Remote-sensing data and deep-learning techniques in crop map** and yield prediction: A systematic review

A Joshi, B Pradhan, S Gite, S Chakraborty - Remote Sensing, 2023 - mdpi.com
Reliable and timely crop-yield prediction and crop map** are crucial for food security and
decision making in the food industry and in agro-environmental management. The global …

Time-series pattern recognition in smart manufacturing systems: A literature review and ontology

MA Farahani, MR McCormick, R Gianinny… - Journal of Manufacturing …, 2023 - Elsevier
Since the inception of Industry 4.0 in 2012, emerging technologies have enabled the
acquisition of vast amounts of data from diverse sources such as machine tools, robust and …

[HTML][HTML] A robust index to extract paddy fields in cloudy regions from SAR time series

S Xu, X Zhu, J Chen, X Zhu, M Duan, B Qiu… - Remote Sensing of …, 2023 - Elsevier
Timely and accurate map** of paddy rice cultivation is needed for maintaining sustainable
rice production, ensuring food security, and monitoring water usage. Synthetic Aperture …

[HTML][HTML] Application of deep learning in multitemporal remote sensing image classification

X Cheng, Y Sun, W Zhang, Y Wang, X Cao, Y Wang - Remote Sensing, 2023 - mdpi.com
The rapid advancement of remote sensing technology has significantly enhanced the
temporal resolution of remote sensing data. Multitemporal remote sensing image …

[HTML][HTML] Map** corn dynamics using limited but representative samples with adaptive strategies

Y Wen, X Li, H Mu, L Zhong, H Chen, Y Zeng… - ISPRS Journal of …, 2022 - Elsevier
Map** the corn dynamics at a large scale and multiple years is essential for global food
security. Traditional map** approaches by collecting training samples from field surveys …

20 m Annual Paddy Rice Map for Mainland Southeast Asia Using Sentinel-1 SAR Data

C Sun, H Zhang, L Xu, J Ge, J Jiang… - Earth System Science …, 2022 - essd.copernicus.org
Over 90% of the world's rice is produced in the Asia-Pacific Region. Synthetic aperture radar
(SAR) enables all-day and all-weather observations of rice distribution in tropical and …

Review of synthetic aperture radar with deep learning in agricultural applications

MGZ Hashemi, E Jalilvand, H Alemohammad… - ISPRS Journal of …, 2024 - Elsevier
Abstract Synthetic Aperture Radar (SAR) observations, valued for their consistent acquisition
schedule and not being affected by cloud cover and variations between day and night, have …

[HTML][HTML] Transferable deep learning model based on the phenological matching principle for map** crop extent

S Ge, J Zhang, Y Pan, Z Yang, S Zhu - International Journal of Applied …, 2021 - Elsevier
Accurate and timely crop map** is essential for global food security assessments;
however, conventional crop map** models are usually applicable to specific spatial or …