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RESEARCH ARTICLE

Combining multiple methods for automated soil delineation: from traditional to digital

Fellipe A. O. Mello https://orcid.org/0000-0002-0771-9080 A , José A. M. Demattê A * , André C. Dotto A , Karina P. P. Marques A , Danilo C. Mello B , Michele D. Menezes C , Sérgio H. G. Silva C and Nilton Curi C
+ Author Affiliations
- Author Affiliations

A Department of Soil Science, Luiz de Queiroz College of Agriculture, University of São Paulo, Pádua Dias Avenue, 11, Postal Box 09, Piracicaba, São Paulo 13416-900, Brazil.

B Department of Soil Science, Federal University of Viçosa, Peter Henry Rolfs Avenue, Viçosa, Minas Gerais 36570-900, Brazil.

C Department of Soil Science, Federal University of Lavras, Lavras, Minas Gerais 37200-900, Brazil.

* Correspondence to: jamdemat@usp.br

Handling Editor: Brendan Malone

Soil Research 61(1) 55-69 https://doi.org/10.1071/SR21067
Submitted: 22 October 2021  Accepted: 7 June 2022   Published: 11 July 2022

© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing

Abstract

Context: Soil maps are a fundamental tool for agriculture development and for land management planning. Digital soil mapping (DSM) consists of a group of techniques based on geotechnologies and statistics/geostatistics that helps soil specialists to map soil types and properties.

Aims: Four DSM strategies were applied in south-east Brazil. The goal was to visually delineate soil polygons with support of different strategies.

Methods: The delineation started with aerial photographs, followed by a bare soil image composition. Afterwards, it was added layers with landscape characterisation derived from digital terrain covariates and clustering analysis. Finally, digital clay content map from A and B horizons were used to produce a soil texture gradient raster (clay content increasing in depth).

Key results: The increasing number of polygons proved that the addition of covariates increased the detail level of the soil map, enhancing visualisation of the landscape variation, resulting on a map that substantially improved both national and state soil inventories.

Conclusions: We concluded that combining simple geotechnological tools might be of great utility for increasing detailed soil information proper for farmers and decision making.

Implications: Therefore, new soil information will be available for end users, supporting land management, food production sustainability, and soil conservation.

Keywords: aerial images, digital soil mapping, landscape compartments, landscape modelling, pedology, remote sensing, soil geography, soil mapping.


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