Street Canyon Research Articles

Graph Neural Networks optimized with Gazelle Optimization Algorithm for Urban Plantscape Design Based on Large-scale Street View

The center of human activity and a key point of contact for social interaction between city people and the built environment is the street. With more street-level photos becoming available, urban landscape studies have more chances to examine and evaluate streetscapes closely and from various angles. This manuscript present the graph neural networks (GNN) optimized with gazelle optimization algorithm (GOA) for urban plants cape design based on large-scale street view (UPLS-GNN-GOA). Initially data is taken from ADE20K dataset. Afterward the data is fed to General Robust Subband Adaptive Filtering (GRSAF) based pre-processing process. The pre-processing output is given to Discrete Fractional Fourier Transforms (DFrFT) to extract the street greenery and openness of street canyons. After that, the extracted features are fed to Graph Neural Networks (GNN) to classify the public health, urban microclimate, human perception. The weight parameters of the GNN are optimized using Gazelle Optimization Algorithm (GOA).The UPLS-GNN-GOA method is implemented in Python, and its efficiency is determined using a series of performance evaluation metrics analysis, including accuracy, precision, recall, f1-score, and sensitivity. The proposed UPLS-GNN-GOA method shows the highest accuracy of 98%, precision of 98%, and F1-score of 97% while comparing other existing methods such as urban plantscape design based on convolutional neural network (UPLS-CNN), urban plantscape design based on deep convolutional neural network (UPLS-DCNN) and urban plantscape design based on deep learning and convolutional neural network (UPLS-DL-CNN) respectively.

3D reconstruction of spherical images based on incremental structure from motion

ABSTRACT 3D reconstruction plays an increasingly important role in modern photogrammetric systems. Conventional satellite or aerial-based remote sensing (RS) platforms can provide the necessary data sources for the 3D reconstruction of large-scale landforms and cities. Even with low-altitude UAVs (Unmanned Aerial Vehicles), 3D reconstruction in complicated situations, such as urban canyons and indoor scenes, is challenging due to the frequent tracking failures of camera frames and high data collection costs. Recently, spherical images have been extensively exploited due to the capability of recording surrounding environments using one camera exposure. Classical 3D reconstruction pipelines, however, cannot be used for spherical images. Besides, there exist few software packages for the 3D reconstruction of spherical images. Based on the imaging geometry of spherical cameras, this study investigates the algorithms for relative orientation using spherical correspondences, absolute orientation using 3D correspondences between the scene and spherical points, as well as cost functions for BA (bundle adjustment) optimization. Besides, an incremental SfM (Structure from Motion) workflow has been proposed for spherical images by using the above-mentioned algorithms. The proposed solution is finally verified by using three spherical datasets captured by both consumer-grade and professional spherical cameras. The results demonstrate that the proposed SfM workflow can achieve the successful 3D reconstruction of complex scenes and provide useful clues for the implementation in open-source software packages. The source code would be publicly available.

Exploring the combined cooling effect of street canyon geometry and the surrounding built environment.

Exploring the impact of complex urban morphology on the urban heat island (UHI) effect is essential for sustainable environmental management and enhancing human well-being. This study explored the combined cooling effect of street canyon geometry and the surrounding built environment using a CatBoost model and the Shapley method. The findings indicated that in streets with low building height and density, a high proportion of sky and vegetation and a flatter skyline are conductive to mitigate UHI effect. In streets with high building height and density, a lower proportion of sky and vegetation, and a well-proportioned skyline, can effectively mitigate UHI effect. Regardless of the building density and height around the street, street trees are the optimal choice for greening construction and improvement of large and medium-sized cities in China, given their high controllability and the current urban stock background. Therefore, reasonable control and allocation of street trees can effectively adjust the street canyon geometry, providing suitable cooling strategies for streets with different surrounding built environments. This study proposed a method to mitigate the UHI effect through street canyon geometry, which can be extended to other high-density urban thermal environment studies and guide policymakers on street construction and urban design.

A wind tunnel study on flow instability and pollutant dispersion inside an isolated street canyon

A wind tunnel study on flow instability and pollutant dispersion inside an isolated street canyon

Comparison of cooling grey solutions in the sense-city urban demonstrator for adapting cities to heat waves

SummaryFaced with the increase in urban heat in summer, cities must quickly adapt by offering cool islands. If nature-based solutions are efficient and popular, other so-called grey solutions exist and can also provide solutions. In this paper we compare standard grey solutions in Sense-city, an urban demonstrator equipped with sensor, located in the scientific campus of Cité Descartes at Marne la Vallée. Our objective is on the one hand to compare the effectiveness of standard solutions over time, but also to study the ability of sense-city and its canyon street to study this phenomenon despite its relatively small size. MethodsIn this work we follow an experimental approach using a wide coverage of calibrated sensors deployed in Sense-city. We have conducted two measurement campaigns in July 2021 and July–August 2022 where we study the effectiveness of standard solutions (shading, white floor surface, street watering) to reduce the air temperature in the canyon street of sense-city. As the days are different, we compare the temperature difference in the street canyon equipped with these cooling solutions with that on the surrounding area. This method allows us to overcome daily variations. To interpret the results, we analyse the shades and we follow the temperature over time and not only during the hottest hours. We also calculate the UTCI (Universal Thermal Climate Index) to compare the perceived temperature. FindingsThe results show that despite its small size, the canyon street of sense-city behaves like a canyon street and that the measured temperature differences due to heat exchanges comply with physical laws and that the number and spatial distribution of sensors is validated. The Sense-city demonstrator can therefore be used to carry out thermal efficiency experiments. In addition, the method we used to compare cooling solutions allows us to limit the impacts due to slight daily variations. Finally, while watering is effective in rapidly lowering the temperature in the street, shading remains an optimal solution for the perceived temperature, even if it would be ideal to close them at the end of the day to allow air circulation.

Research on Prediction Model of Particulate Matter in Dalian Street Canyon

In urban areas where populations commonly reside, particle mass concentrations in street canyons can pose significant risks to human health. This study aimed to investigate the diffusion mechanism of particle mass concentrations in urban street canyons by developing and applying a prediction model based on the mathematical modeling of physical processes. The prediction model considered factors such as the influence of traffic wind, natural wind, traffic flow, and other relevant variables influencing particle mass concentrations in street canyons. Field measurements were conducted in Dalian, China, to verify the feasibility of the model. Particle mass concentrations, traffic flow, temperature, relative humidity, and wind speed were measured on Shichang Street (a two-lane one-way road), Tangshan Street (a four-lane two-way road), and Shengli Road (a six-lane two-way road). The results indicated that the majority of traffic peaks occurred around 19:00 on all road types. The PM1.0 mass concentration was well diluted on the four-lane two-way road, with the least dilution observed on the two-lane one-way road. A strong correlation between the particle mass concentrations and traffic flow was discovered. Furthermore, a prediction model was established, accurately predicting the particle mass concentrations when the prediction step was from 5 to 15 s. The coefficient of determination (R2) between the predicted and measured values on the two-lane one-way road, four-lane two-way road, and six-lane two-way road was 0.9319, 0.6582, and 0.9238, respectively. Additionally, the prediction model allowed for a detailed analysis of traffic flow limitations, corresponding to the recommended World Health Organization (WHO) PM2.5 values. Overall, the findings of this study offer valuable insights for forecasting particle exposure levels in street canyons.

ASSESSMENT OF THE INFLUENCE OF THE INTENSITY OF TRAFFIC FLOWS ON THE STATE OF THE STREET AND ROAD NETWORK OF THE CITY

The article is devoted to the assessment and forecasting of the level of atmospheric air pollution in street canyons in Kyiv by controlling the parameters of traffic flow. Today, road transport is the main anthropogenic source of environmental pollution. The specificity of air pollution by traffic flows lies in their ground location, close proximity to people's homes, which leads to the accumulation of pollutants near the ground surface - in the breathing zone of people. The article analyzes the main approaches to modeling the dispersion of pollutants in the atmosphere from motor vehicles. It is advisable to assess the level of urban air pollution in homogeneous elements of the urban area - street canyons. Based on the urban street canyons model (OSPM), the level of pollution in the street canyons of the Pechersk district of Kyiv by the main harmful substances contained in car exhaust gases is determined. The critical intensity of traffic flows for each of the street canyons at which the level of pollution by the corresponding harmful substance reaches the maximum permissible value was determined. Thus, the obtained results of the study allow us to quickly predict the level of air pollution in the roadside space of cities and prevent environmentally hazardous situations by controlling the parameters of the traffic flow.

Effects of solar radiation and tree planting on photochemical reaction kinetics in urban street canyon

The investigation of the impact of tree planting on photochemical reaction kinetics and dispersion characteristics of reactive pollutants in street canyons under actual solar radiation remains a pertinent subject for research. The numerical models were employed and validated through wind-tunnel experiments to investigate the dynamic and thermodynamic effects of tree planting (LAD = 4.77) on turbulent flow, heat transfer, and NOx-O3 photochemical reaction in urban street canyons. The effects of solar radiation at three local solar times (LST0900, LST1200 and LST1500) and three background O3 concentrations (20 ppb, 100 ppb and 200 ppb) were considered. The ozone depletion rate (dO3) was defined to measure the photochemical reaction equilibrium. The results show that the presence of trees can offset the impact of varying LST solar radiation and promote greater stability in flow structures within street canyons. Specifically, a stable clockwise main vortex is observed in the upper part, while multiple smaller vortices form more regularly in the lower part. Compared with no trees, planting trees can effectively reduce the temperature by about 5 K in the lower part of street canyon through the shading and transpiration cooling effects. In conjunction with its dynamic effects, the tree planting can also effectively reduce the average concentration of pollutants before the reaction. It results in a predominant accumulation of NOx near the pollution source at the bottom center, thereby mitigating their detrimental impacts on both windward and leeward sides. Additionally, under the same background O3 concentration, tree planting can also influence the equilibrium process of photochemical reactions and enhance their reverse reaction leading to ozone depletion. The findings of this study contribute to a deeper understanding of the impact of tree greening on the local microclimate within urban street canyons.

Assessing the influence of street canyon shape on aircraft noise: Results from measurements in courtyards near Amsterdam Schiphol Airport

Aircraft noise is a major stressor for communities in the vicinity of airports. Aircraft noise prediction models omit the built environment, based on an implicit assumption that the impact of buildings on the propagation of aircraft noise is neglectable. In this article a study is presented in which aircraft noise levels were measured near walls facing towards and away from aircraft flyovers in an urban test environment near Amsterdam Schiphol Airport. The test environment comprises three adjacent courtyards, each enclosed by stacked shipping containers. To examine the influence of street geometry on aircraft noise, specifically for slanted roofs and building insets, the shipping containers were stacked in a different pattern around each courtyard. In total, sound levels for 2383 aircraft flyovers were analysed across five months at ten microphone positions within the courtyards, for both arrivals and departures. Depending on the geometry of the courtyards, mean differences (LA,max) between facades with- and without a line of sight towards the aircraft ranged between −1,3dBA and 5,0dBA for arrivals, and 8,7dBA and 13,6dBA for departures. SEL values ranged between between −0,8dBA and 4,3dBA for arrivals, and 8,1dBA and 11,6dBA for departures. The results suggest that slanted roofs perpendicular to the flight direction deflect incident sound, substantially reducing the sounds levels inside courtyards. Contrarily, building insets at building sides facing away from the flight paths did not reduce sound levels underneath the overhangs significantly. The findings stress the importance of architectural and urban design to mitigate aircraft noise.

Effects of street tree configuration and placement on roadside thermal environment within a tropical urban canyon.

The Urban Heat Island (UHI) effect increases surface and air temperatures, affecting urban health and well-being. A well-known UHI mitigation measure is the increased roadside tree vegetation facilitating evapotranspiration and shade. In its implementation, the identification of thermally optimal street tree configurations and a quantitative assessment of how various street tree configurations impact the roadside thermal environment were deemed essential and were chosen as the main aims of the study. Twelve tropical urban canyons were categorized into three clusters representative of different street tree placement and configuration scenarios. A control cluster devoid of any roadside trees was also selected. The CFD-based 3-D microclimate model 'ENVI-met' was used to identify suitable roadside urban tree planting scenarios for better microclimate regulation. From a tree planting scenario analysis done as part of the study, the greening scenario of using a 'Continuous tree row (Densely foliated - high Leaf Area Density - LAD)' tree configuration was recognized with the highest ambient temperature reduction of 1.41°C. The study outcomes reveal that tree configuration of high LAD street trees placed in closer spacing contributes towards the better cooling effect of roadside environments and thus improves thermal comfort for warmer tropical climates of higher humidity levels. The study's findings offer valuable insights for urban planning professionals and policymakers involved in designing future cities and urban developments. They emphasize the importance of strategic tree-planting designs and configurations to enhance thermal comfort and livability in urban areas. This highlights the need to avoid ad-hoc procedures and instead prioritize well-planned roadside tree configurations within urban canyons.

Temporal Evolution of Vehicle Exhaust Plumes in a Congested Street Canyon Environment

Air pollutants from traffic make an important contribution to human exposure, with pedestrians likely to experience rapid fluctuation and high concentrations on the pavements of busy streets. This monitoring campaign was on Hennessy Road in Hong Kong, a densely populated city with deep canyons, crowded footpaths and low wind speeds. Kerbside NOx concentrations were measured using electrochemical sensors with baseline correction and subsequently deconvoluted to determine concentrations at 1-s resolution to study the dispersion of exhaust gases within the first few metres of their on-road source. The pulses of NOx from passing vehicles were treated as segments of a Gaussian plume originating at the tailpipe. The concentration profiles in segments were fit to a simple analytical equation assuming a continuous line source with R2 > 0.92. Least squares fitting parameters could be attributed to vehicle speed and source strength, dispersion, and sensor position. The width of the plume was proportional to the inverse of vehicle speed. The source strength of NOx from passing vehicles could be interpreted in terms of individual emissions, with a median value of approximately 0.18 g/s, but this was sensitive to vehicle speed and exhaust pipe position. The current study improves understanding of rapid changes in pollutant concentration in the kerbside environment and suggests opportunities to establish the contribution from traffic flow to pedestrian exposure in a dynamic heavily occupied urban microenvironment.

GNSS/5G Joint Position Based on Weighted Robust Iterative Kalman Filter

The Global Navigation Satellite System (GNSS) is widely used for its high accuracy, wide coverage, and strong real-time performance. However, limited by the navigation signal mechanism, satellite signals in urban canyons, bridges, tunnels, and other environments are seriously affected by non-line-of-sight and multipath effects, which greatly reduce positioning accuracy and positioning continuity. In order to meet the positioning requirements of human and vehicle navigation in complex environments, it was necessary to carry out this research on the integration of multiple signal sources. The Fifth Generation (5G) signal possesses key attributes, such as low latency, high bandwidth, and substantial capacity. Simultaneously, 5G Base Stations (BSs), serving as a fundamental mobile communication infrastructure, extend their coverage into areas traditionally challenging for GNSS technology, including indoor environments, tunnels, and urban canyons. Based on the actual needs, this paper proposes a system algorithm based on 5G and GNSS joint positioning, aiming at the situation that the User Equipment (UE) only establishes the connection with the 5G base station with the strongest signal. Considering the inherent nonlinear problem of user position and angle measurements in 5G observation, an angle cosine solution is proposed. Furthermore, enhancements to the Sage–Husa Adaptive Kalman Filter (SHAKF) algorithm are introduced to tackle issues related to observation weight distribution and adaptive updates of observation noise in multi-system joint positioning, particularly when there is a lack of prior information. This paper also introduces dual gross error detection adaptive correction of the forgetting factor based on innovation in the iterative Kalman filter to enhance accuracy and robustness. Finally, a series of simulation experiments and semi-physical experiments were conducted. The numerical results show that compared with the traditional method, the angle cosine method reduces the average number of iterations from 9.17 to 3 with higher accuracy, which greatly improves the efficiency of the algorithm. Meanwhile, compared with the standard Extended Kalman Filter (EKF), the proposed algorithm improved 48.66%, 35.17%, and 38.23% at 1σ/2σ/3σ, respectively.

Tree form characteristics as criteria for tree species selection to improve pedestrian thermal comfort in street canyons: Case study of a humid subtropical city

The combined effect of tree characteristics on heat stress in different street canyons has been widely reported. However, there remains a lack of effective methods for improving pedestrian thermal comfort through the use of integrated knowledge of tree characteristics. Here, a tree species selection approach was developed for assessing the dynamic effects of tree forms and canyon geometries on pedestrian thermal comfort to address the issue of the right tree in the right street canyon. The leaf area density (LAD), crown diameter (CD), tree height (HT), and trunk height (TH) were used as criteria for determining tree species characteristics, and the weighted outdoor thermal comfort autonomy (OTCAw) was adopted as a quantitative index of thermal comfort variation over time. In a case study of Wuhan, China, we evaluated the thermal comfort enhancement potential of 45 tree forms in street canyons with varying aspect ratios and orientations from 7:00 to 21:00 by using a validated ENVI-met model. Accordingly, tree pruning strategies and 19 optimal tree forms were proposed for corresponding street canyons. Our study provides insight into the optimal street tree species for minimizing heat exposure of pedestrians under various urban canyon configurations.

Effects of arcade design on wind and thermal environment inside an idealized 2D urban canyon with realistic solar heating

The arcade design has been widely used in the architecture design since it can provide space for commercial retails and improve local thermal comfort. However, the influences of different arcade design parameters on wind and thermal environment under realistic solar heating conditions are not fully understood, which hinders further application of the arcade design. This paper aims to investigate the effects of different arcade design parameters on wind and thermal environment under different solar heating conditions. Numerical wind flow, solar radiation and heat transfer simulations of a two-dimensional deep street canyon with aspect ratio of three are performed. The steady Reynolds-Averaged Navier-Stokes model with standard k−ε turbulence model is employed in this investigation, while considering solar radiation model. Moreover, the realistic solar heating simulations are achieved by setting different local solar times, i.e., LST0900 (leeward wall heating), LST1200 (street ground heating) and LST1500, (windward wall heating). Under realistic solar heating conditions, the building wall heating and the street ground heating are shown to evidently influence the strength and location of the predominant recirculation inside the street canyon, especially for the windward wall heating. Moreover, analysis results have shown that the arcade width has larger influences on wind and thermal environment than that of the arcade height. Particularly, the wind velocity increases 2.1 to 3.8 times, the air temperature decreases 0.42–2.24 °C and the Physiological Equivalent Temperature value drops between 2.2 °C and 7.0 °C when the arcade width increases to half of building width.

Long-term trends of black carbon and particle number concentrations and their vehicle emission factors in Stockholm

Black carbon (BC) and particle number (PN) concentrations are usually high in cities due to traffic emissions. European mitigation policies, including Euro emission standards, have been implemented to curb these emissions. We analyzed BC and PN (particle diameter Dp > 4 nm) concentrations in Stockholm spanning the years 2013–2019 (BC) and 2009–2019 (PN) measured at street canyon and rooftop sites to assess the effectiveness of the implemented policies. Combining these data with inverse dispersion modeling, we estimated BC and PN emission factors (EFBC and EFPN) for the mixed fleet, reflecting real-world driving conditions. The pollutants showed decreasing trends at both sites, but PN concentrations remained high at the canyon site considering the World Health Organization (WHO) recommendations. BC concentrations declined more rapidly than PN concentrations, showing a −9.4% and −4.9% annual decrease at the canyon and −7.2% and −0.5% at the rooftop site in the years 2013–2019. The EFBC and EFPN trends showed that the mitigation strategies for reducing particulate emissions for on-road vehicles were successful over the study period. However, the introduction of biofuels in the vehicle fleet —ethanol and later rapeseed methyl ester (RME)— increased the concentrations of particles with Dp < 10 nm before the adoption of particulate filters in the exhausts. Stricter Euro emission regulations, especially with diesel particulate filters (DPF) in Euro 5, 6, and VI vehicles, led to 66% decrease in EFBC and 55% in EFPN. Real-world EFBC surpassed HBEFA (Handbook Emission Factors for Road Transport) database values by 2.4–4.8 times; however, direct comparisons between real-world and HBEFA EFPN are difficult due to differences in lower cut-off sizes and measurement techniques. Our results underscore the necessity for revising the HBEFA database, updating laboratory testing methods and portable emission measuring systems (PEMS) measurements to account for liquid condensate contributions to PN measurements.

Online Street View-Based Approach for Sky View Factor Estimation: A Case Study of Nanjing, China

The Sky View Factor (SVF) stands as a critical metric for quantitatively assessing urban spatial morphology and its estimation method based on Street View Imagery (SVI) has gained significant attention in recent years. However, most existing Street View-based methods prove inefficient and constrained in SVI dataset collection. These approaches often fall short in capturing detailed visual areas of the sky, and do not meet the requirements for handling large areas. Therefore, an online method for the rapid estimation of a large area SVF using SVI is presented in this study. The approach has been integrated into a WebGIS tool called BMapSVF, which refines the extent of the visible sky and allows for instant estimation of the SVF at observation points. In this paper, an empirical case study is carried out in the street canyons of the Qinhuai District of Nanjing to illustrate the effectiveness of the method. To validate the accuracy of the refined SVF extraction method, we employ both the SVI method based on BMapSVF and the simulation method founded on 3D urban building models. The results demonstrate an acceptable level of refinement accuracy in the test area.

Evaluating the impact of pavement reflectance and aspect ratio on thermal conditions in a scale model of a street canyon: introducing PAVSCAM

Evaluating the impact of pavement reflectance and aspect ratio on thermal conditions in a scale model of a street canyon: introducing PAVSCAM

Blinded by the light: does heat or light enhance wild mosquito (Diptera: Culicidae) attraction to CO2-baited traps in the Great Salt Lake area?

The New Jersey Light Trap has been among the earliest trap models used for mosquito surveillance in the United States. This trap was modernized in the 1950s to the miniature CDC light trap, with the addition of CO2 following soon after. The incandescent light has the tendency to attract nontarget insects, as well as losing a substantial portion of their energy as heat. Few studies have delineated whether heat or light in isolation make a difference in field collections using the former traps within the United States. Our study focused on isolating heat and light variables by using incandescent bulbs, light emitting diode (LED) bulbs, and electric heating patches affixed to a base model CO2 trap as designed at the Salt Lake City Mosquito Abatement District. Sites were selected in the urban and suburban foothills and canyons of the Wasatch Mountain front, industrial areas near the Salt Lake City International Airport, and rural wetlands in the marshes outlying the Great Salt Lake. Five traps were replicated within each sector during the summer and fall summer seasons. Collections were composed of Aedes dorsalis (Meigen), Culex pipiens L., Culex tarsalis Coquillett, and Culiseta inornata (Williston). Composition changes were a result of seasonal, rather than spatial, shifts. The results showed that LED light traps depressed collections of key species. Otherwise, there were negligible differences in collections among incandescent, heat film, and base model traps. In the Intermountain West, the miniature CDC trap is reliable enough to make programmatic decisions even if light usage varies by district.

Evaluation of surface urban energy and water balance scheme (SUEWS) using scaled 2D model experiments under various seasons and sky conditions

Urban energy balance models are essential for better understanding of urban climate processes and mitigating urban heat island intensity. In this study, the Surface Urban Energy and Water Balance Scheme (SUEWS) is evaluated using scaled outdoor experiments of idealized city models consisting of street canyons (aspect ratio H/W = 2, H = 0.5) and hollow concrete building models, under various seasonal and sky conditions in a humid subtropical climate in 2020, using three evaluation approaches. The results indicate that the model effectively simulates net all-wave radiation (Q∗), with the coefficient of determination (R2) exceeding 0.970. Storage heat flux (ΔQS) derived from the Objective Hysteresis Model (OHM) is compared to those obtained from the residual term method (RTM) and element surface temperature method (ESTM), revealing the RTM tend to overestimate ΔQS compared to the observation-based ESTM. Compared to using default OHM coefficients, applying fitted OHM coefficients obtained under seasons and sky conditions improves the simulations of ΔQS and sensible heat flux (QH), reducing statistical errors by approximately 50% for ΔQS and increasing R2 in rainy summer from 0.353 to 0.793 for QH, respectively. Additionally, the improved available energy simulation suggests the importance of accurately partitioning between QH and latent heat flux (QE) for the future development of SUEWS.

T-SPP: Improving GNSS Single-Point Positioning Performance Using Transformer-Based Correction

GNSS (global navigation satellite systems) technology enables high-precision single-point positioning (SPP) in open environments. However, the accuracy of GNSS positioning is significantly compromised in complex urban canyons due to signal obstructions and non-line-of-sight propagation errors. To address this challenge, we propose a GNSS displacement estimation algorithm. This method learns nonlinear dependencies between GNSS raw measurements and corresponding position changes, capturing dynamic and layered features in GNSS measurement data for displacement estimation. We introduce a denoising auto-encoder (DAE) to preprocess raw GNSS observations, reducing the impact of noise. The model simultaneously outputs estimated displacement and model confidence. The fusion process dynamically combines positioning results from the SPP algorithm and the D-Tran model, adaptively blending them to achieve accurate and optimal positioning estimation. This approach optimizes the accuracy of estimated positioning results while maintaining confidence in the estimation. Experimental results show a 61% reduction in root mean square error (RMSE) and 100% availability in urban canyon environments compared to traditional single-point positioning techniques.