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Climate change is reshaping forest ecosystems, presenting urgent and complex challenges that demand attention. In this context, research that quantifies interactions between climate and forests is substantial. However, modelling at a spatial resolution relevant for ecological processes presents a significant challenge, especially given the diverse geographical contexts in which it is applied. In our study, we aimed to assess the effects of applying CHELSA v.2.1 and WorldClim v2.1 data on bioclimatic analysis within the Río Puelo catchment area in northern Patagonia. To achieve this, we inter-compared and evaluated present and future bioclimates, drawing on data from both climate datasets. Our findings underscore substantial consistency between both datasets for temperature variables, confirming the reliability of both for temperature analysis. However, a strong contrast emerges in precipitation predictions, with significant discrepancies highlighted by minimal overlap in bioclimatic classes, particularly in steep and elevated terrains. Thus, while CHELSA and WorldClim provide valuable temperature data for northern Patagonia, their use for precipitation analysis requires careful consideration of their limitations and potential inaccuracies. Nevertheless, our bioclimatic analyses of both datasets under different scenarios reveal a uniform decline in mountain climates currently occupied by N. pumilio, with projections suggesting a sharp decrease in their coverage under future climate scenarios. [ABSTRACT FROM AUTHOR]

To make more rational use of water resources and effectively protect and restore vegetation in alpine regions, alpine grasslands under different terrains（slope aspect and position） were selected as research objects in the Liancheng National Nature Reserve of Gansu Province. The variations in soil hydrological characteristics in the 0-30 cm soil layer of alpine grasslands under the different terrains（slope aspect and slope position） were investigated. The results showed that with an increase in soil depth, the soil water content of the alpine grasslands decreased, and the soil bulk density increased under different terrain conditions. The soil water content of the shady slope was higher than that of the sunny slope, whereas the opposite was true for soil bulk density. The soil water content and soil bulk density on the lower slope were higher than those on the upper slope. Total soil porosity, capillary porosity, and non-capillary porosity showed that the shady slope was larger than the sunny slope, and the upper part of the slope was larger than the lower part of the slope. The results showed that the upper part of the shady slope was the highest. The soil water-holding capacity in different slope directions and positions was as follows: shady slope＞ sunny slope and upper slope＞ middle slope＞ lower slope. The initial infiltration rate(0.47-5.90 mm·min-1) was higher than the stable infiltration rate(0.08-1.36 mm·min-1) and average infiltration rate(0.09-1.54 mm·min-1). The soil permeability of alpine grasslands on different terrains was as follows: sunny slope＞ shady slope and upper slope＞ middle slope＞ lower slope. The terrain（slope aspect and position） of the alpine grasslands has a significant impact on the soil hydrological characteristics. Therefore, the relationship between terrain and soil hydrological characteristics should be fully considered during the ecological protection, restoration, and sustainable development of alpine grassland ecosystems in the Liancheng National Nature Reserve of Gansu Province. [ABSTRACT FROM AUTHOR]

Digital Elevation Models (DEMs) are a necessity for modelling many large-scale environmental processes. In this study, we investigate the potential of data from two spaceborne lidar altimetry missions, ICESat-2 and GEDI—with respect to their vertical accuracies and planimetric data collection patterns—as sources for rasterisation towards creating global DEMs. We validate the terrain measurements of both missions against airborne lidar datasets over three areas in the Netherlands, Switzerland, and New Zealand and differentiate them using land-cover classes. For our experiments, we use five years of ICESat-2 ATL03 data and four years of GEDI L2A data for a total of 252 million measurements. The datasets are filtered using parameter flags provided by the higher-level products ICESat-2 ATL08 and GEDI L3A. For all areas and land-cover classes combined, ICESat-2 achieves a bias of −0.11 m, an MAE of 0.43 m, and an RMSE of 0.93 m. From our experiments, we find that GEDI is less accurate, with a bias of 0.09 m, an MAE of 0.98 m, and an RMSE of 2.96 m. Measurements in open land-cover classes, such as "Cropland" and "Grassland", result in the best accuracy for both missions. We also find that the slope of the terrain has a major influence on vertical accuracy, more so for GEDI than ICESat-2 because of its larger horizontal geolocation error. In contrast, we find little effect of either beam power or background solar radiation, nor do we find noticeable seasonal effects on accuracy. Furthermore, we investigate the spatial coverage of ICESat-2 and GEDI by deriving a DEM at different horizontal resolutions and latitudes. GEDI has higher spatial coverage than ICESat-2 at lower latitudes due to its beam pattern and lower inclination angle, and a derived DEM can achieve a resolution of 500 m. ICESat-2 only reaches a DEM resolution of 700 m at the equator, but it increases to almost 200 m at higher latitudes. When combined, a 500 m resolution lidar-based DEM can be achieved globally. Our results indicate that both ICESat-2 and GEDI enable accurate terrain measurements anywhere in the world. Especially in data-poor areas—such as the tropics—this has potential for new applications and insights. [ABSTRACT FROM AUTHOR]

This paper presents the first method for synthesizing seasonal transition of terrain textures for an input heightfield. Our method reproduces a seamless transition of terrain textures according to the seasons by learning measured data on the earth using a convolutional neural network. We attribute the main seasonal texture transition to vegetation and snow, and control the texture synthesis not only with the input heightfield but also with the annual temperature and precipitation based on Köppen's climate classification as well as insolation at the location. We found that month-by-month synthesis yields incoherent transitions, while a naïve conditioning with explicit temporal information (e.g., month) degrades generalizability due to the north–south hemisphere difference. To address these issues, we introduce a simple solution—periodic conditioning on the annual data without explicit temporal information. Our experiments reveal that our method can synthesize plausible seasonal transitions of terrain textures. We also demonstrate large-scale texture synthesis by tiling the texture output. [ABSTRACT FROM AUTHOR]

The sporadic E‐layer (Es) exhibits unique opportunity for exploring the coupling from lower to upper atmosphere. It was found that the East Asia is with the highest intensity and occurrence probability of Es. By using the long‐term data of 21 ionosonde stations in China and Japan over the past 60 yrs, this paper explores the probable control on the Es layer from the lower layers. It is found that the intensity of the Es layer is strongly correlated with the surface atmospheric temperature, terrain, and land‐sea boundary. The correlation coefficient of the intensity of Es with surface temperature is as high as 0.8204, while that with the terrain and land‐sea boundary is up to 0.6668. Based on the coupling between the lower and upper atmosphere, this paper reveals the probable controls from lower layers on the intensity of the Es in East Asia. Plain Language Summary: As an occasional ionized layer of the ionosphere, the sporadic E‐layer (Es) exhibits unique opportunity for exploring the coupling from lower to upper atmosphere. Despite extensive research on both behavior and mechanism of the Es, none have adequately explained the strong inhomogeneous of its global morphology. It is found in fact that the East Asia is with the highest intensity and occurrence probability of Es. By using the long‐term data of 21 ionosondes in China and Japan over the past 60 yrs, this letter explores the formation mechanism of the strongest Es regions in the world. It is found that the intensity of the Es layer is strongly correlated with the surface atmospheric temperature, terrain, and land‐sea boundary. The correlation coefficient between the intensity of Es and surface temperature is highest, while that with the terrain and land‐sea boundary is also high. By analyzing the data as long as six decades, this letter reveals the probable controls from lower layers on the intensity of the Es in East Asia. Key Points: By analyzing the six‐decade data of 21 ionosondes in East Asia, it reveals probable controls on the strongest Es layer from lower layersFor the first time, it is found that the intensity of Es layer is highly correlated with the surface atmospheric temperatureAn interesting coupling from lower to upper atmosphere may be found by taking advantage of observations longer than half of a century [ABSTRACT FROM AUTHOR]

Abstract Background Understanding of the ratio of photosynthetic photon flux density (Q p ) to global solar radiation (R s ) (Q p /R s ) is crucial for applying R s to ecology-related studies. Previous studies reported Q p /R s and its variations based on measurements from a single observatory tower, instead of multi-site-based measurements over complex terrains. This may neglect spatial heterogeneity in the terrain, creating a gap in an understanding of how terrain affects Q p /R s and how this effect interacts with meteorological factors. Methods Here the Qingyuan Ker Towers (three towers in a valley with different terrains: T1, T2, and T3) were utilized to measure Q p and R s over mountainous forests of Northeast China. An airborne LiDAR system was used to generate a digital elevation model, and sky view factor of sectors (SVFs) divided from the field of view of tower’s pyranometer was calculated as a topographic factor to explain the variations of Q p /R s . Results The results identified significant differences in Q p /R s of the three towers at both daily and half-hour scales, with larger differences on clear days than on overcast days. Q p /R s was positively correlated with SVFs of T1 and T3, while this correlation was negative with that of T2. The effect of SVFs on Q p /R s interacted with clearness index, water vapor pressure and solar zenith angle. Random forest-based importance assessment demonstrated that explanation (R 2) on Q p /R s was improved when SVFs was included in the predictor variable set, indicating that incorporating terrain effects enhances the prediction accuracy of Q p /R s . The improvement in the R 2 values was more pronounced on clear days than on overcast days, suggesting that the effect of terrain on Q p /R s depended on sky conditions. Conclusions All findings suggested that Q p /R s is affected by terrain, and integrating terrain information into existing Q p /R s models is a feasible solution to improve Q p /R s estimates in mountainous areas.

Terrain surface roughness, often described abstractly, poses challenges in quantitative characterization with various descriptors found in the literature. In this study, we compared five commonly used roughness descriptors, exploring correlations among their quantified terrain surface roughness maps across three terrains with distinct spatial variations. Additionally, we investigated the impacts of spatial scales and interpolation methods on these correlations. Dense point cloud data obtained through Light Detection and Ranging technique were used in this study. The findings highlighted both global pattern similarities and local pattern distinctions in the derived roughness maps, emphasizing the significance of incorporating multiple descriptors in studies where local roughness values play a crucial role in subsequent analyses. The spatial scales were found to have a smaller impact on rougher terrain, while interpolation methods had minimal influence on roughness maps derived from different descriptors.

The aim of the analysis was to carry out a detailed assessment of the site in Krościenko nad Dunajcem in terms of its suitability for the construction of a photovoltaic farm. Geospatial data and analysis of urban planning documents such as the Local Spatial Development Plan and the Municipality's Conditions Study were used. Factors such as insolation, topography, terrain, forestation and hydrological factors were studied in an attempt to understand their influence on the selection of the optimal location for a photovoltaic installation. The research material and methodology were based on the analysis of geospatial data of the area and the interpretation of urban planning documents. Tools were used to analyse spatial relationships and assess potential risks for a photovoltaic investment. The main conclusions of the research indicate that the terrain conditions in Krościenko nad Dunajcem are suitable for the implementation of a photovoltaic farm. The identification of optimal locations was based on the analysis of spatial factors, which confirms the potential of the area for efficient construction of photovoltaic installations. The conclusions of the analysis indicate that taking spatial factors into account is crucial when planning and selecting the location of a photovoltaic farm. However, it is necessary to continue monitoring environmental and technical aspects to ensure the sustainability of the photovoltaic project in the area.

Central North America is the global hotspot for tornadoes, fueled by elevated terrain of the Rockies to the west and a source of warm, moist air from equatorward oceans. This conventional wisdom argues that central South America, with the Andes to the west and Amazon basin to the north, should have a "tornado alley" at least as active as central North America. Central South America has frequent severe thunderstorms yet relatively few tornadoes. Here, we show that conventional wisdom is missing an important ingredient specific to tornadoes: a smooth, flat ocean-like upstream surface. Using global climate model experiments, we show that central South American tornado potential substantially increases if its equatorward land surface is smoothed and flattened to be ocean-like. Similarly, we show that central North American tornado potential substantially decreases if its equatorward ocean surface is roughened to values comparable to forested land. A rough upstream surface suppresses the formation of tornadic environments principally by weakening the poleward low-level winds, characterized by a weakened low-level jet east of the mountain range. Results are shown to be robust for any midlatitude landmass using idealized experiments with a simplified continent and mountain range. Our findings indicate that large-scale upstream surface roughness is likely a first-order driver of the strong contrast in tornado potential between North and South America. [ABSTRACT FROM AUTHOR]

Understanding the biophysical limitations on forest carbon across diverse ecological regions is crucial for accurately assessing and managing forest carbon stocks. This study investigates the role of climate and disturbance on the spatial variation of two key forest carbon pools: aboveground carbon (AGC) and soil organic carbon (SOC). Using plot‐level carbon pool estimates from Nepal's national forest inventory and structural equation modelling, we explore the relationship of forest carbon stocks to broad‐scale climatic water and energy availability and fine‐scale terrain and disturbance. The forest AGC and SOC models explained 25% and 59% of the observed spatial variation in forest AGC and SOC, respectively. Among the evaluated variables, disturbance exhibited the strongest negative correlation with AGC, while the availability of climatic energy demonstrated the strongest negative correlation with SOC. Disturbances such as selective logging and firewood collection result in immediate forest carbon loss, while soil carbon changes take longer to respond. The lower decomposition rates in the high‐elevation region, due to lower temperatures, preserve organic matter and contribute to the high SOC stocks observed there. These results highlight the critical role of climate and disturbance regimes in shaping landscape patterns of forest carbon stocks. Understanding the underlying drivers of these patterns is crucial for forest carbon management and conservation across diverse ecological zones including the Central Himalayas. [ABSTRACT FROM AUTHOR]

Melting layer usually exists in precipitation where ice particles gradually melt into liquid particles. Utilizing the detection from the Dual-frequency Precipitation Radar onboard Global Precipitation Measurement Mission Core Observatory during 2018-2022, this paper investigates the quasi-global climatological features of Melting layer over 65°S ~65°N and analyzes the relationships with elevation in the golden case involving the section along 32.5°N across China. The distribution of Melting layer is latitude-dependent: Melting layer is higher in 30°S~30°N and decrease toward the mid-and high-latitude, which are generally lower in 30°S~65°S throughout the year. The height and thickness of Melting layer change more dramatically in mid-and high latitudes than in low latitudes for diurnal variations. The higher elevation terrain has the lower Melting layer top height than other terrains, yet the geometric thickness of Melting layer is also thinner. A golden case is selected to represent the analysis of Melting layer play role in rainfall. When the Melting layer grow thinner with steeply rising elevation due to the thermal change and orographic uplift, there is weak rain with a greater number of smaller raindrops in the golden case. However, Melting layer can get widen and raindrops can get sufficient growth as the elevation declines. [ABSTRACT FROM AUTHOR]

In order to quantitatively analyze the roughness of the bench floor during open-pit mine blasting, this study proposes a real-time measuring method for the three-dimensional terrain of the bench floor during the excavation process. Real-time monitoring is conducted at the boundary and discrete internal points of the workbench floor during electric shovel operation, utilizing real-time kinematic global navigation satellite system (RTK-GNSS) positioning technology. An improved convex hull algorithm is introduced to automatically extract the optimal boundary of discrete point clouds based on their spatial distribution characteristics. This study establishes a digital elevation model (DEM) using five interpolation algorithms for 3D terrain visualization simulation. Through cross-validation, a comparative analysis of the DEM accuracy, the simulation results of the ordinary kriging interpolation algorithm were found to be optimized. The optimized interpolation algorithm is applied to simulate the 3D terrain in the Dexing open-pit copper mine, and the relevant terrain parameters were calculated. This dataset can serve as a precise foundation for the real-time path planning of elevation blasting design and ground leveling operations. [ABSTRACT FROM AUTHOR]

Using large eddy simulation, we investigate the combined effect of terrain and surface sensible heat flux (SHF) heterogeneity on the development of afternoon deep moist convection (DMC). We implement an analytically derived, two‐dimensional terrain and SHF variations transformed from a κ−3 (where κ is the wavenumber) spectrum spanning wavelengths from 32 to 0.2 km. By separately coupling multiscale terrain with a homogeneous SHF field and the multiscale SHF field with flat terrain, we discern the individual impacts of these κ−3‐spectrum forcings on DMC. Our specific forcing configuration demonstrates that the multiscale terrain had a greater influence on DMC development compared to the multiscale SHF field. While the solely surface SHF heterogeneity forcing results in a wider pool of high relative humidity above the boundary layer, its significance is relatively lower in the mountainous terrain cases due to the shorter interaction time between highly buoyant thermals and the surrounding environment. However, when the multiscale terrain and SHF field are synchronized, DMC develops rapidly within a time frame of 4.5 hr, which is facilitated by enhanced surface buoyancy fluxes, the presence of highly buoyant thermals, and the persistence of mesoscale structures such as near‐surface convergence and mesoscale updrafts. Our study highlights the importance of the synergistic effects between multiscale terrain and surface SHF heterogeneity in DMC development. Additionally, our multiscale analyses of atmospheric variables reveal distinct atmospheric regimes between the pre‐storm and DMC periods. These findings contribute to a better understanding of the complex dynamics involved in the formation of afternoon DMC. Plain Language Summary: Our research used a high‐resolution model to explore how clouds and precipitation form in the afternoon in response to spatial variations in surface thermal properties and terrain height. Specifically, we analyze the effects of multiscale terrain height variation and surface thermal variation that is warmer and drier over higher terrain and cooler and moister over lower terrain. This is a realistic representation of how summits and valleys are differently heated in a mountainous area. Air flow moving up toward higher terrain is caused by both the difference in pressure between the summit and valley, as well as the varying thermal properties across the surface. To see the effects of each factor, we ran two additional simulations with a flat surface and homogeneous thermal properties. On the surface with thermal properties covarying with terrain height, a storm with rain quickly formed by 1500 local time. This study suggests that the contrasting thermal properties of warm summits and cool valleys greatly increase the chances of severe thunderstroms forming. Key Points: Multiscale surface‐thermal variation in phase with terrain has a stronger impact on moist convection than any single variationAn air pool of high humidity above the boundary layer has a lesser effect over mountainous terrain compared to surface thermal variationMesoscale variance of atmospheric variables significantly rises post onset of deep moist convection [ABSTRACT FROM AUTHOR]

Background: Understanding of the ratio of photosynthetic photon flux density (Qp) to global solar radiation (Rs) (Qp/Rs) is crucial for applying Rs to ecology-related studies. Previous studies reported Qp/Rs and its variations based on measurements from a single observatory tower, instead of multi-site-based measurements over complex terrains. This may neglect spatial heterogeneity in the terrain, creating a gap in an understanding of how terrain affects Qp/Rs and how this effect interacts with meteorological factors. Methods: Here the Qingyuan Ker Towers (three towers in a valley with different terrains: T1, T2, and T3) were utilized to measure Qp and Rs over mountainous forests of Northeast China. An airborne LiDAR system was used to generate a digital elevation model, and sky view factor of sectors (SVFs) divided from the field of view of tower's pyranometer was calculated as a topographic factor to explain the variations of Qp/Rs. Results: The results identified significant differences in Qp/Rs of the three towers at both daily and half-hour scales, with larger differences on clear days than on overcast days. Qp/Rs was positively correlated with SVFs of T1 and T3, while this correlation was negative with that of T2. The effect of SVFs on Qp/Rs interacted with clearness index, water vapor pressure and solar zenith angle. Random forest-based importance assessment demonstrated that explanation (R2) on Qp/Rs was improved when SVFs was included in the predictor variable set, indicating that incorporating terrain effects enhances the prediction accuracy of Qp/Rs. The improvement in the R2 values was more pronounced on clear days than on overcast days, suggesting that the effect of terrain on Qp/Rs depended on sky conditions. Conclusions: All findings suggested that Qp/Rs is affected by terrain, and integrating terrain information into existing Qp/Rs models is a feasible solution to improve Qp/Rs estimates in mountainous areas. [ABSTRACT FROM AUTHOR]

The aim of the analysis was to carry out a detailed assessment of the site in Krościenko nad Dunajcem in terms of its suitability for the construction of a photovoltaic farm. Geospatial data and analysis of urban planning documents such as the Local Spatial Development Plan and the Municipality's Conditions Study were used. Factors such as insolation, topography, terrain, forestation and hydrological factors were studied in an attempt to understand their influence on the selection of the optimal location for a photovoltaic installation. The research material and methodology were based on the analysis of geospatial data of the area and the interpretation of urban planning documents. Tools were used to analyse spatial relationships and assess potential risks for a photovoltaic investment. The main conclusions of the research indicate that the terrain conditions in Krościenko nad Dunajcem are suitable for the implementation of a photovoltaic farm. The identification of optimal locations was based on the analysis of spatial factors, which confirms the potential of the area for efficient construction of photovoltaic installations. The conclusions of the analysis indicate that taking spatial factors into account is crucial when planning and selecting the location of a photovoltaic farm. However, it is necessary to continue monitoring environmental and technical aspects to ensure the sustainability of the photovoltaic project in the area. [ABSTRACT FROM AUTHOR]

Terrain surface roughness, often described abstractly, poses challenges in quantitative characterization with various descriptors found in the literature. In this study, we compared five commonly used roughness descriptors, exploring correlations among their quantified terrain surface roughness maps across three terrains with distinct spatial variations. Additionally, we investigated the impacts of spatial scales and interpolation methods on these correlations. Dense point cloud data obtained through Light Detection and Ranging technique were used in this study. The findings highlighted both global pattern similarities and local pattern distinctions in the derived roughness maps, emphasizing the significance of incorporating multiple descriptors in studies where local roughness values play a crucial role in subsequent analyses. The spatial scales were found to have a smaller impact on rougher terrain, while interpolation methods had minimal influence on roughness maps derived from different descriptors. [ABSTRACT FROM AUTHOR]

High-quality height reference data are embedded in the accuracy verification processes of most remote sensing terrain applications. The Ice, Cloud, and Land elevation Satellite 2 (ICESat-2)/ATL08 terrain product has shown promising results for estimating ground heights, but it has not been fully evaluated. Hence, this study aims to assess and enhance the accuracy of the ATL08 terrain product as a height reference for the newest versions of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the Shuttle Radar Topography Mission (SRTM), and TanDEM-X (TDX) DEMs over vegetated mountainous areas. We used uncertainty-based filtering method for the ATL08 strong and weak beams to enhance their accuracy. Then, the results were evaluated against a reference airborne LiDAR digital terrain model (DTM), by selecting 10,000 points over the entire area and comparing the accuracy of ASTER, SRTM, and TDX DEMs assessed by the LiDAR DTM to the accuracy of the ASTER, SRTM, and TDX DEMs assessed by the ATL08 strong beams, weak beams, and all beams. We also detected the impact of the terrain aspect, slope, and land cover types on the accuracy of the ATL08 terrain elevations and their relationship with height errors and uncertainty. Our findings show the accuracy of the ATL08 strong beams was enhanced by 43.91%; while the weak beams accuracy was enhanced by 74.05%. Furthermore, slope strongly influenced ATL08 height errors and height uncertainty; especially on the weak beams. The errors induced by the slope significantly decreased when the uncertainty levels were reduced to <20 m. The evaluations of ASTER, SRTM, and TDX DEMs by ATL08 strong and weak beams are close to those assessed by LiDAR DTM points within 0.6 m for the strong beams. These findings indicate that ATL08 strong beams can be used as a height reference over vegetated mountainous regions. [ABSTRACT FROM AUTHOR]

Music has long served as a bridge between science and nature, allowing for the artistic expression of natural and human‐made phenomena. While music has been used in geomorphology as an engaging teaching strategy, its application in specific scientific inquiries within geomorphology remains relatively unexplored. Drawing on the morphological similarities between music and terrain relief, this work introduced a novel music‐based method for modelling and expressing terrain relief based on the drainage basin profile (DBP). It converts terrain relief into pitches and time values according to mapping rules and then describes terrain relief in an audible form. Based on 5 sample areas and 360 drainage basins on the Loess Plateau, we developed the application of the proposed method on four core geomorphic tasks, including landform interpretation, analysis, recognition and classification. Experimental results show that (1) terrain music can interpret the terrain relief and landform evolution processes through its musical structure and rhythmic variations; (2) music derivatives are related to different terrain features, such as terrain relief, terrain variation intensity, landform evolution degree and terrain complexity, and have a well‐functioning relationship with a series of conventional terrain derivatives; (3) leveraging machine learning techniques, the terrain music method is effective for landform recognition, achieving an overall accuracy of 88.85% and a mean accuracy of 88.85%; and (4) via a case study in Northern Shaanxi, music modelling successfully divided it into 12 distinct landform regions and 8 landform types. Different landform regions exhibit clear regional boundaries and gradual transition zones, while specific landform regions share prominent terrain, spatial clustering and landform processes. Our delineation provides reasonable and effective landform differentiation but captures additional bed‐rock mountain features compared with a traditional method. This study highlights that music is not only an artistic expression but also a valuable research paradigm for a wide range of geomorphic tasks, offering fresh perspectives and enhancing our understanding of loess landforms. The results show a promising effort to integrate music theory into practical geomorphic tasks, demonstrating the potential of using music as a medium for conveying and analysing spatial information in geomorphology. [ABSTRACT FROM AUTHOR]

In the previous literature, amphibious robots focused mainly on locomotion in underwater and flat land surface manoeuvring. Few amphibious robots focused on unstructured land environments. The amphibious robot designs were more emphasised in academics, leading to more work done in building amphibious robots that mimic biological amphibians, imitating the geometry and overall functionality of the amphibious robots. Developing amphibious robots with propulsive mechanisms for manoeuvring in a water environment received more attention than other functionalities like adaptability on rough natural terrain and obstacle repositioning capability. However, practical applications like reconnaissance and surveying posed challenges in the ground environment, which had unstructured and complex terrain profiles, especially in the transition area. Therefore, reviewing the amphibious robots focused on manoeuvring complex uneven surfaces was essential. The literature had comprehensive review papers on navigation strategies encompassing manoeuvring on flat ground surfaces and underwater locomotion. There was a need for a focused study that highlighted the amphibious robot that manoeuvred in an unstructured land environment. The open challenges and recent solutions by designing new mechanisms and deployment issues were highlighted and reviewed. Hence, the paper addressed a more specific review of amphibious robot locomotion in an unstructured environment. The paper also discussed a case study of an amphibious robot capable of locomotion in unstructured environments. It was envisaged that the review would provide directions and insights to researchers and robotic system designers on developing robust propulsive mechanisms for amphibious robots capable of locomotion in unstructured environments.

ABSTRACTHigh-quality height reference data are embedded in the accuracy verification processes of most remote sensing terrain applications. The Ice, Cloud, and Land elevation Satellite 2 (ICESat-2)/ATL08 terrain product has shown promising results for estimating ground heights, but it has not been fully evaluated. Hence, this study aims to assess and enhance the accuracy of the ATL08 terrain product as a height reference for the newest versions of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the Shuttle Radar Topography Mission (SRTM), and TanDEM-X (TDX) DEMs over vegetated mountainous areas. We used uncertainty-based filtering method for the ATL08 strong and weak beams to enhance their accuracy. Then, the results were evaluated against a reference airborne LiDAR digital terrain model (DTM), by selecting 10,000 points over the entire area and comparing the accuracy of ASTER, SRTM, and TDX DEMs assessed by the LiDAR DTM to the accuracy of the ASTER, SRTM, and TDX DEMs assessed by the ATL08 strong beams, weak beams, and all beams. We also detected the impact of the terrain aspect, slope, and land cover types on the accuracy of the ATL08 terrain elevations and their relationship with height errors and uncertainty. Our findings show the accuracy of the ATL08 strong beams was enhanced by 43.91%; while the weak beams accuracy was enhanced by 74.05%. Furthermore, slope strongly influenced ATL08 height errors and height uncertainty; especially on the weak beams. The errors induced by the slope significantly decreased when the uncertainty levels were reduced to

Geostrophic adaptation is another frontogenesis mechanism that forms a stationary front, which differs from the balanced front, but often leads to local catastrophic weather in the mountainous area of southern Anhui. Conducting analysis and research on the frontogenesis conditions of geostrophic adaptation is of great significance for how mountainous terrain causes catastrophic weather. Taking the formation of a stationary front on 22 February 2022, which resulted in a local blizzard as an example, the quasi-geostrophic frontogenesis function of topographic frontogenesis is calculated and analyzed based on the following dataset, including the high-resolution hourly reanalysis data from the European meteorological center ERA and conventional data from ground stations, the new generation Doppler (CINRAD/SA) weather radar data, the 3-D wind field data obtained with a 3-D wind field inversion technique and the interpolation method with the accuracy of 0.02°×0.02°. The results are as follows. (1) During this frontogenesis process, the northeast wind flow on the ground intensified, and the gradient of the flow function increased, resulting in discontinuous fluid density at the foot of the leeward slope (30.5°—31.0°N), which leads to geostrophic adjustment to frontogenesis in a narrow area at its front. Thus, a local snowstorm with a small scale and short duration occurred. The geostrophic adjustment to frontogenesis occurs in a stable atmospheric structure and an environment of wet symmetry instability. (2) By analyzing the four terms of the surface frontogenesis function and their related factors, it is shown that the contribution of vertical motion tilt term to frontogenesis is dominant, while the horizontal deformation and convergence have minor contributions. It indicates that the geostrophic adjustment to frontogenesis is mainly the result of the upward transportation of potential temperature, rather than the deformation of the wind field. (3) By analyzing the four terms of the high-altitude frontogenesis function and the mesoscale wind field retrieved by radar, during the adjusting of the wind field from a non-equilibrium state to an equilibrium state, a strong secondary circulation appears in the middle and lower layers of the atmosphere at an altitude of 1.5-3.0 km above the front zone, which leads to the cooling due to the rise of cold air over the cold zone. While above the warm zone, non-adiabatic heating released by snowfall condensation latent heat causes warming, resulting in an increase in the temperature gradient at the front zone and frontogenesis.

Given the necessity of connecting the unconnected, covering blind spots has emerged as a critical task in the next-generation wireless communication network. A direct solution involves obtaining a coverage manifold that visually showcases network coverage performance at each position. Our goal is to devise different methods that minimize the absolute error between the estimated coverage manifold and the actual coverage manifold (referred to as accuracy), while simultaneously maximizing the reduction in computational complexity (measured by computational latency). Simulation is a common method for acquiring coverage manifolds. Although accurate, it is computationally expensive, making it challenging to extend to large-scale networks. In this paper, we expedite traditional simulation methods by introducing a statistical model termed line-of-sight probability-based accelerated simulation. Stochastic geometry is suitable for evaluating the performance of large-scale networks, albeit in a coarse-grained manner. Therefore, we propose a second method wherein a model training approach is applied to the stochastic geometry framework to enhance accuracy and reduce complexity. Additionally, we propose a machine learning-based method that ensures both low complexity and high accuracy, albeit with a significant demand for the size and quality of the dataset. Furthermore, we describe the relationships between these three methods, compare their complexity and accuracy as performance verification, and discuss their application scenarios.

This article aims to identify potential sites for agricultural use in the state of Manipur of north east India by employing the analytic hierarchy process in a geographic information system environment in conjunction with the use of remote sensing and soil data. Within the analytic hierarchy process, each terrain variable underwent a pairwise comparison and criteria weights were assigned according to their relative importance. Eight variables were selected and used in land suitability analysis for agriculture. It was found that Manipur had 57% (12,660 km2) of its total geographical area suitable for agriculture. However, 8126 km2 (37%) and 1374 km2 (6%) of the total geographical area was currently and permanently unsuitable land respectively. The distribution of suitable land varied greatly, with highly, moderately and marginally suitable land covering only 8%, 16% and 33% respectively of the total geographical area. The highly suitable agricultural land is predominantly concentrated in the Imphal valley (70%), though 90% of moderately suitable and 96% of marginally suitable land also exist in the hills. The hilly areas constitute 96% and 97% respectively of currently unsuitable and permanently unsuitable land in the state. Suitable land comprises of land with low to medium altitude, gentle to moderate slopes, soil of fine or acceptable quality, and with minimal flood risk. Unsuitable lands tend to be diametrically opposite to these attributes with steep hill slopes. The nature of distribution of land suitability types influences the agricultural pattern in Manipur. Agriculture in the hill areas comprises mainly of shifting cultivation on hill slopes, whereas in the valley region it is irrigated and permanent. This analysis of Manipur has a wider applicability since the shifting cultivation-irrigated agriculture combination is similar to that which exists across much of the highlands of South East Asia. [ABSTRACT FROM AUTHOR]

Objectives: The seasonal subsidence and uplift of the surface elevation in permafrost area occur due to the annual melting and freezing of active layer, which has an important impact on the safety of engineering construction, the balance of ecological environment, and global climate change. Using global navigation satellite system-interferometric reflectometry (GNSS-IR) to monitor frozen soil deformation is a new technique. Aiming at the terrain influence caused by the non-daily-repeatable orbits of GLONASS and Galileo satellites, this paper proposes a new method to calculate the freeze-thaw deformation of permafrost using these GNSS data. Methods: By introducing the inclination angle of reflector surface, the effects of terrain changes are eliminated, and the seasonal freeze-thaw deformation closer to the actual situation is obtained. The GNSS signal-to-noise ratio data of 2018 and 2019 snow-free days at SG27 site in northern Alaska are used for experiments and compared with the results obtained by existing retrieval methods to verify the effectiveness of this method in monitoring permafrost deformation. Results: The results show that compared with the methods without considering the terrain effect, the surface elevation changes obtained by GLONASS and Galileo have smaller discreteness and smaller uncertainty, and the fitting consistency and determination coefficient R2 of the composite model have been improved. The total average standard deviations are reduced by about 28.9 % and 36.9 %, and the total average R2 are increased by about 0.23 and 0.24, respectively. The total average increases of daily data utilization rate of non-repetitive orbits are about 19.6 % and 22.8 % . Conclusions: This study provides a valuable reference for monitoring permafrost freeze-thaw deformation, and expands the application of GNSS-IR in GNSS system for permafrost freeze-thaw monitoring. [ABSTRACT FROM AUTHOR]

The accelerated urbanization in the last decade and population growth in developing countries in the Middle East and North Africa (MENA) region have increased the count of humans exposed to air pollution. This work aims to provide an insight into air quality in the Greater Cairo (GC) area which is one of the largest megacities in the MENA region and is classified as its most polluted city according to the reports of the World Health Organization (WHO). Exploratory data analysis and cluster analysis were used to assess the pollutants data and meteorological data to understand the impacts of weather factors on air quality in GC. According to the results, GC suffers from particle matter of 10 micrometres or less (PM10) pollutants. The annual averages ranged from 97 ± 10 to 203 ± 42 µg/m³. Though short-term exposure to gaseous pollutants did not exceed the limits, the long-term exposures exceeded those in some congested traffic areas. The annual averages ranged from 20 ± 5 to 63 ± 24 µg/m³ for Nitrogen dioxide (NO2) and from 9 ± 3 to 21 ± 5 µg/m³ for sulphur dioxide (SO2). Also, the terrain affects the spatial variation of pollutants observation. There is a negative correlation between the monitoring site elevation and the pollutant concentration. [ABSTRACT FROM AUTHOR]

Il existe aujourd’hui une importante quantité de lignes directrices à suivre si l’on veut faire de la recherche éthique en contexte autochtone. Dans la pratique, même avec la meilleure volonté, il est difficile de démêler ce à quoi il faut se conformer et ce qui est vraiment éthique. La voie prônée informellement dans le milieu des études autochtones est la recherche collaborative, mais est-elle toujours possible?

In order to quantitatively analyze the roughness of the bench floor during open-pit mine blasting, this study proposes a real-time measuring method for the three-dimensional terrain of the bench floor during the excavation process. Real-time monitoring is conducted at the boundary and discrete internal points of the workbench floor during electric shovel operation, utilizing real-time kinematic global navigation satellite system (RTK-GNSS) positioning technology. An improved convex hull algorithm is introduced to automatically extract the optimal boundary of discrete point clouds based on their spatial distribution characteristics. This study establishes a digital elevation model (DEM) using five interpolation algorithms for 3D terrain visualization simulation. Through cross-validation, a comparative analysis of the DEM accuracy, the simulation results of the ordinary kriging interpolation algorithm were found to be optimized. The optimized interpolation algorithm is applied to simulate the 3D terrain in the Dexing open-pit copper mine, and the relevant terrain parameters were calculated. This dataset can serve as a precise foundation for the real-time path planning of elevation blasting design and ground leveling operations.

There are now a large number of guidelines to follow if you want to carry out ethical research in an Indigenous context. In practice, even with the best will in the world, it is difficult to disentangle what needs to be adhered to and what is truly ethical. The path informally advocated in the field of Indigenous studies is collaborative research, but is this always possible?. [ABSTRACT FROM AUTHOR]

Urban heat islands are hotter than rural places. Sustainable urban growth and improving urban environments need understanding Urban Heat Island (UHI) causes and finding effective mitigation techniques. This research examines the seasonal deviations in surface temperatures for the UHI effect in Pune, India, focusing on land use patterns and water body cooling. Land use categorization included residential, commercial, industrial, vegetation, and open spaces. The research studied the cooling potential and temperature variance by distance from water bodies in the form of lakes, rivers, and ponds. These aquatic bodies have surface and ambient temperature sensors. Roads, soil, commercial areas, residential areas, industrial areas, and vegetation have all shown increases in NDBI, ranging from 15.84 to 36.45%. Urban regions with heat accumulation and dissipation have been revealed by DEM and contour maps. The research found that the water bodies have a cooling effect on LST till the distance of 350 m. The research finds hotter places and shows how natural features mitigate UHI by analyzing land use patterns and water body cooling. The findings emphasize the significance of green areas and water bodies in urban design and development to improve Pune's climate resilience and inhabitability. HIGHLIGHTS Study examines how UHI gets affected by Landuse variation and Water cooling with remote sensing and geospatial analysis.; The findings inform urban planning and climate change adaptation in similar cities.; Urban water bodies can act as natural climate buffers by cooling.; The study illuminates the UHI effects on urban climate resistance.;

An historically heavy rainfall event occurred in North China from 29 July to 1 August in 2023, causing serious disasters. In this study, the precipitation characteristics and causes of this heavy rainfall event was investigated utilizing various observational data from such as conventional surface and upper air data, FY-4A satellite TBB, and ERA5 reanalysis data. The results are as follows. This event exhibited significant extremity in North China in terms of many aspects, such as the duration and accumulated precipitation. Torrential rainfall occurred in many regions, including western Beijing, central and southwest Hebei, with the total accumulated precipitation amount of exceeding 400 mm and even greater than 1 000 mm locally. The extreme precipitation was mostly distributed in the eastern foot of the Taihang Mountains. Based on the evolution characteristics of FY-4A satellite TBB, hourly precipitation, and major impact systems, severe precipitation can be divided into three stages. The first stage had the largest precipitation coverage and accumulated precipitation, while the second stage had the strongest convection with extreme hourly precipitation of over 100 mm·h-1 occurring at several stations. The extremely heavy rainfall event took place under the background of stable circulation with Typhoon residual vortex stagnating after its moving northward. Typhoons "Doksuri" and "Khanun" provided continuous and abundant water vapor and energy. Obvious upper-level divergence and low-level strong convergence provided stable and powerful dynamic conditions. Due to the forced uplift of the eastward airflow along the eastern foothills of the Taihang Mountains, precipitation was increased and sustained.

Topographic variables derived from digital elevation models (DEM) are the most commonly used predictor in soil organic carbon (SOC) prediction. The predictability of these variates for the spatial heterogenity of SOC is influenced by the size of DEM resolution. This paper aimed to investigate the resolution effect of the topography at multiple DEM resolutions and select the most important predictors and the optimal resolution for SOC prediction in a large-scale and morphologically complex area. The study area, covering 15 600 km2, was located in a mountainous province in China. A total of 3901 soil samples and three machine learning algorithms including random forest, gradient boosted regression tree, and artificial neural network were used to construct the SOC predictive models at resolutions of 30, 90, 150, 210, 270, 330, and 390 m. Topographic factors were derived from the DEM with an original resolution of 30 m and were subsequently resampled to varying resolutions by using the bilinear interpolation algorithm. The importance of each variate in each predictive model was computed for the most important predictor selection, and the determination coefficient (R2) and Root Mean Square Error (RMSE) of each predictive model were computed for the accuracy evaluation. Comparative analysis on point-based topographic representation, the accuracy of predictive models, and the variable importance was conducted among different resolutions to investigate the resolution effect on the SOC prediction and to select the optimal resolution for this study area. The results showed that topography was the key factor influencing the SOC distribution in this large-scale area due to the region's mountainous nature, and the relative contribution of the topography to predict SOC distribution varied with DEM resolutions. Elevation was the most important topographic factor at all DEM resolutions. Accuracies of predictive models built on the three machine learning algorithms were all dependent on DEM resolution, indicating that DEM resolution had an important effect on SOC prediction. Overall, the random forest predictive models outperformed the other two algorithms, and its most accurate result was obtained at the 210-m resolution with an R2 of 0.25 and an RMSE of 4.77 g kg–1. In conclusion, we found that finer resolutions did not necessarily produce more accurate SOC predictions even in a large-scale and morphologically complex area. Therefore, investigating the resolution effect is suggested to select an optimal resolution for the SOC prediction in other regions characterized by similar geomorphological conditions as this study area. [ABSTRACT FROM AUTHOR]

The wind environment of a site is one of the important factors affecting the observation performance of large aperture and high-performance radio telescopes. Exploring the relationship between the effects of different terrains on wind flow is important to optimize the wind environment of the site. The terrain of the Qitai radio telescope (QTT) site located in east Tianshan Mountains at an elevation of about 1800 m was used to study the wind flow in the adjacent zone of antenna based on numerical simulation. The area from 600m south to 600m north of the antenna is defined as the antenna adjacent zone, and three groups of boundaries with different terrains are set up upstream and downstream, respectively. Since the zone where the antenna is located is a slope terrain, in order to verify the influence of terrain on the wind flow and to clarify the relationship between the influence of boundary terrain on the wind flow, a control group of horizontal terrain is constructed. The simulation results show that the wind flow is mainly influenced by the terrain. The highest elevation of the upstream and downstream boundary terrains affects the basic wind speed. The upstream boundary terrain has a greater impact on wind flow than the downstream boundary terrain. In addition, the wind speed profile index obtained by numerical simulation is smaller than the actual index for the wind from south. Therefore, the wind speed at the upper level (about 100 m) obtained by inversion based on the measured wind speed at the bottom (about 10 m) is also smaller than the actual wind speed. [ABSTRACT FROM AUTHOR]

[Objective] Rice terraces in the subtropical monsoon region of China are representatives of intensive farming in southern mountainous areas, with various ecosystem service functions. Quantifying their landscape pattern and identifying the impact of major natural factors are key to implementing reasonable protection and achieving sustainable regional development. [Method] Based on ArcGIS spatial analysis technology, the rice terraces in Jiabang, Guizhou, Longji, Hunan, Lianhe and Hani, Yunnan, which were located in the subtropical monsoon mountain area, were taken as the research objects to discuss the impact of natural factors such as topography, soil and lithology on the landscape pattern of rice terraces on the basis of their landscape horizontal and vertical pattern analyses. [ Result] The landscape of various terraced fields mainly included forest land, terraced fields, construction land, water body and unused land, among which the distribution area of terraced fields was Hani > Ziquejie > Jiabang > Longji > Llanhe, and all were concentrated in the central region; The landscape of each terraced field showed a clear hierarchical distribution on the vertical gradient, with the terraced field structure accounting for the largest proportion, followed by forest land, and the village being the smallest; Jiabang, Longji, Ziquejie and Lianhe terraces were mainly distributed in the east, southeast, and south slope directions ( > 60% ) with good light and heat conditions at elevations below 1200 meters ( > 80% ) and slopes from 5 to 24 ° ( > 70% ), while Hani terraces were mainly distributed in the northeast, east, southeast, west and northwest directions ( > 60% ) with relatively flat terrain at elevations below 1900 meters ( > 90% ) ; Hani and Ziquejie terraces were mainly composed of gneiss ( 59. 04%) and granite ( 89. 65%) with good water storage capacity, respectively. The combined terraces were mainly composed of rhyolite ( 40. 27%) with medium water retention capacity, while Jiabang and Longji rice terraces were mainly composed of sandstone (79. 84% and 51. 74%) with strong water permeability; Red soil, yellow soil and paddy soil were the main soil types of Hani, Jiabang, Longji, Ziquejie and Lianhe terraced landscape, and 78. 2%, 97. 8%, 71. 63%, 87. 66% and 99. 9% terraced fields were developed in each terraced landscape. [ Conclusion] The study aimed to further explore the main factors affecting the spatial distribution of subtropical monsoon rice terraces and provide important references for the future development, utilization and protection of terraces. [ABSTRACT FROM AUTHOR]

Physically, river floodplains have both the subdued morphology of natural terrain created as extreme discharges and sediments pass through catchment drainage systems and, to an increasing extent, the forms that arise from purposeful human constructions. Together, these direct out-of-channel inundation. As defined here, 'territories' and their humanly constructed physical forms have historically consumed or modified naturally created 'terrains' in a collection of actions that we summarize as 'morphophagia'. A more inclusive physical geography is presented, adding-in explanations for the evolutionary phasing of humanly-generated, but environmentally functioning, physical forms in the UK in the Modern Era (since c.1500 CE). Floodplain developments here took place in five main episodes of historically-contingent accumulation: the Early Modern (c.1500–1780 CE) started with a framework of purposeful owned land, and then followed periods that can be related to Kondratieff global economic phases (c.1790–1840,1840–1900,1900–1947,1947–2000 CE). Three different groups of forcings operated: (1) the compartmentalizing and patched infill patterns set by territorial units, rights and developer ownerships; (2) the availability, motivations and timings for capital and labour investment; and (3) the evolving technical possibilities exploited by entrepreneurs and agents. Epistemic frameworks for broadening the analysis of coupled terrain and territory systems, exploring actuating social forces as much as their symptomatic physical outcomes, are discussed. Globally, there have been different forcings, timings and emplacement layouts operating at scales from local river reaches to city expansion and economic regions. As perceptions of environmental stasis now disintegrate, enthusiasm for reinvigorating economic growth, with further population increase and sprawling construction may, as in the past, discount the hazards of floodplain occupation. When and why risky anthropo-physical floodplain emplacements occur needs greater systematic understanding as social and economic initiatives are being considered. [ABSTRACT FROM AUTHOR]

Trees, woods, and forests impact on warfare through their roles as terrain, and as important or even essential resources. Furthermore, since ancient times, access to the resources provided by forests has been the direct cause of major conflicts (Rotherham, 2024). For early civilisations as in the Mediterranean region for instance, the loss of forest resources through over-exploitation or conquest from outside, could cause collapse (Perlin, 1989). Indeed, as regional timber resources were exhausted and supply-lines to necessary forests became over-extended, there was inevitable strain on social and economic or political structures. Woods and forests also provided essential resources for the successful waging of war and for the undertaking of military campaigns, and this was the case from antiquity and certainly up until the First World War (Cana, 1920; Rotherham, 2024; Pearson et al., 2010).Along with trees, woods, and forests as resources, forested landscapes have influenced conflicts through their roles as the settings within which military campaigns were implemented (Cana, 1920; Clayton, 2012). Forested countryside has proved critical in tipping the balance of conflict between, for example, native, indigenous peoples and external forces often unfamiliar with the local terrain. The forest influences the type of warfare waged and the nature of resistance to invasion by external forces. Indeed, history is populated by examples whereby superior, external, military forces have been unable to suppress or remove much smaller and technologically inferior communities fighting from a forested homeland (Grunwald, 2006; Perrett, 1990).Finally, all the above-mentioned factors result in warfare impacting of forested countryside when a conflict takes place. This impact occurs for various and varied reasons from simple over-exploitation of the resources for fuel, construction, or other uses, or because in times of conflict the usual processes governing the uses of forest resources break down (Pearson, 2012; Matteson, 2015). A result may be a long-term impact of forest or woodland degradation because of the short-term over-utilization during conflicts.These issues are explored with examples to illustrate the processes and consequences of forested countryside influencing warfare, and the impacts of war on trees, woods, and forests.

Urban ecosystem is an intricate agglomeration of human, fauna and flora populations coexisting in natural and artificial environments. As a city develops and expands over time; it may become unbalanced, affecting the quality of ecosystem and urban services and leading to environmental and health problems. Fine particulate matter (particulate matter with aerodynamic diameter ≤2.5 μm - PM2.5) is the air pollutant posing the greatest risk to human health. Quito, the capital city of Ecuador, exhibits a high occurrence of exposure to unhealthy levels of PM2.5 due to a combination of natural and social variables. This study focused on three central parks of this high elevation city, investigating the spatial distribution of PM2.5 concentrations. The particle pollution was then modeled using Normalized Difference Vegetation Index (NDVI). Hazardous instantaneous levels of PM2.5 were consistently found on the edges of the parks along busy avenues, which are also the most frequented areas. This raises concerns about both short- and long-term exposures to toxic traffic pollution in recreational areas within urban dwellings in the global south. The NDVI model successfully predicted the spatial concentrations of PM2.5 in a smaller urban park, suggesting its potential application in other cities. However, further research is required to validate its effectiveness.

The article is devoted to the influence of terrain, landscapes, and meteorological conditions on the establishment of air quality monitoring points in the relevant territory of the Lviv region. The main factors affecting the distribution of the concentration of pollutants in atmospheric air during the design of air monitoring stations have been determined. It was established that the level of the surface concentration of pollutants increases with an increase in the power of the emission source, the density, and size of impurity particles, and decreases with an increase in the height and radius of the orifice of the emission source, the temperature of the emission, and the rate of release of impurities from the source.

The development of wheeled ground robots has enabled them to be used for a variety of tasks. These robots must be able to move with accuracy and precision, especially when faced with obstacles or inclines. To improve the movement of these robots on a slope, lidar data can be used to detect the location and shape of obstacles. In recent years, Lidar technology has become an essential tool for various robotic applications. It has proven to be a game-changer in the field of autonomous navigation, especially in situations where robots have to operate in unknown environments. Lidar technology provides a high-resolution 3D map of the environment around the robot, enabling it to navigate autonomously while avoiding obstacles. In this paper, we discuss the use of Lidar technology in improving the movement of a wheeled ground robot on a slope. We describe the steps involved in obtaining Lidar data, processing the data to create a 3D map of the environment, and using the map to plan more efficient movement of the robot. We present an applied example of how Lidar data improves the movement of a ground robot with wheels on a slope, calculating the inclination of the ground, calculating the force required for the movement of the robot, creating three-dimensional models of the terrain to be navigated, creating plans for more efficient movement, and reducing damage and wear of the robot.

The purpose of the paper is to study the mechanism of the interaction between super low-level jet and terrain to enhance rainstorm. Using the surface observation precipitation data of Liaoning Province and ERA5 reanalysis data, this paper analyzes a sudden mountain rainstorm that occurred in the Changbai Mountains, eastern Liaoning Province on the night of 14 July 2021, focusing on the role of flow around and flow over in this rainstorm. The results show that: (1) under the favorable circulation background of the southeast of the Northeast Cold Vortex and the rear of the Subtropical High, the southward low-level jet and super low-level jet are established, which brings abundant water vapor and energy to the eastern part of Liaoning. The periodic change of precipitation is related to the intensity, location and direction of low-level jet. (2)The terrain height difference in the transition area of the mountain plain forces the airflow to generate the flow over. The vertical ascent forced by the flow over gradually weakens from bottom to top. The maximum value area is located on the mountain slope. The extremum center of regional flow over is located in the center of the rain belt, and the flow over caused by terrain is specially important to the range and intensity of the precipitation. (3)The east-west direction-dominated flow around has a certain contribution to the formation of the local vortex in the rainstorm area, and the surrounding flow plays a role in converging the warm moist current in the precipitation center, and indirectly provides an amplification effect for the air upraise. Under the combined action of flow over and flow around, the upswing branch of secondary circulation in the sloping area triggers convective development and releases unstable energy, which leads to the occurrence of local heavy rainstorms in mountainous areas.

L’engouement pour la recherche en contexte autochtone a fait en sorte que des balises formelles ont été implantées pour encadrer la venue des chercheurs dans les communautés. Bien que bienvenue, cette implantation ne s’est pas faite sans une bureaucratisation accrue des relations de recherche. Il appert que de nombreuses communautés autochtones, dont les ressources sont limitées, ne sont pas bien outillées pour faire face aux impératifs administratifs préconisés par les protocoles en recherche autochtone. Partant d’expériences de recherche anthropologique de terrain en contexte innu, le présent article montre comment des relations de recherche respectueuses ont pu être implantées en dehors du cadre bureaucratique et administratif généralement préconisé par les protocoles de recherche. Le cœur de cette démarche se situe dans la participation radicale du chercheur à la vie sociale et plus particulièrement à la prise au sérieux des prémisses de socialité des personnes avec qui il travaille. L’erreur serait de penser que cette démarche de collaboration se situe dans l’informalité : elle se situe plutôt dans un cadre éminemment formel qui correspond aux critères et valeurs des collaborateurs autochtones du chercheur.

This paper presents performance improvements for Ellipsoid Clipmaps, an out-of-core planet-sized geodetically accurate terrain rendering algorithm. The performance improvements were achieved by eliminating unnecessarily dense levels, more accurate block culling in the geographic coordinate system, and more efficient rendering methods. The elimination of unnecessarily dense levels is the result of analyzing and determining the optimal relative height of the viewer with respect to the most detailed level, resulting in the most consistent size of triangles across all visible levels. The proposed method for estimating the visibility of blocks based on view orientation allows rapid block-level view frustum culling performed in data space before visualization and spatial transformation of blocks. The use of a modern geometry pipeline through task and mesh shaders forced the handling of extremely fine granularity of blocks, but also shifted a significant part of the block culling process from CPU to the GPU. The approach described achieves high throughput and enables geodetically accurate rendering of the terrain based on the WGS 84 reference ellipsoid at very high resolution and in real time, with tens of millions of triangles with an average area of about 0.5 pix2 on a 1080p screen on mid-range graphics cards.

The enthusiasm for research in an Indigenous context has led to the introduction of formal guidelines for researchers to visit communities. While welcome, this has not been achieved without increased bureaucratization of research relationships. It appears that many Indigenous communities, with their limited resources, are ill-equipped to deal with the administrative imperatives of Indigenous research protocols. Based on the experiences of anthropological field research in the Innu context, this article shows how respectful research relationships could be established outside the bureaucratic and administrative framework generally advocated by research protocols. The heart of this approach lies in the researcher􀂶s radical participation in social life, and more specifically in taking seriously the social premises of the people with whom he works. The mistake would be to think that this collaborative approach is situated in informality: rather, it takes place within an eminently formal framework that corresponds to the criteria and values of the researcher􀂶s Indigenous collaborators. [ABSTRACT FROM AUTHOR]

The use of a Machine Learning (ML) classification algorithm to classify airborne urban Light Detection And Ranging (LiDAR) point clouds into main classes such as buildings, terrain, and vegetation has been widely accepted. This paper assesses two strategies to enhance the effectiveness of the Deep Learning (DL) classification algorithm. Two ML classification approaches are developed and compared in this context. These approaches utilize the DL Pipeline Network (DLPN), which is tailored to minimize classification errors and maximize accuracy. The geometric features calculated from a point and its neighborhood are analyzed to select the features that will be used in the input layer of the classification algorithm. To evaluate the contribution of the proposed approach, five point-clouds datasets with different urban typologies and ground topography are employed. These point clouds exhibit variations in point density, accuracy, and the type of aircraft used (drone and plane). This diversity in the tested point clouds enables the assessment of the algorithm's efficiency. The obtained high classification accuracy between 89% and 98% confirms the efficacy of the developed algorithm. Finally, the results of the adopted algorithm are compared with both rule-based and ML algorithms, providing insights into the positioning of DL classification algorithms among other strategies suggested in the literature. [ABSTRACT FROM AUTHOR]

Atmospheric conditions and terrain are representative elements of radar operating environments. The radar operating environment varies depending on the installation location and changes radar performance. In the case of the atmospheric condition, it changes every moment and changes radar performance, so it is not easy to supplement radar performance by reflecting it in real time. On the other hand, in the case of terrain, when radar is installed, the surrounding terrain information does not change significantly, so radar performance can be supplemented through analysis. In this paper, the radar performance variation was analyzed according to the beam steering angle reflecting the atmospheric measurement data of the past five years using the M&S analysis tool. As a result, when the beam was raised by 0.3° compared to the original angle, the maximum detection range increased by about 7.1 NM, and the standard deviation was reduced by about 1.2 NM. [ABSTRACT FROM AUTHOR]

Satellite imagery-based solar irradiance mapping studies are essential for large-scale solar energy assessments but are limited in spatial resolution and accuracy. Despite efforts to increase map resolution by correcting inaccuracies caused by shadows on the terrain, the computational time of these models and the massive volume of generated data still pose challenges. Particularly, forecasting generates large amounts of time series data, and the data production rate is faster than the computational speed of traditional terrain correction. Moreover, while previous research has been conducted to expedite computations, a novel and innovative technology in terrain correction is still required. Therefore, we propose a new correction method that can bypass complex calculations and process enormous data within seconds. This model extends the lookup table concept, optimizes the results of many shadow operations, and stores them in memory for use. The model enabled 90 m scale computations across Korea within seconds on a local desktop computer. Optimization was performed based on domain knowledge to reduce the required memory to a realistic level. A quantitative analysis of computation time was also conducted, revealing a previously overlooked computational bottleneck. In conclusion, the developed model enables real-time terrain correction and subsequent processing of massive amounts of data. [ABSTRACT FROM AUTHOR]

Based on high-altitude observational data, Zhejiang Doppler radar products, and ERA5 hourly reanalysis data (0.25 °×0.25 °), the present study analyzed the spatial and temporal distribution, life cycle, and environmental parameters of local thermal convection (classified into localized moving convection and localized anchoring convection according to moving speed) in the afternoon under the background of weak synoptic-scale forcing in summer (from June to August) in Zhejiang from 2015 to 2021. The results show that: (1) The triggering frequency of the two types of thermal convection is the same, and the interannual variation is large, but the annual, monthly and daily variation trends are basically the same. Localized anchoring convection easily occurs in the afternoon while localized moving convection easily occurs in the evening. (2) The triggering of local thermal convection is closely related to the terrain. The high-frequency area is located in the coastal areas of eastern, northwestern, and southwestern mountainous areas in Zhejiang while the low-frequency area is located in the plain and basin in central and northern Zhejiang. The triggering frequency of thermal convection decreases with the increase in height, which is mostly triggered at the middle and low altitudes in the mountains and nearby. It is easier to trigger localized anchoring convection in the mid- and high-altitude areas. (3) Both types of convection can be triggered in the environment of weak vertical wind shear, and localized moving convection is easier to develop. [ABSTRACT FROM AUTHOR]