Digital aerial photogrammetry as a spatial and temporal extension of ALS in forest height growth modeling

Abstract

Forest height is the key variable measured within the frame of forest monitoring and, at the same time, the most important input variable in forest growth modeling. In particular, top height (TH), a fundamental stand attribute that affects biomass allocation and carbon storage. In this study, we demonstrated the potential of digital aerial photogrammetry (DAP) data in TH growth modeling. We used DAP-derived TH corrected by using reference TH values calculated based on airborne laser scanning (ALS) data. The novelty of this approach lies in the fact that we corrected DAP-based TH measurement using reference from different years. In the developed approach, the ALS-derived TH is updated to the year of DAP data collection using a TH growth model, so that it can be used as a reference for the correction of the DAP-derived TH. We showed that the effectiveness of TH updating is almost independent of the growth model used, indicating that this parameter can be updated using models that are not adapted to local growth conditions. We then showed that the TH derived from the DAP data corrected by using the proposed approach is useful for developing appropriate local TH growth models.

Keywords

• DAP
• airborne laser scanning
• LiDAR
• top height
• growth models
• remote sensing