Identifying tree locations is a basic step in the derivation of other tree parameters using remote sensing techniques, particularly when using airborne laser scanning. There are several techniques for identifying tree...Identifying tree locations is a basic step in the derivation of other tree parameters using remote sensing techniques, particularly when using airborne laser scanning. There are several techniques for identifying tree positions. In this paper, we present a raster-based method for determining tree position and delineating crown coverage. We collected data from nine research plots that supported different mixes of species. We applied a raster-based method to raster layers with six different spatial resolutions and used terrestrial measurement data as reference data. Tree identification at a spatial resolution of 1.5 m was demonstrated to be the most accurate, with an average identification ratio (IR) of 95% and average detection ratio of 68% being observed. At a higher spatial resolution of 0.5 m, IR was overestimated by more than 600%. At a lower spatial resolution of 3 m, IR was underestimated at less than 44% of terrestrial measurements. The inventory process was timed to enable evaluation of the time efficiency of automatic methods.展开更多
Background: The distribution of forest vegetation within urban environments is critically important as it influences urban environmental conditions and the energy exchange through the absorption of solar radiation and...Background: The distribution of forest vegetation within urban environments is critically important as it influences urban environmental conditions and the energy exchange through the absorption of solar radiation and modulation of evapotranspiration. It also plays an important role filtering urban water systems and reducing storm water runoff.Methods: We investigate the capacity of ALS data to individually detect, map and characterize large(taller than15 m) trees within the City of Vancouver. Large trees are critical for the function and character of Vancouver’s urban forest. We used an object-based approach for individual tree detection and segmentation to determine tree locations(position of the stem), to delineate the shape of the crowns and to categorize the latter either as coniferous or deciduous.Results: Results indicate a detection rate of 76.6% for trees > 15 m with a positioning error of 2.11 m(stem location). Extracted tree heights possessed a RMSE of 2.60 m and a bias of-1.87 m, whereas crown diameter was derived with a RMSE of 3.85 m and a bias of-2.06 m. Missed trees are principally a result of undetected treetops occurring in dense, overlapping canopies with more accurate detection and delineation of trees in open areas.Conclusion: By identifying key structural trees across Vancouver’s urban forests, we can better understand their role in providing ecosystem goods and services for city residents.展开更多
为提高干形复杂树种材积无损估算的精度,利用地基激光雷达点云数据,构建基于人工蒙古栎最优削度模型的二元材积方程。以哈尔滨市城市林业示范基地的蒙古栎人工林为研究对象,使用地基激光雷达扫描获得完整点云数据,经过裁剪、高程归一化...为提高干形复杂树种材积无损估算的精度,利用地基激光雷达点云数据,构建基于人工蒙古栎最优削度模型的二元材积方程。以哈尔滨市城市林业示范基地的蒙古栎人工林为研究对象,使用地基激光雷达扫描获得完整点云数据,经过裁剪、高程归一化、滤波、单木分割和枝叶分离等处理提取树干结构参数。根据蒙古栎干形特征,选用6种削度方程模型(Biging(1984)、Amidon(1984)、孟宪宇(1982)、Kozak(2004)-Ⅱ、曾伟生等(1997)、Max and Burkhart(1976)),通过非线性回归拟合,筛选最优模型并构建削度-二元材积方程。研究结果表明,单木定位识别精度为95.22%,树高和胸径的提取值与实测值决定系数(R2)分别为0.97和0.98;最优削度模型拟合结果的决定系数(R^(2))和均方根误差(RMSE)分别为0.99和0.38 cm。所构建的蒙古栎削度-二元材积方程与现有材积计算方法进行残差分析表明,其估算结果具备可靠性,可为利用地基激光雷达点云数据估算干形复杂的树种材积提供重要技术支持。展开更多
根据点和多边形在表示和绘制物体上各自不同的特点,提出了一种有效绘制细节高度复杂物体的多分辨率方法.3D表面被映射到参数平面,经规则采样成为几何图像,P-Quadtrees是基于几何图像建立的四叉树多分辨率层次结构.通过对四叉树的遍历,...根据点和多边形在表示和绘制物体上各自不同的特点,提出了一种有效绘制细节高度复杂物体的多分辨率方法.3D表面被映射到参数平面,经规则采样成为几何图像,P-Quadtrees是基于几何图像建立的四叉树多分辨率层次结构.通过对四叉树的遍历,面向视点的表面用较大多边形面片绘制,光照细节通过法向映射完成;轮廓部分通过视点相关的LOD(level of detail)控制进行细化,使用点来绘制物体复杂精细的轮廓.通过此方法,细节复杂模型的绘制不仅可以被硬件加速,而且无论在表面还是在轮廓部分都能获得很好的视觉效果.展开更多
基金supported by the Scientific Grant Agency of the Ministry of Education,Science,Research and Sport of the Slovak Republicthe Slovak Academy of Sciences under Project No.1/0953/13:‘‘Geographic information on forest and forest landscape:creation and utilization of particularity’’
文摘Identifying tree locations is a basic step in the derivation of other tree parameters using remote sensing techniques, particularly when using airborne laser scanning. There are several techniques for identifying tree positions. In this paper, we present a raster-based method for determining tree position and delineating crown coverage. We collected data from nine research plots that supported different mixes of species. We applied a raster-based method to raster layers with six different spatial resolutions and used terrestrial measurement data as reference data. Tree identification at a spatial resolution of 1.5 m was demonstrated to be the most accurate, with an average identification ratio (IR) of 95% and average detection ratio of 68% being observed. At a higher spatial resolution of 0.5 m, IR was overestimated by more than 600%. At a lower spatial resolution of 3 m, IR was underestimated at less than 44% of terrestrial measurements. The inventory process was timed to enable evaluation of the time efficiency of automatic methods.
文摘Background: The distribution of forest vegetation within urban environments is critically important as it influences urban environmental conditions and the energy exchange through the absorption of solar radiation and modulation of evapotranspiration. It also plays an important role filtering urban water systems and reducing storm water runoff.Methods: We investigate the capacity of ALS data to individually detect, map and characterize large(taller than15 m) trees within the City of Vancouver. Large trees are critical for the function and character of Vancouver’s urban forest. We used an object-based approach for individual tree detection and segmentation to determine tree locations(position of the stem), to delineate the shape of the crowns and to categorize the latter either as coniferous or deciduous.Results: Results indicate a detection rate of 76.6% for trees > 15 m with a positioning error of 2.11 m(stem location). Extracted tree heights possessed a RMSE of 2.60 m and a bias of-1.87 m, whereas crown diameter was derived with a RMSE of 3.85 m and a bias of-2.06 m. Missed trees are principally a result of undetected treetops occurring in dense, overlapping canopies with more accurate detection and delineation of trees in open areas.Conclusion: By identifying key structural trees across Vancouver’s urban forests, we can better understand their role in providing ecosystem goods and services for city residents.
文摘为提高干形复杂树种材积无损估算的精度,利用地基激光雷达点云数据,构建基于人工蒙古栎最优削度模型的二元材积方程。以哈尔滨市城市林业示范基地的蒙古栎人工林为研究对象,使用地基激光雷达扫描获得完整点云数据,经过裁剪、高程归一化、滤波、单木分割和枝叶分离等处理提取树干结构参数。根据蒙古栎干形特征,选用6种削度方程模型(Biging(1984)、Amidon(1984)、孟宪宇(1982)、Kozak(2004)-Ⅱ、曾伟生等(1997)、Max and Burkhart(1976)),通过非线性回归拟合,筛选最优模型并构建削度-二元材积方程。研究结果表明,单木定位识别精度为95.22%,树高和胸径的提取值与实测值决定系数(R2)分别为0.97和0.98;最优削度模型拟合结果的决定系数(R^(2))和均方根误差(RMSE)分别为0.99和0.38 cm。所构建的蒙古栎削度-二元材积方程与现有材积计算方法进行残差分析表明,其估算结果具备可靠性,可为利用地基激光雷达点云数据估算干形复杂的树种材积提供重要技术支持。
文摘根据点和多边形在表示和绘制物体上各自不同的特点,提出了一种有效绘制细节高度复杂物体的多分辨率方法.3D表面被映射到参数平面,经规则采样成为几何图像,P-Quadtrees是基于几何图像建立的四叉树多分辨率层次结构.通过对四叉树的遍历,面向视点的表面用较大多边形面片绘制,光照细节通过法向映射完成;轮廓部分通过视点相关的LOD(level of detail)控制进行细化,使用点来绘制物体复杂精细的轮廓.通过此方法,细节复杂模型的绘制不仅可以被硬件加速,而且无论在表面还是在轮廓部分都能获得很好的视觉效果.
