Ecological stability in the Arctic zone of the European north-east of Russia can be ensured by the natural-ecological framework (NEF), including the ecological framework—protected areas with legislative restrictions on nature management, and the natural framework—territories that do not have a protected status, but maintain ecological balance. The purpose of the work is a quantitative assessment of the compliance of the spatial structure of the NEF of the region with the scientific recommendations of N.F. Reimers and F.R. Shtilmark on the necessary share of the NEF area and the recommendations of the Arctic Council on the share of the area of protected areas from the area of natural subzones. The analysis, conducted on the basis of the formed database of multi-scale geospatial data, consisting of three sets of vector and raster layers, including protected areas, areas of high landscape and ecological value, disturbed lands and licensed areas for subsoil development, showed the following. The region’s NEF is represented by unevenly distributed protected areas and ecologically significant landscapes, the largest areas of which are in the subtundra forest and large swamp areas. The disturbed lands in the NEF structure are not large, but the NEF area located within the licensed subsoil areas, and therefore under threat of degradation, is significant and amounts to about 13 % in the northern subarctic tundra and forest tundra. The recommended share of the NEF area is noted only for the arctic tundra and northern taiga. In the southern subarctic tundra, this is only 1/5 of the norm. The recommended share of the area of protected areas from the area of natural subzones is also noted only for the arctic tundra (52 %), and for the forest tundra it is only 2.8 % instead of 15. Of all the natural subzones, the forest-tundra least meets scientific recommendations and characterized by a combination of: an insignificant share of the NEF from the area of the subzone, the lowest share of the area of the protected area from the NEF area, the largest area of already disturbed and threatened lands within the NEF. Thus, the potential of ecological balance in the region can be ensured by improving the NEF structure by increasing the number of protected areas and developing legislatively formalized restrictions on nature management, primarily for the territories of the natural framework located within the licensed areas for subsoil development.
Remote sensing data (RSD) and the machine learning methods used with them are currently used in mapping geographic processes and objects of the earth’s surface associated with the functioning of ecosystems and landscapes. RSD is often used to map one of the landscape components—vegetation, often representing the main source of information about it. This also applies to such hard-to-reach areas as the Uzon caldera. Thus, the purpose of this work was to create a cartographic model of the vegetation of a part of the Uzon caldera. For this purpose, the work used a generalized map of the caldera vegetation compiled by A.O. Pesterov, data from geobotanical descriptions provided by employees of the Botanical Institute of the Russian Academy of Sciences as auxiliary materials for creating a training sample for machine learning. The work also used data on the height of the vegetation cover, aboveground biomass, as well as several Sentinel-2 and Landsat-9 channels, from which a composite raster was created. In addition to channels 4–8 of Sentinel-2 and channel 10 of Landsat-9, the classified raster included ArcticDEM data. The training sample was created based on auxiliary data; the test sample was created by expert assessment based on high-resolution remote sensing data and geobotanical description data. K-means and Random Forest were selected as the classification methods used. For the first, the elbow method was used to assess the expression and separability of classes from each other in the classified raster. This method showed the inconsistency of the unsupervised classification method and the need to use methods with training. For the second, an accuracy assessment was used on test data with pre-determined optimal parameters of the trained model; an error matrix for each class was also compiled and classification quality metrics were calculated in Python 3.0. Thus, the overall accuracy of the model was 90 %. Statistical characteristics of the model were calculated and the features of its operation with the resulting vegetation classes were identified.
The development of wildfires in the steppes of Northern Eurasia and adjacent territories has intra-regional differences due to the change in latitudinal-zonal conditions, landscape diversity, spatial structure and the level of impact of agricultural activities. One of the poorly studied territories in this regard is the Ural-Altai steppe sector on an area of 1.18 million km2, or 52 % of all the steppes of Northern Eurasia. The use of global products based on MODIS images—MCD14ML (thermal anomalies) and MCD64A1 (burnt areas) for 2001–2023 allowed us to identify the features of the formation of fire situations. A macro-regional trend towards a reduction in fire areas has been confirmed, with a particularly significant decline in the middle and southern steppe subzones. This trend is due to the widespread increase in pasture load on land, and for agricultural regions, the increasing fragmentation of space by newly cultivated agricultural fields. There is a high interannual variability in the development of fires, most likely related to the variety of meteorological conditions of fire danger in individual years. It has been revealed that according to the long-term and intra-annual dynamics of fires, the northern steppes have common features with the forest-steppes, and the middle and southern steppes with the northern steppes. The specified groupings of natural subzones (“pyrogenic areas”) specific fire situations correspond, differing in the conditions of spatial development of fires and the structure of agricultural production, etc. The intra-annual daily dynamics of fires indirectly confirms the anthropogenic cause of most fires. In the agriculturally developed regions, two peaks of fires are recorded—in April and in September-October, corresponding to the beginning and end of seasonal agricultural work. As the archives of MODIS images containing information from 2001 accumulate, the series of global fire data created on their basis becomes a convenient tool for identifying the features of fire situations at the macro-regional level.
The spatial and temporal variability in the development of steppe fires is largely due to the peculiarities of seasonal, interannual and long-term vegetation conditions. At the same time, there is no objective understanding of which phytocenotic parameters of steppe vegetation are recorded by spectral vegetation indices (SVI) based on Earth remote sensing materials. In this regard, the purpose of the study was to identify these correspondences, as well as to test aerial photography materials as an additional source of detailed information about the spatial and temporal structure of vegetation cover. In the area located in the foothill steppes of the Southern Urals, field studies were conducted in 2023–2024, during which vegetation descriptions and mowing were carried out monthly during the growing season (April–October), aerial photography using a UAV with a standard RGB-sensor. Vegetation is represented by the Stipa zalesskii–Festuca valesiaca–Stipa capillata community and its pasture-degraded variant Ceratocarpus arenarius–Potentilla bifurca. The objective advantage of aerial photographs and color vegetation index (CVI) NDI, VARI, ExG, GLI, ExGR and ExR distribution schemes based on them is their high level of detail, which makes it possible to assess the features of spatial differentiation of vegetation cover, the direction of seasonal and long-term changes. It was revealed that the values of NDVI Sentinel-1–2 and CVI were most often highly correlated with the projective cover of green vegetation. A close relationship was observed with other phytocenotic indicators (total projected coverage, total phytomass reserves and green vegetation) in the hydrothermal conditions favorable for vegetation in 2024 due to the abundance of green vegetation. The results obtained suggest that the main factors of discrepancies between spectral and color indexes and the actual parameters of steppe communities are: a) the overlap of green vegetation with dead phytomass; b) the small share of diverse grasses in the structure of steppe communities; c) seasonal differences in the spectral response of dominant plants and in the aspects they create; d) morphological features of plant species, the volumetric structure of vegetation cover created by them. The revealed phenological reactions of communities to the features of hydrothermal conditions in 2023 and 2024 indicate a high degree of interannual and seasonal variability in their fire status.
This study presents a geospatial approach to the assessment of soil fertility within a representative agricultural territory in the Don River Basin. The analysis is based on the integration of agrochemical survey data with cartographic modeling using GIS tools, enabling the construction of detailed maps for key soil properties, including humus content, soil pH, nitrogen (N), phosphorus (P), and potassium (K) availability. The results demonstrate a high degree of spatial heterogeneity in nutrient distribution across the study area. Medium-humus chernozems predominate, while high-humus zones in the western sector exhibit lower pH values, indicating enhanced acidity due to the presence of humic acids and reduced calcium buffering. Nitrogen availability shows a patchwork pattern, with medium and high content dominating, although low-nitrogen zones persist in the western part of the region. Phosphorus availability is markedly elevated in the central part of the area, suggesting potential over-application of fertilizers and ecological oversaturation. Potassium, in contrast, is uniformly abundant, indicating non-limiting status for crop production. An integrated fertility index was developed by overlaying the individual nutrient maps, revealing that 20.3 % of the territory represents high-fertility reference soils, while 15.8 % requires fertility enhancement. The findings confirm the utility of geoinformation methods in agrochemical monitoring and support their application for sustainable land-use planning and adaptive management of soil resources. The methodology offers a replicable framework for regional agroecological diagnostics.
The relevance of this work lies in the need for continuous monitoring of the state of natural environments in view of increasing industrialization in the cities of the Republic of Sakha (Yakutia). This study is especially relevant due to the increase in anthropogenic impact on a fairly small territory of these cities. Heavy metals in the form of industrial and motor transport emissions fall on the surface of urban soils together with dust into the human body. The aim was to determine the degree of anthropogenic pollution of soil cover in the studied territories with the help of geographic information systems (GIS-technologies). In this work we used the urban soil kappametry as a predictive and search method for detecting the presence of heavy metals in soil. The obtained data were statistically processed, average values and degrees of their variability were determined. GIS-technologies through QGIS 3.20 software were used for map construction. The results of measuring the volumetric magnetic susceptibility of soil surface in the territory of Yakutsk (295 points), Aldan (232 points) and Neryungri (49 points) are presented. Average, minimum and maximum values of magnetic susceptibility of urban soils were determined. The territories with high automobile traffic as well as territories near industrial enterprises are characterized by increased values of soil magnetic susceptibility. With the help of statistical methods of data interpretation, coefficients of variation, limits of the obtained data were revealed. The constructed maps-charts of spatial distribution of magnetic susceptibility maxima showed that the territories adjacent to highways and streets with intensive automobile traffic can be considered as the most polluted with heavy metals. In this case, GIS-technologies clearly reflect the areas that need increased attention to address heavy metal problems in the soil.
Large-scale mapping of terrestrial ecosystems in the suburbs of Nickel (Murmansk Region), subjected to long-term impact of copper-nickel production, was carried out. The study combined modern methods of remote sensing (using UAV) with traditional methods (field geobotanical descriptions). During the field work in 2023–2024 about 65 geobotanical descriptions with GPS-binding were performed, 10 orthophotomaps and digital relief models were created. The results of the work made it possible to identify a clear dependence of the distribution of vegetation on geomorphological conditions. Technogenic wastelands with a sandy-gravelly substrate with small number of plants (less than 15 %) prevail on large structural-denudation ridges. On ridges of smaller size and height, a greater variety of vegetation was noted (up to 90 % of projective coverage) with birch overgrowth and a pronounced shrub tier. In waterlogged depressions, shrubby forms of willow, sedge and horsetail in the grass layer dominate. Areas with a high projective coverage of liverwort (up to 80 %), which plays the role of a pioneer species mark succession processes. A classification has been developed, including 15 types of ecosystems considering the position in the relief, projective coverage of various types, morphometric parameters of vegetation. We created a series of thematic plans on a scale of 1:5 000 using QGIS with an easy to understand legend. The study showed that, despite the long-term industrial impact, the initial stages of successional processes are observed, especially in relief depressions close to streams and reservoirs. The results obtained are important for the development of remediation measures and monitoring of vegetation dynamics after the closure of the smelter in 2020.
Assessing urban dynamics is a critical prerequisite for fostering sustainable regional development, particularly in rapidly urbanizing areas experiencing intense demographic and economic transformation. This study investigates the potential of nighttime satellite imagery—specifically data from the Suomi National Polar-orbiting Partnership (Suomi NPP) and its Visible Infrared Imaging Radiometer Suite (VIIRS)—to serve as a proxy for tracking spatial and temporal patterns of urban growth in the Tashkent Region of Uzbekistan, a key economic hub in Central Asia undergoing significant structural change. Drawing on a comprehensive dataset comprising 11 664 radiance observations across 81 urban settlements between 2012 and 2023, we analyze metrics of radiance growth, intensity distribution, temporal frequency, and variability to characterize urban trajectories. Our findings reveal robust correlations between nighttime light radiance and both economic activity and urban expansion, enabling the classification of settlements into three distinct categories of urban dynamism: low, moderate, and high. Notably, in some cases—such as Bekabad—radiance aligns more closely with industrial output than with population size, underscoring the method’s sensitivity to economic structure. The approach demonstrates high scalability, cost-efficiency, and reliability, especially in contexts where official socio-economic statistics are sparse, inconsistent, or delayed. By validating radiance as a robust indicator of urban vitality, this research establishes a foundation for integrating remote sensing data with conventional planning tools to support evidence-based decision-making in regional policy, infrastructure investment, and sustainable urban management. The developed methodological framework is readily transferable to other regions facing similar data limitations, offering a replicable model for monitoring urban change in the Global South.
Small towns, making up the vast majority of urban settlements in Russia and remaining the nodal elements of the spatial framework, continue to perform a critically important function of service centers for vast territories. Despite limited resources, demographic aging and a general tendency to shrink, their role in conditions of fragmentation of the developed space and reduction of the service sector in rural areas is only increasing. At the same time, this group of cities is extremely heterogeneous and demonstrates different development trajectories determined by a set of factors, among which the position in the settlement system relative to large cities and agglomeration centers is key. The relevance of the study is due to the need to analyze the position of small towns in the settlement system, primarily in relation to large agglomeration cores. In the context of increasing spatial polarization, it is of fundamental importance to identify patterns that determine the demographic dynamics of small towns, depending on the scale of the nearest large center and transport accessibility to it. The dominant trend of depopulation in most small towns is accompanied by the steady growth of a significant part of them, which indicates the complex nature of center-peripheral interactions and requires the use of modern analysis methods, including geoinformation technologies. International experience, especially in the light of the changes caused by the COVID-19 pandemic, demonstrates a structural shift in the spatial preferences of the population, creating new opportunities for the development of peripheral territories. The methodological basis of the study was a comprehensive GIS analysis, including spatial statistical methods and geoinformation modeling. To assess spatial interaction, the binary logistic regression method was used, and GIS tools were used to model the probability of demographic growth as a function of the scale of the central core and the distance to it. The conducted research revealed the fundamental patterns of the spatial organization of small towns in Russia in the context of agglomeration influence, demonstrating a clear center-peripheral influence on development. The revealed spatial structure is characterized by a multilevel organization with a regular alternation of growth and depression belts. Geoinformation modeling made it possible to determine critical distances with high accuracy and identify specific zones and thresholds.
This study aims to assess the accuracy of global satellite products used to determine sea surface temperature and chlorophyll-a concentration in the surface water layer, with a focus on the Arctic and Far Eastern seas of Russia. The analysis is based on data from the MODIS and VIIRS imaging systems, as well as integrated products from the Copernicus Marine Portal, which were compared with in situ measurements collected between 2018 and 2022 in the Kara, Okhotsk, and Pechora seas. To automate the comparison process, a specialized module was developed in QGIS, enabling the extraction of satellite data at field station points, followed by the calculation of the root mean square error (RMSE), coefficient of determination (R2), and characterization of discrepancies. The results revealed a systematic overestimation of satellite-derived chlorophyll-a concentrations: 68–93 % of satellite estimates exceeded the in situ measurements, particularly in coastal zones influenced by suspended organic matter. The lowest RMSE (1.63 mg/m3) was observed for MODIS/Terra data; however, no significant correlation between satellite and field data was found. For sea surface temperature, a general underestimation was noted (RMSE of 2.8°C), except for the Copernicus OSTIA product, which showed high agreement with field data (R2 = 0.81, RMSE = 1.7°C). Integrated Copernicus products, which combine data from multiple satellite platforms, exhibited mixed results: a relatively high error for chlorophyll-a (6.03 mg/m3) but the best accuracy for temperature among all analyzed parameters. Geographically, the highest errors were observed in shallow areas of the seas, likely due to the presence of suspended organic matter in the water.
The work is devoted to the research of the toponymic complex of the local territory according to maps and GIS data. The aim of the study is to identify patterns of formation and development of the toponymic microsystem based on the analysis of changes recorded in cartographic sources of different periods. The territory of the south-eastern part of the Ryazan District of the Ryazan Region is analyzed. The relevance of the work is dictated by modern urban processes that lead to changes in the toponymic system of large cities and their suburbs. Ignoring the laws of the system can lead to disruption of synchronous and diachronic toponymic connections. The novelty of the work lies in the study of an interesting complex of ancient Slavic and modern names, which has not previously been analyzed. System analysis ultimately makes it possible to establish the main features of any toponymic microsystem. Etymological, typological, cartographic methods are used, as well as materials from history and archeology. The study established the chronology of the system’s development. The toponymic landscape of the area began to take shape 800 years ago. The main toponyms were the names of the cities of Dyadkov, Lgov, Vyshgorod, Glebov, which arose at approximately the same time. Over the following centuries, a transformation of these toponyms took place due to changes in the status of settlements. Rural microtoponymy and toponymy of modern residential areas of the regional center were also formed. An indicator of the stability of a toponymic system is: a large body of toponyms, the preservation of toponymy of early chronological layers, a variety of types and types of toponyms, the development of microtoponyms, and the replenishment of the toponymic fund. The following basic patterns of the formation and development of the toponymic microcomplex have been identified: common geographical, historical, ethnic conditions, the presence of age, stability, synchronous and diachronic connections between individual layers and groups within one synchronous layer, variability, renewal. The toponymic microsystem, together with nature and architecture, creates the identity of the territory, which distinguishes it from other territories. This once again indicates the importance of studying the toponymy of individual areas. Maps and GIS allow us to record the state of a toponymic microsystem of a certain period, providing data for identifying and analyzing diachronic changes in this system by comparing maps from different periods.
Today, twenty types of cadasters are maintained in order to ensure a single, nationwide, comprehensive accounting and assessment of the natural and economic potential of the Republic of Uzbekistan and its individual regions. This article is aimed at improving geoinformation and cartographic technologies for creating an information database of the state cadastre of buildings and constructions in the unified system of state cadasters. Such improvements are crucial to fostering transparency and enabling more efficient property tax collection practices, which are essential for maintaining an accurate and up-to-date cadastral database. The need for state registration of rights to immovable property is growing. It is known that in order to conduct transactions involving immovable property, such as sale, inheritance, rent, gift, and other activities, the rights to land plots, structures, and constructions must first be registered with the governmental authority. The information gathered via state registration is utilized for land and property tax collection, among other uses. It should be mentioned that the preliminary data is generated as a consequence of assessing the quantitative, qualitative, and legal state of the item based on its registration. These data are produced using the principal data from the state cadastre of structures and constructions. According to research conducted in the research object, following the creation of the primary data, modifications are recorded on the basis of registration, if the owner of the property does not ask for additional data formation. This procedure is intended to take place every five years. It should be mentioned that after completing the activities associated with the objects, namely sale, inheritance, rent, gift, etc., most immovable property owners have been seen to transfer the rights to specific structures and constructions from the state register in a timely way. However, the fact that property owners construct new buildings and constructions based on their needs without architectural designs or consent from the appropriate body weakens the credibility and transparency of cadastral information. More specifically, the cadastral data is leading to inconsistencies with field survey data. To solve such difficulties, we realize the significance of creating state cadastre information on structures and constructions utilizing cutting-edge technologies.
This study examines the urbanization processes and the economic-geographic characteristics of housing infrastructure in Tashkent, Uzbekistan, from 2015 to 2024. As the capital of the Republic of Uzbekistan and one of Central Asia’s largest cities, Tashkent has undergone significant demographic and economic transformations in recent years. Over the nine years, the city’s population surged 28.2 % from 2 371 300 to 3 040 800. The population density is growing from 7 000 to 9 000 people per km2. This growth is driven by internal and external migration flows, a high birth rate (20–25 per 1 000 people), and economic reforms. The research employs various methods, including statistical analysis, cartographic modeling, Geographic Information Systems (GIS), and case study analysis. The escalation of housing prices and deficiencies in water supply, public transportation, and social services (e. g., schools and kindergartens) have intensified social inequalities. GIS-based analyses indicate that central districts (Shaykhontohur, Yakkasaray, Yunusobod) benefit from well-developed infrastructure, while peripheral areas (Sergeli, Yangihayot, Bektemir suffer from limited access to communal and transportation services. Construction of new residential complexes often fails to align with existing infrastructure capacities, resulting in water supply interruptions, traffic congestion, and environmental challenges. The study highlights the critical need for synchronized infrastructure development that accommodates demographic growth, environmentally sustainable construction practices, and regulated migration within urban planning frameworks. This research proposes evidence-based strategies to foster sustainable urbanization in Tashkent and aims to inform and enhance urban development policies. Looking ahead, comprehensive approaches addressing regional balance, infrastructure modernization, and the fulfillment of social needs will be paramount for the city’s sustainable growth.
This study investigates the various types of green spaces in Tashkent, analyzes their spatial distribution, and assesses the ecosystem services they provide. The extent of green space coverage across the city was quantified using the Normalized Difference Vegetation Index (NDVI). To evaluate the cooling efficiency of green spaces, a surface temperature map was generated by processing the red, near-infrared, and thermal infrared bands from Landsat-8 satellite imagery. The InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model was utilized to assess both the urban cooling effect and the flood mitigation capacity of green areas. The findings indicate that green spaces in multi-storey residential zones provide greater cooling and flood mitigation services than those in traditionally built neighborhoods. They also exhibit significantly higher cooling efficiency during the summer, with the maximum Heat Mitigation Index reaching 0.83. Furthermore, the flood mitigation potential of green spaces in Tashkent depends on the city’s river terrace formations. The terraces of the Chirchik River correspond to A, C, and D hydrological soil groups with varying infiltration rates. Green spaces on the floodplain and terrace I (A group) exhibit the highest infiltration and thus the greatest potential for reducing flood risks, whereas terraces II and III (C group) and IV and V (D group) show lower infiltration. Additionally, green spaces on terraces II and III (C group) have higher flood mitigation potential than those on terraces IV and V (D group).
The Pavlodar Region, located in the northeastern part of Kazakhstan, is an industrially and economically developed area endowed with substantial land resources. Due to the intensive exploitation of natural resources, low resilience to anthropogenic impacts, and the widespread manifestation of degradation processes, a comprehensive study of the region and environmental condition is highly relevant. The aim is to address issues of environmental protection and to develop strategies for sustainable land use. To provide a detailed characterization of the Pavlodar Region, a wide array of literary sources, analytical reference materials, and cartographic data were utilized, forming the basis of a GIS. This GIS includes parameters describing the state of natural and anthropogenic landscapes, as well as assessments of various degradation processes. It is used to analyze the region’s land resources, land use patterns, and the associated ecological risks, especially concerning soil cover. Natural conditions, the intensity of agricultural activity, and the environmental status of administrative units within the region were compared using unified, ranked scales. According to the proposed approach, the overall environmental situation and degree of land degradation across most of the region are assessed as unfavorable. The most critical conditions are observed in the Aktogay, Aksu (city), Pavlodar, Pavlodar (city) districts. Soil composition analysis indicates that nearly 70 % of the region’s soils belong to the valuable category of arable land. More than 36 % of dark chestnut soils—the most fertile in the region—are in a critical state, as well as over 15 % of medium chestnut (low-humus dark chestnut) soils, which are also widely used in agriculture. The developed GIS serves as an effective tool for the integrated analysis of cartographic and statistical data reflecting the region’s natural and socio-economic conditions, land use practices, and existing and potential anthropogenic impacts on the environment.
The study assesses the functionality of green infrastructure (GI) at cultural attractions through the example of five historical parks in Beijing: The Temple of Heaven, the Forbidden City, the Summer Palace, Beihai Park, and the Old Summer Palace. The relevance of the work lies in the need to balance cultural heritage preservation and ecological functions of such sites amid urbanization. The selected parks are unique case studies, combining UNESCO World Heritage status (or the highest national tourism category, AAAA) with their role as major GI elements, reflecting centuries-old traditions of Chinese garden art rooted in the harmony of nature and architecture. Their development dynamics capture both historical challenges (destruction during wars and revolutions) and modern trends (urban greening, green corridor projects), making them representative models for studying GI multifunctionality. The methodology includes three stages: GIS analysis (MSPA, visual and automated interpretation of high- and ultra-high-resolution satellite imagery from Sentinel-2 and Google Planet) to evaluate GI spatial structure, connectivity, and composition; field observations of green zone functions (recreation, sports, cultural-historical value); modeling the impact of cultural status on GI condition through a system of compensatory properties. Central parks provide up to 43 % of the GI in Beijing’s historic core, but their isolation limits citywide connectivity. Peripheral parks are integrated into the city’s green belt, balancing ecological and recreational roles. Cultural significance drives the adoption of eco-oriented solutions (green drainage, waste segregation) and high-quality maintenance, mitigating negative impacts of high visitor traffic. The study demonstrates that cultural attractions can act as drivers of GI development under adaptive management, offering a model for harmonizing ecological, recreational, and historical priorities. The scientific contribution includes a novel GI assessment algorithm integrating landscape metrics and social functions, as well as the concept of an “eco-cultural balance”, where historical value enhances ecological resilience.
In the context of rapid urbanization in major cities of Kazakhstan—such as Astana, Almaty, and Shymkent—the need for spatial analysis of the urban fringe has become increasingly pressing. These areas are characterized by pronounced socio-environmental heterogeneity, unstable land use patterns, and insufficient infrastructure provision. This study proposes a methodological framework for delineating the urban fringe based on the integration of geoinformation analysis and landscape metrics. The outer boundary of the fringe is defined as the intersection of the administrative boundary and the “real city” boundary, derived from nighttime light data (VIIRS) and built-up surface data (GHS-BUILT). To identify the inner boundary, the Shannon Diversity Index was calculated using GlobeLand30 land cover data within a 960 m moving window. The entire study area was aggregated into a regular hexagonal grid with cells of approximately 1 km2, enabling detailed spatial analysis of land use mosaic patterns. The results revealed a clear division into three territorial types: the city core, the urban fringe, and peripheral subcenters. Urban fringes occupy more than 80 % of the total area of cities studied, highlighting their significance for urban planning. The proposed methodology demonstrates both universality and applicability across flat and mountainous terrains, ensuring high accuracy and reproducibility of results. The findings can inform infrastructure optimization, land use management, and the development of sustainable urban development strategies. Future research will focus on a more in-depth analysis of the socio-economic and environmental characteristics of fringe areas, as well as on adapting the methodology to other cities with consideration of their specific contexts.
The organization of space (features of the settlement structure, the settlement system), being one of the qualitative characteristics of any culture, is not only closely related to the geographical features of the region, but also fully includes them. Therefore, any changes related to the landscape and climate naturally affect the features of the organization of space and the dynamics of changes in the settlement system. The main method is spatial analysis. At the current level of technology development, such work is carried out using GIS technologies, which include not only archaeological data, but also data from related natural science disciplines. This paper presents the results of research in the field of paleomedia reconstruction and their inclusion in the combined GIS of the northeastern Black Sea Region. This paper presents the results of research in the field of paleomedia reconstruction and their inclusion in the combined GIS of the northeastern Black Sea Region. To reconstruct the paleolandscape environment and climate, a complex of paleogeographic studies was carried out, including the study of Holocene terraces on the coast from the Mamai-Kale fortress (the westernmost point) to Ochamchira (the eastern point) and spore-pollen analysis. The conducted studies allowed us to identify micro-regional features of the paleoclimate for different parts of the coast based on the analysis of sedimentation processes. The first and most important result was the identification of a system of terraces of the Holocene period, reflecting not only the transgressive and regressive processes of the world ocean, but also the tectonic features of the region. Studies of the features in the structure of the formation of coastal terraces in different parts of the coast of northwestern Colchis have allowed us to identify two main types of sediments: sediments of shallow stagnant waterlogged bodies of lagoon-lake type and terraces with horizons of pebbles and gravelites, representing channel, delta, or floodplain alluvium with relative sorting of material, as well as unsorted outflows of mudflows. Summarizing the results obtained, it should be said that at the moment it has been possible to outline the evolution of the settlement system as a whole in large strokes. Two factors play a key role here: the altitude of the mountains and the wetlands of the area. The main settlements are being fixed, and new ones must be sought at altitudes from about 100 m to 500 m above sea level. In the higher altitude zone, settlements are more often of a cult or seasonal nature (shepherds’ camps). And coastal settlements are actively developing during periods of drier climate, when the coast is draining, but they are abandoned during wetter periods.
The study aims to assess the contribution of technogenic (grey infrastructure) and soil and vegetation cover (green infrastructure) to the formation of a comfortable environment in the southern part of Moscow. The relevance of the work is due to the lack of large-scale studies integrating the analysis of landscape sites taking into account technogenic transformations, despite their role as an urban environment. The work tested a comprehensive methodology combining the identification of landscape locations with an assessment of the state of their components, which allows us to identify the relationship between the morphology of development, the functionality of green areas and the comfort of living. The object of study was a 50 km2 polygon covering geomorphologically and urbanistically heterogeneous territories of the Central, Southern and South-Western districts of Moscow. The methods included a desk stage (analysis of remote sensing data, cartographic sources, including the Copernicus-10 digital elevation model and the General Plan of Moscow) and field studies with a point assessment of the characteristics of gray and green infrastructure. The results showed that the northern part of the polygon (floodplain terraces of the Moscow River) is characterized by an average degree of greenery with a relatively high quality of gray infrastructure, but the courtyards suffer from a deficit of green areas. The central zone (aquatic-glacial plains) demonstrates contrasts: new buildings have modern gray infrastructure, but minimal greenery, while the areas of Stalinist development combine the average quality of both components. The southern part (moraine plains) is distinguished by a high proportion of green spaces, but their condition is deteriorating due to litter and conflicts with man-made objects. It was found that old buildings (Khrushchev, Brezhnev) support more stable ecosystems due to self-seeding vegetation, while modern neighborhoods have predominantly decorative landscaping with a low environment-forming function and a high proportion of sealed surfaces of courtyard spaces.
The international community has been concerned about climate change and the increasing anthropogenic impact since the last century, however, effective methods to minimize the negative impact have not yet been developed. The article is devoted to the development of a methodology for geoinformation monitoring of the spatial distribution of surface temperature fields in the resort city of Pyatigorsk of the Caucasian Mineral Waters and the identification of correlations between the fields of surface temperature and urban and environmental indicators (landscaping and built-up areas). The aim of the study is to assess the influence of anthropogenic factors on the formation of microclimatic conditions of the urban environment and identify the most vulnerable areas in terms of thermal comfort of the population. Maps of the spatial dynamics of surface temperature anomalies have been obtained and patterns of changes in the temperature regimes of urban areas depending on the level of urbanization and the degree of landscaping have been identified. The results of the study are important for optimizing urban planning policy, improving the quality of life of citizens and preserving the unique natural potential of the Caucasus Mineral Waters Region. The methods of remote sensing of the Earth, cartographic analysis and statistical data processing are used. Modern remote sensing technologies simplify the analysis of indicators by providing objective data and reducing the resource intensity of ongoing research. Despite the established relatively low statistical reliability of the revealed correlations between the temperature of the earth’s surface and the levels of landscaping and built-up, the use of geoinformation monitoring methods confirms the expediency due to the availability of remote satellite images that provide a detailed study of individual fragments of urban areas and record the dynamics of spatial reorganization of green areas, their transformation into built-up areas within a given chronological period.
