Abstract
Canopy height is an essential feature in forest inventory, and for the assessment of biomass and carbon budgets. Spatially explicit maps of forest height over large areas can be derived from satellite synthetic aperture radar data. We aimed to evaluate the capacity of TanDEM-X (TDX) data to assess canopy height in Mediterranean forests of Spain, which are of relatively short height (typically R 2 = 0.91 and root-mean-square error = 1.24 m in one of the study sites. However, in some areas the results were much worse, especially in regions characterized by rugged terrain with broadleaved species. This work demonstrates the feasibility of deriving a forest height map over the entire area of Spain from TDX data. Stratification per slope interval and selection of long interferometric baselines are recommended.
Highlights
F OREST canopy height is a key parameter in forest inventory [1], for estimation of biomass and carbon storage [2], for assessment of essential biodiversity variables [3], and to enable periodical reports and informed management decisions [4]
Before analyzing the forest height inversion results, we inspect here the input data and its sensitivity to forest height, for which individual scenes are selected at the four test sites
It is important to note that the height of ambiguity (HoA) for zero slope of the four scenes is very similar (32–37 m), so a relative comparison among ROIs is possible
Summary
F OREST canopy height is a key parameter in forest inventory [1], for estimation of biomass and carbon storage [2], for assessment of essential biodiversity variables [3], and to enable periodical reports and informed management decisions [4]. Estimating forest height over large areas requires modeling [5], [6] and benefits from complete coverage of spatially explicit data, only possible with satellite acquisitions [7]–[9]. I.e., LiDAR systems provide forest height estimations with unsurpassed accuracy. Satellite-based forest canopy height has been estimated globally from the Geoscience Laser Altimeter System LiDAR aboard the Ice, Cloud and land Elevation Satellite (ICESat) and the Advanced Topographic Laser Altimeter System instrument on ICESat-2 with sampling strategies [7], [8], [12], [13]. GEDI mission has a sampling strategy that requires support from other spatially comprehensive datasets to extrapolate height estimations globally [15]. Global maps of forest height support global climate and sustainable development initiatives but have limited accuracy and resolution for national resource inventory
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