湖北农业科学 ›› 2022, Vol. 61 ›› Issue (10): 141-146.doi: 10.14088/j.cnki.issn0439-8114.2022.10.025

• 信息工程 • 上一篇    下一篇

基于时序影像及关键物候特征的江苏省夏收农作物提取

王宗伟1,2, 卢刚1,2, 秦慧杰1, 张汛1, 陈刚强1, 黄博超1   

  1. 1.江苏省测绘工程院, 南京 210013;
    2.自然资源部国土卫星遥感应用重点实验室,南京 210013
  • 收稿日期:2020-02-21 出版日期:2022-05-25 发布日期:2022-06-14
  • 作者简介:王宗伟(1988-),男,安徽宿州人,工程师,硕士,主要从事卫星遥感应用研究工作,(电话)18100601228(电子信箱)wangzongwei328@163.com。
  • 基金资助:
    江苏省自然资源科技计划项目(2020045); 江苏省自然资源发展专项(JSZRHYKJ202002)

Extraction of summer harvest crops in Jiangsu Province based on time series images and key phenological features

WANG Zong-wei1,2, LU Gang1,2, QIN Hui-jie1, ZHANG Xun1, CHEN Gang-qiang1, HUANG Bo-chao1   

  1. 1. Jiangsu Province Surveying and Mapping Engineering Institute, Nanjing 210013,China;
    2. Key Laboratory of Land Satellite Remote Sensing Application,Ministry of Natural Resources,Nanjing 210013,China
  • Received:2020-02-21 Online:2022-05-25 Published:2022-06-14

摘要: 农作物遥感分类与识别是提取农作物种植范围和面积的基础,也是开展农作物长势、产量、所受灾害等相关信息监测的基础。油菜和小麦是江苏省越冬主要农作物,为解决江苏省主要夏收农作物快速、准确提取的难题,以宜兴市为例,提出了基于时序影像及关键物候特征的夏收农作物提取方法,基于不同农作物在生长发育过程中差异性特征,结合农作物的物候信息,采用表达作物每个生长期阶段特征的时间序列影像数据,对不同的农作物进行提取,提取结果显示,总体精度为92.65%,Kappa系数为0.86,说明利用该方法提取江苏省夏收农作物技术可行,提取结果可为农作物种植面积估算提供参考,为农作物精细监测、耕地非粮化监测提供技术支撑。

关键词: 时序影像, 关键物候特征, 农作物提取, 小麦, 油菜

Abstract: Crop remote sensing classification and recognition is not only the basis for extracting the planting range and area of crops, but also the basis for monitoring the growth, yield, disasters and other related information of crops. Rape and wheat are the main winter crops in Jiangsu Province. In order to solve the problem of rapid and accurate extraction of main summer crops in Jiangsu Province, taking Yixing city as an example, this paper proposed a summer harvest crop extraction method based on time series images and key phenological features. Based on the different characteristics of different agricultural crops in the process of growth and development, combined with the phenological information of crops, the time series image data expressing the characteristics of each growth stage of crops were used to extract different crops. The extraction results showed that the overall accuracy was 92.65% and the Kappa coefficient was 0.86, indicating that the technology of extracting summer harvest crops in Jiangsu Province was feasible, and the extraction results could provide reference for the estimation of crop planting area, and offer technical support for crop fine monitoring and the monitoring of non-grain production of cultivated land.

Key words: time series image, key phenological characteristics, crop extraction, wheat, rape

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