基于时间序列全极化合成孔径雷达的水稻物候期反演

doi:10.3785/j.issn.1008-9209.2020.09.231

浙江大学学报（农业与生命科学版）

2021, Vol. 47

Issue (3): 404-414 DOI: 10.3785/j.issn.1008-9209.2020.09.231

农业工程

基于时间序列全极化合成孔径雷达的水稻物候期反演

李宏宇¹(

),李坤^2,^3,⁴(

),杨知⁵

^1.上海市测绘院，上海 200063
^2.中国科学院空天信息创新研究院，北京 100101
^3.中科卫星应用德清研究院/浙江省微波目标特性测量与遥感重点实验室，浙江湖州 313200
^4.中国科学院大学，北京 100049
^5.中国电力科学研究院有限公司，北京 100192

Retrieval of rice phenological stages based on time-series full-polarization synthetic aperture radar data

Hongyu LI¹(

),Kun LI^2,^3,⁴(

),Zhi YANG⁵

^1.Shanghai Surveying and Mapping Institute, Shanghai 200063, China
^2.Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
^3.China Science and Technology Satellite Application Deqing Research Institute/Zhejiang Key Laboratory of Microwave Target Characteristic Measurement and Remote Sensing, Huzhou 313200, Zhejiang, China
^4.University of Chinese Academy of Sciences, Beijing 100049, China
^5.China Electric Power Research Institute Co. , Ltd. , Beijing 100192, China

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摘要：

基于多时相全极化合成孔径雷达（synthetic aperture radar, SAR）数据，对江苏省淮安市金湖县附近地区水稻进行种类识别和关键物候期反演；通过提取分析水稻极化特征参数时序曲线变化特征，筛选出对水稻物候变化敏感的极化特征参数，构造出一个能体现水稻生长关键物候变化特征的雷达物候指数（radar phenology index, RPI），利用Savitzky-Golay（S-G）滤波重构后的雷达物候指数反演水稻关键物候期。结果表明：粳稻和籼稻在极化参数香农熵的响应方面差异较大，利用香农熵可将籼稻和粳稻较好地识别出来，识别精度分别为92.38%和95.10%，取得了较好的识别效果；利用曲线导数法提取水稻时序雷达物候指数曲线特征点，识别出水稻3个关键物候期，且识别出的水稻关键物候期日期与野外地面调查获得的日期相差全部在±16 d以内，说明利用雷达物候指数可以较准确地反演出水稻关键物候期。

关键词： 全极化合成孔径雷达; 水稻物候期反演; 雷达物候指数

Abstract:

Rice species identification and the retrieval of key phenological stages were processed in the area around Jinhu County, Huai’an City, Jiangsu Province, based on multi-temporal full-polarization synthetic aperture radar (SAR) data. By extracting and analyzing the change characteristics of the time-series curve of the polarization characteristic parameters of rice, the polarization characteristic parameters that are sensitive to the changes of rice phenology were screened out, and a radar phenology index (RPI) that can reflect the key phenological changes of rice growth was constructed, and then was reconstructed by Savitzky-Golay (S-G) filter. The key phenological stages of rice were retrieved by the RPI. The results showed that the response of the polarization parameter Shannon entropy was quite different between japonica rice and indica rice, indicating that Shannon entropy could be used to identify indica rice and japonica rice with precisions of 92.38% and 95.10%, respectively; the curve derivative method was used to extract the characteristic points of the time-series RPI curve of rice, and three key phenological stages of rice were identified. The dates of the identified key phenological stages of rice were all within ±16 d from the date obtained in the field survey. The above results show that the use of RPI can more accurately retrieve the key phenological stages of rice.

Key words: full-polarization synthetic aperture radar retrieval of rice phenology radar phenology index

收稿日期: 2020-09-23 出版日期: 2021-06-25

CLC:

TP 79

基金资助: 国家自然科学基金面上项目“多时相极化SAR与作物生长模型耦合的区域水稻产量差当季估算方法研究”(41871272)

通讯作者: 李坤 E-mail: lihongyu19931222@163.com;likun@radi.ac.cn

作者简介: 李宏宇（https://orcid.org/0000-0002-8597-9953），E-mail：lihongyu19931222@163.com

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引用本文:

李宏宇,李坤,杨知. 基于时间序列全极化合成孔径雷达的水稻物候期反演[J]. 浙江大学学报（农业与生命科学版）, 2021, 47(3): 404-414.

Hongyu LI,Kun LI,Zhi YANG. Retrieval of rice phenological stages based on time-series full-polarization synthetic aperture radar data. Journal of Zhejiang University (Agriculture and Life Sciences), 2021, 47(3): 404-414.

链接本文:

http://www.zjujournals.com/agr/CN/10.3785/j.issn.1008-9209.2020.09.231 或 http://www.zjujournals.com/agr/CN/Y2021/V47/I3/404

图1 2015年9月16日RADARSAT-2全极化SAR数据RGB假彩色合成图R：HH极化；G：HV极化；B：VV极化。

表1 获取的RADARSAT-2全极化SAR数据参数

表2 全极化SAR部分特征参数提取列表

图2 典型地物极化特征参数变化特征

图3 水稻种类识别的决策树算法

图4 研究区地物识别结果图

表3 基于多时相全极化SAR数据的研究区地物分类混淆矩阵

图5 第10号样本田2015年水稻RPI插值处理前后对比图

图6 第10号样本田时序RPI经S-G滤波处理前后对比图

图7 粳稻生长的各个物候阶段（10号样本田）a：出芽期至幼苗期；b：分蘖初期至分蘖中期；c：拔节期至孕穗期；d：抽穗扬花期；e：乳熟期至完熟期。

图8 水稻样本田识别结果与野外观测物候比较

图9 19个水稻样本田获取的水稻物候反演结果与观测值对比分布图

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