Assessment of pine aboveground biomass within Northern Steppe of Ukraine using Sentinel-2 data

Viktoriia Lovynska, Yuriy Buchavyi, Petro Lakyda, Svitlana Sytnyk, Yuriy Gritzan and Roman Sendziuk
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Viktoriia Lovynska: Department of Parks and Gardens, Faculty of Agronomy, Dnipro State Agrarian and Economic University, Dnipro, Ukraine
Yuriy Buchavyi: Department of Ecology and Technologies of Environmental Protection, National Technical University "Dnipro Polytechnic", Dnipro, Ukraine
Petro Lakyda: Education and Research Institute of Forestry and Landscape Park Management, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine
Svitlana Sytnyk: Department of Forest Measurement and Forest Management, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine
Yuriy Gritzan: Department of Parks and Gardens, Faculty of Agronomy, Dnipro State Agrarian and Economic University, Dnipro, Ukraine
Roman Sendziuk: Department of Forest Measurement and Forest Management, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine

Journal of Forest Science, 2020, vol. 66, issue 8, 339-348

Abstract: The present study offers the results of the spectral characteristics, calculated vegetative indices and biophysical parameters of pine stands of the Northern Steppe of Ukraine region obtained using Sentinel-2 data. For the development of regression models with the prediction of the biomass of pine forests using the obtained spectral characteristics, we used the results of the assessment of the aboveground biomass by the method of field surveys. The results revealed the highest correlation relations between the parameters of the general and trunk biomass with the normalised difference vegetation index (NDVI) and transformed vegetation index (TVI) vegetative indices and the fraction of absorbed photosynthetic active radiation (FARAP) and fraction of vegetation cover (FCOVER) biophysical parameters. To generate the models of determining the forest aboveground biomass (AGB), we used both the single- and two-factor models, the most optimum of which were those containing the NDVI predictor separately and in combination with the FCOVER predictor. The predicted values of the total AGB for the mentioned models equalled 32.5 to 236.3 and 39.9 to 253.4 t.ha-1. We performed mapping of the AGB of pine stands of the Northern Steppe using multi-spectral Sentinel-2 images, particularly the spectral characteristics of their derivatives (vegetative indices, biophysical parameters). This study demonstrated promising results for conducting an AGB-mapping of pine woods in the studied region using free-access resources.

Keywords: Pinus sylvestris L.; spectral indices; remote sensing; allometric regression; Steppe zone (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnljfs:v:66:y:2020:i:8:id:28-2020-jfs

DOI: 10.17221/28/2020-JFS

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