Prediction of Forest Stand Attributes Using TerraSAR-X Stereo Imagery

Remote Sensing

Mikko Vastaranta¹  Mikko Niemi¹  Mika Karjalainen³  Jussi Peuhkurinen²  Ville Kankare¹  Juha Hyyppä³ 

[1] Department of Forest Sciences, University of Helsinki, Helsinki FI-00014, Finland; E-Mails:;Arbonaut Oy Ltd., Latokartanontie 7 A, Helsinki FI-00700, Finland; E-Mail:;Centre of Excellence in Laser Scanning Research, Finnish Geodetic Institute, Masala FI-02431, Finland

关键词: remote sensing;    GIS;    forestry;    airborne laser scanning;    radargrammetry;    forest management planning;    forest inventory;   

DOI  :  10.3390/rs6043227

来源: mdpi

【 摘 要 】

Consistent, detailed and up-to-date forest resource information is required for allocation of forestry activities and national and international reporting obligations. We evaluated the forest stand attribute prediction accuracy when radargrammetry was used to derive height information from TerraSAR-X stereo imagery. Radargrammetric elevations were normalized to heights above ground using an airborne laser scanning (ALS)-derived digital terrain model (DTM). Derived height metrics were used as predictors in the most similar neighbor (MSN) estimation approach. In total, 207 field measured plots were used in MSN estimation, and the obtained results were validated using 94 stands with an average area of 4.1 ha. The relative root mean square errors for Lorey’s height, basal area, stem volume, and above-ground biomass were 6.7% (1.1 m), 12.0% (2.9 m²/ha), 16.3% (31.1 m³/ha), and 16.1% (15.6 t/ha). Although the prediction accuracies were promising, it should be noted that the predictions included bias. The respective biases were −4.6% (−0.7 m), −6.4% (−1.6 m²/ha), −9.3% (−17.8 m³/ha), and −9.5% (−9.1 t/ha). With detailed DTM, TerraSAR-X stereo radargrammetry-derived forest information appears to be suitable for providing consistent forest resource information over large areas.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland