In-Season Automated Mapping of Xinjiang Cotton Based on Cumulative Spectral and Phenological Characteristics

In-Season Automated Mapping of Xinjiang Cotton Based on Cumulative Spectral and Phenological Characteristics

Obtaining timely, accurate, and automated data on the spatial distribution and planting area of cotton is crucial for production management and informed trade decision-making. In this regard, remote sensing technologies are important and effective means. Methods based on machine learning, and deep l...

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Bibliographic Details
Main Authors: Yongsheng Huang, Yaozhong Pan, Yu Zhu, Xiufang Zhu, Xingsheng Xia, Qiong Chen, Jufang Hu, Hongyan Che, Xuechang Zheng, Lingang Wang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Automatic mapping
cotton identification
cumulative spectral and phenological (CSP) characteristics
Otsu–Sauvola
Sentinel-2 time series
Online Access:https://ieeexplore.ieee.org/document/10827816/
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