be used to enhance the perception of relief features (Simonett and Davis, 1983).
On the other
hand all the potentialities of SAR data are far to be exploited and validated. In those domain of geoscientific applications, these technical characteristics of RADARSAT are being proved highly attractive:
As part of the Applications Development and Research Opportunity (ADRO) program
sponsored by the Canadian Space Agency (CSA), a research has been started on the potential of RADARSAT for the detection and monitoring of natural hazards. The main objectives of this research is to integrate RADARSAT images in projects of natural
risks prevention to observe and understand phenomena of natural hazards. These projects are often limited by simple constraints: high relief contrast, accessibility of study site, limitation of optical images due to clouds, complex natural phenomena,
etc. RADARSAT could then be integrated in a technical network concerning cartography and monitoring of risk areas to prevent the risk, to reduce impact an occurence and to better manage the environment.
- possibilities to reach every point
on the globe, namely areas where the setting up of permanent monitoring system is difficult, either due to the fact of cloudiness or due to the weak of logistic support on the field;
- agility in incidence, which allows to adapt the acquisition of
data to the constraints of relief; and
- programming of acquisition in high or low resolution, a good tool to change scales over the priority basins of risk.
Earth observations with any satellite must
be able to localise sensitive region. Several approaches can be used:
To allow the successful use and integration of the RADARSAT imagery with geoscientific data in these different approaches, the specific
geometric and radiometric characteristics of the data have to be addressed adequately. This paper presents then a method and simple and operational tools serving to integrate and generate for geoscientific applications value-added products, such as
the new-developed chromo-stereoscopic visualisation tool and the 3D images with RADARSAT data and DEM over a challenging study site: the Reunion Island in the Indian Ocean. Actual morphology can be studied and possible landslides hazards anticipated
on this chromo-stereoscopic images. Moreover, with systematic data acquired at different period of the year, the evolution of this morphology is an asset to explain and model the erosion processes.
- the detection of permanent factors at the origin of the processes (slope, unprotected soil, sensible surface); and
- the detection of characteristic changes on the
surface, corresponding to the consequence of a hazard. In this last approach, time series are required.