[HTML][HTML] Advances in Earth observation and machine learning for quantifying blue carbon
Blue carbon ecosystems (mangroves, seagrasses and saltmarshes) are highly productive
coastal habitats, and are considered some of the most carbon-dense ecosystems on the …
coastal habitats, and are considered some of the most carbon-dense ecosystems on the …
Artificial intelligence-based decision support systems in smart agriculture: Bibliometric analysis for operational insights and future directions
As the world population is expected to touch 9.73 billion by 2050, according to the Food and
Agriculture Organization (FAO), the demand for agricultural needs is increasing …
Agriculture Organization (FAO), the demand for agricultural needs is increasing …
A low-cost approach for soil moisture prediction using multi-sensor data and machine learning algorithm
A high-resolution soil moisture prediction method has recently gained its importance in
various fields such as forestry, agricultural and land management. However, accurate …
various fields such as forestry, agricultural and land management. However, accurate …
[Retracted] Multisensor Data and Cross‐Validation Technique for Merging Temporal Images for the Agricultural Performance Monitoring System
VKS Maddala, K Jayarajan, M Braveen… - Journal of Food …, 2022 - Wiley Online Library
Many approaches for crop yield prediction were analyzed by countries using remote sensing
data, but the information obtained was less successful due to insufficient data gathered due …
data, but the information obtained was less successful due to insufficient data gathered due …
Assessing machine learning-based prediction under different agricultural practices for digital map** 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 …
Remote estimates of soil organic carbon using multi-temporal synthetic images and the probability hybrid model
Soil organic carbon (SOC) plays a key role in soil function, ecosystem services, and the
global carbon cycle. Digital SOC map** is essential for agricultural production …
global carbon cycle. Digital SOC map** is essential for agricultural production …
Application of deep learning models to detect coastlines and shorelines
Identifying and monitoring coastlines and shorelines play an important role in coastal
erosion assessment around the world. The application of deep learning models was used in …
erosion assessment around the world. The application of deep learning models was used in …
A review on digital map** of soil carbon in cropland: progress, challenge, and prospect
Cropland soil carbon not only serves food security but also contributes to the stability of the
terrestrial ecosystem carbon pool due to the strong interconnection with atmospheric carbon …
terrestrial ecosystem carbon pool due to the strong interconnection with atmospheric carbon …
Map** the soil C: N ratio at the European scale by combining multi-year Sentinel radar and optical data via cloud computing
Spatial information on the soil carbon-to-nitrogen (C: N) ratio is essential for sustainable soil
use and management. The unprecedented availability of Sentinel optical and radar data on …
use and management. The unprecedented availability of Sentinel optical and radar data on …
MAE-NIR: A masked autoencoder that enhances near-infrared spectral data to predict soil properties
Soil available nutrients are crucial for promoting crop growth, and controlling their content is
essential for increasing yield, promoting smart agriculture, and protecting the environment …
essential for increasing yield, promoting smart agriculture, and protecting the environment …