Soil moisture retrieval from remote sensing measurements: Current knowledge and directions for the future
Soil moisture (SM) is an essential parameter for understanding the interactions and
feedbacks between the atmosphere and the Earth's surface through energy and water …
feedbacks between the atmosphere and the Earth's surface through energy and water …
Conventional and digital soil mapping in Iran: Past, present, and future
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 …
investigates the history of soil survey in Iran, particularly more recent developments in the …
Assessing machine learning-based prediction under different agricultural practices for digital mapping of soil organic carbon and available phosphorus
Predicting soil chemical properties such as soil organic carbon (SOC) and available
phosphorus (Ava-P) content is critical in areas where different land uses exist. The …
phosphorus (Ava-P) content is critical in areas where different land uses exist. The …
Integration of Sentinel-1/2 and topographic attributes to predict the spatial distribution of soil texture fractions in some agricultural soils of western Iran
This research was intended to examine the use of radar data obtained from Sentinel-1
imagery with different combinations of topographic attributes and multispectral data to …
imagery with different combinations of topographic attributes and multispectral data to …
Spatial prediction of soil surface properties in an arid region using synthetic soil image and machine learning
Abstract Evaluation of spatial variability and mapping of soil properties is critical for
sustainable agricultural production in arid lands. The main objectives of the present study …
sustainable agricultural production in arid lands. The main objectives of the present study …
Digital mapping for soil texture class prediction in northwestern Türkiye by different machine learning algorithms
Soil texture classes (STCs) influence the physical, chemical and biological properties of the
soil, and accurate spatial predictions of STCs are essential for agro-ecological modeling …
soil, and accurate spatial predictions of STCs are essential for agro-ecological modeling …
Bio-inspired hybridization of artificial neural networks: An application for mapping the spatial distribution of soil texture fractions
Soil texture and particle size fractions (PSFs) are a critical characteristic of soil that
influences most physical, chemical, and biological properties of soil; furthermore, reliable …
influences most physical, chemical, and biological properties of soil; furthermore, reliable …
Comparative analysis of random forest, exploratory regression, and structural equation modeling for screening key environmental variables in evaluating rangeland …
N Kaveh, A Ebrahimi, E Asadi - Ecological Informatics, 2023 - Elsevier
Abstract Above-Ground Biomass (AGB) is a key indicator of rangeland health and
productivity, as well as ecosystem conservation and resource sustainability. Estimating …
productivity, as well as ecosystem conservation and resource sustainability. Estimating …
Monitoring properties of the salt-affected soils by multivariate analysis of the visible and near-infrared hyperspectral data
The study aimed to estimate the properties of the salt-affected soils (SAS) using
hyperspectral remote sensing. The study was carried out on typical SAS from 372 locations …
hyperspectral remote sensing. The study was carried out on typical SAS from 372 locations …
Different approaches to estimating soil properties for digital soil map integrated with machine learning and remote sensing techniques in a sub-humid ecosystem
Today, data mining has become a relevant topic in digital soil mapping. In this current study,
prediction of some soil properties and their spatial distribution were examined by machine …
prediction of some soil properties and their spatial distribution were examined by machine …