Aboveground biomass estimation in conifer and deciduous forests with the use of a combined approach

Abstract

The complex action of environmental factors often triggers the biomass formation in forest plantations, which is crucial for carbon balance and environmental monitoring, especially in the context of climate change. In this article, we present data on the aboveground biomass accumulation for black locust and common pine (Pinus sylvestris and Robinia pseudo­acacia) as the two most common forest-forming species in the steppe zone. For this purpose, we propose a reliable approach to monitoring of aboveground forest biomass with combining Sentinel-2 multispectral imaging techniques (with L-band) and biometric processing data from coniferous and deciduous stands obtained from field surveys. We represent the results of field surveys with established indicators of aboveground biomass of forest plantations in the field experiment, which averaged 159.9 ± 9.0 t/ha in the studied region. The biometric indexes obtained from the field experiments were used to develop models for predicting biomass using the remote method. Based on the processing of satellite image data, forest vegetation indices were analysed, among which the NDVI (normalized difference vegetation index) was the best predictor to assess biomass. The multiple regression method was found to be the best for predicting and mapping the aboveground biomass in P. sylvestris and R. pseudoacacia within the studied area (RMSE – 23.46 t/ha). Based on the results obtained, we created a map of the aboveground biomass distribution in black locust and common pine stands within the studied region. We established reliable correlations between biometric parameters (mean diameter at breast height, mean height) and aboveground biomass of stands with indicators of spectral bands in satellite images. This enables us to use the constructed models to estimate the overall productivity of coniferous and deciduous forest stands for large areas.