Estimating soil aggregate size distribution from images using pattern spectra

Bosilj, Petra, Gould, Iain, Duckett, Tom and Cielniak, Grzegorz (2020) Estimating soil aggregate size distribution from images using pattern spectra. Biosystems Engineering, 198 . pp. 63-77. ISSN 1537-5110

Full content URL: https://doi.org/10.1016/j.biosystemseng.2020.07.01...

Documents
Estimating soil aggregate size distribution from images using pattern spectra
Accepted Manuscript
[img] PDF
Estimating_soil_aggregate_size_distribution_using_pattern_spectra.pdf - Whole Document
Restricted to Repository staff only until 17 August 2021.

2MB
Item Type:Article
Item Status:Live Archive

Abstract

A method for quantifying aggregate size distribution from the images of soil samples is introduced. Knowledge of soil aggregate size distribution can help to inform soil management practices for the sustainable growth of crops. While current in-field approaches are mostly subjective, obtaining quantifiable results in a laboratory is labour- and time-intensive. Our goal is to develop an imaging technique for quantitative analysis of soil aggregate size distribution, which could provide the basis of a tool for rapid assessment of soil structure. The prediction accuracy of pattern spectra descriptors based on hierarchical representations from attribute morphology are analysed, as well as the impact of using images of different quality and scales. The method is able to handle greater sample complexity than the previous approaches, while working with smaller samples sizes that are easier to handle. The results show promise for size analysis of soils with larger structures, and minimal sample preparation, as typical of soil assessment in agriculture.

Keywords:pattern spectra, Component Trees, Soil Aggregate Analysis
Subjects:F Physical Sciences > F870 Soil Science
G Mathematical and Computer Sciences > G740 Computer Vision
D Veterinary Sciences, Agriculture and related subjects > D750 Soil as an Agricultural medium
Divisions:College of Science > Lincoln Institute for Agri-Food Technology
College of Science > School of Computer Science
ID Code:42179
Deposited On:28 Oct 2020 09:53

Repository Staff Only: item control page