中国农业科学 ›› 2010, Vol. 43 ›› Issue (16): 3306-3315 .doi: 10.3864/j.issn.0578-1752.2010.16.005

• 耕作栽培·生理生化·农业信息技术 • 上一篇    下一篇

HJ-1号卫星数据与统计抽样相结合的冬小麦区域面积估算

张锦水,申克建,潘耀忠,李苓苓,侯东

  

  1. (北京师范大学资源学院/地表过程与资源生态国家重点实验室)
  • 收稿日期:2009-12-31 修回日期:2010-04-12 出版日期:2010-08-15 发布日期:2010-08-15

HJ-1 Remotely Sensed Data and Sampling Method for Wheat Area Estimation

ZHANG Jin-shui, SHEN Ke-jian, PAN Yao-zhong, LI Ling-ling, HOU Dong
  

  1. (北京师范大学资源学院/地表过程与资源生态国家重点实验室)
  • Received:2009-12-31 Revised:2010-04-12 Online:2010-08-15 Published:2010-08-15

摘要:

【目的】探讨利用HJ-1号卫星遥感数据进行冬小麦种植面积测量的可行性,并进一步结合统计抽样的方法,估算区域冬小麦种植面积,解决单靠遥感进行冬小麦种植面积测量时多期影像信息误差积累和生长差异性影响的问题。【方法】以北京市为研究区,采用多时相HJ-1号卫星遥感数据与分层抽样相结合的方法进行冬小麦种植面积测量:利用多时相HJ-1号卫星遥感数据获取冬小麦遥感识别结果(56 506.67 hm2),结合耕地地块数据建立入样总体,以耕地地块内冬小麦遥感识别面积作为分层标志进行分层随机抽样,反推得到北京市冬小麦面积总量(59 680 hm2)。【结果】多时相冬小麦遥感识别结果MAE为0.17,bias为-0.05,抽样反推区域总量面积提高了约5%,在一定程度上纠正了HJ-1号卫星多期遥感影像提取冬小麦区域面积偏低的问题。【结论】本文方法能够准确测量出区域冬小麦总量面积,具有较强的应用性和普适性,为采用HJ-1号卫星遥感数据进行农作物种植面积遥感测量进行了先期的方法探讨,深化了该遥感数据源的应用。

关键词: 冬小麦, 面积估算, 分层抽样, 遥感

Abstract:

【Objective】 The method combing the advantages of remotely sensed data and sampling has showed the better actual value in practice for solving the problems about mis-registration error and regional difference. 【Method】 Taking Beijing as a study area, a combing method with multi-temporal HJ-1 remotely sensed data was used for wheat planting area estimation. Firstly, the multi-temporal remote sensing images were adopted for the wheat area, then integrating the cultivated parcel for building sample populations. Secondly, with wheat area in the parcel as the stratified flag, the stratified random sample method was applied. Thirdly, after ground survey for every sample, the overall regional wheat area was derived. The results showed that MAE and bias was 0.17 and -0.05 respectively. 【Result】 The sample method increased by 5% for regional wheat planting area, which corrected some remote sensing errors. 【Conclusion】 It was concluded that the method can guarantee the regional and parcel scale accuracy, and can be broadly used in crop area estimation.

Key words: winter wheat, area estimation, strata sample, remote sensing