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Title: | Mapping of Potential Fuel Regions Using Uncrewed Aerial Vehicles for Wildfire Prevention | Authors: | Andrada, Maria Eduarda Russell, David Arevalo-Ramirez, Tito Kuang, Winnie Kantor, George Yandun, Francisco |
Keywords: | semantic mapping; simultaneous localization and mapping (SLAM); LiDAR; forest inventory; autonomous drones; forest monitoring; remote sensing; flammable material detection; vegetation classification | Issue Date: | 2023 | Publisher: | MDPI | Project: | CMU Portugal Affiliated Ph.D. grant (ref. PRT/BD/ 152194/2021) from the Portuguese Foundation for Science and Technology (FCT) Project of the Central Portugal Region and cofunded by the program Portugal 2020, under the reference CENTRO-01-0247-FEDER-045931 |
Serial title, monograph or event: | Forests | Volume: | 14 | Issue: | 8 | Abstract: | This paper presents a comprehensive forest mapping system using a customized drone payload equipped with Light Detection and Ranging (LiDAR), cameras, a Global Navigation Satellite System (GNSS), and Inertial Measurement Unit (IMU) sensors. The goal is to develop an efficient solution for collecting accurate forest data in dynamic environments and to highlight potential wildfire regions of interest to support precise forest management and conservation on the ground. Our paper provides a detailed description of the hardware and software components of the system, covering sensor synchronization, data acquisition, and processing. The overall system implements simultaneous localization and mapping (SLAM) techniques, particularly Fast LiDAR Inertial Odometry with Scan Context (FASTLIO-SC), and LiDAR Inertial Odometry Smoothing and Mapping (LIOSAM), for accurate odometry estimation and map generation. We also integrate a fuel mapping representation based on one of the models, used by the United States Secretary of Agriculture (USDA) to classify fire behavior, into the system using semantic segmentation, LiDAR camera registration, and odometry as inputs. Real-time representation of fuel properties is achieved through a lightweight map data structure at 4 Hz. The research results demonstrate the effectiveness and reliability of the proposed system and show that it can provide accurate forest data collection, accurate pose estimation, and comprehensive fuel mapping with precision values for the main segmented classes above 85%. Qualitative evaluations suggest the system’s capabilities and highlight its potential to improve forest management and conservation efforts. In summary, this study presents a versatile forest mapping system that provides accurate forest data for effective management. | URI: | https://hdl.handle.net/10316/112158 | ISSN: | 1999-4907 | DOI: | 10.3390/f14081601 | Rights: | openAccess |
Appears in Collections: | I&D ISR - Artigos em Revistas Internacionais |
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Mapping-of-Potential-Fuel-Regions-Using-Uncrewed-Aerial-Vehicles-for-Wildfire-PreventionForests.pdf | 46.24 MB | Adobe PDF | View/Open |
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