Forest mapping and monitoring using active 3D remote sensing
Vastaranta M. (2012). Forest mapping and monitoring using active 3D remote sensing. https://doi.org/10.14214/df.144
Abstract
In this thesis, forest mapping and monitoring applications using active 3D remote sensing (RS) were developed. The main aim in forest mapping and inventory is to produce accurate information for forest managers with the use of efficient methodologies. In forest monitoring, it is important to locate harvesting sites and stands where forest operations should be carried out as well as to provide updates regarding forest growth, among other changes in forest structure. In recent years, RS has taken a significant technological leap forward. It has become possible to acquire 3D, spatially accurate information from forest resources using active RS methods. In practical applications, mainly 3D information produced by airborne laser scanning (ALS) has opened up groundbreaking potential in natural resource mapping and monitoring. In addition to ALS, new satellite radars are also capable of acquiring spatially accurate 3D information. The main objectives of the present study were to develop 3D RS methodologies for large-area forest mapping and monitoring applications. In substudy I, we aim to map harvesting sites, while in substudy II, we monitor changes in the forest canopy structure. In studies III-V, efficient mapping and monitoring applications were developed and tested. Spatially accurate 3D RS enables the mapping of harvesting sites, the monitoring of changes in the canopy structure and even the making of a fully RS-based forest inventory. ALS is carried out at relatively low altitudes, which makes it relatively expensive per area unit, and other RS materials are still needed. Spaceborne stereo radargrammetry proved to be a promising technique to acquire additional 3D RS data efficiently as long as an accurate digital terrain model is available as a ground-surface reference.
Keywords
forest inventory;
forest management;
LiDAR;
laser scanning;
synthetic aperture radar;
radargrammetry
Published 29 May 2012
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Available at https://doi.org/10.14214/df.144 | Download PDF
Original articles
Vastaranta M., Holopainen M., Yu X., Hyyppä J., Hyyppä H., Viitala R. (2011). Predicting stand-thinning maturity from airborne laser scanning data. Scandinavian Journal of Forest Research 26 (2):187−196.
https://doi.org/10.1080/02827581.2010.547870
Vastaranta M., Korpela I., Uotila A., Hovi A., Holopainen M. (2012). Mapping of snow-damaged trees in bi-temporal airborne LiDAR data. European Journal of Forest Research.
https://doi.org/10.1007/s10342-011-0593-2
Vastaranta M., Kankare V., Holopainen M., Yu X., Hyyppä J., Hyyppä H. (2012). Combination of individual tree detection and area-based approach in imputation of forest variables using airborne laser data. ISPRS Journal of Photogrammetry and Remote Sensing 67: 73−79.
https://doi.org/10.1016/j.isprsjprs.2011.10.006
Karjalainen M., Kankare V., Vastaranta M., Holopainen M., Hyyppä J. (2012). Prediction of plot-level forest variables using TerraSAR-X stereo SAR data. Remote Sensing of Environment 117: 338−347.
https://doi.org/10.1016/j.rse.2011.10.008
Vastaranta M., Holopainen M., Karjalainen M., Kankare V., Hyyppä J., Kaasalainen S. (2014). TerraSAR-X stereo radargrammetry and
airborne scanning LiDAR height metrics in imputation of forest
aboveground biomass and stem volume. IEEE Transactions on Geoscience
and Remote Sensing 52 (2): 1197-1204.