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遥感技术与应用  2015, Vol. 30 Issue (5): 891-898    DOI: 10.11873/j.issn.1004-0323.2015.5.0891
模型与反演     
与抽样相结合的县级作物遥感面积估算应用实例
李宜展1,2,朱秀芳1,2,张锦水1,2,潘耀忠1,2,李慕义1,2
(1.北京师范大学地表过程与资源生态国家重点实验室,北京 100875;
2.北京师范大学资源学院,北京 100875)
A Case Study for Area Estimation of Crop in County Level based on Remote Sensing Data and Sampling Technology
Li Yizhan1,2,Zhu Xiufang1,2,Zhang Jinshui1,2,Pan Yaozhong1,2,Li Muyi1,2
(1.State Key Laboratory of Earth Surface Processes and Resource Ecology,
Beijing Normal University,Beijing 100875,China;
2.College of Resources Science and Technology,Beijing Normal University,Beijing 100875,China )
 全文: PDF 
摘要:

为了探索遥感卫星影像和无人机调查在实际遥感面积估算中的调查效果和适用性,以广东省阳春市晚稻为例,采用卫星影像与无人机调查结果相结合,使用两种面积估算方法进行2013年晚稻种植面积估算。实验结果表明,比估计和回归估计方法的估算结果分别为22 501.1 hm2和22 781.1 hm2,二者的CV分别为8.84%和1.03%。研究结果表明:①无人机调查可获得高质量的面积测量信息;②优化后的样本能够支持面积估算过程,但其理论意义需要更进一步地讨论与证明;③卫星数据与无人机调查数据相结合的方法可以提供满足统计精度要求的面积测量结果,具有良好的应用前景。

关键词: 无人机卫星影像面积估算晚稻    
Abstract:

Unmanned aerial vehicle (UAV) is an effective tool and an appreciate alternative mean to supply,even partially replace the traditional ground investigation,especially at large scale investigation,due to its greater availability and flexibility.However,there is little study on area estimation using UAV in domestic,and this investigation approach is not yet adopted operationally.Therefore,it is necessary to explore the applicability and flexibility,and point out the issues that should be noted at the area estimation processes with UAVs in practical cases.In this study,the area estimation of rice,main crop in south China was implemented in Yangchun,Guangdong Province.Satellite imageries were acquired at key growth period of late rice.Support Vector Machine (SVM) was used to generate the classification of arable land.This study constructed 300 m×300 m square grids covering the whole study area.Then,grids that contain the arable land in classification were reserved to form the population.After that,we proposed a sampling method to reduce the cost and made full use of UAVs’ intensive investigation ability.This method included four steps:firstly,stratified random sampling method was used to select investigation samples from 300 m×300 m square grids and the variance of those samples (V1) was calculated.Secondly,big rectangle grids were built up and covered the whole study area,and each big rectangle grid contained 5×6small square grids which may be from different strata.Thirdly,the variance of 5×6small square grids (V2) in each big rectangle grid was calculated and compared with the variance of selected samples in step1.If the V2 of a given rectangle grid is equal to or near to V1,the big rectangle grid can be used to replace the samples selected from step1.Fourthly,according to the required sample size and the comparison results in step 3,we selected three big rectangle grids as final samples for UAVs investigation.Ratio estimator and difference regression estimator were adopted to estimate the sowing area of late rice in Yangchun of Guangdong Province in 2013.Their area estimations were 22 501.1 hm2 and 22 781.1 hm2,respectively,and their coefficient of variation were 8.84% and 1.03%,respectively.Above the results suggest that the UAVs investigation provide reliable ground truth.The proposed sample selection method in this study enhances the feasibility and operability of UAVs in crop area estimation.

Key words: Unmanned aerial vehicles    Satellite imagery    Area estimation    Late rice
收稿日期: 2014-03-08 出版日期: 2015-12-08
:  F 321.1  
基金资助:

高分辨率对地观测重大专项(民用部分)“基于高分辨率遥感的国家统计业务化应用示范”(一期)(E0307/1112 )。

通讯作者: 朱秀芳(1982-),女,浙江天台人,副教授,主要从事人类活动与气候变化间的响应以及遥感应用方面的研究。Email:zhuxiufang@bnu.edu.cn。   
作者简介: 李宜展(1988-),女,山东菏泽人,博士研究生,主要从事土地覆盖变化监测、统计遥感方向的研究。Email:lyzh0427@163.com。
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引用本文:

李宜展,朱秀芳,张锦水,潘耀忠,李慕义. 与抽样相结合的县级作物遥感面积估算应用实例[J]. 遥感技术与应用, 2015, 30(5): 891-898.

Li Yizhan,Zhu Xiufang,Zhang Jinshui,Pan Yaozhong,Li Muyi. A Case Study for Area Estimation of Crop in County Level based on Remote Sensing Data and Sampling Technology. Remote Sensing Technology and Application, 2015, 30(5): 891-898.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2015.5.0891        http://www.rsta.ac.cn/CN/Y2015/V30/I5/891

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