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Using synthetic data to evaluate the benefits of large field plots for forest biomass estimation with LiDAR

Fassnacht, Fabian Ewald ; Latifi, Hooman ; Hartig, Florian


With the maturation of methods for estimating aboveground forest biomass by remote sensing, researchers increasingly need test data, particularly ground reference data, that are large enough to fine-tune existing approaches and test their robustness under diverse conditions. In this context, realistic synthetic datasets present an interesting alternative to costly and limited field data. Here, we ...


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