首页> 外文期刊>International journal of remote sensing >Stand volume estimation by combining low laser-sampling density LiDAR data with QuickBird panchromatic imagery in closed-canopy Japanese cedar (Cryptomeria japonica) plantations
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Stand volume estimation by combining low laser-sampling density LiDAR data with QuickBird panchromatic imagery in closed-canopy Japanese cedar (Cryptomeria japonica) plantations

机译:通过将低激光采样密度LiDAR数据与QuickBird全色图像相结合来估算林冠日本柳杉(人工柳杉)人工林中的林分积

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摘要

This study proposes a simple method for stand volume estimation by combining low laser-sampling density Light Detection and Ranging (LiDAR) data (i.e. 1 hit per 4 m~2) with high-resolution optical imagery (i.e. 0.6 m) in coniferous plantations. The study area was in closed-canopy, mountainous, Japanese cedar (Cryptomeria japonica) plantations on undulating terrain at an elevation of 135-391 m above sea level. A total of 25 circular plots (0.04 ha) were established and stand volumes within plots were investigated in the field. The field-measured, plot-level stand volume ranged from 262.8 to 984.0 m~3 ha~(-1) and the average value was 555.7 m~3 ha~(-1). We used the measurements as validation data to evaluate estimates derived from an empirical regression model that was constructed on the basis of the allometry between crown diameter and diameter at breast height (DBH) from previous research. As a result, stand volume at various stand conditions could be estimated precisely regardless of different laser footprint sizes of 0.16-0.47 m when combining low-density LiDAR data with QuickBird panchromatic imagery. The maximum random error and root mean square error (RMSE) in stand volume estimates by data combination were 10% and 39% of the average stand volume, respectively. Thus, this method based on allometry and using low-density LiDAR data and high-resolution optical imagery could be capable of offering precise stand volume estimates in coniferous forests in different localities.
机译:这项研究提出了一种简单的方法,通过将针叶人工林中的低激光采样密度光检测和测距(LiDAR)数据(即每4 m〜2命中1次)与高分辨率光学图像(即0.6 m)相结合。研究区域位于海拔135-391 m的起伏地形中的封闭树冠,山区,日本雪松(日本柳杉)人工林中。总共建立了25个圆形样地(0.04公顷),并在田间调查了样地内的林分体积。实地测绘的林分蓄积量为262.8至984.0 m〜3 ha〜(-1),平均值为555.7 m〜3 ha〜(-1)。我们将这些测量值用作验证数据,以评估从经验回归模型得出的估计值,该模型是根据先前研究的冠径和胸高直径(DBH)之间的异度法构建的。结果,当将低密度LiDAR数据与QuickBird全色图像结合使用时,无论0.16-0.47 m的激光足迹尺寸大小如何,都可以精确估算各种支架条件下的支架体积。通过数据组合估算的林分体积估计的最大随机误差和均方根误差(RMSE)分别为平均林分体积的10%和39%。因此,这种基于异速测量法并使用低密度LiDAR数据和高分辨率光学图像的方法,能够在不同地区的针叶林中提供准确的林分蓄积量估计。

著录项

  • 来源
    《International journal of remote sensing》 |2010年第5期|1281-1301|共21页
  • 作者单位

    Forestry and Forest Products Research Institute, 1, Matsunosato, Tsukuba, Ibaraki 305-8687, Japan;

    rnRiver Basin Research Centre, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan;

    rnForestry and Forest Products Research Institute, 1, Matsunosato, Tsukuba, Ibaraki 305-8687, Japan;

    Japan International Research Centre for Agricultural Sciences, 1-1 Ohwashi, Tsukuba,Ibaraki 305-8686, Japan;

    rnResearch Institute for Humanity and Nature, 457-4 Motoyama, Kamigamo, Kita-ku,Kyoto 603-8047, Japan;

    rnJapan International Research Centre for Agricultural Sciences, 1-1 Ohwashi, Tsukuba,Ibaraki 305-8686, Japan;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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