Hasil untuk "Mathematical geography. Cartography"

Felix De la Cruz Serrano

The widespread availability of generative artificial intelligence tools poses new challenges for school mathematics education, particularly regarding the formative role of traditional mathematical tasks. In post-AI educational contexts, many activities can be solved automatically, without engaging students in interpretation, decision-making, or mathematical validation processes. This study analyzes a secondary school classroom experience in which open mathematical tasks are implemented as a didactic response to this scenario, aiming to sustain students' mathematical activity. Adopting a qualitative and descriptive-interpretative approach, the study examines the forms of mathematical work that emerge during task resolution, mediated by the didactic regulation device COMPAS. The analysis is structured around four analytical axes: open task design in post-AI contexts, students' mathematical agency, human-AI complementarity, and modeling and validation practices. The findings suggest that, under explicit didactic regulation, students retain epistemic control over mathematical activity, even in the presence of generative artificial intelligence.

Jamal S. Huseynov, T. Huseynova, A. Tagiyev

The article provides a detailed overview of the effects of climate changes on the meteorological factors (air temperature and atmospheric precipitation) that play a key role in human activity in the Greater Caucasus region in 1991-2020. In the analysis, the climate changes and its effects on the quality of life were studied. It has been determined that anomalies recorded in air temperature and precipitation occur mainly in densely populated and work areas. The research was conducted on the basis of mathematical, statistical and cartographic methods. The conducted studies show that the effects of climate changes in the Greater Caucasus region affect agriculture, tourism, etc. It is also inevitable in the industrial field. Therefore, by conducting mitigation measures in advance and continuous development, conditions can be created to improve the quality of life of the population. Mathematical statistical analysis shows that since the main population of the province is located in the city of Baku, large waste sources that pollute the atmosphere and environment are located here. It was determined that as a result of climate changes, which are considered an environmental crisis, there was a 4% decrease in the amount of precipitation in the general region, and an increase in the average annual temperature by 0.80C. The amount of atmospheric precipitation in this province has reached 6 mm. A greater decrease in individual hydrometeorological stations was recorded in the Absheron Peninsula. The main altitudinal effects of climate changes are recorded in the zone where the population is settled, where there is employment and where fresh water resources are formed. Due to the ongoing extreme heat, water in the rivers is decreasing, which, on the one hand, reduces the possibilities of irrigation in agriculture, and on the other hand, leads to a decrease in water resources in general. Similar declines in snowfall threaten many winter tourism centers and local economies. So, both weak and strong effects of climate changes on the quality of life of the population have been determined. The negative effects of climate change on the economy lead to lower overall well-being, lower incomes and job losses, all of which ultimately lead to lower quality of life. Climate change is already seriously affecting all key indicators of quality of life, and worryingly, with its expected acceleration, this impact will be even greater.

Jarosław Czochański

W 2015 r. nastąpiły w polskim systemie prawnym zmiany stanowiące efekt opóźnionego wdrożenia zapisów dokumentu Europejskiej Konwencji Krajobrazowej z 2000 r., wprowadzające m.in. wykonanie audytów krajobrazowych na poziomie województw. Zmiany te wprowadziła Ustawa z dnia 24 kwietnia 2015 r. o zmianie niektórych ustaw w związku ze wzmocnieniem narzędzi ochrony krajobrazu – zwana powszechnie „ustawą krajobrazową”. Na potrzeby tego działania opracowana została nowa, odrębna metodyka i procedura badawcza, oparta na doświadczeniach badań krajobrazowych i kulturowych w Polsce, po raz pierwszy przyjęta w postaci aktu prawa – tj. Rozporządzenia Rady Ministrów. Na zakres audytu krajobrazowego składa się identyfikacja cech przyrodniczych i kulturowych krajobrazu, wyróżnienie jednostek krajobrazowych stanowiących jednolite typologicznie jednostki niższego rzędu od mikroregionów, wykonanie ich badania i ustrukturyzowanej charakterystyki, ocena walorów i zagrożeń oraz – na ich podstawie, wyznaczenie tzw. krajobrazów priorytetowych, wyróżniających się najwyższymi walorami pod względem przyrodniczym, kulturowym i fizjonomicznym. Dla tych krajobrazów następuje opracowanie wniosków i rekomendacji, służących ochronie ich walorów i zrównoważonemu wykorzystaniu ich przestrzeni. Mimo relatywnie długiego okresu przygotowania wymienionego rozporządzenia (ukazało się ono dopiero w 2019 r.) nie ustrzeżono się błędów merytorycznych, polegających na niepełnym zdefiniowaniu zróżnicowania typologicznego krajobrazów Polski, nieprecyzyjnym wskazaniu metod ich wyznaczania i budzącej zastrzeżenia procedurze wyznaczania krajobrazów priorytetowych. Cała metodyka jest na tyle skomplikowana i szczegółowa, że prace nad audytem krajobrazowym, do końca 2023 r. zakończyły jedynie dwa województwa. Pomimo przygotowania dobrych założeń merytorycznych w sferze naukowej, z doświadczeń wykonywania audytów w województwach dobitnie wynika nieprecyzyjne określenie metod wyznaczania i typologizacji jednostek krajobrazowych, błędne sformułowanie sformalizowanych metod służących wyznaczeniu krajobrazów priorytetowych oraz – w rezultacie – uzyskanie zróżnicowanych, niejednorodnych w skali kraju i niezadowalających wyników. Ze względu na bardzo szeroki zakres problemów przeprowadzenia audytu krajobrazowego w artykule skupiono się na ocenie jego pierwszej, zakończonej już części, podziału przestrzeni na jednostki krajobrazowe wg przyjętych kryteriów podziału i typologii oraz ocenie błędów i rozpoznanych problemów wdrażania procedur badawczych. Wnioskiem z tej oceny jest twierdzenie o potrzebie weryfikacji założeń metodycznych audytu, praktycznie na każdym etapie wprowadzonej procedury. Artykuł nie odwołuje się do analogicznych doświadczeń zagranicznych i ma charakter dyskusyjny, skupiając się na wykazaniu błędów i problemów, wymagających zdaniem autora naprawy.

Sylvain Fontaine

Neuroscience and AI have an intertwined history, largely relayed in the literature of both fields. In recent years, due to the engineering orientations of AI research and the monopoly of industry for its large-scale applications, the mutual expansion of neuroscience and AI in fundamental research seems challenged. In this paper, we bring some empirical evidences that, on the contrary, AI and neuroscience are continuing to grow together, but with a pronounced interest in the fields of study related to neurodegenerative diseases since the 1990s. With a temporal knowledge cartography of neuroscience drawn with advanced document embedding techniques, we draw the dynamical shaping of the discipline since the 1970s and identified the conceptual articulation of AI with this particular subfield mentioned before. However, a further analysis of the underlying citation network of the studied corpus shows that the produced AI technologies remain confined in the different subfields and are not transferred from one subfield to another. This invites us to discuss the genericity capability of AI in the context of an intradisciplinary development, especially in the diffusion of its associated metrology.

Louis Boucherie

Complex systems are made up of many interacting components. Network science provides the tools to analyze and understand these interactions. Community detection is a key technique in network science for uncovering the structures that shape the behavior of these networks. This thesis introduces the Adaptive Cut, a novel method that improves clustering methods by employing multi-level cuts in hierarchical dendrograms. Overcoming the limitations of traditional single-level cuts-especially in unbalanced dendrograms-the Adaptive Cut provides a multi-level cut by optimizing a Markov chain Monte Carlo with simulated annealing. In addition, we propose the Balanceness score, an information-theoretic metric that quantifies dendrogram balance and predicts the benefits of multilevel cuts. Evaluations on over 200 real and synthetic networks show significant improvements in partition density and modularity. In the second part, our analysis shows that incorporating network geometry allows redefining administrative boundaries into non-contiguous regions that better reflect social and spatial dynamics. We also discuss the representation of hierarchical data in hyperbolic space through Poincare maps, which can represent tree-like structures in low dimension. In addition, we examine how geography constrains human mobility, an aspect often overlooked in scale-free characterizations of mobility. By incorporating geography via the pair distribution function from condensed matter physics, we separate geographic constraints from mobility choices. Analyzing datasets containing millions of individual movements, we identify a universal power law that spans five orders of magnitude, thereby bridging the divide between distance-based and opportunity-driven models of human mobility.

Marcos Eduardo Valle, Santiago Velasco-Forero, Joao Batista Florindo et al.

Mathematical morphology provides a nonlinear framework for image and spatial data processing and analysis. Although there have been many successful applications of mathematical morphology to vector-valued images, such as color and hyperspectral images, there is still no consensus on the most suitable vector ordering for constructing morphological operators. This paper addresses this issue by examining a reduced ordering approximating the Condorcet ranking derived from a set of vector orderings. Inspired by voting problems, the Condorcet ordering ranks elements from most to least voted, with voters representing different orderings. In this paper, we develop a machine learning approach that learns a reduced ordering that approximates the Condorcet ordering. Preliminary computational experiments confirm the effectiveness of learning the reduced mapping to define vector-valued morphological operators for color images.

Ziyu Yan, Bin Sun, Zhihai Gao et al.

As the most extensive temperate grassland in the world, the Eurasian Steppe provides various ecological services that support the environment and human well-being. However, grassland degradation has become a serious environmental issue. Most of the traditional degradation assessments ignore the sensitivity of grassland ecosystems to climatic conditions. In response, our study introduces a new comprehensive identification framework that integrates vegetation growth and climate change, using a novel long-term monitoring methodology to detect grassland degradation and improvement. The framework quantifies the area and degree of degradation and improvement in the Eurasian Steppe using long time-series data from 2000 − 2020. Then, the driving factors of grassland change were analyzed using a quantitative model. Our findings reveal a clear trend of improvement in the Eurasian Steppe was identified, with the improved area being 4.72 times larger than the degraded area (221.4 × 104 and 46.92 × 104 km2, respectively). The Tibetan Plateau and Loess Plateau led to the improvement. Simultaneously, the area surrounding the northern Caspian Sea has been severely degraded. The three areas correspond to frigid humid and semi-humid grassland, temperate humid and semi-humid grassland, and temperate arid and semi-arid grassland, respectively. Globally, the combined effects of climate change and human activities dominated the observed grassland degradation and improvement, accounting for 77.13% and 89.64%, respectively. Our method provides a robust tool for detecting grassland degradation and improvement across large scales, offering scientific support for achieving the United Nations’ Sustainable Development Goals (SDGs), particularly land degradation neutrality (LDN).

Divya Jyoti Bajpai, Manjesh Kumar Hanawal

The large size of DNNs poses a significant challenge for deployment on devices with limited resources, such as mobile, edge, and IoT platforms. To address this issue, a distributed inference framework can be utilized. In this framework, a small-scale DNN (initial layers) is deployed on mobile devices, a larger version on edge devices, and the full DNN on the cloud. Samples with low complexity (easy) can be processed on mobile, those with moderate complexity (medium) on edge devices, and high complexity (hard) samples on the cloud. Given that the complexity of each sample is unknown in advance, the crucial question in distributed inference is determining the sample complexity for appropriate DNN processing. We introduce a novel method named \our{}, which leverages the Data Cartography approach initially proposed for enhancing DNN generalization. By employing data cartography, we assess sample complexity. \our{} aims to boost accuracy while considering the offloading costs from mobile to edge/cloud. Our experimental results on GLUE datasets, covering a variety of NLP tasks, indicate that our approach significantly lowers inference costs by more than 43\% while maintaining a minimal accuracy drop of less than 0.5\% compared to performing all inferences on the cloud. The source code is available at https://anonymous.4open.science/r/DIMEC-1B04.

Haicang Zhou, Weiming Huang, Yile Chen et al.

Road network representation learning aims to learn compressed and effective vectorized representations for road segments that are applicable to numerous tasks. In this paper, we identify the limitations of existing methods, particularly their overemphasis on the distance effect as outlined in the First Law of Geography. In response, we propose to endow road network representation with the principles of the recent Third Law of Geography. To this end, we propose a novel graph contrastive learning framework that employs geographic configuration-aware graph augmentation and spectral negative sampling, ensuring that road segments with similar geographic configurations yield similar representations, and vice versa, aligning with the principles stated in the Third Law. The framework further fuses the Third Law with the First Law through a dual contrastive learning objective to effectively balance the implications of both laws. We evaluate our framework on two real-world datasets across three downstream tasks. The results show that the integration of the Third Law significantly improves the performance of road segment representations in downstream tasks.

Qinjun Wang, Jingjing Xie, Jingyi Yang et al.

Fine-grained sediments are Quaternary sediments with grain sizes of not more than 2 mm. They start first when meeting water, their stability is related to the initial water volume triggering debris flow, and thus plays an important role in debris flow hazards early warning. The permeability coefficient is the inter-controlled factor of fine-grained sediment stability. However, there is no hyperspectral model for detecting the fine-grained sediment permeability coefficient in large areas, which seriously affects the progress of debris flow hazards early warning. Therefore, it is of great significance to establish a hyperspectral detection model for the permeability coefficient of fine-grained sediments. Taking Beichuan County, Southwestern China as the case, a permeability coefficient hyperspectral detection model was established. The results show that eight bands are sensitive to the permeability coefficient with a correlation coefficient (R) of 0.6343. T-test on the model shows that P-values for sensitive bands are all less than 0.05, indicating the established model has a good prediction ability with a precision of 85.83%. These sensitive bands also indicate the spectral characteristics of the permeability coefficient. Therefore, it provides a scientific basis for fine-grained sediment stability detection in large areas and lays a theoretical foundation for debris flow hazards’ early warning.

Simon Scheider, Harm Bartholomeus, Judith Verstegen

The recent success of large language models and AI chatbots such as ChatGPT in various knowledge domains has a severe impact on teaching and learning Geography and GIScience. The underlying revolution is often compared to the introduction of pocket calculators, suggesting analogous adaptations that prioritize higher-level skills over other learning content. However, using ChatGPT can be fraudulent because it threatens the validity of assessments. The success of such a strategy therefore rests on the assumption that lower-level learning goals are substitutable by AI, and supervision and assessments can be refocused on higher-level goals. Based on a preliminary survey on ChatGPT's quality in answering questions in Geography and GIScience, we demonstrate that this assumption might be fairly naive, and effective control in assessments and supervision is required.

Daniel Sternheimer

We briefly recount the long friendship that developed between Ludwig and us (Moshe Flato and I), since we first met at ICM 1966 in Moscow. That friendship extended to his school and family, and persists to this day. Its strong personal impact and main scientific components are sketched, including reflexions on what mathematical physics is (or should be).

Hao Kang, S. Ruan

In this paper we propose an age-structured susceptible-infectious-susceptible epidemic model with nonlocal (convolution) diffusion to describe the geographic spread of infectious diseases via long-distance travel. We analyze the well-posedness of the model, investigate the existence and uniqueness of the nontrivial steady state corresponding to an endemic state, and study the local and global stability of this nontrivial steady state. Moreover, we discuss the asymptotic properties of the principal eigenvalue and nontrivial steady state with respect to the nonlocal diffusion rate. The analysis is carried out by using the theory of semigroups and the method of monotone and positive operators. The spectral radius of a positive linear operator associated to the solution flow of the model is identified as a threshold.

I. Kalynych, Mariya Nychvyd, I. Prodanets et al.

The aim of this work. This article is devoted to the study of geodynamic processes in the Tysza River basin within the Transcarpathian region with an analysis of geodetic observations obtained over the past decade. Method. Karst monitoring began with the identification of the most dangerous areas of the earth's surface that are subject to vertical displacements. After the detection of the most dangerous areas the local geodetic monitoring was carried out at facilities within the urban settlement to prevent possible accidents: Solotvyno, Dilove and Bila Tserkva. A collection of archival aerial photography was also used to develop a methodology for identifying changes in landscapes and landforms under the influence of geodynamic processes. Results. UAVs were used to remove karsts. On the basis of digital aerial photography data were created: orthophotos and digital terrain models. Digital aerial photography was carried out in accordance with the requirements of regulatory documents. To determine the dynamics of landslides and karst the digital aerial photography must be repeated several times at certain intervals. Aerial photography work was carried out in two stages in 2020 and 2021 Contour points were selected for identification marks. They are recognized on aerial photography and the terrain with an accuracy of at least 0.1 mm on the scale of the created plan. Mathematical processing of geodetic GPS measurements was performed using Trimble Geomatics Office software. After photogrammetric processing, the quality control of the obtained results was performed and digital surface models using DEM and TIN methods. Orthophotomaps on a scale of 1:1000 were made from raster images of aerial photographs, taking into account the created digital terrain model. There is a need for monitoring work to update information on the state of modern karst formations and areas with exogenous processes in Solotvyno and Bila Tserkva, Tyachiv district and the village Dilove, Rakhiv district, Transcarpathian region. The technology of topographic and geodetic works with the use of UAVs and GPS measurements in mountainous areas has been developed and tested. The results of aerial photography were used to visualize the study objects and to convey information regarding the deformation processes to local governments. For processes of natural or man-made nature (displacement, landslides, karst) requires the development of individual approaches to the use of UAVs. With the mass use of UAV images, a data bank is formed, which cannot be obtained by other methods. The study made it possible to create the method of complex determination of movements in exogenous and technogenic areas in mountainous areas with the use of the latest technologies. It allows quick establishing a plan-altitude basis of the required accuracy in the reference coordinate system in solving a number of applied geodesy problems using satellite technologies and UAVs for observations by objects.

Rostyslav Sossa, M. Yurkiv

Ancient maps and plans are important sources of information for multifaceted knowledge of the past. In many studies, the accuracy parameters of spatial data are in demand. The purpose of our work is to study the geometric accuracy of the Lviv plan 1894 by Józef Khovanec. The methodology for studying the accuracy assessment is based on the transformation and geometric analysis of sets of identical points in the ancient plan and the modern reference one. For such a transformation, the Helmert transformation with four parameters and multiquadratic interpolation methods are used. The obtained results make it possible to graphically visualize the inaccuracies of the old plan in the form of displacement vectors, scale and rotation isolines, which clearly territorially diversify the distortions of the cartographic image. Using the method of least squares, a value was obtained that characterizes the positional accuracy of the ancient plan. All calculations and illustrations were made in the MapAnalyst software package, which specializes in the cartometric analysis of old maps. The results of cartometric analysis are influenced by a number of different factors, the decisive ones for the study were the following: the quality of the original; selection of a set of identical items; interpolation technique. When choosing identical points, the main attention is paid to their uniform distribution over the entire area of the plan at a constant position in time. The results obtained represent only one of the possible mathematical models built on the basis of the input data. However, we consider the achieved results to be valid. The processed technique significantly speeds up and simplifies the study of the accuracy of old plans and can be used for similar studies of other cartographic works, and the obtained numerical results and graphic visualizations can be used to compare old plans with each other.

I. Yashkov, D. A. Surkov

The article gives a brief survey of a set of 14 thematic maps of the late 1920s–1940s representing the territory of the modern Khanty-Mansi Autonomous Okrug — Yugra. This collection of electronic maps, which has been received by the Museum of Geology, Oil and Gas in 2020, is a unique cartographic source containing a valuable historical information on the region’s territory as regards of economy and nature management, land use and land tenure system, economic geography and geourbanistics, as well as geobotany, environmental history and other earth sciences and related disciplines. The maps are hand-made with the use of original design of the legend and the system of symbolic designation. These cartographic products are also of great scientific value, first of all, in connection to the historical geography. The preparation of the maps had been fulfilled at a time when there were no extensive topographic and geodesic works on the territory of Western Siberia, and expeditionary works and field surveys were not widespread. At that period, the region was characterized by the predominance of traditional economic forms of its indigenous inhabitants, as well as the development of agriculture, fishery and logging by special settlers. Today, these maps are of particular importance as they provide information for comparative analysis — since the beginning of the 1950s, the large-scale industrialization of the region began in connection with the discovery of the country’s largest hydrocarbon reserves and the start of exploitation of the West Siberian oil and gas province. This new period of the region’s development, which is lasting up to the present day, to a large extent transformed all previous forms of economic use of territory and radically changed the course of environmental history.

Mabrouk Laâbar, Mongi Sghaier

La présente communication interroge le changement institutionnel induit par le grand projet de développement agro-pastoral et de promotion des initiatives locales pour le sud-est (PRODESUD) dans le système de gouvernance des parcours collectifs du sud de la Tunisie. L’analyse institutionnelle que nous proposons pour la discussion de cette problématique comprend deux étapes. La première fait intervenir l’outil de grammaire institutionnel développé par Crawford et Ostrom (1995, 2005) pour l’identification et la structuration des nouvelles règles de gestion soutenues par PRODESUD toute au long de la période 2003-2020. La deuxième étape propose la discussion de la conformité de ces nouvelles règles aux principes de bonne gouvernance identifiés par la théorie des communs (Ostrom, 1990, 2000, 2009). Les résultats de l’analyse montrent que le projet PRODESUD a apporté un bon nombre de solutions pratiques permettant à une conciliation assez intéressante entre les conditions socio-écologiques contraignantes des grands parcours du sud tunisien et les principes de bonne gouvernance énoncés par Ostrom (1990).

S. Schäfer

Meng Jin, Ming Lin, Yufu Liu et al.

Thousands of satellites and instruments are providing very unique long-term, refined, and diverse perception capabilities for the states and changes of the Earth's surface environment. When leveraging Earth Observation (EO) techniques in SDG monitoring in specific regions, an important prerequisite is to evaluate whether EO could meet user requirements in terms of spatial coverage, temporal frequency and observing variables or objects. It is highly expected to have a quantitative model that can not only represent EO capabilities and observation requirements but also evaluate the potential of EO capability to fulfil these requirements. This paper first describes EO capabilities from the satellite's orbit, operation time, spatial resolution, revisit cycle, accessibility and observation relevance level to variables. Observation requirements and priorities are then derived from SDG indicators. Finally, the potential model is established to match EO capabilities and user requirements. Taking SDG 14.1.1 as an example, this model is capable of returning an ordered list of satellites and instruments for users to refer to. This model meets the gap of evaluating EO potential to fulfil SDG monitoring. It could make full use of the available EO capabilities worldwide to meet SDG indicator monitoring requirements.

Andrii Galayda, B. Chetverikov, I. Kolb

The aim of the work is to propose a method of creating a geographic information online resource for the management of Lisovohrynivetska UTC. To implement the tasks, a technological scheme was proposed, which consisted of 9 stages of work. The first stage involved the collection and analysis of disparate data in both vector and raster formats on the territory of the Lisovohrenivetska united territorial community. In the second stage, with the help of Global Mapper software, all vector data files in *.dxf and *.dmf formats, which were previously available, were converted to *.shp format for further processing in ArcGIS software. As a result of the conversion, graphic and attributive data were obtained in the required format and according to the layers they contain, the geodatabase with symbols according to the classifier was edited to create 1: 2000 scale plans. The next step was to unify the database of convertible files, as vector data was created with different construction of attribute tables. In addition, there is a need to enter vector data into the edited geospatial database. To do this, a ArcPy script was written that rearranges attribute tables and enters data into a geodatabase. Adjusted and populated the attribute database of vector objects for those columns where there was no information. The penultimate step was to develop the structure of the geoportal on the basis of ArcGIS-online to download the geodatabase to Lisovohrynivetska UTC on the server, to enable their external use with a unique login and password. The last step, after creating the structure of the geoportal, was to upload vector and raster geodata prepared by ArcGIS to the geoportal. As a result of the realization of the set purpose the technique of creating the geoinformation online resource for the management of the united territorial community is offered and described. During the implementation of the method the data of 24 disparate vector layers for the Lisogrynivtska community of Khmelnytsky region were processed and converted. Raster cartographic materials for UTC were collected and processed. The geodatabase according to the classifier for scale 1: 2000 is created. The structure of the geoportal based on the ArcGIS-online kernel with a connected map-base based on the online resource GoogleMaps, where all processed materials are downloaded, has been developed. The scientific novelty is to develop the concept of accumulation of heterogeneous vector and raster geospatial data in one geodatabase, by converting them into a specific format. Additional modules have been written in ArcPy to unify the database structure. Implemented geoinformation system is located on the geoportal and is designed for management decisions of community leaders. In addition, the created GIS can be used for land management and surveying work on community sites.