Pattern based map comparisons

Map comparison techniques based on a pixel-by-pixel comparison are useful for many purposes, but fail to reveal important aspects of map similarities and differences. In contrast, pattern based map comparison techniques address the question of structural similarity, although with these approaches the comparison problem becomes open ended, since there is an unlimited number of ways to characterise a pattern. Two types of pattern based technique are used here to analyse the test sets of maps. The first, a fuzzy polygon based matching technique, focuses on the meso-scale aspects of pattern. It is based on the areal intersection of land use polygons on the two maps being compared. The areal intersection, areal complement, and polygon size values are fuzzified into an appropriate set of categories, a set of fuzzy inference rules is applied to derive memberships in local matching categories, and finally the local matching category memberships are defuzzified to yield local matching values for each land use polygon on the reference map. The second approach, fractal analysis, captures macro-scale or global qualities of the maps. Two measures are calculated here: the radial dimension and the cluster size—frequency dimension. The polygon matching approach provides only limited insight when applied to the case of the map set representing differences in classification. It proves much more effective when applied to the problem of change detection, revealing areas where the pattern has changed and giving local measures of the degree of change. The approach is particularly useful in the case where there is a considerable degree of random change at the pixel level, as changes in the underlying pattern are extracted from the noise, while pixel based approaches largely detect the noise.     

Establishing Classification and Hierarchy in Populated Place Labeling for Multiscale Mapping for The National Map

Current standards for federal mapping call for use of the Geographic Names Information System (GNIS) point layer for placement of United States populated place labels. However, this point layer contains limited classification information and hierarchy information, resulting in problems of map quality for database-driven, multi-scale, reference mapping, such as maps served by The National Map Viewer from USGS. Database-driven mapping often relies simply on what labels fit best in the map frame. Our research investigates alternative sources for labeling populated places, including polygons defined by the U.S. Census Bureau, such as incorporated place, census designated place (CDP), and economic place. Within each of these polygon layers we investigate relevant attributes from the decennial and economic censuses, such as population for incorporated places and CDPs, and the number of employees for economic places. The data selected are available for the entire country to serve national mapping requirements. This combination of data allows a more refined classification of populated places on maps that better represents relative importance. Visual importance on maps through scale should derive from more than simply residential population, but also economic importance, though comparison is made to this simpler case. We differentiate a fourth category of GNIS populated place points, essentially “neighborhoods” and related features—which are not incorporated places, CDPs, nor economic places. Populated places in this fourth class do not have federally defined boundaries, necessitating an alternative method for determining hierarchy in label presentation through scale.     

What is the difference between two maps? A remote senser’s view

In remote sensing, thematic map comparison is often undertaken on a per-pixel basis and based upon measures of classification agreement. Here, the degree of agreement between two thematic maps, and so the difference between the pair, was evaluated through visual and quantitative analyses for two scenarios. Quantitative assessments were based on basic site-specific measures of agreement that are used widely in accuracy assessment (e.g. the overall percentage of pixels with the same class label in each of the two maps and the kappa coefficient of agreement) as well as an information theory based approach that allows the degree of mutual or shared information to be assessed even if different classification schemes have been used to produce the maps. The results indicated that in the first map comparison scenario, focused on labelling, there was a fair degree of correspondence between the maps but with an overall difference in information content of ∼42%. In the second comparison scenario, focused on change in time, considerable change had occurred with a change in class label for ∼42% of the pixels. It was also apparent that global assessments masked local scale changes.     

Approach to calculating spatial similarity degrees of the same river basin networks on multi-scale maps

Obtaining spatial similarity degrees among the same objects on multi-scale maps is of importance in map generalization. This paper firstly defines the concepts of ‘map scale change’ and ‘spatial similarity degree’; then it proposes a model for calculating the spatial similarity degree between a river basin network at one scale and its generalized version at another scale. After this, it validates the new model and gets 16 points in the model validation process. The x-coordinate and y-coordinate of each point are map scale change and spatial similarity degree, respectively. Last, a formula for calculating spatial similarity degree taking map scale change as the only variable is obtained by the curve fitting method. The formula along with the model can be used to automate the algorithms for simplifying river basin networks.     

Number of Polygons Generated by Map Overlay: The Case of Convex Polygons

This paper analyzes the number of polygons generated by map overlay. Overlay of maps yields a number of small polygons, and often causes problems in computation, handling, and storage of derived polygons. One method to deal with these problems is to estimate the number of derived polygons before executing overlay operation. To this end, a stochastic model is proposed by which the expected number of derived polygons is calculated. The results are summarized as follows: (1) the number of polygons generated by map overlay depends on the number of original polygons and their perimeters; (2) the number of derived polygons increases with the perimeters of original polygons; (3) McAlpine and Cook's (1971) earlier method underestimated the number of derived polygons; and (4) the number of polygons generated by the overlay of maps having the same lattice system is proportional to the square of the number of overlaid maps and the number of polygons on the map, and inversely proportional to the area-perimeter ratio of the unit cell.     

Cartographic Design Matters – A Comparison of Thematic Polygon Design

The number of web services providing cartographic data is increasing. A main challenge is to enable a user to combine these services, not only from a technical perspective, but also from a cartographic one. One common use case for these services is to create mashups based on thematic polygons on top of background maps. In this study we compare four cartographic designs of thematic polygons: only boundaries, transparencies, hatches and icons. The aim of the comparison is to investigate whether the designs are good for identifying the extent of the polygons and if the design disturbs the reading of the background map. The comparison is based on an eye-tracking study, where 24 participants performed polygon identification tasks as well as background search tasks. The study revealed that hatches were more efficient than the other designs for polygon identification. Hatches had significantly shorter total fixation times as well as scanpath lengths, possibly since the participants were able to identify the extent of the polygon solely based on the interior (i.e. the hatches), while for the other designs the participants were extensively reliant on the boundaries. However, the results also indicate that the hatches design disturbs the reading of the background map more than the other designs; hatches also appear visually unpleasant for many users. Since each design had its strengths and weaknesses, we recommend producers of services for thematic data to provide several designs so users can select an appropriate design for their own use cases.     

Automatic interpretation of digital maps

In the past, the availability and/or the acquisition of spatial data were often the main problems of the realization of spatial applications. Meanwhile this situation has changed: on one hand, comprehensive spatial datasets already exist and on the other hand, new sensor technologies have the ability to capture fast and with high quality large amounts of spatial data. More and more responsible for the increasing accessibility of spatial data are also collaborative mapping techniques which enable users to create maps by themselves and to make them available in the internet. However, the potential of this diversity of spatial data can only hardly be utilized. Especially maps in the internet are represented very often only with graphical elements and no explicit information about the map’s scale, extension and content is available. Nevertheless, humans are able to extract this information and to interpret maps. For example, it is possible for a human to distinguish between rural and industrial areas only by looking at the objects’ geometries. Furthermore, a human can easily identify and group map objects that belong together. Also the type, scale and extension of a map can be identified under certain conditions only by looking at the objects’ geometries. All these examples can be subsumed under the term “map interpretation”. In this paper it is discussed how map interpretation can be automated and how automatic map interpretation can be used in order to support other processes. The different kinds of automatic map interpretation are discussed and two approaches are shown in detail.     

基于栅格化思想的矢量电子地图几何变化检测

在检测不同版本矢量电子地图的变化时,通常采用要素遍历、坐标比较的方法,这种方法计算速度慢、效率较低。针对这一不足,提出一种基于栅格化思想的矢量电子地图几何变化统计比较检测方法(SCAG),即利用矢量电子地图进行栅格化处理时构造的统计数据对点、线、面等形状地物的几何变化进行变化统计分析和要素快速检测,其计算量比遍历的方法显著减少,效率提高。最后通过实验验证了SCAG检测方法的可行性、合理性和高效性。     

Global and local indicators of spatial association between points and polygons: A study of land use change

The existing indicators related to spatial association, especially the K function, can measure only the same dimension of vector data, such as points, lines and polygons, respectively. We develop four new indicators that can analyze and model spatial association for the mixture of different dimensions of vector data, such as lines and points, points and polygons, lines and polygons. The four indicators can measure the spatial association between points and polygons from both global and local perspectives. We also apply the presented methods to investigate the association of temples and villages on land-use change at multiple distance scales in the Guoluo Tibetan Autonomous Prefecture in Qinghai Province, PR China. Global indicators show that temples are positively associated with land-use change at large spatial distances (e.g., >6000 m), while the association between villages and land-use change is insignificant at all distance scales. Thus temples, as religious and cultural centers, have a stronger association with land-use change than the places where people live. However, local indicators show that these associations vary significantly in different sub-areas of the study region. Furthermore, the association of temples with land-use change is also dependent on the specific type of land-use change. The case study demonstrates that the presented indicators are powerful tools for analyzing the spatial association between points and polygons.     

Categorical maps, comparisons, and confidence

The comparison of categorical maps is a common problem in several different contexts. Differences between categorical maps can be characterized and measured in a variety of ways. In 2004 we invited individuals from remote sensing, geographical information analysis, spatial modelling, and landscape ecology to participate in a virtual workshop in order to compare strategies for comparison. This revealed that the key dimensions of comparison relate to (1) the map characteristics considered, (2) the nature of the comparison, (3) the handling of geographical space, (4) the units of computed measures, and (5) the tests of significance.Ferko Csillag deceased     

Cartographic reconstruction of building footprints from historical maps: A study on the Swiss Siegfried map

Extracting features from printed maps has been a challenge for decades; historical maps pose an even larger problem due to manual, inconsistent drawing or scribing, low printing quality, and geometrical distortions. In this article, a new workflow is introduced, consisting of a segmentation step and a vectorization step to acquire high‐quality polygon representations of building footprints from the Siegfried map series. For segmentation, an ensemble of U‐Nets is trained, yielding pixel‐based predictions with an average intersection over union of 88.2% and an average precision of 98.55%. For vectorization, methods based on contour tracing and orientation‐based clustering are proposed to approximate idealized polygonal representations. The workflow has been tested on 10 randomly selected map sheets from the Siegfried map, showing that the time required to manually correct these polygons drops to about 45 min per map sheet. Of this sample, approximately 10% of buildings required manual corrections. This workflow can serve as a blueprint for similar vectorization efforts.     

一种基于视觉感受的电子地图载负量计算方法研究

电子地图载负量是衡量电子地图在满足清晰易读条件下所能表达地物要素多少的重要量化指标。本文通过定量分析影响电子地图载负量的图面负载度、图面压盖度和色彩对比度,提出一种基于视觉感受的电子地图载负量计算方法。该方法从矢量数据出发,在精确计算图面负载度的基础上,首次以图面压盖度和色彩对比度作为权值参与计算,得到电子地图载负量。最后,基于地理信息平台TerraGIS对该方法进行了嵌入试验,获得不同图面负载度、图面压盖度和色彩对比度的实验地图载负量计算结果并将其与传统方法下的计算结果进行对比。又基于眼动仪的视觉感知试验,对不同实验地图下的用户平均眼动时间进行显著性差异分析,并结合热点图结果,分析了该方法计算得到的载负量结果的合理性,从而证明了该方法的科学性与实用性。     

TIN-based Tag Map Layout

With the widespread use of tag clouds, multiple map-based variations have been proposed. Like standard tag clouds (also called word clouds), these ‘tag maps’ all share the basic strategy of displaying words within a ‘geographic space’ and scaling the word size to depict frequency (or importance) of those words within some dataset. While some tag maps simply plot a standard tag cloud on top of a map, the subset of tag maps we focus on here are those in which the collection of words are displayed within bounded geographic regions (often of irregular shape) that the words are relevant for. For this form of tag map, map scale and polygon shape add constraints to word size and position that have not been considered in most prior approaches to tag map word layout. In this paper, we present a layout strategy for tag map generation that includes consideration of the shape and size of the geographical regions acting as containers for the tags. The method introduced here uses a triangulated irregular network (TIN) to subdivide the geographical region into many triangle subareas, with the centroid of each triangle being a potential location to centre a tag on. All the triangles are sorted by their area and all the tags are sorted by their weight value (e.g. frequency, importance or popularity). Positioning of tags is undertaken sequentially from most important (or frequent or popular) with potential locations being the TIN triangle centroids (tried from largest to smallest triangle). After each tag placement, the TIN is recalculated to integrate the tag centroid and bounding corners into the TIN creation. The limited whitespace in the geographical region, at any specific scale, is used fully by dynamically adjusting the font size along with the number and the direction of tags. The method can be applied to add tags within geographic polygons that are convex, concave and other more complex regions containing holes or islands.     

The Use of Spatial Cognitive Abilities in Geographical Information Systems: The Map Overlay Operation

Spatial cognitive abilities play an important role in the use of GIS, although they have yet to be examined in a controlled experimental setting. This study aimed to develop an experimental design which measures spatial cognitive abilities in the use of GIS, specifically the map overlay operation. Subjects ( n = 134) received three map overlay tests in which they were given two of the following: input map layers, logical operator(s), or output map layer(s). Subjects were required to select the correct logical operator for Test 1, to select the correct output map layer for Test 2, and to select the correct input map layers for Test 3. Each test contained a total of 16 questions, based on a 4 ('and', 'or', 'xor', 'not' operators) × 2 (one or two polygons per map layer) × 2 (three or five polygon edges) factorial design. Results indicated a significant main effect of logical operators and number of polygons on performance; however, there was no effect of the number of polygon edges on performance. Significant two-way interactions revealed an effect of the number of polygon edges and the number of polygons using various logical operators on performance. In addition, performance was not significantly different between males and females or between GIS users and non-users. Overall, results show that map overlays in which a visual correspondence can be made between the same polygons in the input and output map layers are cognitively less demanding than map overlays in which the shape of the polygons have been radically transformed between the input and output map layers. This study helps further develop our understanding of the spatial cognitive abilities which are required in the use of GIS, and whether certain sub-populations differ in these cognitive abilities. These results may contribute to more effective and efficient GIS teaching and interface design by taking into account individual spatial cognitive abilities.     

Opening the London Underground to visually handicapped tourists

Abstract

There are several practical rules for determining categories (class intervals) for maps representing statistical data, like arithmetic, geometric or equal steps etc. In this paper, however a coherent method is proposed to provide statistically separable Classes on a map with minimum redundancy in terms of information content.

The number of class intervals can be directly computed by means of appropriate statistical methods if the widths of classes are determined by t-test, i.e. when their difference is significant at a high level of confidence. A class narrower than this width would represent data in different categories due only to variance, however, the selection of wider classes leads to a certain loss of information.

The class intervals determined this way should be positioned on the statistical data-set so that each category contains approximately equal number of data providing maximum information content of the output map. At the final step the class intervals derived this way should be rounded, if necessary, to provide user-friendly maps.     

基于结构特征的地图上带晕线多边形的识别

在建立GIS的过程中,从现有的各种比例尺的地形图上获取地理信息是必不可少的工作。带晕线多边形是基本比例尺地形图上最主要的地物要素类别之一,文中在地图二值图像的基础上,根据带晕线多边形的结构特征,利用一系列图像变换技术,首次成功地实现了带晕线多边形的自动识别与提取。提出并实现了用于带晕线类多边形影像分割的4方向RLS变换方法,详细讨论了收缩变换、扩张变换、细化、开图形删除和带晕线类多边形的识别等算法。实验表明,利用文中所述方法进行带晕线多边形识别与提取的正确率可达96%左右。     

A comparative analysis of gridding systems for point-based land cover/use analysis

For spatial analyses, raster land cover/use maps are converted into points, where each point holds attribute of its corresponding land cover/use. However, these are not identical in terms of areas or shapes; thus assigning a point to each isolated shape is not an adequate solution and for that gridding is suggested. Square, hexagon and triangle are among the basic land use gridding systems where each of them has its own advantages in such process. This research aims to compare the systems in providing accurate representations of the original land cover/use maps, assess the data loss while increasing resolution and suggest suitable gridding system. The research finds the errors in area and feature numbers as criteria for selected classes. Modules that find out errors in each scale considering each criterion and class alone are proposed. The modules suggest both the best system for each criterion alone and for combined criteria.     

Knowledge Discovery from Area–Class Resource Maps: Capturing Prototype Effects

This paper presents a knowledge discovery approach to extracting knowledge from area–class resource maps. Prototype theory forms the basis of the approach which consists of two major components: (1) a scheme for organizing knowledge used in categorizing geographic entities which allows for the modeling of indeterminate boundaries and non–uniform memberships within categories; and (2) a data mining method using the Expectation Maximization (EM) algorithm for extracting such knowledge from area–class maps. A case study on knowledge discovery from a soil map demonstrates the details of the approach. The study shows that knowledge for classifying geographic entities with indeterminate boundaries is embedded in area–class maps and can be extracted through data mining; and that continuous spatial variation of geographic entities can be better modeled if the knowledge discovery process retains knowledge of within-class variations as well as transitions between classes.     

顾及制图规则的地图多要素协同移位方法

在地图自动编制中,有时多类地图要素多个空间目标之间同时发生空间冲突,在移位过程中会影响到邻近区域的地图目标,这就需要对地图要素移位进行协同处理。在自动识别邻近空间冲突区的条件下,提出了一种顾及地图制图规则的解决地图目标群空间冲突的协同处理方法,并用参数表方法形式化表达了地形图上地图要素移位的常用制图规则。首先利用约束性Delaunay三角网识别出可能的空间冲突区域,并建立移位操作区;然后,建立移位传播关联线网,依据制图规则在关联线网上以能量最小化Beam移位模型为基础,对整个空间冲突区的地图目标群进行协同移位;最后,用实验验证了所提方法的有效性和适用性。