汪康宁, 马婷, 吕杰. 基于随机森林算法的凉水自然保护区蓄积量反演研究[J]. 西南林业大学学报, 2016, 36(5): 125-129. DOI: 10.11929/j.issn.2095-1914.2016.05.021
引用本文: 汪康宁, 马婷, 吕杰. 基于随机森林算法的凉水自然保护区蓄积量反演研究[J]. 西南林业大学学报, 2016, 36(5): 125-129. DOI: 10.11929/j.issn.2095-1914.2016.05.021
Wang Kangning, Ma Ting, Lv Jie. Stock Volume Estimation Research Based on Random Forest Algorithm in Liangshui Nature Reserve[J]. Journal of Southwest Forestry University, 2016, 36(5): 125-129. DOI: 10.11929/j.issn.2095-1914.2016.05.021
Citation: Wang Kangning, Ma Ting, Lv Jie. Stock Volume Estimation Research Based on Random Forest Algorithm in Liangshui Nature Reserve[J]. Journal of Southwest Forestry University, 2016, 36(5): 125-129. DOI: 10.11929/j.issn.2095-1914.2016.05.021

基于随机森林算法的凉水自然保护区蓄积量反演研究

Stock Volume Estimation Research Based on Random Forest Algorithm in Liangshui Nature Reserve

  • 摘要: 以黑龙江凉水自然保护区为研究对象,采用GF1卫星遥感影像为数据源,提取遥感影像在不同窗口大小下的纹理特征信息,与遥感影像自身的光谱信息相结合;利用随机森林算法,结合地面蓄积量采样点数据,建立凉水自然保护区蓄积量反演模型。结果表明:只基于卫星光谱的反演模型的相关系数为059,基于卫星光谱与纹理特征的蓄积量反演模型的相关系数为065;当窗口大小为3 × 3时,森林蓄积量反演效果最好。研究表明,基于卫星光谱信息和纹理特征信息,利用随机森林算法进行森林蓄积量反演在森林资源调查方面具有良好的应用前景。

     

    Abstract: This research taking Liangshui Nature Reserve in Heilongjiang as study area, using GF1 satellite image as data source, textural features under different window sizes and spectral feature were extracted from GF1 image. Forest stock volume inversion model were constructed using random forest algorithm and Liangshui forest volume data obtained by field investigation. Experimental results showed the coefficient of determination R2 was 059 for the spectrally based volume estimation model, and the coefficient of determination R2 was 065 for the spectral and textural feature combining model. When window size is set to 3 × 3, the forest stock volume inversion model achieves the best result. The result indicate that forest stock volume estimation based on spectral and textural feature from satellite image using random forests has potential application in forest inventory.

     

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