Contrastive-Learning-Based Time-Series Feature Representation for Parcel-Based Crop Mapping Using Incomplete Sentinel-2 Image Sequences

Contrastive-Learning-Based Time-Series Feature Representation for Parcel-Based Crop Mapping Using Incomplete Sentinel-2 Image Sequences

Parcel-based crop classification using multi-temporal satellite optical images plays a vital role in precision agriculture. However, optical image sequences may be incomplete due to the occlusion of clouds and shadows. Thus, exploring inherent time-series features to identify crop types from incompl...

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Bibliographic Details
Main Authors: Ya’nan Zhou, Yan Wang, Na’na Yan, Li Feng, Yuehong Chen, Tianjun Wu, Jianwei Gao, Xiwang Zhang, Weiwei Zhu
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Remote Sensing
Subjects:
crop mapping
feature representation
contrastive learning
incomplete time series
Sentinel-2 image
Online Access:https://www.mdpi.com/2072-4292/15/20/5009

Internet

https://www.mdpi.com/2072-4292/15/20/5009

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