Combining Geo‐SOM and Hierarchical Clustering to Explore Geospatial Data

Geo‐SOM is a useful geovisualization technique for revealing patterns in spatial data, but is ineffective in supporting interactive exploration of patterns hidden in different Geo‐SOM sizes. Based on the divide and group principle in geovisualization, the article proposes a new methodology that combines Geo‐SOM and hierarchical clustering to tackle this problem. Geo‐SOM was used to “divide” the dataset into several homogeneous subsets; hierarchical clustering was then used to “group” neighboring homogeneous subsets for pattern exploration in different levels of granularity, thus permitting exploration of patterns at multiple scales. An artificial dataset was used for validating the method's effectiveness. As a case study, the rush hour motorcycle flow data in Taipei City, Taiwan were analyzed. Compared with the best result generated solely by Geo‐SOM, the proposed method performed better in capturing the homogeneous zones in the artificial dataset. For the case study, the proposed method discovered six clusters with unique data and spatial patterns at different levels of granularity, while the original Geo‐SOM only identified two. Among the four hierarchical clustering methods, Ward's clustering performed the best in pattern discovery. The results demonstrated the effectiveness of the approach in visually and interactively exploring data and spatial patterns in geospatial data.     

Modeling and Communicating the Conceptual Intent of Geo‐Analytical Tasks for Human‐GIS Interaction

One of the fundamental issues of geographical information science is to design GIS interfaces and functionalities in a way that is easy to understand, teach, and use. Unfortunately, current geographical information systems (including ArcGIS) remains very difficult to use as spatial analysis tools, because they organize and expose functionalities according to GIS data structures and processing algorithms. As a result, GIS interfaces are conceptually confusing, cognitively complex, and semantically disconnected from the way human reason about spatial analytical activities. In this article, we propose an approach that structures GIS analytical functions based on the notion of “analytical intent”. We describe an experiment that replaces ArcGIS desktop interface with a conversational interface, to enable mixed‐initiative user‐system interactions at the level of analytical intentions. We initially focus on the subset of GIS functions that are relevant to “finding what's inside” as described by Mitchell, but the general principles apply to other types of spatial analysis. This work demonstrates the feasibility of delegating some spatial thinking tasks to computational agents, and also raises future research questions that are key to building a better theory of spatial thinking with GIS.     

A GIS‐Based Site Identification for the Seasonal Storage of Solar Heating: Promises and Pitfalls

This research presents the use of GIS to identify potential locations of the Seasonal Storage of Solar Heating (S³H) within the state of Pennsylvania. The S³H utilizes a large pit to store thermal energy collected during the warm months for later use in the cold months. To maximize its overall efficiency, S³H must be built where several locational parameters occur in unison: abandoned mine lands (AMLs), institutions, soil type, and land use. These parameters were mapped using GIS with potential locations identified through the application of neighborhood statistics. Potential locations were verified through the use of aerial photographs, hillshades, and site visitations. The verification process revealed spatial inaccuracies associated with the AML dataset. As a result, the horizontal positional accuracy of AMLs was tested according to the Geospatial Positioning Accuracy Standards – National Standard for Spatial Data Accuracy (NSSDA). Results indicate larger than expected positional offset for a dataset that is crucial to funding the reclamation of AMLs.     

ASPHAA: A GIS‐Based Algorithm to Calculate Cell Area on a Latitude‐Longitude (Geographic) Regular Grid

One characteristic of a Geographic Information System (GIS) is that it addresses the necessity to handle a large amount of data at multiple scales. Lands span over an area greater than 15 million km² all over the globe and information types are highly variable. In addition, multi‐scale analyses involve both spatial and temporal integration of datasets deriving from different sources. The currently worldwide used system of latitude and longitude coordinates could avoid limitations in data use due to biases and approximations. In this article a fast and reliable algorithm implemented in Arc Macro Language (AML) is presented to provide an automatic computation of the surface area of the cells in a regularly spaced longitude‐latitude (geographic) grid at different resolutions. The approach is based on the well‐known approximation of the spheroidal Earth's surface to the authalic (i.e. equal‐area) sphere. After verifying the algorithm's strength by comparison with a numerical solution for the reference spheroidal model, specific case studies are introduced to evaluate the differences when switching from geographic to projected coordinate systems. This is done at different resolutions and using different formulations to calculate cell areas. Even if the percentage differences are low, they become relevant when reported in absolute terms (hectares).     

A GIS‐based multi‐criteria seismic vulnerability assessment using the integration of granular computing rule extraction and artificial neural networks

This study proposes multi‐criteria group decision‐making to address seismic physical vulnerability assessment. Granular computing rule extraction is combined with a feed forward artificial neural network to form a classifier capable of training a neural network on the basis of the rules provided by granular computing. It provides a transparent structure despite the traditional multi‐layer neural networks. It also allows the classifier to be applied on a set of rules for each incoming pattern. Drawbacks of original granular computing (GrC) are covered, where some input patterns remained unclassified. The study was applied to classify seismic vulnerability of the statistical units of the city of Tehran, Iran. Slope, seismic intensity, height and age of the buildings were effective parameters. Experts ranked 150 randomly selected sample statistical units with respect to their degree of seismic physical vulnerability. Inconsistency of the experts' judgments was investigated using the induced ordered weighted averaging (IOWA) operator. Fifty‐five classification rules were extracted on which a neural network was based. An overall accuracy of 88%, κ = 0.85 and R² = 0.89 was achieved. A comparison with previously implemented methodologies proved the proposed method to be the most accurate solution to the seismic physical vulnerability of Tehran.     

VGDI – Advancing the Concept: Volunteered Geo‐Dynamic Information and its Benefits for Population Dynamics Modeling

The concept of Volunteered Geographic Information (VGI) has progressed from being an exotic prospect to making a profound impact on GIScience and geography in general, as initially anticipated. However, while massive and manifold data is continuously produced voluntarily and applications are built for information and knowledge extraction, the initially introduced concept of VGI lacks certain methodological perspectives in this regard which have not been fully elaborated. In this article we highlight and discuss an important gap in this concept, i.e. the lack of formal acknowledgment of temporal aspects. By coining the proposed advanced framework ‘Volunteered Geo‐Dynamic Information’ (VGDI), we attempt to lay the ground for full conceptual and applied spatio‐temporal integration. To illustrate that integrative approach of VGDI and its benefits, we describe the potential impact on the field of dynamic population distribution modeling. While traditional approaches in that domain rely on survey‐based data and statistics as well as static geographic information, the use of VGDI enables a dynamic setup. Foursquare venue and user check‐in data are presented for a test site in Lisbon, Portugal. Two core modules of spatio‐temporal population assessment are thereby addressed, namely time use profiling and target zone characterization, motivated by the potential integration in existing population dynamics frameworks such as the DynaPop model.     

An open source GIS‐based Planning Support System: Application to the land use plan of La Troncal,Ecuador

Planning Support Systems (PSS) comprise a wide variety of geo‐technological tools related to GIS and spatial modeling aimed at addressing land planning processes. This article describes the OpenRules system, a PSS based on a previous system called RULES. Among OpenRules new features are its architecture, based exclusively on free and open source software, and its applicability to all land use types, including rural and urban uses. In addition, OpenRules incorporates an unlimited number of land evaluation factors and a new objective in land use spatial allocation. OpenRules has been programmed in Java and implemented as a module of the free GIS software gvSIG, with full integration between the GIS and the decision support tools. Decision support tools include multicriteria evaluation, multiobjective linear programming and heuristic techniques, which support three basic stages of land use planning processes, namely land suitability evaluation, land use area optimization and land use spatial allocation. The application of OpenRules to the region of La Troncal, Ecuador, demonstrates its capability to generate alternative and coherent solutions through a scientific and justified procedure at low cost in terms of time and resources.     

基于Agent的游览路线设计与模拟

本文以庐山游客游览路线智能模拟为研究实例,从游客个体的微观层次出发,解决了庐山旅游路线空间数据库的构建、游客agent游览路线模拟概念模型的构建、游客agent行为规则的定量化,以及游客agent游览路线模拟的实现等关键技术问题。研究结果表明,游客游览过程的动态模拟能够直观反映游客的旅游路线,基于Re-past建模仿真平台的游客agent空间行为模型结合了Agent与GIS,实现游客游览路线过程的动态模拟,有效改善了GIS的空间行为过程模拟功能,为游客选择更优游览路线的提供合理参考。     

航空重力测量数据向下延拓基于信噪比的正则化方法的研究

本文研究了正则化方法在航空重力测量数据向下延拓问题中的应用。首先对这种不适定问题的线性模型,分析了设计阵的复共线性结构与其对参数估计危害之间的关系,利用参数LS估计的信噪比提取了各个参数是否受到复共线性严重危害的信息,从而在一定程度上揭示了设计阵复共线性结构的特征。然后提出了基于信噪比的正则化方法（SNR）,以信噪比为依据构造正则化矩阵,以极小化均方误差为目标选取正则化参数。本文构造正则化矩阵无需利用附加物理或先验信息,这对于在缺乏此类信息的情况下运用正则化方法提供了新的手段。最后进行了数值试验,结果表明,本文提出的新方法（SNR）比普通的正则化方法（OR）在滤噪和保真方面表现更佳。     

A Clustering‐Based Approach to the Capacitated Facility Location Problem1

This research develops a clustering‐based location‐allocation method to the Capacitated Facility Location Problem (CFLP), which provides an approximate optimal solution to determine the location and coverage of a set of facilities to serve the demands of a large number of locations. The allocation is constrained by facility capacities – different facilities may have different capacities and the overall capacity may be inadequate to satisfy the total demands. This research transforms this special location‐allocation problem into a clustering model. The proposed approach has two parts: (1) the allocation of demands to facilities considering capacity constraints while minimizing the cost; and (2) the iterative optimization of facility locations using an adapted K‐means clustering method. The quality of a location‐allocation solution is measured using an objective function, which is the demand‐weighted distance from demand locations to their assigned facilities. The clustering‐based method is evaluated against an adapted Genetic Algorithm (GA) alternative, which integrates the allocation component as described above but uses GA operations to search for ‘optimal’ facility locations. Experiments and evaluations are carried out with various data sets (including both synthetic and real data).     

基于建筑角点的机载和车载点云数据配准

提出一种基于建筑角点的机载和车载点云数据配准方法。首先采用随机抽样一致性算法(Random Sample Consensus,RANSAC)对建筑面片进行稳健估计,结合建筑轮廓在二维平面上投影的拟合直线,解算出建筑角点的三维坐标。利用提取到的同名角点,采用六参数转换模型计算机载和车载点云数据间的空间转换参数,进而完成机载和车载点云数据的配准。实验表明,该方法能有效地提取建筑角点,实现机载和车载点云数据的精确配准。     

基于土地适宜性评价与元胞自动机模型的城市开发边界划定方法

城市开发边界的划定可以在一定程度上引导城市空间的良性扩张。为了研究边界划定的方法,以我国某港口城市作为研究区域,在空间增长模拟的方向进行探索。研究中借助土地适宜性评价和元胞自动机边界工具,构建既符合生态资源环境要求又符合城市发展需要的边界划定,同时,为了实现城市用地健康和动态管控举措,提出了建立健全土地用地管理机制的要求。     

联立偏度与峰度变化曲线的机载LiDAR点云滤波方法

针对经典滤波算法易受参数、阈值选取影响以及传统偏度平衡方法滤波结果不理想等问题,提出一种联立偏度与峰度变化曲线的机载LiDAR点云二次滤波方法。该方法不受参数与阈值选取影响,在联立初始LiDAR点云二者基础上,通过在其变化曲线上寻找最优偏度平衡点完成一次滤波;然后对初次滤波后获取地面点进行多项式曲面拟合,根据拟合后的高差统计值进行偏度平衡二次滤波。实验结果表明:该方法能保证变化很小的前提下,减少和总误差,滤波效果更好。     

基于生命周期理论的地理信息产业发展相关问题研究

依据产业生命周期理论,用定性的方法判断了地理信息产业发展所处的发展阶段;并根据产业发展的阶段特点和特征,提出了地理信息产业在成长期和成熟期政府需要制定的政策建议和企业发展战略建议,以期为政府制定产业政策和企业制定发展战略提供参考和依据。     

航空重力测量中基准站与测线的距离对精度的影响

简要介绍了航空重力测量中基准站的布设原则,结合2010年某地区的实际测量数据分析了基准站与测线的距离对航空重力测量的精度的影响。实际数据验证表明,基准站距离测线360km时,其交叉点重力异常不符值标准差可以达到±2．0816mGal,其精度符合规范要求,所以在GPS基准站布设困难的地区,可以依据测区的具体情况适当地放宽GPS的布设位置和距离。     

顾及地形效应的重力向下延拓模型分析与检验

向下延拓是航空重力测量数据实际应用中必不可少的技术环节。向下延拓属于不适定反问题,其解算过程具有较大的不确定性,故该问题一直是大地测量领域国内外学者的研究热点。本文深入分析研究了当前国内外最具代表性的3种向下延拓计算模型的技术特点和适用条件,提出了应用超高阶位模型、局部地形改正和移去—恢复技术顾及地形效应,以及位场延拓结果球面化曲面的工程化方法,重点探讨了计算模型的稳定性及数据观测误差对延拓计算结果的影响。通过理论分析、数值仿真和实测数据计算等手段,定量评估了不同向下延拓模型的解算精度及其可靠性。其主要结论是:传统逆Poisson积分模型解严重受制于输入数据观测噪声的干扰,在现有作业条件下,该模型至多只能用于1km以下高度的延拓解算;频谱截断积分和位模型加地改两种延拓新模型具有良好的计算稳定性,完全适用于2′分辨率和5km飞行高度条件下的航空重力测量数据向下延拓解算,其延拓计算精度可达2×10~(-5) m/s~2,可满足各方面实际应用需求。     

理论与实践结合的测量平差教学改革

测量平差是测绘类专业重要的基础核心课程,课程理论性强、公式多、难度大。针对这一问题,本文提出在构建合理教学体系的前提下,理论部分完善教学体系,改善教学方法,采用多媒体与板书相结合、平差案例与平差理论相结合的教学方式;在实践性教学环节,引入测量平差实践技能实习,使测量平差理论与实践"零距离",让学生更好地理解测量项目中内业外业是一个完整的过程,体会测量平差在测量中的地位和作用。教学实际操作表明,该教学方法对学生学习平差课程的效果有很大改善。     

利用算子微分理论和反演方法探求地图投影正解变换

探求地图投影模型是一个很复杂的数学问题,涉及诸多数学理论和方法,解算步骤和过程一般都很繁琐。此处根据现代数学中的算子微分理论和微分几何理论,采用反演的方法对地图投影的正解变换进行了研究,简化了地图投影正解求解的过程和步骤。基本思路是先通过求解地图投影的反解变换,再根据反解变换求其相应的正解变换。并利用微分算子理论中的等角和等面积投影定理,分别验证了所探求的正反解是等角投影还是等面积投影。最后经过算例证明该方法的快捷性和有效性。