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遥感技术与应用  2023, Vol. 38 Issue (1): 78-89    DOI: 10.11873/j.issn.1004-0323.2023.1.0078
青促会专栏     
基于Sentinel-1/2影像的水稻种植面积提取方法研究
乔树亭1,2(),叶回春2,3,黄文江2,3,4,黄珊瑜5,刘荣豪1(),郭安廷2,3,钱彬祥2,4
1.太原理工大学 水利科学与工程学院,山西 太原 030024
2.中国科学院空天信息创新研究院 数字地球重点实验室,北京 100094
3.中国科学院空天信息研究院海南研究院 海南省地球观测重点实验室,海南 三亚 572029
4.中国科学院大学,北京 100094
5.农业农村部规划设计研究院,北京 100125
Study on Extraction Method of Rice Planting Area based on Sentinel-1/2 Image: A Case Study of Sanjiang Plain
Shuting QIAO1,2(),Huichun YE2,3,Wenjiang HUANG2,3,4,Shanyu HUANG5,Ronghao LIU1(),Anting GUO2,3,Binxiang QIAN2,4
1.College of Water Resources Science and Engineering,Taiyuan University of Technology,Taiyuan 030024,China
2.Key Laboratory of Digital Earth Science,Chinese Academy of Sciences,Beijing 100094,China
3.Hainan Institute,Institute of Aerospace Information Research,Chinese Academy of Sciences,Sanya 572029,China
4.University of Chinese Academy of Sciences,Beijing 100049,China
5.Academy of Agricultural Planning and Engineering,Beijing 100125,China
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摘要:

水稻是中国主要粮食作物之一,稻米产量关系到民生福祉。及时、准确地获取水稻种植面积信息及其空间分布状况对于区域农业发展规划和产量评估具有重要意义。针对水稻与其他农作物易混以及光学数据易受云雨天气影响等问题,以东北三江平原为例,利用中高分辨率Sentinel-1微波数据、Sentinel-2光学数据,分别构建时序水体指数SDWI和植被指数NDVI组成水稻完整的物候生长曲线,分析水稻移栽期、分蘖期、抽穗期、成熟期4个重要生长时期不同的光谱差异,通过阈值分割和组合不同时期的数据,来实现水稻不同物候时期种植面积的提取,并与传统的基于单一光学数据的方法进行对比。研究结果表明:经过地表样本点的验证,所构建方法可以精确提取三江平原水稻几个关键生育期的种植面积并且优于单一使用光学数据的方法。同时利用单生育期影像例如移栽期影像提取水稻面积也可使总体精度达到87.08%,随着生育期数据的完整,总体精度也不断提高,其中基于全生育期的面积提取总体精度也高达91.88%,Kappa系数为0.834,可以满足实际应用需求。因此这种的多源数据结合的水稻种植面积提取方法能够准确、高效地提取三江平原水稻不同物候时期种植面积,为短期内的农情调查管理和区域农业可持续发展提供依据。

关键词: 水稻面积提取物候特征Sentinel?2Sentinel?1三江平原    
Abstract:

Rice is one of the main grain crops in China, and rice yield is related to people's well-being. Timely and accurate acquisition of rice planting area information and its spatial distribution is of great significance for regional agricultural development planning and yield assessment. To solve the problems of rice mixing easily with other crops and optical data being susceptible to cloud and rain weather, taking the Sanjiang Plain in northeast China as an example, a complete rice phenological growth curve was constructed by using time-series water index SDWI and vegetation index NDVI, respectively, based on sentinel-1 microwave data and Sentinel-2 optical data. The spectral differences of four important growth stages of rice were analyzed, including transplanting stage, tillering stage, heading stage and maturity stage, and the planting area of rice in different phenological stages was extracted by threshold segmentation and combination of data of different stages, and compared with the traditional method based on single optical data. The results show that the proposed method can accurately extract the planting area of rice in several key growth stages in Sanjiang Plain, and is superior to the method using optical data alone. At the same time, the overall accuracy of rice area extraction from single growth period images such as transplanting period images can also reach 87.08%. With the completeness of growth period data, the overall accuracy of rice area extraction based on the whole growth period is also as high as 91.88%, and the Kappa coefficient is 0.834, which can meet the requirements of practical application. Therefore, the rice planting area extraction method combined with multi-source data can accurately and efficiently extract the rice planting area in different phenological periods in Sanjiang Plain, and provide a basis for short-term agricultural situation investigation and management and regional agricultural sustainable development.

Key words: Rice area extraction    Phenological characteristics    Sentinel-2    Sentinel-1    Sanjiang plain
收稿日期: 2022-02-16 出版日期: 2023-04-12
ZTFLH:  S127  
基金资助: 中国科学院战略性先导科技专项“水稻土和白浆土质量与产能提升三江示范区”(XDA28100500);国家自然科学基金项目(42001384);中国科学院青年创新促进会项目资助(2021119)
通讯作者: 刘荣豪     E-mail: tyutqiaoshuting@126.com;liuronghao@tyut.edu.cn
作者简介: 乔树亭(1998-),男,山西孝义人,硕士研究生,主要从事植被定量遥感及应用研究。E?mail:tyutqiaoshuting@126.com
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引用本文:

乔树亭,叶回春,黄文江,黄珊瑜,刘荣豪,郭安廷,钱彬祥. 基于Sentinel-1/2影像的水稻种植面积提取方法研究[J]. 遥感技术与应用, 2023, 38(1): 78-89.

Shuting QIAO,Huichun YE,Wenjiang HUANG,Shanyu HUANG,Ronghao LIU,Anting GUO,Binxiang QIAN. Study on Extraction Method of Rice Planting Area based on Sentinel-1/2 Image: A Case Study of Sanjiang Plain. Remote Sensing Technology and Application, 2023, 38(1): 78-89.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2023.1.0078        http://www.rsta.ac.cn/CN/Y2023/V38/I1/78

图1  三江平原土地利用数据、位置及样本点分布
月份45678910
水稻播种灌水移栽苗期分蘖抽穗成熟收获
玉米播种出苗拔节抽穗开花灌浆成熟收获
大豆播种幼苗分化开花结荚成熟收获
表1  三江平原主要农作物生育期情况汇总
图2  提取水稻种植区面积技术流程图
图3  时序MNDWI曲线(已经过去云筛选及SG滤波处理,标注为显著置信区间)
图4  时序NDVI曲线(已经过去云筛选及SG滤波处理,标注为显著置信区间)
日期方案
4月20日~5月20日

Sentinel-2 MNDWI

(移栽期)

Sentinel-2 MNDWI

(移栽期)

Sentinel-2 MNDWI

(移栽期)

Sentinel-2 MNDWI

(移栽期)

6月20日~7月20日

Sentinel-2 NDVI

(分蘖期)

Sentinel-2 NDVI

(分蘖期)

Sentinel-2 NDVI

(分蘖期)

7月20日~8月20日

Sentinel-2 NDVI

(抽穗期)

Sentinel-2 NDV

I(抽穗期)

9月20日~10月20日

Sentinel-2 NDVI

(成熟期)

表2  基于Sentinel-2数据的不同生育期水稻种植面积提取方案
图5  时序SDWI曲线(已经过SG滤波平滑处理且标注为显著置信区间)
日期方案
5月20日~6月20日Sentinel-1 SDWI(移栽期)、DEMSentinel-1 SDWI(移栽期)、DEMSentinel-1 SDWI(移栽期)、DEMSentinel-1 SDWI(移栽期)、DEM
6月20日~7月20日Sentinel-2 NDVI(分蘖期)Sentinel-2 NDVI(分蘖期)Sentinel-2 NDVI(分蘖期)
7月20日~8月20日Sentinel-2 NDVI(抽穗期)Sentinel-2 NDVI(抽穗期)
9月20日~10月20日Sentinel-2 NDVI(成熟期)
表3  基于Sentinel-1和Sentinel-2数据的不同生育期水稻种植面积提取方案
图6  不同方案提取水稻各生育期面积结果
方案

面积精度

/%

生产者

精度/%

用户精度

/%

总体精度

/%

Kappa

系数

87.6777.0690.6185.240.702
92.0379.0590.3086.350.723
94.3079.8990.3086.840.733
89.4985.3888.4889.180.776
83.2177.6495.7687.080.742
88.8380.0095.7688.560.770
96.4681.6195.4589.420.786
90.4586.4694.8591.880.834
表4  不同方案水稻种植面积验证精度对比
图7  基于全生育期数据的方案④与方案⑧的水稻面积提取结果细节对比图
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