A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
TerraSAR-X Stereo Radargrammetry and Airborne Scanning LiDAR Height Metrics in Imputation of Forest Aboveground Biomass and Stem Volume
Tekijät: Vastaranta, Mikko; Holopainen, Markus; Karjalainen, Mika; Kankare, Ville; Hyyppä, Juha; Kaasalainen, Sanna
Kustantaja: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Kustannuspaikka: PISCATAWAY
Julkaisuvuosi: 2014
Journal: IEEE Transactions on Geoscience and Remote Sensing
Tietokannassa oleva lehden nimi: IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Lehden akronyymi: IEEE T GEOSCI REMOTE
Vuosikerta: 52
Numero: 2
Aloitussivu: 1197
Lopetussivu: 1204
Sivujen määrä: 8
ISSN: 0196-2892
eISSN: 1558-0644
DOI: https://doi.org/10.1109/TGRS.2013.2248370
Tiivistelmä
Our objective is to evaluate the boreal forest aboveground biomass (AGB) and stem volume (VOL) imputation accuracy when scanning LiDAR or TerraSAR-X stereo radargrammetry-derived point-height metrics are used as predictors in the nearest neighbor imputation approach. Treewise measured field plots are used as reference data in the AGB and VOL imputations and accuracy evaluations. The digital terrain model (DTM) that is produced by the National Land Survey of Finland is used to obtain aboveground elevation values for the TerraSAR-X stereo radargrammetry. The DTM that is used (i.e., grid size 2 m) is derived from LiDAR surveys with an average point density of similar to 0.5 points/m(2). The respective DTM and point data are used in LiDAR imputations of AGB and VOL. The relative root mean square errors (RMSEs) for AGB and VOL are 29.9% (41.3 t/ha) and 30.2% (78.1 m(3)/ha) when using TerraSAR-X stereo radargrammetry metrics. The respective LiDAR estimation accuracy values are 21.9% (32.3 t/ha) and 24.8% (64.2 m(3)/ha). LiDAR imputations are clearly more accurate than imputations that are made by using TerraSAR-X stereo radargrammetry metrics. However, the difference between imputation accuracies of LiDAR- and TerraSAR X-based features are smaller than in any previous study in which LiDAR and different types of synthetic aperture radar materials are compared in the variable predictions regarding forests. We conclude that TerraSAR X stereo radargrammetry is a promising remote-sensing technique for large forest-area AGB and VOL mapping and monitoring when an accurate LiDAR-based DTM is available.
Our objective is to evaluate the boreal forest aboveground biomass (AGB) and stem volume (VOL) imputation accuracy when scanning LiDAR or TerraSAR-X stereo radargrammetry-derived point-height metrics are used as predictors in the nearest neighbor imputation approach. Treewise measured field plots are used as reference data in the AGB and VOL imputations and accuracy evaluations. The digital terrain model (DTM) that is produced by the National Land Survey of Finland is used to obtain aboveground elevation values for the TerraSAR-X stereo radargrammetry. The DTM that is used (i.e., grid size 2 m) is derived from LiDAR surveys with an average point density of similar to 0.5 points/m(2). The respective DTM and point data are used in LiDAR imputations of AGB and VOL. The relative root mean square errors (RMSEs) for AGB and VOL are 29.9% (41.3 t/ha) and 30.2% (78.1 m(3)/ha) when using TerraSAR-X stereo radargrammetry metrics. The respective LiDAR estimation accuracy values are 21.9% (32.3 t/ha) and 24.8% (64.2 m(3)/ha). LiDAR imputations are clearly more accurate than imputations that are made by using TerraSAR-X stereo radargrammetry metrics. However, the difference between imputation accuracies of LiDAR- and TerraSAR X-based features are smaller than in any previous study in which LiDAR and different types of synthetic aperture radar materials are compared in the variable predictions regarding forests. We conclude that TerraSAR X stereo radargrammetry is a promising remote-sensing technique for large forest-area AGB and VOL mapping and monitoring when an accurate LiDAR-based DTM is available.
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