Spatial Analysis Research Articles

Frequencies of micronuclei in buccal cells and their spatial distribution in a population living in proximity to coal mining areas in southern Brazil

The extraction and burning of coal release genotoxic pollutants, and understanding the relationship between genetic damage and the spatial distribution of residences in coal-using regions is crucial. The study aimed to conduct a spatial analysis of genotoxic damage through the of micronuclei (MNs) number and their proximity to coal mining/burning in the largest coal exploration region in Brazil. In this study, the detection of genotoxic damage was performed using the MN assay in oral cells of residents exposed to coal mining activities. Spatial analysis was conducted using QGIS 3.28.10 based on information obtained from a questionnaire administered to the population. Multiple linear regression analysis was carried out to assess the influence of the distance from residential areas to polluting sources on the number of MNs found. Additionally, Spearman's correlation was performed to identify the strength and direction of the association between the frequency of MNs and each of the polluting sources. A total of 147 MNs were quantified among all participants in the coal mining region. Notably, residents living within 2 km and 10 km of pollution sources exhibited the highest prevalence of MNs. The analysis demonstrated a significant correlation between closer proximity to pollution sources and increased MN frequency, underscoring the spatial relationship between these sources and genotoxic damage. Environmental pollutants from anthropogenic sources present a major health risk, potentially leading to irreversible damage. The spatial analysis in this study highlights the importance of targeted public policies. These policies should aim for a sustainable balance between economic development and public health, promoting effective measures to mitigate environmental impacts and protect community health.

Fundamental LCZ Mapping with ArcGIS-Based Spatial and Correlational Analyses to Study the Impacts of Infrastructural Area- Maximum Volume (A-MV) Attributes on OTC – An Urban Aw Summer Case

The aim of this study is to map the study location stretches into 100mx100m local climate zones (LCZs) on the basis of primary observations and secondary photographic data for spatial analysis of various urban infrastructural elements (grey(G)-built structures, blue(B)-water bodies and green (Gr)-natural vegetation) and impact assessment of their estimated area (EA) and maximum volume (EMV)) on the air temperature (Ta) that characterizes the outdoor thermal comfort (OTC). Climate Modification by Urban Infrastructure, Fundamental Concepts of Urban Infrastructure Mensuration Parameters, Fundamental Concepts of Urban Grey Blue Green Infrastructure (UGBGI) and Concepts Of OTC, Koppen Classification and LCZs are the linked areas. Study locations are based on socio-economic and geophysical attributes. Initial 200 pilot survey responses regarding thermal sensation votes and other subjective details were used. Preferred values of Physiological Equivalent Temperature (PET) and optimum Ta have been used. After the mapping in ArcGIS and polygonal delineation of the areas, EA values were compiled in tabular format. Based on primary measurements and secondary studies, a maximum height (hmax) value was assigned to each sub-category for EMV evaluation. Statistically, the EA and estimated perimeter (EP) values were analyzed using QQ, scatter plots, histogram and generate near table tools in ArcGIS. EA and EMV values were correlated with mean Ta values by linear regression. The R-square values generated gave a clear idea about the extent of their impacts on Ta. From the established relationships and preferred PET and optimum Ta values, optimum EA, EMV and hmax values of the broader categories(G,B,Gr) required for preferred OTC levels were finally evaluated.

Phytoplankton biomass in northern lakes reveals a complex response to global change

Global change may introduce fundamental alterations in phytoplankton biomass and community structure that can alter the productivity of northern lakes. In this study, we utilized Swedish and Finnish monitoring data from lakes that are spatially (135 lakes) and temporally (1995-2019, 110 lakes) extensive to assess how phytoplankton biomass (PB) of dominant phytoplankton groups related to changes in water temperature, pH and key nutrients [total phosphorus (TP), total nitrogen (TN), total organic carbon (TOC), iron (Fe)] along spatial (Fennoscandia) and temporal (25 years) gradients. Using a machine learning approach, we found that TP was the most important determinant of total PB and biomass of a specific species of Raphidophyceae - Gonyostomum semen - and Cyanobacteria (both typically with adverse impacts on food-webs and water quality) in spatial analyses, while Fe and pH were second in importance for G. semen and TN and pH were second and third in importance for Cyanobacteria. However, in temporal analyses, decreasing Fe and increasing pH and TOC were associated with a decrease in G. semen and an increase in Cyanobacteria. In addition, in many lakes increasing TOC seemed to have generated browning to an extent that significantly reduced PB. The identified discrepancy between the spatial and temporal results suggests that substitutions of data for space-for-time may not be adequate to characterize long-term effects of global change on phytoplankton. Further, we found that total PB exhibited contrasting temporal trends (increasing in northern- and decreasing in southern Fennoscandia), with the decline in total PB being more pronounced than the increase. Among phytoplankton, G. semen biomass showed the strongest decline, while cyanobacterial biomass showed the strongest increase over 25 years. Our findings suggest that progressing browning and changes in Fe and pH promote significant temporal changes in PB and shifts in phytoplankton community structures in northern lakes.

Spatially resolved tissue imaging to analyze the tumor immune microenvironment: beyond cell-type densities

IntroductionThe tissue immune microenvironment is associated with key aspects of tumor biology. The interaction between the immune system and cancer cells has predictive and prognostic potential across different tumor types....

Gonorrhea cluster detection in Manitoba, Canada: Spatial, temporal, and spatio-temporal analysis

In Canada, Gonorrhea infection ranks as the second most prevalent sexually transmitted infection. In 2018, Manitoba reported an incidence rate three times greater than the national average. This study aims to investigate the spatial, temporal, and spatio-temporal patterns of Gonorrhea infection in Manitoba, using individual-level laboratory-confirmed administrative data provided by Manitoba Health from 2000 to 2016. Age and sex patterns indicate that females are affected by infections at younger ages compared to males. Moreover, there is an increase in repeated infections in 2016, accounting for 16% of the total infections. Spatial analysis at the 96 Manitoba regional health authority districts highlights significant positive spatial autocorrelation, demonstrating a clustered distribution of the infection. Northern districts of Manitoba and central Winnipeg were identified as significant clusters. Temporal analysis shows seasonal patterns, with higher infections in late summer and fall. Additionally, spatio-temporal analysis reveals clusters during high-risk periods, with the most likely cluster in the northern districts of Manitoba from January 2006 to June 2014, and a secondary cluster in central Winnipeg from June 2004 to November 2012. This study identifies that Gonorrhea infection transmission in Manitoba has temporal, spatial, and spatio-temporal variations. The findings provide vital insights for public health and Manitoba Health by revealing high-risk clusters and emphasizing the need for focused and localized prevention, control measures, and resource allocation.

Long-Term Response of Floodplain Meadow Normalized Difference Vegetation Index to Hydro-Climate and Grazing Pressure: Tamir River Plains, Mongolia

The greenery of floodplain meadows in arid regions, such as Mongolia, is influenced by climate, hydrology, and land use. In this study, we analyzed the NDVI (Normalized Difference Vegetation Index) of two floodplain meadows located along the South Tamir and Tamir Rivers using LANDSAT images. Our goal was to observe NDVI spatial changes, variations, and mean values in mid-August every six years from 1991 to 2015 and to identify the factors driving these differences. To achieve this, we conducted variance analysis to identify changes in NDVI and implemented Principal Component Analysis to determine the influence of hydro-meteorological factors and grazing intensity. Our findings indicate a significant decrease in greenness, as measured by pixel-scale NDVI, during the late summer period. This decrease was consistently observed, except for a series of harsh winters that followed relatively dry summers, resulting in a disastrous event called dzud, which led to the death of livestock. The decrease in NDVI was amplified by lower precipitation in June, higher temperatures and wind speed in July, and increased precipitation in August, along with a higher frequency of days with convective rain. Our findings have important implications for managing grazing in Mongolia’s grasslands, promoting sustainable land use, and mitigating sandstorms. The variance and average values of NDVI at the pixel level can serve as reliable markers of sustainable pasture management in areas where other vegetation measures are limited.

Assessment of Gait Patterns during Crutch Assisted Gait through Spatial and Temporal Analysis.

The use of crutches is a common method of assisting people during recovery from musculoskeletal injuries in the lower limbs. There are several different ways to walk with crutches depending on the patient's needs. The structure of crutch gaits or crutch gait patterns varies based on the delay between the aid and foot placement, the number of concurrent points of contact, and laterality. In a rehabilitation process, the prescribed pattern may differ according to the injury, the treatment and the individual's condition. Clinicians may improve diagnosis, assessment, training, and treatment by monitoring and analyzing gait patterns. This study aimed to assess and characterize four crutch walking patterns using spatial and temporal parameters obtained from the instrumented crutches. For this purpose, 27 healthy users performed four different gait patterns over multiple trials. Each trial was recorded using a portable system integrated into the crutches, which measured force, position, and acceleration. Based on the data angle, an algorithm was developed to segment the trials into gait cycles and identify gait phases. The next step was to determine the most appropriate metrics to describe each gait pattern. Several metrics were used to analyze the collected data, including force, acceleration, angle, and stride time. Among 27 participants, significant differences were found between crutch gait patterns. Through the use of these spatial and temporal parameters, promising results were obtained for monitoring assisted gait with crutches. Furthermore, the results demonstrated the possibility of using instrumented crutches as a clinical tool.

Construction of coastal zone ecological network based on the perspective of land-sea integration: A case study of Jinzhou City, China

The rapid urbanization of coastal zones has intensified ecological challenges in both land and marine environments, leading to increased landscape fragmentation. The scientific establishment of ecological network, which plays a pivotal role in safeguarding coastal biodiversity and ecological security, represents a significant approach to effectively connecting fragmented habitats within the coastal zone. The study selected Jinzhou in Liaoning Province and its adjacent coastal seas as the research area. The ecological sources within the study area were identified by supplementing ecological red line data, employing morphological spatial pattern analysis (MSPA), comprehensive habitat quality evaluation, landscape connectivity assessment, and ecological sensitivity evaluation. The land-sea integrated resistance surface was constructed by considering both natural and anthropogenic impacts. Ecological corridors were extracted based on circuit theory, and measures to optimize the ecological network were proposed. The results showed that: (1) The ecological sources of Jinzhou City was primarily distributed in the significant ecological functional areas or sensitive regions such as Yixian Yanwulu Mountain, Xihe Mountain, Dabijiashan special protection island, and Liaohe Estuary Protection area, with a total area of 1840.35 km2 (2) The ecological corridors within the study area were primarily located in the municipal areas of Jinzhou City District, Linghai City, Yixian County, Beizhen City, and Heishan County. The distribution of corridors in the sea area was relatively sparse. (3) The addition of supplementary ecological sources significantly improved the connectivity of the optimized ecological network. The results of the study can provide scientific insights for guiding the construction of coastal ecological networks and integrated land-sea ecosystem management in coastal regions.

Spatio-Temporal Analysis of Vegetation Index Change on Land Surface Temperature in Yogyakarta Special Region Using MODIS Imagery (2000-2023)

Yogyakarta has become a province renowned for its abundance of tourist destinations and learning opportunities for students from all over Indonesia. Temperature and vegetation density are key factors contributing to comfort in both academic pursuits and recreational activities. This study utilizes NDVI (Normalized Difference Vegetation Index) and LST (Land Surface Temperature) to determine these crucial parameters. MODIS imagery serves as a vital data source for analyzing NDVI and LST. The aim of this research is to comprehend the environmental dynamics of DIY (Yogyakarta Special Region) by exploring the relationship between NDVI and LST. Through the Pearson correlation method, the relationship between these variables is deeply evaluated. The analysis reveals a significant correlation between changes in NDVI and LST, indicating a complex interaction between vegetation and land surface temperature. However, these significant findings have minimal impact on Yogyakarta City and Sleman, which serve as the focal points of community activities in Yogyakarta. These changes can be attributed to various factors, including changes in land use, urbanization, and climate variability, which show weak correlation values when associated with vegetation. Another finding is that Yogyakarta City exhibits the most distinct response in vegetation density and surface temperature compared to the surrounding four cities. This is attributed to Yogyakarta City being the administrative center and economic hub of DIY. These findings provide a deeper understanding of the environment's response to these factors in DIY. By employing spatial and temporal analysis, this study offers valuable insights for climate change mitigation efforts and adaptation to the evolving environmental dynamics.

Elevating the RRE Framework for Geospatial Analysis with Visual Programming Platforms: An Exploration with Geospatial Analytics Extension for KNIME

Reproducibility, replicability, and expandability (RRE) have emerged as fundamental concerns in the realm of scientific research and development. Wherein, devising effective solutions for RRE within geospatial analysis stands out as a particularly critical challenge that demands immediate attention. Although there has been an evolution from basic reproducibility of code and data to a more comprehensive cyberinfrastructure, this integrated solution is still grappling with issues of limited user accessibility, steep learning curves particularly in coding skills, and difficulties in achieving collaboration with other data science platforms This study proposes a framework that combines open-source GIS with visual programming platforms, grounded in principles of standardization and educationalization, to advance the RRE framework in geographic analysis. Using the Geospatial Analytics Extension for KNIME as an example, we demonstrate the platform’s adaptability and utility through case studies in a recent textbook with an in-depth illustration of spatial accessibility analysis, specifically via the Generalized Two-Step Floating Catchment Area (G2SFCA) method. Our findings shed light on the transformative potential of such an integrative strategy, offer fresh perspectives for enhancing the RRE in geospatial analysis and craft a well-structured, intuitive, and extensive GIS knowledge tree.

Spatio-temporal pattern evolution of green development efficiency in Northeastern China and its driving factors

Scientific analysis of green development efficiency is crucial for promoting healthy green development at home. The subjects of this study were 181 counties in three provinces in Northeast China. As a first step, the Super-SBM model is utilized to estimate the efficiency of 181 counties from 2006 to 2020; in addition, spatial autocorrelation analysis is applied to assess green development efficiency, spatially and temporally, of 181counties; and to examine the driving factors and spillover effects associated with the efficiency of 181 counties, the Spatial Durbin model (SDM) is utilized. The conclusions show that 181 counties have low levels of green development efficiency and are all on a downward trajectory. Liaoning Province has the highest level, Jilin Province has the second highest level, and Heilongjiang Province has the lowest level. According to the geographical distribution, the locations with high and very high green development efficiency are roughly located in Mohe City, Huma County, Xunke County, Daqing Municipal District, Harbin Municipal District, Changchun Municipal District, Wafangdian City, Dalian Municipal District, and Zhuanghe City. There is a favorable spatial connection of efficiency across regions, but the positive spatial agglomeration trend first diminishes and then gradually increases. Economic development, industrial structure, policy regulations, and environmental protection play significant roles in economic development, industrial structure, policy regulations, and environmental protection. The contribution of this essay is of paramount importance for understanding the status quo and potential for green development in different counties in Northeast China and for realizing coordinated regional green development.

Role of arylalkylamine N-acetyltransferase 7 in reproduction and limb pigmentation of Aedes aegypti.

Arylalkylamine N-acetyltransferase (aaNAT) is a crucial enzyme that catalyses the transfer of acetyl groups from acetyl coenzyme A to arylalkylamines and arylamines. Evolutionary studies have identified a distinct class of aaNATs specific to mosquitoes, yet their functions remain elusive. This study focuses on Ae-aaNAT7, a mosquito-unique gene in Aedes aegypti (Diptera:Culicidae),to explore its functionality. Temporal and spatial expression analysis of Ae-aaNAT7 mRNA revealed high expression during embryonic development and in first-instar larvae, with notable expression in the limbs of adult mosquitoes based on tissue expression profiling. By further employing CRISPR/Cas9 technology for loss-of-function studies, our investigation revealed a reduction in the area of white spotting in the limbs of Ae-aaNAT7 mutant adult mosquitoes. Further investigation revealed a significant decrease in the fecundity and hatchability of the mutants. Dissection of the ovaries from Ae-aaNAT7 heterozygous mutants showed a noticeable reduction in the oocyte area compared with wild type. Dissection of the exochorion of the eggs from Ae-aaNAT7 homozygous mutants consistently revealed a striking absence of mature embryos. In addition, RNA interference experiments targeting Ae-aaNAT7 in males resulted in a reduction in fecundity, but no effect on hatchability was observed. These collective insights underscore the substantial impact of Ae-aaNAT7 on reproduction and its pivotal contribution to adult limb pigmentation in Ae. aegypti. These revelations offer insights pivotal for the strategic design of future insecticide targets.

Modeling and assessing spatial and temporal changes in recent agricultural land-use in Ben Tre province, Vietnam

Modeling and assessing spatial and temporal changes in recent agricultural land-use in Ben Tre province, Vietnam

Intrinsic and synaptic determinants of receptive field plasticity in Purkinje cells of the mouse cerebellum

Non-synaptic (intrinsic) plasticity of membrane excitability contributes to aspects of memory formation, but it remains unclear whether it merely facilitates synaptic long-term potentiation or plays a permissive role in determining the impact of synaptic weight increase. We use tactile stimulation and electrical activation of parallel fibers to probe intrinsic and synaptic contributions to receptive field plasticity in awake mice during two-photon calcium imaging of cerebellar Purkinje cells. Repetitive activation of both stimuli induced response potentiation that is impaired in mice with selective deficits in either synaptic or intrinsic plasticity. Spatial analysis of calcium signals demonstrated that intrinsic, but not synaptic plasticity, enhances the spread of dendritic parallel fiber response potentiation. Simultaneous dendrite and axon initial segment recordings confirm these dendritic events affect axonal output. Our findings support the hypothesis that intrinsic plasticity provides an amplification mechanism that exerts a permissive control over the impact of long-term potentiation on neuronal responsiveness.

Analysis of spatial patterns and influencing factors of farmland transfer in China based on ESDA-GeoDetector

Farmland transfer is a critical component in facilitating agricultural scale management and improving agricultural production efficiency. This study examines the spatial distribution of farmland transfer in China and identifies the factors influencing it, offering valuable guidance for advancing China’s farmland transfer practices. Through the application of mathematical statistics and GIS spatial analysis, the study investigates changes in spatial patterns related to the scale, rate, mode, and recipients of farmland transfer across China's 30 provinces from 2015 to 2020. Geographical detectors are also employed to identify the key factors influencing the extent and pace of farmland transfer. The study reveals that between 2015 and 2020, China's farmland transfer area increased from 29,789 to 37,638 million hectares. Provinces with abundant farmland resources generally experienced larger farmland transfers, while economically developed regions and major grain-producing areas saw higher rates of farmland transfers. The predominant mode of farmland transfer in China was leasing (subcontracting), accounting for over 80% of the total transferred area. Large-scale grain growers and family farms were significant participants in farmland transfers, acquiring approximately 60.1% of the transferred lands, followed by professional cooperatives (21.5%), enterprises (10.4%), and other entities (7.9%). Key factors influencing the farmland transfer area include the "regional farmland area", the "proportion of family farms supported by loans", and the "proportion of non-agricultural population", with explanatory powers of 0.663, 0.319, and 0.225, respectively. Notably, there is a substantial interaction between the "regional farmland area" and factors such as the "proportion of family farms supported by loans" and the "grain yield per unit area", with explanatory powers reaching 0.957 and 0.901, respectively. These findings offer valuable insights for promoting farmland transfer in agriculturally rich regions. Factors affecting the farmland transfer rate include "grain yield per unit area", "GDP per capita", and the "proportion of non-agricultural population", each with an explanatory power above 0.500. Moreover, their interactive explanatory powers with other indicators exceed 0.600, indicating that provinces with high agricultural productivity or economic development levels are more likely to undergo farmland transfer. The paper concludes by proposing strategies and recommendations to promote farmland transfer in both "large agricultural areas" and "metropolitan suburbs."

Effects of catchment land use on temperate mangrove forests

Human land use changes are threatening the integrity and health of coastal ecosystems worldwide. Intensified land use for anthropogenic purposes increases sedimentation rates, pollutants, and nutrient concentrations into adjacent coastal areas, often with detrimental effects on marine life and ecosystem functioning. However, how these factors interact to influence ecosystem health in mangrove forests is poorly understood. This study investigates the effects of catchment human land use on mangrove forest architecture and sedimentary attributes at a landscape-scale. Thirty sites were selected along a gradient of human land use within a narrow latitudinal range, to minimise the effects of varying climatic conditions. Land use was quantified using spatial analysis tools with existing land use databases (LCDB5). Twenty-six forest architectural and sedimentary variables were collected from each site. The results revealed a significant effect of human land use on ten out of 26 environmental variables.Eutrophication, characterised by changes in redox potential, pH, and sediment nutrient concentrations, was strongly associated with increasing human land use. The δ15N values of sediments and leaves also indicated increased anthropogenic nitrogen input. Furthermore, the study identified a positive correlation between human land use and tree density, indicating that increased nutrient delivery from catchments contributes to enhanced mangrove growth. Propagule and seedling densities were also positively correlated with human land use, suggesting potential recruitment success mechanisms. This research underpins the complex interactions between human land use and mangrove ecosystems, revealing changes in carbon dynamics, potential alterations in ecosystem services, and a need for holistic management approaches that consider the interconnectedness of species and their environment. These findings provide essential insights for regional ecosystem models, coastal management, and restoration strategies to address the impacts of human pressures on temperate mangrove forests, even in estuaries that may be relatively healthy.

Examining spatial and socioeconomic disparities in internet resilience during extreme weather events: a case study of Hurricane Harvey and Winter Storm Uri

The resilience of internet service is crucial for ensuring consistent communication, situational awareness, facilitating emergency response in our digitally-dependent society. However, due to empirical data constraints, there has been limited research on internet service disruptions during extreme weather events. To bridge this gap, this study utilizes observational datasets on internet performance to quantitatively assess the extent of internet disruption during two recent extreme weather events. Taking Harris County in the United States as the study region, we jointly analyzed the hazard severity and the associated internet disruptions in the context of two extreme weather events. The results show that the hazard events significantly impacted regional internet connectivity. There exists a pronounced temporal synchronicity between the magnitude of disruption and hazard severity: as the severity of hazards intensifies, internet disruptions correspondingly escalate, and eventually return to baseline levels post-event. The spatial analyses show that internet service disruptions can happen even in areas that are not directly impacted by hazards, demonstrating that the repercussions of hazards extend beyond the immediate area of impact. This interplay of temporal synchronization and spatial variance underscores the complex relationships between hazard severity and Internet disruption. Furthermore, the socio-demographic analysis suggests that vulnerable communities, already grappling with myriad challenges, face exacerbated service disruptions during these hazard events, emphasizing the need for prioritized disaster mitigation strategies and interventions for improving the resilience of internet services. To the best of our knowledge, this research is among the first studies to examine the Internet disruptions during hazardous events using a quantitative observational dataset. The insights obtained hold significant implications for city administrators, guiding them towards more resilient and equitable infrastructure planning.

Research on the temporal and spatial pattern evolution characteristics and decoupling effect of electricity power consumption in China

Exploring the evolution of spatial and temporal patterns of electricity power consumption in China is of great significance and value for the promotion of Carbon Peaking and Carbon Neutrality Strategy and the scientific allocation of electricity resources. Therefore, this paper takes China as an example and innovatively applies nighttime light data from a combination of two remote sensing satellites. And using spatial analysis methods to analyze the evolution of spatial and temporal patterns of electricity power consumption over a longer study time series. Meanwhile, this paper also uses the Tapio decoupling model to study the decoupling effect of electricity power consumption and economic growth in China. The results of the study show that, during the period 2000–2019, China's electricity power consumption was in an unbalanced state, with the eastern coastal region dominating. It also formed a gradient distribution from the coastal area to the inland area. In terms of spatial connection, it shows an unbalanced distribution pattern of “low in the west and high in the east”. In addition, the spatial linkage of electricity power consumption among provinces is more than 93 % of weak linkage, and gradually increases to 97 %, indicating that the spatial linkage of electricity power consumption among regions is gradually weakening. The decoupling state of electricity power consumption in China is characterized by two types of decoupling: Weak decoupling and Expansive coupling. The decoupling status has experienced a significant change from 84 % of provinces being Expansive coupling to 100 % of provinces being Weak decoupling.

Spatial analysis of the physical resilience of old urban neighborhoods against earthquakes: a case study of the old texture of Tehran

Spatial analysis of the physical resilience of old urban neighborhoods against earthquakes: a case study of the old texture of Tehran

Forecasting an urban sound model using space syntax theory in three different urban patterns in Egypt

The objective of this study is to investigate an acoustic environment based on spatial configurations. To achieve this objective, two types of data were utilized. First, the urban acoustic data was collected from 96 measurements based on equivalent continuous A-weighted sound pressure levels across three different urban areas in Cairo, Egypt, during weekends and at night. The data was plotted on a contour map in an effort to investigate their distribution in the urban area. Secondly, the data was collected using DepthMapX software, and in this way, spatial analysis was produced with diverse spatial attributes. Moreover, on-site observations of pedestrian and traffic rates were made, and land use distribution was observed.Statistical analysis was also conducted using the Statistical Package for Social Sciences (SPSS). Our statistical analysis showed that the value of sound pressure level (LAeq) is greatly influenced by spatial attributes in highly accessible spatial configurations, with Normalized Angular Integration (NAIN) being the most accurate predictor of sound pressure level. Our findings also verified the existence of a high correlation between commercial and mixed land uses and (LAeq).Additionally, this study revealed that the urban sound model can predict sound pressure level (LAeq) in an urban setting. This dataset functions as a valuable resource for future research, urban designers, and policymakers who are addressing sustainable issues pertaining to soundscape, noise pollution, and urban planning.