蔡耀通, 林辉, 孙华, 等. 基于TanDEM-X数据的林分平均高反演方法研究[J]. 西南林业大学学报(自然科学), 2019, 39(5): 110–117 . DOI: 10.11929/j.swfu.201903121
引用本文: 蔡耀通, 林辉, 孙华, 等. 基于TanDEM-X数据的林分平均高反演方法研究[J]. 西南林业大学学报(自然科学), 2019, 39(5): 110–117 . DOI: 10.11929/j.swfu.201903121
Yaotong Cai, Hui Lin, Hua Sun, Meng Zhang, Jiangping Long. Stand Allocation High Inversion Method Based on TanDEM-X Data[J]. Journal of Southwest Forestry University, 2019, 39(5): 110-117. DOI: 10.11929/j.swfu.201903121
Citation: Yaotong Cai, Hui Lin, Hua Sun, Meng Zhang, Jiangping Long. Stand Allocation High Inversion Method Based on TanDEM-X Data[J]. Journal of Southwest Forestry University, 2019, 39(5): 110-117. DOI: 10.11929/j.swfu.201903121

基于TanDEM-X数据的林分平均高反演方法研究

Stand Allocation High Inversion Method Based on TanDEM-X Data

  • 摘要: 以TanDEM-X /TerraSAR-X HH单极化干涉对和GF-2遥感数据为基础,提出结合极化干涉与混合像元分解技术的改进差分法来反演林分平均高,并利用外业数据进行精度验证。结果表明:以植被丰度校正冠层高度模型,林分平均高的估测精度和R2值得到大幅提高,均方根误差也随之降低。因此,本研究提出的方法能有效降低林分低郁闭度产生的混合像元作用对林分平均高反演的影响,提高林分平均高的反演精度。

     

    Abstract: An improved differential method combining polarization interference and mixed pixel decomposition techniques is proposed to invert the average height of stands based on TanDEM-X/TerraSAR-X HH single-polarization interference pairs and GF-2 remote sensing data. And use the field data to verify accuracy. The results show that the canopy height model is corrected by vegetation abundance, the estimation accuracy and R2 value of the average height of the stand are greatly improved, and the root mean square error is also reduced. Therefore, the method proposed in this study can effectively reduce the influence of the mixed pixel function produced by the low canopy density of the stand on the average high inversion of the stand, and improve the average high inversion accuracy of the stand.

     

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