Assessment of the impacts of surface topography, off-nadir pointing and vegetation structure on vegetation lidar waveforms using an extended geometric optical and radiative transfer model

In order to prioritize the measurement requirements and accuracies of the two new lidar missions, a physical model is required for a fundamental understanding of the impact of surface topography, footprint size and off-nadir pointing on vegetation lidar waveforms and vegetation height retrieval. In this study, we extended a well developed Geometric Optical and Radiative Transfer (GORT) vegetation lidar model to take into account for the impacts of surface topography and off-nadir pointing on vegetation lidar waveforms and vegetation height retrieval and applied this extended model to assess the aforementioned impacts on vegetation lidar waveforms and height retrieval.Model simulation shows that surface topography and off-nadir pointing angle stretch waveforms and the stretching effect magnifies with footprint size, slope and off-nadir pointing angle. For an off-nadir pointing laser penetrating vegetation over a slope terrain, the waveform is either stretched or compressed based on the relative angle. The stretching effect also results in a disappearing ground peak return when slope or off-nadir pointing angle is larger than the “critical slope angle”, which is closely related to various vegetation structures and footprint size. Model simulation indicates that waveform shapes are affected by surface topography, off-nadir pointing angle and vegetation structure and it is difficult to remove topography effects from waveform extent based only on the shapes of waveform without knowing any surface topography information.Height error without correction of surface topography and off-nadir pointing angle is the smallest when the laser beams at the toward-slope direction and the largest from the opposite direction. Further simulation reveals within 20° of slope and off-nadir pointing angle, given the canopy height as roughly 25 m and the footprint size as 25 m, the error for vegetation height (RH100) ranges from − 2 m to greater than 12 m, and the error for the height at the medium energy return (RH50) from − 1 m to 4 m. The RH100 error caused by unknown surface topography and without correction of off-nadir pointing effect can be explained by an analytical formula as a function of vegetation height, surface topography, off-nadir pointing angle and footprint size as a first order approximation. RH50 is not much affected by topography, off-nadir pointing and footprint size. This forward model simulation can provide scientific guidance on prioritizing future lidar mission measurement requirements and accuracies.     

Physically based vertical vegetation structure retrieval from ICESat data: Validation using LVIS in White Mountain National Forest, New Hampshire, USA

Vegetation structure retrieval accuracies from spaceborne Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud and land Elevation Satellite (ICESat) data are affected by surface topography, background noise and sensor saturation. This study uses a physical approach to remove surface topography effect from lidar returns to retrieve vegetation height from ICESat/GLAS data over slope terrains. Slope-corrected vegetation heights from ICESat/GLAS data were compared to airborne Laser Vegetation Imaging Sensor (LVIS) (20 m footprint size) and small-footprint lidar data collected in White Mountain National Forest, NH. Impact of slope on LVIS vegetation height estimates was assessed by comparing LVIS height before and after slope correction with small-footprint discrete-return lidar and field data.Slope-corrected GLAS vegetation heights match well with 98 percentile heights from small-footprint lidar (R² = 0.77, RMSE = 2.2 m) and top three LVIS mean (slope-corrected) heights (R² = 0.64, RMSE = 3.7 m). Impact of slope on LVIS heights is small, however, comparison of LVIS heights (without slope correction) with either small footprint lidar or field data indicates that our scheme improves the overall LVIS height accuracy by 0.4-0.7 m in this region. Vegetation height can be overestimated by 3 m over a 15° slope without slope correction. More importantly, both slope-corrected GLAS and LVIS height differences are independent of slope. Our results demonstrate the effectiveness of the physical approach to remove surface topography from large footprint lidar data to improve accuracy of maximum vegetation height estimates.GLAS waveforms were compared to aggregated LVIS waveforms in Bartlett Experimental Forest, NH, to evaluate the impact of background noise and sensor saturation on vegetation structure retrievals from ICESat/GLAS. We found that GLAS waveforms with sensor saturation and low background noise match well with aggregated LVIS waveforms, indicating these waveforms capture vertical vegetation structure well. However, waveforms with large noise often lead to mismatched waveforms with LVIS and underestimation of waveform extent and vegetation height. These results demonstrate the quality of ICESat/GLAS vegetation structure estimates.     

A threshold insensitive method for locating the forest canopy top with waveform lidar

Lidars have the unique ability to make direct, physical measurements of forest height and vertical structure in much denser canopies than is possible with passive optical or short wavelength radars. However the literature reports a consistent underestimate of tree height when using physically based methods, necessitating empirical corrections. This bias is a result of overestimating the range to the canopy top due to background noise and failing to correctly identify the ground.This paper introduces a method, referred to as “noise tracking”, to avoid biases when determining the range to the canopy top. Simulated waveforms, created with Monte-Carlo ray tracing over geometrically explicit forest models, are used to test noise tracking against simple thresholding over a range of forest and system characteristics. It was found that noise tracking almost completely removed the bias in all situations except for very high noise levels and very low (< 10%) canopy covers. In all cases noise tracking gave lower errors than simple thresholding and had a lower sensitivity to the initial noise threshold.Finite laser pulses spread out the measured signal, potentially overriding the benefit of noise tracking. In the past laser pulse length has been corrected by adding half that length to the signal start range. This investigation suggests that this is not always appropriate for simple thresholding and that the results for noise tracking were more directly related to pulse length than for simple thresholding. That this effect has not been commented on before may be due to the possible confounding impacts of instrument and survey characteristics inherent in field data. This method should help improve the accuracy of waveform lidar measurements of forests, whether using airborne or spaceborne instruments.     

利用SPOT图象阴影提取城市建筑物高度及其分布信息

在分析SPOT卫星图象阴影与建筑物实际高度关系的基础上,阐述了依据图象建筑物来估算城市建筑物高度的原理和方法,进而探讨了以数据融合为手段的,从SPOT全色图象中准确界定阴影范围的方法,并以此为基础,研究出了一种基于图象阴影特征的城市建筑物高分级及其分布信息自生成技术,在以北京市为例的试验中,建筑物高度分级结果的抽样验证准确率达80％以上,显示出卫星遥感在城市应用方面的巨大潜力。     

A reactive GRASP and path relinking for a combined production–distribution problem

An NP-hard production–distribution problem for one product over a multi-period horizon is investigated. The aim is to minimize total cost taking production setups, inventory levels and distribution into account. An integer linear model is proposed as a compact problem specification but it cannot be solved to optimality for large instances. Instead of using a classical two-phase approach (production planning and then route construction for each day), metaheuristics that simultaneously tackle production and routing decisions are developed: a GRASP (greedy randomized adaptive search procedure) and two improved versions using either a reactive mechanism or a path-relinking process. These algorithms are evaluated on 90 randomly generated instances with 50, 100 and 200 customers and 20 periods. The results confirm the interest of integrating production and distribution decisions, compared to classical two-phase methods. Moreover, reaction and path-relinking give better results than the GRASP alone.     

厚煤层大采高采场煤壁的破坏规律与失稳机理

基于大采高采场煤壁稳定性控制需要,在现场实测基础上,采用数值模拟分析了煤层采动裂隙的发展演化规律,并用滑移线理论分析了煤壁失稳的力学过程.研究表明:仅含层理煤层的采动剪切破坏面由倾向相反的共轭面组成;含节理煤层中,硬煤的采动破坏面为剪切破坏面与节理张裂面组成的倾向相反的共轭面,软煤采动破坏面为倾向采空区的单向平面;超前塑性区内硬煤的后继剪切破坏面仍为倾向相反的共轭面,软煤内则为倾向煤壁的单向平面.采用塑性滑移线确定了煤壁片帮的危险范围,影响煤壁失稳的主要因素为端面距与砌体梁结构的回转变形压力.     

墩高对连续梁桥抗震性能的影响

以南水北调中线工程中某预应力混凝土连续梁桥为例,采用有限元程序MIDAS建立了考虑和不考虑桩土作用的两种有限元计算模型,选取5,10,15,20,25 m等5个墩身高度,采用反应谱分析法,分析在顺桥向及横桥向地震输入下不同墩身高度对结构的自振周期、制动墩和非制动墩的墩顶位移、墩底内力、墩顶内力的影响规律,以及桩土作用效应随墩身高度的变化规律,可为同类桥梁结构的抗震设计提供理论依据.     

世界已建高坝大库统计分析

为了解和掌握世界范围内的高坝大库建设情况,统计全球已建成的特大型高坝大库资料。在此基础上,根据地区、坝型和建成年代对高坝大库有关特征进行分析,总结了世界高坝大库的地区分布规律、主要坝型和历史建设趋势,得出如下结论:世界高坝大库工程主要分布于亚洲、欧洲、北美洲;高坝的坝型通常是混凝土拱坝、堆石坝和混凝土重力坝,而形成特大水库的大坝多为混凝土重力坝、堆石坝和混凝土拱坝;高坝大库工程基本上建成于1945年以后,目前世界高坝大库的建设中心已转移至中国。     

水闸底流消能计算公式的分析与改进

以上海市东风西沙水库下游水闸消能设计为例,对水闸消能计算中遇到的问题加以分析后发现,在上游水位不变、过闸单宽流量不变、下游水深较小的情况下,下游水深越小,采用《水闸设计规范》(SL265—2001)中的消能计算公式计算得到的消力池深度反而越小,这与实际情况有较大的出入。通过理论推算,对原计算公式进行了修正,并采用修正后的计算公式进行了消能计算,计算结果与实际情况相符。     

坐标转换在悬高测量中的应用

悬高测量是在目标点底部设置棱镜测量距离,再测定目标点的垂直角,计算出目标点的高程(高度)。但在目标点底部无法设置棱镜,悬高测量就无法进行。为此,文章介绍的悬高测量方法、计算原理和计算公式较好地解决了以上问题。同时讨论了其实际测量中的注意事项。