Accuracy Assessment of Global Topographic Data (srtm & Aster Gdem) in Comparison with Lidar for Tropical Montane Forest

Shuttle Radar Topographic Mission (SRTM) and ASTER Global Digital Elevation Model (GDEM) provide topographic data in a global scale which are freely available for users. The potential use of these datasets for many forestry applications is highly depending on the accuracy of the datasets. In this study, we evaluated the accuracy of SRTM and ASTER GDEM version 2 with high accuracy topographic data of Light Detection and Ranging (LiDAR) acquired using Riegl LMS-Q560 sensor. This study is conducted in tropical montane forest area of approximately 3,600 hectare, Malaysian Borneo. We resampled both the SRTM (90m resolution) and ASTER GDEM (30m resolution) with bilinear interpolation and cubic convolution method to one, two and five meter pixel resolutions. The evaluation was divided into two sites; site 1 (2,100 ha) and site 2 (1,500 ha). The SRTM (SD=9.0m-10.4m; RMSE=9.3m-10.6m) was found to produce better topographic data in comparison with ASTER GDEM (SD=16.9m-18.7m; RMSE=17.0m-19.3m). Our result revealed that resampling using cubic convolution performs only slightly better than bilinear interpolation method (when compared for all SD and RMSE values) for SRTM. Resampling to higher spatial resolution (i.e. 1m) did not influence significantly the performance (when compared for all mean, standard deviation and RMSE values).