Can tree cover extent be estimated directly from ICESat-2 spaceborne lidar data?

We performed the estimation at two boreal forest areas in Finland, Valtimo and Pello, using two methods: post-classification and logistic regression estimation. In post-classification, dominant height and canopy cover were estimated first, and areas where dominant height was (≥ 5 m) and canopy cover (≥ 10%) were considered forested. In the second method, logistic regression was used to determine the areas with tree cover using ICESat-2 variables as predictors. The reference values were obtained using airborne laser scanning data and locally measured field plots. The transferability of the ICESat-2 models was also assessed.Our results indicated that ICESat-2 data are suitable for the estimation of tree cover extent over large areas. The overall accuracy ranged from 92% to 95% both for post-classification and logistic regression, depending on the study area. Although the performance of the two classification methods was similar, the classification accuracies were generally lower in Pello. The ICESat-2 models for dominant height and canopy cover had RMSE% values of 21.1–24.5% and 24.9–36.8%, respectively. We conclude that ICESat-2 data appear promising for estimation of accurate statistics on tree cover extent in the boreal biome.

Abstract licence: CC BY-NC

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