DONG Jin-hui,YANG Xiao-dong,GAO Lin,et al.Information Extraction of Winter Wheat Lodging Area Based on UAV Remote Sensing Image[J].HEILONGJIANG AGRICULTURAL SCIENCES,2016,(10):147-152.[doi:10.11942/j.issn1002-2767.2016.10.0147]
基于无人机遥感影像的冬小麦倒伏面积信息提取
- Title:
- Information Extraction of Winter Wheat Lodging Area Based on UAV Remote Sensing Image
- 文章编号:
- 1002-2767（2016）10-0147-06
- Keywords:
- UAV remote sensing platform; crop monitoring; lodging information extraction; precision agriculture
- 分类号:
- S127；S512
- 文献标志码:
- A
- 摘要:
- 倒伏是农业生产中造成减产、作物品质降低的主要原因，基于无人机飞控平台农情监测系统的灾情严重度实时监测以及时采取防治措施提供科学依据。以人工目视解译统计得到的倒伏面积作为判别依据，通过对比最小距离法、最大似然法、神经网络、支持向量机四种监督分类方法对单张无人机影像的分类效果，择优用于无人机拼接数码影像，估算江苏里下河地区小麦倒伏面积。结果表明：最小距离法、最大似然法、神经网络、支持向量机四种方法的分类精度分别为63.57%、98.15%、81.13%、85.04%，最大似然分类法得到的精度最高，其运算速度也最快，与无人机遥感平台农情监测系统快速、便捷的需求相符。将最大似然法应用于整张拼接影像，监测得到倒伏像元个数为7 183 950，估算面积为353.810 8 m2，与人工目视解译结果的误差为7.43%，突出了无人机在信息获取方面方便、快捷的特点，表明搭载数码相机的无人机遥感平台对农情监测有一定可行性，可以为精准农业深入开展提供新的契机。
- Abstract:
- Lodging is one of the common disasters in agricultural production,it can make the crop yield and quality decrease,resulting in production and harvest .Real time monitoring of lodging can take preventive measures timely,to minimize the impact on yield.The UAV equipped with digital cameras to form agricultural monitoring system of remote sensing platform was adopted to capture the winter wheat lodging digital image in late filling stage of 2014 in Jiangsu Yangzhou Lixiahe region,four supervised classification methods for single wheat lodging classification accuracy were compared with the minimum distance method,maximum likelihood method,neural network and support vector machine .The results showed that the classification accuracy of minimum distance method,maximum likelihood method,neural network and support vector machine were 63.57%,98.15%,81.13% and 85.04%，the maximum likelihood method had the highest precision and the fastest computing speed ,which could meet remote sensing platform agricultural condition monitoring system with fast and convenient.Therefore ,maximum likelihood classification algorithm was used to extract the information of 2014 grain filling stage of winter wheat mosaic lodging area ,stitching monitoring lodging pixel number was 7 183 950 and area estimation was 353.810 8 m2,and artificial visual solution error translation result was 7.43%,the UAV in the information acquisition aspects,fast and convenient features was highlighted,that was equipped with digital camera without man-machine remote sensing platform feasibility of agricultural condition monitoring to provide a new opportunity for precision agriculture development.
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备注/Memo
收稿日期：2016-08-05