Forest canopy height derived from the SRTM-NED were compared to three LIDAR vegetation metrics for the Sierra Nevada forest. Generally the SRTM-NED was found to under estimate the vegetation canopy height. The SRTM SAR signal was found to penetrate, on average, into 44% of the canopies. The residual errors as a function of LVIS canopy height and cover were found to generally increase with height and cover. Likewise, the RMSE was found to initially increase with canopy height and cover but saturates at 50m height and 60% cover.
This investigation is based on the EU project ASSIST(Alpine Safety, Security & Informational Services and Technologies). It is focused on the identification of parameters and/or indicators for natural hazards with special emphasis on landslides analysis. In order to derive the related parameters with adequate accuracy, automated classification and visual interpretation of QUICKBIRD data are used complementarily. For this purpose a comprehensive work has been performed to segregate land cover classes from QUICKBIRD data, to derive geo-morphometric information, and to create a landslide inventory from 'pseudo-stereo' QUICKBIRD interpretation. For estimating the landslide probability on a catchment-and on a single pixel basis the weights-of-evidence method was employed. Such susceptibility maps can subsequently be integrated into the multi platform geo-service framework, which is also developed within the ASSIST project. This framework is used to improve the risk management capacities in mountainous regions by realizing an integrated pre-operational service. The demonstrator includes the client applications for building up an overall crisis management system, e.g. the use of mobile units, a mobile command centre, web-based presentations and open interfaces for other systems.
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