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The halfway point for the implementation of the United Nations Sustainable Development Goals (SDGs) was marked in 2023, as set forth in the 2030 Agenda. Geospatial technologies have proven indispensable in assessing and tracking fundamental components of each of the 17 SDGs, including climatological and ecological trends, and changes and humanitarian crises and socio-economic impacts. However, gaps remain in the capacity for geospatial and related digital technologies, like AI, to provide a deeper, more comprehensive understanding of the complex and multi-factorial challenges delineated in the SDGs. Lack of progress toward these goals, and the immense implementation challenges that remain, call for inclusive and holistic approaches, coupled with transformative uses of digital technologies. This paper reviews transdisciplinary, holistic, and participatory approaches to address gaps in ethics and diversity in geospatial and related technologies and to meet the pressing need for bottom-up, community-driven initiatives. Small-scale, community-based initiatives are known to have a systemic and aggregate effect toward macro-economic and global environmental goals. Cybernetic systems thinking approaches are the conceptual framework investigated in this study, as these approaches suggest that a decentralized, polycentric system—for example, each community acting as one node in a larger, global system—has the resilience and capacity to create and sustain positive change, even if it is counter to top-down decisions and mechanisms. Thus, this paper will discuss how holistic systems thinking—societal, political, environmental, and economic choices considered in an interrelated context—may be central to building true resilience to climate change and creating sustainable development pathways. Traditional and Indigenous knowledge (IK) systems around the world hold holistic awareness of human-ecological interactions—practicable, reciprocal relationships developed over time as a cultural approach. This cultural holistic approach is also known as Systemic Literacy, which considers how systems function beyond "mechanical" aspects and include political, philosophical, psychological, emotional, relational, anthropological, and ecological dimensions. When Indigenous-led, these dimensions can be unified into participatory, community-centered conservation practices that support long-term human and environmental well-being. There is a growing recognition of the criticality of Indigenous leadership in sustainability practices, as well as that partnerships with Indigenous peoples and weaving knowledge systems, as a missing link to approaching global ecological crises. This review investigates the inequality in technological systems—the "digital divide" that further inhibits participation by communities and groups that retain knowledge of "place" and may offer the most transformative solutions. Following the review and synthesis, this study presents cybernetics as a bridge of understanding to Indigenous systems thinking. As non-Indigenous scholars, we hope that this study serves to foster informed, productive, and respectful dialogues so that the strength of diverse knowledges might offer whole-systems approaches to decision making that tackle wicked problems. Lastly, we discuss use cases of community-based processes and co-developed geospatial technologies, along with ethical considerations, as avenues toward enhancing equity and making advances in democratizing and decolonizing technology. [ABSTRACT FROM AUTHOR]

Urban villages represent informal residential areas emerging since China's rapid urbanization process. Scientific map generalization of urban villages with scientific maps aids readers in discerning their distribution and making informed decisions concerning them. However, there is still a scarcity of research on the automatic extraction and generalization of urban villages from vector data, which needs to be studied to further improve the expression of maps. To address this problem, this paper presents a methodology for the extraction and generalization of urban villages from Digital Line Graphics. Firstly, a heuristic approach is employed to analyze the atypical morphological characteristics of urban villages. Then, indices based on computational geometry and the modified Hausdorff distance are utilized to quantify these traits. Lastly, an automatic generalization principle for urban villages is offered. The approach was tested in experimental blocks and proved to be effective. It offers a novel method for the automatic extraction and cartography of urban villages. [ABSTRACT FROM AUTHOR]

The cyberspace map, as one of the important tools for describing cyberspace, provides a visual representation of the dynamic and elusive nature of cyberspace. It has become a research hotspot in multiple disciplinary fields. Compared with traditional maps, cyberspace maps lack the guidance of cartography theory and have not yet formed a unified understanding. Clarifying the concept of the cyberspace map and developing a conceptual model of it could enhance people's unified understanding of cyberspace. Drawing from the perspective of cartography, this paper analyzes the current situation of cyberspace map research, first discussing the characteristics and definition of the cyberspace map and then proposing the conceptual model of a cyberspace map. This model elaborates on the types of map elements and their specific composition, the strength of their element–space association, the mapping of relationships between elements, element symbolization, and map expression. Then, based on the model proposed in this paper, typical maps are compared and analyzed, and design suggestions are provided. Finally, the entire article is summarized. This paper aims to adapt the development trend of cartography to the ternary space, clarify the basic concept of the cyberspace map, promote the development of cyberspace mapping theory, and lay the foundation for future research. [ABSTRACT FROM AUTHOR]

The topographic map plays a very important role in economic construction. In the process of drawing topographic maps, different symbols represent different ground objects, but the symbols representing complex ground objects are often complicated and difficult to create. Moreover, the creation process of complex map symbols can seriously affect the efficiency of topographic map production. Therefore, this paper proposes an automatic derivation method for creation of complex map symbols in a topographic map. The data used are new geographic entity data under the background of Chinese new fundamental surveying and mapping situation. Firstly, four derivation modes of complex map symbols are summarized, including feature-point mode, centroid mode, feature-line mode, and parallel-line mode; then, using the four modes singly or in combination, the complex map symbols of the topographic map are directly derived from the geographic entity data based on programming, and the topographic map cartographic result is obtained automatically. Finally, some topographic maps for Shanxi Province, China, is used for the validation of the creation of map symbols. The experimental results show that the proposed method can automatically derive the complex map symbols of the topographic map, greatly improving production efficiency and obtaining a good visualization effect. The proposed method is a new approach for a new situation and realizes the transformation and upgrading of fundamental surveying and mapping achievements. [ABSTRACT FROM AUTHOR]

Maps are the culmination of numerous choices, with many offering multiple alternatives. Not all of these choices are inherently guided by default, clarity, or universally accepted best practices, guidelines, or recommendations. In the realm of cartography, it is a distinct feature that individual decisions can be made, particularly regarding data preparation and selection and design aspects. As each map is a product of a multitude of decisions, the confidence we place in maps hinges on the reasonableness of these decisions. The trustworthiness of maps depends on whether these decisions are sound, unquestioned, readily accessible, and supported by dependable groups of decision makers whose reliability can be assessed based on their track record as an institution, reputation, and competence. The advent of user-friendly map-making software and data manipulation tools has placed some of these decisions in the hands of the general populace and those interested in using maps to convey specific agendas. This mirrors other forms of communication and has given rise to a growing discourse on "fake news", "fake media", and "fake maps", ultimately prompting us to question how we can trust the information being conveyed and how we can differentiate between "fake" and "trustworthy" maps. This paper highlights the fundamental aspects determined by the pure nature of cartographic modeling, which influences every attempt to understand, analyze, and express the context and trustworthiness of maps. It then identifies fundamental aspects of trustworthiness with respect to maps. Combining these two fundamental considerations represents an epistemological attempt to identify a research portfolio. An example of an empirical study on identifying selected aspects of this portfolio demonstrates the potential of gaining a better understanding of the context given. [ABSTRACT FROM AUTHOR]

This paper studies the design of point symbols on widely used online maps and apps that portray tourist points of interest (POIs). Tourist maps are among the most commonly used types of maps nowadays. The ease of travel leads to an ever-increasing demand for tourist maps. Therefore, appropriate map design, content and technical means are necessary for better information transfer and communication between the map and the user. Online maps and apps were selected according to specific criteria (e.g., language, geographic area, pictographic symbols, interactivity). Pictographic point symbols for POIs related to tourism activities were collected and described by variables. The frame and the pictogram of the point symbols were the two main directions for choosing the descriptive variables. Description is based on the cognitive scheme for interpretation of cartographic symbols with some improvements. The study reveals the characteristics of the point symbols and constitutes a documentation of the applied practices. The main trends prevalent in the design of these symbols are highlighted and commented on in relation to traditional cartographic practices and guidelines for the design of point symbols. [ABSTRACT FROM AUTHOR]

The think-aloud method is a widely used method for evaluating the usability of websites and software. However, it can also be used with cartographic products, an area which has been neglected up to now. It is a method in which test participants verbalise all their thought processes aloud. The participants are given a test scenario containing tasks to be completed. The method aims to reveal the participants' subjective attitudes toward a product in order to evaluate its usability. The present paper describes the use of the think-aloud method to evaluate the usability of a cartographic work—the regional atlas of the Moravian-Silesian Region. The study includes (I) a complete review of the method, based on the studies conducted; (II) testing tools for working with recorded data; (III) designing an experiment for evaluating the usability of the atlas; and (IV) the resulting qualitative and quantitative evaluation of the atlas based on the obtained results. During the study, three approaches were proposed to process and analyse the audio recordings. The first option was to separate the audio recordings into individual annotations and analyse them. The second option was to convert the recordings to text and perform a linguistic analysis. The third supplementary option was to use all the material produced and to analyse it subjectively and retrospectively, from the researcher's perspective. All three options were used in the final assessment of the atlas. Based on the participants' statements, any shortcomings in the studied atlas were identified for each topic (e.g., non-dominant maps or exceedingly complex infographics), and recommendations for their elimination were proposed. [ABSTRACT FROM AUTHOR]

Quantile, equal interval, and natural breaks methods are widely used data classification methods in geospatial analysis and cartography. However, when applied to data with skewed distributions, they can only reveal the variations of either high frequent values or extremes, which often leads to undesired and biased classification results. To handle this problem, Esri provided a compromise method, named geometric interval classification (GIC). Although GIC performs well for various classification tasks, its mathematics and solution process remain unclear. Moreover, GIC is theoretically only applicable to single-peak (single-modal), one-dimensional data. This paper first mathematically formulates GIC as a general optimization problem subject to equality constraint. We then further adapt such formulated GIC to handle multi-peak and multi-dimensional data. Both thematic data and remote sensing images are used in this study. The comparison with other classification methods demonstrates the advantage of GIC being able to highlight both middle and extreme values. As such, it can be regarded as a general data classification approach for thematic mapping and other geospatial applications. [ABSTRACT FROM AUTHOR]

The halfway point for the implementation of the United Nations Sustainable Development Goals (SDGs) was marked in 2023, as set forth in the 2030 Agenda. Geospatial technologies have proven indispensable in assessing and tracking fundamental components of each of the 17 SDGs, including climatological and ecological trends, and changes and humanitarian crises and socio-economic impacts. However, gaps remain in the capacity for geospatial and related digital technologies, like AI, to provide a deeper, more comprehensive understanding of the complex and multi-factorial challenges delineated in the SDGs. Lack of progress toward these goals, and the immense implementation challenges that remain, call for inclusive and holistic approaches, coupled with transformative uses of digital technologies. This paper reviews transdisciplinary, holistic, and participatory approaches to address gaps in ethics and diversity in geospatial and related technologies and to meet the pressing need for bottom-up, community-driven initiatives. Small-scale, community-based initiatives are known to have a systemic and aggregate effect toward macro-economic and global environmental goals. Cybernetic systems thinking approaches are the conceptual framework investigated in this study, as these approaches suggest that a decentralized, polycentric system—for example, each community acting as one node in a larger, global system—has the resilience and capacity to create and sustain positive change, even if it is counter to top-down decisions and mechanisms. Thus, this paper will discuss how holistic systems thinking—societal, political, environmental, and economic choices considered in an interrelated context—may be central to building true resilience to climate change and creating sustainable development pathways. Traditional and Indigenous knowledge (IK) systems around the world hold holistic awareness of human-ecological interactions—practicable, reciprocal relationships developed over time as a cultural approach. This cultural holistic approach is also known as Systemic Literacy, which considers how systems function beyond “mechanical” aspects and include political, philosophical, psychological, emotional, relational, anthropological, and ecological dimensions. When Indigenous-led, these dimensions can be unified into participatory, community-centered conservation practices that support long-term human and environmental well-being. There is a growing recognition of the criticality of Indigenous leadership in sustainability practices, as well as that partnerships with Indigenous peoples and weaving knowledge systems, as a missing link to approaching global ecological crises. This review investigates the inequality in technological systems—the “digital divide” that further inhibits participation by communities and groups that retain knowledge of “place” and may offer the most transformative solutions. Following the review and synthesis, this study presents cybernetics as a bridge of understanding to Indigenous systems thinking. As non-Indigenous scholars, we hope that this study serves to foster informed, productive, and respectful dialogues so that the strength of diverse knowledges might offer whole-systems approaches to decision making that tackle wicked problems. Lastly, we discuss use cases of community-based processes and co-developed geospatial technologies, along with ethical considerations, as avenues toward enhancing equity and making advances in democratizing and decolonizing technology.

Where the streets have no name is probably the preferred place for a volunteer OpenStreetMapper. Launched in 2004, the Open Street Map project aimed to share geographical data based on volunteer mapping and led to the collection of geographical data from almost every country in the world within fifteen years. The increased dissemination of cartographic data via the Internet has been helpful in real life, socially, and has resulted in the number of published documents increasing rapidly. To evaluate the impact of volunteered cartography on scientific research, a science mapping approach was applied to the published literature on the Open Street Map project on the basis of co-occurrence and co-citation analyses, which showed that the main themes (conceptual network) were of technical relevance, collaboration among scholars and among institutes (social network) was not strong, and knowledge and ideas circulated within a limited network. In this study, documents published by OpenStreetMappers were analysed for the first time; thus, it was possible to highlight gaps in volunteered cartography and to discuss further improvements to the Open Street Map project. [ABSTRACT FROM AUTHOR]

An introduction is presented wherein the editor discusses various reports on topics including the comparison between OpenStreetMap and volunteered geographic information (VGI), the role of collaborative mapping as a way to engage citizens in decision-making, and an outline of blueprint for collaborative geospatial shoreline inventory.

Automatically acquiring comprehensive, accurate, and real-time mapping information and translating this information into digital maps are challenging problems. Traditional methods are time consuming and costly because they require expensive field surveying and labor-intensive post-processing. Recently, the ubiquitous use of positioning technology in vehicles and other devices has produced massive amounts of trajectory data, which provide new opportunities for digital map production and updating. This paper presents an automatic method for producing road networks from raw vehicle global positioning system (GPS) trajectory data. First, raw GPS positioning data are processed to remove noise using a newly proposed algorithm employing flexible spatial, temporal, and logical constraint rules. Then, a new road network construction algorithm is used to incrementally merge trajectories into a directed graph representing a digital map. Furthermore, the average road traffic volume and speed are calculated and assigned to corresponding road segments. To evaluate the performance of the method, an experiment was conducted using 5.76 million trajectory data points from 200 taxis. The result was qualitatively compared with OpenStreetMap and quantitatively compared with two existing methods based on the F-score. The findings show that our method can automatically generate a road network representing a digital map. [ABSTRACT FROM AUTHOR]

Transitional waters (TWs) are relevant ecological and economical ecosystems that include estuaries, deltas, bays, wetlands, marshes, coastal lakes, and coastal lagoons and play a central role in providing food, protecting coastal environments, and regulating nutrients. However, human activities such as industrialization, urbanization, tourism, and agriculture are threatening these ecosystems, which results in contamination and habitat degradation. Therefore, it is essential to evaluate contamination in TW to develop effective management and protection strategies. This study analyses the application of geospatial technologies (GTS) for monitoring and predicting contaminant distribution in TW. Cartography, interpolation, complex spatial methods, and remote sensing were applied to assess contamination profiles by heavy metals, and persistent organic compounds, and analyze contamination indices or some physicochemical water parameters. It is concluded that integrating environmental and demographic data with GTS would help to identify critical points of contamination and promote ecosystem resilience to ensure long-term health and human well-being. This review comprehensively analyzes the methods, indicators, and indices used to assess contamination in transitional waters in conjunction with GTS. It offers a valuable foundation for planning future research on pollution in these types of waters or other similar water bodies worldwide. [ABSTRACT FROM AUTHOR]

Propelled by emerging technologies such as artificial intelligence and deep learning, the essence and scope of cartography have significantly expanded. The rapid progress in neuroscience has raised high expectations for related disciplines, furnishing theoretical support for revealing and deepening the essence of maps. In this study, CiteSpace was used to examine the confluence of cartography and neural networks over the past decade (2013–2023), thus revealing the prevailing research trends and cutting-edge investigations in the field of machine learning and its application in mapping. In addition, this analysis included the systematic categorization of knowledge clusters arising from the fusion of cartography and neural networks, which was followed by the discernment of pivotal clusters in the field of knowledge mapping. Crucially, this study diligently identified the critical studies (milestones) that have made significant contributions to the development of these elucidated clusters. Timeline analysis was used to track these studies' origins, evolution, and current status. Finally, we constructed collaborative networks among the contributing authors, journals, institutions, and countries. This mapping aids in identifying and visualizing the primary contributing factors of the evolution of knowledge mapping encompassing cartography and neural networks, thus facilitating interdisciplinary and multidisciplinary research and investigations. [ABSTRACT FROM AUTHOR]

Globally, most weather-related damages are caused by thunderstorms. Besides floods, strong wind, and hail, one of the major thunderstorm ground effects is lightning. Therefore, lightning investigations, including detection, cluster identification, tracking, and nowcasting are essential. To enable reliable decisions, current and predicted lightning cluster- and track features as well as analysis results have to be represented in the most appropriate way. Our paper introduces a framework which includes identification, tracking, nowcasting, and in particular visualization and statistical analysis of dynamic lightning data in three-dimensional space. The paper is specifically focused on enabling users to conduct the visual analysis of lightning data for the purpose of identification and interpretation of spatial-temporal patterns embedded in lightning data, and their dynamics. A graphic user interface (GUI) is developed, wherein lightning tracks and predicted lightning clusters, including their prediction certainty, can be investigated within a 3D view or within a Space-Time-Cube. In contrast to previous work, our approach provides insight into the dynamics of past and predicted 3D lightning clusters and cluster features over time. We conclude that an interactive visual exploration in combination with a statistical analysis can provide new knowledge within lightning investigations and, thus, support decision-making in weather forecast or lightning damage prevention. [ABSTRACT FROM AUTHOR]

The quality aspects of OpenStreetMap (OSM), as the global representation of crowd-sourced mapping, have always been of priomary concern to academics. While the methodologies for checking its quality against the national maps have been implemented by a number of studies, there are minimal works on how to practically improve the quality of OSM towards being an authoritative map source. This paper presents a method for conflating road attributes, namely the name and reference code, of OSM with the Open Data provided by Ordnance Survey (the British national mapping agency). The added values in the proposed methodology include the daily updates and serving of the conflated maps via open Web Services. More importantly, the OSM crowd correction is facilitated by frequently highlighting and web-serving the individual differences. There are currently over 5,800 differences in matching road names and references between the two datasets. In addition to describing the conflation methodology, the different geographic distribution patterns of the identified differences are discussed. A negative effect of the road density on the ratio of the mismatched features between the two datasets is observable, evidenced by their different geographical distribution over the map. It is shown that the best correspondence between attributes exists in the very dense areas, followed by the very low density areas, and lastly in the middle to large sized cities. [ABSTRACT FROM AUTHOR]

This paper presents a novel RGB-D 3D reconstruction algorithm for the indoor environment. The method can produce globally-consistent 3D maps for potential GIS applications. As the consumer RGB-D camera provides a noisy depth image, the proposed algorithm decouples the rotation and translation for a more robust camera pose estimation, which makes full use of the information, but also prevents inaccuracies caused by noisy depth measurements. The uncertainty in the image depth is not only related to the camera device, but also the environment; hence, a novel uncertainty model for depth measurements was developed using Gaussian mixture applied to multi-windows. The plane features in the indoor environment contain valuable information about the global structure, which can guide the convergence of camera pose solutions, and plane and feature point constraints are incorporated in the proposed optimization framework. The proposed method was validated using publicly-available RGB-D benchmarks and obtained good quality trajectory and 3D models, which are difficult for traditional 3D reconstruction algorithms. [ABSTRACT FROM AUTHOR]

With the opening up of the Landsat archive, global high resolution land cover maps have begun to appear. However, they often have only a small number of high level land cover classes and they are static products, corresponding to a particular period of time, e.g., the GlobeLand30 (GL30) map for 2010. The OpenStreetMap (OSM), in contrast, consists of a very detailed, dynamically updated, spatial database of mapped features from around the world, but it suffers from incomplete coverage, and layers of overlapping features that are tagged in a variety of ways. However, it clearly has potential for land use and land cover (LULC) mapping. Thus the aim of this paper is to demonstrate how the OSM can be converted into a LULC map and how this OSM-derived LULC map can then be used to first update the GL30 with more recent information and secondly, enhance the information content of the classes. The technique is demonstrated on two study areas where there is availability of OSM data but in locations where authoritative data are lacking, i.e., Kathmandu, Nepal and Dar es Salaam, Tanzania. The GL30 and its updated and enhanced versions are independently validated using a stratified random sample so that the three maps can be compared. The results show that the updated version of GL30 improves in terms of overall accuracy since certain classes were not captured well in the original GL30 (e.g., water in Kathmandu and water/wetlands in Dar es Salaam). In contrast, the enhanced GL30, which contains more detailed urban classes, results in a drop in the overall accuracy, possibly due to the increased number of classes, but the advantages include the appearance of more detailed features, such as the road network, that becomes clearly visible. [ABSTRACT FROM AUTHOR]

Cartographic generalization is a problem, which poses interesting challenges to automation. Whereas plenty of algorithms have been developed for the different sub-problems of generalization (e.g., simplification, displacement, aggregation), there are still cases, which are not generalized adequately or in a satisfactory way. The main problem is the interplay between different operators. In those cases the human operator is the benchmark, who is able to design an aesthetic and correct representation of the physical reality. Deep learning methods have shown tremendous success for interpretation problems for which algorithmic methods have deficits. A prominent example is the classification and interpretation of images, where deep learning approaches outperform traditional computer vision methods. In both domains-computer vision and cartography-humans are able to produce good solutions. A prerequisite for the application of deep learning is the availability of many representative training examples for the situation to be learned. As this is given in cartography (there are many existing map series), the idea in this paper is to employ deep convolutional neural networks (DCNNs) for cartographic generalizations tasks, especially for the task of building generalization. Three network architectures, namely U-net, residual U-net and generative adversarial network (GAN), are evaluated both quantitatively and qualitatively in this paper. They are compared based on their performance on this task at target map scales 1:10,000, 1:15,000 and 1:25,000, respectively. The results indicate that deep learning models can successfully learn cartographic generalization operations in one single model in an implicit way. The residual U-net outperforms the others and achieved the best generalization performance. [ABSTRACT FROM AUTHOR]

Shoho Castle Maps are maps of castle towns throughout Japan drawn by Kano School painters on the order of the shogun in 1644. The Shoho Castle Map of Takada, Joetsu City, Niigata Prefecture was used to visualize local distortions in historical maps and to scrutinize the mapmaking process. A novel method, geographically weighted bidimensional regression, was developed and applied to visualize the local distortions of the map. Exaggerated expressions by mapmakers that have not been identified in previous studies were revealed. That is, in addition to the castle being drawn enlarged, the town where the merchants and artisans lived was drawn larger than the castle. Therefore, the Takada Shoho Castle Map reflects mapmakers' intentions, besides enlarging military facilities, which appear to have emphasized the pictorial composition of the map by placing the main gate to the castle at the center and drawing the map area evenly from the center in a well-balanced layout. [ABSTRACT FROM AUTHOR]

The field of planetary mapping and cartography builds almost exclusively on remote-sensing data and can be defined by three distinct concepts: systematic imaging as performed through spacecraft surveying, reference mapping as performed through the compilation of reference maps, i.e., regional to global image and topographic maps, and thematic mapping, which aims at abstracting and contextualizing spatial information to generate complex thematic maps, such as geologic or geomorphologic maps. While thematic mapping represents the highest form of abstraction of information that is provided through systematic mapping, thematic mapping also provides scientific reasoning in support of systematic mapping and exploration through spatially contextualized knowledge. For the development of knowledge, it is paramount to manage and exploit the value of thematic maps as research products, and to design a reliable and transparent development process from the beginning of the mapping phase as there is almost no validation for thematic maps. A key element in accomplishing these objectives is well-designed structures and metadata which are maintained within spatial data infrastructures (SDI) and shared as a coordinated process in research data management through data models. In this contribution, we focus on the need to transfer planetary thematic maps into findable, accessible, interoperable, reusable (FAIR), as well as transparent research data assets to facilitate improved knowledge extraction and also to compensate for limitations caused by the lack of conventional validation options. We review the current status of planetary thematic mapping, and we discuss the principles and roles of mappers and publishers in the process of creating and stewarding digital planetary maps and associated data products. We then present and discuss a set of recommendations that are closely tied to the FAIR concepts in research data management to accomplish such tasks. [ABSTRACT FROM AUTHOR]

This article sets forth the early phases of a methodological proposal for designing and developing Volunteered Geographic Information (VGI) initiatives based on a system perspective analysis in which the components depend and interact dynamically among each other. First, it focuses on those characteristics of VGI projects that present different goals and modes of organization, while using a crowdsourcing strategy to manage participants and contributions. Next, a tool is developed in order to design the central crowdsourced processing unit that is best suited for a specific project definition, associating it with a trend towards crowd-based or community-driven approaches. The design is structured around the characterization of different ways of participating, and the task cognitive demand of working on geo-information management, spatial problem solving and ideation, or knowledge acquisition. Then, the crowdsourcing process design helps to identify what kind of participants are needed and outline subsequent engagement strategies. This is based on an analysis of differences among volunteers' participatory behaviors and the associated set of factors motivating them to contribute, whether on a crowd or community-sourced basis. From a VGI system perspective, this paper presents a set of guidelines and methodological steps in order to align project goals, processes and volunteers and thus successfully attract participation. This methodology helps establish the initial requirements for a VGI system, and, in its current state, it mainly focuses on two components of the system: project and participants. [ABSTRACT FROM AUTHOR]

Land surface water mapping is one of the most basic classification tasks to distinguish water bodies from dry land surfaces. In this paper, a water mapping method was proposed based on multi-scale level sets and a visual saliency model (MLSVS), to overcome the lack of an operational solution for automatically, rapidly and reliably extracting water from large-area and fine spatial resolution Synthetic Aperture Radar (SAR) images. This paper has two main contributions, as follows: (1) The method integrated the advantages of both level sets and the visual saliency model. First, the visual saliency map was applied to detect the suspected water regions (SWR), and then the level set method only needed to be applied to the SWR regions to accurately extract the water bodies, thereby yielding a simultaneous reduction in time cost and increase in accuracy; (2) In order to make the classical Itti model more suitable for extracting water in SAR imagery, an improved texture weighted with the Itti model (TW-Itti) is employed to detect those suspected water regions, which take into account texture features generated by the Gray Level Co-occurrence Matrix (GLCM) algorithm, Furthermore, a novel calculation method for center-surround differences was merged into this model. The proposed method was tested on both Radarsat-2 and TerraSAR-X images, and experiments demonstrated the effectiveness of the proposed method, the overall accuracy of water mapping is 98.48% and the Kappa coefficient is 0.856. [ABSTRACT FROM AUTHOR]

2D maps with contour lines can be difficult for students to visualize in three-dimensions to interpret relief. Despite this challenge, teaching based on 2D contour lines is still used, which could generate frustration/motivation problems among students. Recently, strategies based on 3D technologies such as Augmented Reality (AR) have proven to be motivating for students. Has the time come for a paradigm shift in the teaching of land interpretation/representation? The present paper shows the results of an experiment in which 41 engineering students of the subject Cartography performed an activity with 2D contour lines. The impact on students’ motivation was compared with AR. In addition, data about efficiency, effectiveness and user satisfaction were assessed. Results showed that traditional 2D contour line activities were less motivating for students, compared to AR. However, students perceived that doing 2D exercises made them more competent than with AR, although they reported that the 2D exercises required more effort. In terms of participant’s spatial reasoning acquisition, 2D strategies offered results similar to AR. Overall, these results suggest that 2D teaching methodologies are still effective and can be complemented by the use of innovative 3D visualization technologies. [ABSTRACT FROM AUTHOR]

Multiple laser scanner hardware configurations can be applied to Mobile Mapping Systems. As best practice, laser scanners are rotated horizontally or inclined vertically to increase the probability of contact between the laser scan plane and any surfaces that are perpendicular to the direction of travel. Vertical inclinations also maximise the number of scan profiles striking narrow vertical features, something that can be of use when trying to recognise features. Adding a second scanner allows an MMS to capture more data and improve laser coverage of an area by filling in laser shadows. However, in any MMS the orientation of each scanner on the platform must be decided upon. Changes in the horizontal or vertical orientations of the scanner can increase the range to vertical targets and the road surface, with excessive scanner angles lowering point density significantly. Limited information is available to assist the manufacturers or operators in identifying the optimal scanner orientation for roadside surveys. The method proposed in this paper applies 3D surface normals and geometric formulae to assess the influence of scanner orientation on point distribution. It was demonstrated that by changing the orientation of the scanner the number of pulses striking a target could be greatly increased, and the number of profiles intersecting with the target could also be increased--something that is particularly important for narrow vertical features. The importance of identifying the correct trade-off between the number of profiles intersecting with the target and the point spacing was also raised. [ABSTRACT FROM AUTHOR]

In this paper, we address the topic of user-centered design (UCD) for cartography, GIScience, and visual analytics. Interactive maps are ubiquitous in modern society, yet they often fail to "work" as they could or should. UCD describes the process of ensuring interface success--map-based or otherwise--by gathering input and feedback from target users throughout the design and development of the interface. We contribute to the expanding literature on UCD for interactive maps in two ways. First, we synthesize core concepts on UCD from cartography and related fields, as well as offer new ideas, in order to organize existing frameworks and recommendations regarding the UCD of interactive maps. Second, we report on a case study UCD process for GeoVISTA CrimeViz, an interactive and webbased mapping application supporting visual analytics of criminal activity in space and time. The GeoVISTA CrimeViz concept and interface were improved iteratively by working through a series of user→utility→usability loops in which target users provided input and feedback on needs and designs (user), prompting revisions to the conceptualization and functional requirements of the interface (utility), and ultimately leading to new mockups and prototypes of the interface (usability) for additional evaluation by target users (user... and so on). Together, the background review and case study offer guidance for applying UCD to interactive mapping projects, and demonstrate the benefit of including target users throughout design and development. [ABSTRACT FROM AUTHOR]

The assessment of data quality from different sources can be considered as a key challenge in supporting effective geospatial data integration and promoting collaboration in mapping projects. This paper presents a methodology for assessing positional and shape quality for authoritative large-scale data, such as Ordnance Survey (OS) UK data and General Directorate for Survey (GDS) Iraq data, and Volunteered Geographic Information (VGI), such as OpenStreetMap (OSM) data, with the intention of assessing possible integration. It is based on the measurement of discrepancies among the datasets, addressing positional accuracy and shape fidelity, using standard procedures and also directional statistics. Line feature comparison has been undertaken using buffering techniques and statistics, whilst shape metrics, including moments invariant, have been applied to assess polygon matching. The analyses are presented with a user-friendly interface which eases data input, computation and output of results, and assists in interpretation of the comparison. The results show that a comparison of positional and shape characteristics of OS data or GDS data, with those of OSM data, indicates that their integration for large scale mapping applications is not viable. [ABSTRACT FROM AUTHOR]

Urban villages represent informal residential areas emerging since China’s rapid urbanization process. Scientific map generalization of urban villages with scientific maps aids readers in discerning their distribution and making informed decisions concerning them. However, there is still a scarcity of research on the automatic extraction and generalization of urban villages from vector data, which needs to be studied to further improve the expression of maps. To address this problem, this paper presents a methodology for the extraction and generalization of urban villages from Digital Line Graphics. Firstly, a heuristic approach is employed to analyze the atypical morphological characteristics of urban villages. Then, indices based on computational geometry and the modified Hausdorff distance are utilized to quantify these traits. Lastly, an automatic generalization principle for urban villages is offered. The approach was tested in experimental blocks and proved to be effective. It offers a novel method for the automatic extraction and cartography of urban villages.

Despite the growing efficiency of the map-design process in general, tactile mapping has remained peripheral to mainstream cartography. For a specific group of people with visual impairment, however, tactile maps are the only effective way to obtain a complex idea about the geospatial distribution of the surrounding world. As there are numerous specifics in creating these 3D maps and only a limited group of users, tactile products have usually been either very simple creations or, on the other hand, difficult and expensive to produce. Modern trends and progress in the availability of new technologies (e.g., 3D printing) bring new possibilities for keeping tactile map production both effective and up to date. Therefore, this paper aims to present a methodology to apply the TouchIt3D technology to link 3D-printed multi-material tactile maps with a mobile device. Utilizing this solution resulted in a set of interactive tactile maps following current trends of inclusive education. Using OpenStreetMap data together with a semi-automated workflow significantly lowered expenses compared to antecedent maps with similar functionality. A semi-automated workflow was designed, focusing on three use cases of independent movement: walking, using public transport, and tourism. [ABSTRACT FROM AUTHOR]

There are many studies related to Imagery Segmentation (IS) in the field of Geographic Information (GI). However, none of them address the assessment of IS results from a positional perspective. In a field in which the positional aspect is critical, it seems reasonable to think that the quality associated with this aspect must be controlled. This paper presents an automatic positional accuracy assessment (PAA) method for assessing this quality component of the regions obtained by means of the application of a textural segmentation algorithm to a Very High Resolution (VHR) aerial image. This method is based on the comparison between the ideal segmentation and the computed segmentation by counting their differences. Therefore, it has the same conceptual principles as the automatic procedures used in the evaluation of the GI's positional accuracy. As in any PAA method, there are two key aspects related to the sample that were addressed: (i) its size—specifically, its influence on the uncertainty of the estimated accuracy values—and (ii) its categorization. Although the results obtained must be taken with caution, they made it clear that automatic PAA procedures, which are mainly applied to carry out the positional quality assessment of cartography, are valid for assessing the positional accuracy reached using other types of processes. Such is the case of the IS process presented in this study. [ABSTRACT FROM AUTHOR]

Indigenous maps are critical in understanding the historic and current land tenure of Indigenous groups. Furthermore, Indigenous claims to land can be seen in their connections via toponymy. European concepts of territory and political boundaries did not coincide with First Nation/American Indian views, resulting in the mistaken view that Natives did not have formal concepts of their territories. And Tribes/First Nations with cross-border territory have special jurisdictional problems. This paper illustrates how many Native residents were very spatially aware of their own lands, as well as neighboring nations' lands, overlaps between groups, hunting territories, populations, and trade networks. Finally, the Sinixt First Nation serve as a perfect example of a case study on how an Aboriginal people are currently inputting and using a GIS representation of their territory with proper toponymy and use areas. [ABSTRACT FROM AUTHOR]

Structurally describing the portrayal-related information by using a standalone Digital Cartographic Model on top of a Digital Landscape Model has been proved applicable and beneficial for 2D mapping but has not yet been applied to 3D cadastre. This study, therefore, evaluates the applicability of digital cartographic model and the corresponding visualization pipeline for 3D cadastre in the context of Chinese urban cadastre. This research starts by identifying the requirements and design features of 3D cadastre mapping through a literature review and interviews with users and cartographers. Addressing the limitations of the existing general-purpose models, this paper proposes an ad hoc 3D cadastre digital cartographic model. The main developments of the proposed model are the inclusion of 3D content modeling, the support of the compound 3D symbols, and the introduction of the semantic transformation. The proposed model is then embedded into three parts of the cadastre visualization pipeline: the symbolic rule design, graphic content creation, and scene dissemination. The empirical result of qualitative proof-of-concept user tests supports that the proposed visualization pipeline is applicable and yields promising visualization results. The digital cartographic model-based visualization pipeline is a novel 3D cadastre mapping paradigm that facilitates designing, producing, sharing, and administrating. [ABSTRACT FROM AUTHOR]

Cartographic generalization is a problem, which poses interesting challenges to automation. Whereas plenty of algorithms have been developed for the different sub-problems of generalization (e.g., simplification, displacement, aggregation), there are still cases, which are not generalized adequately or in a satisfactory way. The main problem is the interplay between different operators. In those cases the human operator is the benchmark, who is able to design an aesthetic and correct representation of the physical reality. Deep learning methods have shown tremendous success for interpretation problems for which algorithmic methods have deficits. A prominent example is the classification and interpretation of images, where deep learning approaches outperform traditional computer vision methods. In both domains-computer vision and cartography-humans are able to produce good solutions. A prerequisite for the application of deep learning is the availability of many representative training examples for the situation to be learned. As this is given in cartography (there are many existing map series), the idea in this paper is to employ deep convolutional neural networks (DCNNs) for cartographic generalizations tasks, especially for the task of building generalization. Three network architectures, namely U-net, residual U-net and generative adversarial network (GAN), are evaluated both quantitatively and qualitatively in this paper. They are compared based on their performance on this task at target map scales 1:10,000, 1:15,000 and 1:25,000, respectively. The results indicate that deep learning models can successfully learn cartographic generalization operations in one single model in an implicit way. The residual U-net outperforms the others and achieved the best generalization performance.

In map generalization, scale reduction and feature symbolization inevitably generate problems of overlapping objects or map congestion. To solve the legibility problem with respect to the generalization of dispersed rural buildings, selection of buildings is necessary and can be transformed into an optimization problem. In this paper, an improved genetic algorithm for building selection is designed to be able to incorporate cartographic constraints related to the building selection problem. Part of the local constraints for building selection is used to constrain the encoding and genetic operation. To satisfy other local constraints, a preparation phase is necessary before building selection, which includes building enlargement, local displacement, conflict detection, and attribute enrichment. The contextual constraints are used to ascertain a fitness function. The experimental results indicate that the algorithm proposed in this article can obtain good results for building selection whilst preserving the spatial distribution characteristics of buildings. [ABSTRACT FROM AUTHOR]

Maps are the culmination of numerous choices, with many offering multiple alternatives. Not all of these choices are inherently guided by default, clarity, or universally accepted best practices, guidelines, or recommendations. In the realm of cartography, it is a distinct feature that individual decisions can be made, particularly regarding data preparation and selection and design aspects. As each map is a product of a multitude of decisions, the confidence we place in maps hinges on the reasonableness of these decisions. The trustworthiness of maps depends on whether these decisions are sound, unquestioned, readily accessible, and supported by dependable groups of decision makers whose reliability can be assessed based on their track record as an institution, reputation, and competence. The advent of user-friendly map-making software and data manipulation tools has placed some of these decisions in the hands of the general populace and those interested in using maps to convey specific agendas. This mirrors other forms of communication and has given rise to a growing discourse on “fake news”, “fake media”, and “fake maps”, ultimately prompting us to question how we can trust the information being conveyed and how we can differentiate between “fake” and “trustworthy” maps. This paper highlights the fundamental aspects determined by the pure nature of cartographic modeling, which influences every attempt to understand, analyze, and express the context and trustworthiness of maps. It then identifies fundamental aspects of trustworthiness with respect to maps. Combining these two fundamental considerations represents an epistemological attempt to identify a research portfolio. An example of an empirical study on identifying selected aspects of this portfolio demonstrates the potential of gaining a better understanding of the context given.

Maps enable us to relate to spatial phenomena and events from viewpoints far beyond direct experience. By employing signs and symbols, maps communicate about near as well as distant geospatial phenomena, events, objects, or ideas. Besides acting as identifiers, map signs and symbols may, however, not only denote but also connote. While most cartographic research has focused on the denoting character of visual variables, research from related disciplines stresses the importance of connotative qualities on affect, cognition, and behavior. Hence, this research focused on the connotative character of map symbols by empirically assessing the affective qualities of shape stimuli. In three stimulus conditions of cartographic and non-cartographic contexts, affective responses towards a set of eight shape stimuli were assessed by employing a semantic differential technique. Overall findings showed that shape symbols lead to, at times, highly distinctive affective responses. Findings further suggest two particular stimulus clusters of affective qualities that prevailed over all stimulus conditions, i.e., a cluster of asymmetric stimuli and a cluster of symmetric stimuli. Between the intersection of psychology, cartography, and semiotics, this paper outlines theoretical perspectives on cartographic semiotics, discusses empirical findings, and addresses implications for future research. [ABSTRACT FROM AUTHOR]

Toponymy, a transversal discipline for geography, linguistics, and history, finds one of its main supports in cartography. Due to exhaustiveness on the territory, cadastral cartography and its toponymy have the ideal characteristics to develop systematic geographical analyses. Moreover, cadastre and geographical names are part of the geographic reference data according to Annex 1 of the INSPIRE directive. This work presents the design, implementation, and application of a methodology based on Geographic Information Systems and Extract, Transform, and Load (ETL) tools for detecting coincidences between the cadastral geoinformation and the official gazetteer corresponding to the province of Gipuzkoa, Spain. Methodologically, this study proposes a solution to the issues raised by bilingualism in the study area. This problem is approached a priori, in the previous data treatment, and a posteriori, applying semantic criteria. The results show a match between the datasets of close to 40%. In this way, the uniqueness and richness of the analyzed source and its outstanding contribution to the potential integration of the official toponymic corpus are evidenced. [ABSTRACT FROM AUTHOR]

Eye movement research is a burgeoning frontier area in cartography that has attracted much attention from cartographers. However, the substantial amount of relevant literature poses a challenge for researchers aiming to obtain a rapid understanding of the intellectual structure of this research field. The purpose of this paper is to introduce the use of bibliometric analysis methods and multiple visual metaphors to visualize the intellectual structure of eye movement research in cartography, including the classic literature, research theme clusters, and research hotspots, etc. We also explain the use of geovisualization method, which can efficiently represent the spatial distribution of scientific power. Although the analysis results may not fully describe the whole research field, this method is generally applicable. We hope that it will not only help researchers to quickly grasp the evolution and trends of this research field, but will also become a novel method of merging geovisualization with knowledge visualization. [ABSTRACT FROM AUTHOR]

Weather is one of the things that interest almost everyone. Weather maps are therefore widely used and many users use them in everyday life. To identify the potential usability problems of weather web maps, the presented research was conducted. Five weather maps were selected for an eye-tracking experiment based on the results of an online questionnaire: DarkSky, In-Počasí, Windy, YR.no, and Wundermap. The experiment was conducted with 34 respondents and consisted of introductory, dynamic, and static sections. A qualitative and quantitative analysis of recorded data was performed together with a think-aloud protocol. The main part of the paper describes the results of the eye-tracking experiment and the implemented research, which identify the strengths and weaknesses of the evaluated weather web maps and point out the differences between strategies in using maps by the respondents. The results include findings such as the following: users worked with web maps in the simplest form and they did not look for hidden functions in the menu or attempt to find any advanced functionality; if expandable control panels were available, the respondents only looked at them after they had examined other elements; map interactivity was not an obstacle unless it contained too much information or options to choose from; searching was quicker in static menus that respondents did not have to switch on or off; the graphic design significantly influenced respondents and their work with the web maps. The results of the work may be useful for further scientific research on weather web maps and related user issues. [ABSTRACT FROM AUTHOR]

In this paper, online map services are reviewed from a cartographic point of view. The most popular online map services are selected based on worldwide website traffic data, provided by specialized sites, such as Similarweb, in terms of global coverage and popularity among users. Online map services are commented based on cartographic principles, conventions and traditional practices addressing topics, such as: Cartographic projection, orientation, scale, marginalia, content (thematic layers), symbology, generalization, annotation, color use and overall map design. Color schemes utilized in web maps are discussed in more detail, since based on studies concerning the selection of the preferable map by experts and laymen, color is undisputedly the most frequently mentioned factor. It can be stated that online map services generally adopt well-known cartographic practices, which are not always applied as expected. Moreover, suggestions for the improvement of online map services are made regarding cartographic projection, legend, content, symbolization, color, etc. [ABSTRACT FROM AUTHOR]

Cold-water coral reefs are hotspots of biological diversity and play an important role as carbonate factories in the global carbon cycle. Reef-building corals can be found in cold oceanic waters around the world. Detailed knowledge on the spatial location and distribution of coral reefs is of importance for spatial management, conservation and science. Carbonate mounds (reefs) are readily identifiable in high-resolution multibeam echosounder data but systematic mapping programs have relied mostly on visual interpretation and manual digitizing so far. Developing more automated methods will help to reduce the time spent on this laborious task and will additionally lead to more objective and reproducible results. In this paper, we present an attempt at testing whether rule-based classification can replace manual mapping when mapping cold-water coral carbonate mounds. To that end, we have estimated and compared the accuracies of manual mapping, pixel-based terrain analysis and object-based image analysis. To verify the mapping results, we created a reference dataset of presence/absence points agreed upon by three mapping experts. There were no statistically significant differences in the overall accuracies of the maps produced by the three approaches. We conclude that semi-automated rule-based methods might be a viable option for mapping carbonate mounds with high spatial detail over large areas. [ABSTRACT FROM AUTHOR]

Cartographic generalization is one of the important processes of transforming the content of both analogue and digital maps. The process of reducing details on the map has to be conducted in a planned way in each case when the map scale is to be reduced. As far as digital maps are concerned, numerous algorithms are used for the generalization of vector line elements. They are used if the scale of the map (on screen or printed) is changed, or in the process of smoothing vector lines (e.g., contours). The most popular method of reducing the number of vertices of a vector line is the Douglas-Peucker algorithm. An important feature of most algorithms is the fact that they do not take into account the cartographic properties of the transformed map element. Having analysed the existing methods of generalization, the authors developed a proprietary algorithm that is based on the analysis of the curvature of the vector line and fulfils the condition of objective generalization for elements of digital maps that may be used to transform open and closed vector lines. The paper discusses the operation of this algorithm, along with the graphic presentation of the generalization results for vector lines and the analysis of their accuracy. Treating the set of verification radii of a vector line as a statistical series, the authors propose applying statistical indices of position of these series, connected with the shape of the vector line, as the threshold parameters of generalization. The developed algorithm allows for linking the generalization parameters directly to the scale of the topographic map that was obtained after generalization. The results of the operation of the algorithm were compared to the results of the reduction of vertices with use of the Douglas-Peucker algorithm. The results demonstrated that the proposed algorithm not only reduced the number of vertices, but that it also smoothed the shape of physiographic lines, if applied to them. The authors demonstrated that the errors of smoothing and position of vertices did not exceed the acceptable values for the relevant scales of topographic maps. The developed algorithm allows for adjusting the surface of the generalized areas to their initial value more precisely. The advantage of the developed algorithm consists in the possibility to apply statistical indices that take the shape of lines into account to define the generalization parameters. [ABSTRACT FROM AUTHOR]

Cartographic representations are subject to sensory perception and rely on the translation of sensory perceptions into cartographic symbols. In this respect, cartography is closely related to aesthetics, as it represents an academic discipline of sensory perceptions. The scholarly concern with cartographic aesthetics, by today, has strongly been focused on the aesthetic impact of cartographic representations. The consideration of the philosophical sub-discipline of aesthetics however is rather restrained. This is also true for the connection between sociological questions and the social construction of aesthetic judgments. We address both topics in this article. We refer to post-critical cartographic theory. It accepts the socially constructed nature and power-bound nature of maps but does not reject "traditional" and widely established positivist cartography. Drawing on the theory of deviant cartographies related to this, we understand cartography designed according to aesthetic criteria as meta-deviant, as it makes the contingency of world interpretations clear. Especially augmented and virtual environments show a great potential to generate aesthetically constructed cartographic representations. Participatory cartography enables many people to reflect on the contingency of their spatial experiences and spatial abstractions without expert-like special knowledge. A prerequisite, however, is the greatest possible openness to topics and representations. This is not subject to a moral restriction. [ABSTRACT FROM AUTHOR]

This articles presents a new series of maps showing the climate and environmental variability of Botswana. Situated in southern Africa, Botswana has an arid to semi-arid climate, which significantly varies in its different regions: Kalahari Desert, Makgadikgadi Pan and Okavango Delta. While desert regions are prone to droughts and periods of extreme heat during the summer months, other regions experience heavy downpours, as well as episodic and unpredictable rains that affect agricultural activities. Such climatic variations affect social and economic aspects of life in Botswana. This study aimed to visualise the non-linear correlations between the topography and climate setting at the country's scale. Variables included T °C min, T °C max, precipitation, soil moisture, evapotranspiration (PET and AET), downward surface shortwave radiation, vapour pressure and vapour pressure deficit (VPD), wind speed and Palmer Drought Severity Index (PDSI). The dataset was taken from the TerraClimate source and GEBCO for topographic mapping. The mapping approach included the use of Generic Mapping Tools (GMT), a console-based scripting toolset, which enables the use of a scripting method of automated mapping. Several GMT modules were used to derive a set of climate parameters for Botswana. The data were supplemented with the adjusted cartographic elements and inspected by the Geospatial Data Abstraction Library (GDAL). The PDSI in Botswana in 2018 shows stepwise variation with seven areas of drought: (1) −3.7 to −2.2. (extreme); (2) −2.2 to −0.8 (strong, southern Kalahari); (3) −0.8 to 0.7 (significant, central Kalahari; (4) 0.7 to 2.1 (moderate); (5) 2.1 to 3.5 (lesser); (6) 3.5 to 4.9 (low); (7) 4.9 to 6.4 (least). The VPD has a general trend towards the south-western region (Kalahari Desert, up to 3.3), while it is lower in the north-eastern region of Botswana (up to 1.4). Other values vary respectively, as demonstrated in the presented 12 maps of climate and environmental inventory in Botswana. [ABSTRACT FROM AUTHOR]

This paper presents a new perspective of national power--sustainable national power (SNP)--emphasizing both the traditional comprehensive national power (CNP) and social and environmental sustainability. We propose a measurement to quantify the SNP based on the measurement of comprehensive national power and a sustainable adjusted index. In addition, density-equalizing maps are adopted to visualize the sustainable national power of countries in order to gain a better understanding for its current state and future development from a cartographic perspective. China and its neighboring countries are selected as a case study area. The results show that China outperforms other countries in most of the CNP dimensions but performs poorly in various SNP-adjusted dimensions within the study area. The composite score shows that China is with the highest regional SNP, followed by Japan, Russia, South Korea and India. Furthermore, time series of cartograms reveal evidence showing power transitions among countries. In addition, the effectiveness of cartograms for cartographic communication is discussed. [ABSTRACT FROM AUTHOR]

This paper deals with the issue of the perceptual aspects of selected graphic variables (specifically shape and size) and map background in cartographic visualization. The continued experimental study is based on previous findings and the presupposed cross-cultural universality of shape and size as a graphic variable. The results bring a new perspective on the usage of shape, size and presence/absence of background as graphic variables, as well as a comparison to previous studies. The results suggest that all examined variables influence the speed of processing. Respondents (Czech and Chinese, N = 69) identified target stimuli faster without a map background, with larger stimuli, and with triangular and circular shapes. Czech respondents were universally faster than Chinese respondents. The implications of our research were discussed, and further directions were outlined. [ABSTRACT FROM AUTHOR]

Modern positioning and sensor technology enable the acquisition of movement positions and attributes on an unprecedented scale. Therefore, a large amount of trajectory data can be used to analyze various movement phenomena. In cartography, a common way to visualize and explore trajectory data is to use the 3D cube (e.g., space-time cube), where trajectories are presented as a tilted 3D polyline. As larger movement datasets become available, this type of display can easily become confusing and illegible. In addition, movement datasets are often unprecedentedly massive, high-dimensional, and complex (e.g., implicit spatial and temporal relations and interactions), making it challenging to explore and analyze the spatiotemporal movement patterns in space. In this paper, we propose 4D time density as a visualization method for identifying and analyzing spatiotemporal movement patterns in large trajectory datasets. The movement range of the objects is regarded as a 3D geographical space, into which the fourth dimension, 4D time density, is incorporated. The 4D time density is derived by modeling the movement path and velocity separately. We present a time density algorithm, and demonstrate it on the simulated trajectory and a real dataset representing the movement data of aircrafts in the Hong Kong International and the Macau International Airports. Finally, we consider wider applications and further developments of time density. [ABSTRACT FROM AUTHOR]

This paper describes a study of the evaluation of cartographic quality of urban plans in the Czech Republic using eye-tracking. Although map visualization is a crucial part of the urban planning process, only a few studies have focused on the evaluation of these maps. The plans of four Czech cities with different styles of visualization and legends were used in this eye-tracking experiment. Respondents were required to solve spatial tasks consisting of finding and marking a certain symbol on a map. Statistical analyses of various eye-tracking metrics were used, and the differences between experts and students and between the map and legend sections of the stimuli were explored. The study results showed that the quality of map symbols and the map legend significantly influence the legibility and understandability of urban plans. For correct decision-making, it is essential to produce maps according to certain standards, to make them as clear as possible, and to perform usability testing on them. [ABSTRACT FROM AUTHOR]