Research highlights: In this study, the possibility of developing predictive models for both individual trees and forest stands, based on information derived from digital surface models (DSMs), was evaluated. Background and objectives: Unmanned aerial systems (UASs) make it possible to obtain digital images with increased spectral and spatial resolution at a lower cost. Based on the variables extracted by means of the digital representation of surfaces, we aimed at generating mathematical models that would allow the prediction of the main biometric features of both individual trees and forest stands. Materials and methods: Forest stands are characterized by various structures. As such, measurements may address upper-level trees, but most often are oriented towards those belonging to the mean tree category, randomly selected from those identifiable from digital models. In the case of grouped trees, it is the best practice to measure the projected area of the entire canopy. Tree and stand volumes can be determined using models based on features measured in UAS-derived digital models. For the current study, 170-year-old mixed sessile oak stands were examined. Results: Mathematical models were developed based on variables (i.e., crown diameter and tree height) extracted from digital models. In this way, we obtained results characterized by root mean square error (RMSE) values of 18.37% for crown diameter, 10.95% for tree height, and 8.70% for volume. The simplified process allowed for the estimates of the stand volume using crown diameter or diameter at breast height, producing results with RMSE values of 9%. Conclusions: The accuracy of the evaluation of the main biometric features depends on the structural complexity of the studied plots, and on the quality of the DSM. In turn, this leads to the necessity to parametrize the used models in such a manner that can explain the variation induced by the stand structure.
Forests play an important role in biodiversity conservation, being one of the main providers of ecosystem services, according to the Economics of Ecosystems and Biodiversity. The functions and ecosystem services provided by forests are various concerning the natural capital and the socio-economic systems. Past decades of remote-sensing advances make it possible to address a large set of variables, including both biophysical parameters and ecological indicators, that characterize forest ecosystems and their capacity to supply services. This research aims to identify and implement existing methods that can be used for evaluating ecosystem services by employing airborne and terrestrial stationary laser scanning on plots from the Southern Carpathian mountains. Moreover, this paper discusses the adaptation of field-based approaches for evaluating ecological indicators to automated processing techniques based on airborne and terrestrial stationary laser scanning (ALS and TLS). Forest ecosystem functions, such as provisioning, regulation, and support, and the overall forest condition were assessed through the measurement and analysis of stand-based biomass characteristics (e.g., trees’ heights, wood volume), horizontal structure indices (e.g., canopy cover), and recruitment-mortality processes as well as overall health status assessment (e.g., dead trees identification, deadwood volume). The paper, through the implementation of the above-mentioned analyses, facilitates the development of a complex multi-source monitoring approach as a potential solution for assessing ecosystem services provided by the forest, as well as a basis for further monetization approaches.
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