Estimation of species diversity in the Hyrcanian forests using Sentinel-2 Data (Case study: Kheyrud forest, Mazandaran)

As a sustainable forest indicator, biodiversity plays a crucial role in understanding the effects of climate change on forest ecosystems. Measuring the diversity of trees and shrubs in forests is essential for monitoring and evaluating changes in biodiversity. Remote sensing (RS) is an effective tool for collecting such data. To estimate tree and shrub species diversity, we used Sentinel-2 data from August 10 and October 13, 2021. We measured 75 field plots with dimensions of 20 m × 20 m in the Patom, Namkhaneh, and Gorazban districts. In each field plot, the tree species and diameter at breast height of all trees with a diameter greater than 7.5 cm were recorded. We used the Jaccard and Sorensen indices in R software to calculate the beta diversity indices for each sample plot. Preprocessing steps were applied to the Sentinel2 data, and we then performed several spectral transformation approaches, that is, vegetation indices (VIs), principal component analysis (PCA), and Tasseled Cap, and generated texture variables. A vector map was used to extract the spectral and textural values corresponding to each field plot. Correlation analysis between the measured species diversity and spectral and textural variables was conducted at a 95% probability level. Multiple Linear Regression (MLR) analysis was performed using stepwise and Random Forest (RF) methods for modeling. Our regression analysis revealed that texture variables with a window size of 5×5 and spatial resolution of 10 m in Sentinel-2 summer images had the best performance in estimating the Sorensen diversity index( R2= 0.383 and RMSE%= 36.57). However, based on our results, we can conclude that the Sentinel-2 data has a moderate performance in estimating diversity in the Patom, Namkhaneh, and Gorazbon districts.