Map Layout Research Articles

Maps Around Me

Visual exploration of maps often requires a contextual understanding at multiple scales and locations. Multiview map layouts, which present a hierarchy of multiple views to reveal detail at various scales and locations, have been shown to support better performance than traditional single-view exploration on desktop displays. This paper investigates the extension of such layouts of 2D maps into 3D immersive spaces, which are not limited by the real-estate barrier of physical screens and support sensemaking through spatial interaction. Based on our initial implementation of immersive multiview maps, we conduct an exploratory study with 16 participants aimed at understanding how people place and view such maps in immersive space. We observe the layouts produced by users performing map exploration search, comparison and route-planning tasks. Our qualitative analysis identifies patterns in layoutgeometry (spherical, spherical cap, planar),overview-detail relationship (central window, occluding, coordinated) andinteraction strategy. Based on these observations, along with qualitative feedback from a user walkthrough session, we identify implications and recommend features for immersive multiview map systems. Our main findings are that participants tend to prefer and arrange multiview maps in a spherical cap layout around them and that they often rearrange the views during tasks.

Graphic map load comparison of two Czech school atlases using edge detection

Abstract. Map complexity has been studied by cartographers for decades. Unfortunately, it is not being systematically measured as an essential map property and used to optimize cartographic products during the map-making process. Therefore, the appropriate load of map content in a map usually remains dependent only on the subjective assessment of the cartographer designing the map.The paper aims to describe and examine newly developed easy-to-use metric for graphic map load evaluation. A plugin for an open-source software Gimp was developed to provide an accessible tool to measure graphic map load of various geospatial visualizations in an image file format. This tool was then used to compare two Czech school atlases produced by Kartografie PRAHA, a.s. publisher in terms of their graphic map load. The examined atlases include: the latest World School Atlas (in Czech Školní atlas světa) and the new equivalent called Pupil’s Atlas (originally Školní atlas světa) intended to fit especially to younger pupils. Both the atlases are captured in Figure 1.The equivalent maps (the same or very similar map extents, scales, captured regions and map types) in both atlases were compared to investigate differences in graphic map load. For this, a developed metric implemented in the form of an extension to well-known image processing software Gimp was used. The extension advances an edge detection filter to identify both sharp and smooth edges in order to estimate the graphic map load of map samples. Also, a distribution of map load across the map layout is shown. Subsequently, measured values were compared and used to estimate the differences in the potential readability of those products.

Interactive Spatial Visualization of Aggregated Non-spatial Coronavirus Data

Abstract. The article describes the process of aggregation of media-based data about coronavirus pandemic in the Olomouc region, Czech Republic. Originally non-spatially located news from different sources and various platforms (government, social media, news portals) were automatically aggregated into a centralized database. The application “COVID-map” is an interactive web map solution which visualizes records from the database in a spatial way. COVID-map has been developed within Ad hoc online hackathon as an academic project at the Department of Geoinformatics, Palacký University Olomouc, Czech Republic. Alongside spatially localized data, map application collects statistical data from official sources e.g. from the governmental crisis management office.Our approach focuses on cartographical aspects of COVID-map solution. It respects current trends in both development of cartographic oriented outputs and web-based interactive map application. It is fully responsive. Originally, nonspatial data were aggregated, verified, geo-located, and finally visualized in the map environment. The layout combines three main parts: interactive map with spatial data; information panel with updated statistical data; and a sidebar with a filterable list of verified and geo-located news. The main cartographic method used for the visualisation is the choropleth map. It shows the distribution of positively tested people per 10 000 inhabitants for each sub-region. In comparison with similar coronavirus visualisation made during the current pandemic, our solution respects fundamental cartographical rules.Following cartographical topics are discussed in the article: the correct choice of cartographic method and its implementation; determination of a colour scale; recalculation statistics data into relative units by choropleths map method; design of map symbols and legend; searching for a suitable visualization of spatial and non-spatial sources into map layout; discussion on the suitability of using a clustering method.The motivation for this project was both social responsibility and dissatisfaction with the wrong implementation of basic cartographic methods in a variety of alternative solutions. The impact was immediate. Within a few days after the launch, tens of thousands users per day visited the COVID-map. It has been published by regional and national media. The COVID-map solution could be considered as a suitable ad-hoc implementation of the correctly used cartographical method on the example of coronavirus pandemic. The application “COVID-map” is available online at URL: https://gis.upol.cz/covid/mapa/.

Updating Topographic Maps at Scale 1:250000 for Libyan Territory Using Quantum GIS (QGIS) and Open Geospatial Data: Libya Topo-Project

From the beginning of the twentieth century, topographic maps for the Libyan state carried out by various compilers, where the first mapping was carried out by the Italian Military Geographical Institute, the Soviet Union Military, and the U.S. Army, followed by mapping carried out by the Libyan state from the 1950s to the 2000s. Most of these maps have not been digitized and updated using the techniques of geographic information systems and remote sensing. This paper discusses on the objectives, methodology and results of the Libya Topography Project, “Libya Topo” for updating the previously compiled topographical map at scale, 1:250000. Open spatial data from different platforms (OSM, Logistics Cluster, Landsat 8 satellite imagery, and SRTM data, etc.). Also, POIs extracted from previously compiled topographic and geological maps. Spatial database for each UTM zone created to store the features and raster. As for the cartographic style, the map layout adopted is the style of the U.S. Defense Mapping Agency maps. The results of the project are an update of 121 topographical map sheets using Quantum (GIS), those will be freely available for the interested users on request (e.g., environmentalists, academics, and university students, etc.).

COMMUNITY ACTION PLAN (CAP) DALAM PENATAAN KAWASAN KUMUH DARI PERSPEKTIF GOOD URBAN GOVERNANCE: SEBUAH TINJAUAN LITERATUR

Urban slums is one of the main issues that developing countries discussed nowadays, whether to eliminate slums area or through sustainable development policies and official rental housing policies. One of the method is the CAP method as a way to build a community that could take actions in accordance with problems, needs and potential resources. However, the CAP method requires a good governance because it involves government, citizens, social and private organizations. Through a literature study approach, this research expects to obtain a framework and relevant theory to the implementation of the Community Action Plan (CAP) in the slum area management with the perspective of good urban governance. The analysis results shows that the CAP can be implemented for management of slums area through the stages of preparation, social environmental mapping, and approval of the CAP and a new layout map. However, the implementation must confirm four domains of constrains to assess a good urban governance, such: responsibility, accountability, representation, access, strength, legitimacy and effectiveness. This results in governance that is not only responsive and effective, but also resilient, reliable and balanced.

A Survey on Transit Map Layout – from Design, Machine, and Human Perspectives

Transit maps are designed to present information for using public transportation systems, such as urban railways. Creating a transit map is a time‐consuming process, which requires iterative information selection, layout design, and usability validation, and thus maps cannot easily be customised or updated frequently. To improve this, scientists investigate fully‐ or semi‐automatic techniques in order to produce high quality transit maps using computers and further examine their corresponding usability. Nonetheless, the quality gap between manually‐drawn maps and machine‐generated maps is still large. To elaborate the current research status, this state‐of‐the‐art report provides an overview of the transit map generation process, primarily from Design, Machine, and Human perspectives. A systematic categorisation is introduced to describe the design pipeline, and an extensive analysis of perspectives is conducted to support the proposed taxonomy. We conclude this survey with a discussion on the current research status, open challenges, and future directions.

Land use Land Cover Monitoring and Change Detection of Tinsukia, India

This study is driven towards land use land cover (LULC) mapping and LULC change detection in Tinsukia district, India. LULC mapping and change detection provides land planner and environmental scientists a better understanding of the land surface processes occurring in a given landscape so that they can come up with a strategy for sustainable development keeping degradation of natural environment from anthropogenic activities at bay. This study utilized remote sensing data products and software’s for LULC mapping and LULC change. Landsat data has been utilized in ENVI for the classification of LULC and LULC change detection during the period 1991-2020. The LULC classification was achieved through Maximum Likelihood Classification (MLC) which is a widely preferred classificatory method. Image change detection was achieved through ENVI thematic change workflow. On top of that ArcGIS version 10.2 was used for preparing all map layouts. Results reveal that the study area has undergone significant changes in its LULC pattern. Substantial increases were recorded in agricultural area (862.4 sq. km to 1186 sq. km), built up area (473.4 sq. km to 699.5 sq. km) and waterbodies (81 sq. km to 146.7 sq. km). A declining trend was evident in degraded vegetation (772.2 sq. km to 274.3 sq. km) and barren land (798.8 sq. km to 641 sq. km). In the short study period, the study area already seems to be changing in its LULC pattern due to anthropogenic activities. The steady increases to the agricultural land and built up area (BUA) is a potential threat to the LULC balance and it may have manifold impacts to LULC dynamics in the future if proper land utilization policy is not adopted.

Tertiary sulci, transcriptomics, and functional gradients in human cortex

Understanding how the anatomical structure of the brain across spatial scales generates a flexible infrastructure of functional representations subserving the complex aspects of human cognition is a major goal of neuroanatomists, cognitive neuroanatomists, and cognitive neuroscientists. Traditionally, it is well‐accepted that deep, primary indentations in the cerebral cortex, or sulci, serve as landmarks of functional and architectonic areas in primary sensory cortex, but not in association cortex. Nevertheless, findings from the last decade show that shallow, tertiary sulci that emerge late in gestation and continue to develop after birth serve as landmarks identifying microarchitectonic and functional transitions in human visual association cortex (Weiner, 2019, The Anatomical Record), which is consistent with classic anatomical theories (Sanides, 1964, Neuropsychologia). What factors might explain this unexpected anatomical‐functional coupling across spatial scales in visual association cortex? In this talk, I will first briefly summarize a series of studies from my lab revealing the contribution of gene expression (e.g. transcriptomics) in both the arealization of cortical hierarchies, as well as the topological layout of functional maps within areas. I will then discuss additional studies from my lab showing that the anatomical‐functional correspondences identified in human visual association cortex also a) extend to lateral prefrontal and posterior cingulate cortices and b) have behavioral implications. Finally, I will show how the combination of these findings have immediate translational, developmental, and evolutionary applications for understanding how the hominoid brain efficiently leverages shallow, rather than deep, sulci to house cognitively, microarchitectonically, and functionally complex transitions in association cortices ‐ a cortical organization that enables a fast read‐out of neural information that contributes to efficient human behavior.

Utility and usability of intrinsic tag maps

ABSTRACT Intrinsic tag maps fit a tag cloud inside a geographic boundary to emphasize the association of the tags with a particular administrative region. So far, little is known about their utility and usability. Here, we present the results of an empirical study to help fill this gap. The study uses information retrieval tasks to evaluate intrinsic tag map utility and uses user confidence and preference judgments as a metric of usability. Key independent variables in the empirical study include tag orientation and shape of geographic territory tags are positioned within. The user responses show that the intrinsic tag maps have good performance in some gisting tasks and can be used with great confidence. However, the performance degrades when the intrinsic tag maps are used to search for specific tags. The user responses also show that the readability and layout of the intrinsic tag maps needs improvement. Additionally, results show that geographic territory shape has a significant effect on the information retrieval and both geographic territory shape and tag orientation have a significant effect on the confidence, readability, and preference of the intrinsic tag map. Overall, our research results can be used to improve tag map designs to achieve better utility and usability and as the starting point for subsequent tag map research.

Methods of determining nomenclature of topographic maps: theory and practice

The cartographic method is the main method of teaching geography in the institutions of general education in the New Ukrainian School, the basis for the formation of skills of each citizen. Aim of the research: to reveal the theoretical aspects of the methodology for determining the nomenclature of topographic maps for teachers and methodologists of geography of general secondary education institutions, students of higher education institutions and to provide appropriate methodological recommendations for their practical implementation. Main material. To achieve this goal, the following research methods were used: the method of comparative-historical analysis, which allowed to establish the causal and historical conditionality of the formation the methodology for determining the nomenclature of topographic maps; empirical (observation of the pedagogical process, conversations with students and teachers of geography, generalization of personal pedagogical experience, questioning of teachers and methodologists), which contributed to the substantiation of the need to develop and implement in the geography of the New Ukrainian School (NUS) effective methodology for determining the nomenclature of geographers nomenclature The pedagogical experiment made it possible to identify not only the links between the studied components of the nomenclature of topographic maps, but also to carry out qualitative analysis and accurate quantitative measurement of both changes made in the educational process and the results of the whole process. The analysis of curricula in geography involves mastering the concepts and terms «topographic map», «map layout», «map nomenclature», evaluation of certain types of nomenclature definition of topographic maps; encourages the theoretical substantiation of such a methodology based on the pedagogical experience of the teacher of geography in modern school. The main focus of the article is on the practical aspect of the methodology for determining the nomenclature of a topographic map; methodological recommendations are given regarding approaches to the evaluation of particular types of their definition. For the first time, methodological recommendations on the educational practice of determining the nomenclature of topographic maps for institutions of general secondary education, in particular the concept of «map layout» and «map nomenclature» and the like, are introduced into scientific use. They significantly influence the achievement of new socio-economic results of geographical education. Conclusions. The results of the experimental study confirm the importance of theoretical and practical aspects of the methods development for determining the nomenclature of topographic maps in educational practice, its content and methodological basis. The developed guidelines for practical implementation of the methodology for determining the nomenclature of topographic maps in institutions of General secondary education of the New Ukrainian school will contribute to improving the quality of knowledge on geography and the Ukrainian educational system as a whole.

Coverage Path Planning for Decomposition Reconfigurable Grid-Maps Using Deep Reinforcement Learning Based Travelling Salesman Problem

Optimizing the coverage path planning (CPP) in robotics has become essential to accomplish efficient coverage applications. This work presents a novel approach to solve the CPP problem in large complex environments based on the Travelling Salesman Problem (TSP) and Deep Reinforcement Learning (DRL) leveraging the grid-based maps. The proposed algorithm applies the cellular decomposition methods to decompose the environment and generate the coverage path by recursively solving each decomposed cell formulated as TSP. A solution to TSP is determined by training Recurrent Neural Network (RNN) with Long Short Term Memory (LSTM) layers using Reinforcement Learning (RL). We validated the proposed method by systematically benchmarked with other conventional methods in terms of path length, execution time, and overlapping rate under four different map layouts with various obstacle density. The results depict that the proposed method outperforms all considered parameters than the conventional schemes. Moreover, simulation experiments demonstrate that the proposed approach is scalable to the larger grid-maps and guarantees complete coverage with efficiently generated coverage paths.

Panoramic Camera-Based Human Localization Using Automatically Generated Training Data

In this paper, a panoramic camera-based human localization method using automatically generated training data is proposed to locate a human target accurately in a room scenario. The method recognizes a feature object and detects the edge pixel locations of the object in the observed image and room layout map. Then it partitions the target area into four subareas and matches the edge pixel locations of each subarea in the image with the ones in the layout map to generate the training data. A training data augmentation method is also proposed to automatically generate quadruple training data for localization performance improvement. With the generated training data, general regression neural network (GRNN) is used to construct one regression model for each subarea to calculate the human target's location. When the human target is observed and detected as a foreground target in the image, the foreground pixel location that can represent the human target's location most accurately is searched and used to calculate the human target's location coordinates with one of the four constructed GRNN models. Experimental results demonstrate that our panoramic camera-based human localization method is able to achieve a mean error of 0.77m, which outperforms fingerprinting and propagation model localization methods.

A comprehensive model to prioritise lean tools for manufacturing industries: a fuzzy FMEA, AHP and QFD-based approach

This paper describes a start-to-end lean tools (LTs) selection model for manufacturing industries. The integrated model utilises value stream mapping (VSM) and plant layout for identifying wastes from current state of the organisation. For prioritising the wastes along with associated risks, failure mode and effects analysis (FMEA) is adopted. Selection of LTs is done using analytic hierarchy process (AHP) and house of quality (HoQ). This model utilises fuzzy logic (FL) to convert the linguistic judgements into numerical values for computation. Future state map deployed with the shortlisted LTs is developed to compare current and future states. The model is applied in PVC pipe manufacturing industry and the results show notable improvements. The raw material saving of 2.5 kg, 3% reduction of value added time, 7% reduction of non-value added time and 5% reduction of lead time in the production of PVC pipes per batch are obtained in future state.

What Went Wrong for Bad Solvers during Thematic Map Analysis? Lessons Learned from an Eye-Tracking Study

Thematic map analysis is a complex and challenging task that might result in map user failure for many reasons. In the study reported here, we wanted to search for differences between successful and unsuccessful map users, focusing—unlike many similar studies—on strategies applied by users who give incorrect answers. In the eye-tracking study, followed by a questionnaire survey, we collected data from 39 participants. The eye-tracking data were analyzed both qualitatively and quantitatively to compare participants’ strategies from various perspectives. Unlike the results of some other studies, it turned out that unsuccessful participants show some similarities that are consistent across most analyzed tasks. The main issues that characterize bad solvers relate to improper use of the thematic legend, the inability to focus on relevant map layout elements, as well as on adequate map content. Moreover, they differed in the general problem-solving approach used as they, for example, tended to choose fast, less cautious, strategies. Based on the collected results, we developed tips that could help prevent unsuccessful participants ending with an incorrect answer and therefore be beneficial in map use education.

Assembling fixed wing UAV for the low-cost aerial mapping

The development for the improvement of technology of spatial information may be challenged in the future the spatial information is photogrammetry technique using Unmanned Area Vehicles (UAV). In this paper, the aim is to assembly the low-cost UAV particularly named “fixed-wing.” The photos derived by UAV were processed by photogrammetry technique to obtain the aerial photography map. The experiment was in Kandangan village, Duduk Sampeyan district, East Java Province. The map layout should be accorded with The BIG rules number 15/2014.

Machine Learning to Support the Presentation of Complex Pathway Graphs.

Visualization of biological mechanisms by means of pathway graphs is necessary to better understand the often complex underlying system. Manual layout of such pathways or maps of knowledge is a difficult and time consuming process. Node duplication is a technique that makes layouts with improved readability possible by reducing edge crossings and shortening edge lengths in drawn diagrams. In this article, we propose an approach using Machine Learning (ML) to facilitate parts of this task by training a Support Vector Machine (SVM) with actions taken during manual biocuration. Our training input is a series of incremental snapshots of a diagram describing mechanisms of a disease, progressively curated by a human expert employing node duplication in the process. As a test of the trained SVM models, they are applied to a single large instance and 25 medium-sized instances of hand-curated biological pathways. Finally, in a user validation study, we compare the model predictions to the outcome of a node duplication questionnaire answered by users of biological pathways with varying experience. We successfully predicted nodes for duplication and emulated human choices, demonstrating that our approach can effectively learn human-like node duplication preferences to support curation of pathway diagrams in various contexts.

AgROS: A Robot Operating System Based Emulation Tool for Agricultural Robotics

This research aims to develop a farm management emulation tool that enables agrifood producers to effectively introduce advanced digital technologies, like intelligent and autonomous unmanned ground vehicles (UGVs), in real-world field operations. To that end, we first provide a critical taxonomy of studies investigating agricultural robotic systems with regard to: (i) the analysis approach, i.e., simulation, emulation, real-world implementation; (ii) farming operations; and (iii) the farming type. Our analysis demonstrates that simulation and emulation modelling have been extensively applied to study advanced agricultural machinery while the majority of the extant research efforts focuses on harvesting/picking/mowing and fertilizing/spraying activities; most studies consider a generic agricultural layout. Thereafter, we developed AgROS, an emulation tool based on the Robot Operating System, which could be used for assessing the efficiency of real-world robot systems in customized fields. The AgROS allows farmers to select their actual field from a map layout, import the landscape of the field, add characteristics of the actual agricultural layout (e.g., trees, static objects), select an agricultural robot from a predefined list of commercial systems, import the selected UGV into the emulation environment, and test the robot’s performance in a quasi-real-world environment. AgROS supports farmers in the ex-ante analysis and performance evaluation of robotized precision farming operations while lays the foundations for realizing “digital twins” in agriculture.

The definition of scale series for atlas maps depending on the density of mapped objects

Abstract. The definition of scale series i.e. the identification of groups of scales in which maps will be created is one of the important tasks of designing the mathematical basis of the atlas. Map scale calculation based on the map format and the size of the mapping area is the most common approach to calculating the scale of the being created atlas maps. This approach allows to take into account the margins and layout of maps on the page. But usually these parameters aren’t known even at the design stage of a new atlas. So it is also necessary to take into account the completeness and detail of the content of the atlas maps at the stages of designing the atlas and determining the scale series for small-scale maps. The authors propose to carry out the calculation of scale series for atlas maps depending on the density of the mapped objects and the graphical load associated with it. In this case, both the density of general geographical objects (for example, settlements) and the density of objects of a thematic content (for example, volcanoes and earthquake epicentres, industrial centres, etc.) can be taken into account. These factors are important when designing general geographic atlases and when creating atlases containing a large number of thematic maps respectively. The method to determine the scale series for atlas maps depending on the density of the mapped objects is developed by authors and presented in Figure 1.

Text-to-picture tools, systems, and approaches: a survey

Text-to-picture systems attempt to facilitate high-level, user-friendly communication between humans and computers while promoting understanding of natural language. These systems interpret a natural language text and transform it into a visual format as pictures or images that are either static or dynamic. In this paper, we aim to identify current difficulties and the main problems faced by prior systems, and in particular, we seek to investigate the feasibility of automatic visualization of Arabic story text through multimedia. Hence, we analyzed a number of well-known text-to-picture systems, tools, and approaches. We showed their constituent steps, such as knowledge extraction, mapping, and image layout, as well as their performance and limitations. We also compared these systems based on a set of criteria, mainly natural language processing, natural language understanding, and input/output modalities. Our survey showed that currently emerging techniques in natural language processing tools and computer vision have made promising advances in analyzing general text and understanding images and videos. Furthermore, important remarks and findings have been deduced from these prior works, which would help in developing an effective text-to-picture system for learning and educational purposes.

Data-driven main color map feature learning, design and simulation for smart ethnic cloth

How to protect and develop traditional ethnic cloth culture are the key problems of current societal interest. Through earlier research of smart techniques of pattern layout and texture appearance simulation of traditional Ethnic cloth, a data-driven intelligent design and simulation model based on main color feature learning is proposed in this paper. We employ a combination-based design technique, which uses pattern elements data and skeletons data to design a digital layout for ethnic cloth. We use Octree to quantize the color map for the designed ethnic cloth layout and extract main color map based on k-means clustering. Using a cubic convolution interpolation algorithm with yarn structure template, we render each region that is segmented through the main color map. Then, we can generate a good representation of the texture appearance of the designed layout which is shown as a realistic fabric material. Finally, the designed layout will be transferred to intelligent loom produced based on industrial Internet of things. We design several traditional Ethic cloths (Tujia brocade) layouts and simulate their textures based on our method to analyze its applicability and validity. We also compare the design and simulation results with previously proposed algorithms, which indicate that our model can design complex patterns and simulate exquisite material of Tujia brocade.