Estimating the spatial distribution,extent and potential lignocellulosic biomass supply of Trees Outside Forests in Baden-Wuerttemberg using airborne LiDAR and OpenStreetMap data     

《International Journal of Applied Earth Observation and Geoinformation》2017

Trees Outside Forests (TOF) represent a source of lignocellulosic biomass that has received increasing attention in the recent years. While some studies have already investigated the potential of TOF in Germany, a spatial explicit analysis, specifically for Baden-Wuerttemberg, is still lacking. We used a unique wall-to-wall airborne Light Detection and Ranging (LiDAR) dataset combined with OpenStreetMap (OSM) data to map and classify TOF of the federal state of Baden-Wuerttemberg (∼35.000 km²) in south-western Germany. Furthermore, from annual biomass potentials of TOF areas collected from available literature, we calculated the mean annual biomass supply for all TOF areas in Baden-Wuerttemberg. This combination of remote sensing-based classification and available literature resulted in a mean annual biomass supply between ∼490,000–730,000 t from TOF in Baden-Wuerttemberg. The classification congruence on three reference sites was very high (∼99%) using a simple filter technique applied to the LiDAR data and masking man-made objects using OSM data. In contrast, the available literature revealed a high variability of biomass potentials, supporting the demand for an inventory system. Still, the results demonstrate the applicability of LiDAR based vegetation mapping and the value of OSM data in Baden-Wuerttemberg to detect man-made objects.  相似文献   

Retrieving aboveground biomass of wetland Phragmites australis (common reed) using a combination of airborne discrete-return LiDAR and hyperspectral data     

《International Journal of Applied Earth Observation and Geoinformation》2017

Wetland biomass is essential for monitoring the stability and productivity of wetland ecosystems. Conventional field methods to measure or estimate wetland biomass are accurate and reliable, but expensive, time consuming and labor intensive. This research explored the potential for estimating wetland reed biomass using a combination of airborne discrete-return Light Detection and Ranging (LiDAR) and hyperspectral data. To derive the optimal predictor variables of reed biomass, a range of LiDAR and hyperspectral metrics at different spatial scales were regressed against the field-observed biomasses. The results showed that the LiDAR-derived H_p99 (99th percentile of the LiDAR height) and hyperspectral-calculated modified soil-adjusted vegetation index (MSAVI) were the best metrics for estimating reed biomass using the single regression model. Although the LiDAR data yielded a higher estimation accuracy compared to the hyperspectral data, the combination of LiDAR and hyperspectral data produced a more accurate prediction model for reed biomass (R² = 0.648, RMSE = 167.546 g/m², RMSE_r = 20.71%) than LiDAR data alone. Thus, combining LiDAR data with hyperspectral data has a great potential for improving the accuracy of aboveground biomass estimation.  相似文献   

基于车载LiDAR点云的地物分类方法的研究     

邵帅  刘春晓  周光耀  井文胜 《测绘与空间地理信息》2017,(2):198-201

基于点云分类常用的近邻聚类法和物体表面分割等方法,本文提出了一种基于最大网格密度的近邻聚类的方法。该方法首先对原始点云进行低点提取,设置格网的大小,在此基础上对点云数据进行去噪并进行主成分分析,再对点云空间进行均匀格网化,使具有最大密度的格网为聚类中心,加入高程、强度以及法向量等特征对分割后的点云实现了不同地物的分类,提高了运算效率,降低了错分率。  相似文献   

Using low-density discrete Airborne Laser Scanning data to assess the potential carbon dioxide emission in case of a fire event in a Mediterranean pine forest     

Antonio Luis Montealegre-Gracia  María Teresa Lamelas-Gracia  Alberto García-Martín  Juan de la Riva-Fernández  Francisco Escribano-Bernal 《地理信息系统科学与遥感》2017,54(5):721-740

The aim of study is to map the carbon dioxide (CO₂) emission of the aboveground tree biomass (AGB) in case of a fire event. The suitability of low point density, discrete, multiple-return, Airborne Laser Scanning (ALS) data and the influence of several characteristics of these data and the study area on the results obtained have been evaluated. A sample of 45 circular plots representative of Pinus halepensis Miller stands were used to fit and validate the model of AGB. The ALS point clouds were processed to obtain the independent variables and a multivariate linear regression analysis between field data and ALS-derived variables allowed estimation of AGB. Then, the influence of several characteristics on the residuals of the model was analyzed. Finally, conversion factors were applied to obtain the CO₂ values. The AGB model presented a R² value of 0.84 with a relative root-mean-square error of 27.35%. This model included ALS variables related to vegetation height variability and to canopy density. Terrain slope, aspect, canopy cover, scan angle and the number of laser returns did not influence AGB estimations at plot level.  相似文献   

半自动机载LiDAR点云建筑物三维重建方法   总被引：1，自引：1，他引：0  

周平华  熊彪 《测绘科学》2017,42(5)

针对全自动建筑物3D重建存在需要后续人工检验,且发现重建错误需要花费额外时间修改的问题,提出了一种半自动的面向对象的机载LiDAR点云建筑物3D重建方法。基于建筑物类别点云的联通分析和平面生长分割结果,提出了自动的建筑物栋数检测、单栋建筑物外轮廓提取、单栋建筑物内部结构线提取方法;同时,在计算机无法完成部分工作时,人工辅助计算机完成高程阶越线提取、识别建筑物屋顶附属物点云等工作。实验证明,该方法可以适用于高密度机载LiDAR点云数据中城区大部分建筑物的3D模型重建。  相似文献   

一种利用点云邻域信息的建筑物屋顶面高精度自动提取方法   总被引：1，自引：0，他引：1  

赵传  张保明  陈小卫  郭海涛  卢俊 《测绘学报》2017,46(9):1123-1134

从LiDAR数据中高精度地提取建筑物屋顶面是构建屋顶面拓扑关系、实现建筑物三维模型重建的关键。本文针对现有算法提取复杂建筑物屋顶面适应性较差、精度较低等问题,提出了一种利用点云邻域信息的建筑物屋顶面高精度自动提取方法。通过主成分分析计算点云特征,构建特征直方图,选取可靠种子点;利用提出的局部点云法向量分布密度聚类算法聚类种子点,快速准确地提取初始屋顶面片;构建基于邻域信息的投票模型,有效地解决屋顶面竞争现象。试验结果表明,本文方法可自动、高精度地提取屋顶面,对不同复杂程度的建筑物具有较好的适应性,能为建筑物三维模型重建提供可靠的屋顶面信息。  相似文献   

基于LiDAR的海岛岸线自动提取研究     

郑真真  徐爱功  徐辛超 《测绘与空间地理信息》2017,40(9)

为了探讨栅格化方法与图像分割法对海岛岸线提取的效果,本文主要研究了基于Li DAR数据利用这两种方法对某岛进行瞬时海岸线的提取。利用栅格化方法通过对Li DAR点云数据进行粗差剔除、滤波去噪、构建Terrain数据集、创建栅格表面、生成TIN模型及自动生成等高线,从而实现了瞬时海岸线的提取;利用图像分割法是通过对Li DAR点云数据进行粗差剔除、滤波处理、构建TIN模型、生成二值栅格图像、图像处理与图像边缘提取的过程实现瞬时海岸线的提取。对两种方法提取的海岸线进行叠加显示分析,试验结果表明:两种方法提取的海岸线形态结构基本吻合,海岸线提取效率较传统方法均有提高,但栅格化方法提取的海岸线比图像分割方法提取的海岸线更平滑、更细化,边缘信息较为丰富,与实际海岸线更贴切,效果更加理想。  相似文献   

基于法向量密度聚类的LiDAR点云屋顶面提取     

赵传  张保明  郭海涛  陈小卫 《测绘科学技术学报》2017,34(4)

针对现有算法从LiDAR点云中提取复杂建筑物屋顶面不完整、阈值难以设置的问题,提出一种结合点云空间分布的法向量密度聚类提取屋顶面点云方法。通过构建Delaunay三角网,计算建筑物LiDAR点云的法向量;在分析建筑物点云空间和法向量分布特点的基础上,定义一种邻域关系度量屋顶面点云之间的相似性,并利用提出的算法聚类建筑物点云,得到屋顶面片点云粗提取结果;通过构建屋顶面片缓冲区,经面片处理得到建筑物各屋顶面的完整点云。选取不同复杂程度的建筑物进行实验,结果表明,算法能有效提取复杂建筑物屋顶面点云,具有较好的适应性,并能为建筑物三维重建提供可靠的屋顶面信息。  相似文献   

融合点、对象、关键点等3种基元的点云滤波方法     

林祥国  张继贤  宁晓刚  段敏燕  臧艺 《测绘学报》2016,45(11):1308-1317

基元是影响点云滤波精度和效率的关键因素之一。本文提出了一种基于多基元的三角网渐进加密(MPTPD)滤波方法。它包括点云分割、对象关键点提取、基于关键点的对象类别判别3个主要阶段,且3个阶段的基元分别为点、对象、关键点。使用了4景机载激光雷达和摄影测量点云数据对MPTPD、三角网渐进加密(TPD)、基于对象的三角网渐进加密(OTPD)3种滤波方法进行了性能测试。试验表明,MPTPD方法具有整体上最优的性能:在精度方面,MPTPD与OTPD两种方法的精度相当,MPTPD方法的一类误差I、总误差T比TPD的相应误差分别低约22.07%和8.44%;在效率方面,多数情况下TPD、MPTPD、OTPD方法的效率依次降低,且MPTPD的平均耗时是OTPD平均耗时的57.93%。  相似文献   

机载LiDAR定位精度分析     

覃昕垚  张建军  王勇  方涛 《测绘工程》2016,25(5):32-35,41

介绍机载激光雷达测量技术,根据测量的几何原理推导定位方程。讨论定位的误差来源,建立误差模型并对误差影响进行分析。综合各项因素的影响,将模拟数据代入误差传播公式,计算定位精度。  相似文献