Browsing by Subject "radar imaging"

Accurate and economical remote sensing method with good temporal resolution is required for mapping up-to-date information about the forest resources. Detecting forests by optical satellite images is an inaccurate procedure with the saturation problem. Airborne laser scanning (ALS) is a precise application, but the inventory process is slow and expensive. Recently the new synthetic aperture radar (SAR) satellites with a high spatial resolution have caused a renaissance of radar-based remote sensing. The purpose of the master’s thesis was to investigate the accuracy of forest mapping by radargrammetric processing of TerraSAR-X satellite images. The radargrammetry is based on stereoscopic measurement, which calculates 3D coordinates for corresponding points of the SAR image pair. In the research an area-based approach (ABA) was utilized to estimate forest attributes from the 3D points, and digital terrain model (DTM) produced by ALS was used to calculate height of the corresponding points. In plot-level the relative RMSEs for stem volume, biomass, basal area and mean height were 40.3 %, 39.9 %, 34.0 % and 15.9 %. In stands larger than 2 hectares the corresponding RMSEs were 20.2 %, 20.4 %, 36.1 % and 6.9 %. It’s notable that the estimation of basal area didn’t improve in stand-level at all. According to the research SAR radargrammetry is a precise technology to estimate forest canopy height, but the mapping of forest density is very unclear. Nevertheless the results about the estimation accuracy of forest stem volume and biomass by SAR radargrammetry were clearly better than the comparable estimation accuracy of optical satellite images.