Urban Construction Research Articles

The impact of smart city construction on labour distortions from the perspective of labour mobility: evidence from China

ABSTRACT Migration decisions and labour demand are influenced by smart city construction (SCC). However, the impacts of SCC on the labour market remain black-boxed. This paper investigates the impacts of SCC on labour market distortions through an examination of a large-scale smart city pilot policy in China. Utilising urban panel data in China spanning 2008-2019, we employ a multi-period difference-in-difference model to examine the labour factor allocation effects of SCC. Our findings reveal that SCC effectively mitigates labour wage distortion (LWD) but has an adverse effect on labour misallocation (LMA). labour mobility is a critical mechanism through which SCC alleviates labour wage distortion (LWD) but exacerbates labour misallocation (LMA). Furthermore, the results of heterogeneity analysis indicate that strongly connected and high human capital cities not only benefit from SCC in alleviating LWD but also avoid its negative effects on LMA. Conversely, SCC neither improves LWD nor alleviates LMA in weakly connected and low human capital cities. These findings imply that urban smart construction causes multiple impacts on the labour factor market, which is conducive to factor market guidance policies that can coordinate with SCC.

Sponge City Development from the Perspective of Sustainability: A Case Study of China

Traditional urban construction methods often result in the inability of rainwater to penetrate and store effectively, increasing the risk of urban flooding disasters. At the same time, due to the rapid development of urbanization, the problem of water shortage has become increasingly prominent. The sponge city policy aims to transform the urban construction mode, make full use of natural resources and ecological means, realize the natural accumulation, infiltration and purification of rainwater, and improve the city's absorption, storage and release capacity of rainwater, so as to reduce urban flood disasters and alleviate the shortage of water resources. This paper takes China as an example to explore the construction of a sponge city from the perspective of sustainable development. This paper analyzes the current situation and existing problems of sponge cities development in China, and puts forward the development prospect of PPP model, in order to promote sponge cities construction and sustainable urban development.

Impact of urban land use tax on carbon emission efficiency of urban construction land--Analysis based on panel data of 30 provinces in China.

Reducing urban carbon emissions is an important path for ecological civilization construction, which can be achieved through the adjustment of urban land use tax. Using provincial Panel data from 2011 to 2021, based on the analysis of urban carbon emission efficiency values using a non radial SBM model, the Tobit random effects panel model is used to explore the institutional impact of urban land use tax. The study found that urban land use tax has a significant positive promoting effect on carbon emission efficiency and shows certain regional differences. The eastern region is higher in overall efficiency and technical efficiency than the central and western regions, but the central region has the highest overall scale efficiency. At the same time, factors such as population urbanization, industrial structure, and energy-saving technology level will also have a certain impact on this effect. Based on the institutional effect of improving carbon emission efficiency, the article proposes corresponding countermeasures and suggestions from aspects such as tax rate levels, tax system adjustments, tax incentives, and differentiated regional arrangements.

The Cost of Urban Renewal: Annual Construction Waste Estimation via Multi-Scale Target Information Extraction and Attention-Enhanced Networks in Changping District, Beijing

Construction waste is an inevitable byproduct of urban renewal, causing severe pressure on the environment, health, and ecology. Accurately estimating the production of construction waste is crucial for assessing the consumption of urban renewal. However, traditional manual estimation methods rely heavily on statistical data and historical experience, which lack flexibility in practical applications and are time-consuming and labor-intensive. In addition, their accuracy and timeliness need to be improved urgently. Fortunately, with the advantages of high-resolution remote sensing images (HRSIs) such as strong timeliness, large amounts of information, and macroscopic observations, they are suitable for the large-scale dynamic change detection of construction waste. However, the existing deep learning models have a relatively poor ability to extract and fuse features for small and multi-scale targets, and it is difficult to deal with irregularly shaped and fragmented detection areas. Therefore, this study proposes a Multi-scale Target Attention-Enhanced Network (MT-AENet), which is used to dynamically track and detect changes in buildings and construction waste disposal sites through HRSIs and accurately estimate the annual production of urban construction waste. The MT-AENet introduces a novel encoder–decoder architecture. In the encoder, ResNet-101 is utilized to extract high-level semantic features. A depthwise separable-atrous spatial pyramid pooling (DS-ASPP) module with different dilation rates is constructed to address insufficient receptive fields, resolving the issue of discontinuous holes when extracting large targets. A dual-attention mechanism module (DAMM) is employed to better preserve positional and channel details. In the decoder, multi-scale feature fusion (MS-FF) is utilized to capture contextual information, integrating shallow and intermediate features of the backbone network, thereby enhancing extraction capabilities in complex scenes. The MT-AENet is used to extract buildings and construction waste at different periods in the study area, and the actual production and landfill volume of construction waste are calculated based on area changes, indirectly measuring the rate of urban construction waste resource conversion. The experimental results in Changping District, Beijing demonstrate that the MT-AENet outperforms existing baseline networks in extracting buildings and construction waste. The results of this study are validated according to government statistical standards, providing a promising direction for efficiently analyzing the consumption of urban renewal.

Triggering of Land Subsidence in and Surrounding the Hangjiahu Plain Based on Interferometric Synthetic Aperture Radar Monitoring

In the early stages, uncontrolled groundwater extraction led to the Hangjiahu (HJH) Plain becoming one of the areas with the most severe land subsidence in China. Since the beginning of this century, comprehensive measures have been taken to control the continuous aggravation of large land subsidence patterns in some areas; however, urban land subsidence issues, influenced by various factors, still persist and exhibit complex geographical distribution characteristics. In this study, we utilized Sentinel-1A images and the SBAS-InSAR technique to capture surface deformation over the HJH Plain in Zhejiang from 16 March 2017 to 20 January 2023. Through a comparative analysis with geological conditions, changes in surface mass loading, rainfall and groundwater, and land use types, we discussed the contributions of natural and anthropogenic factors to land subsidence. Augmented with optical remote sensing images and field investigations, we conducted a correlation analysis of the land subsidence status. The preliminary findings suggest that changes in surface mass loading and short-term heavy rainfall under extreme weather conditions can lead to periodic land subsidence changes in the region. Additionally, extensive infrastructure construction triggered by urbanization has resulted in significant and sustained land subsidence deformation. The research findings play an important guiding role in formulating scientifically effective strategies for land subsidence prevention and control, as well as urban planning and construction.

THE NEW URBAN CONCEPT OF HANSEATIC CITIES OF THE RIGA ARCHBISHOPRIC IN THE 13TH–14TH CENTURIES

Bishop of Riga Albert established bishoprics and centers of spiritual life on the Southern Baltic Sea coast to subjugate the local population. Sacred buildings were the main architectural highlights of the urban environment. Later, Riga became the main military base for expansion in the Baltics, the economic base of the Teutonic Order, and the administrative center of the Archbishopric of Riga (1255–1562). On the Baltic Sea coast, new bishoprics began to be established in the lands of the subject Prussians. Important cities were involved in the Hanseatic League. Consequently, the concept of urban planning and construction changed in the 13th– 14th centuries. Research object: urban space of the Hanseatic League cities on the Prussian lands in the 13th–14th centuries. Research problem: sacral buildings changed urban aesthetics and the urban space of the Hanseatic cities, which has not been studied enough to preserve their identity. Research goal: analysis of the impact of churches for the citizenship parishes on the planning, visual image, and architectural-spatial development of the Hanseatic League cities in the lands of the subject Prussians. Novelty: analysis of common and local features of the structural evolution of the Hanseatic cities under the authority of the Archbishopric of Riga during the 13th and 14th centuries. Research methods: analysis of archive documents, projects, cartographic materials, and studies of published literature.

Numerical Simulation of Double Row Piles Prestressed Anchor Cable Support Based on ABAQUS

With the development of urban construction, there are more and more high-rise buildings, and excavation support methods have emerged. Traditional support methods have the drawbacks of a small range of safety factors and high economic requirements. Based on this, this article proposes a new type of support method using double row piles and prestressed anchor cables, and establishes a numerical model using ABAQUS software. The results indicate that: (1) As the excavation depth increases, the horizontal displacement of the foundation ditch continues to increase, and the displacement of the piles also continues to increase. (2) After soil excavation, there is a bottom bulge phenomenon at the bottom of the foundation ditch, and the piles move upwards, causing the soil around the foundation ditch to decrease.

Selection of Water Transmission Method and Analysis of Pipe Network Zoning in Municipal Water Supply and Drainage Design

With the acceleration of urbanization, the demand for water supply and drainage pipe networks has increased significantly. In the planning of urban construction, it is necessary to optimize the design of the water supply and drainage system pipe network to effectively save energy while providing residents with more accessible water resources. Therefore, the municipal water supply and drainage system and the water transmission methods should be designed according to the geographical conditions of the city. In this paper, we mainly analyze the design of municipal water supply and drainage systems and the selection of water transmission methods. Besides, the optimization of the water supply and drainage network zoning process and pipe network maintenance is also discussed, so as to provide a reference for municipal water supply and drainage work.

Computer vision neural networks in support systems for making decision on a smart farm

The creation of smart farms and urban farms (city farm) has become one of the development trends in recent years, both in agroengineering and in urban construction. A high level of automation significantly reduces the degree of human participation in the production processes of a smart farm. As a result, the requirements for the experience and professional knowledge in the field of agriculture of the owner and staff of such a farm are reduced. The article discusses the issues of creating intelligent decision support systems for a “smart” agricultural farm, in particular, for urban, city farms. In such systems, artificial neural networks (ANN) of computer vision are used to process the results of observations and recognize situations requiring human intervention. Using the example of an urban farm for growing strawberries, a number of applied tasks are formulated (detection of fruits classified by maturity, detection and classification of diseases, detection of stolons). The results of an experimental study of computer vision systems for these tasks are presented. The research methodology included the use of pre-trained neural network models with their additional training on their own sets of images and subsequent assessment of the accuracy of detection and classification. Neural networks configured for such tasks in decision support systems are complemented by algorithms working with knowledge bases and computational and logical models. Thus, a hardware and software complex is being created that allows not only to automate the execution of current business tasks, but also to recommend solutions in case of difficult situations that normally require a lot of professional experience and knowledge from the staff. The study was conducted on the basis of the agrobiotechnical complex of Tyumen State University.

A Two-Layer SD-ANN-CA Model Framework for Multi-Typed Land Use and Land Cover Change Prediction under Constraints: Case Study of Ya’an City Area, Western China

Land use and land cover change (LUCC) prediction of cities in Western China requires higher accuracy in quantitative demand and spatial layout because of complex challenges in balancing relationships between urban constructions and ecological developments. Considering city-level areas and various types of land use and land cover, existing LUCC models without constraint or with only loose demand constraints were impractical in providing evidence of high accuracy and high-resolution predictions in areas facing fierce land competition. In this study, we proposed a two-layer SD-ANN-CA model to simulate and explore the LUCC trend and layout predictions for 2018, 2028, and 2038 in Ya’an City, Western China. The two-layer structure with an upper layer of the SD model and a lower layer of the ANN-CA model, as well as the advantages of all three methods of system dynamics (SD), artificial neural network (ANN), and cellular automata (CA), have allowed us to consider the macro-level demand constraints, meso-level driving factors constraints, and the micro-level spatial constraints into a unified model framework. The simulation results of the year 2018 have shown significant improvement in the accuracy of the ANN-CA model constructed in our earlier work, especially in types of forest land (error-accuracy: 0.08%), grassland (error-accuracy: 0.23%), and construction land (error-accuracy: 0.18%). The layout predictions of all six types of land use in 2028 and 2038 are then carried out to provide visual evidence support, which may improve the efficiency of planning and policy-making processes. Our work may also provide insights into new ways to combine quantitative methods into spatial methods in constructing city-level or even regional-level LUCC models with high resolution.

Spatio-temporal data fusion techniques for modeling digital twin City

ABSTRACT The digital twin city technique maps the massive city environmental and social data on a three-dimensional virtual model. It presents the operational status of physical world and supports intelligent city governance. However, the inefficient utilization of distributed data resources, and the lack of sharing and collaboration among multiple departments restrict the data formulation of digital twin city construction. This research proposes a new cross-domain spatio-temporal data fusion framework for supporting complex urban governance. It integrates the heterogeneous urban information generated and stored by different government departments using multiple-information techniques. A specified geographic base reflecting the real city status is established, using geographical entities with unified address as identifiers to encapsulate the urban elements information. We introduce a comprehensive urban spatio-temporal data center construction process, which has already supported multiple urban governance projects. The two distinct advantages in using this data fusion system are: 1) The proposed Bert+PtrNet+ESIM-based address mapping method associates the urban elements information to their corresponding geographic entities with 99.3% F1-Score on real-world dataset. 2) The Wuhan spatio-temporal data center operation illustrates the capability of our framework for complex urban governance, which significantly improves the efficiency of urban management and services. This integrated system engineering provides reference and inspiration for further spatio-temporal data management, which contributes to the future social governance in digital twin city platform.

Application of new features based on artificial intelligent robot technology in medium-scale urban design pedigree and intelligent management and control

Since the 21st century, China has been vigorously developing urban construction, and now the rise of artificial intelligence (AI) has brought new opportunities for urban design and management. Meso-scale cities are the most developed cities in China and play an important role in economic and social development. The current robot technology is mainly divided into industrial robots and service robots, which can play an important role in the development of cities. This paper aims to apply AI robotics technology to the analysis and intelligent management of mesoscale urban design genealogy. Firstly, the development pedigree of the mesoscale city was analyzed, from which the characteristics of previous designs could be clearly understood. Then, the urban management and control system is intelligently designed from many aspects, the characteristics of the robot are analyzed, and the application of the intelligent robot in urban design is introduced. After that, four developing meso‑scale cities in a province were selected as the evaluation objects, and an Analytic Hierarchy Process (AHP) was proposed to evaluate the application effect of robotics technology in meso‑scale cities. The results showed that the overall score of the robot in urban traffic design was greater than 70 points, and the overall score of urban architectural design was greater than 65 points, which was in the acceptable range. In the application score of urban environment design, the influence was about 70 to 80 points, and the aesthetics was more than 75 points. The cultural aspect of the design impact score was no more than 75 points, while the cultural support aspect score was around 80 points. After the weight calculation, the final overall score was 489 points, and the comprehensive average score was 36 points. The overall composite score and average score were both good. This showed that the application of robot technology to the pedigree analysis and intelligent management and control of mesoscale urban design could achieve good results.

Three-Dimensional ERT Advanced Detection Method with Source-Position Electrode Excitation for Tunnel-Boring Machines

Tunnel-boring machines (TBMs) are widely used in urban underground tunnel construction due to their fast and efficient features. However, shield-tunnel construction faces increasingly complex geological environments and may encounter geological hazards such as faults, fracture zones, water surges, and collapses, which can cause significant property damage and casualties. Existing geophysical methods are subject to many limitations in the shield-tunnel environment, where the detection space is extremely small, and a variety of advanced detection methods are unable to meet the required detection requirements. Therefore, it is crucial to accurately detect the geological conditions in front of the tunnel face in real time during the tunnel boring process of TBM tunnels. In this paper, a 3D-ERT advanced detection method using source-position electrode excitation is proposed. First, a source-position electrode array integrated into the TBM cutterhead is designed for the shield-tunnel construction environment, which provides data security for the inverse imaging of the anomalous bodies. Secondly, a 3D finite element tunnel model containing high- and low-resistance anomalous bodies is established, and the GREIT reconstruction algorithm is utilized to reconstruct 3D images of the anomalous body in front of the tunnel face. Finally, a physical simulation experiment platform is built, and the effectiveness of the method is verified by laboratory physical modeling experiments with two different anomalous bodies. The results show that the position and shape of the anomalous body in front of the tunnel face can be well reconstructed, and the method provides a new idea for the continuous detection of shield construction tunnels with boring.

How to restore ecological impacts from wind energy? An assessment of Zhongying Wind Farm through MSPA-MCR model and circuit theory

The wind energy industry is developing rapidly in China with a maximum capacity worldwide. Meanwhile, the stability of the ecological network is challenged by extensive renewable energy expansion. There are still research deficiencies in wind farm ecological impacts at project scale from an ecological restoration perspective. It is of great necessity to monitor the ecological impacts with time going and explore ecological restoration strategies for wind power development. The research case of Zhongying Wind Farm is selected based on investigation and interviews regarding its ecological impact in the prior study. It employs a comparative methodology by comparing the ecological quality before and after the construction of Zhongying Wind Farm. Raw data from Landsat 8, the Digital Elevation Model (DEM), the Normalized Difference Vegetation Index (NDVI), and wind turbine statistics originating from open data platforms are analyzed and visually represented with ArcGIS. This paper establishes an ecological network based on morphological spatial pattern analysis (MSPA) and the Minimum Cumulative Resistance (MCR) model to quantify wind farms’ impacts on ecological corridors. The circuit theory and Pajek software are used to identify and categorize the ecological nodes into weak and obstacle points. The results reveal that ecological impacts on ecological corridors decay with distance, reflecting changes in length, connection strength and cumulative values of corridors. While the impacts on ecological nodes depend on nodes’ attributes: the number of weak points increased by 18.5 %, and obstacle points increased by 350 %, with their locations shifting from the edges of urban construction sites to the edges of wind farm. Differentiated strategies are proposed according to the impact magnitude of each ecological corridor and node: such as dynamic inspection mechanism, construction prohibition for protection; corridor structure and function recovering, stepping stones addition for restoration; buffer belts, warning radar, and monetary schemes for compensation. This research fills the gap of ecological impact assessment under the challenges of wind energy expansion. It helps to balance wind energy development and ecological restoration at the regional level.

Visualization analysis of urban planning assistant decision network 3D system based on intelligent computing

In recent years, with the continuous development of urban construction and the continuous expansion of urban population, the contradiction between spatial planning and actual urban needs in urban construction has become increasingly acute. However, planning decisions based on traditional urban planning renderings and two-dimensional (2D) planar plans are no longer in line with the actual development needs and specific development status of the city. Urban planning 3D auxiliary systems can improve the accuracy and precision of urban planning decisions. By providing planners with detailed 3D spatial models of the urban environment, potential design defects or conflicts can be identified before urban construction starts. This can reduce costs and risks related to urban development and help create a more livable and sustainable urban environment. This article analyzed and studied urban planning problems based on a three-dimensional (3D) auxiliary system of intelligent computing. In order to examine the effectiveness of intelligent computing 3D auxiliary systems in urban planning and construction, three indicators of development sustainability, transportation network convenience, and urban livability were established for effectiveness evaluation. The final experimental results showed that the average score of the 3D urban planning assistance system based on intelligent computing in urban development sustainability was 9.29 points, transportation convenience score was 92.08 points, and urban livability score was 9.249 points.

Agricultural Land Suitability Assessment Based on GIS at the County Scale in Yibin, China

As agricultural land resources scarce, food security has emerged as a pressing global concern. Conducting a suitability assessment of agricultural land is crucial for agricultural resources and food security. To establish an evaluation index system, we incorporated land, water, climate, and society four dimensions of 16 indicators. And we incorporated Entropy Weight Method (EWM), an objective method, with integrated evaluation model to assess agricultural land suitability in Yibin. Based on actual agricultural production, areas of land of urban construction, rural settlement and mining and water are subtracted. The Findings found that agricultural land suitability in Yibin presented a significant spatial heterogeneity. Areas with suitability and relative suitability accounted for 57.61% of Yibin’s land areas, which suggest Yibin has an abundance of agricultural land resources. Regions moderately suitable predominantly lie in the western and southern areas, covering 32.22% of the land area. Generally suitable areas accounted for 10.03% of Yinbin’s land areas, spatial distribution of which is similar to moderately suitable regions. Moderately and generally areas are potential areas for agricultural production. And regions for unsuitable accounted for only 0.14% of land areas. Overall, results mentioned above indicate that Yibin's agricultural land resources are in good condition. Considered terrain and water sources, this study revealed that the spatial distribution of topography and annual precipitation in Yibin closely mirrored both suitable and relatively suitable regions.

Study on the Evaluation of Urban Park Landscape Pattern Index and Its Driving Mechanisms in Nanchang City

Urban planning is often influenced by industrial and construction activities, leading to a lack of attention to the planning and construction of urban parks, which results in prominent spatial layout problems. Urban parks, as an important part of the urban green space system, play a significant role in improving the ecological environment, promoting urban economic development, and enhancing the daily living standards of the people. As a typical representative of China’s second and third-tier cities, Nanchang’s analysis of the evolution process of urban landscape patterns has reference significance for other similar cities in China. This paper is based on the theoretical foundations of landscape ecology, human geography, and urban planning, and analyzes the evolution of the park landscape pattern in the central urban area of Nanchang from 1999 to 2019 from the perspective of urban context, revealing the driving mechanisms. It provides important references and bases for the further optimization and construction development of the park landscape pattern in Nanchang. The results show that the park area and number in the central urban area of Nanchang have significantly increased, with the overall layout evolving from “central aggregation” to “core aggregation in each area”, and from “central scarcity, more on the periphery” to “inward concentration, outward diffusion”. However, the distribution of various types of parks is uneven, and there is a lack of green corridor links between parks. The park landscape pattern is driven by multiple factors such as natural factors of urban context, socio-economic factors, urban construction factors, historical policies, and related planning, which can have positive or negative effects. Incorporating relevant urban factors into the park planning system analysis can promote the benign development of urban context and park landscape layout, thereby achieving the “parkification” of the city.

Fine Shear-Wave Velocity Structures of Subsurface beneath the Guangdong–Hong Kong–Macao Greater Bay Area with Dense Seismic Array and SPAC Method

Abstract We apply the spatial autocorrelation (SPAC) method to construct the 3D subsurface shear-wave velocity structure model using the short-period dense seismic array (containing 725 nodal geophones) located at the Guangdong–Hong Kong–Macao Greater Bay area (GBA). We first divided the dense array into numerous subarrays, with each subarray consisting of nine nodal geophones, and obtained 562 subarrays that can provide 1D VS profiles of the same quantity. Then, the SPAC method and genetic algorithm are utilized to extract the dispersion curve of the Rayleigh wave from the raw microtremor data and invert VS structure, respectively. Finally, a 3D VS structure model from the surface to 3.3 km depth is derived by combining all 1D VS structures. Relatively low-velocity anomalies above 700 m are considered unconsolidated shallow sediments as well as relatively high-velocity anomalies beneath 1100 m are attributed to consolidated granite bedrock. Meanwhile, low-velocity anomalies that are identified through the vertical VS profile at a depth of about 900–3000 m can be contributed to the fractured zone, and striped low-velocity anomalies in the horizontal VS maps reveal the location of the deeply buried faults in the study area. The results also mean that the SPAC method combined with the records of short-period dense seismic array can be effectively applied to image subsurface structures in high-populated urban area. The development of this noise-resistance and environment-friendly geophysical technique provides a reliable and effective way to explore the complicated subsurface geological structures, which is of great significance to urban engineering construction and earthquake disaster reduction work in densely populated urban agglomerations.

Administrative-led urbanization and urban carbon emission intensity: Evidence from city-county merger in China

Cities in China are concentrated areas of energy consumption and carbon emission. Thus, controlling urban carbon emission intensity is the key to achieving “carbon neutrality” and “carbon peak” goals. Administrative urbanization, for which city–county merger (CCM) plays an important role, is yet to be examined to understand whether it intensified carbon emissions. This study uses panel data of 269 cities from 2008 to 2019 and staggered difference-in-differences method to analyze the impact of administrative-led urbanization on urban carbon emission intensity. The results reveal that the CCM significantly increased urban carbon emission intensity. A mechanism test shows that the CCM can increase carbon emission intensity by inhibiting industrial structure upgrading and promoting urban infrastructure construction. Heterogeneity analysis shows that there is no significant regional difference in carbon intensity; however, regional difference has a more significant positive impact on carbon intensity of sub-provincial cities, general prefecture-level cities, and strong counties with districts.

Assessing Traffic Noise and Its Impact on High-Rise Apartment Buildings Adjacent to an Urban Expressway: A Case Study in Chengdu, China

With rapid urbanization, traffic growth has accelerated in some cities in China. Due to strict urban construction land utilization policies, many high-rise apartment buildings have been constructed adjacent to expressways. To better understand the impact of urban traffic noise on the residents of high residential buildings adjacent to expressways and the differences in noise impacts on different floors, on-site noise monitoring and questionnaires for building residents have been conducted. The characteristics of traffic noise were analyzed based on the measured data, and factors, including time periods and building floors, were considered. According to the results of the questionnaire survey, 56.06% of the male respondents and 54.55% of the female respondents think that the impact of traffic noise on high-rise buildings is “high” or “very high”; 50.53% of the respondents who were in “good” or “very good” condition thought that the traffic noise has a “significant impact” or “very significant impact” on their sleep and daily life. In addition, 25% of respondents living on floors 4–10 and 62.5% of respondents living on floors 11–20 considered the traffic noise to have a “significant impact” or “very significant impact” on their sleep and daily life. The on-site noise monitoring results show that the noise levels (LAeq) outside the windows of the studied buildings remain significantly elevated, with daytime noise on working days ranging from 56 to 70 dB(A), and on weekends ranging from 50 to 65 dB(A). During the four time periods on weekdays from 7 a.m. to 9 a.m., 11 a.m. to 1 p.m., 5 p.m. to 7 p.m., and 10 p.m. to 12 a.m., the average LAeq levels on floors 11–20 are higher than those on floors 4–10 by 4.04 dB(A), 4.92 dB(A), 4.06 dB(A), and 2.67 dB(A), respectively. Similarly, during these time periods on weekends, the levels on floors 11–20 are higher than those on floors 4–10 by 4.96 dB(A), 6.32 dB(A), 5.28 dB(A), and 5.24 dB(A), respectively. This indicates that floors 4–10 of the building experience relatively lower noise levels, while floors 11–20 are subjected to comparatively higher levels of noise disturbance.