Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B4, 129-136, 2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
13 Jun 2016
L. Feng and J.-P. Muller Mullard Space Science Laboratory (MSSL), University College London, Department of Space & Climate Physics, Holmbury St Mary, Surrey, RH5 6NT, UK
Keywords: Global DEM, validation, TanDEM-X intermediate DEM, ICESat elevations Abstract. From the latest TanDEM-X mission (bistatic X-Band interferometric SAR), globally consistent Digital Elevation Model (DEM) will be available from 2017, but their accuracy has not yet been fully characterised. This paper presents the methods and implementation of statistical procedures for the validation of the vertical accuracy of TanDEM-X iDEMs at grid-spacing of approximately 12.5 m, 30 m and 90 m based on processed ICESat data over the UK in order to assess their potential extrapolation across the globe. The accuracy of the TanDEM-X iDEM in UK was obtained as follows: against ICESat GLA14 elevation data, TanDEM-X iDEM has −0.028±3.654 m over England and Wales and 0.316 ± 5.286 m over Scotland for 12 m, −0.073 ± 6.575 m for 30 m, and 0.0225 ± 9.251 m at 90 m. Moreover, 90 % of all results at the three resolutions of TanDEM-X iDEM data (with a linear error at 90 % confidence level) are below 16.2 m. These validation results also indicate that derivative topographic parameters (slope, aspect and relief) have a strong effect on the vertical accuracy of the TanDEM-X iDEMs. In high-relief and large slope terrain, large errors and data voids are frequent, and their location is strongly influenced by topography, whilst in the low- to medium-relief and low slope sites, errors are smaller. ICESat derived elevations are heavily influenced by surface slope within the 70 m footprint as well as there being slope dependent errors in the TanDEM-X iDEMs.
Conference paper (PDF, 1673 KB)

Citation: Feng, L. and Muller, J.-P.: ICESAT VALIDATION OF TANDEM-X I-DEMS OVER THE UK, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B4, 129-136,, 2016.

BibTeX EndNote Reference Manager XML