[HTML][HTML] Machine learning and soil sciences: A review aided by machine learning tools

J Padarian, B Minasny, AB McBratney - Soil, 2020 - soil.copernicus.org
The application of machine learning (ML) techniques in various fields of science has
increased rapidly, especially in the last 10 years. The increasing availability of soil data that …

An overview and comparison of machine-learning techniques for classification purposes in digital soil map**

B Heung, HC Ho, J Zhang, A Knudby, CE Bulmer… - Geoderma, 2016 - Elsevier
Abstract Machine-learning is the automated process of uncovering patterns in large datasets
using computer-based statistical models, where a fitted model may then be used for …

Land suitability assessment and agricultural production sustainability using machine learning models

R Taghizadeh-Mehrjardi, K Nabiollahi, L Rasoli… - Agronomy, 2020 - mdpi.com
Land suitability assessment is essential for increasing production and planning a
sustainable agricultural system, but such information is commonly scarce in the semi-arid …

Pedology and digital soil map** (DSM)

Y Ma, B Minasny, BP Malone… - European Journal of …, 2019 - Wiley Online Library
Pedology focuses on understanding soil genesis in the field and includes soil classification
and map**. Digital soil map** (DSM) has evolved from traditional soil classification and …

Assessing the effects of slope gradient and land use change on soil quality degradation through digital map** of soil quality indices and soil loss rate

K Nabiollahi, F Golmohamadi, R Taghizadeh-Mehrjardi… - Geoderma, 2018 - Elsevier
Slope gradient and land use change are known to influence soil quality and the assessment
of soil quality is important in determining sustainable land-use and soil-management …

A comprehensive review on soil classification using deep learning and computer vision techniques

P Srivastava, A Shukla, A Bansal - Multimedia Tools and Applications, 2021 - Springer
Soil classification is one of the major affairs and emanating topics in a large number of
countries. The population of the world is rising at a majorly rapid pace and along with the …

Digital map** of soil organic carbon at multiple depths using different data mining techniques in Baneh region, Iran

R Taghizadeh-Mehrjardi, K Nabiollahi, R Kerry - Geoderma, 2016 - Elsevier
This study aimed to map SOC lateral, and vertical variations down to 1 m depth in a semi-
arid region in Kurdistan Province, Iran. Six data mining techniques namely; artificial neural …

Conventional and digital soil map** in Iran: Past, present, and future

M Zeraatpisheh, A Jafari, MB Bodaghabadi, S Ayoubi… - Catena, 2020 - Elsevier
Demand for accurate soil information is increasing for various applications. This paper
investigates the history of soil survey in Iran, particularly more recent developments in the …

Assessment of soil quality indices for salt-affected agricultural land in Kurdistan Province, Iran

K Nabiollahi, R Taghizadeh-Mehrjardi, R Kerry… - Ecological …, 2017 - Elsevier
Soil quality indices (SQIs) were an important tool for evaluating agro-ecosystems.
Salinization and alkalization are major environmental problems that have threatened …

Assessing agricultural salt-affected land using digital soil map** and hybridized random forests

K Nabiollahi, R Taghizadeh-Mehrjardi, A Shahabi… - Geoderma, 2021 - Elsevier
Salinization and alkalization are predominant environmental problem world-wide which their
accurate assessment is essential for determining appropriate ways to deal with land …