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Abstract
The characterization of 3D vegetation structures is an important topic, which has been addressed by recent research in remote sensing. The forest inventory requires the proper extraction of accurate structural and functional features of individual trees. This paper presents a novel methodology to study the impact of the canopy reflectance on the 3D tree structure. A heterogeneous natural environment in a Mediterranean forest, in which various tree species (pine, oak and eucalyptus) coexist, was covered using a high-resolution digital camera and a multispectral sensor. These devices were mounted on an Unmanned Aerial Vehicle (UAV) in order to observe the tree architecture and the spectral reflectance at the same time. The Structure from Motion (SfM) method was applied to model the 3D structures using RGB images from the high-resolution camera. The geometric accuracy of the resulting point cloud was validated by georeferencing the study area through multiple ground control points (GCPs). Then, the point cloud was enriched with the reflected light in four narrow-bands (green, near-infrared, red and red-edge). Furthermore, the Normalized Difference Vegetation Index (NDVI) was calculated in order to measure the tree vigor. A comprehensive analysis based on structural and spectral features of individual trees was proposed. A spatial segmentation was developed to detect single-trees in a forest and for each one to identify the crown and trunk. Consequently, structural parameters were extracted, such as the tree height, the diameter at breast height (DBH) and the crown volume. The validation of these measurements was performed by field data, which were taken using a Total Station (TS). In addition, these characteristics were correlated with the mean reflectance in the tree canopy. Regarding the observed tree species, a statistical analysis was carried out to study the impact of reflectance on the 3D tree structure. By applying our method, a more detailed knowledge of forest dynamics can be gained and the impact of available solar irradiance on single-trees can be analyzed.
Highlights
Forests play a key role in the conservation of biological diversity and suppression of climate change effects
Grant et al [7] made a comparison of Light Detection and Ranging (LiDAR) and satellite photogrammetry for forest inventory and the results clearly showed that point cloud data obtained from stereo satellite imagery were useful for the acquisition of forest inventory attributes
The forest structure was modeled using multiple Unmanned Aerial Vehicle (UAV)-based images, which were captured by a high-resolution camera and a multispectral sensor
Summary
Forests play a key role in the conservation of biological diversity and suppression of climate change effects. The observation of reflectance on the 3D tree structure is useful to detect the relationship between the shape of trees and their spectral behaviours. A great variety of technologies and methods have been used to measure and observe 3D vegetation structures, such as RaDAR [3], Light Detection and Ranging (LiDAR) [4] or photogrammetric techniques such as structure-from-motion (SfM) [5]. Grant et al [7] made a comparison of LiDAR and satellite photogrammetry for forest inventory and the results clearly showed that point cloud data obtained from stereo satellite imagery were useful for the acquisition of forest inventory attributes. Unmanned Aerial Vehicles (UAVs) provide a great opportunity to capture multi-source remote sensing data of the forest structure [8,9]. Regarding some UAV-based applications in forestry, Tomaštík et al [10] studied the accuracy of photogrammetric UAV-based point clouds under conditions of a partially open forest canopy and Tian et al [11] proposed a novel tree-height extraction approach for individual trees by combining terrestrial laser scanners (TLS) and UAV
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