Evaluation of Ipad Pro 2020 Lidar for Estimating Tree Diameters in Urban Forest

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.

Evaluation of Azure Kinect Derived Point Clouds to Determine the Presence of Microhabitats on Single Trees Based on the Swiss Standard Parameters

“…The second most accurate results were obtained from TLS, with values close to the reference of 1.3 ± 1.6 cm (c.f Table 3). Nevertheless, the Azure Kinect DBH measurements were more accurate when compared to the best results obtained with the iPad Pro 2020 (σ = ±2.78cm) in this study (Wang et al, 2021). Our results confirmed that the Azure Kinect has a very good potential in the field of low-cost precision sensors.…”

Low-Cost 3d Techniques for Real Sculptural Twins in the Museum Domain

“…The same set was also used to capture the video with the IPAD Pro (Apple) and experiment with the Lidar instrument, testing different working distances and configurations (Table 1). The low resolution obtained from the Lidar did not allow for acceptable results (Figure 5), justifying the previous research on the topic (Luetzenburg et al, 2021;Wang et al, 2021).…”

“…A small insight should also be devoted to introducing Lidar systems integrated with computer vision algorithms in some devices, such as IPADs and iPhones of the latest generation. Although these are very powerful and versatile tools, early experiments showed how they had been created mainly to support other tools, such as Augmented Reality (Luetzenburg et al, 2021;Wang et al, 2021). On the image-matching side, it is essential to highlight the increasingly optimized use of uncalibrated cameras mounted on smartphones for defining reliable complex 3D models (Russo et al, 2019), as well as the application of spherical images to analyse complex environments (Prizeman and Barazzetti, 2021).…”

Tree Diameter at Breast Height (DBH) Estimation Using an iPad Pro LiDAR Scanner: A Case Study in Boreal Forests, Ontario, Canada

“…This study achieved an overall RMSE of 1.5 cm (8.6%) for DBH values estimated from iPad Pro LiDAR data for 15 sites in the boreal forest. This is a lower RMSE than those reported in several previous studies using the iPad Pro to estimate DBH, such as: an urban park (Slovakia), 2.8 cm (7.0%) and 5.2 cm (13.0%); a research forest (Austria), 3.1 cm (10.5%) and 6.3 cm (21.2%); natural and plantation forests (Japan), 2.3 cm (10.5%); and, a university campus (Turkey), 2.3 cm (11.7%) [5,[22][23][24]. A previous study using the same methodology as used in this study reported an RMSE of 1.1 cm (6.2%) for a plantation forest in Canada [11].…”