Terrain Types Research Articles

Enhancing Autonomous Vehicle Navigation in Complex Environment With Semantic Proto‐Reinforcement Learning

ABSTRACTDespite great progress in autonomous vehicle (AV) navigation, the technical challenges within this space are still considerable when it comes to successful integration of AVs into complex real‐world environments. To tackle these challenges, this paper presents a new semantic proto‐reinforcement learning (SP‐RL) method for dynamic path planning and real‐time obstacle avoidance of an autonomous car that can be adapted to various weather conditions in localization‐deficient environments, while predicting the human intentions of different shapes on road. This approach seeks to improve navigation capability of AV in dynamic and unstructured environments, as well as to address real‐time detection and avoidance response for obstacles more promptly while being able to adapt its decision‐making system based on weather condition by using the semantic graph network (SGN) within segmentation process therefore enhanced version configured with prototype‐based reinforcement learning (PRL). This innovation is new competitive edge compared previous existing approaches. Dynamic SGN is used to segment challenging 3D and free space environments, so that the AV can comprehend highly unintuitive areas like parking lots, construction site conditionals, or off‐road scenarios. At the same time, PRL is used to help real‐time decision‐making so the AV can quickly and precisely respond unexpected obstacles or changing environments. This approach is confirmed to be effective by extensive testing in the CARLA simulation environment, showing substantial improvement of AV navigation capability. This work demonstrates an exciting step towards solving the most fundamental problems faced by autonomous vehicles and could help to ensure that future AV systems are safer, more robust, and adaptable than current ones. It is appliable for urban areas which represent high volumes of pedestrians and vehicles, industrial sites with changing conditions that may be unpredictable at times or the challenging off‐road areas in rural geographies where typical terrains are rough, uneven, rugged yet not well‐structured. The model is robust to diverse weather conditions that make AV operations more reliable and safer. The model was tested on root mean square error (RMSE), computational time, no crash, obstacles avoidance, and success rate obtaining overall 98%.

Effects of the Northeast Monsoon on Different Terrain of the Taipei Basin and Lanyang Plain in Taiwan

The Taipei Basin (TPB) and the Lanyang Plain (LYP) are geographically similar, both situated in northern Taiwan. However, significant differences in heat transfer processes arise between the two regions due to local terrain influences under the Northeast Monsoon. Precipitation patterns in the TPB and LYP, especially during the case study of 26 November 2021, differ markedly due to the distinctive dustpan-shaped terrain of the LYP. Our study, based on the WRF model, reveals that while both the TPB and LYP are characterized by downward cold air transfer, the TPB exhibits stronger atmospheric boundary layer mixing and a higher mixing layer height compared to the LYP. Turbulent kinetic energy (TKE) in the TPB is higher during the morning and evening, while vertical heat flux is more pronounced in the LYP. The average sensible heat flux is greater in the TPB, whereas latent heat flux is higher in the LYP. In addition, the amount of water vapor transported into the LYP by the Northeast Monsoon is greater than in the TPB. In the TPB, the wind field, influenced by the terrain, shifts predominantly from northeast to northeasterly and southeasterly. However, upon entering the LYP, the same environmental wind field is affected by the dustpan-shaped terrain, resulting in a counterclockwise near-surface wind pattern. The wind field transitions from northeasterly in the north to westerly, southwesterly, or northwesterly in the south. This difference in wind field causes precipitation in the TPB to be confined mainly to the windward side of the mountainous areas whereas, in the LYP, precipitation occurs both on the windward side and, more abundantly, in the plains. The effect of different types of terrain under the Northeast Monsoon is quite obvious.

Preface to the Proceedings of the 12th Mountain Cartography Workshop, Snow Mountain Ranch, Colorado, April 11–15, 2023

Abstract. The 12th ICA Mountain Cartography Workshop, organized by the International Cartographic Association (ICA)’s Commission on Mountain Cartography (CMC), was held April 11–15, 2023 in Colorado’s Rocky Mountains. Our workshops are usually held biennially, alternating with the International Cartographic Conferences (ICC). This year, however, the workshop was out of sequence due to the COVID-19 pandemic. The workshop, originally scheduled for April 2020, was first rescheduled for April 2022, and then again for April 2023 in response to shifting pandemic conditions. By 2023, pandemic-related travel restrictions had eased and CMC members were eager to once again meet in person. Our successful gathering this year thus concluded the five years of planning that began immediately after the 2018 Hvar, Croatia workshop. The goal of Mountain Cartography Workshops is to bring together cartographers, geographers, and others in a relaxed and beautiful mountain setting to share new developments in cartography, design, and spatial analysis related to mountain environments. Since our first workshop in 1998, the range of presentations has diversified considerably. Although the classic “Swiss-style” cartography of alpine peaks typified by the work of the late Eduard Imhof is still very important, other topics are now enthusiastically embraced. The understanding of what counts as “mountain cartography” has expanded to include every type of irregular terrain—from karst, to canyons, to hidden features on the seafloor, and even to the extraterrestrial. In these proceedings you will find contributions from academic cartographers, freelancers, government mapmakers, historians, journalists, researchers, and software developers. The breadth of contributions reinforces our contention that mountain cartography is a “big tent” discipline. The 2023 workshop had 51 participants from Austria, France, New Zealand, Norway, Portugal, Romania, Russia, Slovenia, Switzerland, and the United States. The theme was “People, Maps, and Mountains” in order to focus on the importance of using cartography to better understand human/mountain interactions—adventure, sustainable management, travel, recreation, etc. Altogether the workshop had 40 presentations in a variety of formats, including peer-reviewed papers, technical demonstrations, group discussions, posters, and short “avalanche talks” held in the evening. These proceedings were edited and assembled by Daniel Huffman. Our thanks go out to Daniel for this generous contribution of time, and also to the many people who anonymously reviewed papers. We hope that you find the following contents interesting and useful. We also encourage you to participate in future Mountain Cartography Workshops. The next one in Zakopane, Poland, is scheduled for April of 2024. But we have already begun planning for the 2026 workshop. Wherever it may be, we can guarantee an inspiring venue. The 2023 workshop program, CMC business meeting notes, and other information are available on the CMC website at www.mountaincartography.org.

Comparison of Deep Learning approaches in classification of lacial landforms

Glacial landforms, created by the continuous movements of glaciers over millennia, are crucial topics in geomorphological research. Their systematic analysis affords invaluable insights into past climatic oscillations and augments understanding of long-term climate change dynamics. The classification of these types of terrain traditionally depends on labor-intensive manual or semi-automated methods. However, the emergence of automated techniques driven by deep learning and neural networks holds promise for enhancing efficiency of terrain classification workflows. This study evaluated the effectiveness of Convolutional Neural Network (CNN) architectures, particularly Residual Neural Network (ResNet) and VGG in comparison with Vision Transformer (ViT) architecture in the glacial landform classification task. By using preprocessed input data from Digital Elevation Model (DEM) which covers regions such as the Lubawa Upland and Gardno-Leba Plain in Poland, as well as the Elise Glacier in Svalbard, Norway, comprehensive assessments of those methods were conducted. The final results highlight the unique ability of deep learning methods to accurately classify glacial landforms. Classification process presented in this study can be the efficient, repeatable and fast solution for automatic terrain classification.

Fish–Seascape Associations Within an Offshore Protected Area in the Arabian Gulf

ABSTRACTCoral reef ecosystems support high fish biodiversity through ecological interactions with structural complexity across multiple spatial scales including coral colony architecture and the surrounding seascape structure. In an era where the complexity of coral reef ecosystems is being diminished, understanding the importance of structural characteristics beyond single focal patches has the potential to better inform actions for protecting, restoring or creating habitat for reef‐associated species. A seascape ecology approach was applied to explore the associations between multiple scales of seascape structure and fish assemblage response variables within a small (49.6 km2) offshore no‐take MPA, Sir Bu Nair Island Protected Area, in Sharjah, United Arab Emirates. Fish–seascape associations were modelled with single regression trees. Both in situ and remote sensing–derived variables produced the best models with highest contributions from coral cover, amount of hard‐bottom habitat type and structural complexity of the seafloor terrain. Fish species richness was significantly higher where coral cover exceeded 35%. The hard‐bottom areas with coral supported diverse assemblages dominated by carnivorous and omnivorous fishes. The Sir Bu Nair Island Protected Area provides a critical refuge for threatened and regionally overexploited species including those with low resilience to fishing. The ecological success of this protected area is key to safeguarding regional marine biodiversity and recovering fish populations to enhance food security.

Accelerometer-Based Pavement Classification for Vehicle Dynamics Analysis Using Neural Networks

This research examines the influence of various pavement types on vehicle dynamics, specifically concentrating on vertical acceleration and its implications for unsprung mass, including the wheels and suspension system. The objective of this project was to categorize pavement types with accelerometer data, enabling a deeper comprehension of the impact of road surface conditions on vehicle stability, comfort, and mechanical stress. Two categorization methods were utilized: a neural network and a multinomial logistic regression model. Accelerometer data were gathered while a car navigated diverse terrain types, such as grates, potholes, and cobblestones. The neural network model exhibited exceptional performance, with 100% accuracy in categorizing all surface types, while the multinomial logistic regression model reached 97.14% accuracy. The neural network demonstrated exceptional efficacy in differentiating intricate surface types such as potholes and grates, surpassing the logistic regression model which had difficulties with these surfaces. These results underscore the neural network’s effectiveness in the real-time categorization of road surfaces, enhancing the comprehension of vehicle dynamics influenced by pavement conditions. Future studies must tackle the difficulty of identifying analogous surfaces by enhancing methodologies or integrating more data attributes for greater precision.

Assessment of digital elevation models accuracy for local geoid modeling

One of the critical factors influencing the accuracy of a local geoid model is the quality of the digital elevation model (DEM). A properly selected high-resolution DEM can significantly mitigate errors in geoid modeling, gravity anomaly processing, and topography and downward continuation correction. Purpose. Evaluating the accuracy of five global DEMs obtained from open sources to identify the most suitable model for creating a local geoid. Methodology. The vertical accuracy of the DEMs was assessed by comparing the heights between the DEM and control points across different types of terrain. The reference values are based on 344 ground benchmarks, where GNSS observations were performed with subsequent adjustment of coordinates and heights. The accuracy analysis involved calculating statistical indicators of the height differences between the GNSS data and the DEM data. Findings. The standard deviation assessment showed favorable values for the COPERNICUS and ALOS DEMs, followed by SRTM, ASTER, and ETOPO. In the mean absolute error calculations for mountainous areas, the ALOS model performed best, followed by COPERNICUS, SRTM, ASTER, and ETOPO. For other types of terrain, COPERNICUS demonstrated the best results in mean absolute error. Originality. This study distinguishes itself through the incorporation of advanced high-resolution DEMs, such as GLO30, providing a modern and thorough evaluation of DEM accuracy specifically for Kazakhstan. What is new is a detailed analysis of the impact of terrain features (plain, hilly, mountainous) on modeling accuracy. This approach advances beyond previous assessments, delivering new and significant insights into the performance of contemporary DEMs. Practice value. The practical value of the results obtained consists in issuing recommendations regarding the possibility of using the studied DEM for the regions of Kazakhstan which differ among themselves in terms of landscape characteristics. The findings indicate that COPERNICUS and ALOS DEMs are highly suitable for precise geoid modeling in southern Kazakhstan. These models can significantly improve the accuracy of local geoid models, benefiting applications in geospatial science and engineering.

How Does Tropical Cyclone‐Induced Remote Moisture Transport Affect Precipitation Over East Asia

AbstractAnalyzing tropical cyclone‐induced remote moisture transport clusters (TRCs) and their effects on precipitation is crucial for understanding precipitation formation and enhancing forecast precision. Prior research, primarily case‐based, did not fully grasp the nature of TRCs. Utilizing an objective TRC identification method, we categorized 65 TRC tracks in East Asia into five types and examined their traits and precipitation links. The findings indicate that the moisture transport height of TRCs varies due to multiple factors, with higher transport linked to the warm conveyor belt and lower transport attributed to Taiwan’s mountain range influencing low‐level moisture. The precipitation peak altitudes of TRCs at higher latitudes are greater, and their precipitation intensity is positively correlated with terrain type, especially coastlines. This study underscores the diversity in TRC characteristics and related precipitation, suggesting that future research should consider the directionality of TRC tracks.

Cartography of board games

ABSTRACT This paper focuses on the maps and map-like features in games. It discusses games with special topics or components, and it collects several titles of games named after a geographical object (city, land, etc.). Finally, it provides a proposed classification of the types of maps observed in the board games investigated. The popularity of board games has been increasing in an unstoppable way in the last years. Several modern board games work with maps or with map-like features. This article focuses on the maps and map-like features in games and attempts to classify the types of map in board games. The board games usually use maps on the main board. There are games that work with the map of the World in various map scales. These maps sometimes look as if they were old maps or they represented the present world. Some games' main board is similar to a map series or a classic atlas. Modular boards help to increase the replayability and give another experience game by game. Other games work with tiles (square, rectanglular or hexagonal shaped) representing a terrain type (forest, moorland, farmland, built in area, etc.). The tiles have to be placed next to each other, thereby the players can collect victory points. Fantasy maps depict fictional worlds: this helps the players to imagine better the fictional world and the characters. Fantasy maps often use partially orthogonal projection and partially bird's eye view.

Numerical Simulation Investigation of Wind Field Characteristics and Acceleration Effects over V-Shaped Hills

Wind energy resources play an important role in sustainable development, and the accelerating effect of wind has been found in V-shaped hills, which informs the siting of wind turbines in this type of terrain. The wind field around the V-shaped hill was simulated using the CFD method. The impact of wind angle, hill pinch angle, and the distance between the hills on the wind field around the V-shaped hill was investigated. Wind acceleration effects at specific locations were studied and analyzed, and these findings were compared with established codes. It was observed that the wind speed at the hill’s top under each wind angle is significantly higher compared to other areas. Additionally, the acceleration ratio at the top generally exhibits a decreasing trend with increasing height. If the wind angle is 15° and the pinch angle is greater than or equal to 15°, or if the distance between the hills is less than or equal to 50 m, the wake zone will gradually transition from two to one. The distance between the hills minimally affects the acceleration ratio at the mid-height and top of the hill. Several codes exhibit inconsistency in specifying acceleration effects in hilly terrain. The findings in this paper align most closely with the American code at the base of the hill. At the hill’s top, the American code is the lowest above 100 m, while the Chinese code is the highest below 100 m. The findings in this paper fall between those of the Japanese and Australian codes. The formulas for the variation in wind speed acceleration ratio at typical locations with respect to height and the angle between the hills are provided.

Assessing the Impact of Geospatial Susceptibility on the Rural Agricultural Landscapes of Village Settlements in Southwestern Nigeria

A theoretical framework for agricultural landscape pattern transitions in rural areas is proposed to fill the gap of current research with an empirical study in the Alabata farm settlement in Ogun State, Southwest Nigeria. Adopting the use of ArcGIS 10.8 and Surfer 27.3 the surface area and volume of the ground surface degraded and exposed to harsh weather conditions due to both natural and man-made anthropogenic activities causing runoffs and continuous soil erosion were calculated, which have affected agricultural production and sent some of the farmers packing, abandoning their farmlands. The farm settlement within the total sampled frame area of 1.50 km2 covers a total distance of 5.11 km. The sample frame was divided into 36 frames with similar ecological microclimates, topographical features, terrain, and soil types that fell into either of the two identified soil types: 1 and 2. The study involved the completion of a questionnaire onsite using three major criteria and only 23 farmers responded positively to the few questions as farmers who were either living on the farm or working as hired laborers on-site at the time of the visit. The transition characteristics of agricultural landscape patterns as represented in abandoned, degraded farmlands and orchards are analyzed from a local perspective.

A dataset of 0.05-degree leaf area index in China during 1983–2100 based on deep learning network

Leaf Area Index (LAI) is a critical parameter in terrestrial ecosystems, with high spatial resolution data being extensively utilized in various research studies. However, LAI data under future scenarios are typically only available at 1° or coarser spatial resolutions. In this study, we generated a dataset of 0.05° LAI (F0.05D-LAI) from 1983–2100 in a high spatial resolution using the LAI Downscaling Network (LAIDN) model driven by inputs including air temperature, relative humidity, precipitation, and topography data. The dataset spans the historical period (1983–2014) and future scenarios (2015–2100, including SSP-126, SSP-245, SSP-370, and SSP-585) with a monthly interval. It achieves high accuracy (R² = 0.887, RMSE = 0.340) and captures fine spatial details across various climate zones and terrain types, indicating a slightly greening trend under future scenarios. F0.05D-LAI is the first high-resolution LAI dataset and reveals the potential vegetation variation under future scenarios in China, which benefits vegetation studies and model development in earth and environmental sciences across present and future periods.

Indiscernible noise determination of a military system equipped with an internal combustion engine

The main objective of this paper is to explore the non-detectability criteria of military systems and to determine the indiscernible noise of military systems equipped with internal combustion engines. Non-detectability is one of the critical requirements evaluated for military defense systems and it is defined strictly in MIL-STD-1474E standard. Furthermore, this standard specifies the limits of sound pressure levels conservatively for 1/3 octave bands. Though, the standard does not define indiscernible or inaudible noise levels for events in the presence of background noise. It is also not explicitly well-defined in the existing literature. This study presents a comparison of non-detectability distance defined in MIL-STD-1474E standard and indiscernible noise of a military system extracted from the measured octave band sound levels, which are processed based on sound propagation theory. In this study, several parameters such as atmospheric absorption, geometric spreading, ground effect, terrain type, obstacle existence are included to determine the indiscernible noise level of the military system of interest. The results are compared with the non-detectability distance limits given in the MIL-STD-1474E standard, and it is observed that the proposed method of indiscernible noise, which is defined as extracted sound level should be lower than the background noise, is well-correlated.

Optimizing energy efficiency through building orientation and building information modelling (BIM) in diverse terrains: A case study in Pakistan

Building orientation plays a key role in enhancing the built environment's energy efficiency through the application of Building Information Modelling (BIM) and energy simulation. Due to their significant global energy consumption, buildings are the focus of energy optimization efforts. This study explores how building orientation, when combined with modern methods like BIM and energy modelling, affects energy usage and savings throughout Pakistan's numerous geographic terrains. The methodology is quantitative, beginning with an extensive review of literature on energy analysis, BIM applications, and urban building energy modelling. Autodesk Insight 360 is employed for energy simulations, which enables the precise prediction of energy consumption by considering various factors such as building orientation, window-to-wall ratios, shading, wall and roof construction, infiltration rates, lighting efficiency, occupancy controls, plug load efficiency, and HVAC systems. Energy simulation of the data indicates that optimizing building orientation alone can result in an average energy savings of 18 %, while combining orientation optimization with improvements in window arrangements and construction materials can achieve savings of up to 30 % over 30 years. The energy simulation results were validated through case study representing typical terrains and building types (commercial and residential), with simulated energy expenditures showing a high correlation (R2 = 0.92) with actual utility bills, adjusted for local energy rates. The findings of this study highlight substantial financial benefits, with potential annual savings ranging from $2500 to $4000 for residential buildings and $10,000 to $15,000 for commercial buildings, depending on building size and location. These results suggest broader applicability to diverse geographical areas and building types in future research. This research contributes significantly to energy-efficient building practices, paving the way for sustainable construction and reduced environmental impact across the varied landscapes of Pakistan.

The creation and assessment of an electrical all-terrain vehicle and its effects on efficiency

Abstract The suspension system consists of tires, tire air, springs, shock absorbers, and connections that facilitate the relative movement among the axles and the automobile. Although ride quality and road holding/handling are mutually exclusive, suspension components nevertheless need to provide both. Adjusting suspensions requires striking the ideal balance. Maintaining maximum contact between the road wheel and the road surface is crucial for the suspension. The vehicle’s suspension greatly affects its handling; since the vehicle must operate on all types of terrain and retain ideal steering geometry, an adaptable system of suspension should be employed. The EATV’s suspension elements will be designed in Solid works, and the resulting model will be examined utilizing Ansys software for optimizing design variables while taking into account how they may affect the efficiency of other automobile parts through simulator testing.

Macroscale Roughness Reveals the Complex History of Asteroids Didymos and Dimorphos

Morphological mapping is a fundamental step in studying the processes that shaped an asteroid surface. However, it is challenging and often requires multiple independent assessments by trained experts. Here we present fast methods to detect and characterize meaningful terrains from the topographic roughness: entropy of information, and local mean surface orientation. We apply our techniques to Didymos and Dimorphos, the target asteroids of NASA's Double Asteroid Redirection Test mission—the first attempt to deflect an asteroid. Our methods reliably identify morphological units at multiple scales. The comparative study reveals various terrain types, signatures of processes that transformed Didymos and Dimorphos. Didymos shows the most heterogeneity and morphology that indicate recent resurfacing events. Dimorphos is comparatively rougher than Didymos, which may result from the formation process of the binary pair and past interaction between the two bodies. Our methods can be readily applied to other bodies and data sets.

Diversity of airborne fungi in cultured and urban sites in Basra Province, Iraq

Abstract. Ameen MKM. 2024. Diversity of airborne fungi in cultured and urban sites in Basra Province, Iraq. Biodiversitas 25: 2870-2877. Atmospheric aerosols consist of particles with diverse sizes, shapes, fungal particles are relatively prevalent. They are related to air pollution and several plant, animal, and human health effects. This study was conducted to compare the airborne fungal biodiversity between cultivated and urban areas in Basra Province, Southern Iraq. Results showed that a total of 1654 fungal colonies consisted of 26 genera and two sterile mycelium belonging to 32 species. These fungal isolates belonged to three groups, namely Ascomycota, Zygomycota and Basidiomycota. Among them, Ascomycota had the highest percentage frequency (90.6%), followed by Zygomycota (6.25%) and Basidiomycota (3.12%). The highest i.e., 0.91and 0.9 fungal diversity was found in Abu Al-Khaseeb 2 and Ad-Dayr, respectively, while the lowest was in urban areas and desert nature as Um Qasr, Al-Zubair 0.78 for each. The highest frequency 18.2 10.9 8.8, and 8.5% of fungal isolates were Cladosporium herbarum, Aspergillus fumigatus, Aspergillus niger, and Penicillium sp., respectively. The highest similarity was 0.77 observed between the airborne fungal communities at the Alseeba and Altannumah sites. From the results of this study, it was concluded that airborne fungi can be influenced by the type of terrain they inhabit. There was greater diversity in cultivated areas compared to urban and non-cultivated areas.

A Robot Ground Medium Classification Algorithm Based on Feature Fusion and Adaptive Spatio-Temporal Cascade Networks

With technological advancements and scientific progress, mobile robots have found widespread applications across various fields. To enable robots to perform tasks safely and effectively in diverse and unknown environments, this paper proposes a ground medium classification algorithm for robots based on feature fusion and an adaptive spatio-temporal cascade network. Specifically, the original directional features in the dataset are first transformed into quaternion form. Then, spatio-temporal forward and reverse neighbors are identified using KD trees, and their connection strengths are evaluated via a kernel density estimation algorithm to determine the final set of neighbors. Subsequently, based on the connection strengths determined in the previous step, we perform noise reduction on the features using discrete wavelet transform. The noise-reduced features are then weighted and fused to generate a new feature representation.After feature fusion, the Adaptive Dynamic Convolutional Neural Network (ADC) proposed in this paper is cascaded with the Long Short-Term Memory (LSTM) network to further extract hybrid spatio-temporal feature information from the dataset, culminating in the final terrain classification. Experiments on the terrain type classification dataset demonstrate that our method achieves an average accuracy of 97.46% and an AUC of 99.80%, significantly outperforming other commonly used algorithms in the field. Furthermore, the effectiveness of each module in the proposed method is further demonstrated through ablation experiments.

Impact of Atmospheric Turbulence on Dynamic Wind Loads on Heliostats

This study analyses the turbulent wind properties in the lower 10 m of the atmospheric surface layer close to the ground where heliostats are located. Power spectral densities of streamwise and vertical components of wind are analysed, and the frequencies associated with the peak of the spectra are determined using field data collected at two open-country terrains in addition to spectral models of ESDU85020. Variations of the peak frequencies with height from the ground, terrain type and average wind speed are discussed and the impact on heliostat wind loads are described. It is found that while the peak frequency of the streamwise turbulence is between 0.01–0.1 Hz, the peak of the vertical turbulence occurs at frequencies in the range of 0.1–1 Hz. It is shown that smaller heliostats that are located closer to the ground are exposed to turbulent wind fluctuations at a higher frequency and are thus expected to experience wind loads with a higher dominant frequency compared to larger heliostats located higher above the ground. These frequencies need to be considered in design of heliostat drives and structural components

Natural conditions of Varandey coastal tundra. Anthropogenic transformation of natural landscapes

The author aims to characterize natural conditions in the coastal area of the Barents Sea, from the settlement of Varandey to the Perevoznoye field. The research covered an area of 20 km2, 40 km long. An integrated climatic characteristic of the studied area is given, including the direction and speed of natural processes forming its shape, cryogenic processes, flora and fauna conditions, soil cover formation. The geomorphological, geological, and hydrological features of the area are outlined. The heterogeneity of the water–salt regime of the coastal area, typical of the northern seas of the Arctic, including the Barents Sea, is noted. In the laidas, the prevalence of accumulation of easily soluble salts over their removal is established, which allows the soils to be distinguished in terms of their salinity. Here, halophytic species are identified. The vegetation cover of the studied area is characterized according to the habitat of flora representatives. The research identified 100 species of vascular plants, 51 species of lichens, and 65 species of mosses. A soil survey found 27 soil varieties, which form the structure of the soil cover; their morphological and physicochemical characterization are given. The data obtained during field studies and remote sensing data were used to determine the structure of landscapes to the level of terrain types and units, as well as to propose their description. Their ecological and geochemical typification is carried out. The fauna composition was assessed based on state registration data and open sources; field observations with reference to biotopes were used. The dynamics of fauna population on the Barents Sea coast was assessed retrospectively. Field survey and remote sensing data made it possible to identify areas with anthropogenic disturbance of tundra landscapes. A typification of the identified anthropogenic disturbances of the natural environment and their areas within the survey area is proposed. The data obtained can be used as signs when assessing the state of natural environments in the coastal part of the northern seas of the Arctic, similar in terms of natural and climatic conditions.