长江流域资源与环境 >> 2020, Vol. 29 >> Issue (10): 2296-2306.doi: 10.11870/cjlyzyyhj202010018

• 农业发展 • 上一篇    下一篇

基于EVI相似性分区的冬小麦面积提取及其动态监测

杨欢1,邓帆1* ,付含聪 1,许诺 1,李彩霞 1,张佳华2*   

  1. (1.长江大学地球科学学院,湖北  武汉 430100;2.中国科学院空天信息创新研究院,北京 100049)
  • 出版日期:2020-10-20 发布日期:2020-11-18

Extraction and Dynamic Monitoring of Winter Wheat Area Based on Zoning with EVI Similarity

YANG Huan 1, DENG Fan 1, FU Han-cong 1, XU Nuo 1 , LI Cai-xia 1 , ZHANG Jia-hua 2   

  1. (1. School of Geosciences, Yangtze University, Wuhan 430100, China;
    2. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100049, China)
  • Online:2020-10-20 Published:2020-11-18

摘要: 及时、准确地获取冬小麦种植面积及时空变化信息对提升作物估产精度和保障粮食安全具有重要意义。冬小麦物候期受地理条件和人为因素影响差异很大,利用遥感进行大尺度种植面积提取时其精度容易受物候差异的影响。根据MODIS EVI数据和Landsat影像,在定量评价冬小麦EVI相似性并结合高程信息对研究区进行分区的基础上,通过对比冬小麦参考时序曲线与待分类像元时序曲线之间相似性提取冬小麦种植面积,并对湖北省2009~2017年冬小麦种植面积时空变化过程进行分析。结果表明:(1)冬小麦面积提取平均精度达95.3%,R 2大于0.90,明显优于未分区提取结果;(2)冬小麦主要集中分布于中部和北部地区,其中,襄阳县、枣阳市的种植面积尤为集中;(3)冬小麦空间分布大致呈现向西北、东南部地区扩张的时空变化格局;(4)在2009~2017年期间,冬小麦种植面积先增后减,总体呈上升趋势,2017年比2009年增加了4%。基于EVI相似性的作物分区提取方法可提高种植面积精度,为大区域内冬小麦面积时空变化遥感监测提供有效方法。

Abstract: Timely and accurately obtaining the planting area of winter wheat and its spatio-temporal change is very important for improving the accuracy of crop yield estimation and food security ensurance. The phenological period of winter wheat is greatly affected by the geographical conditions and human factors, and the extraction accuracy of planting area in a large area by remote sensing is easily affected by the phenological differences. Using MODIS EVI and Landsat as data sources, the winter wheat planting area was extracted by comparing the reference time series with the time series which were to be classified after zoning the study area with winter wheat EVI similarity and elevation information, and the spatial-temporal change process of winter wheat planting area in Hubei Province from 2009 to 2017 was analyzed. The results show that: (1)The average extraction accuracy of winter wheat area was 95.3% with city-level R 2 greater than 0.90, which was better than the extraction accuracy that of  no-zoning; (2) Winter wheat was widely distributed in the middle and northern part of the study area, especially in Xiangyang County and Zaoyang City; (3) There was an obvious spatial-temporal pattern of expansion to the Northwest and Southeast for the spatial distribution of winter wheat; (4)The planting area of winter wheat showed an overall upward trend with an increase of 4% in 2017 compared with 2009, which increased first and then decreased from 2009 to 2017. The method of crop area extraction based on EVI similarity can improve the accuracy of planting area and provide an effective method for remote sensing monitoring of the spatial-temporal change of winter wheat area in a large area.

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