Search Results (342)

With the acceleration of urbanization, wind environment problems in high-density blocks have become increasingly prominent. Most existing studies only focus on the identification of influencing factors, lacking a complete closed loop from “diagnosis” to “design verification”. This study takes 174 blocks along the Qingnian Street Metro Line in Shenyang as research objects, uses PHOENICS (2019) software, and clarifies the seasonal distribution characteristics of the wind environment in high-density blocks through field measurement and simulation verification. The XGBoost-Shap method is employed to identify key morphological factors and their nonlinear influence mechanisms. The K-means clustering method is adopted to construct the typology of calm wind zones, which are classified into three categories: Type A (narrow street canyon-comprehensive resistance type), Type B (high-density enclosed type), and Type C (high-rise obstruction type). Multi-scenario simulations are conducted for each type, and differentiated optimization schemes are designed accordingly. The results show that under specific CFD boundary conditions representing typical cold climate urban environments, eight indicators, including enclosure degree (ED), sky visibility (SVF), and windward area ratio (FAI), have significant seasonal sensitivity effects on wind environments. The effect of multi-strategy collaborative optimization is significantly superior to that of a single intervention. This study verifies the effectiveness of the typological approach in bridging wind environment mechanism identification and spatial optimization design. Thresholds for indicators such as enclosure degree (ED), sky visibility (SVF), and building density (BD) can be used as preliminary design-screening tools, providing a reference for ventilation improvement design ideas along high-density subway lines in actual urban construction. Full article

Green façade applications are among the visible strategies to mitigate Canopy Urban Heat Islands (CUHIs) and improve thermal comfort, particularly in hot arid climates. However, their combined effectiveness at the urban scale, particularly with respect to urban canyon geometry, remains underexplored. This study evaluates the cooling efficiency of green façades and their relationship with height-to-width (H/W) ratios in the hot arid climate of Tehran, Iran. Urban canyons with varying geometries and façade conditions are simulated using ENVI-met 5.1 to assess impacts on air temperature and the Universal Thermal Climate Index (UTCI). Results indicate that urban canyon geometry, particularly higher H/W ratios, plays a dominant role in reducing CUHI intensity and improving outdoor thermal comfort, especially during summer, when deeper canyons show lower air temperature and UTCI values. The addition of green façades further enhances this cooling effect, most significantly in deeper canyon configurations. In contrast, winter conditions show minimal sensitivity to both geometry and façade greening, with only minor variations observed. Overall, the study highlights the importance of integrating urban form and vegetation strategies, demonstrating that the effectiveness of green façades is strongly influenced by canyon geometry and seasonal conditions, providing insights for climate-responsive, geometry-sensitive urban design. Full article

Wildfires in California increasingly threaten communities and ecosystems. However, comprehensive estimation of fire dynamics and fuel structure remains limited. Recent advances in Uncrewed Aerial Vehicle (UAV) technology and high-spatial-resolution mapping have provided increasingly important tools for estimating wildfire fuel-height loss across fuel types. This study used a one-year Uncrewed Aerial Vehicle (UAV) time series to quantify fuel-height loss and vegetation regrowth associated with a prescribed upslope canyon fire near Salinas, California, USA. Multispectral, infrared, and visible UAV imagery collected before, during, and after burning was used to generate orthomosaic, digital surface models (DSMs), fuel-type classifications, and surface-volume estimates. To enable reliable pre- and post-fire comparison, ground control points and tie points were used to train linear regression calibrations that corrected angular discrepancies and elevation offsets among time-series DSMs. Calibrated DSMs were then integrated with ecological field measurements to map fuel-height consumption and post-fire recovery at the individual-plant scale. UAV-derived fuel-height change was associated with in situ twig-diameter measurements, which provide field-based indicators of fire effects in chaparral vegetation, while the maximum recorded temperature explained only a small proportion of variation in fuel-height loss. This workflow can support integrated fire ecology and remote-sensing studies by providing repeatable measurements of post-fire changes in vegetation structure. Full article

Under the growing threat of urban heat stress, street canyons play a critical role in shaping the pedestrian thermal environment. While street greenery is an effective mitigation strategy, its performance varies substantially with physical characteristics—such as aspect ratio, street width, and sidewalk width—highlighting the need for spatially adaptive design. This study evaluates the effects of sidewalk width, street orientation, and planting structure on thermal conditions in a humid subtropical climate in Daegu Metropolitan City, Republic of Korea. The analysis focuses on open low-aspect-ratio street canyons (H/W = 0.86 for E–W and 0.43 for N–S orientations). Using a validated ENVI-met (Version 5.6.1) model based on field measurements from Daegu, Republic of Korea, 56 street-greening scenarios were simulated by systematically varying sidewalk width, street orientation, planting rows, spacing, and planting structure. Results show that multi-row planting served as the primary structural framework governing thermal performance. Optimal configurations varied with sidewalk width, with two-row planting for 6 m sidewalks and three-row planting for 10 m sidewalks providing the most effective cooling. The greatest cooling (−2.02 °C) was achieved when optimized multi-row configurations were combined with multi-layer planting. Once optimal multi-row configurations were established, the presence of understory vegetation had a greater influence on thermal improvement than its specific composition, allowing flexibility in understory design. Clear spatial asymmetries were identified, with the highest thermal stress occurring on the north-side sidewalk in E–W streets and the west-side sidewalk in N–S streets. Targeted planting in these locations produced greater cooling benefits than uniform strategies. These findings provide a spatially grounded framework for climate-responsive street greenery and offer practical design guidance, highlighting the need for context-specific, optimized multi-row planting strategies adapted to local urban and climatic conditions. Full article

In satellite-denied environments such as urban canyons, tunnels, and underground parking facilities, achieving high-precision autonomous positioning for vehicles remains a critical challenge. Although high-precision inertial measurement units (IMUs) can provide accurate dead reckoning, their deployment is limited by cost, size, and power consumption, making low-cost, microelectromechanical systems IMUs (MIMUs) an attractive alternative solution. However, the single MIMU suffers from substantial measurement noise and bias instability, leading to rapid error divergence that cannot sustain long-term autonomous navigation. To address the above issues, this paper proposes an autonomous positioning system based on a wheel-mounted MIMU array (Wheel-AINS). The system adopts a differential layout in which multiple low-cost MIMU chips are installed at the center of each of the left and right rear wheels, forming redundant sensor arrays. By differentially fusing symmetrically mounted chips, common-mode noise and zero bias are effectively canceled while the wheel rotation provides natural rotational modulation. The fused gyroscope outputs and known wheel radius are then used to estimate the vehicle forward speed, replacing traditional odometers. The estimated wheel speed and vehicle kinematic constraints are then integrated within a Kalman filter framework to suppress the error divergence of the inertial navigation system. A dedicated embedded hardware prototype with multi-chip synchronous acquisition and wireless transmission was developed. Three groups of urban road tests with total distances of 0.85 km, 2.14 km, and 2.49 km were conducted. The results indicate that the average position drift rate of the Wheel-AINS is 0.50%, and the average heading RMSE is 12.2°. The closure error of the 2.49 km trajectory is 10.43 m, reduced by approximately 80% compared with a single MIMU. The ablation experiment reveals that the MIMU array fusion module is the primary source of accuracy improvement, reducing the position RMSE from 155.0 m to 10.1 m, while the dual-wheel distance constraint further optimizes the position RMSE to 8.2 m, but increases the heading RMSE from 13.3° to 13.6°. This demonstrates that the proposed method can substantially improve autonomous positioning accuracy while maintaining a notably low system cost, providing a viable technical pathway for long-endurance vehicle navigation in satellite-denied environments. Full article

This study addresses the stratified and turbulent tropospheric delays that impede interferometric synthetic aperture radar (InSAR) deformation monitoring in alpine canyon regions. We introduce a tropospheric delay model that incorporates time-varying Gaussian coefficients and coupled zenith wet delay (ZWD) by combining diverse multi-source data. This model was incorporated into StaMPS for InSAR processing. Evaluation results demonstrated that (1) the model accurately captured seasonal and diurnal tropospheric variations, achieving a root mean squared error (RMSE) of 2.01 cm relative to the GNSS reference data; (2) the model corrected stratified and turbulent delays and reduced interferometric phase standard deviation (STD) by 9.28% compared to the Generic Atmospheric Correction Online Service (GACOS); and (3) the deformation accuracy improved by 19.07% over GACOS. Discussion results indicate that accounting for time-varying Gaussian coefficients is essential and that coupling ZWD to rectify turbulent delays outperformed the filtering method. The observed negative interferogram corrections result from the random intensity of turbulent delays. These findings confirm the effectiveness of the proposed model for high-precision InSAR deformation monitoring in complex alpine terrains. The proposed model aims to enhance studies of tropospheric delay variations in alpine canyon regions and to mitigate such delays in InSAR-based geological hazard monitoring. Full article

The rapid expansion of urbanization in recent decades has intensified the urban heat island effect, driven by reduced vegetation cover, widespread use of heat-absorbing materials, and increases in surface and atmospheric temperature that may reach 5–6 °C. These conditions negatively impact well-being, quality of life, and human health. In response, numerous studies have examined mitigation strategies based on high-albedo materials and urban vegetation. This systematic review analyzes 225 peer-reviewed articles published between 2016 and 2025 addressing urban heat mitigation, surface thermal conditions, urban vegetation, outdoor thermal comfort and microclimate simulations. It provides a comprehensive synthesis, highlighting key findings and implications for future research. According to the Köppen–Geiger classification, most studies were conducted in humid subtropical and warm Mediterranean climates. The analysis focuses on urban canyon interventions, where vegetation is primarily modeled as shading trees (79.2%), along with other forms such as grass or shrubs (27.1%), mainly during the summer season. Results indicate that integrated mitigation strategies combining vegetation and high-albedo surfaces (≈0.8) generally provide greater cooling benefits than isolated interventions. Overall, the findings underscore the importance of the interaction between vegetation shading and surface properties for mitigating urban heat in outdoor spaces. Full article

In the context of global climate change and rapid urbanization, urban outdoor thermal environment issues in summer have become increasingly severe. Shading has been widely recognized as an effective strategy for improving outdoor thermal comfort, yet existing evaluation methods still suffer from limitations in adaptability and accuracy. Taking Chongqing, a typical hot-humid city in China, as a case study, this paper proposes an evaluation method that accounts for human thermal adaptation, introducing three complementary indicators, namely Universal Thermal Climate Index Load (UTCIL), cumulative UTCIL (cUTCIL), and Heat Stress Duration (HSD). Focusing on four shading-related urban canyon morphological factors—orientation, aspect ratio (H/W), building asymmetry, and leaf area index (LAI) of street trees—a series of simulation scenarios was designed to quantitatively explore their impacts on summer outdoor thermal comfort. The applicability and reliability of the ENVI-met model for block-scale outdoor thermal environment simulation were validated by comparing field-measured microclimate data with simulation results. The findings demonstrate that all four morphological factors substantially influence the outdoor thermal environment. Canyon orientation considerably affects thermal comfort, with a 30° clockwise deviation from the north–south yielding optimal conditions, whereas the east–west (90°) orientation produces the poorest thermal environment, with a maximum UTCI of approximately 48.9 °C. For aspect ratio, thermal comfort improves continuously as H/W increases, with the benefit stabilizing beyond H/W = 3.5. Building asymmetry also plays a notable role: raising building height on one side can effectively reduce outdoor thermal stress, and canyons with taller west-side buildings show better thermal performance under the same asymmetry ratio. Furthermore, street tree shading and aspect ratio exhibit a synergistic cooling effect, where high LAI (e.g., 4.77) reduces UTCI_max by approximately 1.8 °C at H/W = 1, but this benefit diminishes as H/W increases. The optimal outdoor thermal environment is achieved through the combination of a high aspect ratio and high LAI. These findings provide a quantitative basis and design references for optimizing outdoor thermal comfort in Chongqing. In addition, the quantitative evaluation proposed method can offer a methodological reference for other hot-humid regions. Full article

Reliable spatial georeferencing of mobile mapping platforms is a fundamental prerequisite for high-fidelity urban remote sensing products such as 3D point clouds and digital twins. However, in deep urban canyons, severe signal occlusion and multipath effects reduce visible GNSS satellites, causing ambiguity resolution (AR) failure and degraded observation geometry for UGV-borne systems. Conventional Vehicle-to-Vehicle (V2V) cooperation offers limited improvement due to symmetric ground-level occlusion. To overcome this, we propose an asymmetric GNSS/UWB fusion method that introduces Unmanned Aerial Vehicles (UAVs) as high-altitude dynamic spatial anchors to reconstruct the 3D observation geometry. Two contributions are presented: (i) an asymmetric heterogeneous stochastic model coupling carrier-to-noise ratio (C/N0) and elevation angle to handle the quality disparity between air and ground sensor links, preventing multipath contamination of high-fidelity UAV observations; and (ii) a dynamic baseline constrained least-squares algorithm integrating Ultra-Wideband (UWB) ranging to stabilize GNSS positioning under high-dynamic relative motion. Validated through high-fidelity simulations and field experiments, the method achieves a 98.2% AR success rate and sub-decimeter 3D accuracy under extreme occlusion (≤3 visible satellites), while urban-canyon tests demonstrate 100% positioning availability across all evaluated epochs and reduce the 95th-percentile 3D error from 7.25 m to 0.19 m under the tested single-UAV/single-UGV configuration. The framework supports smart city modeling, 3D reconstruction, and infrastructure monitoring. Full article

Urban thermal comfort in winter is an important but insufficiently quantified component of sustainable, climate-adapted urban design in cold-weather cities facing energy-intensive winter environmental challenges. This study uses high-resolution simulations to evaluate discomfort across a downtown district in Sapporo, Japan, based on the standard effective temperature (SET*) index and universal thermal climate index (UTCI). A total of 2438 sampling points were assessed under 69 hourly winter scenarios. Discomfort hotspots were found in east–west streets and wind-exposed corners, driven by limited solar access or intensified wind. SET* is a more sensitive indicator under cold conditions, particularly in shaded areas. Wind speed and mean radiant temperature distributions revealed the environmental drivers of discomfort. The influence of building height was confirmed via quantitative correlation analysis, which revealed significant negative relationships between adjacent building heights and SET* across all streets analyzed, especially in east–west street canyons, where correlation coefficients ranged from −0.80 to −0.52 in the representative street. These findings contribute to urban sustainability by providing a quantitative tool for identifying winter thermal vulnerability and supporting passive, climate-adapted public-space design. The proposed framework can help improve winter walkability, outdoor activity, and the environmental quality of downtown spaces in cold-region cities. Full article

As they are home to numerous significant ecosystems, natural resources, and a growing population, coastal regions are among the most vital locations on Earth. This study, pertaining to the east coast of the UAE, integrates nine distinct characteristics to provide a thorough methodology for assessing integrated coastal vulnerability. Land use and land cover (LULC), nearshore bathymetry, coastal geomorphology, coastal slope, shoreline erosion and deposition, population density, wave and tide, and nearshore benthic features are important parameters that are examined. For the first time, coastal benthic features are included to assess coastal vulnerability in this region. By combining the variably weighted rank values of the nine variables, an Integrated Coastal Vulnerability Index was created, which divides the coastline into low-, moderate-, and high-risk categories. The methodology improves the precision of regional risk assessments by combining these factors with data from real-time coastal surveillance. Approximately 26.4% of the UAE’s 178 km east coast (or 47.1 km) is at high risk, followed by 17.3% (or 30.9 km) at moderate risk and 56.3% (or 100.2 km) at low risk. The offshore areas of the east coast of the UAE are prone to shoaling and tunneling effects from incoming high waves at certain areas due to the concave-shaped bathymetry and medium-range canyons present, which exacerbate storm surges or tsunamis due to the shoaling effect. For a 3 m rise in sea level, most significantly, 5.58 km² of plantation and 14.39 km² of residential areas will be damaged in the Kalba and Fujairah regions. Additional commercial spaces totaling 1.07 km² will also have an impact, adding to the existing 2.59 km² of oil bunkers in Fujairah. More than 40,000 people who live within 3.0 m of the UAE’s east coast in six separate districts—Kalba, Fujairah City, Mirbah and Qidfa, Khorfakkan, Dadna and Bidya, and Dibba—will be impacted if a tsunami wave or storm surge of three meters strikes the east coast. Our results are intended to assist government agencies, coastal planners, and policymakers in the Northeast Emirates (Fujairah and Sharjah) in creating sustainable and successful adaptation and mitigation plans for areas most vulnerable to coastal hazards. In addition to enhancing scientific knowledge of coastal vulnerabilities, this integrative method is a useful tool for making well-informed decisions in the face of shifting socio-economic and climatic situations. Full article

Accurate and continuous high-frequency water level monitoring is essential for flood control, water resource regulation, and hydrological studies in the Yellow River. However, traditional methods are often limited in complex inland river environments with insufficient temporal resolution, poor continuity, and weak robustness. In this study, high-frequency water level changes and their dynamic responses to water-sediment regulation were estimated at Huayuankou and Xiaolangdi stations based on a sliding window, variational mode decomposition (VMD), and multi-GNSS interferometric reflectometry (GNSS-IR). The results show that high-temporal-resolution water level series with a 5-minute interval were achieved at Huayuankou and Xiaolangdi. When compared with in situ gauge measurements, the GNSS-IR estimated water level has a root mean square error (RMSE) of 0.09 and 0.14 m, and coefficient of determination (R²) values with 0.92 and 0.96, respectively. These results demonstrated strong effects by reservoir regulation in both wide-and-shallow wandering reaches and canyon-controlled reaches. Water level responses to the 2025 water-sediment regulation operation showed that Xiaolangdi responded rapidly to upstream reservoir releases, whereas Huayuankou exhibited a delayed response, with the flood peak arriving about 21 h later and attenuating during downstream propagation. The proposed method shows strong potential for high-frequency water level monitoring and dynamic response analysis from GNSS-IR in complex inland rivers. Full article

Accurate long-horizon drought forecasting is essential for water resource management and early warning systems in semi-arid regions. This study evaluates five state-of-the-art Transformer architectures—Vanilla Transformer, Informer, Autoformer, Temporal Fusion Transformer (TFT), and PatchTST—for 24-month forecasting of the Standardized Precipitation Index (SPI-12) across four climatically homogeneous regions of Zacatecas, Mexico (Semi-arid, Highlands, Mountains, and Canyons). Models were trained on monthly precipitation data from 1965–2022 and evaluated on an independent test period (2023–2024) using MAE, RMSE, Pearson correlation, and the Diebold–Mariano test. The results show that PatchTST achieved the best overall performance in three of the four regions, significantly outperforming the other models in most cases. The Vanilla Transformer performed best in the less variable Highlands region. These findings demonstrate that the model’s suitability is strongly dependent on regional climatic characteristics. PatchTST’s patch-based approach proved particularly effective for capturing complex temporal dependencies in highly variable semi-arid environments. This study highlights the potential of Transformer architectures, especially PatchTST, to improve long-horizon SPI forecasting and strengthen operational drought monitoring systems in water-scarce regions. Full article

Outdoor open spaces are essential for daily activities in ageing rural environments, yet the thermal effectiveness of vegetation under varying structural configurations remains unclear. Most existing Outdoor Thermal Comfort studies focus on dense urban canyons; the present study addresses this gap by examining a complexity threshold in vegetation cooling under high-SVF rural conditions and the radiation–ventilation trade-off that underlies it. An ENVI-met model was calibrated using field data from a typical village on the North China Plain and 17 vegetation scenarios were simulated. The findings reveal a non-linear relationship between vegetation complexity and cooling efficiency. A threshold of complexity was observed: the cooling performance declined with an increase in stratification from a double-layer (Scenario 12) to a triple-layer (Scenario 14) structure, with the change in mean radiant temperature (∆T_mrt) dropping from 23.16 °C to 21.10 °C. This is due to a radiation–ventilation trade-off, in which denser vegetation increases shading but reduces near-surface ventilation. Dense arrangements exhibit a heat trap effect, with the long-wave radiation flux changing from a cooling (−3.42 K/h) to a heating (+2.11 K/h) state. The results show a threshold effect in vegetation cooling and that thermal comfort is not necessarily enhanced by increased complexity. A shaded-canopy and permeable-understory structure is found to be optimal. The findings inform vegetation design in climate-adaptive rural settings. Full article

With the widespread adoption of smartphones, location-based services have become increasingly important. Consequently, accurate and reliable global satellite navigation system positioning on smartphones has become essential. However, achieving accurate positioning in urban areas remains challenging because of the inherent limitations of smartphones and severe multipath effects. To address this issue, this study proposes two methods to improve positioning accuracy using contextual information. First, an environmental context indicator was used to refine the C/N₀-based observation covariance model. Second, normalized C/N₀ and code-pseudorange residuals were used to detect non-line-of-sight satellites and adjust the observation covariance. Experiments were conducted in both open and urban areas, and performance was evaluated using circular error probable (CEP) and distance root mean square (DRMS). The experimental results showed that, in open areas, the proposed method achieved submeter to decimeter-level horizontal accuracy and precision. In semi-urban areas, CEP95, CEP50, and DRMS decreased by approximately 8, 2, and 4 m, respectively. In urban canyons, CEP95, CEP50, and DRMS decreased by approximately 15, 2, and 5 m, respectively. Full article