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Proceedings Paper

Study on measuring the planting area of winter wheat based on per-field classification of remote sensing
Author(s): Xiaohe Gu; Yaozhong Pan; Huifang Wang
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Paper Abstract

According to the problem of spectra variation inside and spectral mixed on boundary of the farmland in mid-resolution images, this paper aims at carrying out per-field classification to improve the accuracy of measuring winter wheat plant area. This paper chooses the urban agriculture region with complex plant structure as experiment area and digitizes the parcel boundary by QuickBird image. By utilizing the farm parcel as end member, the study extracts the information of spectrum, vegetation index and texture from multi-temporal TM images. We establish the evaluation system of field accuracy and total accuracy. The classification methods used in this paper include Support Vector Machine (SVM) and Maximum Likelihood. The study showed that the per-field classification got higher total accuracy field accuracy and stability than per-pixel classification when using for winter wheat plant area measuring. It was useful to improve the accuracy by introducing vegetation index and texture information into per-field classification. The method of both SVM and maximum likelihood got gross accuracy above to 97% and field accuracy above to 90%. The SVM method was more stable than maximum likelihood method, and required much smaller size of training samples. So SVM was more suitable for winter wheat per-field classification. It was useful to improve the accuracy by introducing vegetation index and texture information into per-field classification. This study could provide a new idea about the remote sensing measurement of crop planting area.

Paper Details

Date Published: 30 October 2009
PDF: 8 pages
Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74981V (30 October 2009); doi: 10.1117/12.833734
Show Author Affiliations
Xiaohe Gu, National Engineering Research Ctr. for Information Technology in Agriculture (China)
Yaozhong Pan, Beijing Normal Univ. (China)
Huifang Wang, National Engineering Research Ctr. for Information Technology in Agriculture (China)


Published in SPIE Proceedings Vol. 7498:
MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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