Mahalanobis Distance Based Hyperspectral Characteristic Discrimination of Leaves of Different Desert Tree Species
LIN Hai-jun1, ZHANG Hui-fang2, GAO Ya-qi2*, LI Xia1, YANG Fan1, ZHOU Yan-fei1
1. College of Pratacultural and Environmental Science, Xinjiang Agricultural University, Urumqi 830052, China 2. Xinjiang Academy of Forestry Sciences Modern Forestry Institute, Urumqi 830000, China
Abstract：The hyperspectral reflectance of Populus euphratica, Tamarix hispida, Haloxylon ammodendron and Calligonum mongolicum in the lower reaches of Tarim River and Turpan Desert Botanical Garden was measured by using the HR-768 field-portable spectroradiometer. The method of continuum removal, first derivative reflectance and second derivative reflectance were used to deal with the original spectral data of four tree species. The method of Mahalanobis Distance was used to select the bands with significant differences in the original spectral data and transform spectral data to identify the different tree species. The progressive discrimination analyses were used to test the selective bands used to identify different tree species. The results showed that The Mahalanobis Distance method was an effective method in feature band extraction. The bands for identifying different tree species were most near-infrared bands. The recognition accuracy of four methods was 85%, 93.8%, 92.4% and 95.5% respectively. Spectrum transform could improve the recognition accuracy. The recognition accuracy of different research objects and different spectrum transform methods were different. The research provided evidence for desert tree species classification, monitoring biodiversity and the analysis of area in desert by using large scale remote sensing method.
Key words：Hyperspectral;Desert tree species;Mahalanobis Distance;Stepwise discriminant analysis
林海军1，张绘芳2，高亚琪2*，李 霞1，杨 帆1，周艳飞1. 基于马氏距离法的荒漠树种高光谱识别[J]. 光谱学与光谱分析, 2014, 34(12): 3358-3362.
LIN Hai-jun1, ZHANG Hui-fang2, GAO Ya-qi2*, LI Xia1, YANG Fan1, ZHOU Yan-fei1. Mahalanobis Distance Based Hyperspectral Characteristic Discrimination of Leaves of Different Desert Tree Species. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2014, 34(12): 3358-3362.
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