Towards automation of in-season crop type mapping using spatiotemporal crop information and remote sensing data
CONTEXT Mapping crop types from satellite images is a promising application in
agricultural systems. However, it is a challenge to automate in-season crop type mapping …
agricultural systems. However, it is a challenge to automate in-season crop type mapping …
A systematic review of the use of Deep Learning in Satellite Imagery for Agriculture
Agricultural research is essential for increasing food production to meet the needs of a
rapidly growing human population. Collecting large quantities of agricultural data helps to …
rapidly growing human population. Collecting large quantities of agricultural data helps to …
Rapid early-season maize mapping without crop labels
Maize (Zea mays), the second most-produced crop worldwide, serves as the cornerstone for
global food security and human livelihood. Early-season maize mapping benefits maize …
global food security and human livelihood. Early-season maize mapping benefits maize …
Early-and in-season crop type mapping without current-year ground truth: Generating labels from historical information via a topology-based approach
Land cover classification in remote sensing is often faced with the challenge of limited
ground truth labels. Incorporating historical ground information has the potential to …
ground truth labels. Incorporating historical ground information has the potential to …
[HTML][HTML] Mapping corn dynamics using limited but representative samples with adaptive strategies
Mapping the corn dynamics at a large scale and multiple years is essential for global food
security. Traditional mapping approaches by collecting training samples from field surveys …
security. Traditional mapping approaches by collecting training samples from field surveys …
Automated in-season mapping of winter wheat in China with training data generation and model transfer
Accurate and timely information on winter wheat spatial distribution is essential for food
security and environmental sustainability. However, high-quality nation-wide winter wheat …
security and environmental sustainability. However, high-quality nation-wide winter wheat …
Improvement Of In-season Crop Mapping For Illinois Cropland Using Multiple Machine Learning Classifiers
Large-area crop type identification and mapping for cropland are intensively crucial for
agriculture research, yield forecast, and disaster management. The United States …
agriculture research, yield forecast, and disaster management. The United States …
The effects of winter cover crops on maize yield and crop performance in semiarid conditions—Artificial neural network approach
Maize is the most widespread and, along with wheat, the most important staple crop in the
Republic of Serbia, which is of great significance for ensuring national food security. With the …
Republic of Serbia, which is of great significance for ensuring national food security. With the …
In-season crop type identification using optimal feature knowledge graph
Early or in-season crop type mapping using remote sensing data is important for crop
managements to maximize crop yield. Existing remote sensing-based approaches in the …
managements to maximize crop yield. Existing remote sensing-based approaches in the …
Classifying crop types using two generations of hyperspectral sensors (Hyperion and DESIS) with machine learning on the cloud
I Aneece, PS Thenkabail - Remote Sensing, 2021 - mdpi.com
Advances in spaceborne hyperspectral (HS) remote sensing, cloud-computing, and
machine learning can help measure, model, map and monitor agricultural crops to address …
machine learning can help measure, model, map and monitor agricultural crops to address …