Tertiary Roads Research Articles

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.

The association of road, traffic, and environmental factors with wrong-way riding behavior on shared e-bikes

Wrong-way riding (WWR) behavior of electric bikes (e-bikes) is a hazardous practice that frequently threatens traffic safety. It is imperative to accurately detect instances of WWR and analyze the various factors contributing to this behavior to develop and implement effective management policies. The emergence of shared e-bikes and advancements in machine learning have opened up new avenues for accurately examining the determinants of WWR behavior. Therefore, this study utilizes a large-scale dataset of shared e-bike trajectory data to establish a framework for detecting WWR behavior. Subsequently, association rule mining investigates the correlation among road, traffic, environmental factors, and the likelihood of higher and lower WWR behavior. The results indicate that: (1) In the association rules for higher WWR frequency, the absence of central separation facilities and bike lane separation facilities on the tertiary road, as well as lower land use density and the lack of public transportation facilities, enhanced the likelihood of WWR occurrence; (2) In the association rules for lower WWR frequency, longer crossing facility distance, physical bike lane separation, along with higher land use mixing and the presence of public transportation facilities, reduce the probability of WWR occurrence; (3) Time conditions display spatial heterogeneity, and different land use and road condition modulate the impact of time factors on rider’ intention for WWR. Finally, based on the study findings, adequate policy recommendations are proposed for urban management agencies to reduce WWR behavior and enhance the safety of the e-bike traffic system.

Soil improvement withsugarcane bagasse ash : technical-economic viabilityfor tertiary roads

Introduction: Economic evaluation of soil subgrade improvement using sugarcane bagasse ash case study: Propal Road - La Cabaña Sugar Mill”, developed at the Pontifical Javeriana University of Cali in 2022. Problem: Tertiary roads in Colombia are essential for mobility in rural areas and for the sugar industry, which generates waste such as sugarcane bagasse ash (SGBA). Objective: To present the results of the economic and technical feasibility study of using sugarcane bagasse ash for soil improvement in tertiary roads. Methodology: Characterization tests of natural soil state and modified Proctor, expansion index, CBR, and unconfined compression for stabilized soils at percentages of 5, 10, 15, and 20% of SGBA are carried out. Results: The mechanical properties of the soil improve with additions of ash between 5% and 15%; however, the utilization of 15% of SGBA is proposed to favor the disposal of a significant volume of this waste. Conclusion: The technical and economic feasibility of using SGBA as a promising solution to improve tertiary roads in Colombia is demonstrated. Originality: Viability of implementing sugarcane bagasse ash on rural roads of sugar mills and agricultural areas with production of this type of waste. Limitations: Similar studies should be carried out for each region to confirm the appropriate percentage for subgrade stabilization using SGBA.

Characterization of the family economy of the La Hermosa farm in the village of La Libertad in Florencia - Caquetá

The peasant family economy in the La Hermosa farm, located in the La Libertad hamlet of Florencia, Caquetá, faces significant challenges due to the disarticulation of the community and the lack of inclusion of plot holders in communal projects. This study analyzes the family economy of the farm, characterized by the multifunctionality of its activities, including swine, poultry and agricultural production. The main economic activity is swine farming, which generates income in the short and medium term, allowing for continuous production cycles. Poultry production, divided between egg and chicken production, contributes additional income, while bread crops are essential for family nutrition and food sovereignty. The peasant economy on the farm is characterized by the active participation of family labor and its articulation with local markets. However, marketing faces obstacles such as the poor condition of tertiary roads and increased transportation costs. Short marketing circuits allow a direct relationship between producers and consumers, favoring the sale of fresh and organic products. This work highlights the importance of implementing agroecological practices and sustainable production systems that preserve biodiversity and contribute to food security and sovereignty. It also emphasizes the need for policies that strengthen the peasant family economy, guaranteeing its economic viability and its capacity to adapt to environmental changes. The research also underlines the relevance of community participation and the integration of producers in local development projects to improve the living conditions of peasant families.

How Are Macro-Scale and Micro-Scale Built Environments Associated with Running Activity? The Application of Strava Data and Deep Learning in Inner London

Running can promote public health. However, the association between running and the built environment, especially in terms of micro street-level factors, has rarely been studied. This study explored the influence of built environments at different scales on running in Inner London. The 5Ds framework (density, diversity, design, destination accessibility, and distance to transit) was used to classify the macro-scale features, and computer vision (CV) and deep learning (DL) were used to measure the micro-scale features. We extracted the accumulated GPS running data of 40,290 sample points from Strava. The spatial autoregressive combined (SAC) model revealed the spatial autocorrelation effect. The result showed that, for macro-scale features: (1) running occurs more frequently on trunk, primary, secondary, and tertiary roads, cycleways, and footways, but runners choose tracks, paths, pedestrian streets, and service streets relatively less; (2) safety, larger open space areas, and longer street lengths promote running; (3) streets with higher accessibility might attract runners (according to a spatial syntactic analysis); and (4) higher job density, POI entropy, canopy density, and high levels of PM 2.5 might impede running. For micro-scale features: (1) wider roads (especially sidewalks), more streetlights, trees, higher sky openness, and proximity to mountains and water facilitate running; and (2) more architectural interfaces, fences, and plants with low branching points might hinder running. The results revealed the linkages between built environments (on the macro- and micro-scale) and running in Inner London, which can provide practical suggestions for creating running-friendly cities.

Road construction, economic growth, and poverty alleviation in China

AbstractImproving transportation infrastructure has been recognized as a necessary instrument for a region to achieve economic growth and poverty alleviation. A systematic assessment of the impact of China's transportation improvements on economic growth and poverty reduction is insufficient, especially in the context of China's targeted poverty alleviation policies. This study first constructed a theoretical framework of road construction promoting economic growth and poverty alleviation. Then, based on county panel data from 2014 to 2018, the spatial analysis technology was applied to investigate the spatio‐temporal patterns of China's road construction and rural poverty alleviation, and finally, a mediating effect model was used to quantitatively measure the impact of road construction on economic growth and poverty alleviation. Results indicate that China has made remarkable achievements in road construction and poverty reduction over the past five years. Road and railway mileage increased by 14 times and 0.66 times, respectively. Road construction in poor areas was dominated by low‐grade roads and railways. There was a mediating effect between road construction and poverty alleviation, and economic growth was the mediating variable between them. The poverty reduction effects of different road levels varied with poverty levels and across regions. But on both the national and regional scale, the poverty reduction effect of road construction was higher than that of railways. The effect of high‐grade road construction on poverty reduction in poor areas was more obvious than that of low‐grade roads. The poverty reduction effect of the primary road construction was 2–3.5 times that of the tertiary road. The poverty reduction effects of railway construction and road construction followed a gradually increasing gradient from east to west. These results indicate that transportation infrastructure construction is an important way to promote economic growth and poverty alleviation in poor areas. Our findings would provide a scientific basis for transportation infrastructure planning and investment decision‐making in less‐developed countries.

Residue from coal combustion for plastic soil improvement

The combustion of coal in Hoffman-type furnaces generates ash as one of the process residues. This research seeks to make use of this residue to improve plastic subgrade soils in tertiary roads, considering that in Colombia a large percentage of these are not paved. A soil with high plasticity has been selected to make mixtures with ash dosages that vary from 0% to 15% with respect to the dry weight of the soil. To determine the variation of the physical and mechanical properties of the soil-ash mixtures tests of consistency limits, compaction tests, and California bearing ratio were carried out. The results showed that the mixture in which 12% of the coal combustion residue is added to the soil, as a percentage for the dry weight of the soil, has a better physical behavior and bearing capacity than the soil in its natural state. obtaining an increase of up to 75% in the California bearing ratio.

A Monitoring Program to Evaluate the Coastal Grassland Restoration Incentive Program

The Gulf Coast Joint Venture (GCJV) is a regionally based, biologically driven, landscape-oriented volunteer partnership of private, state, and federal conservation organizations dedicated to the delivery of habitat important to priority bird species. The GCJV partnership’s Coastal Grassland Restoration Incentive Program (C-GRIP) provides financial incentives to private landowners for conducting habitat treatments that address the greatest limiting factor(s) to providing suitable grassland bird habitat on their property. The C-GRIP program is a way for the GCJV to deliver bird habitat to meet planning objectives for grassland birds, including northern bobwhite (Colinus virginianus). Our monitoring objective is to evaluate whether the C-GRIP program is effective in providing a relative increase in the density (number/acre) of priority grassland bird species in focal delivery areas versus control areas over a 10-year period. Twenty survey routes (2 within each of 5 focal areas and 2 outside of each area, serving as controls), located on secondary and tertiary roads, were designated in the Texas Mid-Coast Initiative Area of the GCJV. Each route is 15 miles long and the land cover is similar along all survey routes. Each route has ≥30 point-count stations separated by ≥0.5 mile. We recognize that some routes will experience increased development over time, especially in counties neighboring large population centers such as Houston and Victoria. The plan is to continue to monitor these routes, as long as safety concerns do not increase. Survey data will be analyzed using Program Distance 7.3, release 1. Our poster will include details about the monitoring objective, survey route selection, and survey methods.

Analysis of Satellite Images Using Deep Learning Techniques and Remotely Piloted Aircraft for a Detailed Description of Tertiary Roads

This document presents the results of a proof of concept for describing with more detail the social and complementary infrastructure around the tertiary roads of the Taminango region in the department of Nariño, Colombia. A dataset with samples of free satellite images from Google Maps and OpenStreetMaps was obtained. Then, a supervised deep learning algorithm with FCN (Fully Convolutional Network) topology is applied for the points of interest labeling process and the identification of the state of the roads using Keras and TensorFlow. Subsequently, a system consisting of a desktop application and a mobile application that integrates the functionalities of the trained algorithm through an intuitive interface and simple logic that stimulates interaction with the consultant is proposed. The desktop application includes a GUI designed in Python for tagging points of interest. The mobile application was developed with Flutter and comprises a database with documentation of the routes and road network in the region. It includes an augmented reality system in Vuforia Engine and Unity with virtual content developed in Blender and SolidWorks; A 3D model of the map of the region has been recreated for easier interaction and visualization of the points of interest and the status of the studied roads. In addition, complementary information was collected through remotely piloted aircraft for data acquisition in environments difficult to access, and through the community participation for the description and identification of areas not visible on official maps or statistics. This study addresses a method for the classification and identification of state of tertiary road network of the studied region, as well as labeling points of interest for the efficient management of resources for the development of new infrastructure there.

Distribution and land use characteristics of alluvial fans in the Lhasa River Basin, Tibet

In Lhasa River Basin (LRB), land suitable for settlement or living is experiencing a shortage of resources. Alluvial fans have the potential to alleviate this problem. However, basic information, such as the distribution and land use types of alluvial fans, is rarely studied. In this study, Google Earth, ArcGIS and visual interpretation were used to obtain the outlines, areas, quantities and distribution of alluvial fans. Meanwhile, to show the utilisation potential of alluvial fans, we analysed the land use, their distance from the roads, places (town and village) and rivers. The results showed 826 alluvial fans exist in LRB, with a total area of 1166.03 km2. The number of alluvial fans with areas between 0.1 and 1 km2 is 517, accounting for 62.59% of the total number of alluvial fans. Grassland is the dominant land use type, accounting for 68.70% of the total area of alluvial fans. The cropland area accounted for 2.16% of alluvial fans and accounted for 18.98% of the total cropland area in LRB. Exactly 93.70%, 53.63% and 61.86% of the total number of alluvial fans were located within 5 km from the tertiary road, village, and river, respectively. To sum up, our survey results showed that alluvial fans are important land resources in LRB and may have huge utilisation potential.

Survival and cause-specific mortality of European wildcat (Felis silvestris) across Europe

Humans have transformed most landscapes across the globe, forcing other species to adapt in order to persist in increasingly anthropogenic landscapes. Wide-ranging solitary species, such as wild felids, struggle particularly in such landscapes. Conservation planning and management for their long-term persistence critically depends on understanding what determine survival and what are the main mortality risks. We carried out the first study on annual survival and cause-specific mortality of the European wildcat with a large and unique dataset of 211 tracked individuals from 22 study areas across Europe. Furthermore, we tested the effect of environmental and human disturbance variables on the survival probability. Our results show that mortalities were mainly human-caused, with roadkill and poaching representing 57% and 22% of the total annual mortality, respectively. The annual survival probability of wildcat was 0.92 (95% CI = 0.87–0.98) for females and 0.84 (95% CI = 0.75–0.94) for males. Road density strongly impacted wildcat annual survival, whereby an increase in the road density of motorways and primary roads by 1 km/km2 in wildcat home-ranges increased mortality risk ninefold. Low-traffic roads, such as secondary and tertiary roads, did not significantly affect wildcat's annual survival. Our results deliver key input parameters for population viability analyses, provide planning-relevant information to maintain subcritical road densities in key wildcat habitats, and identify conditions under which wildcat-proof fences and wildlife crossing structures should be installed to decrease wildcat mortality.

What type of infrastructures do e-scooter riders prefer? A route choice model

E-scooter is an innovative travel mode that meets the demand of many travelers. A lack of understanding of user routing preferences makes it difficult for policymakers to adapt existing infrastructures to accommodate these emerging travel demands. This study develops an e-scooter route choice model to reveal riders’ preferences for different types of transportation infrastructures, using revealed preferences data. The data were collected using Global Positioning System units installed on e-scooters operating on Virginia Tech’s campus. We applied the Recursive Logit route choice model to 2000 randomly sampled e-scooter trajectories. The model results suggest e-scooter riders are willing to travel longer distances to ride in bikeways (59% longer), multi-use paths (29%), tertiary roads (15%), and one-way roads (21%). E-scooter users also prefer shorter and simpler routes. Finally, slope is not a determinant for e-scooter route choice, likely because e-scooters are powered by electricity.

Resource Selection by Wild and Ranched White-Tailed Deer (Odocoileus virginianus) during the Epizootic Hemorrhagic Disease Virus (EHDV) Transmission Season in Florida.

Simple SummaryEpizootic hemorrhagic disease virus is transmitted by Culicoides midges and causes serious disease in wild and privately ranched white-tailed deer (Odocoileus virginianus) in the United States. The U.S. deer ranching industry is fast growing and generates an estimated ~USD 8 billion annually. In Florida, there are over 400 registered deer farms, and virus rates are high among these populations. While vaccines for the virus are becoming available, many farms have large hunting preserves, where safely capturing deer is difficult. At the same time, these farms are situated in proximity to wild deer populations, and both populations are at risk. We studied habitat selection in ranched deer within a ~180 ha high-fenced preserve. We GPS-collared deer in the hunting preserve and nearby state-managed lands to compare habitat selection. During 2016, we collected GPS data from 15 ranched and eight wild deer and built resource selection function models. These models suggest ranched deer select habitats more likely to support several midge species that transmit the virus compared to wild deer. These differences in habitat use may partially explain previously confirmed higher rates of disease exposure in the ranched deer. Our results may inform ranch land management strategies that reduce midge–deer contact.Epizootic hemorrhagic disease virus (EHDV) causes serious disease in wild and privately ranched white-tailed deer (Odocoileus virginianus) in the United States. In Florida, there is high EHDV prevalence, yet no treatments. There are few management strategies for the disease due to limited knowledge of virus–vector–host interactions. We conducted a telemetry study on white-tailed deer to examine resource use by wild and ranched animals in the Florida panhandle during the 2016 transmission risk period. We built generalized linear mixed models (GLMMs) to estimate resource selection and map habitat preferences for wild and ranched deer in the study area to reveal how second-order selection may relate to higher disease prevalence in ranched deer. Wild deer preferred areas closer to tertiary roads and supplementary food sources but farther from permanent water. Ranched deer selected bottomland mixed forest and areas closer to tertiary roads, supplementary food sources, and permanent water. Ranched deer behaviors may increase the likelihood of EHDV vector encounters, as these deer selected preferred habitats of several putative vector species, which may increase vector blood meal success and viral transmission risk. Disparate resource selection behaviors may be a factor in observed differential EHDV exposure risk between ranched and wild white-tailed deer in Florida.

Assessment on skidding roads and densities

Ormanların optimal şekilde işletmeye açılmasında yol ağları, ulaşım ve taşıma altyapısının temel unsurudur. Ana ve tali orman yolları ile yeterince işletmeye açılamayan orman alanlarında üçüncül yollar olarak sürütme ve/veya traktör yolları yapılarak sürütme mesafeleri kısaltılmaya ve sürütme maliyetleri azaltılmaya çalışılır. Ormancılığa yönelik birçok uygulamada olduğu gibi sürütme yollarının da orman ekosistemi üzerinde geçici ve/veya kalıcı olumsuz etki potansiyeli bulunmaktadır. Öte yandan, herhangi üretim bölmesi veya bölmeciğinde, üretim operasyonları için sürütme yol uzunluğunun nasıl bir artış gösterdiğine ilişkin yeterli veri, bilgi ve kayıtlara rastlanmamaktadır. Bu çalışmanın amacı; sürütme yollarının niteliklerini özetlemek, ayırt edici özelliklerini tarif etmek, örnek alınan bazı üretim bloklarında sürütme yolu yoğunluklarını hesaplayıp bu değerlerin değişimine göre sürütme yolu ağlarının potansiyel ekolojik etkileri konusunda bazı değerlendirmeler yapmaktadır. Isparta Orman Bölge Müdürlüğü sınırları içinde, Google Earth programından yararlanılarak rastgele seçilen 30 adet üretim ünitesinin, üretim öncesi ve sonrasındaki uydu görüntüleri üzerinden sürütme yolu yoğunlukları hakkında veri toplanmış ve analiz edilmiştir. Buna göre, üretim sezonunun hemen bitiminde, sürütme yolu uzunluklarının üretim üniteleri başına ortalama 3290 m olduğu ve sürütme yol yoğunluğunun da ortalama 83.1 m/ha’a eriştiği belirlenmiştir. Sürütme yollarının ortalama 3 m genişlikte bir alan kaybına neden olduğu kabul edildiğinde; 1 ha’ lık orman alanının yaklaşık % 2.5’i sürütme yollarından dolayı kaybolmaktadır.

Resource selection at homesites by wolves and eastern coyotes in a Canis hybrid zone

AbstractWe modeled resource selection by wolves (Canis spp.), eastern coyotes (C. latrans), and admixed canids during the pup‐rearing season at den and rendezvous sites (collectively, homesites) within a largely unprotected landscape proposed as the recovery zone for federally and provincially threatened eastern wolves (C. lycaon) in Ontario, Canada. Overall, canids selected wetlands, while avoiding secondary roads and open‐structure rock‐grass habitat patches. Packs with greater wolf ancestry selected wetlands and tertiary roads more strongly, while avoiding mixed conifer‐hardwood forests. Contrary to our prediction, canids with greater coyote ancestry did not establish homesites closer to roads, which likely mitigated their risk of human‐caused mortality during pup‐rearing. Packs exhibited increased selection of wetlands within territories as a function of increasing availability of wetlands. Packs with abundant access to wetlands may prioritize this habitat type to exploit beavers, a valuable prey species during pup‐rearing. Packs with higher pup survival selected hardwood forests and avoided conifer forests more than packs with lower pup survival. This is consistent with our understanding of habitat relations of the main prey species for canids in central Ontario and suggests that selecting prey‐rich habitat types at homesites increases fitness. A proposed goal of eastern wolf recovery is numerical and geographical expansion outside of the population core in Algonquin Provincial Park. Thus, our results provide valuable information for conservation by quantifying resource selection of wolves, coyotes, and hybrids during pup‐rearing and identifying links between fitness and homesite selection.

Does cycling infrastructure reduce stress biomarkers in commuting cyclists? A comparison of five European cities

There is substantial evidence that the environment has an important impact on the use of bicycles. Changes in the built environment, such as cycling infrastructure provision, usually aim at improving the efficiency, enjoyability and safety of cycling. They can also shape affective responses, for instance by triggering or preventing stress situations during cycling. The repeated occurrence of intensely stressful events may make actual cyclists more likely to abandon cycling and deter prospective cyclists from actually taking up this form of mobility. Therefore, using a novel approach, based on stress biomarker measurements obtained directly from cyclists, the objective of this study is to investigate the relationship between urban environment and cyclists' stress. It also investigates if different types of cycling infrastructures in the contexts of two different countries and in five different cities have different relationships with stress. Using a stress sensor, 70 young adults were invited to cycle along a standard route in Oxford, London (the United Kingdom), Amsterdam, Houten and Groningen (the Netherlands). These routes were around 6 km long and had a wide range of characteristics. Multilevel logistic regression analysis indicates that the probability of stressful events occurring is significantly lower on physically segregated cycle paths than on cycle paths on streets, with cycling on general use streets falling in-between these extremes. We also find higher probabilities of stress for primary roads compared to tertiary roads, at intersections than on straight roads, on cobbled and off-road surfaces compared to asphalt, and in noisier places. Models for the individual cities suggested that the relationship between cycling infrastructure and the likelihood of stressful events occurring may depend on the local context. Only for noise conditions, intersection types and cycling infrastructures were the effects consistent across the cities. These findings may be useful for urban infrastructure planning and management, indicating specific attributes that should be adjusted to make cycling less stressful.

Toward a Type-based Analysis of Road Networks

Road networks are major influential factors in the development of any nation. Due to different factors involved in their evolution, road networks exhibit complex structures, which result in problems such as inefficient traffic patterns, congestion, and environmental pollution. The existing metrics of road network analysis are found to be inadequate to reveal the complexity of networks that contributes to such problems. Therefore, we propose a new dimension for the road network analysis using road-types to understand such problems and analyze 57 cities from eight regions around the world: (i) India, (ii) North America, (iii) South America, (iv) Europe, (v) Asia, (vi) China, (vii) Japan, and (viii) Oceania. We define four new metrics: (i) Link Type Distribution , (ii) Link Type Demand , (iii) Preference Cost , and (iv) Type Closeness , for measuring the influence of road-types in the cities concerned. Link type distribution computes the share of each road-type in shortest paths while link type demand measures the type distribution considering the users’ preference of road-types. The metric preference cost is defined to measure the additional cost users incur on choosing higher-quality roads and type closeness computes the minimum distance a user needs to travel to reach the preferred road-type. Our analysis shows that, in cities of India, Europe, Asia, China, and Oceania, the primary, secondary, and tertiary roads play a crucial role in the shortest paths in terms of link type distribution as well as link type demand. Also, the involvement of secondary road-type is an important feature among cities from all regions except Japan, where the distribution and demand concentrated in tertiary as well as unclassified types. Cities in North and South American regions provide more importance to residential roads besides the secondary type. In addition to distribution and demand, our analysis shows that the primary, secondary, and tertiary road-types with higher demands suffer from link type deficits while the least demanded types are offered with link type surpluses, which explains one of the reasons for inefficient traffic patterns in congested cities. As far as the additional cost incurred for higher-quality roads is concerned, cities in India and USA provide least preference cost while Chinese and South American cities incur high costs. Among the 57 road networks concerned, Japan shows uniqueness in terms of the proposed metrics due to their inclusion of tertiary and unclassified roads.

Road network drives urban ecosystems - a longitudinal analysis of impact of roads in the central Himalaya

This study investigates spatio-temporal paradigm of the impact of road networks on urban ecosystem dynamics (UED) by analysing the composition and configuration of land use land cover (LULC) and land surface temperatures (LST) derived from Landsat data for the years 2000 and 2017. The results indicate a positive association between road network and built-up land showing higher concentration of built-up land closer to the road network. This increase in grey infrastructure has led to an increase in the maximum LST by 6 °C to 7.5 °C along primary and tertiary roads, whereas 4 °C to 5 °C along secondary roads. Rapid intensification of road network along with the associated disproportionate changes in LULC and LST are deemed to be the major contributors to UED. Findings from this study will serve as baseline for examining the influence of road network on regional urban growth and assist in sustainable road infrastructure planning.

On the logistics of cocoa supply chain in Côte d’Ivoire: Simulation-based analysis

Côte d’Ivoire produces about 42 percent of the world’s total Cocoa but processes only 30 percent of the total production. A large part of the country depends on the commercial benefits of the Cocoa production and supply chain of it. In this paper, we develop a simulation model that assess the performance of the logistics of the Cocoa supply chain in Côte d’Ivoire. The simulation model shed light on the potential of improvements in the logistics of the Cocoa supply chain by identifying inefficiencies, bottlenecks, and blockers that hinder the productivity and performance of the Cocoa supply chain. Results from simulations show that reduction of checkpoints along the roads will increase productivity by 30 percent, while the value of beans in the Port will increase 3 percent and of butter 5 percent. Investing in improving secondary and tertiary roads will increase the productivity by 9 percent and value by 1 percent while investing in improving road infrastructure and checkpoints will raise the productivity by 27 percent and the value by 3 percent. The results suggest that a combination of reducing the checkpoints with the investment in secondary and tertiary roads will increase productivity while at the same time the pollution will be reduced importantly. The results also suggest that the switching from only producing beans to butter should be accompanied with the increase in productivity otherwise the value at the market would not be sensitive. Other important results are also presented in this paper, together with suggestions for improvement in order to optimize the logistics of Cocoa supply chain, and increase the profitability of the Cocoa sector, and hence the living conditions and wellbeing of the farmers in the country.

Diskretna Furijeova transformacija i cepstrum analiza pojave vibracija kod kamiona sa poluprikolicom

The aim of this paper is to present a novel technique to analyse the vibration signals during transportation in order to give new information to engineers to better understand these physical events. One of the primary sources of damages during transportation is the permanent vibration transmitted from the platform of semi-trailer to the cargo. The nature of this vibration depends on the road conditions and the features of the vehicle. In this study, a 2-axle-truck with a 3-axle-semi-trailer equipped with air spring suspension was observed to analyse the vibration circumstances. The affecting factors during the transportation were the type of the road (motorway, primary road, secondary road, tertiary road), and different vehicle speed levels. The vibration events were measured and registered on the platform of the trailer, then these values were evaluated in MATLAB environment. The presence of the harmonic vibrational components, the stationarity of the mode shapes, the characteristic frequency narrow-bands of the RMS and PSD values were primarily studied. The applied methods that were used are: discrete Fourier transformation, autocorrelation-, cross-correlation functions and cepstrum analysis.