Anna Kellinghusen, Anna Orschulik, Katrin Vorhölter
et al.
Integrated teaching encourages students to think across disciplines and view key human issues from various perspectives. Although mathematics and geography are taught as separate subjects in schools, they frequently intersect in real-world issues, with scientific problems often analyzed using mathematical methods. The purpose of this article is to systematically review the understanding of study characteristics, teaching content, and forms of integration between geography and mathematics. A systematic review of 26 studies was conducted in accordance with PRISMA guidelines, involving searches of four databases from 2000 to 2023. Screening and selection were performed independently by two researchers. Data were analyzed via structured qualitative content analysis. This systematic review demonstrates that integrated teaching can improve knowledge and skills of students compared to segregated teaching. The findings reveal that contents such as Education for Sustainable Development, cartography, and astronomy and space travel are the main topics covered in subject-integrated mathematics and geography lessons. The study also highlights gaps, especially in long-term effects and teacher involvement in quantitative research.
Georeferenced Access Points as a Strategic Node in the Evolution of Territorial Information Systems - This paper explores the strategic role of georeferenced access points and civic numbering as foundational components of advanced Territorial Information Systems (SIT) within Italian public administrations. The quality and consistency of georeferenced street and building numbers represent a fundamental component of territorial data infrastructures, enabling reliable integration between cadastral datasets, administrative services and emergency response systems.
Drawing from the experience of LdP Progetti GIS — involving more than 130 municipalities across five regions — the article demonstrates how the integration of Accesses, Buildings and Street Toponyms enables an interoperable Web-GIS ecosystem supporting digital services, data governance and operational decision-making. Real case studies from the municipalities of Siena, Arezzo, Empoli and Pistoia illustrate concrete applications such as emergency management, fiscal intelligence (TARI compliance), housing planning and economic activity monitoring. The results highlight significant improvements in administrative efficiency, transparency and open-data availability, positioning geospatial infrastructures as a key enabler of digital transformation in the Public Sector.
Accurately monitoring disaster effects is a crucial task in relief efforts (e.g. typhoon rescue). Social media data plays a vital role in disaster management, while deep learning-based methods gain more attention in typhoon disaster research. However, most existing classification methods for typhoon disasters are limited to multi-class but single-label levels, contradicting the reality that a social media text may correspond to multiple types of disaster damage. This paper proposes a siamese text classification network (SiamTCN) for multi-class multi-label information extraction from typhoon disasters based on Sina Weibo data. The SiamTCN leverages a dual-path architecture with shared weights, utilizing multi-head self-attention and convolution to extract hidden features from texts. A novel multi-class multi-label contrastive loss function is proposed to optimize the model. Additionally, address information is extracted through address matching and check-in locations. The spatio-temporal characteristics provide actionable insights for disaster management, enabling timely and targeted responses to affected regions. Experiments are conducted on Sina Weibo texts collected from six typical typhoon land-falls in Chinese coastal regions from 2018 to 2023. The results demonstrate that the accuracy achieved by the proposed method is 0.9454, 0.9391, and 0.9422, respectively. The code for this paper is available at https://github.com/SiamTCN.
China’s Earth Observation(EO) System has undergone significant development since the 1970s, as China has dedicated substantial efforts to advancing remote sensing technology. With fifty years of development, China has successfully narrowed the remote sensing technology gap with foreign countries through collaborative endeavors of the government and enterprises. At present, China has constructed a comprehensive EO system that has been proven indispensable for driving economic growth and facilitating sustainable development. This paper provides an overview of the development, missions, andapplications of China’s EO system, while also exploring future directions and technical trends of China’s EO system.
ABSTRACT The seventeenth century was a time of upheaval for the geographical traditions of the Persian world, but Mahmud bin Valī remains a little-recognized figure in its intellectual history. His Baḥr al-Asrār, written in Persian, combines classical Islamic geography with empirical observations, and offers a synthesis of historiography, economic geography, and environmental analysis. In contrast to European contemporaries, such as Blaeu and Clüver, who developed a mathematical cartography, Valī’s work remained textual and reflected the descriptive and historical geography that characterized Persian scholarship. His focus on trade networks, irrigation systems, and political landscapes demonstrates the continuing vitality of Islamic geographical traditions in Iran, Central Asia, and Mughal India. By reassessing Baḥr al-Asrār, this work situates Mahmud bin Valī within broader debates about the production of geographical knowledge and affirms the role of the Persian world in shaping an early modern understanding of space, mobility, and territoriality. His contributions challenge Eurocentric narratives of geographical progress and emphasize the continuing influence of Persian intellectual traditions on Eurasian geography.
Earth observation (EO) data such as satellite imagery can have far-reaching impacts on our understanding of the geography of poverty, especially when coupled with machine learning (ML) and computer vision. Early research used computer vision to predict living conditions in areas with limited data, but recent studies increasingly focus on causal analysis. Despite this shift, the use of EO-ML methods for causal inference lacks thorough documentation, and best practices are still developing. Through a comprehensive scoping review, we catalog the current literature on EO-ML methods in causal analysis. We synthesize five principal approaches to incorporating EO data in causal workflows: (1) outcome imputation for downstream causal analysis, (2) EO image deconfounding, (3) EO-based treatment effect heterogeneity, (4) EO-based transportability analysis, and (5) image-informed causal discovery. Building on these findings, we provide a detailed protocol guiding researchers in integrating EO data into causal analysis -- covering data requirements, computer vision model selection, and evaluation metrics. While our focus centers on health and living conditions outcomes, our protocol is adaptable to other sustainable development domains utilizing EO data.
Anatoly Bainazarov, Viktoriia Achkasova, Arsen Mikailov
et al.
The purpose of this article is to analyze the integration of the mathematical and natural competence formation in students during the study of geography in institutions of general secondary education. The basic material. As part of the combination of mathematical competence with any subject, including geography, it is important to understand how to perform numerical operations, work with geometric objects in space and on a plane, as well as establish spatial relationships between objects in the environment. It is also important to solve problems, especially a practical one, to build mathematical models of objects, processes, and phenomena. It`s also important to analyze and forecast the development of social phenomena, etc. The integration of natural and mathematical competence of students is expressed in the following signs: holistic understanding of the world; definition of a range of problems that can be solved using mathematical methods; logical thinking, performing actions according to an algorithm, justifying one’s own actions; the ability to use mathematical terms, symbolic and graphic information; the ability to orientate on a plane and space; the ability to measure and calculate values in life situations. Solving problems and performing tasks of a creative or exploratory nature organizes the creative level of students’ cognitive activity. If we consider the analysis of the problem itself, the search for ways to solve it, and the solution itself, this is all a creative process that makes it possible to raise students’ interest in the educational material. The teacher can transform and form a scientific view in students, as well as establish interdisciplinary connections between subjects, considering the activity approach, which is also emphasized by the «New Ukrainian School». Conclusions - the integration relationships of geographical and mathematical competences are very strong, but to form the necessary geographic subject competences, a geography teacher must have a sufficiently high level of the mathematical competence. Analyzing the educational (model) program in geography, updated in 2022, we can establish that most often the mathematical competence of students of grades 6-11 is formed precisely within the frame of practical work. In general, it was calculated that for all courses it is 23 practical works. Based on the analysis of the list in the educational and modular programs, we can note that research topics include mathematical calculations, statistical analysis, etc. in the 6th, 8th, 10th, and 11th grades.
The erudite priest Marciano Di Leo (1751–1819), a prominent personality in the historical and geographical panorama of his time, not only in his home territory, authored a vast literary and poetic production, but also tried his hand at producing some maps, referring to a province of the Kingdom of Naples. At a time when the principles of geodetic cartography had become increasingly known, even locally, hand in hand with improvements in technology and accuracy of measurements, the author reflects the historical narratives of progress of the European (and Neapolitan) Enlightenment and translates them into an unpublished manuscript of statistical, historical, and geographical nature, accompanied by numerous maps of various scales. The rediscovery of a largely unknown—and therefore not very thorough—minor cartographic production underscores the spread even in more marginal contexts of the most innovative ideas and increasingly precise scientific foundations in the cartographic-mathematical representation of the territory. It also illustrates the role of a number of intellectuals in the service of the political choices of their time, in an attempt-often unrealized-to bring about a decisive change of course in public administration, in accordance with Enlightenment ideals and in the spirit of reform that spread throughout Europe thanks to the French Revolution.
This paper examines the recent advances and applications of AI in human geography especially the use of machine (deep) learning, including place representation and modeling, spatial analysis and predictive mapping, and urban planning and design. AI technologies have enabled deeper insights into complex human-environment interactions, contributing to more effective scientific exploration, understanding of social dynamics, and spatial decision-making. Furthermore, human geography offers crucial contributions to AI, particularly in context-aware model development, human-centered design, biases and ethical considerations, and data privacy. The synergy beween AI and human geography is essential for addressing global challenges like disaster resilience, poverty, and equitable resource access. This interdisciplinary collaboration between AI and geography will help advance the development of GeoAI and promise a better and sustainable world for all.
The past decade has witnessed the rapid development of geospatial artificial intelligence (GeoAI) primarily due to the ground-breaking achievements in deep learning and machine learning. A growing number of scholars from cartography have demonstrated successfully that GeoAI can accelerate previously complex cartographic design tasks and even enable cartographic creativity in new ways. Despite the promise of GeoAI, researchers and practitioners have growing concerns about the ethical issues of GeoAI for cartography. In this paper, we conducted a systematic content analysis and narrative synthesis of research studies integrating GeoAI and cartography to summarize current research and development trends regarding the usage of GeoAI for cartographic design. Based on this review and synthesis, we first identify dimensions of GeoAI methods for cartography such as data sources, data formats, map evaluations, and six contemporary GeoAI models, each of which serves a variety of cartographic tasks. These models include decision trees, knowledge graph and semantic web technologies, deep convolutional neural networks, generative adversarial networks, graph neural networks, and reinforcement learning. Further, we summarize seven cartographic design applications where GeoAI have been effectively employed: generalization, symbolization, typography, map reading, map interpretation, map analysis, and map production. We also raise five potential ethical challenges that need to be addressed in the integration of GeoAI for cartography: commodification, responsibility, privacy, bias, and (together) transparency, explainability, and provenance. We conclude by identifying four potential research directions for future cartographic research with GeoAI: GeoAI-enabled active cartographic symbolism, human-in-the-loop GeoAI for cartography, GeoAI-based mapping-as-a-service, and generative GeoAI for cartography.
This paper surveys the long-standing connections and impact between Vaughan Jones's theory of subfactors and various topics in mathematical physics, namely statistical mechanics,quantum field theory,quantum information and two-dimensional conformal field theory.
Vegetation phenology has long been adapted to environmental change and is highly sensitive to climate change. Shifts in phenology also affect feedbacks of vegetation to environmental factors such as topography and climate by influencing spatiotemporal fluctuations in productivity, carbon fixation, and the carbon water cycle. However, there are limited studies which explores the combined effects of the climate and terrain on phenology. Bamboo forests exhibit the outstanding phenological phenomena and play an important role in maintaining global carbon balance in climate change. Therefore, the interaction mechanisms of climate and topography on bamboo forest phenology were analyzed in Zhejiang Province, China during 2001–2017. The partial least squares path model was applied to clarify the interplay between the climate and terrain impacts on phenology under land cover/use change. The results revealed that the average start date of the growing season (SOS) significantly advanced by 0.81 days annually, the end date of the growing season (EOS) was delayed by 0.27 days annually, and the length of the growing season (LOS) increased by 1.08 days annually. There were obvious spatial differences in the partial correlation coefficients between the climate factors and phenological metrics. Although the SOS, EOS and LOS were affected by different climatic factors, precipitation was the dominant factor. Due to the sensitivity of the SOS and EOS to precipitation, a 100 mm increase in regional annual precipitation would cause the average SOS to advance by 0.18 days and the EOS to be delayed by 0.12 days. Regarding the terrain factors affecting climate conditions, there were clear differences in the influences of different altitudes, slopes and aspect gradients on bamboo forest phenology. This study further showed that topographic factors mainly affected the interannual variations in phenological metrics under land cover/use change by affecting precipitation. This study clarified the spatial pattern of bamboo forest phenology and the interactive mechanisms between vegetative phenology and environmental conditions, as this information is crucial in assessing the impact of phenological change on the carbon sequestration potential of bamboo forests.
The textbook contains basic theoretical information about the geodetic and mathematical foundations of maps. It discusses the basic properties of topographic maps and methods of their use. Much attention is paid to the content of topographic maps of different scales — the display of physical, geographical and socio-economic objects on them. Meets the requirements of the federal state educational standards of higher education of the latest generation. The textbook is intended for students of pedagogical and agricultural universities studying in the fields of "Geography" and "Land management and cadastre".
João Vitor Roque Guerrero, G. Mataveli, Reinaldo Lorandi
et al.
Soil erosion is one of the greatest environmental problems in the 21st Century, mainly due to the economic, social, and environmental damages caused worldwide. Brazil is inserted within this context, where the implementation of strategies to support territorial planning aimed at soil conservation is urgently required. Thus, this work aimed to use geoenvironmental cartography techniques to map the potential erosive zones at the Gouveia stream watershed (Brotas, Brazil) based on geographic data systematized by geoprocessing. Parameters of geology, pedology, terrain shape, terrain slope, land use, and land cover were used and systematized in a GIS environment through mathematical operations and fuzzy inference to map the potential erosive zones. The results indicate that 63% of the basin consists of “High” and “Very High” potential areas for the erosion process, which requires an urgent need to implement management strategies and sustainable territorial planning. This approach can potentially contribute to the decision-making process in the study area and be applied in other watersheds worldwide.
Cartography includes two major tasks: map making and map application, which is inextricably linked to artificial intelligence technology. The cartographic expert system experienced the intelligent expression of symbolism. After the spatial optimization decision of behaviorism intelligent expression, cartography faces the combination of deep learning under connectionism to improve the intelligent level of cartography. This paper discusses three problems about the proposition of “deep learning + cartography”. One is the consistency between the deep learning method and the map space problem solving strategy, based on gradient descent, local correlation, feature reduction and non-linear nature that answer the feasibility of the combination of “deep learning + cartography”; the second is to analyze the challenges faced by the combination of cartography from its unique disciplinary characteristics and technical environment, involving the non-standard organization of map data, professional requirements for sample establishment, the integration of geometric and geographical features, as well as the inherent spatial scale of the map; thirdly, the entry points and specific methods for integrating map making and map application into deep learning are discussed respectively.
Map is the basic language of geography and an indispensable tool for spatial analysis. But for a long time, maps have been regarded as an objective and neutral scientific achievement. Inspired by critical geography, critical cartography/GIS came into being with the goal of clarifying the discourse embedded in cartographic practice. Power relationship challenges the untested assumption in map representation that is taken for granted. After more than 40 years of debate and running in, this research field has initially shown an outline, and critical cartography/GIS has roughly formed two research directions: the deconstruction path mainly starts from the identity of cartography subject and the process of map knowledge production, and analyzes the inseparable relationship between cartography and national governance and its internal power mechanism respectively; the construction path mainly relies on cooperative mapping and anti-mapping to realize the reproduction of map data. Domestic critical cartography/GIS research has just started, and it is necessary to continue to absorb the achievements of critical geography and carry out research in different historical periods. The deconstruction research of different types of maps also needs to strengthen the in-depth bridging between the construction path and the deconstruction path, and to be more open to the public. Impartial map application research, and actively apply the research results to social practice.
“Theoretical Geography” by William Bunge (1928–2013) was studied in detail from cartographic point of view. The history of creating this work was also considered. The book was a manifesto of a new direction in geography, based on mathematical methods and metacartography. The latter’s concept developed by Bunge formed a new look at the subject, methodology and philosophical foundations of cartography. Bunge was first to suggest the ambiguity of the map’s epistemological essence, included anamorphoses into the contents of cartographic works, presented maps and aerial photos as part of a general imaging system and correlated cartography with mathematics. He made a significant contribution to development of the transport cartography theory, to mapping methods (innovations related to development of topographic bases and application of cartographic representation methods). The author analyzes the development of this composition’s cartographic ideas by his contemporaries, as well as in the subsequent works of Bunge himself. It was concluded that the contribution of “Theoretical Geography” to cartography is not smaller than that to geographical science development.
Intertidal vegetation plays an essential role in habitat provision for waterbirds but suffers great losses due to human activities. However, it is challenging in tracking the human-driven loss and degradation of intertidal vegetation due to rapid urbanization in a high temporal resolution. In this study, a methodological framework based on full Landsat time-series (FLTS) is proposed to detect the year of change (YOC) of intertidal vegetation converted to impervious surfaces (ISs) and artificial ponds (APs), and the condition of the remaining intertidal vegetation was also assessed by FLTS, in the Fujian province, a subtropical coastal area lying in southeast China. The accuracies of the YOC detection of intertidal vegetation converted to IS and AP were 91.84% and 72.73%, with mean absolute errors of 0.26 and 1.06, respectively. The total areas of intertidal vegetation encroached by IS and AP were 31.68 km2 and 23.85 km2, respectively. Most ISs were developed later than 2010, and most APs were developed earlier than 2005, which are highly related to the implementation of local policies for economic development. The remaining intertidal vegetation in growing, stable, and degraded conditions were 43.05%, 56.38%, and 0.57%, respectively. The results indicated that areas of intertidal vegetation were reclaimed for anthropogenic uses at a considerable rate, although the intertidal vegetation still increased owing to natural development after the establishment of natural reserves. The study demonstrates that the FLTS has capacities in monitoring the dynamics in coastal zones solely for its dense earth observations.
Technological progress has touched practically all spheres of human activity. In the twenty first century, it is important to discover the world without a laptop or a smartphone, without software security, which allows you to quickly and effectively manage your business needs. Cartography has changed a lot and today. Making geographical discoveries, mankind from very ancient maps and protoplans came to mathematical cartography, and technological progress made it possible to create electronic maps, without which no modern person can do today. Cartography, as a science, is closely related to geography, and geographic insights have long been a tool for cartography. As a prime example of what Columbus declared to the New World, that cardinal change in the manifestation of people about the world. The achievements of modern cartography are based on technological progress. Far from skin science can boast of such a rich history of its formation as cartography, even though it is the root of ancient hours and skin historical period of the formation of cartography as a science of appearances with prominent examples of humankind and skin in its own way for culture. The path of the formation of cartography as a science can be mentally subdivided into several periods: cartography of the ancient world; cartography of the period of great geographic appearances of seafarers; cartography, which is based on technical progress and mathematical basis; the latest cartography with the best modern technologies. Cartography appeared, and the people learned how to designate coordinates. Modern cartography is a collapsible technological process based on the fundamental achievements of science and technology. Previously, the cards were hung on stones, created behind an additional penzle and parchment, but now the process has been completed, which allows you to take an electronic card and visualization using various modern technologies that are practically accessible to the skin.