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This paper aims to promote urban–rural synergy in carbon reduction and achieve the dual carbon goal, reconstruct the low-carbon urban–rural spatial pattern and explore planning strategies for carbon mitigation in urban agglomerations.

The authors propose the idea of land governance zoning based on low-carbon scenario simulation, using the Beijing–Tianjin–Hebei (BTH) urban agglomeration as the empirical research area. Specifically, the authors analyze its spatiotemporal evolution characteristics of carbon balance over the past two decades and simulate the land use pattern under the scenario of low-carbon emission in 2030. Furthermore, the authors create spatial zoning rules combined with land use transition characteristics to classify the urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone and put forward corresponding targeted governance principals.

The study findings classify the BTH urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone, which account for 28.1%, 17.2%, 20.1% and 34.6% of the total area, respectively. The carbon sink restoration zone and carbon sink protection zone are mainly distributed in the northern and western parts and Bohai Rim region. The carbon transition agriculture zone and carbon control development zone are mainly distributed in the southeastern plain and Zhangjiakou.

The authors suggest restoring and rebuilding ecosystems mainly in the northwest and east parts to increase the number of carbon sinks and the stability of the ecosystem. Besides, measures should be taken to promote collaborative emission reduction work between cities and optimize industrial and energy structures within cities such as Beijing, Langfang, Tianjin and Baoding. Furthermore, the authors recommend promoting sustainable intensification of agriculture and carefully balance between both economic development and ecological protection in Zhangjiakou and plain area.

The authors propose a zoning method based on the optimization of land use towards low-carbon development by combining “top-down” and “bottom-up” strategies and provide targeted governance suggestions for each region. This study provides policy implications to implement the regional low-carbon economic transition under the “double carbon” target in urban agglomerations in China.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

The study aims to devise a comprehensive evaluation model (CEM) for evaluating spatial equity in the layout of elderly service facilities (ESFs) to address the inequity in the layout of ESFs within city center communities characterized by limited land resources and a dense elderly population.

The CEM incorporates a suite of analytical tools, including accessibility assessment, Lorenz curve and Gini coefficient evaluations and spatial autocorrelation analysis. Utilizing this model, the study scrutinized the distributional equity of three distinct categories of ESFs in the city center of Xi’an and proposed targeted optimization strategies.

The findings reveal that (1) there are disparities in ESFs’ accessibility among different categories and communities, manifesting a distinct center (high) and periphery (low) distribution pattern; (2) there exists inequality in ESFs distribution, with nearly 50% of older adults accessing only 18% of elderly services, and these inequalities are more pronounced in urban areas with lower accessibility, and (3) approximately 14.7% of communities experience a supply-demand disequilibrium, with demand surpassing supply as a predominant issue in the ongoing development of ESFs.

The CEM formulated in this study offers policymakers, urban planners and service providers a scientific foundation and guidance for decision-making or policy amendment by promptly assessing and pinpointing areas of spatial inequity in ESFs and identifying deficiencies in their development.

Airports are booming in China, to enlarge their capacities and stimulate economic development. Large-span spatial steel structures are commonly used in the terminal buildings of airport projects. Their advantages include prefabrication, strength, usability, adaptability and aesthetic quality. To manage large-span spatial steel structure projects, building information modeling (BIM) is recommended. Although there are plenty of studies on BIM application in steel structure projects, it is still rare to apply BIM to optimize the schedule and cost of steel structures, especially for airport projects.

This paper aims to develop a framework in which BIM and a time-cost optimization model are integrated to optimize construction costs and the duration of large-span spatial steel structure projects. A real case study was conducted to verify the feasibility of the BIM-based time-cost optimization model in an airport terminal building, which was built with a large-span spatial steel structure.

The results preliminarily support the reliability of the proposed BIM-based time-cost optimization model. The BIM-based time-cost optimization model will benefit construction planning for professionals and enrich relevant research on the application of BIM in large-span spatial steel structure projects.

The steel structure is difficult to control budgets and progress. This paper is expected to be adopted for optimizing the time and cost plans for projects involving steel structures in airport terminal buildings.

The purpose of this paper is to explore how a retail distribution network can be rationalised from a spatial perspective to improve service responsiveness and delivery efficiency.

This paper applies spatial analytics to examine variability of demand, both spatially and from a service delivery perspective, for an auto-parts retail network. Spatial analytics are applied to map the location of stores and customers to represent demand and service delivery patterns and to delineate market areas.

Results show significant spatial clustering in customer demand; whilst the delivery of products to customers, in contrast, is spatially dispersed. There is a substantial gap between revenue generated and costs. Market area analysis shows significant overlap, whereby stores compete with each other for business. In total, 80 per cent of customers can be reached within a 15-minute-radius, whilst only 20 per cent lies outside the market areas. Segmentation analysis of customers, based on service delivery, also shows the prevalence of the Pareto principle or 80:20 rule whereby 80 per cent of the revenue is generated by 20 per cent of customers.

Spatially integrated strategies are suggested to improve the efficiency of the retail network. It is recommended that less accessible and unprofitable customers could be either charged extra delivery cost or outsourced without the risk of a substantial reduction in revenue or quality of service delivery.

Innovative application of spatial analytics is used to analyse and visualise unit-record sales data to generate practical solutions to improve retail network responsiveness and operational efficiency.

The purpose of this paper is to develop a virtual reality (VR)-based and user-oriented decision support system for interior design and decoration. The four-phase decision-making process of the system is verified through a case study of an office building.

Different “spatial layouts” are presented by VR for users to decide their preference (Phase 1). According to the selected spatial layout, a “spatial scene” is constructed by VR and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to determine the spatial scene preference (Phase 2). Based on the binary integer programming method, the system provides the optimal preliminary solution under a limited decoration budget (Phase 3). Finally, the consistency between the overall color scheme and pattern is fine-tuned by VR in order to obtain the final solution (Phase 4).

The questionnaire survey results show that decision makers generally affirm the operation and application of VR, and especially recognize the advantages in the improvement of VR-based interior design feasibility, communication efficiency and design decision-making speed. The optimization of the costs and benefits enables decision makers to effectively evaluate the impact of design decisions on subsequent project implementation during the preliminary design process.

The VR-based decision support system for interior design retains the original immersive experience of VR, and offers a systematic multiple criteria decision- making and operations research optimization method, thus, providing more complete decision-making assistance. Compared with traditional design communication, it can significantly reduce cognitive differences and improve decision-making quality and speed.

Despite the enormous need to succeed in the urban model, scientists and policymakers should work consistently to create blueprints to regulate urbanization. The absence of coordination between the crucial requirements and the regional strategies of the local authorities leads to a lack of conformance in urban development. The purpose of this paper is to address this issue.

This study intends to manage future urban growth patterns using integrated methods and then employ the results in the genetic algorithm (GA) model to considerably improve growth behavior. Multi-temporal land-use datasets have been derived from remotely sensed images for the years 1990, 2000, 2010 and 2020. Urban growth patterns and processes were then analyzed with land-use-and-land-cover dynamics. Results were examined for simulation and utilization of the GA.

Model parameters were derived and evaluated, and a preliminary assessment of the effective coefficient in the formation of urbanization is analyzed, showing the city's urbanization pattern has followed along with the transportation infrastructure and outward growth, and the scattering rates are high, with an increase of 5.64% in building area associated with a decrease in agricultural lands and rangelands.

The research achieved a considerable improvement over the growth behavior. The conducted research design was the first of its type in that field to be executed to any specific growth pattern parameters in terms of regulating and policymaking. The method has integrated various artificial intelligence models to monitor, measure and optimize the projected growth by applying this design. Other research on the area was limited to projecting the future of Amman as it is an urbanized distressed city.

The purpose of this paper is to examine the determinants of local public health expenditure in a decentralized health system, taking into account the electoral calendar and the effect of central and local elections, besides spatial interaction among municipalities and political alignment. The authors state that the expenditure in public health at the local level is positively influenced by vicinity and by elections calendar.

The authors performed a Spatial Durbin Model with a balanced panel using the data from 399 Brazilian municipalities from 2005 to 2012. The authors use a distance-based spatial matrix, whose choose was based on simplicity and relevance of Moran’s I and Geary’s C coefficients for spatial autocorrelation. The authors also cluster the data in the estimations, according to the distribution of regional facilities in the entire period and considering the occurrence of regionalization in public health services.

The empirical contribution lies in four issues: first, the authors demonstrate a positive spatial effect in the public health expenditure. Second, the estimations show that election-year shifts public spent, as a response for vote-seeking incumbents’ behavior. Third, reelected mayors increase local public health allocations, as well as single candidates and incumbents from the same party of central governments. Finally, populational concentration directly decreases health expenditure (even if those municipalities represent a lower unit cost of acquiring votes, the optimization of public health infrastructure and mobility in achieving public health services negatively affect health spent).

This study supports the statement that public health spent at local level is positively influenced by vicinity and by occurrence of elections.