Assessment of Cartosat-1 and WorldView-2 stereo imagery in combination with a LiDAR-DTM for timber volume estimation in a highly structured forest in Germany

Abstract

Stereo satellites provide height information of the earth's surface with increasing accuracy. High temporal resolution and wide regional coverage are the great advantages of satellites compared with aerial surveys. There is currently little experience of how accurate forest attributes can be modelled using high-resolution stereo satellite data, especially for highly structured forests in Central Europe. Thus, the potential of Cartosat-1 and WorldView-2 was assessed for timber volume estimation in a complex forest in Germany. Digital surface models were generated using Semi-Global Matching. Canopy height models (CHMs) were computed by subtracting a Light detection and ranging (LiDAR) terrain model. The CHMs were co-registered with field plots of a forest inventory. Explanatory variables were derived from the CHMs for timber volume estimation using regressions. Accuracies were evaluated at plot and stand levels. Results were compared with estimations based on a LiDAR-CHM. At plot level the following root mean squared errors (RMSEs) for timber volume estimation were obtained: 50.26 per cent for Cartosat-1, 44.40 per cent for WorldView-2 and 38.02 per cent for LiDAR. The RMSEs were smaller than the standard deviation of the observed timber volume. The RMSEs at a stand level yielded 21.49 per cent for Cartosat-1, 19.59 per cent for WorldView-2 and 17.14 per cent for LiDAR. The study demonstrates the potential of satellite stereo images for regionalization of sample plot inventories.