Abstract
Abstract. Obtaining information about forest attributes is essential for planning, monitoring, and management of forests. Due to the time and cost consuming of Tree Density (TD) using field measurements especially in the vast and remote areas, remote sensing techniques have gained more attention in scientific community. Khyroud forest, a part of Hyrcanian forest of Iran, with a high species biodiversity and growing volume stock plays an important role in carbon storage. The aim of this study was to assess the capability of Sentinel-2 data for estimating the tree density in the Khyroud forest. 65 square sample plots with an area of 2025 m2 were measured. In each sample plot, trees with diameter at the breast height (DBH) higher than 7.5-cm were recorded. The quality of Sentinel-2 data in terms of geometric correction and cloud effect were investigated. Different processing approaches such as vegetation indices and Tasseled Cap transformation on spectral bands in combination with an empirical approach were implemented. Also, some of biophysical variables were computed. To assess the model performance, the data were randomly divided into parts, 70% of sample plots were used for modelling and 30% for validation. The results showed that the SVR algorithm (linear kernel) with a relative RMSE of 23.09% and a R2 of 0.526 gained the highest performance for tree density estimation.
Highlights
Forest’s ecosystem is one of the most important carbon sinks of the terrestrial ecosystem
Recognition of available resources and accessibility to an update database are important for forest planning and management (Ahmadi Sani, 2008) in this study, we aim to investigate the relationship between the Sentinel-2 derived features and the tree density, hereafter Tree Density (TD), for Beech (Fagus Orientalis) stands in Khyroud forests
Applied machine learning approaches strengthened the hypothesis of estimating TD of Fagus Orientalis stands using Sentinel-2 images, but a need for further investigation is remain
Summary
Forest’s ecosystem is one of the most important carbon sinks of the terrestrial ecosystem. Field data measurement is a conventional method for estimating the forest structural attributes This method produces the most accurate results, it is labor intensive, expensive and time consuming. It still lacks providing the spatially explicit of forest attributes in large area. Remote sensing data have been shown to provide a solution for the above-mentioned challenges (Vashum and ayakumar, 2012). To the best of our knowledge, a few studies have been conducted to estimate tree density using remote sensing data over Hyrcanian and Zagros forests of Iran (Pir Bavaghar, 2011; Kalbi et al, 2013; Noorian et al, 2014). Recognition of available resources and accessibility to an update database are important for forest planning and management (Ahmadi Sani, 2008) in this study, we aim to investigate the relationship between the Sentinel-2 derived features and the tree density, hereafter TD, for Beech (Fagus Orientalis) stands in Khyroud forests
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