Analysis of RapidEye imagery for agricultural land mapping

Huiyong Sang; Jixian Zhang; Liang Zhai; Wenhan Xie; Xiaoxia Sun

doi:10.1117/12.2210864

9 December 2015 Analysis of RapidEye imagery for agricultural land mapping

Huiyong Sang, Jixian Zhang, Liang Zhai, Wenhan Xie, Xiaoxia Sun

Proceedings Volume 9808, International Conference on Intelligent Earth Observing and Applications 2015; 98081W (2015) https://doi.org/10.1117/12.2210864
Event: International Conference on Intelligent Earth Observing and Applications, 2015, Guilin, China

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.

Citation Download Citation

Huiyong Sang, Jixian Zhang, Liang Zhai, Wenhan Xie, and Xiaoxia Sun "Analysis of RapidEye imagery for agricultural land mapping ", Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 98081W (9 December 2015); https://doi.org/10.1117/12.2210864

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KEYWORDS

Vegetation

Agriculture

Associative arrays

Image resolution

Near infrared

Remote sensing

Volume rendering

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