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The purpose of this manual is to provide technical staff ranging from site supervisors to engineers with a technical reference which details commonly used work methods and best practices for constructing rural roads. It describes all phases of works management from the initial stages of identification and design, through technical planning, work organization, works implementation procedures, site administration, to reporting and control.

This book contributes to the debate about the role of agriculture in poverty reduction by addressing three sets of questions:Does investing in agriculture enhance/harm overall economic growth, and if so, under what conditions? Do poor people tend to participate more/less in growth in agriculture than in growth in other sectors, and if so, when? If a focus on agriculture would tend to yield larger participation by the poor, but slower overall growth, which strategy would tend to have the largest payoff in terms of poverty reduction, and under which conditions?.

This article investigates whether public investments that led to improvements in road quality and increased access to agricultural extension services led to faster consumption growth and lower rates of poverty in rural Ethiopia. Estimating an Instrumental Variables model using Generalized Methods of Moments and controlling for household fixed effects, we find evidence of positive impacts with meaningful magnitudes. Receiving at least one extension visit reduces headcount poverty by 9.8 percentage points and increases consumption growth by 7.1 percentage points. Access to all-weather roads reduces poverty by 6.9 percentage points and increases consumption growth by 16.3 percentage points. These results are robust to changes in model specification and estimation methods.

In Nepal and many developing countries around the world, roads are vehicles for development for communities in rural areas. By reducing travel time on foot, opportunities are opened for quicker transportation of goods and better access to employment, education, health care and markets. Roads also fuel migration and numerous social changes, both positive and negative. Poorly constructed roads in mountainous areas of Nepal have increased erosion and landslide risk as they often cut through fragile geology, destabilizing slopes and altering local hydrological conditions, with costs to lives and livelihoods. The convergence of the newly constituted decentralized Nepali government with China's Belt and Road Initiative is likely to bring more roads to rural communities. The new provincial government administrations now have the opportunity to develop policies and practices, which can realign the current trend of poorly engineered, inefficient and hazardous road construction toward a more sustainable trajectory. This commentary provides an overview of some of the obstacles along the way for a more sustainable road network in Nepal and illustrates how good governance, development and landslide risk are intertwined. The opinion presented in this brief commentary lends little hope that Nepal's current pathway of unsustainable road construction will provide the country with the much-needed sustainable road network, unless checks and balances are put in place to curb noncompliance with existing laws and policies.

The traditional aim in transportation planning is to maximise gains associated with vehicular travel distances or times, indirectly prioritising populations that live near existing or proposed roads—remote populations that first require hours of walking to reach roads are overlooked. In this paper, rural roads optimisation is performed using a new model that estimates proposed roads’ accessibility gains, considering reductions in vehicular travel time and reductions in walking time required by remote populations to reach them. This ensures that even the most remote populations that may benefit from new roads are included in their evaluation. When presented with a large number of proposed roads and the requirement of determining a plan within a suitable budget, it is often infeasible to construct all proposed roads. In such instances, subsets of well-performing road-combinations that are evaluated with respect to multiple objectives need to be identified for analysis and comparison–for which multi-objective optimisation approaches can be employed. Traditional optimisation approaches return a small number of road-combination plans only, limited to user-specified budget levels and objective weight sets. This paper presents an innovative heuristic solution approach that overcomes such limitations by returning thousands of well-performing solutions scattered across a budget span, and not limited in number to user-specified objective weight sets at fixed budget levels. The heuristic is employed along with a more traditional weighted-sum integer-linear programming approach to determine high-quality road-combination plans selected from 92 roads recently proposed for construction in Nepal’s remote Karnali province. Using these two approaches with inputs from the new multi-modal accessibility model, it is illustrated how rural roads planning can be performed to the benefit of rural populations regardless of their proximity to roads. New planning and analysis benefits of the heuristic are demonstrated by comparing its solutions to those determined by the weighted-sum approach, providing a level of detail and sophistication not previously possible for rural roads planning and analysis.

This study investigates the impact of the Sihao Rural Road (SHRR) Program on travel behavior in Qingshuihe County, Inner Mongolia, China focusing on travel mode choice, travel frequency, and travel distance. Using an integrated Structural Equation Model (SEM) and Discrete Choice Model (DCM) framework, data were collected from 127 households between August 2023 and March 2024. The analysis reveals that the SHRR program significantly reduces travel frequency, likely due to improved local accessibility that decreases the need for frequent trips. Simultaneously, SHRR facilitates longer travel distances and promotes greater reliance on motorized modes. This suggests that enhanced infrastructure enables residents to travel farther and more efficiently using private vehicles, motorcycles, and electric bicycles. Car ownership plays a critical role, significantly influencing both travel distance and the adoption of motorized modes. However, its relationship with the use of electric bicycles is more complex, with effects mediated by other factors such as travel distance and frequency. These findings underscore the importance of considering both direct and indirect effects of rural infrastructure policies when evaluating their impact on mobility patterns and transport mode choices.

Rural roads contribute significantly to the socio-economic and cultural development of rural habitations/villages. Improved road infrastructure facilitates rural population to look for work beyond their respective communities. They fuel the development of non-farm markets and create possible livelihood diversification opportunities for rural people, thereby decreasing their liability to economic distresses. The developing countries like India have been introducing various schemes to improve the status of their citizens. In 2000, Government of India launched Pradhan Mantri Gram Sadak Yojana (PMGSY) with a broad objective of improving the mobility of the rural population to achieve sustainable development in a phased manner. This article proposes a comprehensive approach to investigate the impact of the development of rural road infrastructure on livelihood diversification of the target population at the habitation level by employing fuzzy framework. It also accounts econometric modeling to assess the influence of diversification and control variables on household income. The effectiveness of the proposed model is illustrated by taking a case study of the construction of PMGSY roads in Jhunjhunu district of Rajasthan state, India. The findings reveal that newly constructed roads have been used prominently for agricultural activities. However, there is minimal growth in other occupations leading to low diversification of livelihood due to unawareness and lack of resources. It is, therefore, necessary that the policy makers should focus to implement reliable schemes to maximize livelihood diversification in a sustainable way. Thus, rural population can be served in an effective manner by promoting both farm and non-farm activities.

Rural roads contribute significantly to the living conditions of rural populations. However, they also lead to detrimental impacts on physical and social environments. In this context, the present study proposes a novel fuzzy multicriteria approach that amalgamates fuzzy TOPSIS and an improved fuzzy weighted average method to assess the negative impacts on physical and social environments, due to rural road construction. The approach offers a structured comprehension and incorporates detailed criteria that reflect the adverse effects. The attributes identified and assessed in this study are air quality, vegetation cover status, noise pollution, transmissible disease, habits/behaviour, safety and security, and road accidents. The approach includes both qualitative and quantitative data from focus group discussions. The results presented here are essential to identify corrective actions, promote effective distribution of funds, and facilitate effective decisionmaking for sustainable rural development.

With the continuous expansion of rural road construction and increasing management demands, traditional rural road inspection and maintenance models are becoming insufficient to meet current needs. The analysis of inspection results and the development of maintenance plans are often delayed. To address these challenges, this paper proposes a rural road distress sample recognition and annotation method based on machine vision techniques, and establishes a corresponding disease target identification sample database. The method is trained and validated using the U-Net algorithm, achieving an accuracy of 94.95%. Additionally, a lightweight detection system is developed to facilitate rural road surface disease target detection and automatic recognition. The self-developed automatic recognition system significantly enhances the accuracy and efficiency of pavement disease recognition. Furthermore, a management platform has been implemented to enable the dynamic management of rural road disease data and maintenance operations.

Road building has long been under-mapped globally, arguably more than any other human activity threatening environmental integrity. Millions of kilometers of unmapped roads have challenged environmental governance and conservation in remote frontiers. Prior attempts to map roads at large scales have proven inefficient, incomplete, and unamenable to continuous road monitoring. Recent developments in automated road detection using artificial intelligence have been promising but have neglected the relatively irregular, sparse, rustic roadways characteristic of remote semi-natural areas. In response, we tested the accuracy of automated approaches to large-scale road mapping across remote rural and semi-forested areas of equatorial Asia-Pacific. Three machine learning models based on convolutional neural networks (UNet and two ResNet variants) were trained on road data derived from visual interpretations of freely available high-resolution satellite imagery. The models mapped roads with appreciable accuracies, with F1 scores of 72–81% and intersection over union scores of 43–58%. These results, as well as the purposeful simplicity and availability of our input data, support the possibility of concerted program of exhaustive, automated road mapping and monitoring across large, remote, tropical areas threatened by human encroachment.