基于细化地表模型的地表长度测量方法改进

基于不规则三角网的数字地形分析原理,提出了线状地物的地表长度测量方法,针对该方法中平坦三角形引起的测长误差,引入了细化地表模型,对三种地形分别进行改进,并通过理论误差分析和长城长度测量试验,验证了该改进方法的可行性和精度。     

Comparison of Extrapolation and Interpolation Methods for Estimating Daily Photosynthetically Active Radiation(PAR)——A Case Study of the Poyang Lake National Nature Reserve,China

Measurements of photosynthetically active radiation(PAR),which are indispensable for simulating plant growth and productivity,are generally very scarce.This study aimed to compare two extrapolation and one interpolation methods for estimating daily PAR reaching the earth surface within the Poyang Lake national nature reserve,China.The daily global solar radiation records at Nanchang meteorological station and daily sunshine duration measurements at nine meteorological stations around Poyang Lake were obtain...     

GIS中随机误差点位不确定性描述法研究

考虑到G IS分析决策时后续计算的简便性,以及不确定性描述的简单性,本文罗列了点位精度描述的多种方法,包括数学描述以及计算置信度的方法,用直观的二维(三维)图形对抽象的点位质量可视化,并进行分析比较。为简化各种描述点位精度的置信度计算,以采用k值所对应的描述误差椭圆的概率值为置信度为前提,对各种描述方法进行分类和比较,得出结论:在各种描述点位精度的方法中,点位均方向误差和误差区间,形式很简单,容易描述和参与计算。其中,点位均方向误差和区间表示法具有较强的实用性、简易性、灵活性、优势互补性,很适合来描述G IS中随机误差点位不确定性。     

基于路径的聚类分析

聚类分析的很多算法中都采用连接两点直线的欧氏距离来判断空间亲疏性,然而当有障碍物层存在时,连接两点的直线已不能完全表达它们之间的关系,特别是当有指定的交通路线时,两点之间的连通路径和距离必须遵从特定的路径。文中讨论在了障碍物或指定的交通路线存在的情况下点集的聚类分析,给出了解决有障碍物或指定交通路线时进行聚类分析的算法PathClust。     

一种适应局部密度变化的空间聚类方法

研究一种适应空间局部密度变化的空间聚类算法(简称ADBSC).在该算法中,首先提出一种新的空间局部密度度量方法,即k-空间近邻最大距离,而为了表达空间局部密度变化特征,引入距离变化率概念,用于度量邻近目标间空间局部密度变化情况.然后将所有空间邻近的距离变化率小于给定变化率阈值的空间目标标记为局部密度相等,再将空间邻近的局部密度相等的空间目标聚为一类,得到空间聚类结果.并给出ADBSC算法的详细描述和计算过程.最后,通过模拟实验和实际算例,对提出的方法进行验证.结果表明,该算法能够自动适应空间位置的局部密度变化,适应不同形态的空间簇,而且比DBSCAN算法更实用.     

一种顾及邻近域内实体间距离的空间异常检测新方法

空间异常检测已成为空间数据挖掘和知识发现的一个重要研究内容.空间异常蕴含着许多意想不到的知识,现有的空间异常检测方法大多依据空间邻近域的非空间属性差异来计算偏离因子,忽略了邻近域内空间实体间距离的影响.本文首先讨论了空间邻近域内实体间距离对空间异常检测的影响,在此基础上,提出了一种顾及邻近域内实体间距离的空间异常度量方法--SOM法,并分析了它的复杂度.由于该方法是利用实体非空间属性的加权内插值与实测值的差值作为度量空间异常程度的参数,从而顾及了邻近域内所有实体相互间距离对非空间属性偏离的影响,并且克服了现有检测方法在不均匀分布空间实体集内寻找空间异常的缺陷.最后,通过一个实际算例验证了所提方法的可行性和正确性.     

宽水域地区长边三角高程测量试验精度分析

本文介绍在水网和长距离(2Km左右)跨江跨河地区，进行四等三角高程测量的试验研究。通过对观测方法和设备的改进以及进一步实验研究，有望实现更长距离和更高精度的跨江跨河三角高程测量以及取代现有的跨河水准测量。     

The utility of travelling when destinations are heterogeneous. How much better is the next destination as one travels further?

In many studies travel behaviour (for example, commuting) is analysed on the basis of a utility function with the distance (d) travelled as one of the arguments. An example is U=U(d,Y-cd,T-td) where Y and T denote money and time constraints, and c and t money and time costs per unit distance. This standard approach is not without problems, however, since it ignores the fundamental fact that most transport has a derived character: travelling kilometres is not an activity that gives utility per se, but only because these kilometres bring people to certain places they want to visit. In this paper we develop a method that provides a justification for utility functions such as shown here by showing that these can be made consistent with theories that take into account the derived character of transport.     

Distance predicting functions and applied location-allocation models.

Distances between demand points and potential sites for implementing facilities are essential inputs to location-allocation models. Computing actual road distances for a given problem can be quite burdensome since it involves digitalizing a network, while approximating these distances by l _p -norms, using for instance a geographical information system, is much easier. We may then wonder how sensitive the solutions of a location-allocation model are to the choice of a particular metric. In this paper, simulations are performed on a lattice of 225 points using the k-median problem. Systematic changes in p and in the orientation of the orthogonal reference axes are used. Results suggest that the solutions of the k-median are rather insensitive to the specification of the l _p -norm. Received: 12 October 1998/Accepted: 17 September 1999     

The effect of spatial distance on the discriminability of colors in maps

ABSTRACT

The spatial distance (gap) between map symbols can have a great impact on their discriminability, however, there is little empirical evidence to establish spatial and attribute thresholds. In this paper, we examine the effect of the spatial gap in discriminability of color hue and value, that is, we conducted an online study to obtain performance metrics; then an eye-tracking study to understand participants’ strategies and cognitive processes. Participants completed two experimental tasks (compare two areas and decide if their color is the same; and compare three areas and rank them from the lightest to the darkest). The color distances and the spatial distances were strictly controlled for the compared areas. Our analyses confirmed that, overall, increasing the gap between colors has a consistent negative impact on the ability to differentiate them with both sequential and qualitative schemes. Furthermore, we observed that sequential schemes require larger color distances than qualitative schemes for discriminability. Finally, our results suggested that for qualitative colors, the largest tested color distance ?E₀₀ = 10 yields considerably higher levels of accuracy in color discrimination (even when the spatial gap between the two colors is large), thus we recommend ?E₀₀ = 10 to practicing cartographers and other information visualization designers.