Hasil untuk "Cartography"

Paul S. Heckbert, Michael Garland

Mabel Sánchez-Torres, Francisco Javier Paniagua Rojano, Raúl Magallón Rosa

The article examines the application of artificial intelligence (AI) in the fight against disinformation through a comparative analysis of different European initiatives collected by the SmartVote project. It analyzes their characteristics and contributions to identify common trends in technological development and collaboration models. The methodology combines a systematic documentary analysis of institutional and technical sources—public project records, reports, and official repositories—with a structured questionnaire addressed to the coordinators of the selected initiatives. This mixed approach made it possible to triangulate quantitative and qualitative information on the types of technology employed, areas of impact, stakeholders involved, and levels of funding. The results show a predominance of multimodal AI-based tools aimed at automated content detection and verification. Most of the projects rely on cooperation networks among universities, technology companies, media outlets, and social organizations, structured under the principle of human oversight. The main challenges include algorithmic accuracy, bias prevention, and Europe’s technological dependence. Overall, the initiatives studied are committed to transparency, interdisciplinary collaboration, and the ethical use of AI in defense of informational integrity.

Saifei Tu, Qimin Cheng, Qunshan Zhao et al.

High-resolution (HR) land-cover mapping is an important task for surveying the Earth’s surface and supporting decision-making in sectors such as agriculture, forestry and smart cities. However, it is impeded by the scarcity of HR high-quality labels, complex ground details and high computational cost. To address these challenges, we propose VCNet, a weakly supervised end-to-end deep learning network for large-scale HR land-cover mapping. It leverages easy-access low-resolution (LR) land-cover products as the sole guidance of supervision, fully eliminating the need for manual annotation. In VCNet, we propose a cross-feature learning backbone to learn complete details of various land objects for fine-scale land cover mapping. Besides, it is hybridized with a high-resolution maintaining module and label refining strategies to constantly refine coarse LR labels for guiding the framework training. Extensive experiments in the Chesapeake Bay dataset demonstrate the superiority of VCNet in generating HR land-cover maps from LR labels. Furthermore, we constructed the Tokyo dataset to analyze VCNet’s sensitivity to different LR labels. To verify its practical application potential, VCNet was utilized to produce a 1 m resolution land-cover map for Shanghai (China’s economic epicenter) from a lower resolution (10-m) product, greatly enriching complex ground details. Besides, due to the importance of transportation networks for highly urbanized region, we introduced road category in the practical mapping of Shanghai, which fills a critical gap in traditional land cover classification systems. This contribution offers a scalable solution for evidence-based decision-making in comparable developed regions. Our code is available at: https://github.com/Tusaifei/VCNet.

Ning Zhou, Guo Zhang, Chunyang Zhu et al.

With the expansion of human activities into mountainous regions, jungles, deserts, rural roads, and off-road terrains, there is an increasing demand for reliable navigation and location services in wild unstructured environments. Unlike urban environments, where established methodologies exist for constructing navigation maps, roadless unstructured environments lack comprehensive frameworks for navigation map construction. The conventional waypoint-based structures, which are well-suited to urban environments, are often ill-suited to the expansive and unstructured nature of field regions. Moreover, the absence of predefined user paths necessitates a fundamentally different approach to map construction. To address this challenge, we propose a novel method for generating navigation maps in unstructured roadless environment. New methodology leverages remote sensing as input for environmental perception, translating user traversability into geographical parameters and constructing a navigation mesh as a computational map. Compared with existing methods, the new method can adapt to large-scale unstructured environments. To validate the proposed method, reliability sampling tests and operational experiments were conducted on traversable area delineation and the navigation map generation. The experimental results indicate an 84% accuracy in traversable area analysis, with the constructed navigation map effectively supporting positioning and path planning while significantly reducing computational complexity in large-scale path planning tasks. The navigation mesh generated through this method effectively enhances the implementation of navigation and positioning services in off-road and roadless environments. The proposed method facilitates the construction of navigation maps capable of delivering navigation and localization services without requiring human presence in the target area.

P. Burrough, A. Frank

Current geographical information systems GIS deal almost exclusively with well-defined, static geographical objects ranging from physical landscapes to towns and transport systems. Such objects, exactly located in space, can easily be handled by modern GIS, yet form only a small proportion of all the possible geographical objects.; This book challenges the assumption that the world is compsed of exactly defined and bounded geographic objects such as land parcels, rivers and countries. ignoring the essential complexity of the world, current GIS do not adequately address problems as diverse as the resolution of crime between national boundaries, or the interpretation of views of people from different cultures. This work, bringing together a range of specialists from fields such as linguistics, computer science, land surveying, cartography and soil science, examines current research into the challenges of dealing with geographical phenomena that cannot easily be forced into one of the two current standard data models.

Vassilios Krassanakis, Paweł Cybulski

Eye tracking constitutes a valuable tool for the examination of human visual behavior since it provides objective measurements related to the performed visual strategies during the observation of any type of visual stimuli. Over the last decade, eye movement analysis contributed substantially to the better understanding of how visual attention processes work in different types of maps. Considering the clear need for the examination of map user reaction during the observation of realistic cartographic products (i.e. static maps, animated maps, interactive and multimedia maps), a critical amount of experimental studies were performed in order to study different aspects related to map reading process by the cartographic community. The foundation of these studies is based on theories and models that have been developed in similar research domains (i.e. psychology, neuroscience etc.), while the research outcomes that produced over these years can be used directly for the design of more effective and efficient maps. The aim of the present article is to summarize and present the current panorama of the existing eye tracking studies in cartographic research appeared over the last decade. Additionally, methodological contributions (including analysis tools) of cartographic society in the field of eye movement analysis are reported, while existing challenges and future perspectives are also discussed.

Jiawei Long, Jianhu Zhao, Xi Zhao et al.

In the absence of global navigation satellite system (GNSS) signals and acoustic positioning systems, and relying only on inertial measurement unit (IMU) and Doppler velocity log (DVL), underwater terrain matching has become the primary approach of underwater navigation and localization. To address the limitations of current underwater terrain matching methods, which heavily depend on high-precision background fields of seafloor terrain and are subject to the richness of seafloor terrain information, we propose a novel underwater terrain matching method based on multibeam bathymetric point cloud descriptors. This method generates discriminant descriptors from the bathymetric point cloud patches, which can be directly used to accurately measure the similarity between two patches to complete the matching. This approach eliminates the need for recalculating similarity between different patches and reduces memory requirements for storing original bathymetric data. Specifically, our method fully considers the principle of multibeam data measurement and includes a patch construction method of multibeam bathymetric point cloud and a terrain descriptor generation model based on point cloud neural networks. We compared the proposed method with other state-of-the-art underwater terrain matching methods on both a test set and real-world data. The results demonstrate that our method exhibits superior matching performance.

Eniola Rebecca Sonuga

Umoja (noun): /ooh-moh-jah/ Umoja, is the Swahili philosophy of unity. Its principles underscore the significance of cooperation and communal solidarity. Umoja has historically been associated with various aspects of African social and political life, accentuating the influence of communal synergy in traditional land tenure systems. The Umoja philosophy encourages individuals to consider collective-wellbeing as being complementary to individual interests, thereby fostering a profound sense of social responsibility in traditional approaches to land holding.  In contemporary African society, Umoja continues to wield substantial influence in facilitating social cohesion and the establishment of robust and supportive communities. Notwithstanding, the principles of Umoja remain relatively uncharted in the context of modern approaches to land reform policies.  This research paper aims to pioneer this course by examining the methods through which the principle of Umoja can radically transform modern approaches to land reform policies, with the ultimate objective of lifting millions of Africans out of multidimensional poverty. Consequently, the paper posits that conventional land reform strategies, primarily centered on the formalization of individual property rights, give rise to substantial challenges that impede advancements in land reform, agriculture, the proliferation of the African Continental Free Trade Agreement (AfCFTA), and broader economic development. The paper culminates by advocating for the implementation of a novel paradigm, termed the Productivity Based Redistribution-Communal Land Holding (PBR-CLH) System, designed to facilitate the consolidation of communal property rights across the continent, while coexisting with prevailing individual property rights frameworks. The PBR-CLH System encompasses a set of policies encompassing Productivity Based Redistribution of land, coupled with the establishment of Communal Land Holding structures.

M. Keskin, P. Kettunen

ABSTRACT This review article collects knowledge on the use of eye-tracking and machine learning methods for application in automated and interactive geovisualization systems. Our focus is on exploratory reading of geovisualizations (abbr. geoexploration) and on machine learning tools for exploring vector geospatial data. We particularly consider geospatial data that is unlabeled, confusing or unknown to the user. The contribution of the article is in (i) defining principles and requirements for enabling user interaction with the geovisualizations that learn from and adapt to user behavior, and (ii) reviewing the use of eye tracking and machine learning to design gaze-aware interactive map systems (GAIMS). In this context, we review literature on (i) human-computer interaction (HCI) design for exploring geospatial data, (ii) eye tracking for cartographic user experience, and (iii) machine learning applied to vector geospatial data. The review indicates that combining eye tracking and machine learning is promising in terms of assisting geoexploration. However, more research is needed on eye tracking for interaction and personalization of cartographic/map interfaces as well as on machine learning for detection of geometries in vector format.

D. Fairbairn, Jess Hepburn

ABSTRACT This overview paper summarises the ‘state of the art and of the science’ of eye-tracking, and its applications in map use research. Cartographic research is introduced, and its contemporary direction, which indicates that the main areas of such research are now focussed on human beings and their interaction with maps and geospatial displays, is stressed. A brief outline of several different methodologies for map use research is presented: observation, thinking loud, keyboard analysis, eye-tracking, and questionnaires. The role of eye-tracking as a major methodology for use, user, and usability investigation is explored; along with the possible choices for the researcher in the important areas of participant selection, eye-tracking equipment, set-up and use of the testing environment, and analysis of output data. Typical outcomes from eye tracking research are considered, with an assessment of its value in cartographic research in general. Future directions are suggested, along with the need for cartography to promote the valuable work done by researchers using eye-tracking for map use studies to the wider human-computer interaction community, expanding the scope of the geospatial-based stimuli in such experiments beyond maps, making use of the significant expertise and enthusiasm of cartographic researchers.

Atınç Pırtı

The European Commission (EC) originally proposed ideas for a European Galileo satellite navigation system in 1999. A four-phase development is planned, involving investment from both the public and commercial sectors. Galileo is intended for both public and government use; the system is administered and operated by civil administration. Galileo will consist of a constellation of 30 satellites, a number of globally situated ground stations, and a ground control and monitoring system – all of which are quite similar to the structure, format, and layout of GPS. This document discusses an experiment at the project site that used the static approach to integrate GPS, GLONASS, GALILEO, Beidou, and QZSS signals. This research analyses the possible precision of GPS-only and GPS/GLONASS/GALILEO/Beidou/QZSS. These results suggest that combining a GPS system with GALILEO, GLONASS Beidou, and QZSS is preferable for surveying purposes. Integrating GPS/GLONASS/GALILEO/Beidou/QZSS static measurements in the study region with 0–120 millimetre accuracy looks to be possible in three days.

Kutaiba Alhaj Hussen, Emna Chabaane, Elisabeth Nelson et al.

Summary: The developmental cartography of human lymphopoiesis remains incompletely understood. Here, we establish a multimodal map demonstrating that lymphoid specification follows independent direct or stepwise hierarchic routes converging toward the emergence of newly characterized CD117lo multi-lymphoid progenitors (MLPs) that undergo a proliferation arrest before entering the CD127- (NK/ILC/T) or CD127+ (B) lymphoid pathways. While the differentiation of CD127- early lymphoid progenitors is mainly driven by Flt3 signaling, emergence of their CD127+ counterparts is regulated cell-intrinsically and depends exclusively on the divisional history of their upstream precursors, including hematopoietic stem cells. Further, transcriptional mapping of differentiation trajectories reveals that whereas myeloid granulomonocytic lineages follow continuous differentiation pathways, lymphoid trajectories are intrinsically discontinuous and characterized by sequential waves of cell proliferation allowing pre-commitment amplification of lymphoid progenitor pools. Besides identifying new lymphoid specification pathways and regulatory checkpoints, our results demonstrate that NK/ILC/T and B lineages are under fundamentally distinct modes of regulation. (149 words)

Yu Feng, F. Thiemann, Monika Sester

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.

Isaac Chaparro Hernández

La investigación describe y explica los patrones, costos y límites de la movilidad cotidiana causados por la estructura urbana de Ciudad Juárez. La concatenación de las teorías clásicas y contemporáneas de localización, estructura urbana y movilidad fundamentaron los procesos de análisis y resultados de este estudio. Metodológicamente se implementaron las técnicas de autocorrelación espacial I de Moran y G de Getis-Ord para el análisis de los censos económicos del INEGI, que identificaron espacialmente los subcentros de empleo total, manufactura y terciario en los periodos 1993, 2004, 2009 y 2014. Por otro lado, se realizó un levantamiento bietápico de datos en toda la ciudad por medio de encuestas origen-destino, las cuales mostraron, desde una escala macro, los patrones de movilidad en términos de tiempo, distancia, orígenes, destinos, cantidad de viajes, preferencias de transporte, motivos, edades y costos económicos. En una escala micro, la teoría de grafos y el análisis de redes permitieron modelar espacialmente cada viaje intraurbano, los resultados se detallan en un Atlas de Movilidad que incluye cada una de las 64 unidades territoriales en que se dividió la ciudad. La investigación propone una metodología replicable, además provee información relevante y actual de la ciudad, útiles para otros estudios, toma de decisiones y políticas públicas de estructuración y movilidad urbana.

R. Howes, Anand P. Patil, F. Piel et al.

Blood group variants are characteristic of population groups, and can show conspicuous geographic patterns. Interest in the global prevalence of the Duffy blood group variants is multidisciplinary, but of particular importance to malariologists due to the resistance generally conferred by the Duffy-negative phenotype against Plasmodium vivax infection. Here we collate an extensive geo-database of surveys, forming the evidence-base for a multi-locus Bayesian geostatistical model to generate global frequency maps of the common Duffy alleles to refine the global cartography of the common Duffy variants. We show that the most prevalent allele globally was FY*A, while across sub-Saharan Africa the predominant allele was the silent FY*BES variant, commonly reaching fixation across stretches of the continent. The maps presented not only represent the first spatially and genetically comprehensive description of variation at this locus, but also constitute an advance towards understanding the transmission patterns of the neglected P. vivax malaria parasite.

S. Vitale, S. Ciarcia

ABSTRACT This paper furnishes a brief, but exhaustive, description of the tectonics and stratigraphy of the Campania region (southern Italy). The attached geological map (Main Map) at 1:250,000 scale should be considered as a first attempt to provide a more detailed geological cartography of the entire region, with respect to the available literature, in the light of scientific advances in stratigraphy and tectonics reached in the last years. The geological setting, proposed in this study, is the result of a review and reinterpretation of the current geological knowledge plus original surveys carried out in some key sectors of the area. We also include a schematic stratigraphic chart and three geological cross-sections illustrating the tectonic architecture in depth for the internal and external zones. The geodatabase was compiled in GIS format and subsequently imported in vector graphic software to allow a classical cartographic design.

Simon Iain Hay, E. Okiro, P. Gething et al.

Simon Hay and colleagues derive contemporary estimates of the global clinical burden of Plasmodium falciparum malaria (the deadliest form of malaria) using cartography-based techniques.

E. Rignot, A. Rivera, G. Casassa

Digital elevation models of the Northern and Southern Patagonia Icefields of South America generated from the 2000 Shuttle Radar Topography Mission were compared with earlier cartography to estimate the volume change of the largest 63 glaciers. During the period 1968/1975–2000, these glaciers lost ice at a rate equivalent to a sea level rise of 0.042 ± 0.002 millimeters per year. In the more recent years 1995–2000, average ice thinning rates have more than doubled to an equivalent sea level rise of 0.105 ± 0.011 millimeters per year. The glaciers are thinning more quickly than can be explained by warmer air temperatures and decreased precipitation, and their contribution to sea level per unit area is larger than that of Alaska glaciers.

J. Crampton

U. Wardenga

<p>The contribution uses the example of the 1969 Congress of German Geographers in Kiel to illustrate how traditions are born and passed on in German-speaking geography. By means of hermeneutic source criticism, it investigates how the events of „Kiel 1969“ gave rise to a myth. It concludes that the congress's participants experienced „Kiel 1969“ as the site of an enormously dense social interaction within their science. Most importantly, participants' suggestive oral reports in the aftermath of the congress turned it into the „myth of Kiel“, which became an essential driving force of German-speaking geography's modernization.</p>