Search

While the past of terrain cannot be known precisely because an effect can result from many different causes, exploring these possible pasts opens the way to numerous applications ranging from movies and games to paleogeography. We introduce unerosion, an attempt to recover plausible past topographies from an input terrain represented as a height field. Our solution relies on novel algorithms for the backward simulation of different processes: fluvial erosion, sedimentation, and thermal erosion. This is achieved by re‐formulating the equations of erosion and sedimentation so that they can be simulated back in time. These algorithms can be combined to account for a succession of climate changes backward in time, while the possible ambiguities provide editing options to the user. Results show that our solution can approximately reverse different types of erosion while enabling users to explore a variety of alternative pasts. Using a chronology of climatic periods to inform us about the main erosion phenomena, we also went back in time using real measured terrain data. We checked the consistency with geological findings, namely the height of river beds hundreds of thousands of years ago. [ABSTRACT FROM AUTHOR]

The collection mechanism inside the cloud is associated with the coalescence process. It controls the rainfall rate in the presence of high moisture content and low cloud condensation nuclei concentrations. The effectiveness of the coalescence mechanism is determined by the magnitude of the coalescence efficiency. This study compared the effectiveness of six coalescence efficiencies to identify the appropriate formulation, which can simulate the cloudburst event of 10 June 2021 over Sauni Binsar, Uttarakhand, at 11:45 IST (06:15 UTC). The coalescence efficiencies have been estimated between the lifting condensation levels and freezing levels over 100 equidistance intervals, with variation in the bins of colliding droplet pairs. The comparative analysis shows that Ochs’s formulation estimated high values of coalescence efficiencies ranging between 60 and 100% for all bins of droplet diameters during the cloudburst event. The maximum values of coalescence efficiency were found to be high for small cloud droplet diameter of 1–100 µm for collector droplet diameter of 50–7000 µm. The estimates provided by Seifert and Chen and Liu were below 80%, while Low and List, Beard and Ochs estimated coalescence efficiency values of up to 70% for all-collector cloud droplet diameters and small cloud droplet diameters. However, the estimated coalescence efficiencies by Brazier–Smith formulation are very low, not exceeding 20%, for all collector cloud droplet diameters and small cloud droplet diameters. The selection of appropriate coalescence parametrization is essential for appropriately simulating rainfall intensities using microphysics parametrization during extreme weather events. Research highlights: The coalescence process plays an important role in determining rain rate, and modelling it is a challenge. Six coalescence efficiencies have been estimated for the cloud burst event of Sauni Binsar, Uttarakhand, India. Ochs’s formulation estimated high values of coalescence efficiencies ranging between 60 and 100% for all bins of droplet diameter, which was expected. Seifert and Chen and Liu formulations estimated coalescence efficiencies below 80%, and Low and List and Beard and Ochs estimated coalescence efficiency up to 70% for the all-collector cloud droplet diameter and small cloud droplet diameter. The estimated coalescence efficiencies by Brazier–Smith formulation are very low, not exceeding 20%. [ABSTRACT FROM AUTHOR]

Leaf Area Index (LAI), as a pivotal parameter in characterizing the structural properties of vegetation ecosystems, holds significant importance in assessing the carbon sink function. Given the availability of multiple long-term LAI products, validating these LAI products with consideration of topographic factors is a prerequisite for enhancing the quality of LAI products in mountainous areas. Therefore, this study aims to evaluate the performance of MODIS LAI and GLASS LAI products from 2001 to 2021 by comparing and validating them with ground-measured LAI data, focusing on the spatio-temporal and topographic aspects in the Qinling Mountains. The results show that the GLASS LAI product is a better choice for estimating LAI in the Qinling Mountains. The GLASS LAI product has better completeness and generally higher values compared to the MODIS LAI product. The time-series curve of the GLASS LAI product is more continuous and smoother than the MODIS LAI product. Both products, however, face challenges in quantifying LAI values of evergreen vegetation during winter. The MODIS and GLASS LAI products exhibit differences between sunny and shady slopes, with mean LAI values peaking on sunny slopes and reaching their lowest on shady slopes. When the slope ranges from 0 to 10°, the mean values of GLASS LAI product show a higher increasing trend compared to the MODIS LAI product. At elevations between 1450 and 2450 m, the mean LAI values of the GLASS LAI product are higher than the MODIS LAI product, primarily in the southern Qinling Mountains. Compared to ground-measured LAI data, the GLASS LAI product (R² = 0.33, RMSE = 1.62, MAE = 0.61) shows a stronger correlation and higher accuracy than the MODIS LAI product (R² = 0.24, RMSE = 1.61, MAE = 0.68). [ABSTRACT FROM AUTHOR]

Soil degradation can negatively impact its physical and chemical properties over the long term. We investigated the natural recovery of physical properties of disturbed soils on an abandoned machine operating trail in a deciduous mountain forest in northern Iran. The machine operating trail hadn't been used for the last 20 years. Dry bulk density and total porosity were assessed for three levels of traffic intensity (light, moderate, and heavily trafficked trails) and two levels of slope gradients (gentle, ≤20%, and steep, >20%), in four different soil depths (0–10, 10.1–20, 20.1–30, and 30.1–40 cm) as well as in undisturbed (control) areas. Over the course of the 20-year recovery period, it was observed that in the depth intervals of 0–10, 10.1–20, 20.1–30, and 30.1–40 cm, trails subjected to heavy traffic on gently sloping terrain displayed mean values that exhibited an increase of 78%, 62%, 55%, and 47% in bulk density, respectively, and a decrease of 27%, 26%, 28%, and 27% in total porosity, respectively, when compared to undisturbed soil. In the case of steep slopes, analogous assessments indicated an increase of 82%, 69%, 39%, and 31% in bulk density, respectively, and a reduction of 28%, 29%, 26%, and 24% in total porosity, respectively, within the aforementioned depth intervals. However, in the case of lightly trafficked trails situated on gentle slopes, there was a discernible amelioration in surface soil compaction. Our findings consequently suggest that the natural recovery of soil physical properties in the study area extends beyond the examined timeframe of twenty years. [ABSTRACT FROM AUTHOR]

Land scarcity in most cases hampers development and encourages the misuse of land. The suitability of land must be considered before appropriating or allocating land for any use. Land supports the livelihood of every being on the Earth and therefore determines survival, success, and sustainability (sustainable living). This study aimed at integrating remote sensing and GIS-based analysis to determine the rate at which built-up areas have spread across the terrain of Onitsha Metropolis, Anambra State, Nigeria, and the dynamics of other land uses. This research involved both primary and secondary data. The primary data included measurements, direct field observations, and key informant interviews to understand people's perceptions of the land use in the area. The secondary data included satellite images of the area obtained from USGS and analyzed using ArcGIS 10.2 for variations in the terrain of the Onitsha Metropolis; to determine the land use and land cover change (LULCC) of the Onitsha Metropolis over 40 years, published and unpublished articles and books were also consulted. The geological analysis of the study showed that the area of the Ogwashi/Asaba formation is 318.57 km2; the areas of the Nanka sands and Bende-Ameke are 423.07 km2 and 259.42 km2, respectively. The Nanka sands and Bende-Ameke formations are best suited for engineering construction purposes, while the Ogwashi/Asaba formation is suitable for agriculture and should be designated as a buffer zone or park. However, due to the unavailability of land as a result of the growing population and the proximity of the area to the city center, the area is being encroached upon, and a large area (about 30.40%) has been converted to built-up areas as of 2022. Forecast analysis showed that if the trend continues, 158.28 km2 (49.68%) of the alluvium soils of the Ogwashi/Asaba formation will be covered with buildings by 2072. The geology and the terrain of the Onitsha Metropolis determine the soil characteristics and the land use suitability; mapping the geological formations and overlaying these with the land use and land cover change of the area revealed the extent of the encroachment on the Ogwashi/Asaba formation, which must be discouraged. [ABSTRACT FROM AUTHOR]

Introduction. A flight visibility model is presented that takes into account the nature of the underlying surface, the height of the flat terrain, and the dynamics of the aircraft flight due to changes in altitude and ground speed during aerial work. Materials and Methods. Hourly microring weather maps of the Central Russian Plain of the Moscow air hub were used. The research methodology is based on constructing a flight visibility model, taking into account the factors influencing it, including the terrain and the nature of the underlying surface. Results and their Discussion. Flight visibility significantly depends on the nature of the underlying surface, as well as on the elevation of the terrain relative to the departure point at a distance of up to 150 km. The influence of the elevation of the terrain relative to the departure point is 30% more significant than the influence of the nature of the underlying surface. Conclusions. The use of the constructed flight visibility model, which takes into account the influencing physical and geographical conditions, the nature of the underlying surface, the height of the relief of flat terrain under low clouds, will make it possible to make weather-dependent decisions through the use of an intelligent meteorological system, which leads to the improvement of meteorological support for flights during aviation operations.

The Land surface of the Sichuan Basin is characterized by complexity and diversity， with frequent occurrences of heavy rainfall.This study utilizes global reanalysis data from the U.S.National Centers for Environmental Prediction and various categories of land use data， including default land use data from the WRF model， MODIS （Moderate Resolution Imaging Spectroradiometer）， and USGS （United States Geological Survey）.Additionally， the 2015 LUCC2015 （Land use datasets in China 2015） datasets and the 2015 GLASS （Global Land Surface Satellite） land use datasets are incorporated.The WRF（Weather Research and Forecasting）model is used to simulate a heavy rainfall event in Sichuan Province.The impact of changes in land surface classification and variations in terrain height on heavy rainfall is discussed through four sets of land use experiments and two sets of terrain sensitivity experiments.The results indicate that the experiments involving different land use types have a significant impact on regions experiencing heavy precipitation.In comparison to the MODIS experiment， the precipitation distribution from the USGS experiment is more concentrated， with a larger coverage area for intense precipitation centers； the LUCC2015 experiment results in a reduction in rainfall intensity in the northeastern part of the Sichuan Basin， accompanied by a more concentrated precipitation distribution； the GLASS experiment simulation， characterized by a relatively uniform land use， results in a reduction in the intensity of both intense precipitation centers.Additionally， the precipitation centers in the northeastern part of Sichuan shift southward.Various land use types also exert influence on near-surface meteorological parameter fields.Through a comprehensive analysis of the various land use experiments， it is evident that a reduction in urban built-up areas results in a decrease in 2 m temperature by 0.5 to 1 ℃； the reduction in vegetation coverage results in an increase in 2 m temperature and an enhancement of 10 m wind speed； the decrease in surface roughness leads to a significant enhancement in 10 m wind speed， with a magnitude of change ranging from 2 to 4 m·s-1.Compared to the default land use types in WRF， the simulated results under the underlying surface types in the LUCC2015 experiment are better.The topography exerts a pronounced influence on heavy rainfall.Following the reduction in elevation of the western mountainous region in the basin， the absence of mountain barriers allows for a more abundant presence of lower-level water vapor and energy.Consequently， moisture and energy can be transported to more northern regions of Sichuan.With the reduction in elevation of the terrain， the low-level airflow intensifies convergence ahead of the mountains， triggering stronger upward motion of air and resulting in enhanced precipitation intensity.This phenomenon leads to a westward shift in the precipitation location and a more concentrated coverage of rainfall.Conversely， with the uplift of the terrain， the mountainous barrier impedes the entry of warm and moist airflow from the south.As a result， energy and moisture become more dispersed， causing a reduction in airflow convergence in the western and eastern parts of the basin.The weakening of low-level airflow ascent leads to a decrease in precipitation intensity and a more dispersed distribution of rainfall.

Raindrop size distribution （RSD） is fundamental in understanding the precipitation microphysics and quantitative precipitation estimation， especially in complex terrain with complicated rainfall mechanism and high spatial and temporal variability.In this paper， the RSD characteristics of different rainfall rates and rain types in the mountainous and plain areas of the Ili River Valley during the summer of 2020 -2022 are investigated using Parsivel2 disdrometer.The results show that the precipitation in the mountainous and plain areas is mainly composed of small raindrops， and medium raindrops are the largest contribution to the rainfall rate R.Precipitation in the mountainous and plain areas mainly occurs during the late afternoon and early evening， and the concentration of large and medium-sized raindrops is higher in the mountainous areas in all time periods.The spectral width and the concentration of drops with diameters increase with increasing rainfall rate.The number concentration of medium and large particles in the mountainous areas is obviously higher than that in the plain areas during light rain and heavy rain.For the same rainfall rate and rain type， precipitation in the mountainous areas has higher mass-weighted mean diameter （Dm） and lower normalized intercept parameter （log10Nw）.In addition， the convective rain spectrum in the mountainous and plain areas of the Ili River Valley tend to be “continental-like convective cluster”.It is found that there are also significant differences in the μ-Λ relationship and Z-R relationship of precipitation between the two areas， and the empirical relationship of Z =300R1.40 clearly overestimates precipitation.The results reveal the microphysical characteristics of precipitation under different terrain conditions in the Ili River Valley， and provide a reliable factual basis for the subsequent retrieval of precipitation using radar data.

Filtering approaches on Global Ecosystem Dynamics Investigation (GEDI) data differ considerably across existing studies and it is yet unclear which method is the most effective. We conducted an in‐depth analysis of GEDI's vertical accuracy in mapping terrain and canopy heights across three study sites in temperate forests and grasslands in Spain, California, and New Zealand. We started with unfiltered data (2,081,108 footprints) and describe a workflow for data filtering using Level 2A parameters and for geolocation error mitigation. We found that retaining observations with at least one detected mode eliminates noise more effectively than sensitivity. The accuracy of terrain and canopy height observations depended considerably on the number of modes, beam sensitivity, landcover, and terrain slope. In dense forests, a minimum sensitivity of 0.9 was required, while in areas with sparse vegetation, sensitivity of 0.5 sufficed. Sensitivity greater than 0.9 resulted in an overestimation of canopy height in grasslands, especially on steep slopes, where high sensitivity led to the detection of multiple modes. We suggest excluding observations with more than five modes in grasslands. We found that the most effective strategy for filtering low‐quality observations was to combine the quality flag and difference from TanDEM‐X, striking an optimal balance between eliminating poor‐quality data and preserving a maximum number of high‐quality observations. Positional shifts improved the accuracy of GEDI terrain estimates but not of vegetation height estimates. Our findings guide users to an easy way of processing of GEDI footprints, enabling the use of the most accurate data and leading to more reliable applications. Plain Language Summary: The Global Ecosystem Dynamics Investigation (GEDI) collected terrain and canopy observations using laser altimetry. The quality of terrain and canopy observations is influenced by acquisition conditions and land (cover) characteristics. Consequently, a considerable amount of GEDI observations is discarded as noise, and further filtering is necessary to retain only high‐quality observations. Our objective was to assess how environmental and acquisition characteristics influence the accuracy of terrain and canopy height of GEDI observations. Although the main objective of the GEDI mission was to map forests, we also focused on grasslands. GEDI serves not only as an essential source of information on canopy height but also provides accurate terrain observations. Furthermore, it is important to know that GEDI does not overestimate the height of low vegetation as this can result in an overestimation of carbon storage. We distinguished four steps in the GEDI data processing: (a) removal of noise observations, (b) removal of low‐quality data, (c) effect of additional acquisition characteristics, and (d) mitigation of geolocation error. We found that the accuracy of terrain and canopy height observations depended considerably on the number of detected modes, beam sensitivity, landcover, and terrain slope. Key Points: Terrain is crucial for estimates of canopy height, however only 20%–30% of footprints have an absolute error of terrain estimates <3 mThe quality of terrain and canopy height estimates depends on the interplay of number of modes, sensitivity, land cover, and terrain slopeNoise and low‐quality footprints can be successfully removed using number of modes, sensitivity, quality flag and difference from TanDEM‐X [ABSTRACT FROM AUTHOR]

Avalanches are natural events that can lead to significant risks to both human life and property. The creation of an avalanche susceptibility map is a valuable tool for effectively managing the avalanche prone areas. The primary objective of this paper is to utilize and analyse machine learning models for susceptibility mapping, with the goal of classifying avalanche-prone regions based on terrain parameters extracted from a digital elevation model. In other word, to explore the capability of Tree-based machine learning methods to handle the GIS dataset. Fifteen data layers have been extracted, stacked, and processed to create training and testing data using the avalanche inventory. Three tree-based machine learning models has been trained and tuned using grid search on dataset that has been split into 80:20 for model calibration and validation. Results indicated that both advanced models had an excellent performance in terrain-based avalanche modelling (ROC-AUC > 85%), although true positive and true negative analysis demonstrated the superior performance of Random Forest. Feature importance analysis indicated that elevation and aspect are the top effective and most common feature among all the variables and models, respectively. Building a high-quality and informative database is a crucial part, and avalanches inventory classification before susceptibility assessment is a key step in enhancing the accuracy of the model. The study's findings can offer valuable insights for land use planning, enabling the control of avalanche paths and mitigating potential hazards. Additionally, these results can serve as a valuable reference for future studies focused on snow avalanche hazards modelling. [ABSTRACT FROM AUTHOR]

Exploring the impact of climate factors on vegetation phenology is crucial to understanding climate–vegetation interactions as well as carbon and water cycles in ecosystems in the context of climate change. In this article, we extracted the vegetation phenology data from 2002 to 2021 based on the dynamic threshold method in the source region of the Yangtze and Yellow Rivers. Trend and correlation analyses were used to investigate the relationship between vegetation phenology and temperature, precipitation and their spatial evolution characteristics. The results showed that: (i) From 2002 to 2021, the multi-year average start of growing season (SOS), end of growing season (EOS) and length of growing season (LOS) for plants were concentrated in May, October and 4–6 months, with a trend of 4.9 days (earlier), 1.5 days (later), 6.3 days/10 a (longer), respectively. (ii) For every 100 m increase in elevation, SOS, EOS and LOS were correspondingly delayed by 1.8 days, advanced by 0.8 days and shortened by 2.6 days, respectively. (iii) The impacts of temperature and precipitation on vegetation phenology varied at different stages of vegetation growth. Influencing factors of spring phenology experienced a shift from temperature to precipitation, while autumn phenology experienced precipitation followed by temperature. (iv) The climate factors in the previous period significantly affected the vegetation phenology in the study area and the spatial variability was obvious. Specifically, the temperature in April significantly affected the spring phenology and precipitation in August widely affected the autumn phenology. [ABSTRACT FROM AUTHOR]

Copyright of Plateau Meteorology is the property of Plateau Meteorology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Plateau Meteorology is the property of Plateau Meteorology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aeolian sand hazards are often a threat to culverts, which are important channels and pieces of infrastructure of the desert railway. In addition to wind speed, wind direction, and culvert structure, terrain may also be an important reason for the formation of culvert sand hazards. However, there are few studies on the effect of terrain on the sediment accumulation characteristics of culverts. This paper established computational fluid dynamics (CFD) models of railway culverts (flat and concave culverts) based on Euler's two-fluid theory. An analysis of the influence of terrain on the distribution law of the flow fields and sand accumulation around railway culverts was carried out. The results show that the horizontal wind speed curves changes in a "W" shape along the centre axis surface from the forecourt to the rearcourt within a range of 30 m~66.8 m. Low-speed backflow is formed at the inlet and outlet of the culvert, and the minimum wind speed reaches −3.6 m/s and −4.2 m/s, respectively, when the height from the bottom of the culvert is 1.0 m and 1.5 m, resulting in intensified sand sedimentation. In concave culverts, the lower the roadbed height, the easier it is for sand to accumulate at the culvert outlet, the rearcourt, and the track; the sand volume fraction is close to 0.63, affecting the normal operation of the trains. On the contrary, the higher the roadbed, the easier it is for sand to accumulate at the culvert inlet, hindering the passage of engineering vehicles and reducing the function of the culverts. These results reveal that terrain plays a pivotal role in the sand accumulation around culverts and that it should be one of the key considerations for the design of new railway culverts. This work can provide a theoretical basis for preventing and managing sand hazards in railway culverts. [ABSTRACT FROM AUTHOR]

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]

The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission, spanning the past five years, has collected extensive three-dimensional Earth observation data, facilitating the understanding of environmental changes on a global scale. Its key product, Land and Vegetation Height (ATL08), offers global land and vegetation height data for carbon budget and cycle modeling. Consistent measurement accuracy of ATL08 is crucial for reliable time series analysis. However, fluctuations in the temporal accuracy of ATL08 data have been ignored in previous studies, leading to unknown uncertainties in existing time-series analyses. To bridge the knowledge gap, this study analyzes 59 months of ATL08 version 006 data in Finland to assess terrain and surface height accuracy, with a focus on temporal fluctuations across six major land cover types. A random forest (RF) model is employed to quantify the relative importance of error factors affecting height accuracy. Moreover, the study assesses accuracy at two official spatial resolutions, i.e., 100 m × 11 m and 20 m × 11 m, to evaluate the capability of ATL08 for the high-resolution height retrieval. For the terrain, the 100 m segment shows a bias of 0.04 m, a mean absolute error (MAE) of 0.44 m, and a root mean square error (RMSE) of 0.66 m, while the 20 m segment exhibits a bias of 0.10 m, a MAE of 0.35 m, and an RMSE of 0.49 m. For the surface height, the 100 m segment shows a bias of −0.59 m, a MAE of 3.06 m, an RMSE of 4.52 m, a bias% of −3.45 %, a MAE% of 21.26 %, and an RMSE% of 31.40 %. The 20 m segment exhibits a bias of −0.72 m, a MAE of 3.51 m, an RMSE of 5.23 m, a bias% of −5.81 %, a MAE% of 28.52 %, and an RMSE% of 42.47 %. The results indicate that improving segment resolution enhances terrain accuracy but reduces surface height accuracy. According to the error factor analysis, surface coverage and beam type are crucial for terrain retrieval accuracy, with their effects varying over time. Seasonal changes, particularly the presence of snow, affect terrain retrieval accuracy, with the lowest accuracy observed around March each year. This study confirms the critical impact of surface height on its retrieval accuracy and suggests avoiding the use of ATL08 for retrieving low target surface heights, especially in steep terrains. Nevertheless, the analysis affirms the applicability of ATL08 for canopy height estimation in boreal forests, primarily composed of coniferous species, highlighting its potential for extensive spatial and temporal research. This contributes to bridging the gaps between accurate estimates and large area coverage in global carbon budget and cycle studies. Additionally, the findings reveal that similar issues may exist in other satellite laser altimetry missions, emphasizing the important impacts of temporal fluctuations in surface and terrain accuracy when utilizing satellite laser altimetry datasets.

The impact of near-surface observations on analysis and forecasting in complex terrain is studied by introducing the role of terrain in the background error horizontal correlation model. Observation information propagates isotropically on the model level in the height-based terrain-following coordinates since the background error horizontal correlation in CMA-MESO 3DVar system is characterized by an isotropic Gaussian correlation model. However, in the near-surface layer with complex topography, the propagation of observation information is blocked by mountain ranges, and thus its background error covariance is inhomogeneous and anisotropic, and furthermore, the propagation of observation information should vary with topography. The background error horizontal correlation coefficients in complex terrain are computed using NMC method by National Meteorological Center of the USA. Results show that the blocking of large terrain causes the background error horizontal correlation coefficients to decrease more rapidly across mountain ranges, where the near-surface wind field is more localized than the temperature and humidity fields, with smaller horizontal correlation characteristic length scales, and the wind field information propagates over a closer distance. Based on the actual statistical structure, a Gaussian correlation model that includes effects of terrain height and terrain gradient is constructed, and the newly constructed horizontal correlation model accurately characterizes the decrease after mountain ranges are blocked. In CMA-MESO 3DVar analysis, the impact of terrain on the propagation of observational information is effectively incorporated by including a terrain height error term in the background error level correlation model. Idealized experiments show that the horizontal correlation modeling scheme considering the terrain height error term allows the observation information to propagate in an anisotropic manner that varies with terrain height，and significantly reduces the influence of observation information across large terrain features, thereby achieving more reasonable analysis increments. Results of a forecast experiment for a heavy precipitation process in northern China indicate that the correlation modeling scheme varying with the terrain height propagates the anisotropy of the ground observation information and weakens the analytical increment near the ground with large terrain, and thus makes a slightly biased and positive contribution to the precipitation forecast neutrality. Results of a 5-day hourly cycle rapid updating analysis and forecast for precipitation processes in East China show that the horizontal correlation modeling scheme with terrain elevation makes a positive contribution to 10-m wind field at the ground level and the precipitation forecast within 24 hours.

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.

This article proposes to question the relevance and fruitfulness of (re)reading the work of Hannah Arendt in the context of the practices of Philosophy for Children (P4C), in particular with regard to the problematic articulation of singular and plural issues, hindering their political ambition. Generally speaking, Arendt's work is mobilized as much by the opponents as by the defenders of the P4C. Firstly, we will examine three positions which challenge the P4C based on Arendt. This will make it possible to highlight, secondly, three central problems in education and training, and to show how these could be re-examined via Arendtian paradoxology (Tassin, 2018, p. 172). Thirdly, an attempt will be made to reconstruct the political anthropology that Arendt aimed for around amor mundi (love of the world), with a view to proposing a translation into a P4C analysis grid, in school contexts of primary classes (France and Belgium). It is not so much a question of thinking "in the way of" Arendt, as of taking paths that she opened. [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]

Copyright of Recherches en Sciences de Gestion is the property of ISEOR and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

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]

Abstract Filtering approaches on Global Ecosystem Dynamics Investigation (GEDI) data differ considerably across existing studies and it is yet unclear which method is the most effective. We conducted an in‐depth analysis of GEDI's vertical accuracy in mapping terrain and canopy heights across three study sites in temperate forests and grasslands in Spain, California, and New Zealand. We started with unfiltered data (2,081,108 footprints) and describe a workflow for data filtering using Level 2A parameters and for geolocation error mitigation. We found that retaining observations with at least one detected mode eliminates noise more effectively than sensitivity. The accuracy of terrain and canopy height observations depended considerably on the number of modes, beam sensitivity, landcover, and terrain slope. In dense forests, a minimum sensitivity of 0.9 was required, while in areas with sparse vegetation, sensitivity of 0.5 sufficed. Sensitivity greater than 0.9 resulted in an overestimation of canopy height in grasslands, especially on steep slopes, where high sensitivity led to the detection of multiple modes. We suggest excluding observations with more than five modes in grasslands. We found that the most effective strategy for filtering low‐quality observations was to combine the quality flag and difference from TanDEM‐X, striking an optimal balance between eliminating poor‐quality data and preserving a maximum number of high‐quality observations. Positional shifts improved the accuracy of GEDI terrain estimates but not of vegetation height estimates. Our findings guide users to an easy way of processing of GEDI footprints, enabling the use of the most accurate data and leading to more reliable applications.

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.

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.

Land scarcity in most cases hampers development and encourages the misuse of land. The suitability of land must be considered before appropriating or allocating land for any use. Land supports the livelihood of every being on the Earth and therefore determines survival, success, and sustainability (sustainable living). This study aimed at integrating remote sensing and GIS-based analysis to determine the rate at which built-up areas have spread across the terrain of Onitsha Metropolis, Anambra State, Nigeria, and the dynamics of other land uses. This research involved both primary and secondary data. The primary data included measurements, direct field observations, and key informant interviews to understand people’s perceptions of the land use in the area. The secondary data included satellite images of the area obtained from USGS and analyzed using ArcGIS 10.2 for variations in the terrain of the Onitsha Metropolis; to determine the land use and land cover change (LULCC) of the Onitsha Metropolis over 40 years, published and unpublished articles and books were also consulted. The geological analysis of the study showed that the area of the Ogwashi/Asaba formation is 318.57 km2; the areas of the Nanka sands and Bende-Ameke are 423.07 km2 and 259.42 km2, respectively. The Nanka sands and Bende-Ameke formations are best suited for engineering construction purposes, while the Ogwashi/Asaba formation is suitable for agriculture and should be designated as a buffer zone or park. However, due to the unavailability of land as a result of the growing population and the proximity of the area to the city center, the area is being encroached upon, and a large area (about 30.40%) has been converted to built-up areas as of 2022. Forecast analysis showed that if the trend continues, 158.28 km2 (49.68%) of the alluvium soils of the Ogwashi/Asaba formation will be covered with buildings by 2072. The geology and the terrain of the Onitsha Metropolis determine the soil characteristics and the land use suitability; mapping the geological formations and overlaying these with the land use and land cover change of the area revealed the extent of the encroachment on the Ogwashi/Asaba formation, which must be discouraged.

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]

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]

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]

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.

For high spatiotemporal resolution global navigation satellite system interferometric reflectometry (GNSS-IR) snow depth monitoring, addressing terrain effects and multi-GNSS data fusion together is essential due to their coupling. Analyzed multi-GNSS spatiotemporal availability to ensure coverage and revisit rate. Improved data usage and inversion accuracy through complete ensemble empirical mode decomposition. Corrected anisotropic terrain errors using digital elevation model to account for varied reflection footprints. A grid was established for data partitioning and fusion. Considering intersystem errors, the proposed signal peak ratio weighting (PRW) fusion of single-system inversions is based on signal quality. Then, by using inverse distance weighting, the multi-GNSS results were fused, achieving high-accuracy, hourly snow depth inversions with high spatial resolution. With terrain correction, the correlation coefficient (R) reached 0.984, root mean square error (RMSE) 0.136 m, and mean error (ME) –0.060 m, reduced by 9.05% and 24.84%. PRW further enhanced accuracy, increasing R to 0.985, reducing RMSE 14.6% to 0.128 m, improving ME 40.57% to –0.047 m. Grid fusion effectively integrated multi-GNSS data, showing daily R 0.865, RMSE 0.102 m, ME –0.050 m. Across season, R 0.984, RMSE 0.134 m, ME –0.065 m. Compared to equal weighting, R improved 4.72% and 3.05%, RMSE reduced 26.09% and 14.10%, ME decreased 28.57% and 16.44%. Hourly results achieved 94.44% coverage, averaging 5.19 usable tracks, demonstrating effectiveness. Overall, this article presents an end-to-end solution for high spatiotemporal resolution snow depth inversion using GNSS-IR, and the methodology can be extended to other geophysical parameter retrievals.