SlashScan: An iOS application for real-time forest slash pile volume estimation and mapping
| Authors: | Heechan Jeong, Heesung Woo, Woodam Chung, Taejin Kim, Nathaniel Anderson |
| Year: | 2026 |
| Type: | Scientific Journal |
| Station: | Rocky Mountain Research Station |
| DOI: | https://doi.org/10.1016/j.foreco.2026.123776 |
| Source: | Forest Ecology and Management |
Abstract
Forest slash piles require effective management for site preparation and fire risk reduction. While pile burning remains a common disposal method, there is growing interest in utilizing these materials for energy and other bioproducts. Slash piles can serve as temporary carbon storage, and provide wildlife habitat, but they also contribute to surface fuel loads and increase site preparation costs if not properly utilized or disposed. Managing such low-value materials distributed across large forest landscapes poses logistical and economic challenges, especially when the volume and precise location are unknown. This study introduces SlashScan, a mobile application for iPhone and iPad that simultaneously estimates slash pile volume and generates location data in real time without additional equipment. The performance was validated by comparing volume estimates from 14 slash piles acquired using Unmanned Aerial Vehicle (UAV) based Light Detection and Ranging (LiDAR). The mean estimated volumes were 88.11 m³ ± 33.51 m³ for UAV-LiDAR and 92.43 m³ ± 39.18 m³ for SlashScan, with a mean difference of 4.31 m³ . A paired t-test indicated no statistically significant difference between the two methods (p > 0.05). Strong agreement was further demonstrated by high coefficient of determination (R² = 0.948), low root mean square error (RMSE = 10.64 m³), mean absolute error (MAE = 6.72 m³), and mean absolute percentage error (MAPE = 6.76%). These results demonstrate that SlashScan provides volume estimates comparable to those from UAV-LiDAR while offering substantial advantages in portability, cost, and operational simplicity. This study offers a practical tool for improving forest slash management where accessibility and realtime data acquisition are essential.