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Digital map** of GlobalSoilMap soil properties at a broad scale: A review
Soils are essential for supporting food production and providing ecosystem services but are
under pressure due to population growth, higher food demand, and land use competition …
under pressure due to population growth, higher food demand, and land use competition …
Integrating active and passive remote sensing data for map** soil salinity using machine learning and feature selection approaches in arid regions
The prevention of soil salinization and managing agricultural irrigation depend greatly on
accurately estimating soil salinity. Although the long-standing laboratory method of …
accurately estimating soil salinity. Although the long-standing laboratory method of …
Spatial prediction of soil aggregate stability and soil organic carbon in aggregate fractions using machine learning algorithms and environmental variables
Abstract Knowledge about the spatial variability of soil aggregate stability indices, soil
organic carbon (SOC) in various aggregate sizes, and aggregation across the landscape is …
organic carbon (SOC) in various aggregate sizes, and aggregation across the landscape is …
[HTML][HTML] Advancements and Perspective in the Quantitative Assessment of Soil Salinity Utilizing Remote Sensing and Machine Learning Algorithms: A Review
F Wang, L Han, L Liu, C Bai, J Ao, H Hu, R Li, X Li… - Remote Sensing, 2024 - mdpi.com
Soil salinization is a significant global ecological issue that leads to soil degradation and is
recognized as one of the primary factors hindering the sustainable development of irrigated …
recognized as one of the primary factors hindering the sustainable development of irrigated …
Incorporating machine learning models and remote sensing to assess the spatial distribution of saturated hydraulic conductivity in a light-textured soil
Saturated soil hydraulic conductivity (K sat) is a key component in hydrogeology and water
management. This study aimed at evaluating popular tree-based machine learning …
management. This study aimed at evaluating popular tree-based machine learning …
Spectral prediction of soil salinity and alkalinity indicators using visible, near-, and mid-infrared spectroscopy
Drought and the impacts of climate change have led to an escalation in soil salinity and
alkalinity across various regions worldwide, including Iran. The Chahardowli Plain in …
alkalinity across various regions worldwide, including Iran. The Chahardowli Plain in …
Spatiotemporal variations of soil salinization in China's West Songnen Plain
Preventing soil salinization and improving soil productivity play vital roles in achieving the
Sustainable Development Goals (SDGs), the premise of which is understanding the …
Sustainable Development Goals (SDGs), the premise of which is understanding the …
A longitudinal analysis of soil salinity changes using remotely sensed imageries
Soil salinization threatens agricultural productivity, leading to desertification and land
degradation. Given the challenges of conducting labor-intensive and expensive field studies …
degradation. Given the challenges of conducting labor-intensive and expensive field studies …
A framework for determining the total salt content of soil profiles using time-series Sentinel-2 images and a random forest-temporal convolution network
Soil salinization causes a deterioration in soil health and threatens crop growth. Rapid
identification of salinization in farmlands is of great significance to improve soil functions and …
identification of salinization in farmlands is of great significance to improve soil functions and …
[HTML][HTML] Assessment of soil salinity using explainable machine learning methods and Landsat 8 images
The aim of this study is to comparatively analyze the performance of machine learning (ML)
algorithms for modeling soil salinity using field-based electrical conductivity (EC) data and …
algorithms for modeling soil salinity using field-based electrical conductivity (EC) data and …