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Empowering agrifood system with artificial intelligence: A survey of the progress, challenges and opportunities
With the world population rapidly increasing, transforming our agrifood systems to be more
productive, efficient, safe, and sustainable is crucial to mitigate potential food shortages …
productive, efficient, safe, and sustainable is crucial to mitigate potential food shortages …
Evaluating soil moisture content under maize coverage using UAV multimodal data by machine learning algorithms
Timely and accurate estimation of soil moisture content (SMC) is essential for precise
irrigation management at the farm scale. Unmanned aerial vehicle (UAV) remote sensing …
irrigation management at the farm scale. Unmanned aerial vehicle (UAV) remote sensing …
[HTML][HTML] Advanced technologies of soil moisture monitoring in precision agriculture
Facing the dual challenges of limited natural resources, particularly water, and increasing
demands for food security, the role of precision agriculture has become increasingly critical …
demands for food security, the role of precision agriculture has become increasingly critical …
Incremental learning for crop growth parameters estimation and nitrogen diagnosis from hyperspectral data
R Du, J Chen, Y **ang, Z Zhang, N Yang… - … and electronics in …, 2023 - Elsevier
Nitrogen is an essential nutrient in crop growth cycle and directly affects the photosynthesis
of crops. The leaf chlorophyll content (LCC) and leaf area index (LAI) are important for …
of crops. The leaf chlorophyll content (LCC) and leaf area index (LAI) are important for …
A survey of unmanned aerial vehicles and deep learning in precision agriculture
In the wake of significant advances in agronomy, biology, informatics, agricultural robots
(Agri-robots), and artificial intelligence, modern agriculture is transforming from labor …
(Agri-robots), and artificial intelligence, modern agriculture is transforming from labor …
Improving UAV hyperspectral monitoring accuracy of summer maize soil moisture content with an ensemble learning model fusing crop physiological spectral …
H Liu, J Chen, Y **ang, H Geng, X Yang, N Yang… - European Journal of …, 2024 - Elsevier
Soil moisture content (SMC) acquisition is vital for crop stress diagnosis and precision
irrigation. However, UAV remote sensing-based SMC monitoring usually suffers from low …
irrigation. However, UAV remote sensing-based SMC monitoring usually suffers from low …
[HTML][HTML] Integrating UAV hyperspectral data and radiative transfer model simulation to quantitatively estimate maize leaf and canopy nitrogen content
Crop nitrogen (N) content reflects crop nutrient status and plays an important role in
precision nutrient management. Accurate crop N content estimation from remote sensing …
precision nutrient management. Accurate crop N content estimation from remote sensing …
[PDF][PDF] Estimation of soil moisture for different crops using SAR polarimetric data
Soil moisture is an essential factor that influences agricultural productivity and hydrological
processes. Soil moisture estimation using field detection methods takes time and is …
processes. Soil moisture estimation using field detection methods takes time and is …
A critical review on multi-sensor and multi-platform remote sensing data fusion approaches: current status and prospects
Numerous remote sensing (RS) systems currently collect data about Earth and its
environments. However, each system provides limited data in terms of spatial resolution …
environments. However, each system provides limited data in terms of spatial resolution …
Hybrid inversion of radiative transfer models based on topographically corrected Landsat surface reflectance improves leaf area index and aboveground biomass …
S Peng, Z Wang, X Lu, X Liu - International Journal of Digital Earth, 2024 - Taylor & Francis
Accurate monitoring of the leaf area index (LAI) and aboveground biomass (AGB) using
remote sensing at a fine scale is crucial for understanding the spatial heterogeneity of …
remote sensing at a fine scale is crucial for understanding the spatial heterogeneity of …