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地图手工数字化对点误差的统计分布

定义了对点误差,导出了统计分布密度和分布函数,给出了矩母函数、特征函数和数字特征,以及对点误差及其投影分量和标准化分布。     

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Exploring the sensitivity of coastal inundation modelling to DEM vertical error

As sea level is projected to rise throughout the twenty-first century due to climate change, there is a need to ensure that sea level rise (SLR) models accurately and defensibly represent future flood inundation levels to allow for effective coastal zone management. Digital elevation models (DEMs) are integral to SLR modelling, but are subject to error, including in their vertical resolution. Error in DEMs leads to uncertainty in the output of SLR inundation models, which if not considered, may result in poor coastal management decisions. However, DEM error is not usually described in detail by DEM suppliers; commonly only the RMSE is reported. This research explores the impact of stated vertical error in delineating zones of inundation in two locations along the Devon, United Kingdom, coastline (Exe and Otter Estuaries). We explore the consequences of needing to make assumptions about the distribution of error in the absence of detailed error data using a 1 m, publically available composite DEM with a maximum RMSE of 0.15 m, typical of recent LiDAR-derived DEMs. We compare uncertainty using two methods (i) the NOAA inundation uncertainty mapping method which assumes a normal distribution of error and (ii) a hydrologically correct bathtub method where the DEM is uniformly perturbed between the upper and lower bounds of a 95% linear error in 500 Monte Carlo Simulations (HBM+MCS). The NOAA method produced a broader zone of uncertainty (an increase of 134.9% on the HBM+MCS method), which is particularly evident in the flatter topography of the upper estuaries. The HBM+MCS method generates a narrower band of uncertainty for these flatter areas, but very similar extents where shorelines are steeper. The differences in inundation extents produced by the methods relate to a number of underpinning assumptions, and particularly, how the stated RMSE is interpreted and used to represent error in a practical sense. Unlike the NOAA method, the HBM+MCS model is computationally intensive, depending on the areas under consideration and the number of iterations. We therefore used the HBM+ MCS method to derive a regression relationship between elevation and inundation probability for the Exe Estuary. We then apply this to the adjacent Otter Estuary and show that it can defensibly reproduce zones of inundation uncertainty, avoiding the computationally intensive step of the HBM+MCS. The equation-derived zone of uncertainty was 112.1% larger than the HBM+MCS method, compared to the NOAA method which produced an uncertain area 423.9% larger. Each approach has advantages and disadvantages and requires value judgements to be made. Their use underscores the need for transparency in assumptions and communications of outputs. We urge DEM publishers to move beyond provision of a generalised RMSE and provide more detailed estimates of spatial error and complete metadata, including locations of ground control points and associated land cover.     

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中国建设用地与区域社会经济发展关系的空间计量研究

利用空间计量模型,对中国大陆地区的30个省、市、自治区2008年的建设用地面积与社会经济发展之间的关系进行了研究。研究表明:30个省、直辖市和自治区地区建设用地面积、GDP、总人口和城市化率都有显著的空间相关特征,一个区域社会经济的发展不仅会驱动自身区域建设用地的扩张,而且会带动邻近区域的建设用地的增长。传统上只从时间维度出发的研究思路,忽视空间维度的相关性和异质性,低估了区域社会经济发展对建设用地增长的作用,必须在普通面板线性回归模型中描述的基础上引入空间变量进行修正。计量模型检验表明,城市化水平对建设用地总规模的影响不甚显著。说明中国大部分省份的农村居民点用地的利用效率普遍偏低。因此,农村居民点用地的调整与优化已迫在眉睫,从长远看来,提高城市化水平,打破城乡二元化的土地制度,建立统一的土地市场,是缓解土地资源紧缺、提高土地利用效率的有效途径。     

基于相关分析的组合导航RAIM模型研究

探讨基于相关分析理论的组合导航RIAM方法,并给出单个和多个探测粗差的相关分析检验流程。通过模拟12颗GPS和Galileo组合导航卫星定位系统,分别给单颗和两颗正常卫星加入粗差。仿真结果表明：观测值的影响向量与残差的相关系数可以定位含粗差的卫星并将粗差卫星予以剔除。     

基于典型相关分析的变化检测中变化阈值的确定

以东营市为例 ,把基于典型相关分析的方法运用于多时相遥感影像的变化检测中。对于变化阈值的确定 ,采用了一种基于贝叶斯理论的最小错误率的方法。这种方法实质上是一种非监督分类的方法 ,即不需要地面实况数据或其它先验知识 ,直接对典型相关处理后的差值图像进行分析计算得到阈值 ,使变化检测的错误率达到最小。实验结果证明了这种方法的有效性。     

高精度大幅面图纸分块扫描拼接技术研究

针对当前大幅面图纸分块扫描拼接中存在的问题,提出一种基于改正扫描仪误差的大幅图纸整体平差的拼接方法.该方法通过平移黑白相间的格网板建立扫描仪的误差模型,同时利用少量的控制点及连接点,然后通过整体平差来直接解求各扫描图像块的几何变换参数.实践证明这种方法具有拼接精度高、速度快以及可不限图幅大小等优点.