Conceptual design of an autonomous rover with ground penetrating radar : Application in characterizing soils using deep learning
Linna, Petri; Aaltonen, Toni; Halla, Antti; Grönman, Jere; Narra Girish, Nathaniel (2020-09-28)
Linna, Petri
Aaltonen, Toni
Halla, Antti
Grönman, Jere
Narra Girish, Nathaniel
Teoksen toimittaja(t)
Koricic, Marko
Skala, Karolj
Car, Zeljka
Cicin-Sain, Marina
Sruk, Vlado
Skvorc, Dejan
Ribaric, Slobodan
Jerbic, Bojan
Gros, Stjepan
Vrdoljak, Boris
Mauher, Mladen
Tijan, Edvard
Katulic, Tihomir
Pale, Predrag
Grbac, Tihana Galinac
Fijan, Nikola Filip
Boukalov, Adrian
Cisic, Dragan
Gradisnik, Vera
IEEE
28.09.2020
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202101191451
https://urn.fi/URN:NBN:fi:tuni-202101191451
Kuvaus
Peer reviewed
Tiivistelmä
In the pursuit to make agricultural production efficient, the earliest farmers used data in the form of notes of observations. In the current age of data,it has become easier to collect data over a wide spectrum of parameters. There are numerous sensing technologies for measuring processes and parameters over the field surface, typically mounted on satellites, aerial (drone), ground vehicle and static platforms. In the latest understanding, soil is gaining increasing attention and recognition for its significance in not only increasing productivity but also stabilizing the environment. However, characterizing soil in a field is not trivial, especially when required toaccess the deeper layers and quantifying the essential contents –water, nutrients and organic matter. This paper presents a short review of applications of ground penetrating radars (GPR) in measuring soil content and structure. The focusis ondeeplearning constructs that have been used for interpreting and establishing correlations. The review serves to inform design considerations for a planned autonomous rover that will be used for surveying field soils in the Satakunta region of Finland
Kokoelmat
- TUNICRIS-julkaisut [16726]