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Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due to limitations in utilizing heterogeneous sensing data and domain knowledge as well as insufficient generalizability resulting from limited data samples. This paper integrates implicit and qualitative expert knowledge into quantifiable values in tunnel condition assessment and proposes a tunnel structure prediction algorithm that augments a state-of-the-art attention-based long short-term memory (LSTM) model with expert rating knowledge to achieve robust prediction results to reasonably allocate maintenance resources.

Through formalizing domain experts' knowledge into quantitative tunnel condition index (TCI) with analytic hierarchy process (AHP), a fusion approach using sequence smoothing and sliding time window techniques is applied to the TCI and time-series sensing data. By incorporating both sensing data and expert ratings, an attention-based LSTM model is developed to improve prediction accuracy and reduce the uncertainty of structural influencing factors.

The empirical experiment in Dalian Road Tunnel in Shanghai, China showcases the effectiveness of the proposed method, which can comprehensively evaluate the tunnel structure condition and significantly improve prediction performance.

This study proposes a novel structure condition prediction algorithm that augments a state-of-the-art attention-based LSTM model with expert rating knowledge for robust prediction of structure condition of complex projects.

The purpose of this paper is to identify the issues and challenges in humanitarian logistics and to develop a framework for effectively managing the humanitarian logistics in disaster relief supply chain operations in India.

This paper presents a framework to manage humanitarian logistics effectively in disaster management through qualitative analysis. First, the author examines the challenges facing the humanitarian logistics and supply chain through the reviews of the literature on various disasters. Then, the author presented a framework based on the best practices and initiatives taken worldwide in the preparedness and response stage of the humanitarian supply chain to manage and reduce the aftermath of any disaster in context to India.

A framework has been developed to manage humanitarian logistics in the disaster relief operation, which would improve the humanitarian supply chain in India and help to effectively manage natural disasters in the preparedness and response stage at the state and district levels.

The paper mainly emphasises on the preparedness and response stage of disaster supply chain management in Indian context.

None of the disaster incidents can be stopped from taking place, but the impact can be minimised by proper preparedness and effective response during the operations of humanitarian logistics. With this hope, the framework has been developed, which if implemented would help to plan and manage any disaster incident in an effective manner, which ultimately would save millions of lives and cost in terms of infrastructure, property, assets etc.

As natural disaster incidents are occurring frequently in Indian states, there is an urgent need for a framework to manage the logistics operations effectively and efficiently during any disaster relief operations. Limited literature is found on developing and presenting a framework focusing on the preparedness and response phase of disaster supply chain management in context to India. Hence, this paper is believed to be the first to fulfil this gap with main emphasis on the preparedness and response stage of disaster supply chain management in Indian scenario.

Automated condition surveys have been recently introduced for condition assessment of highway infrastructures worldwide. Accurate predictions of the current state, median life (ML) and future state of highway infrastructures are crucial for developing appropriate inspection and maintenance strategies for newly created as well as existing aging highway infrastructures. The paper aims to discuss these issues.

This paper proposes Markov Chain based deterioration modelling using a linear transition probability (LTP) matrix method and a median life expectancy (MLE) algorithm. The proposed method is applied and evaluated using condition improvement between the two successive inspections from the Surface Condition Assessment of National Network of Roads survey of the UK Pavement Management System.

The proposed LTP matrix model utilises better insight than the generic or decoupling linear approach used in estimating transition probabilities formulated in the past. The simulated LTP predicted conditions are portrayed in a deterioration profile and a pairwise correlation. The MLs are computed statistically with a cumulative distribution function plot.

The paper concludes that MLE is ideal for projecting half asset life, and the LTP matrix approach presents a feasible approach for new maintenance regime when more certain deterioration data become available.

The complexity of atmospheric corrosion, further compounded by the effects of climate change, makes existing models inappropriate for corrosion prediction. The commonly used kinetic model and dose-response functions are restricted in their capacity to represent the non-linear behaviour of corrosion phenomena. The application of artificial intelligence (AI)-driven machine learning algorithms to corrosion data can better represent the corrosion mechanism by considering the dynamic behaviour due to changing climatic conditions. Effective use of materials, coating systems and maintenance strategies can then be made with such a corrosivity model. Accurate corrosion prediction will help to improve climate change resilience of the social, economic and energy infrastructure in line with the UN Sustainable Development Goals (SDGs) 7 (Affordable and Clean Energy), 9 (Industry, Innovation and Infrastructure) and 13 (Climate Action). This chapter discusses atmospheric corrosion prediction in relation to the SDGs and the influence of AI in overcoming the challenges.

The purpose of this paper is to explore the emissions of SO₂, NO₂ and SPM in India during 1991‐2003. The Environmental Kuznets' Curve (EKC) is applied to explore the relationship between economic development measured in terms of State Domestic Product (SDP) per capita and different air quality parameters for industrial and residential locations respectively. Several developmental factors contribute to change in emissions of these air quality parameters. These factors generally include the scale effect, composition effect and the pollution abatement effect.

The methodology has focused on testing the EKC hypothesis at state level in India, using cross‐section and time series data for 15 major states. The study has made use of fixed effect version of pooled data estimation technique.

The findings in the paper indicate only a directional inverted U‐shaped EKC relationship for both industrial and residential locations, without being significant statistically. Basically, some developmental factors such as population density, urbanization and policy variables are significant with expected signs in explaining the relationship for most of the cases. The calculated turning point of SDP per capita for different air quality parameters ranges between $163.46 and $408.66

The present study has been restricted to a shorter time period (i.e. 1991‐2003) because of the unavailability of continuous time series data. The study only includes 15 major Indian states and excludes other states due to lack of proper data sources.

The inclusion of several developmental variables (such as urbanization, infrastructure development, population density, policy) helps to detect whether the emissions of different air quality is mainly due to economic growth or other reasons.

The investigation in the paper allows determination of the level of SDP per capita, the emissions of different types of air quality will start to decrease in different Indian states.

The purpose of this paper is to explore the problem of land degradation as a category of environmental terrorism, which has been increasing along with the rise of open pit mining and oil palm plantation activities.

This study uses a doctrinal approach that aims to find the best solution to address the problem of land degradation and environmental terrorism activities in Indonesia through a comparative legal study conducted with the handling of similar cases in Malaysia, which has almost the same character as Indonesia.

This paper finds that both Indonesia and Malaysia have enacted laws and regulations to address environmental concerns. However, it turns out that relying only on law enforcement is not an optimal solution. Addressing the problem of land degradation would also require the implementation of sustainable development practices, public awareness and cooperative dialogue.

This paper provides a new approach to answer the inclusion of environmental degradation as environmental terrorism, which should also be considered a crime against humanity.

In Africa, poverty and food insecurity is pervasive due to intertwined factors including, declining crop yields, land degradation and inadequate policy and institutional support. With ever-increasing populations, climate change effects will be intensified, and a major crisis is inevitable unless measures to sustain land resources are urgently taken. This paper aims to argue that vibrant rural institutions are necessary to ensure food security and environmental protection, consequently contributing to climate change resilience.

The paper demonstrates the role of institutions by evaluating two types of institutions and their impacts the “status quo” and “hybrid” institutions using case studies from the African Highlands Initiative in Uganda and International Forestry Resources and Institutions in Kenya. It further discusses a model that highlights factors affecting smallholder investment in natural resources management and how these can be used to strengthen local institutions in building their resilience against climate change effects.

Weak grassroots institutions characterized by low capacity, failure to exploit collective capital and poor knowledge sharing and access to information, are common barriers to sustainable land management and improved food security.

Case studies from Uganda and IFRI in Kenya barriers in data collection instruments and language.

In Africa, poverty and food insecurity is pervasive due to intertwined factors including, declining crop yields, land degradation and inadequate policy and institutional support. With ever increasing populations, climate change effects will be intensified, and a major crisis is inevitable unless measures to sustain land resources are urgently taken.

In Africa, poverty and food insecurity is pervasive due to intertwined factors including, declining crop yields, land degradation and inadequate policy and institutional support. With ever-increasing populations, climate change effects will be intensified, and a major crisis is inevitable unless measures to sustain land resources are urgently taken.

The paper further discusses a model that highlights factors affecting smallholder investment in natural resources management and how these can be used to strengthen local institutions in building their resilience against climate change effects.

Of late, cities across the globe are taking pragmatic steps towards addressing environmental, social and economic problems in the debate on sustainable development. Even so, little attention has been paid to studies focused on developing countries. The aim of this study is to examine the barriers to green cities development in developing countries.

A comprehensive literature review was conducted to examine the barriers to green cities development. In terms of methodological choice, a quantitative research strategy was used to collect data from professionals who have lines of influence on the greening of our cities and sustainable urban development.

The barriers to green city development identified were lack of awareness of the benefits of a green city, environmental degradation, insufficient policy implementation efforts, excessive generation of solid waste and poor wastewater collection and treatment. It was indicative from the study findings that taking the right sustainable steps in urban development and a paradigm shift towards the pillars of sustainability, Ghanaian cities, especially Kumasi, have a great proclivity of regaining its longstanding status being “Garden City”.

The outcome of this study provides stakeholders in city development an insight into the barriers that inhibit the development of green cities. In practice, this study contributively proposes that the concept of green cities should be incorporated in the education and training of stakeholders to improve the level of awareness.

This paper presents the foremost comprehensive study appraising green city development in Ghana.

The purpose of this paper is to identify the contextual factors affecting infrastructure reporting by New Zealand local authorities.

The paper includes a survey and interview of Annual Report Recipients (ARRs) and Infrastructure Information Preparers (IIPs), together with an assessment of the extent of infrastructure information disclosure in the annual reports of New Zealand local authorities.

This study finds that contrary to the expectations of Lüder’s contingency model (1992), there is an information dissemination gap between the perceptions of ARRs and IIPs regarding infrastructure information reporting in the annual reports of New Zealand local authorities. This finding is consistent with decades of concern about the application of private sector Generally Accepted Accounting Principles to the public sector and the Controller and Auditor General’s (CAG, 2009) concern about the inadequacy of private sector General Purpose Financial Reports in meeting public sector accountability. On the other hand, the study reports that the perceptions of the two groups, ARRs and IIPs, are similar with regard to the importance of infrastructure information items, which is consistent with the expectations of Lüder’s model.

The paper contributes towards theoretical development by adopting Lüder’s (1992) contingency model in the context of infrastructure reporting by New Zealand local authorities and proposing a model of contextual factors by extending Lüder’s model. The practical contribution of the study is in the area of accounting practice and public policy.

The purpose of this paper is to assess the effect of urban regeneration and renewal activities initiated by the Osun State Government in Nigeria on the rental values of commercial properties in Osogbo, the state capital between 2008, before the urban renewal programme through 2017, after the urban renewal programme had been completed.

Primary data utilised for this study were collected from all the Estate Surveying and Valuation firms involved in the formal management of commercial properties in Osogbo, Osun-State, Nigeria. Information on the types of urban infrastructure renewed and rental values of 63 commercial properties from 2008 to 2017 were obtained from the sampled estate surveying and valuation firms practicing in the study area. Data were analysed using descriptive statistics, analysis of variance and Duncan post hoc test.

The findings showed that physical urban infrastructure such as roads, drainages, water supply and wastes disposal have been upgraded in the study area. Also, the study established that the urban regeneration programme had significant impact on the rental values of commercial properties in Osogbo, arising from the statistically significant difference (F(7, 600) = 22.264, p<0.000) between and within annual rental values of commercial properties in the study area. The annual rental values of the commercial properties also exhibited considerable variation based on the Duncan post hoc test.

The findings from this study indicate that urban regeneration programme by the Osun state Government has significantly increased the investment performance of commercial properties in the study area. Hence, while investors could achieve higher returns on investment by venturing into commercial property investment, revenue could also be generated for government through the collection of property taxes in the study area.

This study is one of the few studies that have analysed the effect of urban regeneration programme on commercial property values from the perspective of an emerging African economy, using data from Osun State, Nigeria.