Man-made Features Research Articles

Land Use and Land Cover Change Detection Using Remote Sensing in the Kal River Basin, Raigad District, Maharashtra, India

Land use and land cover (LULC) are distinct yet interrelated concepts that describe the characteristics and utilization of land. Land cover refers to the physical surface, such as vegetation, water bodies, or man-made features, while land use denotes the purpose of land utilization. Changes in LULC significantly impact water resources, making it a critical component in water resource studies. This study aims to detect changes in LULC over a five-year period (2017–2021) in the Kal River basin, a sub-basin of the Savitri River in Maharashtra, India. Sentinel-2 satellite imagery with a 10 m resolution was used, and the supervised classification method, specifically Maximum Likelihood Classification (MLC), was applied to classify LULC into six categories: cropland, bare ground, built-up areas, trees, rangeland, and water bodies. The results show that in 2017, the areas under cropland, tree cover, bare ground, built-up areas, and water bodies were 35.20 km², 187.61 km², 0.133 km², 7.77 km², and 1.89 km² respectively. By 2021, cropland, tree cover and bare ground decreased by 3.82%, 4.85%, and 0.01% respectively while water bodies, rangeland, and built-up areas increased by 0.02%, 8.34%, and 0.32% respectively. The overall accuracy of LULC classification was 77% for 2017 and 91% for 2021 with validation using the Kappa coefficient indicating good to excellent accuracy. This study highlights the importance of monitoring LULC changes for understanding the impacts of human activities and climate on watershed development and water resource management. Such analysis provides valuable insights for decision-makers to plan for sustainable development, land conservation and environmental management, ensuring balanced growth while protecting natural resources in the Kal River basin.

Harnessing geography: How Odisha's natural and man-made features mitigate cyclone impacts

Harnessing geography: How Odisha's natural and man-made features mitigate cyclone impacts

BHOO-MI – BHOONIDHI META INTELLIGENCE

Presently satellite data products are supplied to the users in various formats and with required meta data associated to it. In general, this Meta data contains the latitude/longitude information of the area covered. The utilization of satellite imagery in diverse fields necessities efficient methods to add value to the core images. In this research work, we designed a comprehensive methodology to design a system which provides the intelligence to the basic data product by adding various geographic features over that area. Both natural and manmade geographic features were considered in study. The features include post offices, monuments, airports, museums, hospitals, educational institutes (NITs & IITs) etc. All these features are extracted and preserved as a centralized repository/database. Leveraging a combination of Python programming, web scraping techniques, and advanced geospatial libraries such as Geopandas and Shapely, our system undertakes a multi-step approach. Initially, the system reads the metadata of the satellite image to obtain corner latitude and longitude coordinates. Then the system identifies and extracts relevant feature data. These feature’s meta information is then compiled into a shapefile, providing a comprehensive overview of the features present within the satellite image. This shapefile serves as a valuable resource for further analysis and decision- making in applications such as environmental monitoring, urban planning, and disaster response. Keywords: GIS, Intelligent Satellite Image, Satellite-Image, Data-Preprocessing in Band Data, Point-Data, Geospatial libraries

Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model’s Generalizability in Permafrost Mapping

This paper assesses trending AI foundation models, especially emerging computer vision foundation models and their performance in natural landscape feature segmentation. While the term foundation model has quickly garnered interest from the geospatial domain, its definition remains vague. Hence, this paper will first introduce AI foundation models and their defining characteristics. Built upon the tremendous success achieved by Large Language Models (LLMs) as the foundation models for language tasks, this paper discusses the challenges of building foundation models for geospatial artificial intelligence (GeoAI) vision tasks. To evaluate the performance of large AI vision models, especially Meta’s Segment Anything Model (SAM), we implemented different instance segmentation pipelines that minimize the changes to SAM to leverage its power as a foundation model. A series of prompt strategies were developed to test SAM’s performance regarding its theoretical upper bound of predictive accuracy, zero-shot performance, and domain adaptability through fine-tuning. The analysis used two permafrost feature datasets, ice-wedge polygons and retrogressive thaw slumps because (1) these landform features are more challenging to segment than man-made features due to their complicated formation mechanisms, diverse forms, and vague boundaries; (2) their presence and changes are important indicators for Arctic warming and climate change. The results show that although promising, SAM still has room for improvement to support AI-augmented terrain mapping. The spatial and domain generalizability of this finding is further validated using a more general dataset EuroCrops for agricultural field mapping. Finally, we discuss future research directions that strengthen SAM’s applicability in challenging geospatial domains.

SPATIAL DISTRIBUTION OF TOPONYMY IN KARST AREAS GIRITONTRO

<span>Every object in the form of an earth element or man-made feature has a name with various origins. The origins of place names can be categorized based on geography, history, folklore/culture and language so that their spatial distribution can be known. This research explores the spatial distribution of the origins of naming earth elements and man-made features in the Giritontro District. The study begins by identifying the aspects of the earth's appearance and man-made features and then finding the meaning of naming each identified element. Data collection was carried out using in-depth interviews. Determining the sources used the snowball sampling method. The results of the research show that the toponymically identified objects are dominated by man-made features with a spatial distribution of 92% in Giritontro Village, 72% in Pucanganom Village, 52% in Tlogosari Village and 78% in Jatirejo Village. The remainder is dominated by the earth's elements of the Karst Area, such as caves, hills, and springs, with a spatial distribution of Bayemharjo Village at 63%, Ngargojarjo at 53% and Tlogoharjo Village at 66%. Meanwhile, the spatial distribution of toponymy in Giritontro District, whose origin is dominated by language, is known to be spread across Giritontro District with a percentage of 60%. Apart from that, the toponymy found was predominantly geographically dispersed across Pucanganom Village with a portion of 40%, Tlogosari Village at 60%, Jatirejo Village at 61%, Bayemharjo Village at 61%, Ngargoharjo Village at 57% and Tlogoharjo Village 46%. The geographical conditions referred to are those attached to the object or the object's proximity to geographical things (associations) which are dominant in the Karst Area. </span>

Scenario development for safety assessment in deep geologic disposal of high-level radioactive waste and spent nuclear fuel: A review.

Radiation and radioactive substances result in the production of radioactive wastes which require safe management and disposal to avoid risks to human health and the environment. To ensure permanent safe disposal, the performance of a deep geological repository for radioactive waste is assessed against internationally agreed risk-based standards. Assessing postclosure safety of the future system's evolution includes screening of features, events, and processes (FEPs) relevant to the situation, their subsequent development into scenarios, and finally the development and execution of safety assessment (SA) models. Global FEP catalogs describe important natural and man-made repository system features and identify events and processes that may affect these features into the future. By combining FEPs, many of which are uncertain, different possible future system evolution scenarios are derived. Repository licensing should consider both the reference or "base" evolution as well as alternative futures that may lead to radiation release, pollution, or exposures. Scenarios are used to derive and consider both base and alternative evolutions, often through production of scenario-specific SA models and the recombination of their results into an assessment of the risk of harm. While the FEP-based scenario development process outlined here has evolved somewhat since its development in the 1980s, the fundamental ideas remain unchanged. A spectrum of common approaches is given here (e.g., bottom-up vs. top-down scenario development, probabilistic vs. bounding handling of uncertainty), related to how individual numerical models for possible futures are converted into a determination as to whether the system is safe (i.e., how aleatoric uncertainty and scenarios are integrated through bounding or Monte Carlo approaches).

Mapping socioeconomic conditions using satellite imagery: A computer vision approach for developing countries

Pakistan is a developing country with more than a quarter of its population living under the poverty line. Data relating to the socioeconomic conditions of the population is scarce and sporadic. Government, NGOs, and other interna- tional organizations perform door-to-door surveys to collect data, but these can be expensive and time-consuming to conduct. Currently, statistics about poverty in Pakistan exist only as estimates from field surveys, which are often unofficial and limited. This lack of reliable information leads to ineffective policy decisions. This is one of the biggest challenges in fighting issues such as poverty. Reliable information is thus needed for the unified and concerted direction of development activities. This thesis aims to build a computer vision system that can automat- ically extract information about poverty from publicly available high-resolution satellite imagery. The proposed system output is heat maps indicating poverty and development levels. These heat maps can be overlaid on digital maps for easy visualization. We propose to use transfer learning techniques to extract indica- tors such as geographical and man-made structural features from high-resolution satellite imagery. The trained model learns to filter and distinguish between vari- ous terrains and man-made features, such as highways, buildings, and farmlands. We show that these learned traits are quite useful for mapping socioeconomic variables and even come close to matching the prediction data with field survey data. For a developing country like Pakistan, this thesis is useful because the approach uses publicly available data and is a scalable and inexpensive alterna- tive to traditional surveys. The results from our thesis can aid policymakers and NGOs in distributing their funds to areas that are most deserving and enacting and assessing policies more effectively.

Looking back to move forward: Restoring vegetated canals to meet missing Water Framework Directive goals in agricultural basins

Nitrate pollution and eutrophication remain pressing issues in Europe regarding the quality of aquatic ecosystems and the safety of drinking water. Achieving water quality goals under the Water Framework Directive (WFD) has proven to be particularly challenging in agricultural catchments, where high nitrate concentrations are the main reason for the failure of many water bodies to meet a good ecological status. Canals and ditches are common man-made features of irrigated and drained landscapes and, when vegetated, have recently been identified as denitrification hotspots.By combining experimental data and GIS-based upscaling estimation, the potential capacity of the canal network to reduce nitrate loads was quantified in several scenarios differing in the level of nitrate pollution and in the extent of the canal network length where conservative management practices are implemented. The analysis was carried out in the irrigated lowlands of the Po River basin, which is the largest hydrographic system in Italy and a global hotspot for nitrogen inputs and eutrophication.Scenario simulations showed that maintaining aquatic vegetation in at least 25 % of the canal network length, selecting sites with high nitrate availability (>2.4 mg N L−1), would promote a greater potential for permanent N removal. The increased denitrification capacity would meet the load reduction target required to achieve a WFD good ecological status in waters draining into the Adriatic Sea during the spring-summer months, when the eutrophication risk is higher. Promoting denitrification in the canal network by postponing the mowing of in-stream vegetation to the end of the growing season could be an effective mitigation strategy to improve water quality in agricultural basins and contribute to achieving the WFD goals.

Multi-temporal insar analysis of ground displacement in solotvyno

AbstractRecent studies showed a significant peak of the salt contamination in the Tisza River that exceeded ten times over the average level. The document summarizes the works performed on the investigation of ground displacement using multi-temporal satellite radar interferometry technique in Solotvyno mine located in Tiachiv region. Multi-temporal InSAR aims to identify coherent radar targets exhibiting high phase stability over the entire observation period and derives point data with locations corresponding mainly to the point-wise, man-made features. The middle area with no persecuted targets may correspond to the substantial physical changes of the surface caused by activities like mining or tunneling, adding, or removing structures or their components, and motion perceptible in one pixel.

Systematization of industrial technogenic risks at mining enterprises

Research objective is to develop a general approach to systematizing the signs of mining territories, natural and man-made features safety. Research relevance is due to the need to ensure the safety of economic activity in the territory of mining. Methods of research. Subsoil use implies taking into account multiple factors that lead to the risk of decisions implementation. Risk is considered as a potential, numerically estimated probability of the unfavorable events (situations), their consequences in the form of accidents, human casualties, losses, damages, material losses, etc. Risk is a quantitative assessment of the hazards characterizing a situation with uncertain outcome and obligatory manifestation of unfavorable consequences. It is advisable to assess the safety status of any mining enterprise site by a number of indicators that characterize the system’s resilience to negative impacts caused by infrastructural, natural, geological, technological, economic and financial factors. The risk situation caused by statistical processes is associated with accompanying conditions: the presence of uncertainty, the need for an alternative choice, and the possibility of accepted options (alternatives) probabilistic evaluation. Negative phenomena in subsoil use are manifested in the form of deformation of pit walls and dumps, collapse of an individual or a group of pit benches, destruction of transport lines and power supply utilities, rockfall, beneficiation process flow deviations from the designed one, violations of man-made features and the ecological and biological environment, which should be interpreted as man-made disasters of an industrial nature. Results. The classification of risks as a multidimensional category is justified by the factors (causes) of occurrence, the driving force of which generates a negative process and determines its characteristics or individual features. Conclusions. The systematization of various risks based on infrastructural, mining-geological, process flow and environmental factors ensures, at the initial stage of risk formation, the determination of their characteristics and the development of a system of management measures to ensure the sustainable functioning of a mining enterprise.

ML based approach for inverting penetration depth of SAR signals over large desert areas

Penetration depth of synthetic aperture radar (SAR) signals over a desert is a key parameter to understand the internal properties of the desert. Existing approaches for obtaining the penetration depth require good quality interferometric SAR (InSAR) data of very short temporal and long spatial baselines. Such data are often difficult to obtain in a highly dynamic desert. We propose a new machine learning (ML) based approach for inverting penetration depth of SAR signals over large desert areas by jointly using InSAR, polarimetric SAR (PolSAR) and optical remote sensing data. First, SAR scattering parameters and terrain properties are determined based on PolSAR and Landsat 5 TM multispectral data and a DEM. The penetration depth of SAR signals over a small desert area is obtained based on methods such as using a scattering model. A random forest model is then used to establish the relationship between the SAR scattering parameters and site features, and the penetration depth, and then is used to derive the penetration depth over a large desert area. The approach is applied to calculate the penetration depth of ALOS-1 PALSAR L-band signals for a large part of the Kufra Basin, an area of about 60, 000 km2. The penetration depths of four types of typical landforms in area (i.e., sandy plains, paleochannels, rocks and man-made features) are discussed in relation to the geological and climatic conditions. The average signal penetration depths over the paleochannels, sandy plains, and rocks and man-made features are 2.84 m, 1.97 m, 1.21 m, respectively. It is found that the backscattering coefficient, dielectric constant, surface roughness and mineral composition are the most important parameters in determining the signal penetration depths. An interesting point is that the existence of hematite in the sand can increase the dielectric dissipation of the sand medium and shorten the signal penetration depth.

Noise Reduction of Aeromagnetic Data Using Artificial Neural Network

The high-frequency content of high-resolution aeromagnetic data is of particular interest to geophysic ists to identify mineral deposits, shallow faults, and dikes. However, high-resolution aeromagnetic data is contaminated by cultural noise generated from aircraft and man-made features. The culture noise must be removed before starting the interpretation process. Manual techniques are more selective of the noise; however slower and more expensive because they require considerable hands-on interaction. The present study develops a novel method for detecting and removing the culture noise from aeromagnetic data based on an artificial neural network (ANN) in an automatic way and comparing the results with a conventional algorithm using the nonlinear filter. The proposed method is tested using a theoretical example that combine a magnetic anomaly due to a dyke with three sources of cultural noise, besides using a practical example to increase the number of training pattern. The network is trained based on the backpropagation training function, where the algorithm updates the weight and bias states as per the Levenberg–Marquardt optimization. The optimization is reached during the training and validation process after 3,000 iterations. The correlation coefficient ( R) is utilized along with the mean squared error (MSE) as performance indices of the ANN. The ANN demonstrates the capability to detect the spiky data based on the optimal weights, thus allowing for removing and replacing them with clean data using the piecewise cubic Hermite interpolating polynomial (PCHIP) function. The practical utility of the two-method is discussed using high-resolution aeromagnetic data from the Tushka area located in the southwestern desert of Egypt. Comparing the denoising results using the two methods shows that the current approach is more effective in processing and more closely recovering the original magnetic data.

Evaluating the role of preferential pathways in exacerbating vapour intrusion risks

Vapour intrusion (VI) has been garnering more attention in the research field in the past few decades owing to its associated health risks. Many field studies have been conducted to understand the process of vapour migration from the source to indoor air and the factors affecting it. This research project primarily concentrated on the role of highly permeable backfill materials like sand and gravel used as bedding and embedment for utility lines. These can function as preferential pathways for vapour migration in the vadose zone. Extensive laboratory investigations were carried out over 13 days using two large two-dimensional (2-D) columns, one with preferential pathway and one without preferential pathway, to investigate the natural attenuation process and the role of preferential pathways in VI. The presence of preferential pathway has a role in determining soil gas vapour distribution in the vadose zone. A notable increase in vapour concentrations was observed in the top layer of the column with preferential pathway compared to the column with no preferential pathway. This was due to enhanced distribution of contaminant vapours along the column facilitated by the preferential pathway. An increase in concentration was observed in the column with preferential pathway throughout compared to the column with no preferential pathway, confirming that the presence of natural or man-made drainage features in the sun-surface can influence the distribution of contaminants throughout a site. This research project generates a better understanding of preferential pathways and recommends taking into account the role of highly permeable backfill materials when developing CSM and VI health risks assessments. In this way the strategic priorities for remediation projects will be successfully established.

Geographical Names Study of Nagari, a Local Customary-Based Community Unit in Agam Regency, Indonesia

Nagari names in Agam Regency are lacking historical record despite being a fundamental spatial information. Preliminary research has revealed inconsistencies in nagari name records, even in official government documents. This paper conducts an analysis of nagari names within Agam Regency, West Sumatra Province, Indonesia. Geographical names depict both the natural landscape and human activities, including their interaction with the environment [1], and Agam Regency spans from sea level to 2891 meters, featuring diverse landscapes, while the formation of nagari is deeply rooted in local customary law. This raises a question: what are nagari names in Agam Regency, and what do they signify?. Therefore, the objectives are: 1) establishing a digital nagari name database for Agam Regency, and 2) analysing geographical names based on linguistic and historical meanings. Primary methods used are interviews and literature studies. Approximately 52.44% of names are related to man-made features, human activities, and interactions, while others derive from natural features or a combination of both. Nagari names were found to be clustered around Bukittinggi and Lubuk Basung, historically significant regions. This study contributes to the preservation of nagari names in Agam Regency, and the digital database holds potential for further spatial analyses.

Regional Disparities in the Level of Economic Development in Nashik District: A Geographical Analysis

The present investigation was studying the regional disparities in level of economic development of Nashik district a geographical analysis. It was based on secondary data collected from different government organizations and in government reports. The data covered 2021-22. All the sectors of economic development indicators, cropping intensity, irrigation intensity, area under crops, electricity usage, working population, road distances, percentage of BPL family, were considered for this study. The Z score method was applied in analysing the measurement of economic development. The studied regional diversity which was found in economic development in the study region. High development was found in Nashik, Malegoan, Niphad and Baglan.tahsil while moderate economic development was recorded in Chandwad, Dindori, Sinnar and Yeola tahsils. Surgana, Kalwan, Deola, Nandgoan, Peint, Triembak and Igatpuri tahsil have recorded the lowest economic development. In comparison to other regions, Thus, physical features like topography, soil, rainfall, forest cover and manmade features like concentration of tribal population, percentage working population, crop and irrigation intensity were affected by uneven economic development in this study region. The present paper gave the geographical analysis of economic development in Nashik district during the period of 2021-22.

Transformation of ecological-resource and ecological-geochemical functions of the lithosphere within the Stary Oskol–Gubkin mining district of the Kursk Magnetic Anomaly

The impact of mining production on the natural environment shows itself in many ways: through changes in the chemical and mechanical composition of the atmosphere, deformation of the earth’s surface, activation of exogenous geomorphological processes, violation of hydrological regime, surface water and groundwater alteration, degradation of soil and vegetation cover, disruption of functioning (vital activity) of living organisms—from bacteria to humans. The purpose of this work was to assess the main trends of transformation of the ecological-resource and ecological-geochemical functions of the lithosphere within the Stary Oskol–Gubkin mining area of the Kursk Magnetic Anomaly. This area is a key site for such research in the central part of Russia, which is due to its natural and manmade features: the initial high quality of the natural environment, the high population density—36 people / km2, and the extremely high level of induced load as a result of the mineral mining and processing activities. The research methods included field observations, as well as soil sampling at 12 key sites and at three main rivers of the district. The ecological and geochemical studies were carried out using the quantitative atomic spectral analysis. In the process of research, the tendency of significant alkalinization of soils and surface waters was revealed to exceed background values by 30–50%. Extraction and processing of iron ore has led to a significant degradation of the ecological and resource function, which is manifested in the removal of soil cover over the areas of tens of km2. The main polluting elements are indicated, including Zn, Pb, Mo, Co, Cr, B, Cu. The trend of transformation of the macro- and mesocomponent composition of surface waters was recorded. The content of calcium, sodium, chlorides exceeds the similar indicators in other rivers by 2 to 10 times, and this excess in terms of the content of sulfates is 70 times.

Terrain analysis for environmental sustainability in Taraba Central Senatorial Districts, North-East, Nigeria

Terrain analysis is the process of analyzing and interpreting man-made and natural features on the earth surface, for the assessment of the topography, environmental hazards, livelihood/human activities and infrastructural developments which include; suitability studies for agricultural, industrial, residential and transportation development, assessment of landuse/landcover (LULC), forestry management, military operations, soil erosion estimation and vegetation/ecology. Remotely sensed data (Digital Elevation Models and Landsat 8 image of 2021) were analyzed using Geographical Information System (GIS) techniques to assess the topography, drainage, vegetation, geology and soils of the study area for sustainable development. The result clearly revealed the location, extent and nature of the topography, the mountain ranges, Mambilla Plateau, valleys and the plains were conspicuously shown in different dimensions. The topography of the area is heterogeneous consisting of plains, mountains/highlands and the Mambilla Plateau. The plains could be utilized for agricultural (rain fed and irrigation), industrial, grazing and other activities, but are prone to flood hazard, while the mountains/highlands/plateau could be explored for transhumance, mineral resources, hydro-electricity, communication facilities and military operations. The mountain ranges and plateau were however vulnerable to soil erosion and landslides. The generated slope, depressions, aspect and LULC all revealed the nature of the area which can also be assessed for various environmental monitoring and management. It was recommended that, for sustainable planning and development on land, terrain analysis is necessary especially for suitability studies, natural resources exploration and environmental hazards assessments.

Managing urban riverscapes: An assessment framework to integrate social-ecological values and physical processes

The services that rivers provide and how they affect the landscape plays a dominate role in urban planning and development. Urban riverscapes, which consist of stream channels, their floodplains, biotic communities, and manmade features, are complex social-ecological and hydrogeomorphic systems. Yet, despite recognition of their place and value, rivers are often degraded in urban settings. Successfully managing urban riverscapes requires improved methods to assess them and to more effectively link stressors to values, and to incorporate these considerations in planning. Assessment of urban riverscapes’ physical condition and function—a hydrogeomorphic assessment—is necessary to make these links, and inform more appropriate management strategies for sustainable and valued riverscape systems. The framework and methods used for such an assessment should be appropriate to the urban context, insofar as they are applicable to a range of streams from lightly degraded to highly utilized or constructed. Above all, the framework must prioritize the connection of human communities to riverscapes. In this article, we outline a framework for urban riverscape assessment which considers four facets of urban riverscapes: human values, hydrology, geomorphology, and ecology. The four facets, assessed across multiple nested scales, provide a flexible basis for context-driven hydrogeomorphic assessment, which is vital to informing better planning and management of urban riverscapes. The framework can be integrated with other facets (e.g. geochemical, aquatic ecology) depending on the scope of the assessment. By linking intrinsic, relational, and use-based values to physical conditions, watershed managers can select relevant and measurable indicators that directly inform interventions in the riverscape, catchment, or urban zones to improve riverscape function and urban vitality through planning mechanisms. This assessment framework facilitates dialogue between managers, practitioners, scientists, and the community; enabling technical and non-technical inputs to the development of assessment criteria, and a shared vision to inform targets and goals.

Monitoring Subsidence over the Planned Jakarta–Bandung (Indonesia) High-Speed Railway Using Sentinel-1 Multi-Temporal InSAR Data

Investigation of subsidence situations is important for the design of railway lines. Traditional geological investigations are expensive. Multi-temporal InSAR (MT-InSAR) analysis has shown great potential for detecting subsidence areas along large-scale manmade linear features (LMLFs). The disadvantage of applying high-resolution SAR data such as that from TerraSAR-X and COSMO-SkyMed data is the high cost. By contrast, the free and open data from Sentinel-1 A/B offer an unprecedented opportunity for InSAR applications. Despite these advantages, research investigating the potential for monitoring subsidence along LMSFs using multi-temporal Sentinel-1 InSAR data at the design stage of LMSFs is limited. This paper explores the monitoring ability of MT-InSAR analysis with Sentinel-1 A/B multi-temporal data in an experiment along the planned Jakarta-Bandung high-speed railway in Bandung, Indonesia. Subsidence patterns along the route of the planned high-speed railway were analyzed in detail. By means of validation using 12 leveling points, the root mean square error (RMSE) of the average displacement velocity that was obtained from the MT-InSAR results was found to be 10.31 mm/yr. This paper demonstrates the potential of Sentinel-1 multi-temporal INSAR data to detect potential subsidence areas along planned LMLFs (e.g., the planned high-speed railway that is the focus of this study), serving as a reference for further planning of monitoring subsidence over planned LMLFs.

Наступление нового года по народным календарям таджиков

The article is devoted to the issues of the traditional calendar of the Tajik people. The purpose of the article is to consider the traditional ways of determining the onset of seasons and months among mountain Tajiks based on the use of the method of theoretical analysis. It was revealed that the main ways to determine the onset of the new year were: calculation according to the Iranian solar calendar (the entry of the sun into the constellation Aries); calendar «the sun in man» (the arrival of the sun in the sign of the «heart»); observing the appearance of stars in a certain place; reaching the shade from the sun peaks, rocks and stones; sunrise or sunset behind the sign (behind peaks, rocks, cracks); the appearance of sunlight through cracks (windows, cracks, stones with holes); phenological or behavioral observations of animals, as well as the growth of spring plants and flowers (wagtails, storks, swallows, partridges, cats, beetles). In conclusion, it is concluded that in the past, in different mountainous regions, the Tajiks had their own calendars and calendars based on observations of the cycle of the Sun and Moon, planets and stars; on the perception of natural and man-made features – for example, the fall of shadows on objects at certain points, the migration of animals and birds, and the behavior of animals. Experience and observations were passed down from generation to generation, some natural patterns were discovered and various calendars were compiled. However, along with the introduction of the lunar and solar calendars, and later the Gregorian calendar, vernacular calendars survived until the mid-twentieth century, and some of them even survive to this day.