[HTML][HTML] Remote sensing of soil degradation: Progress and perspective

J Wang, J Zhen, W Hu, S Chen, I Lizaga… - International Soil and …, 2023 - Elsevier
Soils constitute one of the most critical natural resources and maintaining their health is vital
for agricultural development and ecological sustainability, providing many essential …

Soil inorganic carbon, the other and equally important soil carbon pool: distribution, controlling factors, and the impact of climate change

A Sharififar, B Minasny, D Arrouays, L Boulonne… - Advances in …, 2023 - Elsevier
Soil inorganic carbon (SIC) contributes to up to half of the terrestrial C stock and is especially
significant in arid and semi-arid environments, yet has not been explored as much as soil …

A mobile-based system for maize plant leaf disease detection and classification using deep learning

F Khan, N Zafar, MN Tahir, M Aqib, H Waheed… - Frontiers in Plant …, 2023 - frontiersin.org
Artificial Intelligence has been used for many applications such as medical, communication,
object detection, and object tracking. Maize crop, which is the major crop in the world, is …

Digital map** of soil pH and carbonates at the European scale using environmental variables and machine learning

Q Lu, S Tian, L Wei - Science of the Total Environment, 2023 - Elsevier
Soil pH and carbonates (CaCO 3) are important indicators of soil chemistry and fertility, and
the prediction of their spatial distribution is critical for the agronomic and environmental …

[HTML][HTML] Exploring the capability of Gaofen-5 hyperspectral data for assessing soil salinity risks

X Ge, J Ding, D Teng, B **
B Kasraei, MG Schmidt, J Zhang, CE Bulmer… - Geoderma, 2024 - Elsevier
A common practice in digital soil map** (DSM) is to incorporate many environmental
covariates into a machine-learning algorithm to predict the spatial patterns of soil attributes …

Predictive performance of machine learning model with varying sampling designs, sample sizes, and spatial extents

A Bouasria, Y Bouslihim, S Gupta… - Ecological …, 2023 - Elsevier
Using machine learning and earth observation data to capture real-world variability in
spatial predictive map** depends on sample size, design, and spatial extent …

[HTML][HTML] Improving model parsimony and accuracy by modified greedy feature selection in digital soil map**

X Zhang, S Chen, J Xue, N Wang, Y **ao, Q Chen… - Geoderma, 2023 - Elsevier
In the context of increasing soil degradation worldwide, spatially explicit soil information is
urgently needed to support decision-making for sustaining limited soil resources. Digital soil …

[HTML][HTML] The role of remote sensing data and methods in a modern approach to fertilization in precision agriculture

D Radočaj, M Jurišić, M Gašparović - Remote Sensing, 2022 - mdpi.com
The precision fertilization system is the basis for upgrading conventional intensive
agricultural production, while achieving both high and quality yields and minimizing the …