Road Length Research Articles

Analysis of The Relationship of Land Transportation With GRDP in Wholesale and Retail Trade Sector, Car and Motorcycle Reparation

Transportation Land transportation influences national economic growth. Due to the existence of land transportation modes, the national economy can continue to grow from year to year. This study analyzed the variable relationship between land transportation through road length data, road condition data, and GRDP in the wholesale and retail trade sectors. The results of this study show that good national road conditions have a very low positive correlation (0.079). And has an insignificant relationship to GRDP (0.665 0.05). National road conditions have a shallow level of positive correlation (0.074). And has a negligible relationship to GRDP (0.679 0.05). Damaged national road conditions have a superficial negative correlation (-0.040). And has an insignificant relationship to GRDP (0.823 0.05). National road conditions severely damaged did not pass the requirements test, normality test results (0.024 0.05). Provincial road conditions are good, with a positive correlation (0.681). And has a significant relationship to GRDP (0.00 0.05). Medium local roads have a good level of positive correlation (0.586). And has a substantial relationship to GRDP (0.00 0.05). The condition of damaged provincial roads has a low negative correlation (-0.103). It has an insignificant relationship to GRDP (0.563 0.05). The condition of the badly damaged national road does not pass the requirements test, the normality test (0.024 0.05). Moderate district/city road conditions have an average positive correlation (0.356). And has a significant relationship to GRDP (0.039 0.05). The condition of district/city roads is damaged and has a shallow correlation level of (0.105). It has an insignificant relationship with GRDP (0.555 0.05). The condition of district/city roads is badly damaged and has a shallow correlation level of (0.105). It has an insignificant relationship with GRDP (0.555 0.05). The condition of district/city roads is damaged and has a shallow correlation level of (0.105). It has an insignificant relationship with GRDP (0.555 0.05). The condition of district/city roads is badly damaged and has a shallow correlation level of (0.105). It has an insignificant relationship with GRDP (0.555 0.05). The condition of district/city roads is damaged and has a shallow correlation level of (0.105). It has an insignificant relationship with GRDP (0.555 0.05). The condition of district/city roads is badly damaged and has a shallow correlation level of (0.105). It has an insignificant relationship with GRDP (0.555 0.05).

Analisis Pola Spasial dan Determinan Kemiskinan di Provinsi Sumatera Selatan

The purpose of this study was to determine the spatial pattern of the poverty rate and to determine the factors that may have a spatial influence on the poverty rate in South Sumatra Province. The factors that are suspected to influence and have a spatial (regional) dependency effect on the poverty rate are economic growth, population, length of roads in good condition, number of households that have access to decent drinking water, number of villages that can receive internet signals and Gross Regional Domestic Product per capita 2021 year in 15 districts/cities. The data used in this study were sourced from the South Sumatra Central Bureau of Statistics and spatial identity data sourced from https://gadm.org/download_country_v3.html. The analysis method used is spatial regression analysis using the Stata 17 application. The results of this study show that based on the map there are groupings or clusters of poverty rates. However, there is no spatial dependency effect on the poverty rate in South Sumatra Province. Economic growth has a negative but insignificant effect on the poverty rate, population has a negative and significant effect on the poverty rate, the length of highways in good condition has a positive but insignificant effect on the poverty rate, the number of households with access to safe drinking water has a negative but insignificant effect on the poverty rate, the number of villages that can receive internet signals has a positive and significant effect on the poverty rate, and GRDP per capita has a positive and significant effect on the poverty rate in South Sumatra Province.

Analysis of Factors Affecting the Cost Performance of Road Improvement Work in Serang Regency

The Road Infrastructure Development Acceleration Program that has been launched by the Serang Regency Government in the 2017 fiscal year to the 2021 fiscal year, In the implementation of road improvement work in Serang Regency, a working length of 100 kilometers per year has been set for 5 budget years starting from the 2017-2021 fiscal year, the implementation of road improvement work in Serang Regency until the end of 2021 the remaining 20 kilometers due to changes in road length and increase in the volume of work in the field. This study analyzes the factors of additional costs incurred on road improvement work in Serang Regency by identifying the factors causing the cost increase from the largest to smallest factors data collection methods through questionnaires and interviews addressed to contractor personnel with validity, reliability and correlation tests used for data processing, while descriptive analysis is used for data analysis using Jeffreys Amazing Statistics Program (JASP) version 0.16.2 and Relative Importance Index (RII) are expected with this method to determine the factors causing additional costs in road improvement work. The highest level factor was identified as causing the additional cost of implementing Serang Regency road improvement work, namely Volume Changes (Technical Factors) with an RII index value of 0.715.

Analysis of traffic noise spatial distribution characteristics and influencing factors in high-density cities

Urban spatial structure factors can have considerable effects on traffic noise distribution. This study aimed to describe the spatial distribution characteristics of traffic noise and influencing factors in high-density cities. Fifteen indexes were selected from the three aspects of building layout, road organization and land use to analyse the influence of urban spatial structure factors on the noise spatial distribution. This paper selected the central area of Tianjin as the study area. The noise level was generated by the noise simulation software CadnaA, and the numerical statistics were determined by ArcGIS. The correlation between various urban indexes and the spatial distribution of traffic noise were determined with correlation analysis, and multiscale geographically weighted regression (MGWR) analysis was used to determine the degree and scope of influence of various urban indexes on the spatial distribution of traffic noise. The results indicate that there are significant differences in the spatial agglomeration forms of high, medium, and low noise areas among research units, and the spatial agglomeration of low noise areas in each unit is stronger. The building layout indexes, except for the average building height (ABH), are significantly negatively correlated with the noise levels in low noise areas (L70–L90). The road length index (RLI), road area density (RAD), road landscape shape index (RLSI), trunk road length index (TRLI), proportion of traffic land (PT), and degree of land mixing (DLM) are significantly positively correlated with the noise levels of all areas within the unit (L10–L90). Among the three aspects of building layout, road organization, and land use, the architectural landscape shape index (ALSI), RAD, and DLM have the greatest influence on the average spatial sound pressure level (Lavg), with mean regression coefficients of −0.254, 0.520, and 0.174, respectively. The ground space index (GSI), ALSI, proportion of residential land (PR) and PT are the global factors influencing Lavg.

Urban rail transit network topology evolutionary stage has influence on rail ridership: Insights from linear mixed-effects models with heterogeneity in variances

Determining the impact of the evolutionary stage (ES) of urban rail transit (URT) network topology on daily ridership (DR) can be beneficial for policymakers when analyzing recent stagnated ridership in some cities. This paper used city-level data from 26 Chinese cities from 2013 to 2019 to investigate this. Eleven variables comprising socioeconomic attributes (population density and the average wage of employees), the availability of other transit modes (the number of taxis, the number of private cars, the bus network length, and the street network length), service-related attributes (the number of trains in operation, the average headway during peak period, the opened days, and rail fare), and a network topological characteristic (the average path length) were introduced as covariates. In addition, city class was introduced as a grouping variable to capture the unobserved characteristics of the investigated cities. Two linear mixed-effects models (M1 and M2) were developed, with an interaction term between city class and ES being introduced in M2. The variances were allowed to vary to account for the heterogeneity of the predictor, which improved the overall fit of the models. The estimation results reveal a significant positive within-subject effect of ES on DR in both models, which varied according to city class. This implies that for each city, improving ES increased DR and the scale of the increase in DR is associated with the city’s class. However, there is no evidence of a relationship between ES and DR across different cities. In addition, the heterogeneity in the variance indicates that underestimating the variances of the effects could lead to inaccurate conclusions. The results of this study can help transit agencies in mastering ridership and assessing the designs of URT network topology.

Analysis of the Effect of Public Infrastructure on the Economy in South Sumatra Province

The purpose of this study is to analyze how much influence Road Infrastructure, Water and Electricity, on GRDP in South Sumatra Province. The data used in this study is secondary data which includes GRDP data at constant 2010 prices, road length according to good road conditions, water data using the amount of water supplied, and electricity data using the distribution of electricity sold in South Sumatra Province from 2018-2022. The data obtained will be analyzed through panel data regression. The results showed that road infrastructure development has a positive and significant impact on Gross Regional Domestic Product (GRDP), while water infrastructure has a positive but insignificant impact on GRDP. In addition, electricity infrastructure also has a positive and significant impact on GRDP. The results also show that the road and electricity variables jointly affect the GRDP variable in South Sumatra Province in 2018-2022.

Graph-Based Neural Networks’ Framework Using Microcontrollers for Energy-Efficient Traffic Forecasting

This paper illustrates a general framework in which a neural network application can be easily integrated and proposes a traffic forecasting approach that uses neural networks based on graphs. Neural networks based on graphs have the advantage of capturing spatial–temporal characteristics that cannot be captured by other types of neural networks. This is due to entries that are graphs that, by their nature, include, besides a certain topology (the spatial characteristic), connections between nodes that model the costs (traffic load, speed, and road length) of the roads between nodes that can vary over time (the temporal characteristic). As a result, a prediction in a node influences the prediction from adjacent nodes, and, globally, the prediction has more precision. On the other hand, an adequate neural network leads to a good prediction, but its complexity can be higher. A recurrent neural network like LSTM is suitable for making predictions. A reduction in complexity can be achieved by choosing a relatively small number (usually determined by experiments) of hidden levels. The use of graphs as inputs to the neural network and the choice of a recurrent neural network combined lead to good accuracy in traffic prediction with a low enough implementation effort that it can be accomplished on microcontrollers with relatively limited resources. The proposed method minimizes the communication network (between vehicles and database servers) load and represents a reasonable trade-off between the communication network load and forecasting accuracy. Traffic prediction leads to less-congested routes and, therefore, to a reduction in energy consumption. The traffic is forecasted using an LSTM neural network with a regression layer. The inputs of the neural network are sequences—obtained from a graph that represents the road network—at specific moments in time that are read from traffic sensors or the outputs of the neural network (forecasting sequences). The input sequences can be filtered to improve the forecasting accuracy. This general framework is based on the Contiki IoT operating system, which ensures support for wireless communication and the efficient implementation of processes in a resource-constrained system, and it is particularized to implement a graph neural network. Two cases are studied: one case in which the traffic sensors are periodically read and another case in which the traffic sensors are read when their values’ changes are detected. A comparison between the cases is made, and the influence of filtering is evaluated. The obtained accuracy is very good and is very close to the accuracy obtained in an infinite precision simulation, the computation time is low enough, and the system can work in real time.

“Downs's Law” under the lens of theory: Roads lower congestion and increase distance traveled

Downs (1962) claimed a “Law”: that expressways lower congestion even though they reach maximum traffic flow. In urban economics since Strotz (1965), road capacity is measured by road width, and congestion as the delay in travel: wider roads lower congestion. Duranton and Turner (2011), in an econometric study, atypically defined congestion, not as delay in travel, but as aggregate vehicle kilometers traveled (VKT) relative to the aggregate length of roads, concluding that roads are unlikely to relieve congestion. We first provide the theory behind “Downs's Law”. Then, in a series of theoretical models, we endogenize rent, income, the value of time, leisure, Marshallian productivity, consumption-linked trips, road costs, spatial detail, and a suburb-to-city expressway competing with existing roads. In each case we prove that adding more road capacity lowers congestion and increases utility in the short run when city population is fixed; and lowers congestion in the long run too despite induced travel or population growth. Aggregate travel cost and VKT rise or fall, depending on how much congestion is lowered, on the cost elasticity of travel demand, on location-based income and substitution effects, and on which roads are widened.

The Implementation of Autocad® Civil 3D for Road Geometric Redesign on Educational Areas: A Case Leumah Neundet Bandung

Infrastructures, especially those directly related to the transportation system and has a crucial role in society is the road. “Jalan Leumah Neundeut” is a road transportation infrastructure in Sukawarna Village, Sukajadi District, Bandung City, West Java, Indonesia. It has the potential for trip attraction because it very close to the education area and passed by public transportation. This paper’s problem formulation arises based on the need for a well-road transportation infrastructure on “Jalan Leumah Neundeut”. It will be geometrically redesigned in its horizontal alignment to be as ideal as possible to fit the design criteria using AutoCAD® Civil 3D because it does not meet the design criteria, especially regarding the road spaces and lane configuration. The geometric redesign of the “Jalan Leumah Neundeut” horizontal alignment resulted in 450 meters of the total road length, 7 meters of carriageway width with 2/2 UD (undivided with two lanes and two ways) type, 60 km/hour of velocity design, S-C-S type of road curve, 47 meters of LS value, 130 meters of curve design radius, 2% of normal super-elevation, and 8% of maximum super-elevation. With the results obtained, Jalan Leumah Neundeut can maximize its potential.

ПІСЛЯВОЄННЕ ВІДНОВЛЕННЯ ТА ЗРОСТАННЯ ОБСЯГІВ БУДІВНИЦТВА АВТОМОБІЛЬНИХ ДОРІГ

The socio-economic development of a country and its integration into the global community largely depend on the level of road maintenance. The issue of road maintenance has become especially relevant and important during the period of martial law, since, for obvious reasons, roads are critical infrastructure facilities. Of course, the treatment of such facilities should be appropriate to their purpose. All of this requires research, assessment of the effects of the war on the condition of roads due to their destruction, and development of measures to improve the state of road construction. An important role is assigned to the resource base of road construction - first of all, the availability of bitumen and mineral fillers.
 The length of public roads in Ukraine is analyzed in comparison with the leading countries of the world. Positive trends in the market of road construction and repair related to the reform of the road sector are identified. The quality of roads and their saturation in comparison with other countries of the world is assessed.
 The problematic issues of domestic production and imports of bitumen are investigated. The article shows Ukraine's import dependence and lack of organic binder, as well as the practical absence of concrete road construction. The author analyzes the development and improvement of the regulatory framework for the design and construction of roads.
 Prospects for the implementation of the public-private partnership mechanism are shown, taking into account international experience The necessity of implementing the public-private partnership mechanism, in particular, through the concession mechanism, is substantiated. The regulatory framework needs to be updated to meet EU requirements and implement international standards. The implementation of these measures will help to increase the level of validity of operational and strategic management decisions to ensure the effective functioning and development of Ukrainian road sector enterprises.

Analysis of the Influence of Human Development Index and Infrastructure Development on Improving Economic Inequality in Papua Province (Case Study of Eight Districts la Pago Customary territory)

Puspose: This study aims to analyze the effect of human development index and Infrastructure development (road length, health facilities, education facilities, housing facilities, lighting facilities, clean water facilities, per capita income) on improving economic inequality as measured by general public for the period 2013-2022. Method: Secondary data is needed to provide an explanation or answer to the research question. The data analysis model used in this study uses a panel data model with a linear regression approach (OLS). Result and Conclusion: The results showed that HDI (X1) had a positive effect on the gini ratio (Y), with a value of Prob. = 0,0374 < 0,05. Road length (X2) has a positive effect on the gini ratio (Y), with a value of Prob. = 0,0034 < 0,05. Health facilities (X3) have a positive effect on the gini ratio (Y), with a value of Prob. = 0,0079 < 0,05 . Educational facilities (X4) negatively affect the gini ratio (Y), with a value of Prob. = 0,1261 > 0,05. Housing facilities (X5) have a positive effect on the gini ratio (Y), with a value of Prob. = 0,0239 < 0,05. Electric lighting facilities (X6) have a positive effect on the gini ratio (Y), with a value of Prob. = 0,0017 < 0,05. Clean water facilities (X7) have a positive effect on the gini ratio (Y), with a value of Prob. = 0,0131 < 0,05. GRDP per capita (X8) has a positive effect on the gini ratio (Y), with a value of Prob. = 0,0349 < 0,05. Implication of Research: Based on the results of the analysis above, the districts/cities included in Hierarchy I are Jayawijaya Regency and Pegunungan Bintang Regency. In Hierarchy II there are Nduga Regency and Yalimo Regency. In Hierarchy III there are Yahukimo Regency, Lani Jaya Regency, Central Mamberamo Regency and Tolikara Regency. Originality/Value: This shows that Jayawijaya Regency and Pegunungan Bintang Regency are attractive areas for residents to carry out activities in the region due to the availability of various economic, social and government facilities. People who come to the area can get their various needs in close proximity. People will come there for shopping, schooling, and more. This is an attraction for the area to be visited, thus increasing the volume of transactions.

Analisis Pola Kecelakaan Lalu Lintas Menggunakan Metode Clustering Studi Kasus Polresta Samarinda

The increase in traffic accidents which cause major consequences, such as injuries and fatalities, can be caused by an increase in population and the need for vehicles in a certain area. It is difficult to predict the time and location of traffic accidents, which are increasing as road length and vehicle movements increase. In the Samarinda Police area, the rapid growth of urbanization and vehicle mobility is a significant challenge in reducing the number of accidents. Statistics show an alarming number of accidents, requiring more effective handling to prevent them from increasing every year. The K-Means clustering algorithm is used in this research to identify accident-prone hours and group road accident data. Six variables including accident rate, number of fatalities, serious injuries, minor injuries, type of accident, and weather were taken from data collected in 2023 by the Samarinda Police Traffic Unit. After data collection, preprocessing and K-Means Clustering stages were carried out using RapidMiner. The results of the analysis help design more effective prevention strategies.

STATISTICAL STUDY OF PUBLIC HEALTH DISASTER DUE TO ROAD TRAFFIC ACCIDENTS IN INDIA

This research article studies the general trend of traffic accidents on Indian roads for the last 28 years. The study includes accident severity, number of deaths, and injuries due to accidents. The rate of accidents, deaths, and injuries are studied concerning population, number of registered vehicles, and road length. Monthly and timely indices are computed for the number of accidents to study which months of a year and time durations of a day show more accidents than its average and with what percentage? We study the general trend of accidents in rural and urban areas and see which categories of vehicles are more vulnerable to accidents in Million Plus Cities. Comments and suggestions are given to minimize road accidents and avoid serious consequences.

Assessment of the impact of the rise in Lake Victoria water levels on urban flooding using a GIS-based spatial flood modelling approach

ABSTRACT During the period 2018–2021, Lake Victoria experienced a rapid rise in water levels that caused significant urban flooding consequences. However, there are no studies that have extensively investigated the effect of the rising lake water levels on urban flooding. This research responds to this by developing and applying a GIS-based spatial flood modelling approach to simulate the resulting flooding impacts in Entebbe City, Uganda, corresponding to the May 2021 observed maximum lake water level of 13.49 m. Using the validated GIS-based flood model, the simulated flooded area and average flood depth were determined as 9.1 km2 and 1.52 m, respectively. Furthermore, through application of GIS overlay analysis, the total number of affected buildings and length of urban roads were quantified. The proposed methodology provides a robust and computationally efficient approach for identification of at-risk buildings along the lake shoreline and for testing the effectiveness of potential adaptation strategies.

Prediction of transportation index for urban patterns in small and medium-sized Indian cities using hybrid RidgeGAN model

The rapid urbanization trend in most developing countries including India is creating a plethora of civic concerns such as loss of green space, degradation of environmental health, scarcity of clean water, rise in air pollution, and exacerbated traffic congestion resulting in significant delays in vehicular transportation. To address the intricate nature of transportation issues, many researchers and planners have analyzed the complexities of urban and regional road systems using transportation models by employing transportation indices such as road length, network density, accessibility, and connectivity metrics. This study addresses the complexities of predicting road network density for small and medium-sized Indian cities that come under the Integrated Development of Small and Medium Towns (IDSMT) project at a national level. A hybrid framework based on Kernel Ridge Regression (KRR) and the CityGAN model is introduced to predict network density using spatial indicators of human settlements. The major goal of this study is to generate hyper-realistic urban patterns of small and medium-sized Indian cities using an unsupervised CityGAN model and to study the causal relationship between human settlement indices (HSIs) and transportation index (network density) using supervised KRR for the real cities. The synthetic urban universes mimic Indian urban patterns and evaluating their landscape structures through the settlement indices can aid in comprehending urban landscape, thereby enhancing sustainable urban planning. We analyzed 503 real cities to find the actual relationship between the urban settlements and their road density. The nonlinear KRR model may help urban planners in deriving the network density for GAN-generated futuristic urban patterns through the settlement indicators. The proposed hybrid process, termed as RidgeGAN model, can gauge the sustainability of urban sprawl tied to infrastructure and transportation systems in sprawling cities. Analysis results clearly demonstrate the utility of RidgeGAN in predicting network density for different kinds of human settlements, particularly for small and medium Indian cities. By predicting future urban patterns, this study can help in the creation of more livable and sustainable areas, particularly by improving transportation infrastructure in developing cities.

Implementation of 3D spatial planning through the integration of the standards

AbstractTo plan future land use, zoning plans (i.e., spatial plans) are prepared to get the most out of land for both the public and the government. These plans manifest which facilities can be built and where they can be built on land based on defined requirements such as building height and road length. The Land Administration Domain Model (LADM) is well‐known and widely used standard for describing Rights, Restrictions, and Responsibilities (RRRs) with respect to land and buildings. The next version of the standard will contain the Spatial Plan Information (SPI) part to enable better land‐use planning. Three‐dimensional (3D) land‐use planning has gained attention to delineate detailed requirements inclusively and allow different spatial analysis that provides a basis for decisions in the planning. Data standards pertaining to 3D geoinformation are vital to put into practice 3D spatial planning. To this extent, CityJSON is proposed for the effortless and efficient use of 3D city models. This article thus first aims to extend the CityJSON schema based on the proposed SPI part of the LADM such that it allows modeling, storing, visualizing, and utilizing the features and attributes required for the implementation of 3D spatial planning. Then, the usability of the proposed extension schema is demonstrated by the real‐world use cases that benefit from the exemplary CityJSON files that are created based on approved zoning plans in the country. The results of this study show that there is an important opportunity coming from the integration of international standards that enables semantic information along with their spatial counterparts within 3D spatial planning.

Estimating the Spatial Spillover Effects of Transportation Infrastructure on Economic Growth in an Archipelagic Nation

Transportation infrastructure plays a crucial role in facilitating economic growth and mitigating socio-economic disparities. Countries with adequate transportation infrastructure have a comparative advantage in international and domestic trade and in reducing economic and social disparities. Numerous studies have examined the spatial relationship between transportation infrastructure and economic growth, particularly in developed nations like the US and China. However, research on developing countries is scarce and pays little attention to archipelagic nations like the Philippines. This paper estimates the spatial spillover effects of transportation infrastructures in the three major islands of the Philippines for the time period 2003–2020 using the spatial Durbin model (SDM). More specifically, it examined the spatial spillover effects of transportation infrastructure, specifically roads, bridges, airports, and seaports on economic growth. The findings indicate the presence of positive spillover effects of transportation infrastructure at both the national and island levels. However, the spillover effects of transportation infrastructure variables differ significantly across the three major islands. The road length in Luzon and Visayas exhibits a negative trend, whereas Mindanao demonstrates a significant positive trend. The bridges in Luzon and Visayas are positive. Airport passengers in Visayas and Mindanao are negative. Seaport passenger is negative in Luzon, Visayas, and Mindanao. Seaport cargo is positive across major islands. The results of this study indicate that the implementation of appropriate and targeted transportation infrastructure investments in each of the major islands has the potential to foster economic growth Moreover, the results can serve as a valuable resource and integral element of the government’s strategic plan for national and regional development, facilitating the acceleration of economic growth and enhancing productivity at the regional level.

Vertical vs. Horizontal Fractal Dimensions of Roads in Relation to Relief Characteristics

This paper investigated the surface length of roads from both horizontal and vertical perspectives using the theory of fractal dimension of surfaces and curves. Three progressive experiments were conducted. The first demonstrated the magnitude of the differences between the planar road length and the DTM-derived surface road length and assessed its correlation with the DTM-calculated road slope. The second investigated the road distance complexity through the fractal dimension in both planar and vertical dimensions. The third related the vertical with the horizontal fractal dimension of roads across a range of distinct physiographic regions. The study contributed theoretically by linking the planimetric complexity to vertical complexity, with clear applications for advanced transportation studies and network analyses. The core methodology used geographic information systems (GIS) to integrate a high resolution (1 × 1 m) digital terrain model (DTM) with a road network layer. A novel concept, the vertical fractal dimension of roads was introduced. Both the vertical and horizontal fractal dimensions of the roads were calculated using the box-counting methodology. We conducted an investigation into the relationship between the two fractal dimensions using fourteen study areas within four distinct physiographic regions across Slovenia. We found that the average slope of a three-dimensional (3D) road was directly related to the length difference between 3D and two-dimensional (2D) roads. The calculated values for the vertical fractal dimension in the study areas were only slightly above 1, while the maximum horizontal fractal dimension of 1.1837 reflected the more sinuous properties of the road in plan. Variations in the vertical and horizontal fractal dimensions of the roads varied between the different physiographic regions.

The Design and Location Characteristics of Wildlife Overpasses in Hungary

Hungary's motorway network has developed significantly over the past twenty years. These developments have increased the length of fenced roads, which also means increased habitat fragmentation effects. Wildlife crossings have been built on new sections to reduce isolation caused by roads. This study examined 57 wildlife overpasses using satellite imagery. We determined the internal and overall widths of the crossings, their total length and the length of the noise barriers, as well as the width-to-length ratio. The crossings were classified according to ramp design, noise barrier material and noise barrier run-down. In addition, a surface cover map was used to examine landscape features within 500 m of the crossings and evaluate the crossings' placement. Our results show that the average width of the overpass corridor was 14.4 m. The width-to-length ratio was 0.16. Based on this, we concluded that the wildlife crossings in Hungary could be classified as narrow crossings. There was also considerable variation in design characteristics, with the crossings studied not being uniform in either ramp design or noise barrier characteristics. The results of the placement's landscape characterisation indicate that many overpasses in agricultural areas are particularly favourable for roe deer (Capreolus capreolus).

INCREASING THE MINIMUM WAGE AS A MEANS OF POVERTY ALLEVIATION

Poverty alleviation is one measure of the success of economic development; therefore, this study analyzes the link between the minimum wage and the poverty rate. This study uses secondary data, which includes poverty rate, regency/city minimum wage, economic growth, unemployment rate, and length of road in the Greater Solo. The study period covers conditions from 2010 to 2020. Secondary data was analyzed using a panel data regression model based on Fully Modified Ordinary Least Square (FMOLS) estimation. Primary data from interviews with some development economists supplement the regression results. Preliminary data analysis utilized the Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) method to analyze critical variables in poverty alleviation. The results showed increased regency/city minimum wage is followed by decreased poverty. Meanwhile, an increase in the open unemployment rate impacts an increase in the poverty rate. However, economic growth and the road length do not affect the Greater Solo area's poverty level. Furthermore, the results of the MICMAC analysis show a strong influence of the regency/city minimum wage and the open unemployment rate on the poverty rate. Meanwhile, economic growth and road length do not strongly influence the poverty rate.