Assessment of remote sensing in measuring soil parameters for precision tillage

被引：1

作者：

Amanor, Ishmael Nartey ^{[1
,3
]}

Alarcon, Ricardo Ospina ^{[2
]}

Noguchi, Noboru ^{[2
]}

机构：

[1] Hokkaido Univ, Grad Sch Agr, Kita 9,Nishi 9,Kita Ku, Sapporo, Hokkaido 0608589, Japan

[2] Hokkaido Univ, Res Fac Agr, Kita 9,Nishi 9,Kita Ku, Sapporo, Hokkaido 0608589, Japan

[3] Cape Coast Tech Univ, Dept Mech Engn, Box DL 50, Cape Coast, Ghana

来源：

JOURNAL OF TERRAMECHANICS | 2024年 / 113卷

关键词：

Precision tillage; Soil compaction; Packing density; Remote sensing; Hyperspectral camera; DENSITY; SENSOR; GROWTH;

D O I：

10.1016/j.jterra.2024.100973

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Precision tillage (PT) is an innovative method that aims to take mechanical actions in the soil only where it is needed to curb the impact of heavy machinery usage on the soil. This research explores the use of remote sensing to measure relevant soil parameters to implement a PT strategy. This was achieved by combining traditional soil properties measurements and a non-contact approach based on taking hyperspectral camera (HSC) data in the field. Six methods were generated and divided into two sets to determine soil properties to make PT decisions. The first set includes mathematical functions that were generated from the ground true data (GTD). The second set includes functions that were generated from the remotely sensed HSC data and have a relationship with the methods in the first set. It was possible to tune the functions' parameters to increase the accuracy. In addition, prediction error categories set at 5 % intervals were used to select the best method. The results show that a tuned method based on the GTD has an overall error below 5 %, and a tuned method based on HSC data has an overall error below 10 %. (c) 2024 ISTVS. Published by Elsevier Ltd. All rights reserved.

引用

页数：12

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