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IJGI
Special Issues
Cartographic Communication of Big Data
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Cartographic Communication of Big Data

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 21487

Special Issue Editor

Prof. Dr. Giedrė Beconytė

E-Mail Website
Guest Editor
Institute of Geosciences, Vilnius University, M.K. Čiurlionio 21, LT-03101 Vilnius, Lithuania
Interests: thematic maps; cartographic design; cartographic communication; crime mapping; mental maps; spatial analysis; spatial data infrastructures Summary

Special Issue Information

Dear Colleagues,

Spatial data have become ubiquitous and available in volumes so large that the digital copy of all tangible and a significant portion of untangible reality does not anymore sound like a joke. At the end of the 19th century, when Lewis Carrol wrote about a “mile to the mile” map, he meant just topographic data. Now, however, big data are about everything—from the changing climate to COVID-19, mutability and reliability and precision of data vary from scientific data on Paleozoic strata to opinions of users about the beauty of a place automatically collected from a social network. These may be never updated like digital archives or updated every second like locations of airplanes on their routes. Modern GIS technologies and mathematical methods are available for confirmator and exploratory analysis of spatial big data. However, lots of specific knowledge is needed for the correct application of those methods. Moreover, ordinary computational resources of the 21st century cannot always manage datasets of that size and complexity. Those who make the most important decisions in this world, though, usually do not analyze the data. They look at maps—good old communication tools that convey a message quickly and somehow make it memorable regardless whether it is correct or not. The time has come to think what portion of the potential value of existing big data is really absorbed by decision makers and how much we lose due to insufficient or misleading communication.

This Special Issue is dedicated to the efficiency of cartographic communication of big data—methodological and technological, theoretical and practical aspects of modern cartographic visualizations. We call for original papers on novel methods or novel applications of existing methods, the efficiency of which can be demonstrated. Developers of maps for web and mobile platforms, map designers, and users around the world are invited to contribute.

Submissions to the Special Issue should possibly focus on mapping of big data:

  • Cartographic generalization and generalization of data for representation purpose;
  • Cartographic visualization;
  • Visualisation of spatiotemporal big data;
  • Representation of big data in series of maps and atlases;
  • Cartographic and user interface elements in interactive maps;
  • Assessment of efficiency of cartographic communication;
  • Sources and causes of possible misinterpretations of maps and methods of prevention;
  • Cartographis or quasi-cartographic representations in different contexts (multimedia);
  • Other relevant topics.

Dr. Giedrė Beconytė
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • big data
  • generalization
  • cartographic visualization
  • cartographic communication
  • multiscale maps
  • interactive maps
  • exploratory maps
  • map design

Published Papers (6 papers)

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Research

28 pages, 22051 KiB  
Article
Self-Organizing Maps to Evaluate Multidimensional Trajectories of Shrinkage in Spain
by Ana Ruiz-Varona, Javier Lacasta and Javier Nogueras-Iso
ISPRS Int. J. Geo-Inf. 2022, 11(2), 77; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi11020077 - 19 Jan 2022
Cited by 5 | Viewed by 3825
Abstract
The analysis of factors influencing urban shrinkage is of great interest to spatial planners and policy makers. Population loss is usually the most relevant indicator of this shrinkage, but many other factors interact in complex ways over time. This paper proposes a multidimensional [...] Read more.
The analysis of factors influencing urban shrinkage is of great interest to spatial planners and policy makers. Population loss is usually the most relevant indicator of this shrinkage, but many other factors interact in complex ways over time. This paper proposes a multidimensional and spatio-temporal analysis of the shrinkage process in Spanish municipalities between 1991 and 2020. The method is based on the potentiality provided by self-organizing maps. The generated maps group municipalities according to hidden partial correlations among the data behind the variables characterizing the municipalities at different dates. In addition, as the number of map nodes is too big to allow for the detection of distinct types of municipalities, a Ward clustering algorithm is applied to identify homogeneous areas with a higher probability of shrinkage occurring over time. The results indicate that the municipalities with the lowest shrinkage are more stable and have a geographical concentration: they correspond to areas where peripheralization may occur (creation of surrounding districts close to main urban centers) and constitute the hinterland of large functional areas. The results also report a path of decline, with an important increase in the number of municipalities with higher shrinkage values. This approach has important implications for policy making since local governments may profit from shrinkage predictions. Full article
(This article belongs to the Special Issue Cartographic Communication of Big Data)
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12 pages, 15939 KiB  
Article
Analyzing the Behaviors of OpenStreetMap Volunteers in Mapping Building Polygons Using a Machine Learning Approach
by Müslüm Hacar
ISPRS Int. J. Geo-Inf. 2022, 11(1), 70; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi11010070 - 17 Jan 2022
Cited by 6 | Viewed by 3099
Abstract
Mapping as an action in volunteered geographic information is complex in light of the human diversity within the volunteer community. There is no integrated solution that models and fixes all data heterogeneity. Instead, researchers are attempting to assess and understand crowdsourced data. Approaches [...] Read more.
Mapping as an action in volunteered geographic information is complex in light of the human diversity within the volunteer community. There is no integrated solution that models and fixes all data heterogeneity. Instead, researchers are attempting to assess and understand crowdsourced data. Approaches based on statistics are helpful to comprehend trends in crowd-drawing behaviors. This study examines trends in contributors’ first decisions when drawing OpenStreetMap (OSM) buildings. The proposed approach evaluates how important the properties of a point are in determining the first point of building drawings. It classifies the adjacency types of the buildings using a random forest classifier for the properties and aids in inferring drawing trends from the relative impact of each property. To test the approach, detached and attached building groups in Istanbul and Izmir, Turkey, were used. The result had an 83% F-score. In summary, the volunteers tended to choose as first points those further away from the street and building centroid and provided lower point density in the detached buildings than the attached ones. This means that OSM volunteers paid more attention to open spaces when drawing the first points of the detached buildings in the study areas. The study reveals common drawing trends in building-mapping actions. Full article
(This article belongs to the Special Issue Cartographic Communication of Big Data)
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13 pages, 2819 KiB  
Article
Where Maps Lie: Visualization of Perceptual Fallacy in Choropleth Maps at Different Levels of Aggregation
by Giedrė Beconytė, Andrius Balčiūnas, Aurelija Šturaitė and Rita Viliuvienė
ISPRS Int. J. Geo-Inf. 2022, 11(1), 64; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi11010064 - 14 Jan 2022
Cited by 5 | Viewed by 3398
Abstract
This paper proposes a method for quantitative evaluation of perception deviations due to generalization in choropleth maps. The method proposed is based on comparison of class values assigned to different aggregation units chosen for representing the same dataset. It is illustrated by the [...] Read more.
This paper proposes a method for quantitative evaluation of perception deviations due to generalization in choropleth maps. The method proposed is based on comparison of class values assigned to different aggregation units chosen for representing the same dataset. It is illustrated by the results of application of the method to population density maps of Lithuania. Three spatial aggregation levels were chosen for comparison: the 1 × 1 km statistical grid, elderships (NUTS3), and municipalities (NUTS2). Differences in density class values between the reference grid map and the other two maps were calculated. It is demonstrated that a perceptual fallacy on the municipality level population map of Lithuania leads to a misinterpretation of data that makes such maps frankly useless. The eldership level map is, moreover, also largely misleading, especially in sparsely populated areas. The method proposed is easy to use and transferable to any other field where spatially aggregated data are mapped. It can be used for visual analysis of the degree to which a generalized choropleth map is liable to mislead the user in particular areas. Full article
(This article belongs to the Special Issue Cartographic Communication of Big Data)
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18 pages, 5190 KiB  
Article
A Novel Invariant Based Commutative Encryption and Watermarking Algorithm for Vector Maps
by Yu Li, Liming Zhang, Xiaolong Wang, Xingang Zhang and Qihang Zhang
ISPRS Int. J. Geo-Inf. 2021, 10(11), 718; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10110718 - 25 Oct 2021
Cited by 8 | Viewed by 1605
Abstract
Commutative encryption and watermarking (CEW) is an emerging method that combines encryption technology with digital watermarking technology. It has the dual capability of secure transmission and copyright protection. However, the existing CEW methods for vector maps have good robustness in resisting geometric attacks [...] Read more.
Commutative encryption and watermarking (CEW) is an emerging method that combines encryption technology with digital watermarking technology. It has the dual capability of secure transmission and copyright protection. However, the existing CEW methods for vector maps have good robustness in resisting geometric attacks but poor resistance to vertex attacks (e.g., addition, deletion, etc.). To solve this problem, here we propose a novel invariant-based CEW algorithm for vector maps, which consists of permutation-based encryption scheme and coordinates-based watermarking scheme. In the encryption scheme, the encryption key is generated via the Gaussian distribution method combined with the SHA-512 hash method; then, the double random position permutation strategy is applied to the vector map encryption. In watermarking embedding scheme, the original watermark image is scrambled via logistic chaotic encryption before embedding, and the coordinates of all the vertices are normalized. Then, the scrambled watermark image is embedded into the normalized coordinates. Results show that: proposed method is more robust to conventional attacks (e.g., vertex addition and deletion, reordering and data format conversion) and geometric attacks (e.g., scaling and translation). In addition, compared with the existing CEW methods for vector maps, the proposed method has higher security and stronger robustness against vertex attacks. Full article
(This article belongs to the Special Issue Cartographic Communication of Big Data)
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15 pages, 8845 KiB  
Article
Vector Map Encryption Algorithm Based on Double Random Position Permutation Strategy
by Xiaolong Wang, Haowen Yan and Liming Zhang
ISPRS Int. J. Geo-Inf. 2021, 10(5), 311; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10050311 - 07 May 2021
Cited by 8 | Viewed by 3104
Abstract
Encryption of vector maps, used for copyright protection, is of importance in the community of geographic information sciences. However, some studies adopt one-to-one mapping to scramble vertices and permutate the coordinates one by one according to the coordinate position in a plain map. [...] Read more.
Encryption of vector maps, used for copyright protection, is of importance in the community of geographic information sciences. However, some studies adopt one-to-one mapping to scramble vertices and permutate the coordinates one by one according to the coordinate position in a plain map. An attacker can easily obtain the key values by analyzing the relationship between the cipher vector map and the plain vector map, which will lead to the ineffectiveness of the scrambling operation. To solve the problem, a vector map encryption algorithm based on a double random position permutation strategy is proposed in this paper. First, the secret key sequence is generated using a four-dimensional quadratic autonomous hyperchaotic system. Then, all coordinates of the vector map are encrypted using the strategy of double random position permutation. Lastly, the encrypted coordinates are reorganized according to the vector map structure to obtain the cipher map. Experimental results show that: (1) one-to-one mapping between the plain vector map and cipher vector map is prevented from happening; (2) scrambling encryption between different map objects is achieved; (3) hackers cannot obtain the permutation key value by analyzing the pairs of the plain map and cipher map. Full article
(This article belongs to the Special Issue Cartographic Communication of Big Data)
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20 pages, 3352 KiB  
Article
Do Different Map Types Support Map Reading Equally? Comparing Choropleth, Graduated Symbols, and Isoline Maps for Map Use Tasks
by Katarzyna Słomska-Przech and Izabela Małgorzata Gołębiowska
ISPRS Int. J. Geo-Inf. 2021, 10(2), 69; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10020069 - 10 Feb 2021
Cited by 9 | Viewed by 5090
Abstract
It is acknowledged that various types of thematic maps emphasize different aspects of mapped phenomena and thus support different map users’ tasks. To provide empirical evidence, a user study with 366 participants was carried out comparing three map types showing the same input [...] Read more.
It is acknowledged that various types of thematic maps emphasize different aspects of mapped phenomena and thus support different map users’ tasks. To provide empirical evidence, a user study with 366 participants was carried out comparing three map types showing the same input data. The aim of the study is to compare the effect of using choropleth, graduated symbols, and isoline maps to solve basic map user tasks. Three metrics were examined: two performance metrics (answer accuracy and time) and one subjective metric (difficulty). The results showed that the performance metrics differed between the analyzed map types, and better performances were recorded using the choropleth map. It was also proven that map users find the most commonly applied type of the map, choropleth map, as the easiest. In addition, the subjective metric matched the performance metrics. We conclude with the statement that the choropleth map can be a sufficient solution for solving various tasks. However, it should be remembered that making this type of map correctly may seem easy, but it is not. Moreover, we believe that the richness of thematic cartography should not be abandoned, and work should not be limited to one favorable map type only. Full article
(This article belongs to the Special Issue Cartographic Communication of Big Data)
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