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Prediction of Forest Stand Attributes Using TerraSAR-X Stereo Imagery

M. Vastaranta,Mikko T. Niemi,M. Karjalainen,J. Peuhkurinen,V. Kankare,J. Hyyppä,M. Holopainen

Published 2014 in Remote Sensing

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

PUBLICATION RECORD

  • Publication year

    2014

  • Venue

    Remote Sensing

  • Publication date

    2014-04-10

  • Fields of study

    Geology, Computer Science, Environmental Science

  • Identifiers
    DOI 10.3390/rs6043227
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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