Estimation and Extrapolation of Tree Parameters Using Spectral Correlation between UAV and Pléiades Data

Abstract

Abstract:The latest technological advances in space-borne imagery have significantly enhanced the acquisition of high-quality data. With the availability of very high-resolution satellites, such as Pléiades, it is now possible to estimate tree parameters at the individual level with high fidelity. Despite innovative advantages on high-precision satellites, data acquisition is not yet available to the public at a reasonable cost. Unmanned aerial vehicles (UAVs) have the practical advantage of data acquisition at a higher spatial resolution than that of satellites. This study is divided into two main parts: (1) we describe the estimation of basic tree attributes, such as tree height, crown diameter, diameter at breast height (DBH), and stem volume derived from UAV data based on structure from motion (SfM) algorithms; and (2) we consider the extrapolation of the UAV data to a larger area, using correlation between satellite and UAV observations as an economically viable approach. Results have shown that UAVs can be used to predict tree characteristics with high accuracy (i.e., crown projection, stem volume, cross-sectional area (CSA), and height). We observed a significant relation between extracted data from UAV and ground data with R 2 = 0.71 for stem volume, R 2 = 0.87 for height, and R 2 = 0.60 for CSA. In addition, our results showed a high linear relation between spectral data from the UAV and the satellite (R 2 = 0.94). Overall, the accuracy of the results between UAV and Pléiades was reasonable and showed that the used methods are feasible for extrapolation of extracted data from UAV to larger areas.

Forestry Remote Sensing from Unmanned Aerial Vehicles: A Review Focusing on the Data, Processing and Potentialities

“…In this way, the authors intended to improve the acquisition of the compact information of tree trunks and crowns. Regarding to Abdollahnejad et al [105] study, authors used a UAV-RGB sensor, achieving a strong correlation (R 2 = 0.71). Abdollahnejad et al [105] concluded that remote sensing techniques revealed effective for characterizing forest tree parameters.…”

“…Height parameters were widely estimated, once it easily can be obtained using point cloud or raster data (CHM). On the other hand, AGB and DBH estimations are dependent of the allometric equations [85,88,91,95] and/or using regression [37,84,85,88,91,98,103,105,165], since these parameters cannot be directly estimated from UAV-based data.…”

Impact of the Acquisition Geometry of Very High-Resolution Pléiades Imagery on the Accuracy of Canopy Height Models over Forested Alpine Regions

“…Among the few researchers that have used the Pléiades satellites for forestry purposes, the Pléiades image texture for forest structure mapping and forest classification has been investigated previously in [24,25]. Recently, the potential for use Pléiades images has been investigated for estimating forest attributes for 10 m plots in a boreal forest [26], for deriving forest biomass by combining spectral and geometric information [27,28], for predicting forest inventory attributes in New Zealand's planted forests [29] and for modelling tree diversity [30].…”

Accuracy assessment of different photogrammetric software for processing data from low-cost UAV platforms in forest conditions

“…The installation of a GNSS receiver with the RTK technology is several times more expensive than the platform itself, which makes this solution a less preferred one. Most related studies involve costly platforms built for specific applications (Aicardi et al 2017, James et al 2017, Sankey et al 2017, Abdollahnejad et al 2018. It is therefore important to investigate the most cost-effective approach to obtain a readymade orthomosaics based on an inexpensive navigation system with robust computational algorithm.…”