| 结合影像纹理、光谱与地形特征的森林结构参数反演 |
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| 引用本文： | 谢士琴,赵天忠,王威,孟京辉,史京京.结合影像纹理、光谱与地形特征的森林结构参数反演[J].农业机械学报,2017,48(4):125-134. |
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| 作者姓名： | 谢士琴 赵天忠 王威 孟京辉 史京京 |
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| 作者单位： | 北京林业大学,北京林业大学,国家林业局调查规划设计院,北京林业大学,国家林业局调查规划设计院 |
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| 基金项目： | 国家高分辨率对地观测系统重大专项（21-Y30B05-9001-13/15-4） |
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| 摘 要： | 以黑龙江省SPOT5遥感影像和森林资源清查数据为数据源,获得对应样地的影像纹理特征、光谱波段值、光谱组合值以及地形信息,提取样地调查数据的林分信息,采用多元逐步回归分析,建立以SPOT5遥感影像纹理、光谱和地形特征为自变量,多个森林结构参数(林分平均直径、断面积、蓄积量和树种多样性指数)为因变量的估测模型,筛选最优纹理特征生成窗口及最优森林结构参数反演模型。结果表明,SPOT5影像的纹理光谱特征与森林结构参数具有较强的相关性,9×9窗口为最优纹理特征生成窗口;在引入地形因子后模型精度有了较大提高,树种多样性指数估测模型R2adj都在0.72以上,蓄积量模型估测精度最优(R2adj为0.864、RMSE为21.260 m~3/hm~2)。研究表明利用高分辨率遥感影像纹理、光谱和地形特征进行多个森林结构参数估测具有很好的应用效果。
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| 关 键 词： | 森林结构 纹理特征 光谱特征 地形因子 模型估测 |
| 收稿时间： | 2016/12/5 0:00:00 |
Forest Structure Parameters Inversion Based on Image Texture and Spectral and Topographic Features |
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| XIE Shiqin,ZHAO Tianzhong,WANG Wei,MENG Jinghui and SHI Jingjing.Forest Structure Parameters Inversion Based on Image Texture and Spectral and Topographic Features[J].Transactions of the Chinese Society of Agricultural Machinery,2017,48(4):125-134. |
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| Authors: | XIE Shiqin ZHAO Tianzhong WANG Wei MENG Jinghui and SHI Jingjing |
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| Institution: | Beijing Forestry University,Beijing Forestry University,State Forestry Administration Survey Planning and Design Institute,Beijing Forestry University and State Forestry Administration Survey Planning and Design Institute |
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| Abstract: | Taking the SPOT5 satellite images of Heilongjiang Province and national forest inventory data as data source, the image texture, spectral features and topographic information of the sample plots were obtained, forest information of sample plots survey data was extracted as the true value. Through multiple linear regression analysis, forest structural parameters (forest stand quadratic mean diameter, basal area, stand volume and species diversity index) estimation models were established by combination of texture, spectral features and topographic information as independent variables, so as to select the optimal texture feature generation window and the optimal forest structure parameter inversion model. The results indicated that the texture, spectral features of SPOT5 images and forest structure parameters had a strong correlation, and the 9×9 window was the optimal texture generation window;the accuracy of the model was greatly improved after introducing the topographic factor. The estimation model of tree species diversity index R2adj was more than 0.72, and stand volume estimation model was the optimal model with R2adj of 0.864 and root mean square error of 21.260m3/hm2. The study suggested that using high resolution satellite image texture, spectral and topographic features to estimate the forest structural parameters had good application prospect. |
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| Keywords: | forest structure texture features spectral features topographic factors model estimation |
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