A Trunk Diameter Estimation Mobile App for the Masses: Extended version

09 January 2024, Version 2
This content is an early or alternative research output and has not been peer-reviewed by Cambridge University Press at the time of posting.

Abstract

Forest inventories can monitor changes in forest carbon sinks and assess forest biodiversity, which is crucial for studying the role of forests in responding to climate change. In recent years, methods for implementing parts of forest surveys on smartphones have often only been supported on specialized devices or a limited number of models. Most methods also assume a large spacing between trees and unoccluded trunks, and hence are unable to cope with realistic forest environments. We present an intuitive mobile application that can run on most common Android devices and estimate tree diameter in near real-time from a single image capture. We collected 154 samples in three countries across varying latitudes, testing our app in challenging conditions including occlusion, leaning trees, and irregular shapes. Our algorithm has a MAE of 2.31 cm and an RMSE of 3.16 cm. In addition to ensuring measurement accuracy, diameter measurement using our app is approximately 5 times faster than traditional manual surveying. Our research offers a low-cost, accurate solution for rapid trunk diameter measurement, expanding its applicability to a wider range of smartphone models and field scenarios.

Keywords

Trunk Diameter Measurement
ARCore
Mobile Phone
Neural Network
Forest Inventory
Carbon Estimation

Supplementary weblinks

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