Specific Terrain Research Articles

Development of an optimal route planning algorithm using hot zones

The authors in the article address the problem of planning optimal routes in a dynamic environment using OpenStreetMap (OSM) geographic data for the territory of Ukraine. Amid conflict situations and active hostilities, there is a need to adapt classical route-finding algorithms to account for specific terrain constraints. The main aim of the research is to develop an adaptive A* algorithm that considers high-risk areas ("hot zones") which can significantly impact the efficiency and safety of the calculated route. To achieve this goal, the authors conducted an analysis of existing shortest path search algorithms using the classic A* algorithm and its heuristic function, which considers the distance between route points. The study explores a modified version of the A* algorithm that includes an additional cost factor for "hot zones." The proposed approach introduces an adaptive multiplier that restricts route planning through dangerous areas. To validate the proposed method, OSM data containing only basic road information, without military restrictions, was used. This limitation highlights the importance of additional analysis of factors such as safety and risk in route planning. The results demonstrate the effectiveness of the developed adaptive A* algorithm in constructing routes in a dynamic environment, particularly with the ability to avoid dangerous ("hot") zones. The study's conclusions confirm that adding a cost factor in "hot zones" improves route accuracy and enhances travel safety. The developed algorithm can be applied to automated route planning in scenarios where it is crucial to consider variable risk factors and specific terrain conditions.

Research on present situation and development of fire strike equipment for mountain operations

Abstract Mountainous areas account for a large proportion in China’s border regions. In view of the special terrain and complex meteorological conditions of mountain warfare, mountain firepower strike equipment has become the core key for our military to deal with border conflicts. In order to adapt to the changes in future mountain warfare and lead its development, this paper summarizes and analyzes the performance characteristics and development history of mountain warfare equipment at home and abroad. Combined with the influence of future mountain warfare forms and battlefield environments, characteristics of active equipment and the application of high and new technologies on mountain warfare, the future development goals of mountain firepower strike equipment are prospected, and the technical research directions of mountain firepower strike equipment are proposed in stages according to the strike equipment system structure.

SA-SatMVS: Slope Feature-Aware and Across-Scale Information Integration for Large-Scale Earth Terrain Multi-View Stereo

Satellite multi-view stereo (MVS) is a fundamental task in large-scale Earth surface reconstruction. Recently, learning-based multi-view stereo methods have shown promising results in this field. However, these methods are mainly developed by transferring the general learning-based MVS framework to satellite imagery, which lacks consideration of the specific terrain features of the Earth’s surface and results in inadequate accuracy. In addition, mainstream learning-based methods mainly use equal height interval partition, which insufficiently utilizes the height hypothesis surface, resulting in inaccurate height estimation. To address these challenges, we propose an end-to-end terrain feature-aware height estimation network named SA-SatMVS for large-scale Earth surface multi-view stereo, which integrates information across different scales. Firstly, we transform the Sobel operator into slope feature-aware kernels to extract terrain features, and a dual encoder–decoder architecture with residual blocks is applied to incorporate slope information and geometric structural characteristics to guide the reconstruction process. Secondly, we introduce a pixel-wise unequal interval partition method using a Laplacian distribution based on the probability volume obtained from other scales, resulting in more accurate height hypotheses for height estimation. Thirdly, we apply an adaptive spatial feature extraction network to search for the optimal fusion method for feature maps at different scales. Extensive experiments on the WHU-TLC dataset also demonstrate that our proposed model achieves the best MAE metric of 1.875 and an RMSE metric of 3.785, which constitutes a state-of-the-art performance.

Hydraulic models of silled orifices and stilling basins in online dams for flood reduction

ABSTRACT Building flood reduction dams for territory protection is very often necessary as it allows the reduction of peak flows during flood events by creating a storage in upstream areas. An online structure with such characteristics is outlined, presenting one or more openings in order to allow normal and moderate flows to pass downstream. A stilling basin is provided downstream of the openings and, on one side of the flooded area, a spillway weir is set. For low river flows, the openings will act as free-surface weirs. The openings are equipped with a sill in such a way to let the discharge independent of the downstream flow conditions. For moderate flood flows, the water level upstream of the dam will rise, and the openings will become submerged, effectively behaving as an orifice arrangement. For large flood flows, the crest of the flood spillway weir is reached and they will be discharged via both the orifice structure and the flood spillway structure. The silled openings and the stilling basin are one only hydraulic complex. Since no examples exist of their behavior as a whole, the aim of this paper is to give the designers the opportunity to size them given the basic requirement of the flood reduction dam, i.e. the max discharge allowed downstream. For this reason, the paper will focus on the opening discharge coefficients, the stilling basin energy dissipation and water level. Both the orifices and the stilling basins were studied starting from the hydraulic models of three dams that were built in Calabria (Italy). The structures of the stilling basins are original. The results appear in dimensionless form and offer useful guidance for similar hydraulic cases, with the exception of specific terrain related issues. Finally, an example of a preliminary design of orifices and stilling basin is presented.

Research Patents on Potato Harvesters

Background: Potato is a major food crop that is widely grown in more than 100 countries around the world. The production of this crop is a labor-intensive process, and its field production mainly includes seed arrangement, seedling cutting, ploughing, ridging, transplanting, field management, and harvesting (vine cutting, digging, cleaning up, and collection). With the improved models, the labor can be reduced to nearly half in the production process of potato. Objective: The objective of this study was to provide a comprehensive description of the classification, characteristics, and development of existing potato harvesters. Methods: In this study, a review on the principle of potato harvesting and related patents has been conducted. We have also introduced the structural characteristics and differences in applications of potato harvesters. Results: The existing potato harvesters have been analyzed and compared in this paper, and the typical characteristics have been summarized. The main problems existing in the development of potato harvesters are analyzed, the development trend of potato harvesters is forecasted, and the research status and future development trend of potato harvesters and patents are discussed. Conclusion: Based on our research, we have found that potato harvesters can be classified into three categories based on the harvesting process, clearing the vine, and harvesting machine. The combine harvester is capable of both clearing the vine and harvesting, and it has been reported to significantly improve the efficiency. However, for special terrain or other conditions not suitable for the combine harvester, the cutting and harvesting machine can perform both the steps. Currently, potato harvesters are not popular at home and abroad, and future development of potato harvesters must focus on them being intelligent, lightweight, and unmanned.

Shaking Table Test Study of Dynamic Response and Failure Mode of Liquefiable Layer Slope Under Earthquake

As a kind of special terrain, the landslide disaster generated by liquefiable layer slopes under earthquake has become a major engineering challenge due to its large scale and long slip distance. In order to study the seismic response and damage mode of liquefiable layer slope, this paper follows the research line of “geological generalization, physical modeling, and result analysis”, and takes the liquefiable layer slope in the upper reaches of the Yellow River Class secondary terrace as the object of study, generalizes the physical model of the slope, and carries out shaking table test. Based on the PGA amplification coefficient, Fourier analysis and HHT time–frequency characterization of the model slope, it was found that the PGA amplification coefficient increases gradually along the slope height, reaches the maximum value at the top of the liquefiable layer and then decreases gradually, which indicates that the liquefiable sand layer has an obvious energy dissipation effect, and on the horizontal direction of model slope is a tendency to the surface effect; the seismic waves at the discontinuous interface change drastically, and the Hilbert time–frequency spectrum transforms from multiple peaks to a single peak; with the increase of the intensity, the intrinsic frequency of the overall model decreases, and the high-frequency component within the liquefiable sand layer decreases from 5–15[Formula: see text]Hz to 0–5[Formula: see text]Hz, indicating that the liquefiable layer has a filtering effect; the damage process of the liquefiable layer slope is the tensile crack at the top of the slope — seismic subsidence at the top of the slope — the shear yielding at the angle of the slope — shear surface penetration at the slope face — overall slope instability and flow-slip damage. The research results will provide a reference for the study of the disaster mechanism of the liquefiable layer slope.

Transport Characteristics and Potential Source Areas of PM2.5 in Yangquan City Under Different Pollution Levels

Based on the PM2.5 monitoring data, NCEP data, and the meteorological data of the weather situation analysis at the corresponding time in Yangquan City from 2020 to 2022, using the HYSPLIT4 backward trajectory model, multi-station potential source contribution factor analysis （MS-PSCF） and trajectory density analysis （TDA） were introduced to study the differentiation and classification of PM2.5 transport channels and potential sources in Yangquan City. The results showed that： ① The PM2.5 pollution in Yangquan was mainly concentrated in Yangquan and Pingding, whereas the pollution in Yuxian was relatively light. The proportion of days with different pollution levels and the average and maximum values of PM2.5 concentration in Yangquan and Pingding were significantly higher than those in Yuxian, and the distribution characteristics of PM2.5 were closely related to the local special terrain. ② The amount of PM2.5 pollution and the concentration of PM2.5 in different pollution levels were the highest in light wind weather. The influence of east-west regional transport on PM2.5 pollution times and PM2.5 concentration of Yangquan and Pingding was obvious, and the contribution of east wind was significant. The influence of local pollution sources was the main factor in the moderate pollution weather in Yuxian County. ③ There were four main ground conditions for the generation and maintenance of moderate or above pollution weather： warm low pressure type （22%）, high pressure front （bottom） type （54%）, high pressure back type （14%）, and pressure equalization field （10%）. High pressure front （bottom） type was the main ground situation causing the increase in PM2.5 concentration. There were two types of upper air conditions, namely, flat westerly flow type （78%） and northwest flow type （22%）. The upper westerly flow type was the main upper air condition that caused the increase in PM2.5 concentration. ④ The results of transport channels and potential source areas of PM2.5 with different pollution levels obtained by MS-PSCF and TDA were consistent. The main transport channels of PM2.5 were the northeast, southeast, and northwest channels, whereas the northeast and southeast channels were short-distance transport routes, which were the main routes causing the increase in PM2.5 concentration. The northwest channel was consistent with the northwest dust transport channel, belonging to long-distance transmission. The main potential source areas of PM2.5 pollution were located in the central and western parts of Hebei and the southeast part of Hebei, the northeast part of Henan and its junction with the southwest part of Shandong, and the southeast part of Shanxi.

Applicability Study of Euler–Lagrange Integration Scheme in Constructing Small-Scale Atmospheric Dynamics Models

The atmospheric flow field and weather processes exhibit complex and variable characteristics at small scales, involving interactions between terrain features and atmospheric physics. To investigate the mechanisms of these process further, this study employs a Lagrangian particle motion model combined with a Euler background field approach to construct a small-scale atmospheric flow field model. The model streamlines the modeling process by combining the benefits of the Lagrangian dynamics model and the Eulerian integration scheme. To verify the effectiveness of the Euler–Lagrange hybrid model, experiments using the Fluent wind field model were conducted for comparison. The results show that both models have their advantages in handling terrain-induced wind fields. The Fluent model excels in simulating the general characteristics of wind fields under specific terrain, while the Euler–Lagrange hybrid model is better at capturing the upstream and downstream disturbances of the terrain on the atmospheric flow field. These findings provide powerful tools for in-depth diagnostic analysis of atmospheric flow simulation and convective precipitation processes. Notably, the Euler–Lagrange hybrid model demonstrates excellent computational efficiency, with an average computation time of approximately 2 s per time step in a Python environment, enabling rapid simulation of 40 time steps within approximately 90 s.

Epidemiological and mycological profile of superficial mycoses in diabetic patient

Introduction: Superficial mycoses, especially those of nails, scalp and skin, are very common in various countries. The presence of specific terrain, as well as other factors, can affect the prevalence of these. In this sense, diabetic patients are more susceptible to infections especially fungal infections because of changes in the immune system and macro and microvascular changes. The objective of our study was to determine the epidemiological and mycological profile of superficial mycoses in diabetic patients at the Mohammed VI Hospital in Oujda (Morocco). Material and methods: This is a retrospective, observational and descriptive study spread over 34 months, from January 2021 to October 2023 at the Parasitology-Mycology laboratory of the Mohammed VI Hospital Center of Oujda. We collected demographic and mycological data for the included patients. In the laboratory, upon reception of the samples, a direct examination (DE) of the sample was obtained after clarification by KOH to better visualize the mycelial filaments or yeasts and culture on both media: Sabouraud with chloramphenicol and Sabouraud with chloramphenicol and cycloheximide is systematically carried out. Results: We collected 136 diabetic patients referred to our laboratory for suspicion of superficial mycosis. The latter was confirmed in 46 of the 136 diabetic patients (33.82%) referred to our laboratory, which corresponds to 50 lesions among the 166 sites taken, a prevalence of 30.12%. At the mycological examination, the DE allowed the confirmation of the diagnosis of mycoses in 64% (n=32) and showed most often mycelial filaments (n=21; 65.62%) especially at the level of the feet and yeasts were observed in particular at the level of the nails of the hands (n=11; 34.37%). While culture was positive in all cases without exception (100%; n=50), dermatophytes were the most frequently isolated fungi (n=30; 60%), followed by yeasts (n=20; 40%). By species, T. rubrum (n=30; 60%) was the only isolated dermatophyte species, followed by Candida albicans (n=17; 34%). Conclusion: In recent years, we have seen an increase in the prevalence of superficial mycoses in diabetic patients which is why we conducted this study. The results show on the one hand that the most isolated fungi in the superficial mycoses of these patients are dominated by dermatophytes, as T. rubrum represents the most frequently encountered species. Furthermore, the high prevalence of the latter demonstrates the significance of implementing important prevention measures.

The Influence of Human Activity and Environmental Factors on Gully Erosion

Gully erosion, far from confined to specific terrains like badlands or mountainous areas, stands as a global issue contributing significantly to land degradation across various soil types susceptible to crusting or piping. Even after initial triggers cease, formed gullies can persistently generate sediment. This study delves into the multifaceted influences of geology, climate, slope morphology, vegetation, human impact, and soil properties on gully development and broader soil erosion. Drawing from empirical examples globally and locally, it underscores the pivotal role of local soil characteristics in propagating erosion, particularly the gully variant. Anthropogenic factors, especially land use practices and their impact on vegetation, weigh heavily. Rampant deforestation coupled with insufficient re-vegetation or afforestation initiatives have exacerbated the looming erosion threats, contributing to catastrophic consequences. Despite the effectiveness of various strategies in preventing and addressing gully erosion, their sustained implementation on a large scale remains elusive. Thus, research priorities must encompass sub-surface flow erosion mechanisms, predictive models, and the intricate dynamics influencing farmers' adoption or rejection of conservation strategies. To combat soil erosion comprehensively, a holistic approach to soil conservation becomes imperative. This entails employing hydrological or bioenvironmental processes to regulate overland flow and curb excessive runoff. Prioritizing these aspects can inform more robust strategies for soil conservation, mitigating the pervasive impact of erosion on our lands. Keywords: Influence, Human, Activity, Environmental Factors and Gully Erosion

Enhancing LiDAR-UAS Derived Digital Terrain Models with Hierarchic Robust and Volume-Based Filtering Approaches for Precision Topographic Mapping

Airborne Laser Scanning (ALS) point cloud classification in ground and non-ground points can be accurately performed using various algorithms, which rely on a range of information, including signal analysis, intensity, amplitude, echo width, and return number, often focusing on the last return. With its high point density and the vast majority of points (approximately 99%) measured with the first return, filtering LiDAR-UAS data proves to be a more challenging task when compared to ALS point clouds. Various algorithms have been proposed in the scientific literature to differentiate ground points from non-ground points. Each of these algorithms has advantages and disadvantages, depending on the specific terrain characteristics. The aim of this research is to obtain an enhanced Digital Terrain Model (DTM) based on LiDAR-UAS data and to qualitatively and quantitatively compare three filtering approaches, i.e., hierarchical robust, volume-based, and cloth simulation, on a complex terrain study area. For this purpose, two flights over a residential area of about 7.2 ha were taken at 60 m and 100 m, with a DJI Matrice 300 RTK UAS, equipped with a Geosun GS-130X LiDAR sensor. The vertical and horizontal accuracy of the LiDAR-UAS point cloud, obtained via PPK trajectory processing, was tested using Check Points (ChPs) and manually extracted features. A combined approach for ground point classification is proposed, using the results from a hierarchic robust filter and applying an 80% slope condition for the volume-based filtering result. The proposed method has the advantage of representing with accuracy man-made structures and sudden slope changes, improving the overall accuracy of the DTMs by 40% with respect to the hierarchical robust filtering algorithm in the case of a 60 m flight height and by 28% in the case of a 100 m flight height when validated against 985 ChPs.

The role of fire in the Medieval and Early Modern landscape of Bad Waldsee within the broader context of the pre-Alpine forelands of south-western Germany

Fire, an important element of human land use strategies, was part of many early industrial activities but also of burning incidents that significantly impacted settlement structures and development. The spatial proximity of the historically well-documented medieval town and sediment archive deposited in its central lake (Stadtsee) was taken to investigate the interplay of fire and socio-environmental developments during the preindustrial phase of 750−150 bp (ad 1200–1800). The burning episodes were detected using the sediment macroscopic charcoal record (> 150 μm) and were interpreted considering sedimentological, palynological, and historical evidence. Macro-charcoal analysis revealed two main phases of biomass burning: a late Medieval one (653−533 cal bp ), followed by a distinct fire-free interval, and a second Modern Times phase (313 cal bp until today). During the late Medieval times and after ad 1750 (200 cal bp) low-magnitude local fires coincided with high-intensity land use pressure. Major historical events like the Thirty Years’ War and the fire incident near the town (ad 1386, 174 cal bp) were also documented by the charcoal sedimentary record. The specific terrain morphology and the town microclimate impacted the chance of whether certain local burning patterns were detectable at all. This study demonstrates that during the Medieval period to the present day, fire events, mainly anthropogenic, were coupled with the main vegetation developments. Anthropogenic fire was an inseparable part of the Bad Waldsee landscape, as also recorded historically by the town archives.

Gaidai reliability method for long-term coronavirus modelling

Background Novel coronavirus disease has been recently a concern for worldwide public health. To determine epidemic rate probability at any time in any region of interest, one needs efficient bio-system reliability approach, particularly suitable for multi-regional environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of novel coronavirus infection rate. Traditional statistical methods dealing with temporal observations of multi-regional processes do not have the multi-dimensionality advantage, that suggested methodology offers, namely dealing efficiently with multiple regions at the same time and accounting for cross-correlations between different regional observations. Methods Modern multi-dimensional novel statistical method was directly applied to raw clinical data, able to deal with territorial mapping. Novel reliability method based on statistical extreme value theory has been suggested to deal with challenging epidemic forecast. Authors used MATLAB optimization software. Results This paper described a novel bio-system reliability approach, particularly suitable for multi-country environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of extreme novel coronavirus death rate probability. Namely, accurate maximum recorded patient numbers are predicted for the years to come for the analyzed provinces. Conclusions The suggested method performed well by supplying not only an estimate but 95% confidence interval as well. Note that suggested methodology is not limited to any specific epidemics or any specific terrain, namely its truly general. The only assumption and limitation is bio-system stationarity, alternatively trend analysis should be performed first. The suggested methodology can be used in various public health applications, based on their clinical survey data.

Study on the leakage morphology and temperature variations in the soil zone during large-scale buried CO2 pipeline leakage

In the CCUS technology chain, buried CO2 pipelines are inevitable under special terrain conditions. Due to the concealment and the complexity of the soil, they have a higher possibility of leakage. However, there is limited research on buried CO2 pipeline leakage processes. In this study, authors used existing industrial-scale pipelines as CO2 storage containers and constructed a large-scale buried CO2 pipeline experimental system. The leakage hole size and direction were considered to investigate the leakage morphology and temperature changes in the soil. The results showed that during the small-hole leakage, dry ice spheres were formed, which adhered to the pipeline. According to the change of temperature field, the dry ice spheres expanded towards weak areas in the soil, rather than strictly along the jet direction. The volume of dry ice spheres generated in the upward leakage process was the largest, while the volume was the smallest in the downward leakage process. Due to the soil resistance, the volume of dry ice spheres generated in the 3 mm leakage process was always greater than 9 times that of the 1 mm leakage process. The experimental results provide important references for optimizing leakage detection systems and conducting leakage risk assessments.

Kinematics Model Estimation of 4W Skid-Steering Mobile Robots Using Visual Terrain Classification

Accurate real-time kinematics model is very important for the control of a skid-steering mobile robot. In this study, the kinematics model of the skid-steering mobile robots was first designed based on instantaneous rotation centers (ICRs). Then, the extended Kalman filter (EKF) technique was applied to obtain the parameters of ICRs under the same specific terrain online. To adapt to different terrain environments, the fractal dimension-based SFTA (segmentation-based fractal texture analysis) method was used to extract features of different terrains, and the k-nearest neighbor (KNN) method was used to classify the terrains. In the case of real-time terrain recognition, the filter parameters of the EKF for estimating the ICRs are adjusted adaptively. Experiments on a real skid-steering mobile robot show that this method can quickly estimate the kinematics model of the robot in the case of terrain changes, and can meet the needs of practical applications. The average error of odometer estimation based on visual terrain classification is 0.06 m, while the average error of odometer estimation without terrain classification is 0.14 m.

Characteristics and Establishment of Objective Identification Criteria and Predictors for Foehn Winds in Urumqi, China

The special terrain of Urumqi (in the valley area) often triggers strong foehn winds, causing huge losses to local people’s lives and social economies. By using the surface observation data of the hourly temperature, pressure, humidity, and wind from the downwind Urumqi Meteorological Station and the upwind Dabancheng Meteorological Station in the Middle Tianshan Canyon and the NCEP/NCAR reanalysis data during 2008–2022, this paper establishes the dataset of foehn processes at Urumqi Station in the past 15 years and analyzes the variation rules of the associated meteorological variables during the foehn processes. In addition, based on the physical mechanism of the occurrence of foehn, a three-element identification criterion (i.e., 94° ≤ 2 min average wind direction ≤ 168°, 2 min average wind speed ≥ 2.0 m/s, and Δθ between Urumqi station and Dabancheng station ≥ 0.29 K) for foehn in Urumqi is established by comparing and analyzing the variations of wind direction (WD), wind speed (WS), and the potential temperature difference (Δθ) between the two weather stations during the periods of foehn and non-foehn winds from 2013 to 2022. In addition, the performance of the three-element identification criterion is verified, and the results suggest that this criterion has an accuracy of 82.96% and a hit rate of 89.50% for the 2008–2012 foehn events in Urumqi. Moreover, the hit rate of this criterion for foehn wind of gale or above level (i.e., a 2 min wind ≥ 10.8 m/s on average) is 100%. In addition, combined with two predictors of sea-level pressure difference (ΔP) and Δθ between downwind stations and upwind stations, the foehn forecast can be more accurate than that provided by a single predictor. With ΔP ≤ −12 hPa and Δθ ≥ 5 K, the chances for foehn to occur are over 90%. This finding would have some reference and application values for the foehn forecasting.

Deep Learning Vision System for Quadruped Robot Gait Pattern Regulation.

Robots with bio-inspired locomotion systems, such as quadruped robots, have recently attracted significant scientific interest, especially those designed to tackle missions in unstructured terrains, such as search-and-rescue robotics. On the other hand, artificial intelligence systems have allowed for the improvement and adaptation of the locomotion capabilities of these robots based on specific terrains, imitating the natural behavior of quadruped animals. The main contribution of this work is a method to adjust adaptive gait patterns to overcome unstructured terrains using the ARTU-R (A1 Rescue Task UPM Robot) quadruped robot based on a central pattern generator (CPG), and the automatic identification of terrain and characterization of its obstacles (number, size, position and superability analysis) through convolutional neural networks for pattern regulation. To develop this method, a study of dog gait patterns was carried out, with validation and adjustment through simulation on the robot model in ROS-Gazebo and subsequent transfer to the real robot. Outdoor tests were carried out to evaluate and validate the efficiency of the proposed method in terms of its percentage of success in overcoming stretches of unstructured terrains, as well as the kinematic and dynamic variables of the robot. The main results show that the proposed method has an efficiency of over 93% for terrain characterization (identification of terrain, segmentation and obstacle characterization) and over 91% success in overcoming unstructured terrains. This work was also compared against main developments in state-of-the-art and benchmark models.

Investigation and Evaluation of Insolation and Ventilation Conditions of Streetscapes of Traditional Settlements in Subtropical China

Global warming, the urban heat island effect (UHI), and the risks of fossil fuel depletion necessitate a re-evaluation of traditional settlements that have been adapted to local climatic conditions, topography, and available resources, including materials and construction methods, through passive strategies to achieve thermal comfort. Although vernacular settlements have received considerable attention, few have examined and evaluated their streetscapes. This study investigates the impact of topographical features and architectural forms on insolation and ventilation conditions in traditional settlements in China’s southern subtropical climate. The aim is to explore traditional planning configurations of streetscapes at different altitudes to identify architectural forms and planning strategies that effectively improve outdoor users’ thermal comfort conditions. For this purpose, case studies are conducted on three traditional settlements in Lingnan; the Lingnan region has a typical subtropical climate in southern China. The chosen cases represent the main features of different topographical conditions, architectural forms, and climate zones in the Lingnan. We systematically simulated the insolation and ventilation in these settlements’ streetscapes on a monthly and quarterly basis and analyzed their sunlight hours, incident solar radiation, shading percentages, sky view factors (SVF), and wind speed. The findings show the following: (1) Specific terrains can affect streetscapes’ shading percentages and wind speed. The mountain settlement (With an average elevation of 600 m) is located on a southeast-facing slope (10° < slope < 20°). It receives an additional 10% of incident solar radiation compared to gentle terrain. (2) Compared to settlements located in coastal hills and mountainous, plain settlements have better shading and ventilation conditions in streetscapes. In terms of insolation, plain settlements have denser building configurations and narrower, elongated street corridors with a height-to-width ratio (H/W) = 1.9~5.5 (the height–width ratio value as street’s H/W (H = height, W = width); note that it is unitless), which can generate greater lower SVF (44.5%), and shading percentages (63.6%). Regarding ventilation, it is easier to create a “cool lane” (i) when the main street, oriented towards the dominant wind direction in summer, forms an angle <30° with it, (ii) when the primary street follows a NE–SW longitudinal orientation, while SE–NW horizontal streets intersect and weave through it, and (iii) with a H/W = 3~4 resulting in wind speeds of 2.9~4.0 m/s. (3) All the streetscapes have overshadowing occurring in winter; similarly, varying sizes of calm wind zones are created in summer. To alleviate these issues, widening the streetscapes along the buildings can permit solar penetration and natural ventilation. (4) In summer, installing shading devices along the horizontal plane of covered street corridors with a H/W = 1~4 and N–S longitudinal orientation can provide an additional shading of 3.6–22%.

A Calibration Method for Large-Footprint Full-Waveform Airborne Laser Altimeter without a Calibration Field

The geometrical measurement precision of laser spots is affected by the deviation between the parameters of the laser altimeter and the laboratory measurement results, and the inversion accuracy of surface object height is also limited. The measurement parameters and the load state can be obtained by calibration of the laser altimeter system. Usually, ground detectors are deployed to calibrate the measurement parameters of the laser altimeter, including the divergence angle and the energy distribution of the laser beam. A calibration method for a laser footprint spot without a calibration field was proposed in this paper, focused on the airborne large-footprint laser altimeter system. The geometric parameters of the laser spot were calibrated through the laser echo waveforms of a specific terrain. The experimental results show that geometric calibration of the large-footprint laser altimeter can be achieved in the area of the step surface. The divergence angle of the laser beams obtained from the six experimental areas is 4.604 ± 0.359 mRad, and the consistency of the energy distribution from each laser spot reaches 92.67%. A new method of on-orbit calibration and verification is provided for the satellite laser altimeter system.

Gaidai reliability method for long-term coronavirus modelling.

Novel coronavirus disease has been recently a concern for worldwide public health. To determine epidemic rate probability at any time in any region of interest, one needs efficient bio-system reliability approach, particularly suitable for multi-regional environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of novel coronavirus infection rate. Traditional statistical methods dealing with temporal observations of multi-regional processes do not have the multi-dimensionality advantage, that suggested methodology offers, namely dealing efficiently with multiple regions at the same time and accounting for cross-correlations between different regional observations. Modern multi-dimensional novel statistical method was directly applied to raw clinical data, able to deal with territorial mapping. Novel reliability method based on statistical extreme value theory has been suggested to deal with challenging epidemic forecast. Authors used MATLAB optimization software. This paper described a novel bio-system reliability approach, particularly suitable for multi-country environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of extreme novel coronavirus death rate probability. Namely, accurate maximum recorded patient numbers are predicted for the years to come for the analyzed provinces. The suggested method performed well by supplying not only an estimate but 95% confidence interval as well. Note that suggested methodology is not limited to any specific epidemics or any specific terrain, namely its truly general. The only assumption and limitation is bio-system stationarity, alternatively trend analysis should be performed first. The suggested methodology can be used in various public health applications, based on their clinical survey data.