An automated sample generation method by integrating phenology domain optical-SAR features in rice cropping pattern mapping

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成果类型：

期刊论文

作者：

Yang, Jingya;Hu, Qiong;Li, Wenjuan;Song, Qian;Cai, Zhiwen;...

通讯作者：

Wu, WB;Hu, Q

作者机构：

[Wu, WB; Li, Wenjuan; Song, Qian; Wu, Wenbin; Yang, Jingya] Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, State Key Lab Efficient Utilizat Arid & Semiarid A, Beijing 100081, Peoples R China.

[Li, Wenjuan; Song, Qian; Wu, Wenbin; Yang, Jingya] Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Key Lab Agr Remote Sensing, Minist Agr & Rural Affairs, Beijing 100081, Peoples R China.

[Hu, Q; Hu, Qiong] Cent China Normal Univ, Coll Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.

[Cai, Zhiwen] Huazhong Agr Univ, Coll Resources & Environm, Wuhan 430070, Peoples R China.

[Zhang, Xinyu; Wei, Haodong] Huazhong Agr Univ, Macro Agr Res Inst, Coll Plant Sci & Technol, Wuhan 430070, Peoples R China.

通讯机构：

[Wu, WB ; Hu, Q ] C

Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, State Key Lab Efficient Utilizat Arid & Semiarid A, Beijing 100081, Peoples R China.

Cent China Normal Univ, Coll Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.

语种：

英文

关键词：

Automatic sample generation;Rice cropping pattern mapping;Sentinel-1/2;Phenological feature;Unsupervised clustering

期刊：

Remote Sensing of Environment

ISSN：

0034-4257

年：

2024

卷：

314

页码：

114387

DOI：

10.1016/j.rse.2024.114387

基金类别：

CRediT authorship contribution statement Jingya Yang: Writing – original draft, Software, Methodology, Formal analysis, Conceptualization. Qiong Hu: Writing – review & editing, Supervision, Methodology, acquisition, Conceptualization. Wenjuan Li: Writing – review & editing, Visualization, Validation. Qian Song: Writing – review & editing, Validation. Zhiwen Cai: Writing – review & editing, Methodology, Formal analysis. Xinyu Zhang: Formal analysis, Data curation. Haodong Wei: Writing – review & editing, Validation, Formal

机构署名：

本校为通讯机构

院系归属：

城市与环境科学学院

摘要：

Accurate spatio-temporal information on rice cropping patterns is vital for predicting grain production, managing water resource and assessing greenhouse gas emissions. However, current automated mapping of rice cropping patterns at regional scale is heavily constrained by insufficient training samples and frequent cloudy weathers in major rice-producing areas. To tackle this challenge, we proposed a Phenology domain Optical-SAR feature inTegration method to Automatically generate single (SC-Rice) and double cropping Rice (DC-Rice) sample (POSTAR) for efficient and refined rice mapping. POSTAR...

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An automated sample generation method by integrating phenology domain optical-SAR features in rice cropping pattern mapping

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