Primary Roads Research Articles

Patterns of change, driving forces and future simulation of LULC in the Fuxian Lake Basin based on the IM-RF-Markov-PLUS framework

Studying land use and land cover (LULC) patterns, identifying driving forces, and simulating future scenarios are vital for grasping the complex connection between human actions and the environment. This helps in shaping sustainable land management strategies and preparing for the impacts of climate change. However, there is a necessity for a comprehensive system modeling framework that can accurately capture spatial and temporal changes in LULC, analyze driving mechanisms, and provide an integrated analysis of future simulations. In this paper, a comprehensive IM-RF-Markov-PLUS analysis framework is developed, focusing on the Fuxian Lake Basin (FLB) as a study area. The study aims to achieve accurate prediction of LULC by combining the microscopic LULC change trend and the contribution of macroscopic driving forces. The results show that: (1) The IM-RF-Markov-PLUS framework can explore the change patterns and driving mechanisms of LULC in the FLB, and accurately predict the LULC in the FLB. Compared with the PLUS model, its accuracy is improved by 2 %. (2) IM analysis reveals that LULC transformation in the FLB is both general and specific. Although the area of grassland, buildings, roads and structures converted to desert and bare land is minimal, it shows relatively tendentious and specific change characteristics. (3) Different land types are significantly affected by driving factors, with the expansion of LULCs is constrained by major factors. The distance to the lake has the most significant impact on the distribution of garden land, while the primary road has the greatest impact on the distribution of forestland. (4) Under different scenarios, the spatial heterogeneity of LULC patterns is obvious. In 2035, under baseline and economic development scenarios, cultivated land will decrease, while other LULC types will increase. Under the cultivated land protection scenario, cultivated land is protected, with an increase of 5.85 %. Under the ecological protection scenario, there is an increase in ecological land. The largest increase is in forestland, which increases by a total of 3.46 %. The ecological protection scenario presents a viable approach for ensuring the sustainable development of the FLB. The results of this paper may serve as a reliable foundation for implementing LULC strategies in the FLB and offer guidance for crafting sustainable development regulations at the regional level.

Trends in Emissions from Road Traffic in Rapidly Urbanizing Areas

The process of urbanization has facilitated the exponential growth in demand for road traffic, consequently leading to substantial emissions of CO2 and pollutants. However, with the development of urbanization and the expansion of the road network, the distribution and emission characteristics of CO2 and pollutant emissions are still unclear. In this study, a bottom-up approach was initially employed to develop high-resolution emission inventories for CO2 and pollutant emissions (NOx, CO, and HC) from primary, secondary, trunk, and tertiary roads in rapidly urbanizing regions of China based on localized emission factor data. Subsequently, the standard road length method was utilized to analyze the spatiotemporal distribution of CO2 emissions and pollutant emissions across different road networks while exploring their spatiotemporal heterogeneity. Finally, the influence of elevation and surface vegetation cover on traffic-related CO2 and pollutant emissions was taken into consideration. The results indicated that CO2, CO, HC, and NOx emissions increased significantly in 2020 compared to those in 2017 on trunk roads, and the distribution of CO2 and pollutant emissions in Fuzhou was uneven; in 2017, areas of high emissions were predominantly concentrated in the central regions with low vegetation coverage levels and low topography but expanded significantly in 2020. This study enhances our comprehension of the spatiotemporal variations in carbon and pollutant emissions resulting from regional road network expansion, offering valuable insights and case studies for regions worldwide undergoing similar infrastructure development.

Spatiotemporal characteristics and driving mechanisms of land-use transitions and landscape patterns in response to ecological restoration projects: A case study of mountainous areas in Guizhou, Southwest China

With the acceleration of urbanization and industrialization, the land-use mode in mountainous areas has changed significantly, causing serious ecological destruction. Therefore, improving the efficiency of land-resource use in mountainous areas and enhancing ecological protection are important issues. This study focuses on typical mountainous areas in Guizhou Province to explore their significance not only for ecological restoration but also for sustainable socioeconomic development. In this study, we integrated the framework of the interaction between land-use transitions and landscape patterns and employed Spearman's rank correlation coefficient and a spatial bivariate model to reveal the spatiotemporal heterogeneity of landscape patterns and land-use transitions. The results showed that for 1990–2020, the cultivated, forest, and grassland areas decreased by −1353.66, −749.98 and − 541.72 km2 respectively, whereas the water area, urban, and other construction land increased by 799.69, 542.62, and 1230.90 km2, respectively. Moreover, the cultivated land areas converted into urban and other construction land were 358.03 and 661.77 km2 respectively, and the grassland areas converted into forest and other construction land were 3550.08 and 277.32 km2, respectively. Different land-use transitions presented rapid expansion and contraction characteristics, resulting in an increase in overall patch fragmentation, a decrease in uniformity, and an increase in irregular patches, which enhanced the spatial heterogeneity of diversity and complexity. Finally, the land-use transition effects on landscape patterns were primarily elevation, slope, and primary road facility factors. In-depth research on land-use transitional evolution and its impact on landscape patterns has important theoretical and practical value for formulating land-management policies and promoting sustainable development in mountainous areas.

ANALISIS KESELAMATAN JALAN DENGAN PENDEKATAN AUDIT KESELAMATAN JALAN PADA JALAN LOKAL DI KOTA TEGAL

Jalan Sultan Hasanudin – KH. Abdul Ghoni, which is located in Tegal City, Central Java, is a road with a secondary local function which is an alternative way to get to primary roads. By being an alternative road, this road section must meet adequate road safety standards. To improve traffic safety, it is necessary to carry out a road safety audit. This research aims to see the level of road safety in Tegal City, specifically on the Jalan Sultan Hasanudin - Jalan KH section. Abdul Ghoni. The method used in this research is descriptive quantitative obtained from the Hawkeye survey and processed using the Hawkeye processing toolkit software to analyze the data. The research results show that the Sultan Hasanudin – KH. Abdul Ghoni, in the aspect of road equipment facilities, there are 7 road equipment facilities in a damaged condition, in the aspect of the level of road unevenness in the medium category it has a percentage of 45% of the total length of the section, and for the aspect of the transverse slope on the Jl. Sultan Hasanuddin – KH. Abdul Ghoni has not met the standard for the transverse slope of asphalt pavement. Improved safety on the Jl. Sultan Hasanudin carried out further handling and improvements to road equipment and road pavement facilities, so that the Jl. Sultan Hasanuddin – KH. Abdul Ghoni does not have the potential to cause traffic accidents due to deficiencies in road infrastructure or dangerous road conditions.

Sistem Informasi Geografis Untuk Visualisasi Daerah Rawan Kecelakaan Lalu Lintas Jalan Arteri Primer Kota Surabaya

Accidents are an event that often occurs on the highway, especially in big cities, one of which is Surabaya City. Accidents are one of the main problems for the safety of road users. Almost all activities carried out require transportation facilities, if the transportation facilities do not run well due to traffic accidents, the activities carried out will not run well. Therefore, a solution is needed to reduce accidents by building an accident-prone area information system. In determining the criteria for accident-prone areas, it is taken from the Republic of Indonesia Police, the Department of Transportation, and Public Works, based on the number of accidents, the number of fatalities of victims, and road conditions. This research is an effort to visualize the occurrence of accidents using spatial data of Surabaya City road network maps and non-spatial data, namely accident data and road data obtained from the police and the Bina Marga Service. In the final result of this research, an application is obtained that can provide visualization of accident-prone areas such as Ahmad Yani road which is a road with a high accident rate with the number of incidents and has the highest victim fatality weighting results among 9 other primary arterial roads. Keywords:Accident Prone Areas, Geographic Information System, Surabaya City, Traffic, Transportation

Prediction model of factors causing traffic accidents on rural arterial roads: A binary logistic regression approach

In rural areas, land use activities around primary arterial roads influence the road section’s traffic characteristics. Regulations dictate the design of primary arterial roads to accommodate high speeds. Hence, there is a mix of traffic between high-speed vehicles and vulnerable road users (pedestrians, bicycles, and motorcycles) around the land. As a result, researchers have identified several arterial roads in Indonesia as accident-prone areas. Therefore, to improve the road user’s safety on primary arterial roads, it is necessary to develop models of the influence of various factors on road traffic accidents. This research uses binary logistic regression analysis. The independent variables are carelessness, disorderliness, high speed, horizontal alignment, road width, clear zone, road shoulder width, signs, markings, and land use. Meanwhile, the dependent variable is the frequency of accidents, where the frequency of accidents consists of multi-accident vehicles (MAV) and single-accident vehicles (SAV). This study collects data for a traffic accident prediction model based on collision frequency in accident-prone areas. The results, road shoulder width, and road sign factor all have an impact on the frequency of traffic accidents. According to a realistic risk analysis, MAV and SAV have no risk difference. After validation, this model shows a confidence level of 92%. This demonstrates that the model generates estimations that accurately reflect reality and are applicable to a wider population. This research has the potential to assist engineers in improving road safety on primary arterial roads. In addition, the model can help the government measure the impact of implemented policies and engage the public in traffic accident prevention efforts.

Analisis Faktor-faktor yang Mempengaruhi Ketimpangan Wilayah di Provinsi DKI Jakarta dan Provinsi Kalimantan Timur Tahun 2010-2020

Regional inequality is a development problem experienced by Indonesia. DKI Jakarta Province as the capital city of Indonesia and East Kalimantan Province which is designated as a candidate for the new capital city of Indonesia has a high inequality. This study aims to analyze the effect of investment, agglomeration, unemployment rate, primary sector GRDP distribution and road length on regional inequality in DKI Jakarta Province and East Kalimantan Province in 2010‒2020.This study uses the Ordinary Least Square (OLS) regression analysis method and uses a data processing tool in the form of the Eviews 10 application. The data used in this analysis is time series data in 2010-2020 obtained from the BPS, BPS DKI Jakarta and BPS Kalimantan Timur.The study indicates that in the Province of DKI Jakarta the investment variable has a positive and significant influence on regional inequality. The agglomeration variable, the unemployment rate has a negative and significant effect on regional inequality, while the primary sector GRDP distribution and road length variables have no significant effect on regional inequality. Meanwhile, in East Kalimantan Province, the variables of agglomeration, unemployment rate and distribution of GRDP in the primary sector have a positive and significant effect on regional inequality, while the investment variables and road length have no significant effect on regional inequality. Investment variables, agglomeration, unemployment rate, primary sector GRDP distribution and road length together have a positive and significant impact on regional inequality in DKI Jakarta Province and East Kalimantan Province in 2010-2020.

Friend or foe? A spatial approach to overlay bicycle and scooter trajectories

Dockless e-scooter schemes have seen increasing popularity in 28 German cities. Increasing use on insufficiently dimensioned bicycle infrastructure can lead to conflicts between e-scooter riders and cyclists. A new approach was developed in order to detect potential zones of conflict by overlaying aggregated bicycle and e-scooter trajectories in the City of Dresden, Germany. Bicycle data is being obtained by the annual STADTRADELN campaign where cyclists record and transmit daily trips via GPS for a period of three weeks. Simultaneously, e-scooter API data has been collected over a course of 8 weeks from June to September 2021. Origin/Destination data has been generated and routed over a OSM network in order to obtain aggregate d e-scooter flows. We extrapolated the aggregated bicycle data to match them with the timeframe of the e-scooter data acquisition. Afterwards we spatially joined both: bicycle and e-scooter flows and calculated the link wise proportion of e-scooter trips in relation to bicycle trip volumes. Two important findings emerged: (1) Residential roads have a higher proportion of e-scooter trips. (2) E-scooters are exposed to high bicycle trip volumes on primary roads with bicycle infrastructure. We conclude that this approach can detect possible links of conflict, where overtaking cyclists or insufficient space can lead to dangerous situations. That approach is biased towards a missing route choice model for e-scooter riders or better route data of e-scooters, which needs further research.

Seasonality in functional connectivity: A case study with the American marten in Forillon National Park

AbstractProtected areas are essential tools for reducing loss of global biodiversity. To fulfill their ecological functions, protected areas must be connected to their surroundings, a requirement that is difficult to meet in landscapes intensively disturbed by anthropogenic activities. Therefore, protecting movement corridors at the edges of protected areas is crucial, especially for species with broad habitat needs, such as the American marten (Martes americana). However, habitat selection and space use patterns are dynamic processes, so we could expect that functional connectivity would vary temporally in response to changing environmental conditions and levels of human activities. In this study, we aimed at predicting the location of movement corridors for the American marten in Forillon National Park and its periphery during two contrasted periods (snow‐free: May–November; snow‐covered: December–April). We used “seasonal” resource selection functions to identify core areas (interpreted as circuit “nodes”) and CircuitScape to delineate movement corridors between them based on the electrical circuit theory. Habitat selection patterns differed between periods, with martens avoiding open areas, high elevations and road proximity during the snow‐free period, while avoiding areas closer to secondary roads but selecting areas closer to primary roads and housing structures during the snow‐covered period. Consequently, the location of movement corridors differed partially between periods. Functional connectivity was favored by the presence of forest patches for both periods, while being constrained by open environments, especially during the snow‐free period. Our study highlights the importance of modeling functional connectivity at fine temporal scales in order to provide movement corridors that fulfill the requirements of a species at each period of its annual cycle.

Mutual impacts of changing climate and flexible pavement performance considering resilience and sustainable aspects

Roads play a vital role in transportation systems, and their construction and maintenance expenses are high. Those reasons make crucial the examination of factors that accelerate road deterioration and those factors' negative impacts on societies. Climatic-related elements, especially temperature and precipitation, significantly affect the quality and lifespans of roads. The Intergovernmental Panel on Climate Change has reported that increasing greenhouse gas (GHG) emissions is causing changes in climate and that the rate of change has accelerated during the past several decades. To assess the impacts of changing climatic parameters on flexible-pavement performance, this study used 32 climate models to evaluate the performance of interstate, primary, and secondary roads across 11 diverse locations with varying traffic and climatic conditions. The study's findings reveal that changing climate exacerbates pavement distresses, leading to reduced pavement lifespans and increased numbers of reconstruction projects, which in turn raise demands for materials and equipment and contribute to higher GHG emissions. The effects of changing climate and changing climate's associated economic and environmental costs make the application of various engineering solutions to enhance pavement resilience essential, as described in this paper, in the absence of comprehensive emissions reduction strategies.

Simulation and multi-scenario prediction of land-use change in the Gansu section of the Yellow River Basin, China

Introduction: The Gansu section of the Yellow River Basin is an important water resource conservation and replenishment area for the entire Yellow River Basin. With urbanization and socio-economic development, it is urgent to study the characteristics of land-use change and its future simulation in order to realize the coordinated ecological and economic development.Methods: Based on the patch-generating land-use simulation (PLUS) model, this paper investigated the main drivers of land-use type expansion with a comprehensive consideration of natural and socio-economic aspects; moreover, the study simulated land-use change in 2030 under the four scenarios of natural development, cultivated land protection, ecological priority, and economic construction.Results: The results showed the following: 1) the prediction of land-use types continued the historical evolution since 1980. Grassland, cultivated land, and forest land were still the dominant land types, accounting for more than 87% of the basin’s total area. Water bodies and wetlands remained relatively stable, and there was an obvious increase of approximately 20% in construction land. 2) Construction land and grassland were primarily driven by the social factor of the distance from the primary road and the distance from the secondary road, respectively. The cultivated land was greatly affected by the economic factor of population density. 3) The cultivated land protection scenario was the only one of the four scenarios that could make the cultivated land area increase positively, with an increase rate of 0.5%. This scenario also restricted effectively the conversion of cultivated land into construction land. The ecological priority scenario can expand grassland obviously with a proportion of 1.82% and slow down oasis desertion. The economic construction scenario can increase the construction land area the most by a rate of 25.5% to accelerate the economic development of specific regions in the study area.Discussion: Therefore, implementing policies on the basis of choosing suitable scenarios in different areas was significant for optimizing the land-use structure, promoting the efficient use of land resources and ecological environment in the Gansu section of the Yellow River Basin.

A global time series of traffic volumes on extra-urban roads

Traffic on roads outside of urban areas (i.e. extra-urban roads) can have major ecological and environmental impacts on agricultural, forested, and natural areas. Yet, data on extra-urban traffic volumes is lacking in many regions. To address this data gap, we produced a global time-series of traffic volumes (Annual Average Daily Traffic; AADT) on all extra-urban highways, primary roads, and secondary roads for the years 1975, 1990, 2000 and 2015. We constructed time series of road networks from existing global datasets on roads, population density, and socio-economic indicators, and combined these with a large collection of empirical AADT data from all continents except Antarctica. We used quantile regression forests to predict the median and 5% and 95% prediction intervals of AADT on each road section. The validation accuracy of the model was high (pseudo-R2 = 0.7407) and AADT predictions from 1975 were also accurate. The resulting map series provides standardised and fine-scaled information on the development of extra-urban road traffic and has a wide variety of practical and scientific applications.

Evaluating precision medicine tools in cystic fibrosis for racial and ethnic fairness.

Patients with cystic fibrosis (CF) experience frequent episodes of acute decline in lung function called pulmonary exacerbations (PEx). An existing clinical and place-based precision medicine algorithm that accurately predicts PEx could include racial and ethnic biases in clinical and geospatial training data, leading to unintentional exacerbation of health inequities. We estimated receiver operating characteristic curves based on predictions from a nonstationary Gaussian stochastic process model for PEx within 3, 6, and 12 months among 26,392 individuals aged 6 years and above (2003-2017) from the US CF Foundation Patient Registry. We screened predictors to identify reasons for discriminatory model performance. The precision medicine algorithm performed worse predicting a PEx among Black patients when compared with White patients or to patients of another race for all three prediction horizons. There was little to no difference in prediction accuracies among Hispanic and non-Hispanic patients for the same prediction horizons. Differences in F508del, smoking households, secondhand smoke exposure, primary and secondary road densities, distance and drive time to the CF center, and average number of clinical evaluations were key factors associated with race. Racial differences in prediction accuracies from our PEx precision medicine algorithm exist. Misclassification of future PEx was attributable to several underlying factors that correspond to race: CF mutation, location where the patient lives, and clinical awareness. Associations of our proxies with race for CF-related health outcomes can lead to systemic racism in data collection and in prediction accuracies from precision medicine algorithms constructed from it.

Aerial Mapping of the Peruvian Chira Valley Banana Production System to Monitor the Expansion of Fusarium Wilt Caused by Tropical Race 4

The recent incursion of Fusarium wilt of banana (FWB) caused by TR4 threatens banana production in the Chira Valley of Peru. To develop a management strategy, we mapped the entire production area from the air. During 12 flights at an altitude of 610 m (2,000 ft), we gathered 133,700 images in a timeframe of 2 weeks and constructed an orthomosaic map of 73,000 ha. This unveiled the complex logistic network across the banana-producing region, comprising 150 km of primary roads, as well as numerous secondary and tertiary unpaved paths through and bordering banana plantations. Moreover, the Poechos reservoir—with a total length of 450 km—feeds the entire Chira Valley irrigation system, which could further exacerbate TR4 expansion. Using georeferenced landscape details (digital terrain model), we determined areas prone to flooding, which is also relevant for disseminating TR4. Analyses of the maps resulted in the identification of many suspect areas for direct sampling and subsequent analyses to study the expansion of TR4. At four locations, we confirmed two cases, and by June 8, 2023, a total of 207 cases were reported. We conclude that TR4 is a serious threat to the entire region, which exports approximately 25% of the global organic bananas. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Carbon Sequestration in the Green Open Spaces along Primary Road of Pontianak City, West Kalimantan, Indonesia`

Global climate change caused by greenhouse gas (GHG) emissions is currently a focus for various countries worldwide, including Indonesia. Carbon dioxide (CO2) is the main source of emissions, with a significant portion originating in urban areas. This is due to the high levels of air pollution from motor vehicles and rapid industrial growth. Urban green spaces are areas within cities that consist of non-built-up spaces filled with naturally grown or cultivated vegetation. These green spaces exist directly alongside the transportation infrastructure, which helps reduce air pollution, especially CO2, through the vegetation that makes up these areas. One type of urban green space is a green corridor, which forms elongated paths or areas. This study assessed the carbon sequestration of 17 primary road networks in Pontianak City using three allometric models. Plot positions for data collection were determined using purposive sampling, with each side accounting for 5% of the total zigzag plots. This research focused on vegetation at different growth stages, such as saplings, poles, and trees. The results were estimated at 256.86 tons ha-1 (Hardiansyah and Ridwan formula), 269.96 tons ha-1 (Chave formula), and 193 tons ha-1 (Brown formula).

Statistical and Spatial Analysis of Large Truck Crashes in Texas (2017–2021)

Freight transportation, dominated by trucks, is an integral part of trade and production in the USA. Given the prevalence of large truck crashes, a comprehensive investigation is imperative to ascertain the underlying causes. This study analyzed 2017–2021 Texas crash data to identify factors impacting large truck crash rates and injury severity and to locate high-risk zones for severe incidents. Logistic regression models and bivariate analysis were utilized to assess the impacts of various crash-related variables individually and collectively. Heat maps and hotspot analysis were employed to pinpoint areas with a high frequency of both minor and severe large truck crashes. The findings of the investigation highlighted night-time no-passing zones and marked lanes as primary road traffic control, highway or FM roads, a higher posted road speed limit, dark lighting conditions, male and older drivers, and curved road alignment as prominent contributing factors to large truck crashes. Furthermore, in cases where the large truck driver was determined not to be at fault, the likelihood of severe collisions significantly increased. The study’s findings urge policymakers to prioritize infrastructure improvements like dual left-turn lanes and extended exit ramps while advocating for wider adoption of safety technologies like lane departure warnings and autonomous emergency braking. Additionally, public awareness campaigns aimed at reducing distracted driving and drunk driving, particularly among truck drivers, could significantly reduce crashes. By implementing these targeted solutions, we can create safer roads for everyone in Texas.

Driving Sustainability: Analyzing the Influence of Road Transportation Infrastructure on Green Economic Growth in Malaysia

Road infrastructure is an important aspect of the green economy. It integrates environmental, social, and economic factors with the aim of generating a positive net environmental balance. The green Solow growth model proposes that road infrastructure can enhance economic growth while improving environmental quality. This paper examines the relationship between transportation infrastructure and green economic growth in Malaysia, with the aim of ascertaining whether road transportation infrastructure has a role in sustaining economic growth. The study makes use of time series data over the period 1970-2021. This study employs the autoregressive distributed lag (ARDL) model and the error correction model (ECM). The study analyses three models of the total road network and segregates them into federal roads and state roads. The findings show that there are negative long-run relationships between transportation infrastructure and green economic growth. The results also showed that Federal Road had a more negative impact on green economic growth. However, in the short run, only Federal Road shows a significant and negative impact on green economic growth. In Malaysia, the federal road is classified as a primary road extensively utilised by the populace for their routine activities. Thus, federal roads have the potential to generate a more immediate and substantial influence on sustained economic development in comparison to state roads. Nevertheless, road transportation infrastructure can also have adverse effects on the sustainability of long-term economic growth. This study sheds light on the importance of sustainable road development that balances economic growth and the preservation of the environment.

Analisis Hubungan Geometrik Jalan dengan Potensi Kecelakaan di Jalan Imogiri - Dlingo, Bantul, Indonesia

Imogiri - Dlingo road section is a primary collector road located in the Mangunan tourist area, Bantul, Indonesia. This road is a provincial road with hilly terrain, lots of sharp turns, and long ascents and descents, which are potential for traffic accidents. Police data records that in February 2022 there was an accident on this road with 13 deaths and 33 injuries. Therefore, this study aims to evaluate road geometric, both horizontal and vertical alignments on Imogiri - Dlingo road based on Guidelines for Road Geometric Design number 13/P/BM /2021. To do so, road geometric analysis is conducted by employing road safety inspection data, which is then modeled using AutoCAD Civil 3D software. Based on the survey on road geometric, it is known that the number and width of lanes and shoulders are in accordance with Guidelines. Meanwhile, the analysis results using computer program show that this road has 24 horizontal and 6 vertical alignments. Nevertheless, 87% of bend radius, 67% of curve length, 58% of bend angle, 43% of slope, 57% of critical length, and 67% of control design (K) are not fulfilled the requirements. Therefore, Imogiri - Dlingo road is dangerous road and is potentially causing fatal accidents.

Advancing Urban Healthcare Equity Analysis: Integrating Public Participation GIS with Fuzzy Best–Worst Decision-Making

This study provides an innovative collaborative spatial decision support system (SDSS) that aims to ensure an equitable spatial distribution of healthcare services. Evaluating the equality of access to health services across different geographical areas is important, as it requires the analysis of various criteria such as the proximity of health centres and hospitals (HCHs), the quality of services offered, connectivity to primary roads, the availability of public transportation hubs, and the density and distribution patterns of HCHs. This purpose is accomplished via the use of geographic information systems (GIS) and multi-criteria decision analysis (MCDA) methods. The proposed model includes the weights of the criteria, which are determined through the ordered weighted average (OWA) and evaluated based on their ORness, which ranges from 0 to 1. Furthermore, this model is improved by the best–worst fuzzy method (F-BWM). This approach produces a spatial map that clearly shows the equity of healthcare systems in urban environments. The findings show that the maximum score observed in this study was 0.38% (with an ORness value of 1), whilst the minimum score recorded was 0.28%. In the most severe scenario (ORness = 0), over 70% of the region shows different degrees of fairness, ranging from moderate to suitable and very suitable conditions. Governments and health authorities can use this information strategically to allocate resources and address inequities in access to healthcare facilities.

Perbandingan Penggunaan 3 Jenis Pipa untuk Sistem Penyediaan Air (Kajian Kasus Kawasan Industri Terpadu Kabupaten Batang)

Batang Regency is one of the areas located on the north west coast of Central Java province. Batang Regency is located in a strategic position, this area is traversed by primary arterial roads that connect West Java and DKI Jakarta with cities in Central Java and East Java Provinces. Batang Regency is divided into 15 sub-districts consisting of 239 villages, 9 sub-districts, 936 hamlets, 3,680 neighborhood units (RT) and 1,009 community units (RW). The total area of Batang Regency is 78,864.16 Ha. The widest sub-district is Subah District, which is 83.52 Ha (10.59%), while the smallest is Warungasem District, which is 23.55 Ha (2.99%) of the total area of Batang Regency. The Central Government's program to encourage the sector to strengthen the industrial sector in Indonesia, namely one of the developments in the Batang industry. The Government provides supporting facilities in the development of the Batang Industrial area through APBN financing. The Batang Industrial Estate has around 4,300 hectares of land to develop, for the first phase it will develop a land area of 450 hectares. To support the supply of drinking water in this area, PERUMDA of Sendang Kamulyan Drinking Water, Batang Regency will supply drinking water which will take water from the raw water source of the Bangkangan spring at 100 liters/second and will be supplied to the Industrial Area at 80 l/s. For the analysis of the drinking water supply system in this industrial area, the Epanet 2.2 program will be used by comparing the hydraulic analysis of the use of HDPE, PVC and iron pipe types/materials, residual pressure and diameter as well as calculating the amount of investment based on the type of pipe material. The results of running Epanet 2.2 on HDPE, Iron and PVC pipes with remaining water pressure at the end of the pipe at the KITB Junction, the remaining pressure is more than 10 meters, meaning that the water has flowed with sufficient criteria in the service area. Based on the analysis taking into account efficiency, the selected pipe is HDPE with an investment value of Rp. 20,273,230,410. The recommendations given for SPAM KITB, can use HDPE pipes, apart from lower costs HDPE pipes have a better roughness coefficient than PVC pipes and iron pipes and can also minimize pipe leaks. Lessons from this study with Epanet Software can calculate water hydraulics in the piping system such as water velocity, the furthest remaining water pressure can be known quickly, can determine the type and specifications of pipes used for the study area and known cost efficiency based on the type of iron, PVC and HDPE pipes.