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Fourier Transform Analysis of Very High Resolution Remote Sensed Imagery Shows Potential for Estimating Stand Density of Regular-spaced Planted Forests

机译:非常高分辨率遥感图像的傅里叶变换分析显示估算常规间距种植森林的立体密度的可能性

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摘要

An increase in the area of unthinned planted forests is a major issue in Japan, and incomplete record-keeping means that a method for detecting unthinned stands is required. An important indicator of unthinned stands is stand density. In this study, we compared two stand density estimation methods, the discrete Fourier transform method and the local maximum (LM) filtering method, using simulated very high resolution satellite imagery. Even-aged Japanese cedar (Cryptomeria japonica) stands were modeled. Trees were positioned as though planted in a lattice pattern typical of these forests in Japan. The discrete Fourier transform method was more accurate than LM filtering and was stable over a range of stand densities, whereas the accuracy of LM filtering was sensitive to stand density and calculation conditions. Hence, the discrete Fourier transform was superior to LM filtering to estimate even-aged coniferous stand density.
机译:未定种植森林面积的增加是日本的主要问题,不完整的记录保存意味着需要一种用于检测不定位的立场的方法。 一个重要指标的未定名立体是立体密度。 在这项研究中,我们比较了两个站立密度估计方法,离散傅里叶变换方法和局部最大(LM)滤波方法,使用模拟非常高分辨率卫星图像。 均匀的日本雪松(Gryptomeria japonica)的立场被建模。 树木被定位在日本这些森林的典型格子图案中种植。 离散的傅里叶变换方法比LM滤波更精确,并且在一系列静止密度范围内稳定,而LM滤波的精度对静止密度和计算条件敏感。 因此,离散的傅里叶变换优于LM滤波,以估计均匀老化的针叶耐性密度。

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