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Remote Sensing for Land & Resources    2018, Vol. 30 Issue (4) : 28-32     DOI: 10.6046/gtzyyg.2018.04.05
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Classification of Pinus massoniana and Cunninghamia lanceolata using hyperspectral image based on differential transformation
Nianxu XU1,2,3, Qingjiu TIAN1,2(), Huaifei SHEN1,2, Kaijian XU1,2
1. International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
2. Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing 210023, China
3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
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Abstract  

Hyperspectral remote sensing can distinguish small spectrum differences between ground objects, and is expected to solve the classification problem of tree species. In this paper, by using Hyperion hyperspectral image, combined with the ground measured samples, classification of Pinus massoniana and Cunninghamia lanceolata in Wucheng of Huangshan City was conducted. With the 1st and 2nd differential transformation of the image, spectral band combination of 487~559 nm and 681~742 nm differs significantly, and hence was chosen to conduct supervised classification using support vector machine. Classification accuracy of raw, 1st and 2nd differential transformation image reaches 76.50%, 81.42% and 88.52% with Kappa coefficient being 0.528 4, 0.625 7 and 0.769 1 respectively. The results show that 2nd differential transformation and band selection of hyperspectral data can improve the classification accuracy of Pinus massoniana and Cunninghamia lanceolata, thus providing a foundation for further study of classification of coniferous forest with hyperspectral remote sensing.
Keywords hyperspectral      Hyperion      differential transformation      coniferous forest      support vector machine     
:  TP79  
Corresponding Authors: Qingjiu TIAN     E-mail: tianqj@nju.edu.cn
Issue Date: 07 December 2018
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Nianxu XU
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Kaijian XU
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Nianxu XU,Qingjiu TIAN,Huaifei SHEN, et al. Classification of Pinus massoniana and Cunninghamia lanceolata using hyperspectral image based on differential transformation[J]. Remote Sensing for Land & Resources, 2018, 30(4): 28-32.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2018.04.05     OR     https://www.gtzyyg.com/EN/Y2018/V30/I4/28
Fig.1  Hyperion image and ground measured samples in study area
Fig.2  Reflectance spectrum of Pinus massoniana and Cunninghamia lanceolate based on Hyperion pixel
Fig.3  1stand 2nddifferential transformation reflectance spectrum of Pinus massoniana and Cunninghamia lanceolate based on Hyperion pixel
Fig.4  Classification results of Pinus massoniana and Cunninghamia lanceolate based on Hyperion
类别 杉木 马尾松 总计
原始反射率光谱 杉木 63 17 80
马尾松 26 77 103
总计 89 94 183
一阶微分光谱 杉木 61 6 67
马尾松 28 88 116
总计 89 94 183
二阶微分光谱 杉木 70 2 72
马尾松 19 92 111
总计 89 94 183
Tab.1  Accuracy statistics of raw reflectance,1st and 2nd differential transformation spectrum
类别 总体精度/% Kappa系数
原始反射率光谱 76.502 7 0.528 4
一阶微分光谱 81.420 8 0.625 7
二阶微分光谱 88.524 6 0.769 1
Tab.2  Statistical results of overall accuracy and Kappa coefficient
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