Agricultural soils provide a variety of ecological services, including nutrient cycling,water purification and storage, carbon sequestration, and flood protection. Soil Surface Roughness (SSR)represents a key parameter for evaluating the terrain quality structure, especially in the layers beneaththe usual primary tillage depth, and therefore its estimation has been widely investigated over the yearsin many fields of science and engineering. This paper proposes the adoption of an innovative sensingapproach that relies on contactless measurements provided by a depth camera in contrast to traditionalcontact measurements such as pin meter and roller chain. In addition, novel features are investigated toachieve a complete statistical description of the SSR with the least number of parameters. The proposedmethods are validated in an experimental campaign performed on a vineyard plot. This research could beuseful for many applications, including soil erosion prediction models, autonomous vehicle navigation inrural and agricultural settings, and controlled traffic farming.

Novel measurements and features for the characterization of soil surface roughness

Marcella Biddoccu;Eugenio Cavallo;Annalisa Milella;
2022

Abstract

Agricultural soils provide a variety of ecological services, including nutrient cycling,water purification and storage, carbon sequestration, and flood protection. Soil Surface Roughness (SSR)represents a key parameter for evaluating the terrain quality structure, especially in the layers beneaththe usual primary tillage depth, and therefore its estimation has been widely investigated over the yearsin many fields of science and engineering. This paper proposes the adoption of an innovative sensingapproach that relies on contactless measurements provided by a depth camera in contrast to traditionalcontact measurements such as pin meter and roller chain. In addition, novel features are investigated toachieve a complete statistical description of the SSR with the least number of parameters. The proposedmethods are validated in an experimental campaign performed on a vineyard plot. This research could beuseful for many applications, including soil erosion prediction models, autonomous vehicle navigation inrural and agricultural settings, and controlled traffic farming.
2022
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA) Sede Secondaria Bari
Istituto di Scienze e Tecnologie per l'Energia e la Mobilità Sostenibili - STEMS
Soil surface roughness, vision-based sensing, environmental preservation and monitoring, precision agriculture, intelligent vehicles, agricultural robotic
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/413772
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