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Proceedings Paper

Analysis of RapidEye imagery for agricultural land mapping
Author(s): Huiyong Sang; Jixian Zhang; Liang Zhai; Wenhan Xie; Xiaoxia Sun; Wenhan Xie
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Paper Abstract

With the improvement of remote sensing technology, the spatial, structural and texture information of land covers are present clearly in high resolution imagery, which enhances the ability of crop mapping. Since the satellite RapidEye was launched in 2009, high resolution multispectral imagery together with wide red edge band has been utilized in vegetation monitoring. Broad red edge band related vegetation indices improved land use classification and vegetation studies. RapidEye high resolution imagery was used in this study to evaluate the potential of red edge band in agricultural land cover/use mapping using an objected-oriented classification approach. A new object-oriented decision tree classifier was introduced in this study to map agricultural lands in the study area. Besides the five bands of RapidEye image, the vegetation indexes derived from spectral bands and the structural and texture features are utilized as inputs for agricultural land cover/use mapping in the study. The optimization of input features for classification by reducing redundant information improves the mapping precision about 18% for AdaTree. WL decision tree, and 5% for SVM, the accuracy is over 90% for both classifiers.

Paper Details

Date Published: 9 December 2015
PDF: 9 pages
Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 98081W (9 December 2015); doi: 10.1117/12.2210864
Show Author Affiliations
Huiyong Sang, Chinese Academy of Surveying and Mapping (China)
Jixian Zhang, Chinese Academy of Surveying and Mapping (China)
Liang Zhai, Chinese Academy of Surveying and Mapping (China)
Wenhan Xie, Chinese Academy of Surveying and Mapping (China)
Xiaoxia Sun, Chinese Academy of Surveying and Mapping (China)
Wenhan Xie, Chinese Academy of Surveying and Mapping (China)


Published in SPIE Proceedings Vol. 9808:
International Conference on Intelligent Earth Observing and Applications 2015
Guoqing Zhou; Chuanli Kang, Editor(s)

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