Assessing forest inventory information obtained from different inventory approaches and remote sensing data sources

Abstract

International audienceContext Evaluations of forest inventories usually end when accuracy and precision have been quantified. Aims We aim to value the accuracy of information derived from different remote sensing sensors (airborne laser scanning, aerial multispectral and hyperspectral imagery) and four alternative forest inventory approaches. Methods The approaches were (1) mean values or (2) diameter distributions both obtained by the area-based approach (ABA), (3) individual tree crown (ITC) segmentation and (4) an approach called semi-individual tree crown (SITC) segmentation. The estimated tree information was assessed and used to evaluate how erroneous inventory data affect economic value and loss due to suboptimal harvesting decisions. Field measured data used as reference come from 23 field plots collected in a study area in south-eastern Norway typical of managed boreal forests in Norway. Results The accuracy of the forest inventory was generally in line with previous studies. Our results show that using mean values from the area-based approach may yield large economic losses, while adding a diameter distribution to the area-based approach yielded less loss than the individual tree crown methods. Adding information from imagery had little effect on the results. Conclusions Taking inventory costs into account, diameter distributions from the area-based approach without additional information seems favourable

Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging

“…Respectively relative RMSE for stem number of spruce was reported to vary from 33.2% to 51.5%, and for deciduous trees from 110.2% to 144.8%. In this study, the relative RMSE for pine and spruce were larger but for deciduous trees the relative RMSEs were similar as compared to the results by [75]. The relative RMSE value based on ITC, as reported by [75], for stem number of spruce varied between 80.7% and 83.5%, for pine between 55.3% and 60.0%, and for deciduous trees between 102.9% and 121.3%.…”

“…In this study, the relative RMSE for pine and spruce were larger but for deciduous trees the relative RMSEs were similar as compared to the results by [75]. The relative RMSE value based on ITC, as reported by [75], for stem number of spruce varied between 80.7% and 83.5%, for pine between 55.3% and 60.0%, and for deciduous trees between 102.9% and 121.3%. Again, our results are not as accurate for pine and spruce, but were similar for deciduous trees.…”

“…Our results support their findings. In [75], basal-area weighted mean diameter was estimated with relative RMSE of 28% with ITC, whereas with semi-ITC the relative RMSE varied between 12.1% and 14.3%. Our results showed lower accuracies as the relative RMSE with ITC was 41.73% and 47.64% with spectral features and vegetation indices, respectively, and with semi-ITC the corresponding values were 46.68% and 51.95%.…”

“…In [75], on the other hand, ALS data was combined with red-green-infrared, multispectral, and hyperspectral imagery to estimate total volume and species-specific stem number with ITC and semi-ITC. With semi-ITC, the mean relative RMSE for number of pine stems per hectare varied between 34.7% and 47.8% depending on whether only ALS was used or a combination of ALS and aerial imagery.…”

Characterizing the Height Structure and Composition of a Boreal Forest Using an Individual Tree Crown Approach Applied to Photogrammetric Point Clouds

“…In both cases, two alternative methods were tested: the now classical area-based approach (ABA, e.g., [9]) and the individual tree crown (ITC) methods (see [10], and [11] for reviews). For structural attribute quantification, both ABA and ITC can now achieve results of relatively high accuracy.…”