SRTM (shuttle radar topography mission) DEM (digital elevation model) is a near-global terrain product with high accuracy, and has been widely used in many researches, such as hydrological survey, geological hazards assessment, and ecological protection. However, it has been proved that SRTM DEM is systematic higher than the real ground truth in vegetation regions, as the absorption and reflection of radar signal from leaves and trunks of vegetation, and terrain conditions (such as slope and aspect).
To reduce the SRTM systematic bias in vegetated areas, we collected over 150, 000 km2 airborne LiDAR data to develop a new globally corrected SRTM DEM. 1) The SRTM DEM error models depending on canopy height data, canopy cover data and land cover data were built over various vegetation types. 2) The linear regression based method was used to estimate the original SRTM DEM error and therefore correct the SRTM DEM data. The results show that the original SRTM DEM data is around 6 m higher than the actual land surfaces across all vegetation types. Our corrected SRTM DEM data can significantly reduce the bias to near 0 m.
Note: The CSRTM file with an extension of “_corrected.tif” are corrected topographic data. The other SRTM data are not corrected as they are not covered by vegetation.
Zhao, X., Guo, Q. *, Su, Y., Xue, B. 2016. Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas. ISPRS Journal of Photogrammetry and Remote Sensing. 117: 79 – 91.