Version 1
: Received: 20 September 2024 / Approved: 20 September 2024 / Online: 23 September 2024 (07:41:40 CEST)
How to cite:
Kotlarz, J.; Kubiak, K.; Kacprzak, M.; Oszako, T. Remote Sensing Analysis of Wood Volume and Volume Increments in Pine Forest Ecosystems: Insights from Vegetation Indices. Preprints2024, 2024091694. https://doi.org/10.20944/preprints202409.1694.v1
Kotlarz, J.; Kubiak, K.; Kacprzak, M.; Oszako, T. Remote Sensing Analysis of Wood Volume and Volume Increments in Pine Forest Ecosystems: Insights from Vegetation Indices. Preprints 2024, 2024091694. https://doi.org/10.20944/preprints202409.1694.v1
Kotlarz, J.; Kubiak, K.; Kacprzak, M.; Oszako, T. Remote Sensing Analysis of Wood Volume and Volume Increments in Pine Forest Ecosystems: Insights from Vegetation Indices. Preprints2024, 2024091694. https://doi.org/10.20944/preprints202409.1694.v1
APA Style
Kotlarz, J., Kubiak, K., Kacprzak, M., & Oszako, T. (2024). Remote Sensing Analysis of Wood Volume and Volume Increments in Pine Forest Ecosystems: Insights from Vegetation Indices. Preprints. https://doi.org/10.20944/preprints202409.1694.v1
Chicago/Turabian Style
Kotlarz, J., Mariusz Kacprzak and Tomasz Oszako. 2024 "Remote Sensing Analysis of Wood Volume and Volume Increments in Pine Forest Ecosystems: Insights from Vegetation Indices" Preprints. https://doi.org/10.20944/preprints202409.1694.v1
Abstract
This article explores the use of vegetation indices (VIs) in remote sensing for estimating standing wood volume and volume increments in forest ecosystems. The study investigates the correlations between various VIs and wood volume across different forest stand age classes, focusing on the effectiveness of commonly used indices such as Squared Ratio Simple Red Edge (SQSR) and Red-Edge Ratio Vegetation Index (RERVI), as well as other typical indicators including Enhanced Vegetation Index (EVI), Red-Edge EVI (RE-EVI), and Green Normalized Difference Vegetation Index (GNDVI). Additionally, the analysis considers a pair of indicators based on blue and near-infrared channels, resembling the Blue-normalized Difference Vegetation Index (BNDVI). The research reveals that quadratic and power-law models of SQSR and RERVI demonstrate higher correlations (>0.40) with wood volume, especially in younger forest stands (>0.80). Furthermore, the study highlights the potential of NDII and NDWI indices for estimating volume increments in certain classes of forest stands (0.70). However, correlations vary across different forest stand classes, suggesting the need for further investigation into the reliability of VIs for monitoring wood volume and volume increments in forest ecosystems. Overall, this research contributes to the understanding of the applicability of VIs in remote sensing for forest management and ecosystem monitoring.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
