刘芳, 杨广斌. 基于鱼眼照片的森林郁闭度快速提取方法研究[J]. 西南林业大学学报, 2013, 33(2): 71-74. DOI: 10.3969/j.issn.2095-1914.2013.02.015
引用本文: 刘芳, 杨广斌. 基于鱼眼照片的森林郁闭度快速提取方法研究[J]. 西南林业大学学报, 2013, 33(2): 71-74. DOI: 10.3969/j.issn.2095-1914.2013.02.015
LIU Fang, YANG Guangbin. An Efficient Method for Extracting Forest Canopy Density from Fisheye Photos[J]. Journal of Southwest Forestry University, 2013, 33(2): 71-74. DOI: 10.3969/j.issn.2095-1914.2013.02.015
Citation: LIU Fang, YANG Guangbin. An Efficient Method for Extracting Forest Canopy Density from Fisheye Photos[J]. Journal of Southwest Forestry University, 2013, 33(2): 71-74. DOI: 10.3969/j.issn.2095-1914.2013.02.015

基于鱼眼照片的森林郁闭度快速提取方法研究

An Efficient Method for Extracting Forest Canopy Density from Fisheye Photos

  • 摘要: 采用Photoshop、ArcGIS等软件对利用鱼眼照片提取森林郁闭度的方法进行研究,通过照片裁切、灰度处理、影像重分类等处理,求算出森林郁闭度,将该郁闭度值与采用KMean的非监督分类方法及野外观测值进行比较,结果表明:本研究方法所得到的平均郁闭度为056,野外实测平均郁闭度为062,非监督分类平均郁闭度为065,两两之间差值均小于允许的误差范围010,证明该方法在森林郁闭度的测定中快速且有效可行。

     

    Abstract: Canopy density index is not only the important factor of determining forest management, but also one of the main technical parameters measuring forest management level. A method of extracting forest canopy density from the fisheye photos by using PhotoShop, ArcGIS software was studied, and the forest canopy density could be calculated through photo tailoring, greyness processing and image reclassifying. The values of forest canopy density obtained by this method were verified by comparing with the results of KMean unsupervised classification method and the field observation values. The results showed that when the average value of the forest canopy density calculated by this method was 056, the corresponding field observation value was 062, and that of obtained by the unsupervised classification method was 0.65. The differences between any of the two values were less than the permissible error range of 010, indicating that the new method was efficient and practicable.

     

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