GRASS; land cover; landfill management; machine learning; multispectral; OBIA; supervised classification; UAV; Control and Systems Engineering; Information Systems; Aerospace Engineering; Computer Science Applications; Artificial Intelligence
Abstract :
[en] Earth observation technologies offer non-intrusive solutions for monitoring complex and risky sites, such as landfills. In particular, unmanned aerial vehicles (UAVs) offer the ability to acquire data at very high spatial resolution, with full control of the temporality required for the desired application. The versatility of UAVs, both in terms of flight characteristics and on-board sensors, makes it possible to generate relevant geodata for a wide range of landfill monitoring ac-tivities. This study aims to propose a robust tool and to provide data acquisition guidelines for the land cover mapping of complex sites using UAV multispectral imagery. For this purpose, the transferability of a state-of-the-art object-based image analysis open-source processing chain was assessed and its sensitivity to the segmentation approach, textural and contextual information, spectral and spatial resolution was tested over the landfill site of Hallembaye (Wallonia, Belgium). This study proposes a consistent open-source processing chain for the land cover mapping using UAV data with accuracies of at least 85%. It shows that low-cost red-green-blue standard sensors are sufficient to reach such accuracies and that spatial resolution of up to 10 cm can be adopted with limited impact on the performance of the processing chain. This study also results in the creation of a new operational service for the monitoring of the active landfill sites of Wallonia.
Disciplines :
Earth sciences & physical geography
Author, co-author :
Wyard, Coraline ; Université de Liège - ULiège > Département de géographie > Climatologie et Topoclimatologie ; Remote Sensing and Geodata Unit, Institut Scientifique de Service Public (ISSeP), Liège, Belgium
Beaumont, Benjamin ; Remote Sensing and Geodata Unit, Institut Scientifique de Service Public (ISSeP), Liège, Belgium
Hallot, Eric ; Université de Liège - ULiège > Département de géographie ; Remote Sensing and Geodata Unit, Institut Scientifique de Service Public (ISSeP), Liège, Belgium
Language :
English
Title :
UAV-Based Landfill Land Cover Mapping: Optimizing Data Acquisition and Open-Source Processing Protocols
ISSeP - Institut Scientifique de Service Public [BE]
Funding text :
Acknowledgments: The authors acknowledge ISSeP for funding this research. They would like to thank Julien Dumont and Fabian Stassen for performing the UAV flights and data acquisition, the Hallembaye landfill site managers for their interest and for opening the site to UAV flights, and Emilie Navette for its expertise of the site. The authors greatly thank the reviewers for their relevant comments which helped to improve this manuscript.This research was conducted in the framework of the “CETEO” project (https://www.issep.be/wp-content/uploads/Projet-CETEO.pdf; accessed on 23 March 2022), which was funded by the internal Moerman fund of Institut Scientifique de Service Public (ISSeP).
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