Paper Info
Title
Prediction of Forest Stand Attributes Using TerraSAR-X Stereo Imagery
Abstract
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 m(2)/ha), 16.3% (31.1 m(3)/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 m(2)/ha), -9.3% (-17.8 m(3)/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.
Year
DOI
Venue
2014
10.3390/rs6043227
REMOTE SENSING
Keywords
Field
DocType
remote sensing,GIS,forestry,airborne laser scanning,radargrammetry,forest management planning,forest inventory
Laser scanning,Forest inventory,Remote sensing,Basal area,Digital elevation model,Root mean square,Geology
Journal
Volume
Issue
ISSN
6
4
2072-4292
Citations 
PageRank 
References 
2
0.36
11
Authors
7
Name
Order
Citations
PageRank
Mikko Vastaranta129834.91
mikko niemi220.70
Mika Karjalainen3499.88
jussi peuhkurinen492.27
Ville Kankare5659.21
Juha Hyyppa637745.75
Markus Holopainen735740.95