Crop Mapping Using Sentinel Full-Year Dual-Polarized SAR Data and a CPU-Optimized Convolutional Neural Network With Two Sampling Strategies

Crop Mapping Using Sentinel Full-Year Dual-Polarized SAR Data and a CPU-Optimized Convolutional Neural Network With Two Sampling Strategies

Although optical remote sensing can capture the Earth's environment with visible and infrared sensors, it is limited by weather conditions. Often, only a few sets of cloud-free optical imagery are available in cloudy regions, where many agricultural towns are located. On the other hand, r...

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Bibliographic Details
Main Authors: Shengjie Liu, Zhize Zhou, Huaxiang Ding, Yuanjun Zhong, Qian Shi
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural network (CNN)
crop mapping
multitemporal
radar remote sensing
sampling strategy
synthetic aperture radar (SAR)
Online Access:https://ieeexplore.ieee.org/document/9476986/

Internet

https://ieeexplore.ieee.org/document/9476986/

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