The method of extracting rice-crayfish paddy fields distribution in the Jianghan Plain based on Sentinel-2 data

doi:10.14088/j.cnki.issn0439-8114.2024.08.033

Abstract

Abstract: Taking the Jianghan Plain as the study area, and based on the Sentinel-2 MSI L2 data provided by AI Earth cloud platform, on the basis of field sampling samples and visually interpreted samples, the critical time and index threshold to distinguish rice-crayfish paddy fields from other ground types were summarized by analyzing the temporal change of rice-crayfish paddy fields in remote sensing images, so as to construct a decision tree model for rice-crayfish paddy fields extraction. Finally, the spatial distribution of rice-crayfish paddy fields in the Jianghan Plain from 2022 to 2023 was extracted. Finally, the accuracy of the method was evaluated based on the sample data, and the overall accuracy reached 93.25% with Kappa coefficient of 0.842 9, which showed that the method had better extraction results.

Key words: multi-temporal remote sensing, Sentinel-2, rice-crayfish paddy field, decision tree, Jianghan Plain

CLC Number:

P237

WANG Jing, WAN Jun, DENG Huan-huan. The method of extracting rice-crayfish paddy fields distribution in the Jianghan Plain based on Sentinel-2 data[J]. HUBEI AGRICULTURAL SCIENCES, 2024, 63(8): 194-200.

References

[1] 汤以胜,孙晓敏,陈前,等.基于遥感大数据云计算平台下的水稻识别研究[J]. 航天返回与遥感,2022,43(3):113-123.
[2] 陈仲新,任建强,唐华俊,等.农业遥感研究应用进展与展望[J].遥感学报,2016,20(5):748-767.
[3] 李志鹏,刘珍环,李正国,等.水稻空间分布遥感提取研究进展与展望[J].中国农业资源与区划,2014,35(6):9-18.
[4] 姚飞,何隆华.多时相遥感提取水稻种植区研究进展[J].福建农林大学学报(自然科学版),2016,45(6):617-624.
[5] 孙佩军,张锦水,潘耀忠,等.构建时空融合模型进行水稻遥感识别[J].遥感学报,2016,20(2):328-343.
[6] 任鸿瑞,张悦琦,何奇瑾,等.基于FY-3 MERSI遥感数据的水稻种植分布提取[J]. 光谱学与光谱分析,2023,43(5):1606-1611.
[7] 陆俊,黄进良,王立辉,等.基于时空数据融合的江汉平原水稻种植信息提取[J].长江流域资源与环境,2017,26(6):874-881.
[8] 汪荃,陈军军.基于Sentinel-2时序影像的水稻种植信息提取[J].湖北农业科学,2022,61(16):175-181.
[9] 张红华,赵威成,刘强凯.基于多时相遥感影像的水稻种植信息提取[J].安徽农业科学,2022,50(7):234-238.
[10] 许辉,赵阳阳,孙东岳,等.稻虾共作模式研究进展[J].中国农业科技导报,2022,24(2):160-168.
[11] 曹凑贵,江洋,汪金平,等.稻虾共作模式的“双刃性”及可持续发展策略[J].中国生态农业学报,2017,25(9):1245-1253.
[12] 魏浩东,杨靖雅,蔡志文,等.物候窗口和多源中高分辨率影像的稻虾田提取[J]. 遥感学报,2022,26(7):1423-1436.
[13] 魏妍冰,陆苗,吴文斌.基于水体季相差异的稻虾共作提取方法研究[J].中国农业资源与区划,2019,40(3):14-20,34.
[14] 魏妍冰,陆苗,唐华俊,等.江汉平原稻虾共作技术时空扩散的过程及特征[J].地球信息科学学报,2023,25(9):1827-1841.
[15] 陶建斌,赵睿一,王松,等.基于时序Sentinel-2影像物候特征的江汉平原耕地非粮化监测[J/OL].武汉大学学报(信息科学版):1-14[2024-06-12].https://doi.org/10.13203/j.whugis20230020.
[16] 张紫荆,华丽,郑萱,等.基于GEE平台与Sentinel-NDVI时序数据江汉平原种植模式提取[J].农业工程学报,2022,38(1):196-202.
[17] 王爱芳,张运,黄静,等.作物遥感分类研究进展[J].测绘与空间地理信息,2021,44(10):80-83,88.
[18] 阴海明,王立辉,董明霞,等.基于多时相Sentinel-2遥感影像的江汉平原夏收作物提取方法[J].福建农林大学学报(自然科学版),2021,50(1):16-22.
[19] 邓刚,唐志光,李朝奎,等.基于MODIS时序数据的湖南省水稻种植面积提取及时空变化分析[J].国土资源遥感,2020, 32(2):177-185.
[20] 彭乐文,张亚.基于多时相遥感数据的水稻种植面积信息提取[J].湖北农业科学,2020,59(2):157-160,165.
[21] 王大钊,王思梦,黄昌.Sentinel-2和Landsat8影像的四种常用水体指数地表水体提取对比[J].国土资源遥感,2019,31(3):157-165.