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Soil salinity and sodicity in drylands: A review of causes, effects, monitoring, and restoration measures
Soil salinization and sodification are common processes that particularly characterize
drylands. These processes can be attributed either to natural conditions or anthropogenic …
drylands. These processes can be attributed either to natural conditions or anthropogenic …
[HTML][HTML] Soil health and its relationship with food security and human health to meet the sustainable development goals in India
BS Das, SP Wani, DK Benbi, S Muddu… - Soil Security, 2022 - Elsevier
Healthy soil is critical to human health and for achieving sustainable development goals
(SDGs). Although India attained self-sufficiency in food production, realising zero hunger …
(SDGs). Although India attained self-sufficiency in food production, realising zero hunger …
Exploring the potential of UAV hyperspectral image for estimating soil salinity: Effects of optimal band combination algorithm and random forest
C Zhu, J Ding, Z Zhang, Z Wang - … Acta Part A: Molecular and Biomolecular …, 2022 - Elsevier
Hyperspectral remote sensing by unmanned aerial vehicle (UAV) is an important technical
tool for rapid, accurate, and real-time monitoring of soil salinity in arid zone agroecosystems …
tool for rapid, accurate, and real-time monitoring of soil salinity in arid zone agroecosystems …
Remote data for map** and monitoring coastal phenomena and parameters: A systematic review
RM Cavalli - Remote Sensing, 2024 - mdpi.com
Since 1971, remote sensing techniques have been used to map and monitor phenomena
and parameters of the coastal zone. However, updated reviews have only considered one …
and parameters of the coastal zone. However, updated reviews have only considered one …
Current status and development trend of soil salinity monitoring research in China
Y Ma, N Tashpolat - Sustainability, 2023 - mdpi.com
Soil salinization is a resource and ecological problem that currently exists on a large scale in
all countries of the world. This problem is seriously restricting the development of agricultural …
all countries of the world. This problem is seriously restricting the development of agricultural …
Optimizing machine learning models for predicting soil pH and total P in intact soil profiles with visible and near-infrared reflectance (VNIR) spectroscopy
S Xu, Y Zhao, Y Wang - Computers and Electronics in Agriculture, 2024 - Elsevier
Abstract Machine learning (ML) models have recently been used in visible and near-infrared
reflectance (VNIR) spectroscopy applications. However, the predictive performance of ML …
reflectance (VNIR) spectroscopy applications. However, the predictive performance of ML …
[HTML][HTML] Simultaneous estimation of multiple soil properties under moist conditions using fractional-order derivative of vis-NIR spectra and deep learning
Y Liu, Y Lu, D Chen, W Zheng, Y Ma, X Pan - Geoderma, 2023 - Elsevier
The application of visible and near-infrared (vis-NIR) spectroscopy for predicting soil
properties presents a cost-effective and time-efficient approach for evaluating various soil …
properties presents a cost-effective and time-efficient approach for evaluating various soil …
[HTML][HTML] Assessment of soil salinity status under different land-use conditions in the semiarid region of Northeastern Brazil
Soil salinization and sodification, caused by inadequate land management, is one of the
main threats to the semiarid agroecosystems. It is essential to investigate saline levels under …
main threats to the semiarid agroecosystems. It is essential to investigate saline levels under …
[HTML][HTML] Improving soil organic matter estimation accuracy by combining optimal spectral preprocessing and feature selection methods based on pXRF and vis-NIR …
X Shi, J Song, H Wang, X Lv, Y Zhu, W Zhang, W Bu… - Geoderma, 2023 - Elsevier
Rapid and accurate estimation of soil organic matter (SOM) content is of great significance
for agricultural production and carbon stock estimation. Visible-near-infrared spectroscopy …
for agricultural production and carbon stock estimation. Visible-near-infrared spectroscopy …
HPO-empowered machine learning with multiple environment variables enables spatial prediction of soil heavy metals in coastal delta farmland of China
Y Song, D Zhan, Z He, W Li, W Duan, Z Yang… - … and Electronics in …, 2023 - Elsevier
Abstract Machine learning (ML) models have been widely used for predicting spatial
variability of soil heavy metals. However, it is impossible to explore the entire …
variability of soil heavy metals. However, it is impossible to explore the entire …