From 1 dimension to N dimensions-fractal in automated cartographic generalization

Automated cartographic generalization has been an intensive research topic in cartography for decades. Some problems associated with this topic could be resolved to a certain extent using fractal analysis and fractal dimension. This paper investigates the fundamental theories and operational methods of generalization. Among others, methods of calculating fractal dimensions of curves and even complicated 3-dimensional geographic objects are explained. Fractal dimensions can be used as an objective criterion for both scaling the natural geographic objects and economical computer storage. More important is that the generalization algorithms based on fractal dimensions can be performed automatically.     

Selective omission of road features based on mesh density for automatic map generalization

Selection of roads is an intractable generalization operation due to the difficulty in retaining the density difference and connectivity of a road network. This paper proposes a novel approach of selective omission for roads based on mesh density. The density of a road network and its local variations are calculated using meshes as units. Since maps at different scales usually reveal different densities, different density thresholds for road networks are determined on the basis of theoretical analysis and empirical study of mesh densities on maps at different scales. The selection process starts with the identification of the meshes that have a density beyond the threshold. The mesh with the largest density is first treated. Its bounding road segments are ordered according to their relative importance. The least important segment is eliminated. The remaining segments are then merged with the adjacent mesh, thus forming a new mesh. The selection procedure is repeated until none of the meshes has a density beyond the threshold. Such a process of eliminating road segments and merging meshes can ensure the road network connectivity. In this study, the meshes are classified depending on the types of road segment. For the different mesh types, their density thresholds are set to be different, which can be used as an indicator for the preservation of the density difference. This proposed approach considers topological, geometric and semantic properties of the road network. It was applied to two sets of road networks, and the results of selection are convincing. This methodology has now been adopted for the updating of 1:50,000 maps of China.     

基于数字高程模型的水系提取算法

介绍基于地表径流漫流模型从数字高程模型 (DEM )提取水系的一系列算法。这套算法完成下述功能 :洼地的识别和填充、平地的抬升、水流方向的确定、上游集水面积的确定和河流栅格网络的生成以及水系的生成和水流线等级的确定。     

Automated building generalization based on urban morphology and Gestalt theory

Building generalization is a difficult operation due to the complexity of the spatial distribution of buildings and for reasons of spatial recognition. In this study, building generalization is decomposed into two steps, i.e. building grouping and generalization execution. The neighbourhood model in urban morphology provides global constraints for guiding the global partitioning of building sets on the whole map by means of roads and rivers, by which enclaves, blocks, superblocks or neighbourhoods are formed; whereas the local constraints from Gestalt principles provide criteria for the further grouping of enclaves, blocks, superblocks and/or neighbourhoods. In the grouping process, graph theory, Delaunay triangulation and the Voronoi diagram are employed as supporting techniques. After grouping, some useful information, such as the sum of the building's area, the mean separation and the standard deviation of the separation of buildings, is attached to each group. By means of the attached information, an appropriate operation is selected to generalize the corresponding groups. Indeed, the methodology described brings together a number of well-developed theories/techniques, including graph theory, Delaunay triangulation, the Voronoi diagram, urban morphology and Gestalt theory, in such a way that multiscale products can be derived.     

基于消费责任制的碳排放核算及全球环境压力

因区域间贸易而转移的碳排放对于全球各个国家或者地区的碳排放核算及其减排责任划分具有重要而深远的影响。通过构建多区域投入产出分析模型和基于扩展的STIRPAT模型,本文核算了全球39个主要国家基于消费责任制的碳排放,并在此基础上深入探讨了全球环境压力的影响因素问题。研究发现：首先,从以净流出为主的中国和俄罗斯来看,尽管贸易给这些地区带来了大量的资源,但随之会产生严重的区域生态环境问题。而对于美国和欧盟等地区来说,这些国家或者地区通过全球贸易规避了大量的碳减排责任。此外,在全球贸易中,区域净流出的贸易隐含碳排放越小,基于消费责任制核算的区域碳排放量就越大,故而在全球减排目标分配中承担的减排任务也需相应地增加。全球贸易隐含碳排放净流出量较大的地区主要位于亚洲和东欧等地,而净流出量最小的地区主要是以西欧和北美等高度发达的经济体为主。其次,就基于消费责任制核算下的全球环境压力而言,人口因素和富裕程度是导致全球环境压力不断增加的两个重要因素,而提高生产技术水平以及逐渐提高清洁能源在总能源消费中的比重是推动全球节能减排、缓解全球环境压力的有效途径。     

A CORINE map of Great Britain by automated means. Techniques for automatic generalization of the Land Cover Map of Great Britain.

Abstract

The European Commission (EC) programme ‘Co–ordination of Information on the Environment’ (CORINE) includes a project to map the land cover of member states. The CORINE map is essentially one which combines land cover and land use, giving 44 separate classes, in vector, displayed at a scale of 1:100000 with a minimum mappable unit of 25 ha. The Institute of Terrestrial Ecology (ITE) has compiled a digital land cover map of Great Britain (LCMGB) from classification of Landsat–TM data, resampled to a 25 m raster, with a minimum mappable unit of 0.125 ha and 25 cover types. This paper describes a pilot study which demonstrates the successful spatial generalisation with contextual interpretation to convert the LCMGB to CORINE specifications using semi–automated techniques within a GIS environment.     

Colocation of older adults with successful aging based on objective and subjective measures

Aging of the U.S. and world populations highlights the need to understand how and where people age successfully. Older adults with chronic conditions may rate themselves subjectively as aging successfully despite their objective limitations. A typology of successful aging combining objective and subjective criteria has been tested, but spatial patterns in these dimensions have not been widely studied. Our research explores patterns of successful and unsuccessful aging using the colocation quotient, a measure of spatial association among categories in a population. The colocation quotient assesses the degree to which older adults who age successfully are likely to live near other adults who do not age successfully. Data on 5576 participants in the ORANJ BOWL^SM survey, a statewide survey of older adults in New Jersey, were geocoded to the Census block level. Each participant was scored as aging successfully or not on each of the two dimensions. Global and local patterns of colocation of successful and unsuccessful aging in individuals were calculated based on the objective and subjective measures separately and then compared. The analysis reveals a strong regional pattern. In northern New Jersey and along the southeast coast, successful older adults on both dimensions were more likely to be colocated with subjectively unsuccessful older adults. In southern New Jersey, especially in the southwest, successful older adults on both dimensions were more likely to be colocated with the objectively unsuccessful. Spatial analysis of colocation can inform needs assessment for the growing population of older adults by identifying where older people age successfully and where they are aging unsuccessfully.     

基于合理权重赋值方法选择的多因素综合评价模型——以JCR中70种人文地理期刊为例

针对地理学多因素综合评价中较少探讨指标权重赋值方法的选择,以及少有研究涉及人文地理期刊的多因素综合评价,本文设计了基于合理权重赋值方法选择的多因素综合评价模型,并将其应用于科学网数据库内的“期刊引证报告（JCR）”中分类为人文地理类的70种人文地理期刊的综合评价。该模型针对7种指标权重客观赋值方法,采用“异同比较”,分析不同方法在不同参数设置下和聚类与否情况下的权重值、评价值和评价序的变化特征与分布规律,并依据该变化特征与分布规律,实现了对各种方法的“优劣比较”和最优选择。应用该模型对JCR中70种人文地理期刊进行排序分等,其中排名第一的“全球环境变化和政策”等14种期刊为位列第一等分的高影响力期刊。本研究完善了多因素综合评价体系,也丰富了对人文地理期刊的认知。     

Authors' reply to a comment on 'An objective method for smoothing palaeomagnetic data'

Summary. King & Rees (1979), in commenting on our paper (Clark & Thompson 1978), have raised a number of subjects beyond the main theme of our paper. We described a statistical method of smoothing noisy data and illustrated its application using a set of previously published palaeomagnetic declination data. King & Rees acknowledge our success in achieving the main aim of our paper, namely the construction of objective confidence limits for the smooth curve presumed to underlie the data. However, they seem to question the value of our general technique of data-analysis when used to estimate past variations in the geomagnetic field. As they interpose in their comments on our statistical analyses references to 'techniques of sedimentary analysis', 'inclination errors', 'mode of acquisition of remanence' and 'stability tests', we take the opportunity to discuss these additional topics as well as those relating to our original paper.     

基于自然区块的城市热环境空间分异性研究

通过有效解决建设用地子类划分,实现定量评价城市热环境的空间分异性,对改善城市生态环境、实现城市化的健康发展具有重要的意义和科学价值。论文以广州市为例,参考自然城市的概念,基于5类兴趣点(Point Of Interest,POI)开放数据,结合城市建设用地分类标准,构建5类自然区块;在Landsat 8遥感影像地表温度反演的基础上,计算分析自然区块下地表热场等级分布格局、热场平均值及热环境足迹范围,以对城市热环境空间分异性进行评价。研究表明：① 自然区块的构建,能准确地反映各类POI数据空间分布情况,能够实现对建设用地子类型的划分;② 5类自然区块内部地表热场等级均以高温像元为主,但等级分布具有显著差异。同时,自然区块的热场平均值由高到低的排序为：工业区块>商业服务业区块>交通与道路区块>居住区块>公共管理与服务区块;③ 自然区块形成的高温集聚区,存在热量扩散现象,实际影响范围大于其物理边界,5类自然区块的热环境足迹范围具有分异性。热环境足迹影响范围由大到小排序为：工业区块>商业服务业区块>居住区块>道路与交通区块>公共管理与服务区块。研究结果可为微观尺度上分析城市热环境、改善城市生态环境、实现城市化的健康发展提供科学依据。     

基于主客观生活质量评价的农村发展差异分析——以北京山区经济薄弱村为例

从居民生活质量角度评价区域发展程度长期以来备受关注。本文以北京山区经济薄弱村为例,在抽样农户调查基础上,基于小康监测体系中的生活质量指标体系,采用因子分析法构建的主观评价体系,分别测算了村级客观、主观生活质量指数,运用聚类法与差异贡献率法,开展北京山区经济薄弱村居民主客观生活质量的对比评价及影响因素分析。研究表明:1客观指数上,99.29%的村庄低于北京农村的平均水平,村间差异显著,高指数村庄主要分布在地势平坦的近郊区;2主观指数上,具有一定地域趋同性,离城区越近主观满意度越低;3综合来看,深山区与近郊区的村庄自身存在较大的主—客观差异,18.95%的村庄综合生活质量较差,文化娱乐、信息教育、生态环保等生活品质是限制居民生活质量的主要因素;4差异扶贫、提升人口综合素质、扶持生活质量高维度相关产业发展以及开展扶贫动态监测与开发规划,是进一步改善居民生活质量、提升区域发展水平的主要驱动力。主客观生活质量评价能够深入反映区域发展与居民生活质量间的关系,可作为区域综合发展决策的重要辅助方法。     

Rules and constraints for 3D generalization of urban area

In every map, irrespective of its theme, objects are represented at a reduced scale. Map contents do not decrease proportionally to the reduction of the map size. Usually an increasing density of the map contents occurs at smaller scales. That is where the generalization plays an important role. Generalization is the process of creating a legible map at a given scale from a more detailed geographical dataset. It is done in such a manner that the character or essence of the original features is retained at successively smaller scales. Though the purposes and benefits of generalization are manifold it is indeed a complex decision-making process which must be intelligently steered by goals and rules from the geographical application domain such that the generalized representation conveys knowledge consistent with the reality. In recent past, lot of work has been done in 2D generalization (Beard, 1991; Weibel, 1995; Bealla, 1995; Ruas and Plazanet, 1996; Sarjakoski and Kilpeläinen, 1999) which defines a set of operations to be performed with the goal to achieve the similar results to those from manual generalization. But 3D generalization is altogether perceived differently. A given 3D urban area mostly consists of roads and buildings. These buildings are of different styles and features. Further the city area may be viewed from different angles and at different heights. So generalization in general and aggregation in particular must deal with all these issues. In this paper, an effort has been made to address these issues.     

Real and complex spectra – a generalization of WKBJ seismograms

Real plane-waves constitute the building blocks for recently developed spectral techniques in synthetic seismology. While providing numerical convenience, real slowness-spectra model certain wave phenomena in a distributed 'unnatural' way, whereas complex spectra model these phenomena in a compact, more 'natural' way. The theory of complex spectra, called by us the 'Spectral Theory of Transients' (STT) and developed elsewhere, is summarized here and contrasted with the real-spectrum approach. Relying strongly on the theory of analytic functions, STT permits the transient responses to be classified and evaluated according to the singularities they introduce in the complex slowness plane. The method is illustrated for a number of 2-D SH -wave model propagation environments, including interface reflection, head waves, multiple encounters with caustics due to concave boundaries or ducting medium inhomogeneities, and diffraction by structures with edges.     

Multicriteria generalization (MCG): a decision-making framework for formalizing multiscale environmental data reduction

Environmental simulation models need automated geographic data reduction methods to optimize the use of high-resolution data in complex environmental models. Advanced map generalization methods have been developed for multiscale geographic data representation. In the case of map generalization, positional, geometric and topological constraints are focused on to improve map legibility and communication of geographic semantics. In the context of environmental modelling, in addition to the spatial criteria, domain criteria and constraints also need to be considered. Currently, due to the absence of domain-specific generalization methods, modellers resort to ad hoc methods of manual digitization or use cartographic methods available in off-the-shelf software. Such manual methods are not feasible solutions when large data sets are to be processed, thus limiting modellers to the single-scale representations. Automated map generalization methods can rarely be used with confidence because simplified data sets may violate domain semantics and may also result in suboptimal model performance. For best modelling results, it is necessary to prioritize domain criteria and constraints during data generalization. Modellers should also be able to automate the generalization techniques and explore the trade-off between model efficiency and model simulation quality for alternative versions of input geographic data at different geographic scales. Based on our long-term research with experts in the analytic element method of groundwater modelling, we developed the multicriteria generalization (MCG) framework as a constraint-based approach to automated geographic data reduction. The MCG framework is based on the spatial multicriteria decision-making paradigm since multiscale data modelling is too complex to be fully automated and should be driven by modellers at each stage. Apart from a detailed discussion of the theoretical aspects of the MCG framework, we discuss two groundwater data modelling experiments that demonstrate how MCG is not just a framework for automated data reduction, but an approach for systematically exploring model performance at multiple geographic scales. Experimental results clearly indicate the benefits of MCG-based data reduction and encourage us to continue expanding the scope of and implement MCG for multiple application domains.     

Computing the fewest-turn map directions based on the connectivity of natural roads

In this article, we introduce a novel approach to computing the fewest-turn map directions or routes based on the concept of natural roads. Natural roads are joined road segments that perceptually constitute good continuity. This approach relies on the connectivity of natural roads rather than that of road segments for computing routes or map directions. Because of this, the derived routes possess the fewest turns. However, what we intend to achieve are the routes that not only possess the fewest turns but are also as short as possible. This kind of map direction is more effective and favored by people because they bear less cognitive burden. Furthermore, the computation of the routes is more efficient because it is based on the graph encoding the connectivity of roads, which is substantially smaller than the graph of road segments. We experimented on eight urban street networks from North America and Europe to illustrate the above-stated advantages. The experimental results indicate that the fewest-turn routes possess fewer turns and shorter distances than the simplest paths and the routes provided by Google Maps. For example, the fewest-turn-and-shortest routes are on average 15% shorter than the routes suggested by Google Maps, whereas the number of turns is just half as much. This approach is a key technology behind FromToMap.org – a web mapping service using openstreetmap data.     

基于改进三维足迹模型的关中地区土地自然资本利用状况分析

三维生态足迹是可持续发展定量化评价的重要方法,陕西关中地区作为丝绸之路经济带的重要承载地,研究其土地自然资本利用状况对可持续发展具有重要意义。论文采用改进三维足迹模型,并利用足迹广度基尼系数等指标,对关中地区1995—2015年自然资本利用状况从“产品—地类—区域”3个尺度进行了分析。结果表明： ① 1995—2015年,关中地区土地足迹呈现先增后减的变化趋势,土地承载力逐年下降,生态赤字逐年增大,不利于可持续发展;② 关中地区5个市均处于生态赤字状态,足迹深度均超过原长1,消耗存量资本来弥补流量资本的不足已成关中地区社会发展的常态;③ 耕地和建设用地为流量资本占用主要地类,草地、耕地和建设用地为存量资本消耗主要地类;④ 区域内部流量占用不公平程度逐渐增加,若仍不采取合理措施,2025年将呈现较不均衡状态,2030年则为高度不均衡。论文聚焦“实态足迹”,揭示了关中地区土地利用效益,为其可持续发展提供科学参考。     

基于遥感影像的雪线高程提取方法对比分析——以天山北坡为例

利用2010-2014年6~8月MOD10A1、MOD10A2及HJ-1/CCD数据,以天山北坡为研究区,对比分析了积雪持续时间比率法及最大值合成法在雪线高程提取中的精度和适用性。结果表明:当MOD10A1以旬合成,积雪持续时间比率阈值为40%时,提取的雪线高程与"真值"最为接近;基于混淆矩阵法,以目视解译得到的HJ-1/CCD积雪面积为"真值",分析得出,积雪持续时间比率法提取积雪面积的总体精度较高,为98.59%,khat系数为0.90,最大值合成法的总体精度仅为85.29%,khat系数为0.70;基于统计学的方法,计算得出,积雪持续时间比率法提取的雪线高程与"真值"的相关系数较高,为0.77,其平均误差、正、负误差、绝对平均误差以及均方根误差相对较低;最大值合成法提取的雪线高程与"真值"的相关系数较低,仅为0.54,其平均误差、正、负误差、绝对平均误差以及均方根误差相对较高;积雪持续时间比率法提取的雪线高程结果优于最大值合成法。     

基于DEA模型的我国自然灾害区域脆弱性评价

应用数据包络分析(Data Envelopment Analysis,DEA)模型对我国自然灾害的区域脆弱性水平进行研究,在区域灾害系统理论的组织框架下,从区域自然灾害危险性、区域承灾体暴露性和区域自然灾害损失度三个方面构建了区域自然灾害系统的DEA投入产出模型,并利用模型得出的区域自然灾害成灾效率对区域自然灾害的脆弱性进行模拟反映,对我国自然灾害脆弱性的区域分异特征进行分析。研究发现:我国自然灾害脆弱性的整体水平较高,地域格局为西部中部东部,且脆弱性水平与地区经济水平具有明显的负相关关系,经济发达地区的脆弱性相对较低。