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    倾斜摄影测量技术提取落叶松人工林地形信息

    Extraction of topographic information of larch plantation by oblique photogrammetry

    • 摘要:
      目的林下地形是提取单木树高、冠幅等森林参数的必备条件,但由于林区地形起伏较大,传统的测量手段难以获取大范围高精度的森林地区数字地形模型(DTM)。近年来,倾斜摄影测量克服了传统测量技术的缺点,成为获取三维地理信息的新型手段。本文使用无人机倾斜摄影测量技术提取落叶松林下地形,并评测精度与适用性,为后续基于倾斜摄影测量技术提取单木参数的研究提供参考。
      方法选择内蒙古旺业甸林场内山区典型落叶松幼龄林、中龄林和成熟林林分在落叶季进行无人机飞行,采用Context Capture软件对获取的落叶季倾斜像片进行三维重建,生成林区点云。使用布料模拟滤波、加权线性最小二乘、渐进不规则三角网加密法、渐进形态学滤波算法从点云中提取地面点,并采用3种插值方法插值地面点生成测区完整地形。使用激光雷达DTM作为验证数据评价精度。
      结果不同算法的地形提取精度与郁闭度相关。在幼龄林区域和中龄林区域,布料模拟滤波提取地面点的精度最高,决定系数(R2)均达到0.999,均方根误差(RMSE)分别为1.61 m和0.47 m;在成熟林区域,渐进三角网滤波效果最好,R2为0.999,RMSE为0.39 m。在不同郁闭度林分选择最优滤波算法基础上,比较不同插值方法生成的数字地形模型(DTM)精度,结果表明:在幼龄林和中龄林,布料模拟滤波点云后经不规则三角网(TIN)插值得到的DTM精度最高,RMSE分别为1.58 m和0.44 m;成熟林分渐进不规则三角网加密滤波后地面点经克里金(Kriging)法插值得到的DTM精度最高,RMSE为0.31 m。
      结论实验证明,倾斜摄影测量技术可用于落叶松林分地形提取。

       

      Abstract:
      ObjectiveThe underforest terrain is a necessary condition for extracting forest parameters such as individual tree height and crown width. However, due to the large terrain fluctuation of the forest area, it is difficult to obtain a large-scale and high-precision digital terrain model (DTM) of forest area by traditional measurement method. Oblique photogrammetry overcomes the shortcomings of traditional measurement technology and becomes a new method to obtain three-dimensional geographic information. In this paper, UAV oblique photogrammetry technology was used to extract the topography of larch forest, and its accuracy and applicability were evaluated. It provides a reference for subsequent research on extracting individual tree parameters based on oblique photogrammetry technology.
      MethodThe typical young, middle-aged and mature Larix forests in the mountainous area of Wangyedian Forest Farm in Inner Mongolia, northern China were selected for UAV flight in the deciduous season. The oblique images of the deciduous season were reconstructed by Context Capture software to generate point clouds in the forest area. Ground points were extracted from point clouds by cloth simulation filtering (CSF), weighted linear least squares (WLS), progressive irregular triangular network filtering (PTIN) and progressive morphological filtering (PMF), and three interpolation methods were used to interpolate ground points to generate complete topography in the survey area. DTM generated from LiDAR data was used to evaluate the extraction accuracy with validated data.
      ResultThe results showed that the accuracy of terrain extraction by different algorithms was related to canopy density. In young forest and middle-aged forest area, cloth simulation filter (CSF) had the highest accuracy in extracting ground points from photogrammetric point clouds, with the determination coefficient (R2) reaching 0.999 and the root mean square error (RMSE) reaching 1.61 m and 0.47 m, respectively. In mature forest area, progressive triangulated irregular network (PTIN) had the best effect, with R2 0.999 and RMSE 0.39 m. After selecting the optimal filtering algorithm for different canopy density forest stands, the DTM accuracy of different interpolation methods was compared. The results showed that in young and middle-aged forests, the DTMs both generated by the point clouds of cloth simulation filtering (CSF) and triangulated irregular network (TIN) interpolation had the highest precision, RMSE was 1.58 m and 0.44 m, respectively. In mature forest, the DTM generated by the point clouds of progressive triangulated irregular network flitering (PTIN) and kriging (KRG) interpolation had the highest precision, RMSE was 0.31 m.
      ConclusionResearch has shown that oblique photogrammetry can be used for topographic extraction of larch forests.

       

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