Accuracy assessment of lidar-derived digital elevation models

Despite the relatively high cost of airborne lidar-derived digital elevation models (DEMs), such products are usually presented without a satisfactory associated estimate of accuracy. For the most part, DEM accuracy estimates are typically provided by comparing lidar heights against a finite sample of check point coordinates from an independent source of higher accuracy, supposing a normal distribution of the derived height differences or errors. This paper proposes a new methodology to assess the vertical accuracy of lidar DEMs using confidence intervals constructed from a finite sample of errors computed at check points. A non-parametric approach has been tested where no particular error distribution is assumed, making the proposed methodology especially applicable to non-normal error distributions of the type usually found in DEMs derived from lidar. The performance of the proposed model was experimentally validated using Monte Carlo simulation on 18 vertical error data-sets. Fifteen of these data-sets were computed from original lidar data provided by the International Society for Photogrammetry and Remote Sensing Working Group III/3, using their respective filtered reference data as ground truth. The three remaining data-sets were provided by the Natural Environment Research Council's Airborne Research and Survey Facility lidar system, together with check points acquired using high precision kinematic GPS. The results proved promising, the proposed models reproducing the statistical behaviour of vertical errors of lidar using a favourable number of check points, even in the cases of data-sets with non-normally distributed residuals. This research can therefore be considered as a potentially important step towards improving the quality control of lidar-derived DEMs.     

Estimation of covariance matrix from geochemical data with observations below detection limits

Multivariate statistical analyses have been extensively applied to geochemical measurements to analyze and aid interpretation of the data. Estimation of the covariance matrix of multivariate observations is the first task in multivariate analysis. However, geochemical data for the rare elements, especially Ag, Au, and platinum-group elements, usually contain observations the below detection limits. In particular, Instrumental Neutron Activation Analysis (INAA) for the rare elements produces multilevel and possibly extremely high detection limits depending on the sample weight. Traditionally, in applying multivariate analysis to such incomplete data, the observations below detection limits are first substituted, for example, each observation below the detection limit is replaced by a certain percentage of that limit, and then the standard statistical computer packages or techniques are used to obtain the analysis of the data. If a number of samples with observations below detection limits is small, or the detection limits are relatively near zero, the results may be reasonable and most geological interpretations or conclusions are probably valid. In this paper, a new method is proposed to estimate the covariance matrix from a dataset containing observations below multilevel detection limits by using the marginal maximum likelihood estimation (MMLE) method. For each pair of variables, sayY andZ whose observations containing below detection limits, the proposed method consists of three steps: (i) for each variable separately obtaining the marginal MLE for the means and the variances, , , , and forY andZ: (ii) defining new variables by and and lettingA=C+D andB=C–D, and obtaining MLE for variances, and forA andB; (iii) estimating the correlation coefficient _YZ by and the covariance _YZ by . The procedure is illustrated by using a precious metal geochemical data set from the Fox River Sill, Manitoba, Canada.     

基于图像特征的烟叶分级

讨论了基于图像特征的烤烟烟叶分级系统的建模及其实现，给出了烟叶分级模型的数学描述，探讨了模型库的优化和特征隶属度及烟叶模式的可信度的计算问题，并通过试验分析了FTGS系统的性能和有效性。     

古洪水流量的误差计算

古洪水研究已在大型工程和长江三峡，黄河小浪底等的设计洪水中得到动用取得了令人虚心成功，但古洪水流量的推求与实测量的计算往往有大的差别，根据随机误差的传播给出了一般情况下的古洪不流量推误差计算公式，以小流底２３６０ａＢＰ古洪水注同误差的计算为例，对最终计算出的古洪水流量成果给出了一个误差范围。     

物理实验中的不确定度评定

阐述了不确定度的定义、来源、分类及用不确定度评定测量结果的一些表示方法。分析了误差和不确定度的区别。最终给出了测量不确定度的评定。     

基于珠海实证的城市旅游增长极限分析框架

城市旅游是城市的一个开放、高流动的子系统,在一定时期内是相对稳定,有增长极限的。城市旅游增长极限受到供需极限影响,当旅游需求超过供给时,出现过度旅游;而当供给超过需求,就会导致过度旅游化。城市旅游需求增长极限呈现阶梯式,只有当影响城市旅游需求增长的长期因素发生持续重大变化时,城市旅游需求增长才可能突破原有的极限,进入一个新的阶段。城市旅游需求极限规定了城市旅游供给极限,决定了城市在一定时期内适合开发的景区、酒店、餐饮、购物等旅游设施规模。本文基于珠海的实证分析表明,过去十几年,由于旅游供需两方面影响因素缺乏持续重大的变化,城市功能和地位、城市主题和特色等因素相对稳定,加之受到区域其他城市的激烈竞争,珠海中高端旅游需求相对稳定,星级酒店等中高端旅游产品面临增长极限。此时,新增旅游景区和星级酒店并不会带来过夜旅游需求的实质增长,反而可能加剧现阶段旅游供需的失衡,造成过度旅游化。本文也讨论了超越旅游极限的条件以及旅游增长与旅游发展的关系,并进一步建议了旅游统计的改革举措。     

GPS卫星原子钟频率稳定度表征方法分析

原子钟频率稳定度的表征通常在时域和频域进行,而对于“尺度域”小波方差表征方法的分析研究较少。对该方法进行系统归纳总结的基础上,给出时域尺度域两类不同表征方法的实用计算公式及其置信度计算方法,通过对各种方差特性的比较分析,指出其适用范围。分析表明：时域系列方差计算简单、直接,各具特点,可以满足不同的实际需要;尺度域的小波方差是一种具有独特优越性的新方法,但可以达到时域表征方法的效果,适用于进行原子钟频率稳定度的估计。