共查询到20条相似文献，搜索用时 31 毫秒
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Research presented here explores the feasibility of leveraging vegetation data derived from airborne light detection and ranging (LiDAR) and terrestrial laser scanning (TLS) for visibility modeling. Using LiDAR and TLS datasets of a lodgepole pine (Pinus contorta) dominant ecosystem, tree canopy and trunk obstructions were isolated relevant to a discrete visibility beam in a short‐range line‐of‐sight model. Cumulative obstruction factors from vegetation were compared with reference visibility values from digital photographs along sightline paths. LiDAR‐derived tree factors were augmented with single‐scan TLS data for obstruction prediction. Good correlation between datasets was found up to 10 m from the terrestrial scanner, but fine scale visibility modeling was problematic at longer distances. Analysis of correlation and regression results reveal the influence of obstruction shadowing inherent to discrete LiDAR and TLS, potentially limiting the feasibility of modeling visibility over large areas with similar technology. However, the results support the potential for TLS‐derived subcanopy metrics for augmenting large amounts of aerial LiDAR data to significantly improve models of forest structure. Subtle LiDAR processing improvements, including more accurate tree delineation through higher point density aerial data, combined with better vegetation quantification processes for TLS data, will advance the feasibility and accuracy of data integration. 相似文献
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激光雷达是一种监测大气颗粒物分布和传输的有效遥感手段，能够克服常规地面监测站零星分布、无法实现区域覆盖监测的问题。通过布设一台垂直探测激光雷达和一台水平扫描激光雷达，实现大气颗粒物的垂直结构探测以及半径6 km内水平分布情况监测，并结合斜率法和Fernald算法实现更加精确的水平方向消光系数反演，进而实现以三维数据分析颗粒物的传输、分布和浓度变化情况；并利用地面国控站点数据同水平消光系数进行相关性对比。结果表明，利用三维大气探测激光雷达能够有效地揭示城市地区较大区域内的颗粒物分布和传输情况，具有覆盖范围大、探测效率高的优点。 相似文献
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城区机载LiDAR数据与航空影像的自动配准 总被引：2，自引：0，他引：2
为解决机载LiDAR数据与航空影像集成应用中二者的配准问题,提出了一种机载LiDAR数据与航空影像配准的方法。首先,直接在LiDAR点云中提取建筑物3维轮廓线,通过将轮廓线规则化得到由两条相互垂直的直线段组成的建筑物角特征,并在航空影像上提取直线特征;然后,根据影像初始外方位元素将建筑物角特征投影到航空影像上,并采用一定的相似性测度在影像上寻找同名的影像角特征;最后,将角特征的角点当作控制点,利用传统的摄影测量光束法区域网平差解求影像新的外方位元素。解算过程中采用循环迭代策略。本方法的主要特点是,直接从LiDAR点云中提取线特征,避免了常规方法从距离图(或强度图)中提取线特征所产生的内插误差。通过与现有基于点云强度图的配准方法的对比实验表明,在低精度初始外方位元素的辅助下,本文方法能够达到较高的配准精度。 相似文献
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ABSTRACTLight detection and ranging (LiDAR) data are essential for scientific discoveries such as Earth and ecological sciences, environmental applications, and responding to natural disasters. While collecting LiDAR data over large areas is quite possible the subsequent processing steps typically involve large computational demands. Efficiently storing, managing, and processing LiDAR data are the prerequisite steps for enabling these LiDAR-based applications. However, handling LiDAR data poses grand geoprocessing challenges due to data and computational intensity. To tackle such challenges, we developed a general-purpose scalable framework coupled with a sophisticated data decomposition and parallelization strategy to efficiently handle ‘big’ LiDAR data collections. The contributions of this research were (1) a tile-based spatial index to manage big LiDAR data in the scalable and fault-tolerable Hadoop distributed file system, (2) two spatial decomposition techniques to enable efficient parallelization of different types of LiDAR processing tasks, and (3) by coupling existing LiDAR processing tools with Hadoop, a variety of LiDAR data processing tasks can be conducted in parallel in a highly scalable distributed computing environment using an online geoprocessing application. A proof-of-concept prototype is presented here to demonstrate the feasibility, performance, and scalability of the proposed framework. 相似文献
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机载LiDAR数据逐航带平差与航带区域网平差对比 总被引：1，自引：0，他引：1
机载LiDAR系统获取的点云数据在经过预处理解算后仍会残余部分系统误差,因此,在利用点云数据生成DEM等相关数字产品之前,必须检查并改正这部分系统误差。以此为主要目标,本文对机载LiDAR数据的逐航带平差与航带区域网平差展开研究,并以Microsoft Visual Studio 2008 C++为开发平台、基于实测数据对比了两者在完成多航带构成的测区平差时的精度,结果表明:机载LiDAR数据的航带区域网平差方法相较于LZD算法可有效降低逐航带平差导致的误差累积,精度更高。 相似文献
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结合机载、星载激光雷达对GLAS(地球科学激光测高系统)光斑范围内的森林地上生物量进行估测,并利用MODIS植被产品以及MERIS土地覆盖产品进行了云南省森林地上生物量的连续制图。机载LiDAR扫描的260个训练样本用于构建星载GLAS的森林地上生物量估测模型,模型的决定系数(R2)为0.52,均方根误差(RMSE)为31Mg/ha。研究结果显示,云南省总森林地上生物量为12.72亿t,平均森林地上生物量为94Mg/ha。估测的森林地上生物量空间分布情况与实际情况相符,森林地上生物量总量与基于森林资源清查数据的估测结果相符,表明了利用机载LiDAR与星载ICESatGLAS结合进行大区域森林地上生物量估测的可靠性。 相似文献
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机载激光雷达数据的误差分析及校正 总被引：2，自引：2，他引：2
数据质量分析是遥感机理/应用研究（尤其是定量遥感）首要和关键的一步,直接影响遥感反演的精度和遥感应用的效果。激光雷达（Light Detection and Ranging,LiDAR）是一种新兴的主动遥感技术,对数据后处理算法的研究还有待进一步加强,尤其对激光雷达数据的质量分析显得十分迫切。采用了一种基于扫描航带间重叠区数据分析的方法对LiDAR数据质量进行评价,分析误差来源,计算误差的大小,并分别对数据的随机和系统误差进行校正。以机载激光雷达数据为例来进行验证,实验结果表明,这种方法能有效地减少数据误差,达到提高数据质量的目的。 相似文献
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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, RMSEr = 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
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The development of robust and accurate methods for automatic registration of optical imagery and 3D LiDAR data continues to be a challenge for a variety of applications in photogrammetry, computer vision and remote sensing. This paper proposes a new approach for the registration of optical imagery with LiDAR data based on the theory of Mutual Information (MI), which exploits the statistical dependency between same- and multi-modal datasets to achieve accurate registration. The MI-based similarity measures quantify dependencies between aerial imagery, and both LiDAR intensity data and 3D point cloud data. The needs for specific physical feature correspondences, which are not always attainable in the registration of imagery with 3D point clouds, are avoided. Current methods for registering 2D imagery to 3D point clouds are first reviewed, after which the mutual MI approach is presented. Particular attention is given to adoption of the Normalised Combined Mutual Information (NCMI) approach as a means to produce a similarity measure that exploits the inherently registered LiDAR intensity and point cloud data so as to improve the robustness of registration between optical imagery and LiDAR data. The effectiveness of local versus global similarity measures is also investigated, as are the transformation models involved in the registration process. An experimental program conducted to evaluate MI-based methods for registering aerial imagery to LiDAR data is reported and the results obtained in two areas with differing terrain and land cover, and with aerial imagery of different resolution and LiDAR data with different point density are discussed. These results demonstrate the potential of the MI and especially the CMI methods for registration of imagery and 3D point clouds, and they highlight the feasibility and robustness of the presented MI-based approach to automated registration of multi-sensor, multi-temporal and multi-resolution remote sensing data for a wide range of applications. 相似文献
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目前LiDAR技术已经成为DTM的主要生产方法。地面误差对LiDAR生成DTM的精度影响比较明显,特别是由于亚热带森林植被覆盖区LiDAR激光点云少,生成的DTM更复杂,需要分析地面误差对LiDAR生成林下DTM的精度影响。本文以华南农业大学增城教学科研基地为研究对象,从森林郁闭度和坡度两个方面探讨了地面误差对机载LiDAR数据生成林下DTM精度的影响。研究结果发现高程误差会随郁闭度的增大而增大;而随坡度变化趋势不明显,但是坡度为15°时成为误差的分水岭,其前后误差差异比较明显。总体而言,郁闭度的影响更为明显。 相似文献
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The accurate estimation of leaf water content (LWC) and knowledge about its spatial variation are important for forest and agricultural management since LWC provides key information for evaluating plant physiology. Hyperspectral data have been widely used to estimate LWC. However, the canopy reflectance can be affected by canopy structure, thereby introducing error to the retrieval of LWC from hyperspectral data alone. Radiative transfer models (RTM) provide a robust approach to combine LiDAR and hyperspectral data in order to address the confounding effects caused by the variation of canopy structure. In this study, the INFORM model was adjusted to retrieve LWC from airborne hyperspectral and LiDAR data. Two structural parameters (i.e. stem density and crown diameter) in the input of the INFORM model that affect canopy reflectance most were replaced by canopy cover which could be directly obtained from LiDAR data. The LiDAR-derived canopy cover was used to constrain in the inversion procedure to alleviate the ill-posed problem. The models were validated against field measurements obtained from 26 forest plots and then used to map LWC in the southern part of the Bavarian Forest National Park in Germany. The results show that with the introduction of prior information of canopy cover obtained from LiDAR data, LWC could be retrieved with a good accuracy (R2 = 0.87, RMSE = 0.0022 g/cm2, nRMSE = 0.13). The adjustment of the INFORM model facilitated the introduction of prior information over a large extent, as the estimation of canopy cover can be achieved from airborne LiDAR data. 相似文献
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为克服传统农田土地平整测量方法耗时费力的特点，提出采用LiDAR技术对农田地形进行重建的探索性研究。通过HDL-32E型激光雷达等搭建了系统的硬件平台，应用C++语言编写了系统数据的采集程序；在此基础上对激光雷达所采集数据进行了标定，研究了农田地形重建系统中不同坐标系的转换方法；同时基于最小值去噪法设计了更适用于农田地形点云去噪的均值限差去噪法。通过对比在农田起伏较大区域不同坡度范围内RTK与激光雷达所测单元个数，对系统精度进行了评价；最后实现了车载农田地形重建系统的界面显示、应用与精度评估。结果表明，在10°~15°、25°~30°大坡度范围内激光雷达所获农田地形更为丰富，精度更高。该方法重建的农田地形模型点云数据和原始农田地形点云数据投影面积逼近度可达93%，验证了本文研究方法应用于农田地形环境重建的可行性，同时为今后的土地精细平整工作提供了理论参考与依据。 相似文献
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激光雷达技术（Light Detection and Ranging,LiDAR）是近十年来快速发展并得到广泛应用的测量手段。美国地质调查局（USGS）、美国国家宇航局（NASA）以及美国地质学会（AASG）已经开始讨论建设全美高分辨率激光雷达数据库。我国正处于东部城市化、土地利用巨变、西部无图而经济高速发展的时期,国家、地方、企业生产单位迫切需要现实性强、精确度高、比例尺大的地形数据产品。满足这些要求的主要途径是采用激光雷达这一先进的测绘技术。我们建议国家、地方与企业统筹规划,各司其职,努力建设我国的激光雷达基础数据库。本文通过Stoker等（2008）介绍的第二届全美激光雷达战略研讨会上论述的激光雷达技术特点、激光雷达数据的科学需求与应用以及商业化运作问题,结合我国目前的激光雷达发展趋势、测绘数据需求以及土地利用变化监测等科学问题,简析激光雷达技术在我国的应用前景。 相似文献
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Nowadays, Geostatistics and its various interpolation techniques have become a major threshold area in the field of research
in GIS. In this research work poorly sampled (less accurate height data relative to ICESat/GLAS height data) Cartosat-1 height
data has been used with well sampled (more accurate height data relative to Cartosat-1 height data) ICESat/GLAS LiDAR (Light
Detection and Ranging) height point data using Cokriging Interpolation technique, to study the effect of ICESat/GLAS on Cartosat-1
height data. Space borne LiDAR data has led researchers to explore its utilities in many applications. Space borne LiDAR data
can be acquired through space borne LiDAR sensors also, like; GLAS (Geoscience Laser Altimeter System) system onboard ICESat
(Ice, Cloud and land Elevation Satellite) satellite. In this study, it has been tried to apply Cokriging interpolation on
two different sources of data sets, with a common variable (elevation) to generate DES and assessment of this surface has
been conducted by DGPS data. After optimizing Cokriging parameters, results of digital elevation surface (DES) generated using
Cokriging showed that RMSE has been second least than global polynomial in comparison to Kriging interpolation RMSE after
being evaluated by GPS values. So, global polynomial as well as cokriging interpolation technique out performs while comparing
with kriging technique for DES generation. 相似文献
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地面LiDAR不仅能够快速获得建筑物表面精确三维坐标点云信息,并且利用自身所携带的相机同时采集建筑物的影像信息,这使得地面LiDAR在城市三维建模与古建筑精细模型制作中得到广泛应用。然而地面Li-DAR采集的点云数据巨大,离散点之间没有关系,这给建模带来了困难。本文通过将地面LiDAR数据进行预处理得到建筑物点云数据,再通过移动最小二乘法来拟合建筑面构建建筑物模型,实验证明移动最小二乘法拟合得到的建筑物模型光滑准确,能够将建筑物的细节信息表达出来。 相似文献