Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 59-63, 2016
https://doi.org/10.5194/isprs-archives-XLI-B8-59-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
22 Jun 2016
A NEW METHOD TO DETECT REGIONS ENDANGERED BY HIGH WIND SPEEDS
P. Fischer, S. Ehrensperger, and T. Krauß Remote Sensing Technology Istitute, German Aerospace Center (DLR), Münchener Str. 20, 82234 Wessling, Germany
Keywords: Non-Parametric Regression, Boosted Regression Trees, Wind Speeds, Spatial Predictions Abstract. In this study we evaluate whether the methodology of Boosted Regression Trees (BRT) suits for accurately predicting maximum wind speeds. As predictors a broad set of parameters derived from a Digital Elevation Model (DEM) acquired within the Shuttle Radar Topography Mission (SRTM) is used. The derived parameters describe the surface by means of quantities (e.g. slope, aspect) and quality (landform classification). Furthermore land cover data from the CORINE dataset is added. The response variable is maximum wind speed, measurements are provided by a network of weather stations. The area of interest is Switzerland, a country which suits perfectly for this study because of its highly dynamic orography and various landforms.
Conference paper (PDF, 917 KB)


Citation: Fischer, P., Ehrensperger, S., and Krauß, T.: A NEW METHOD TO DETECT REGIONS ENDANGERED BY HIGH WIND SPEEDS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 59-63, https://doi.org/10.5194/isprs-archives-XLI-B8-59-2016, 2016.

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