Accuracy of two LiDAR-based augmented reality apps in breast height diameter measurement

Accurate measurement of the diameter at the breast height (DBH) is essential in forestry-related science and practice, but its measurement is currently done by labor-intensive tools such as calipers or devices designed to measure the girth. With the development in light detection and ranging (LiDAR) and augmented reality (AR) technologies, and their integration in low-cost mobile platforms, affordable proximal measurement applications were released on the market. This study examines the accuracy in DBH measurement of Arboreal Forest (hereafter DA) and Measure (hereafter DM) apps, by taking as a reference the measurements done by an accurate forestry caliper (hereafter DC). A number of 615 trees were considered, of which 395 were broadleaved (DBH between 10 and 73 cm, averaging 39.73 ± 9.91 cm) and 220 were coniferous (DBH between 25 and 89 cm, averaging 52.47 ± 12.81 cm), and measurements were taken under sunny, cloudy and rainy weather. Comparison was done in terms of agreement (Bland and Altman's method), dependence (least square simple ordinary and regression through origin), correlation (Spearman's, Pearson's and Kendall's tests), and difference (mean absolute error - MAE, root mean squared error - RMSE, and bias - BIAS). Besides a close-to-perfect fit, strong association in data, and a good degree of agreement, the results indicated the presence of centimeter-level differences when comparing DM against DC (MAE = 0.715 cm, RMSE = 0.879 cm, BIAS = 0.333 cm) and DA against DC (MAE = 0.953 cm, RMSE = 1.246 cm, BIAS = -0.108 cm). When comparing DA against DM the differences were slightly higher (MAE = 1.175 cm, RMSE = 1.531 cm, BIAS = –0.446 cm). The magnitude in differences found is rather caused by the application used and not by the environmental conditions. Further studies may consider larger data samples to provide better estimates as well as checking the limits in measurement capabilities of these apps.