Abdelkader Nairi, M'hamad Essabiri, Zohra Zikka
et al.
Water erosion is a major threat to land resources and agricultural productivity in semi-arid Mediterranean environments. This study aimed to identify the main factors driving water erosion in the Nfifikh watershed (Morocco) and to assess spatial variations in erosion susceptibility using a combination of the PAP/CAR qualitative model and geographic information systems (GIS). Spatial data, including ASTER-DEM, land use, vegetation cover, and lithological maps, were analyzed alongside field observations to map erosion vulnerability. The PAP/CAR methodology was applied in three stages – descriptive, predictive, and integration – to classify the watershed into stable and unstable zones and to evaluate areas at low, moderate, high, and very high erosion risk. Results indicate that 55.96% of the watershed exhibits high to very high erosion potential, primarily concentrated in downstream agricultural areas and slopes exceeding 20%. Sheet erosion dominates (87.77% of the basin), while rill and gully erosion occur in areas with sparse vegetation and moderates to steep slopes. Approximately 35% of the watershed is highly sensitive, while protective vegetation covers less than 35% of the area, failing to coincide with the most vulnerable zones. High erosion risk areas overlap with regions of intensive agriculture and higher population density, confirming that erosion susceptibility is driven by both natural factors and human activities. These findings provide a reproducible spatial framework for targeted soil and watershed management interventions. The integration of GIS with the PAP/CAR model enables the identification of priority zones for conservation, contributing to sustainable land use planning. This study offers new insights into the spatial dynamics of water erosion in semi-arid Mediterranean watersheds and demonstrates the value of combining cartographic modeling with field verification for environmental management.
The existence of thin clouds within remote sensing images results in the loss of image information. The removal of thin clouds is crucial for enhancing data quality and increasing the application scope of remote sensing imagery. A method that combines model-driven homomorphic filtering and data-driven diffusion models for thin cloud removal is proposed in this paper. Homomorphic filtering guidance and spatial domain guidance are employed to transform the generation process of a pre-trained unconditional cloud-free remote sensing images generative model from random to directed, thereby generating a cloud-free image that corresponds to the provided thin-cloud image. Unlike most existing data-driven methods, this approach requires only cloud-free images for model training, thus avoiding the difficulties associated with dataset construction. Additionally, the prior knowledge obtained from the diffusion model is used to compensate for the inherent color loss in homomorphic filtering, addressing the limitations of traditional model-based methods. Comparative experiments were conducted by training on 655 cloud-free GaoFen-2 satellite scenes and testing on 68 simulated and 20 real thin-cloud scenes. On the simulated set, the proposed method achieved an average Peak Signal to Noise Ratio (PSNR) of 26.0 dB and Structural Similarity Index (SSIM) of 0.873. On real scenes, it raised image sharpness and color saturation by 22% and 40%, respectively, while preserving ground features more effectively than competing methods. These results demonstrate the effective removal of thin clouds and the superior generalization capability of the proposed approach.
Acquiring sufficient visual information for the three-dimensional (3D) reconstruction of ships in navigation is particularly challenging. With the evolution of 3D reconstruction methodologies predicated on neural rendering, the computational pipeline for 3D reconstruction has undergone enhancements and optimizations. However, this pipeline necessitates a substantial corpus of input images. Research into 3D reconstruction from monocular images is in its nascent stages, and to date, no unsupervised deep learning approach for 3D reconstruction of ships from single-view UAV imagery exists within the realm of navigation. This paper introduces a novel network architecture for reconstructing 3D representations of ships from single-view UAV images. Initially, a priori statistical analysis of the dataset is conducted to harness color distribution information for noise generation. Subsequently, a novel generator and mask module are engineered to produce optimized feature outputs. Plus, discriminator and encoder networks, coupled with a tailored loss function, are formulated to direct model optimization. Ultimately, to demonstrate the effectiveness of our proposed method for single-view 3D reconstruction, we conducted experiments across three distinct datasets from various domains. Our method's FID value of 10.61 is impressive. At the same time, it yields an LPIPS value of 0.091, which is the best among the six different methods.
Стаття пропонує цілісну рамку подолання пострадянської інерції у взаємодії землеустрою та топографо-геодезичної діяльності в Україні. Показано, що радянська освітньо-професійна традиція звузила геодезію до вимірювально-інженерних практик і водночас маргіналізувала європейське розуміння землеустрою як проєктно-правової діяльності з формування меж та режимів користування, що мають юридичні наслідки. На основі аналізу міжнародних рамок (FIG, CLGE, INSPIRE, LADM), чинного українського законодавства та довготривалих спостережень автора за професійними дискусіями у соціальних мережах обґрунтовано: (1) необхідність термінологічної уніфікації (surveyor як родове поняття, з розмежуванням land/cadastral surveyor → «землевпорядник», engineering/topographic surveyor → «інженер-геодезист/топограф», «геодезист» — не синонім surveyor); (2) переосмислення функціональних ролей: топографо-геодезична діяльність є інфраструктурним інструментом створення доданої вартості в інших секторах, тоді як землеустрій безпосередньо формує нові об’єкти нерухомості, планувальні структури та управляє цінністю майна через RRR-підходи; (3) інституційну інтеграцію даних і процесів на основі моделей INSPIRE/LADM. Визначено структурні причини «кризи» галузі після 1991 р.: різке скорочення державного попиту на «централізовану геодезію» та технологічна автоматизація вимірювань (GNSS, ДЗЗ, БПЛА, ГІС). Запропоновано модернізацію вищої освіти за спеціальністю G18 («Геодезія та землеустрій») через міждисциплінарні навчальні траєкторії (геодезія × землеустрій × кадастр × просторове планування × оцінка), впровадження семантичних моделей даних, етики та процедур публічної довіри до меж, а також розвиток постійних професійних комунікацій як механізму зняття уявних конфліктів між спільнотами.
Ключові слова: землеустрій; геодезія; топографо-геодезична діяльність; кадастр; межі; RRR (права-обмеження-обтяження); INSPIRE; LADM; термінологічна уніфікація; професійні кваліфікації; НІГД/NSDI; інституційна інтеграція; просторове планування; оцінка нерухомості.
The undirected edge geography is a two-player combinatorial game on an undirected rooted graph. The players alternatively perform a move consisting of choosing an edge incident to the root vertex, removing the chosen edge, and marking the other endpoint as a new root vertex. The first player who cannot perform a move is the loser. In this paper, we are interested in the undirected edge geography game on the grid graph $P_m\square P_n$. We completely determine whether the root vertex is a winning position (N-position) or a losing position (P-position). Moreover, we give a winning strategy for the winner.
ABSTRACT The developing convergence of Artificial Intelligence and GIScience has raised a concern on the emergence of deep fake geography and its potentials in transforming human perception of the geographic world. Situating fake geography under the context of modern cartography and GIScience, this paper presents an empirical study to dissect the algorithmic mechanism of falsifying satellite images with non-existent landscape features. To demonstrate our pioneering attempt at deep fake detection, a robust approach is then proposed and evaluated. Our proactive study warns of the emergence and proliferation of deep fakes in geography just as “lies” in maps. We suggest timely detections of deep fakes in geospatial data and proper coping strategies when necessary. More importantly, it is encouraged to cultivate a critical geospatial data literacy and thus to understand the multi-faceted impacts of deep fake geography on individuals and human society.
Spatial thinking is a unique thinking skill that geographers use to reason. Every individual is believed to have this thinking skill, but not all are aware of it. This condition causes differences in the development of each person. A person’s spatial thinking can be improved by training. Geospatial technology is a representation tool that many people believe can be used to train spatial thinking skills. However, not many people encounter obstacles when using this technology. The complexity of the command to run is an obstacle that is often found. In line with the development of geospatial technology, many applications integrate this technology as part of visualization tools. This teaching and learning were conducted with Action Research Classroom (three cycles) in the form of Project-Based Learning with Science, Engineering, Technology, and Mathematic (STEM) approach. This article discusses the findings of the research on the use of Excel dynamic map chart and virtual globe to improve spatial thinking in research subjects with the case study of Indonesian Geography and World Regional Geography. With the Excel application project, for the context of upper-level education, the findings show an increase in spatial thinking skills and mastery of the use of mapping platforms without the need for prior experience of coding, software, or cartography, although it needs to be corroborated by other studies.
ABSTRACTEvaluating the inequity of healthcare accessibility across demographic groups in the post-COVID era is of critical importance for an aging society like Japan – it helps to achieve better social equity via distributing healthcare resources in health planning and policy making. Our study contributes to the first post-covid evaluation of multi-modal healthcare accessibility in Tokyo, Japan, the most populated metropolis in the world. A further novelty goes to the multi-dimensional examination of the inequity of healthcare accessibility (i.e. hospitals) by public transit, driving and walking – the horizontal inequity across urban space and the vertical inequity across three demographic groups (the young, adult and elderly) through network analysis, spatial accessibility analysis and inequity indexing. We find that low healthcare access areas mainly appear in the peri-urban space as well as regions less covered by public transit. Compared to the adult group, the elderly group experiences significant inequity of healthcare access particularly in the peri-urban areas where driving is the dominant transport mode to access healthcare facilities. We provide timely evidence to the Japanese government and health authorities to have a holistic and latest understanding of multi-modal healthcare access across different demographic groups in the post-COVID era.
W pracy omówiono związki między intensywnością północnoatlantyckiej cyrkulacji termohalinowej (NA THC), charakteryzowanej przez wskaźnik DG3L, i liczbą dni z występowaniem ekstremalnie wysokiej temperatury powietrza nad Polską w latach 1951–2020. Za miarę warunków ekstremalnych przyjęto liczbę dni w roku z temperaturą maksymalną w ciągu doby ≥25°C (dni gorące; D5DG) i ≥30°C (dni upalne; D5DU) oraz liczbę dni z temperaturą średnią dobową ≥25°C (D5D25). Stwierdzono wysoce istotne zależności między zmiennością wskaźnika DG3L a D5DG, D5DU i D5D25, wskazujące, że im bardziej intensywna jest NA THC, tym więcej w roku występuje dni ekstremalnie ciepłych. Długookresowa zmienność liczby dni ekstremalnie ciepłych wyraźnie nawiązuje do zmienności warunków makrocyrkulacyjnych – epok cyrkulacyjnych według klasyfikacji Wangengejma-Girsa. Zwiększona w ciągu roku liczba dni ekstremalnie ciepłych jest powiązana ze wzrostem ponad średnią wieloletnią strefowego makrotypu W. Zmienność NA THC stanowi przyczynę zmian zasobów ciepła w wodach Atlantyku Północnego, co wpływa na kształtowanie się południkowych gradientów termicznych w środkowej troposferze. Wraz ze wzrostem NA THC gradienty te rosną. W wyniku wzrostu tych gradientów dochodzi w atlantycko-eurazjatyckim sektorze cyrkulacyjnym do wzrostu frekwencji fal długich o liczbie falowej 4 (makrotyp W) i spadku frekwencji fal o liczbie falowej 5 (makrotypy E i C; cyrkulacja południkowa). Rezultatem tego jest wzrost wysokości geopotencjału (h500) nad zachodnią i środkową Europą, na południe od 55°N. Nad tym obszarem dochodzi do wzrostu ciśnienia na poziomie morza, co w skali synoptycznej powoduje wzrost częstości występowania pogód antycyklonalnych, bez chmur warstwowych (As, Ns i St; frontalnych), silnego wzrostu usłonecznienia i redukcji opadów. W strukturze strumieni ciepła z powierzchni lądowych do atmosfery spada udział strumieni ciepła parowania, a rośnie udział strumieni ciepła jawnego, powodując silny wzrost temperatury powietrza. Silny trend wzrostowy, jaki zaznacza się w przebiegu wskaźnika DG3L po roku 1988, znajduje swoje odzwierciedlenie w rosnącej od tego momentu liczbie dni ekstremalnie ciepłych nad Polską.
This survey focuses on the geometric problem of log-surfaces, which are pairs consisting of a smooth projective surface and a reduced non-empty boundary divisor. In the first part, we focus on the geography problem for complex log-surfaces associated with pairs of the form $(\mathbb{P}^{2}, C)$, where $C$ is an arrangement of smooth plane curves admitting ordinary singularities. Specifically, we focus on the case in which $C$ is an arrangement consisting of smooth rational curves as its irreducible components. In the second part, containing original new results, we study log-surfaces constructed as pairs consisting of a complex projective $K3$ surface and a rational curve arrangement. In particular, we provide some combinatorial conditions for such pairs to have the log-Chern slope equal to $3$. Our survey is illustrated with many explicit examples of log-surfaces.
ABSTRACT This paper focuses on the maps and map-like features in games. It discusses games with special topics or components, and it collects several titles of games named after a geographical object (city, land, etc.). Finally, it provides a proposed classification of the types of maps observed in the board games investigated. The popularity of board games has been increasing in an unstoppable way in the last years. Several modern board games work with maps or with map-like features. This article focuses on the maps and map-like features in games and attempts to classify the types of map in board games. The board games usually use maps on the main board. There are games that work with the map of the World in various map scales. These maps sometimes look as if they were old maps or they represented the present world. Some games' main board is similar to a map series or a classic atlas. Modular boards help to increase the replayability and give another experience game by game. Other games work with tiles (square, rectanglular or hexagonal shaped) representing a terrain type (forest, moorland, farmland, built in area, etc.). The tiles have to be placed next to each other, thereby the players can collect victory points. Fantasy maps depict fictional worlds: this helps the players to imagine better the fictional world and the characters. Fantasy maps often use partially orthogonal projection and partially bird's eye view.
ABSTRACT Eye movement is a new type of data for cartography and geographic information science (GIS) research. However, previous studies rarely built eye movement datasets with geospatial images. In this paper, we firstly proposed a geospatial image-based eye movement dataset called GeoEye, a publicly shared, widely available eye movement dataset. This dataset consists of 110 college-aged participants who freely viewed 500 images, including thematic maps, remote sensing images, and street view images. In addition, we used the dataset for geospatial image saliency prediction and map user identification. Results demonstrated the scientific benefits and applications of the proposed dataset. GeoEye dataset will not only promote the application of eye-tracking data in cartography and GIS research but also intelligence and customization of geographic information services.
ABSTRACT Frontiers in cartographic research are often found at the intersections where cartography overlaps with other domains in art, science, and technology. In this editorial, we summarize the major themes that are found in a new collection of invited literature reviews. Broad themes that emerge from this collection include the rise of novel virtual environments, ongoing user-centered design challenges for improving the utility and usability of geographic visualizations, and new approaches for representation and analysis for the development of geovisualizations.
ABSTRACT With the rise of the Quantified-Self movement and widespread adoption of self tracking technologies, 'personal' has become a new dimension in the map and geovisualization design process. Despite a rich cartographic literature on how to map movement data, and an equally extensive geovisual analytics literature on how to make sense of complex visual representations of movement data at scale, opportunities exist to adapt and create new map and interaction design paradigms to meet the disparate needs of an ever-growing number of data creators. This paper presents a cross-disciplinary review of literature that reports on the design and evaluation of personal geovisualizations. Specifically, this review paper: contextualizes individual movement data types and provides a short synthesis of cartographic and geovisual analytics approaches that have been employed to explore such data in non-personal contexts; surveys a growing yet disconnected body of foundational work beyond the GIScience discipline; presents a detailed discussion on a collection of works that exemplifies the potential of applying a geographic perspective to personal visualization; and outlines key challenges and opportunities for advancing the state-of-the-art & science in the design of maps and geovisual analytics applications constructed from personal data and that benefit the data creator.
ABSTRACT This article delves into the essence of “Smart Cartography”, a focal point in the international cartographic and geospatial information arena. Rather than the “smart”, the paper concentrates on unpacking the meaning of “cartography” and “map”, by drawing on the ICA 2003 definitions, distilling it to “representation and use of geographical reality”. It posits that the geographical reality, recognized as the “object of mapping” in literature, is the core element needing further investigation. The study further explores historical and contemporary terminology for geographical reality (object of mappings) since the mid-nineteenth century. asserting the reflection of each era's geographical knowledge in its object of mapping. In the constantly evolving, complex world, the paper advocates for a new paradigm capable of encapsulating these characteristics in the representation of geographical reality. Hence, the notion of Smart Cartography must embrace an understanding of temporal changes and spatial dynamism, integrating causally aware systems to comprehend not just the changes but their causes, in turn enhancing the decision-making process. The author concludes that Smart Cartography of the 2030s should adeptly represent the dynamism and complexities of our geographical reality, highlighting its adaptability in line with technological advancements and evolving spatial representation needs.
In recent weeks and months, much has been written in the media (and also in this journal) about the consequences that artificial intelligence (AI) can have for society. In the editorial of issue 1, for example, I wrote that AI could not yet draw maps. As I have learned in the meantime (and thanks to student feedback), there are also current developments that arouse curiosity and that should be further elaborated: What happens when the chatbot ChatGPT is asked how it imagines the cartography of the future? And what happens in a second step when its transcription is used as input for an AI-based image creation software? ChatGPT characterizes the cartography of the future in a few seconds as follows, and Midjourney captures the graphical interpretation in a visualization after about a minute. You can see one result of "AI art" on the cover of this issue: “I envision the cartography of the future as a dynamic and interactive system that seamlessly integrates data from multiple sources to create highly detailed and customizable maps. In my mind's eye, I see a person standing in front of a giant, wall-sized display surrounded by floating holographic images of cities, landmarks, and landscapes. This person directs gestures at the display, and the holographic images come alive, showing real-time information such as traffic patterns, weather conditions and population density. Using hand-movements, the map zooms in and out, providing a more detailed or broader view of the area. Suddenly, a notification appears on the screen indicating an earthquake nearby. The map automatically adjusts, highlighting the affected area and providing real-time updates on seismic activity. As the person continues to explore the map, an area of interest appears and more information is requested. The holographic images expand to provide a 3D view of the location, as well as additional data such as historical landmarks, cultural sites, and environmental factors. In this vision of the future, cartography is not just a static representation of geography, but a living and breathing system that adapts to the needs and interests of the user. It empowers individuals and organizations with the tools they need to make informed decisions and solve complex problems.” At this point, I do not want to evaluate the result of the interaction of two artificial intelligences presented here. Rather, dear KN readers, I would be interested in your opinions and comments on it. What strengths and weaknesses do you see in the result of the case example? Many letters to the editor would be desirable for the discourse on this, which will certainly occupy us all in many ways. Impulses for this part of the editorial and the cover illustration came from the Bochum M.Sc. student Jule Drews— many thanks! Following on from the previous thoughts, I cannot (yet) offer you a separate thematic issue on the development and application of AI in cartography. Instead, this thematically diverse issue contains 6 research articles, which (as usual) were accepted for publication after peer review and have already appeared online first. Many thanks to all 22 authors and to all reviewers who participated! The first two articles are a selection of the works presented at the fourth CityVis workshop on urban data visualisation, held in November 2022, at Potsdam University of Applied Sciences, co-organized by the German Cartographic Society (DGfK). Christoph Huber, Till Nagel and Heiner Stuckenschmidt introduce the concept of data experience points by means of a case study on the visualization of urban air quality. The study includes participation approaches enriching the methodological approach. Liubov Tupikina, Bernardo Monechi, Yasamin Nematollahi, and Vladislav Afanasiev deal with the analysis and visualization of geospatial data in urban space from an urbanist * Dennis Edler Dennis.Edler@ruhr-uni-bochum.de