Estimating Tree Position, Diameter at Breast Height, and Tree Height in Real-Time Using a Mobile Phone with RGB-D SLAM

Tauheed Khan,Chaoyong Shen,Sajjad Saeed,Zhongke Feng,Abdul Mannan,Yongxiang Fan

doi:10.3390/rs10111845

Abstract

Accurate estimation of tree position, diameter at breast height (DBH), and tree height measurements is an important task in forest inventory. Mobile Laser Scanning (MLS) is an important solution. However, the poor global navigation satellite system (GNSS) coverage under the canopy makes the MLS system unable to provide globally-consistent point cloud data, and thus, it cannot accurately estimate the forest attributes. SLAM could be an alternative for solutions dependent on GNSS. In this paper, a mobile phone with RGB-D SLAM was used to estimate tree position, DBH, and tree height in real-time. The main aims of this paper include (1) designing an algorithm to estimate the DBH and position of the tree using the point cloud from the time-of-flight (TOF) camera and camera pose; (2) designing an algorithm to measure tree height using the perspective projection principle of a camera and the camera pose; and (3) showing the measurement results to the observer using augmented reality (AR) technology to allow the observer to intuitively judge the accuracy of the measurement results and re-estimate the measurement results if needed. The device was tested in nine square plots with 12 m sides. The tree position estimations were unbiased and had a root mean square error (RMSE) of 0.12 m in both the x-axis and y-axis directions; the DBH estimations had a 0.33 cm (1.78%) BIAS and a 1.26 cm (6.39%) root mean square error (RMSE); the tree height estimations had a 0.15 m (1.08%) BIAS and a 1.11 m (7.43%) RMSE. The results showed that the mobile phone with RGB-D SLAM is a potential tool for obtaining accurate measurements of tree position, DBH, and tree height.

Highlights

Forest ecosystems are considered important for the survival of both animals and human beings because of their environmental and socio-economic benefits
This paper aims to estimate forest attributes in real-time in a forest inventory using a mobile phone with RGB-D Simultaneous localization and mapping (SLAM)
The method has been widely studied; Reference [34] extracted diameter at breast height (DBH) values by fitting circles to the point cloud at breast height using three different algorithms (Lemen, Pratt and Taubin), and the results showed that the BIAS value was approximately −0.12 to 0.07 cm and the root mean square error (RMSE) was 1.47~2.43 cm in single scan mode, while in merged scan mode, the BIAS was approximately −0.32 to 0 cm, and the RMSE was 0.66~1.21 cm

Summary

Introduction

Forest ecosystems are considered important for the survival of both animals and human beings because of their environmental and socio-economic benefits They provide services such as soil and water conservation, carbon storage, climate regulation, and biodiversity, and provide food, wood, and energy [1,2,3]. Forest inventory primarily involves the collection of forest resource information, which aims to provide accurate estimates of the forest characteristics including the wood volume, biomass, or species diversity within the region of interest [5]. These attributes are precisely estimated by models constructed using tree species, diameter at breast height (DBH), and tree height [6]. The conventional instruments used to measure these properties are calipers and clinometers for the DBH and tree heights, respectively [6,7]

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Conclusion