Abstract
The quality and accuracy of Unmanned Aerial System (UAS) products greatly depend on the methods used to define image orientations before they are used to create 3D point clouds. While most studies were conducted in non- or partially-forested areas, a limited number of studies have evaluated the spatial accuracy of UAS products derived by using different image block orientation methods in forested areas. In this study, three image orientation methods were used and compared: (a) the Indirect Sensor Orientation (InSO) method with five irregularly distributed Ground Control Points (GCPs); (b) the Global Navigation Satellite System supported Sensor Orientation (GNSS-SO) method using non-Post-Processed Kinematic (PPK) single-frequency carrier-phase GNSS data (GNSS-SO1); and (c) using PPK dual-frequency carrier-phase GNSS data (GNSS-SO2). The effect of the three methods on the accuracy of plot-level estimates of Lorey’s mean height (HL) was tested over the mixed, even-aged pedunculate oak forests of Pokupsko basin located in Central Croatia, and validated using field validation across independent sample plots (HV), and leave-one-out cross-validation (LOOCV). The GNSS-SO2 method produced the HL estimates of the highest accuracy (RMSE%: HV = 5.18%, LOOCV = 4.06%), followed by the GNSS-SO1 method (RMSE%: HV = 5.34%, LOOCV = 4.37%), while the lowest accuracy was achieved by the InSO method (RMSE%: HV = 5.55%, LOOCV = 4.84%). The negligible differences in the performances of the regression models suggested that the selected image orientation methods had no considerable effect on the estimation of HL. The GCPs, as well as the high image overlaps, contributed considerably to the block stability and accuracy of image orientation in the InSO method. Additional slight improvements were achieved by replacing single-frequency GNSS measurements with dual-frequency GNSS measurements and by incorporating PPK into the GNSS-SO2 method.
Highlights
Forest inventory provides critical information about the condition and status of forest resources, which is important for the implementation of sustainable forest management
The Global Navigation Satellite System (GNSS)-SO2 point clouds (PCs) was used as a reference since it was expected to have the strongest geometry of the image orientation in comparison to Indirect Sensor Orientation (InSO) and GNSS-SO1 based PCs
The effect of different orientation methods (InSO, GNSS-SO1, GNSS-SO2) applied to Unmanned Aerial System (UAS) images and PCs on the accuracy of plot-level HL estimates was tested on the example of mixed, even-aged pedunculate oak forests characterized by flat terrain
Summary
Forest inventory provides critical information about the condition and status of forest resources, which is important for the implementation of sustainable forest management. Mapping forest resources is possible with the use of remote sensing technology through continuous data acquisition and advanced statistical analysis. Advances in computer technology and the availability of low-cost aerial imagery have resulted in a large number of studies [8,9,10,11,12,13], which demonstrates the great potential of Digital Aerial Photogrammetry (DAP) for forest inventory. The flight endurance and size of a surveyed area limit the performance of UASs compared to traditional technologies from manned aircraft [19], UASs enable flexible multi-temporal data collection, very high spatial resolution, and a considerably lower cost [20,21,22]. UAS-based photogrammetry can be considered as a cost-effective alternative to both ALS and traditional DAP for forest inventory of small areas [14]
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