AI and machine learning for soil analysis: an assessment of sustainable agricultural practices
Sustainable agricultural practices help to manage and use natural resources efficiently. Due
to global climate and geospatial land design, soil texture, soil–water content (SWC), and …
to global climate and geospatial land design, soil texture, soil–water content (SWC), and …
Monitoring changes in global soil organic carbon stocks from space
Soils are under threat globally, with declining soil productivity and soil health in many
places. As a key indicator of soil functioning, soil organic carbon (SOC) is crucial for …
places. As a key indicator of soil functioning, soil organic carbon (SOC) is crucial for …
A Systematic Review on Digital Soil Map** Approaches in Lowland Areas
OD Adeniyi, H Bature, M Mearker - Land, 2024 - mdpi.com
Digital soil map** (DSM) around the world is mostly conducted in areas with a certain
relief characterized by significant heterogeneities in soil-forming factors. However, lowland …
relief characterized by significant heterogeneities in soil-forming factors. However, lowland …
A high‐accuracy vegetation restoration potential map** model integrating similar habitat and machine learning
X Meng, H Pi, X Gao, P He, J Lei - Land Degradation & …, 2023 - Wiley Online Library
Vegetation restoration potential (VRP) map** provides important information for
ecosystem restoration planning. However, the inappropriate assumption of traditional …
ecosystem restoration planning. However, the inappropriate assumption of traditional …
Tree-based algorithms for spatial modeling of soil particle distribution in arid and semi-arid region
Accurate estimation of particle size distribution across a large area is crucial for proper soil
management and conservation, ensuring compatibility with capabilities and enabling better …
management and conservation, ensuring compatibility with capabilities and enabling better …
[HTML][HTML] Could airborne geophysical data be used to improve predictive modeling of agronomic soil properties in tropical hillslope area?
Airborne geophysical data (AGD) have great potential to represent soil-forming factors.
Because of that, the objective of this study was to evaluate the importance of AGD in …
Because of that, the objective of this study was to evaluate the importance of AGD in …
[HTML][HTML] A deep neural network for predicting soil texture using airborne radiometric data
The ternary nature of soil texture, defined by its proportions of clay, silt, and sand, makes it
challenging to predict through linear regression models from other soil attributes and …
challenging to predict through linear regression models from other soil attributes and …
Use of Airborne Radar Images and Machine Learning Algorithms to Map Soil Clay, Silt, and Sand Contents in Remote Areas under the Amazon Rainforest
Soil texture has a great influence on the physical–hydric and chemical behavior of soils. In
the Amazon regions, due to the presence of dense forest cover and limited access to roads …
the Amazon regions, due to the presence of dense forest cover and limited access to roads …
Digital map** of soil weathering using field geophysical sensor data coupled with covariates and machine learning
Understanding the weathering intensities can provide answers for environmental issues,
soil, and geoscience studies. Recently, geophysical approaches and machine learning …
soil, and geoscience studies. Recently, geophysical approaches and machine learning …
[PDF][PDF] A Systematic Review on Digital Soil Map** Approaches in Lowland Areas. Land 2024, 13, 379
OD Adeniyi, H Bature, M Mearker - 2024 - academia.edu
Digital soil map** (DSM) around the world is mostly conducted in areas with a certain
relief characterized by significant heterogeneities in soil-forming factors. However, lowland …
relief characterized by significant heterogeneities in soil-forming factors. However, lowland …