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1.
《The Cartographic journal》2013,50(4):313-320
Abstract

The potential of unclassed animated choropleth maps as a solution to false patterns of geographic change arising from data classification is investigated. Old concerns about unclassed choropleth maps may be mitigated through map interactivity that offers four advantages over traditional data legends, and previous insights from testing static choropleth maps do not necessarily translate to animated cartography. Data from user testing revealed unclassed animated choropleth maps neither help nor hurt the ability of map readers to understand patterns of geographic change. However, the unclassed map (1) appeared 'less jumpy' to participants and was perceived to run at a slower pace (despite running at the same number of frames per second), and (2) subtle geographic shifts (e.g., seasonal unemployment cycles) were more readily noticed on the unclassed maps. Preliminary results also suggest classed data emphasise stability over time – while their unclassed counterparts improve our ability to see changes. This paper also outlines animated simultaneous contrast as a new perceptual issue in the creation of animated choropleth maps.  相似文献   

2.
《The Cartographic journal》2013,50(2):156-166
Abstract

Visual map comparison can supplement statistical analysis by providing information as to where and how spatial correspondence occurs. The associations that may be discovered are influenced by the nature of the map features being compared and the criteria used for making the comparisons. In this paper the author has tried to identify the elements of visual recognition that map readers use to associate or differentiate geographical distributions represented by choropleth maps. The main components of the multivariate map reading process are pointed out, including the perceptual interactions between the actual locations of map tones and the overall similarity between map patterns.  相似文献   

3.
This article presents the use of the frequency histogram legend (FHL) as a substitute to traditional legends in both classed and unclassed choropleth maps. Great variation in the size of mapping units can hinder readers' ability to comprehend statistical distributions from a choropleth map. Replacing conventional legends with FHL can aid readers in their understanding of spatial as well as statistical distributions of the mapped data simultaneously. A customized mapping application was designed in ArcInfo 9.0 to test the use of FHL in both classed and unclassed choropleth maps. Frequency histogram legends were tested on different types of statistical distributions. Although the comparison of the results shows that the FHL works best for a Gaussian or close to a Gaussian distribution for eight or fewer classes, the customized application permits users to generate choropleth maps with frequency histogram legends for any type of statistical distribution with any number of classes. The analysis reveals that readers' background in statistics helped them to effectively utilize and interpret frequency histogram legends in the choropleth maps.  相似文献   

4.
Abstract

There are numerous computer programs to produce choropleth maps and some work has also been published on the use of a grid matrix as a way of dividing an area into discrete units. The purpose of this paper is to combine the two approaches and evaluate the suitability of using a network of grid cells, each containing a representative value of the variable being mapped, as a way of producing choropleth maps on a computer.  相似文献   

5.
Abstract

The spatially discontinuous choropleth map is a poor representation of the underlying continuous distribution of population density. A possible alternative is to derive dasymetric maps at a fine spatial resolution by making use of satellite imagery in a geographical information system. However, there are cartographic problems when these maps are displayed and further processing is needed in order to obtain approximations to a continuous density surface. Isarithmic maps of these density surfaces retain a high degree of spatial accuracy while providing pleasing and highly adaptable presentations.

The methods used to generate dasymetric and isarithmic maps are readily implemented in most raster based geographical information systems. For example, the classification of remotely sensed imagery, the subsequent processing and integration of data, and most of the cartographic display, were all undertaken in this work using the low cost IDRISI GIS that operates on standard IBM PC compatible hardware.  相似文献   

6.
A choropleth map is a form of thematic map used to portray the structural characteristics of some particular geographical distribution not apparent in data presented in tabular form. Preparation of a choropleth map starts with the assignment of map features to classes based on the value of a specific feature attribute followed by the association of classes of features with appropriate map colors or symbols. Map features are often geographical regions with naturally or artificially defined boundaries, but choropleth maps can also be prepared by segmenting the area to be mapped into a regular grid of regions. Maps prepared with each grid shaded in an intuitive manner such as blue for grids with the lowest attribute values to red for the highest values can be termed “heat maps”. This technical note describes the HeatMap Microsoft Excel application which converts information contained in a worksheet into a heat map, and then converts the heat map into a file suitable for display using mapping systems such as Google Earth. An example illustrates how the application can be used to visualize the seventeenth century frontier between the Polish/Lithuanian Commonwealth and the Ottoman Empire.  相似文献   

7.
Animated choropleth maps enable cartographers to visualize time-series data in a way that congruently depicts change over time. However, users have difficulty apprehending information encoded within these displays, and often fail to detect important changes between adjacent scenes. Failures of visual experience, such as change blindness, threaten the effectiveness of dynamic geovisual displays, in which several important changes can occur simultaneously throughout the display. Animated choropleth maps require viewers not only to notice changes but also understand symbolic meanings encoded in rapid transitions between scenes. Graphic interpolation between key frames, also known as “in-betweening” or “tweening”, smoothes transitions and lengthens the duration of the transition between scenes in a dynamic sequence. Previous cartographic literature suggests tweening could be a potential solution for change blindness in the cartographic context. This article examines this issue of change blindness in the cartographic context and reports on a human subjects investigation designed to evaluate the influence of cartographic design variables on map readers' change detection abilities. Our results indicate that 1) map readers have difficulty detecting changes in animated choropleth maps, 2) map readers over-estimate their own change detection abilities, and 3) tweening influences the legibility of change in animated choropleth maps.  相似文献   

8.
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.  相似文献   

9.
Abstract

Geographically weighted regression (GWR) is a local spatial statistical technique for exploring spatial nonstationarity. Previous approaches to mapping the results of GWR have primarily employed an equal step classification and sequential no-hue colour scheme for choropleth mapping of parameter estimates. This cartographic approach may hinder the exploration of spatial nonstationarity by inadequately illustrating the spatial distribution of the sign, magnitude, and significance of the influence of each explanatory variable on the dependent variable. Approaches for improving mapping of the results of GWR are illustrated using a case study analysis of population density–median home value relationships in Philadelphia, Pennsylvania, USA. These approaches employ data classification schemes informed by the (nonspatial) data distribution, diverging colour schemes, and bivariate choropleth mapping.  相似文献   

10.
Many cartographers subscribe to the view that unclassed choropleth maps and multivariate choropleth maps exceed map readers' abilities to process visual information. This paper examines recent evidence which controverts both of these beliefs and discusses applications of a computer program, BICHOR, designed to produce unclassed bivariate choropleth maps interactively on a line plotter or CRT. The maps utilize crossed-line symbolism and putatively overcome both the quantization error inherent in conventionally classed choroplethic displays and the perceptual difficulties associated with color-encoding schemes used for earlier bivariate maps.  相似文献   

11.
Imagery from recently launched high spatial resolution satellite sensors offers new opportunities for crop assessment and monitoring. A 2.8-m multispectral QuickBird image covering an intensively cropped area in south Texas was evaluated for crop identification and area estimation. Three reduced-resolution images with pixel sizes of 11.2 m, 19.6 m, and 30.8 m were also generated from the original image to simulate coarser resolution imagery from other satellite systems. Supervised classification techniques were used to classify the original image and the three aggregated images into five crop classes (grain sorghum, cotton, citrus, sugarcane, and melons) and five non-crop cover types (mixed herbaceous species, mixed brush, water bodies, wet areas, and dry soil/roads). The five non-crop classes in the 10-category classification maps were then merged as one class. The classification maps were filtered to remove the small inclusions of other classes within the dominant class. For accuracy assessment of the classification maps, crop fields were ground verified and field boundaries were digitized from the original image to determine reference field areas for the five crops. Overall accuracy for the unfiltered 2.8-m, 11.2-m, 19.6-m, and 30.8-m classification maps were 71.4, 76.9, 77.1, and 78.0%, respectively, while overall accuracy for the respective filtered classification maps were 83.6, 82.3, 79.8, and 78.5%. Although increase in pixel size improved overall accuracy for the unfiltered classification maps, the filtered 2.8-m classification map provided the best overall accuracy. Percentage area estimates based on the filtered 2.8-m classification map (34.3, 16.4, 2.3, 2.2, 8.0, and 36.8% for grain sorghum, cotton, citrus, sugarcane, melons, and non-crop, respectively) agreed well with estimates from the digitized polygon map (35.0, 17.9, 2.4, 2.1, 8.0, and 34.6% for the respective categories). These results indicate that QuickBird imagery can be a useful data source for identifying crop types and estimating crop areas.  相似文献   

12.
《The Cartographic journal》2013,50(3):233-241
Abstract

There have been numerous efforts over many years to map or delineate urban locations and features in the Kathmandu Valley of Nepal. This study acquired 27 land useland cover maps for the Valley or the urban portions of the Valley. Those maps vary greatly in their mapping parameters. The objectives of this study were to first conduct a cartographic comparison of the differences in the creation and content of the maps and then do an analysis of the urban changes in the Valley based upon the maps. The maps for the Valley have differed in their source materials, the amount of field work involved, scale and minimum mapping units, classifications used, definitions of classes and coordinate systems. Source materials have included various scales and formats of aerial photography and different satellite systems. The most difficult issue in comparing the maps is the varied classification systems and definitions. The same feature will be classified differently from map to map. This is particularly an issue for institutional features such as temples, palaces, educational facilities, open public space and governmental sites. Definitions of residential areas are also not consistent. Even with the differences in mapping parameters, considerable useful information can be obtained by comparing these maps. These include a simply documentation of the urban extent and the generally resulting loss in agricultural lands. There was an increase in urban extent from 22 to 83km2 between 1955 and 2000. Urban expansion has also changed from occurring on the upland river terraces or tars to the floodplains. Finally, while not directly documented in these maps, the tremendous pace of urban growth has resulted in multiple infrastructure and environmental challenges.  相似文献   

13.
Abstract

Tepetates, altered indurated and sterile volcanic tuffs, are located among the neo‐volcanic belt in central Mexico. They are divided into three classes according to the erosion level: outcrop tepetates, discontinuous tepetates (in process of erosion), and underlying tepetates (related to fragile areas with high erosion risk). For local communities and peasants, the existence of tepetates is a heavy constraint, with the impossibility to cultivate the land as it is. In order to know the localization and extension of tepetates, we experimented with various classification techniques of a Landsat Thematic Mapper satellite image. Masking techniques were used, assisted both by a DEM and photo interpretation, in addition to radiometric segmentation to obtain a map of tepetates in a study area. The resulting map showed the location of outcrop tepetates well, in agreement with existing soil maps, but underestimated underlying tepetates and high‐risk erosion localities, due mainly to the heterogeneity of the classes at the scale used (30 m pixel).  相似文献   

14.
Abstract

The standards applied to reclassify landslide-conditioning factors differ among studies and may change the accuracy of identifying landslide-prone areas. Therefore, we identified two standards per factor (elevation, aspect, slope, proximity to roads and proximity to streams) from the existing literature and set them as predisposing criteria in this paper. In addition to the five factors, lithology represented by types and a landslide inventory map produced from field surveys were also used in mapping. Thirty-two landslide susceptibility maps were generated based on weights-of-evidence and evaluated using the relative operative characteristic method. The results show that the subdivision criteria of factors change the accuracy, with the success rate varying from 84.34% to 87.51%. The map with the highest value captures more landslides in relatively higher susceptibility classes and is therefore considered the optimal one. Ultimately, a simplified mode of combining subdivision criteria is proposed to simplify comparison.  相似文献   

15.
In a project to classify livestock grazing intensity using participatory geographic information systems (PGIS), we encountered the problem of how to synthesize PGIS-based maps of livestock grazing intensity that were prepared separately by local experts. We investigated the utility of evidential belief functions (EBFs) and Dempster's rule of combination to represent classification uncertainty and integrate the PGIS-based grazing intensity maps. These maps were used as individual sets of evidence in the application of EBFs to evaluate the proposition that " This area or pixel belongs to the high, medium, or low grazing intensity class because the local expert(s) says (say) so ". The class-area-weighted averages of EBFs based on each of the PGIS-based maps show that the lowest degree of classification uncertainty is associated with maps in which "vegetation species" was used as the mapping criterion. This criterion, together with local landscape attributes of livestock use may be considered as an appropriate standard measure for grazing intensity. The maps of integrated EBFs of grazing intensity show that classification uncertainty is high when the local experts apply at least two mapping criteria together. This study demonstrates the usefulness of EBFs to represent classification uncertainty and the possibility to use the EBF values in identifying and using criteria for PGIS-based mapping of livestock grazing intensity.  相似文献   

16.
Inputs to various applications and models, current global land cover (GLC) maps are based on different data sources and methods. Therefore, comparing GLC maps is challenging. Statistical comparison of GLC maps is further complicated by the lack of a reference dataset that is suitable for validating multiple maps. This study utilizes the existing Globcover-2005 reference dataset to compare thematic accuracies of three GLC maps for the year 2005 (Globcover, LC-CCI and MODIS). We translated and reinterpreted the LCCS (land cover classification system) classifier information of the reference dataset into the different map legends. The three maps were evaluated for a variety of applications, i.e., general circulation models, dynamic global vegetation models, agriculture assessments, carbon estimation and biodiversity assessments, using weighted accuracy assessment. Based on the impact of land cover confusions on the overall weighted accuracy of the GLC maps, we identified map improvement priorities. Overall accuracies were 70.8 ± 1.4%, 71.4 ± 1.3%, and 61.3 ± 1.5% for LC-CCI, MODIS, and Globcover, respectively. Weighted accuracy assessments produced increased overall accuracies (80–93%) since not all class confusion errors are important for specific applications. As a common denominator for all applications, the classes mixed trees, shrubs, grasses, and cropland were identified as improvement priorities. The results demonstrate the necessity of accounting for dissimilarities in the importance of map classification errors for different user application. To determine the fitness of use of GLC maps, accuracy of GLC maps should be assessed per application; there is no single-figure accuracy estimate expressing map fitness for all purposes.  相似文献   

17.
The classification of satellite imagery into land use/cover maps is a major challenge in the field of remote sensing. This research aimed at improving the classification accuracy while also revealing uncertain areas by employing a geocomputational approach. We computed numerous land use maps by considering both image texture and band ratio information in the classification procedure. For each land use class, those classifications with the highest class-accuracy were selected and combined into class-probability maps. By selecting the land use class with highest probability for each pixel, we created a hard classification. We stored the corresponding class probabilities in a separate map, indicating the spatial uncertainty in the hard classification. By combining the uncertainty map and the hard classification we created a probability-based land use map, containing spatial estimates of the uncertainty. The technique was tested for both ASTER and Landsat 5 satellite imagery of Gorizia, Italy, and resulted in a 34% and 31% increase, respectively, in the kappa coefficient of classification accuracy. We believe that geocomputational classification methods can be used generally to improve land use and land cover classification from imagery, and to help incorporate classification uncertainty into the resultant map themes.  相似文献   

18.
Choropleth maps are the most widely used map type for mapping rates, such as those involving disease, crime, and socioeconomic indicators. The essential step of choosing a geographic unit to map is often made in an ad hoc manner. Among the desirable characteristics of choropleth mapping units are high degree of resolution, homogeneity of population size, homogeneity of land area, observation of minimum population thresholds and land area thresholds, temporal stability and currency, compactness of shape, audience familiarity, data availability, and the functional relevance of the unit to the phenomena mapped. Because of the uneven distribution of human populations, no single geographic unit can meet all of these characteristics in practice, and a well designed choropleth map necessarily involves some compromise. We present guidelines for choosing geographic units that take into account the above criteria, considering 12 geographic units ranging from census blocks to states. Even allowing for differences in scale and purpose, some units confer clear advantages over others.  相似文献   

19.
《测量评论》2013,45(80):75-79
Abstract

1. Classes and Varieties. A map projection can be considered from different points of view, each such point of view representing a “class” of projections. The classes, in their turn, are subdivided into “varieties”.  相似文献   

20.
Large data contexts present a number of challenges to optimal choropleth map classifiers. Application of optimal classifiers to a sample of the attribute space is one proposed solution. The properties of alternative sampling‐based classification methods are examined through a series of Monte Carlo simulations. The impacts of spatial autocorrelation, number of desired classes, and form of sampling are shown to have significant impacts on the accuracy of map classifications. Tradeoffs between improved speed of the sampling approaches and loss of accuracy are also considered. The results suggest the possibility of guiding the choice of classification scheme as a function of the properties of large data sets.  相似文献   

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