Abstract
Abstract. Remote Sensing (RS) techniques are increasingly used in urban tree inventory measurements for their improved accuracy and promptness over the conventional methods. The focus of this study is to evaluate the application of iPad Pro 2020 and its LiDAR sensor for urban trees reconstruction and Diameter at Breast Height (DBH) measurements. Altogether, 101 trees were scanned. We have used individual- and multiple-tree scan modes with different settings (Resolution: 10 mm, 15 mm, 20 mm; Confidence: High, Low). With these methods and settings, we have established 12 combinations. The 3DScannerAPP was used to scan and generate point clouds and to estimate DBH circle-fitting algorithm was used within the DendroCloud software. Among 12 methods, the only method with 10 mm resolution, high confidence, and multiple-tree mode has not achieved a 100% detection rate (97%). For multiple-tree mode, the highest estimation accuracy was 7.52% of relative RMSE, and for single-tree mode, it was 7.27%. Low confidence setting had significantly higher accuracy of DBH estimation than high confidence. Furthermore, single-tree mode had a significantly higher accuracy of DBH estimation than multiple-tree mode. The most efficient combination for DBH estimation of urban trees using 3DScannerAPP within iPad Pro 2020, when time and accuracy is considered, was multiple-tree mode with 15 mm resolution and low confidence.
Highlights
Urban trees provide citizens with multiple benefits, such as cooling the air temperature, purifying air from pollutants, regulating water flow, they are improving the mental health of citizens, which makes it important to have information about such trees on an individual level, forest inventory (Mcroberts and Tomppo, 2007; Ciesielski and Sterenczak, 2019)
We focused on: (1) the scanning possibilities of iPad Pro 2020 when urban trees are the objects of scanning; (2) the data acquisition approaches and their impact on Diameter at Breast Height (DBH) estimation accuracy; (3) the impact of different scanning settings on the accuracy of DBH estimation
All the point clouds collected within the experiment from iPad Pro 2020 together with reference data are freely available (Xiaoling et al, 2021c)
Summary
Urban trees provide citizens with multiple benefits, such as cooling the air temperature, purifying air from pollutants, regulating water flow, they are improving the mental health of citizens, which makes it important to have information about such trees on an individual level, forest inventory (Mcroberts and Tomppo, 2007; Ciesielski and Sterenczak, 2019). Based on that it can be used to calculate multiple economic values (Nowak et al, 2002) and ecological benefits such as cooling the air temperature (Ren et al, 2013), purification air from pollution (Janhäll, 2015), and improving the mental health of citizens (Nielsen et al, 2007). Manual forest inventory is costly and time-consuming This demands sustainable alternative methods, such as Remote Sensing (RS). In 2020, Apple Inc. introduced a LiDAR-based depth sensor and enhanced Augmented Reality (AR) application
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