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Review of paddy rice mapping with remote sensing technology

  • role： First author第一作者
  • Affiliation：

    Hubei Provincial Key Laboratory of Environment and Disaster Monitoring and Assessment, Institute of Precision Measurement Science and Technology Innovation, Chinese Academy of Sciences, Wuhan 430077

    University of Chinese Academy of Sciences, Beijing 100049

  • Email：gaoxinyi211@mails.ucas.ac.cn
  • Introduction：高心怡，研究方向为农业遥感。E-mail： gaoxinyi211@mails.ucas.ac.cn
GAO Xinyi12,  
  • role： Corresponding author通信作者
  • Affiliation：

    Hubei Provincial Key Laboratory of Environment and Disaster Monitoring and Assessment, Institute of Precision Measurement Science and Technology Innovation, Chinese Academy of Sciences, Wuhan 430077

  • Email：chihong@whigg.ac.cn
  • Introduction：池泓，研究方向为生态环境遥感。E-mail： chihong@whigg.ac.cn
CHI Hong1*,  
  • Affiliation：

    Hubei Provincial Key Laboratory of Environment and Disaster Monitoring and Assessment, Institute of Precision Measurement Science and Technology Innovation, Chinese Academy of Sciences, Wuhan 430077

HUANG Jinliang1,  
  • Affiliation：

    Hubei Provincial Key Laboratory of Environment and Disaster Monitoring and Assessment, Institute of Precision Measurement Science and Technology Innovation, Chinese Academy of Sciences, Wuhan 430077

LING Feng1,  
  • Affiliation：

    Hubei Provincial Key Laboratory of Environment and Disaster Monitoring and Assessment, Institute of Precision Measurement Science and Technology Innovation, Chinese Academy of Sciences, Wuhan 430077

    University of Chinese Academy of Sciences, Beijing 100049

HAN Yifei12,  
  • Affiliation：

    Hubei Provincial Key Laboratory of Environment and Disaster Monitoring and Assessment, Institute of Precision Measurement Science and Technology Innovation, Chinese Academy of Sciences, Wuhan 430077

    University of Chinese Academy of Sciences, Beijing 100049

JIA Xiaofeng12,  
  • Affiliation：

    Hubei Provincial Key Laboratory of Environment and Disaster Monitoring and Assessment, Institute of Precision Measurement Science and Technology Innovation, Chinese Academy of Sciences, Wuhan 430077

    University of Chinese Academy of Sciences, Beijing 100049

LI Yifan12,  
  • Affiliation：

    School of Surveying and Mapping Engineering, East China University of Technology, Nanchang 330013

HUANG Duan3,  
  • Affiliation：

    Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Resources, Chinese Academy of Sciences, Beijing 100101

DONG Jinwei4

resumen

Rice is one of the main staple foods of human beings. Timely and accurate access to information about the distribution of paddy rice crop areas and its spatial-temporal variations are crucial for food policy formulation. Focusing on the topic “paddy rice remote sensing mapping,” we first summarized the physiological growing process and primary cropping patterns of paddy rice systematically, following a survey of domestic and foreign literature. Globally, rice cultivation is concentrated in Southeast Asia. In China, single-cropping rice production areas are mainly located in the northeastern region and the middle and lower reaches of the Yangtze River. The double- and triple-cropping rice production areas are located in southern provinces, such as Hunan, Jiangxi, and Guangdong. Second, rice mapping primarily relied on radar data in the early stage due to the effect of clouds and rain. With the abundance of remote sensing data sources, optical and radar data were synergistically applied to rice mapping. On the basis of the highlighted features of paddy rice’s “remote sensing signal-spatial-temporal properties,” we discussed typical vegetation index and the radar backscatter coefficient in rice mapping and concluded with mainstream methods of rice mapping in terms of traditional machine learning and deep learning. Afterward, the rice mapping application status was summed up in three ways: using a standard machine learning model, fusing multisource remote sensing data, and using a cloud-based remote sensing computing platform. Results indicate that the existing issues on rice mapping has the following problems: (1) Rice is misclassified due to the plants (aquatic vegetation such as wetlands) with comparable phenological stages. (2) Optical and radar data hardly provide entire observations in phenology stages of paddy rice. (3) Rice mapping in terrain fragmental areas and multiple cropping or rotation regions is still a huge challenge. (4) Generalization of mapping algorithms in rice mapping remains an issue. With an aim to solve these issues, the next steps of rice mapping were explored from the perspectives of rice phenological feature mining, techniques for collection paddy rice time-series observations, and enhancements to finer spatial resolution in rice mapping, specifically for future research. The steps are as follows: (1) focusing on the exploration of the characteristics of remote sensing signals in phenological stages of paddy rice, (2) using various methods to acquire temporal remote sensing data covering the entire phenological stages of paddy rice, (3) improving the spatial resolution of paddy rice mapping via finer spatial resolution data or multiple data fusion model, and (4) taking fully advantage of optical imagery and radar data for integrated mapping of paddy rice and general algorithms in application.

palabra clave

paddy rice;remote sensing mapping;signal-spatial-temporal;multi-sources remote sensing data;machine learning

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