Urban Development Management Research Articles

Managing Smart City development using citizen feedback: transforming opinions into a multi-criteria tool for evaluation and validation of city policies

In the last decade, research in the field of smart cities has expanded from purely technological aspects to include the areas of management development, urban planning and social sciences. In general, the discussion focuses on how the use of technology contributes to the development of the city, urban space and improving the quality of decisions[1].The article offers a tool to enrich the urban development management system. It is argued that by developing appropriate scales, subjective views and perceptions of the citizen can be objectivized and, therefore, are very useful for managers and politicians.In this paper, the development process is carried out in several stages, using inductive and deductive methods. Following focus groups and interviewing representatives of the city authorities, a survey was conducted with the participation of almost a thousand city inhabitants from all Kazakhstan regions. The data were analyzed using IBM SPSS 24 and AMOS 20 tools.The study proposes a scale that includes statements structured in five identified dimensions: willingness to interact, expectation of improvements, willingness to use, concern about efficiency, concern about abuse. As the methodology is disclosed, important theoretical and managerial implications are discussed, the need for information flow management in the interests of participants in the implementation of Smart City is justified.

Feature Recognition of Urban Industrial Land Renewal Based on POI and RS Data: The Case of Beijing

Urban renewal has increasingly become a hot topic in international urban sustainable development management, and many countries have also carried out a lot of practice. However, there is still a lack of fast and effective methods for how quickly identifying the spatial characteristics of urban renewal to dynamically grasp the renewal effect. The purpose of this study is to identify the renewal characteristics of urban industrial land based on the POI (Points of Interest) data and RS data of the Internet map, and to provide an innovative method for better understanding the renewal effect of urban industrial land and its spatiotemporal evolution characteristics. The results show that: 1) Since the decentralization of non-capital functions in Beijing, industrial development has spread from a high degree of agglomeration to the whole area. The number of high-density areas has decreased from nine to five, and the number of medium-density areas has increased significantly.2) Land-use types in the six districts of Beijing have changed, warehousing and logistics land and industrial land have been reduced greatly, and the number and area of park green space have greatly increased.3) The level of matching between RS image interpretation and POI data is uneven. RS interpretation is accurate for large-scale feature recognition, and POI data are sensitive to small-scale industries. In conclusion, In the process of identifying the renewal feature of urban industrial land, POI and RS data can respectively obtain certain results. The integration of POI and RS can better identify the temporal and spatial changes of the industry.

Integrating Sponge City Requirements into the Management of Urban Development Land: An Improved Methodology for Sponge City Implementation

Sponge city planning aims to manage urban development land to prevent flooding and to support the achievement of water resource protection objectives. In this study, from the perspective of rainfall management demand and ability, we present an improved planning method, including two calculation models, aimed at determining the VCRAR (volume capture ratio of annual rainfall) and then integrating VCRAR requirements into the management of urban development land more accurately and objectively, while simultaneously considering the rainfall condition and urban planning attributes to support the implementation of sponge city planning. Compared to the current method, the VCRAR calculation model greatly improves the accuracy of the VCRAR for various space scales, and the conversion model solves the fundamental problem that urban land indicators corresponding to the VCRAR are difficult to calculate objectively and accurately. Moreover, this methodology can achieve a reasonable tradeoff between the development of individual districts and the environmental protection of the whole urban watershed, which allows a poetic vision to be turned into executable planning and design. The results of the application of this methodology in a case study in Jizhou, China, show that the improved method can make land utilization, development period and natural conditions more integrated and scientifically involved in the indicator calculation. The results also quantitatively show that the capacity of volume capture inside the site for one district increases as its green space ratio increases, and it decreases with an increase in the transformation difficulty for stormwater management facilities, when restricted by the investment and available space.

Post-Socialist city in the mirror of global governance transformation

In the last thirty years, questions about the future of urban development have been discussed in the world. Global agents and organizations (the World Bank, the UN) set the vectors of planning policy and set goals for the development of cities around the world. The role of the state in the management of urban development is changing. There is a transition from state regulation to "management", which includes new subjects in the management process: investors, businesses, citizens. The transformation of management models is explained by economic globalization, the emergence of a global economic sector. Cities are starting to compete with each other and focus on attracting investment. Governments of different countries are looking for suitable ways to manage cities. In this context, post-socialist cities that are facing the consequences of the transition from socialism to the market are of particular interest. The object of this research is the transformation in the management of a post-socialist city in the context of global changes. The subject is the ways of conceptualizing transformation in the management of a post–socialist city. Tasks include: 1) identification of the main approaches to the analysis of transformations in the management of a post-socialist city under the influence of global changes; 2) description of the conceptual discussion around the concept of "post-socialist city" and the theoretical possibilities of its application; 3) discussion of these approaches in relation to the study of post-Soviet cities. The article presents an overview of theoretical and methodological concepts describing global transformations in city management. The scientific novelty consists in the expansion of the categorical apparatus for describing and conceptualizing the transformation in the management of post-socialist cities in the context of globalization, the ways for describing the transformation in the management of post-Soviet cities are outlined.

Urbanization and sustainable development for inclusiveness using ICTs

The arrival of information and communication technology (ICT) as well as the deployments of free and open-source software (FOSS) have brought hope to developing countries that the use of enabling technologies potentially mitigates the impact of global environmental and socio-economic crises, and it drive radical changes in a user's skills or culture. In 2019, with widespread territorial disparities, approximately 53.6% people were connected to the Internet worldwide. The majority of the offline user lives in the least developed countries, and only 19% of them use the internet, compared to 87% in developed nations. Sustainable development depends on successful management of open and inclusive urban development, especially in low-income and middle-income countries, where the fastest urbanization is expected to occur by the year 2050. The application of ICT enhances the independence, dignity, and equal opportunities of all people, thereby promoting their integration into society. An inclusive approach-based citizen participation is extremely important for building an inclusive society. Furthermore, this study highlights the current issues and challenges in developing countries, as well as the role of ICT in promoting socio-economic development, where it can serve as a catalyst for the implementation of the concept of sustainable urbanization. Considering the emerging socio-technological aspect, a framework for a sustainable socio-technical ecosystem is presented here to achieve economic independence and empowerment.

Towards the Circular Soil Concept: Optimization of Engineered Soils for Green Infrastructure Application

At conventional construction sites, the removal of soil and other excavated materials causes enormous mass movement, with a significant climate impact and contribution to global CO2 release. This study aimed to generate a Circular Soil concept for reusing excavated materials by creating engineered soils for landscape construction at large building sites. Engineered soils act as a substitute for natural soils and fulfill vital technical and soil functions when installing an urban green infrastructure (GI). In a field study, the vegetation performance on engineered soils was evaluated to establish a methodological approach, to assess the applicability of the Circular Soil concept. First, the technical specifications (grain-size distribution) were modeled for intensive green roof and turfgrass applications. Then, the soil components were optimized, mixed, installed and tested for greenery purposes, focusing on plant growth performance indicators (vitality, projective cover ratio and grass-herb ratio) to assess the vegetation performance. The results showed that the engineered soils match the performance of the reference soil alternatives. In conclusion, the Circular Soil concept has a high potential to contribute considerably to sustainable on-site soil management and the circular economy. It can be applied on a larger scale for urban GI development and sustainable resources management in the landscaping and construction sector.

Urban Traffic Dynamics Prediction—A Continuous Spatial-temporal Meta-learning Approach

Urban traffic status (e.g., traffic speed and volume) is highly dynamic in nature, namely, varying across space and evolving over time. Thus, predicting such traffic dynamics is of great importance to urban development and transportation management. However, it is very challenging to solve this problem due to spatial-temporal dependencies and traffic uncertainties. In this article, we solve the traffic dynamics prediction problem from Bayesian meta-learning perspective and propose a novel continuous spatial-temporal meta-learner (cST-ML), which is trained on a distribution of traffic prediction tasks segmented by historical traffic data with the goal of learning a strategy that can be quickly adapted to related but unseen traffic prediction tasks. cST-ML tackles the traffic dynamics prediction challenges by advancing the Bayesian black-box meta-learning framework through the following new points: (1) cST-ML captures the dynamics of traffic prediction tasks using variational inference, and to better capture the temporal uncertainties within tasks, cST-ML performs as a rolling window within each task; (2) cST-ML has novel designs in architecture, where CNN and LSTM are embedded to capture the spatial-temporal dependencies between traffic status and traffic-related features; (3) novel training and testing algorithms for cST-ML are designed. We also conduct experiments on two real-world traffic datasets (taxi inflow and traffic speed) to evaluate our proposed cST-ML. The experimental results verify that cST-ML can significantly improve the urban traffic prediction performance and outperform all baseline models especially when obvious traffic dynamics and temporal uncertainties are presented.

SUSTAINABLE DEVELOPMENT IN URBAN INDUSTRIALIZATION ERA (CASE STUDY BONTANG CITY)

Sustainable development has become the main indicator for all local governments to sharpening urban development management. By seeing the differences in economic, social, and environmental potential in urban areas in Indonesia, it has different opportunities and challenges to embody, thus this research aims to explore and discover concepts/patterns of sustainable development in Bontang City, East Kalimantan Province. The results of the study indicate that sustainable development has been constructed through collective collegial approaches, transparency, business, and direct involvement of the private sector and society to attain. So the concept not only improves community participation, but it has changed people's behavior were just as a consumer/an object before, then to be an actor.

A Pattern for Urban Development Integrated Management System by Urban Planning Approach (case study: Bandar Abbas)

Due to economic growth and demographic expansion in cities, cities face multitude of challenges. With the rising challenges, there is a need for integrated urban management approach to manage public affairs in the cities. This approach will provide a holistic solution to these problems’ cities are facing. The economic growth has created social, environmental and societal changes in the cities. To solve these problems new tools, technology and policies are required to coordinate and integrate environmental, economic, social factors in relation with urban areas to study and manage growth and solve potential problems.The present study is aimed to investigate the current model of integrated urban development management system from the perspective of urban planning in Bandar Abbas in a Descriptive-Analytical Method. The data of this research have been collected from various sources (library, documentary, electronic, various field sources). The sample size is 40, and the sample size is collected from urban planning experts based out of Bandar Abbas and Tehran. Analysis of qualitative results has been performed using the SWOT model. Based on the results, 14 various factors were identified as strengths, 38 factors as weaknesses, 9 factors as opportunities and 20 factors as threats. According to the results, the most important strength is, citizens increasing expectations from municipality to provide services. The important weakness is citizens not having knowledge and duties as a citizen, municipalities and neighboring countries. The most important threat is the influence of ethnic subcultures in the city and cultural conflicts. According to this analysis, the most important priority is to develop and set up good urban management practices and moving towards an integrated approach of urban planning.

Preferences for Infrastructure and Determinants of Decision to Live in a Makeshift House in Informal Settlements

The upgrade paradigm has been a widely accepted solution to informal settlements. However, implementing an effective upgrade program has been challenging for governments of most developing countries. This paper reports a study which examined informal settlement residents’ preferences for infrastructure provided by an upgrade project and factors influencing their decision to live in a makeshift house. It also examined how an informal settlement upgrade project can be implemented in an effective manner. The data originated from interviews with 231 residents of informal settlements in Port Moresby and was analyzed using mixed methods approach which includes descriptive statistics, qualitative content analysis and binary logistic regression model. The results show that all the residents would support the upgrade project and would pay for service charges associated with infrastructure and services provided by the project. Piped borne water and health care facility were the most preferred. In order for the upgrade project to be successful, residents should be fully involved in planning and implementing the project. Results from the logistic model revealed that decision to live in a makeshift house is influenced by factors such as house and land ownership, frequency of crime in the area, household size, occupation, access to toilet and number of years lived in informal settlement. There is a need to develop an effective mechanism for restricting the emergence of new informal settlements. The findings contribute to urban development planning by providing guidelines for upgrading informal settlements in an effective and efficient manner. The findings will be useful for policy makers, planners and urban development managers in the informal settlement upgrade process.

Research on Urban Land Use Change in Ha Noi, Viet Nam Using Remote Sensing and GIS for Planning Oriented Work

Currently, 55% of the world’s population lives in urban areas, this proportion is expected to increase to 68% by 2050. In the next 30 years, a large amount of the world's population is predictably concentrated in urban areas in the developing world. Ha Noi is the capital and largest city of Viet Nam which has the average growth rate of approximately 3% per year. Urban developmentmanagement has become an important issue in Viet Nam since the negative impacts of the urban sprawl on the environmental sustainability, life quality has been increasing as well. Hence, urban planning and management would be pivotal for creating the effective framework conditions for a sustainable development. The objective of our study is to explore the urban growth of Ha Noi using the Landsat images from 1975 to 2020 compared to the city planning. The volatility analysis information from classified urbanland maps is considered supportive for urban management and planning oriented work. In addition, the remote sensing data analysis is a useful tool to support planners, managers for urban management and decision. This study results showed the urban land area in study site city has been growing about 3 times and the largest rate (4-6 times) for the Dong Anh, Tu Liem, Gia Lam and smallest rate (10-25%) for Ba Dinh and Hai Ba Trung districts.

Spatio-Temporal Patterns of CO2 Emissions and Influencing Factors in China Using ESDA and PLS-SEM

Controlling carbon dioxide (CO2) emissions is the foundation of China’s goals to reach its carbon peak by 2030 and carbon neutrality by 2060. This study aimed to explore the spatial and temporal patterns and driving factors of CO2 emissions in China. First, we constructed a conceptual model of the factors influencing CO2 emissions, including economic growth, industrial structure, energy consumption, urban development, foreign trade, and government management. Second, we selected 30 provinces in China from 2006 to 2019 as research objects and adopted exploratory spatial data analysis (ESDA) methods to analyse the spatio-temporal patterns and agglomeration characteristics of CO2 emissions. Third, on the basis of 420 data samples from China, we used partial least squares structural equation modelling (PLS-SEM) to verify the validity of the conceptual model, analyse the reliability and validity of the measurement model, calculate the path coefficient, test the hypothesis, and estimate the predictive power of the structural model. Fourth, multigroup analysis (MGA) was used to compare differences in the influencing factors for CO2 emissions during different periods and in various regions of China. The results and conclusions are as follows: (1) CO2 emissions in China increased year by year from 2006 to 2019 but gradually decreased in the eastern, central, and western regions. The eastern coastal provinces show spatial agglomeration and CO2 emission hotspots. (2) Confirmatory analysis showed that the measurement model had high reliability and validity; four latent variables (industrial structure, energy consumption, economic growth, and government management) passed the hypothesis test in the structural model and are the determinants of CO2 emissions in China. Meanwhile, economic growth is a mediating variable of industrial structure, energy consumption, foreign trade, and government administration on CO2 emissions. (3) The calculated results of the R2 and Q2 values were 76.3% and 75.4%, respectively, indicating that the structural equation model had substantial explanatory and high predictive power. (4) Taking two development stages and three main regions as control groups, we found significant differences between the paths affecting CO2 emissions, which is consistent with China’s actual development and regional economic pattern. This study provides policy suggestions for CO2 emission reduction and sustainable development in China.

A GIS application supporting urban management towards the attainment of the smart city development goals in Thai Nguyen city

Rapid urbanization and urban development must meet the requirements of smart green growth and sustainable development of Vietnam. Hence, these are the top challenges to be tackled by urban managers. Therefore, urban management databases must be accurate, relevant, and transparent. At the same time, simple access databases will enable users to quickly find the information they need. A combination of attribute data and spatial data is a smart and effective tool. Realistic data, integrated with the Internet of Things, or IoT, makes breakthroughs in the management of urban development by enabling managers and citizens to access real-time data and make effective urban management decisions. Within the framework of this study, a geodatabase was compiled to support effective urban management and information accessibility for the general public in Thai Nguyen city. The database was made in VB.net and later integrated into the Geographic Information System (GIS) to enable users to access, search, analyze, process, and manage the database information. The database will support decision making by urban managers. The co-authors’ findings, on factors affecting urban management, show that local management does limit violations of urban construction regulations. This model will address the main factors affecting urban management (Community Participation, Information Technology, Law and Communication) and improve the urban management efficiency.

Urban Landscape Information Atlas and Model System Based on Remote Sensing Images

City landscape is an element of city image, and city landscape logo should also belong to the entire system of the city image logo. Since the reform and opening up, China’s economic construction industry has attracted worldwide attention, and the improvement of people’s living standards has led to the continuous development of urban construction. The original urban style is gradually replaced by high-rise buildings, the differences between cities are getting smaller and smaller, and the people living in them have gradually abandoned the inheritance of various cultures and customs. This paper aims to study the urban landscape information map and its model system based on remote sensing images. With the support of remote sensing image technology and geographic information system platform, the urban landscape information map model system is developed, which can vividly reflect the changes in the urban landscape pattern. The urban landscape information map is used to display and reveal the spatial evolution of the urban landscape in the process of urban development. Result of empirical analysis: it summarizes the methods of geoscience information map and urban landscape information map and establishes the goal and content of researching urban landscape information map. And it provides a basis for solving the problems of urban development and urban management. In 2021, Shanghai’s urban areas have occupied more than 80%. It is conceivable that the area of arable land must be very small, but the area of green land still accounts for 40%; compared with last year, it is still an increase of 6%.

Assessing the Ecological Value of an Urban Forest Park: A Case Study of Sinhua Forest Park in Taiwan

Urban forests offer multiple functions: they can balance negative effects from the environment and provide the public with a place for leisure and recreation. Hence, urban forests are crucial to urban ecology and have been widely studied. In addition, relevant study results were applied for policymaking in urban development and forest park management. This study evaluated the ecological value of the Sinhua Forest Park and examined whether the socioeconomic background of participants influences their willingness to pay (WTP) for ecological conservation. Questionnaires were distributed to visitors in the Sinhua Forest Park in Tainan, Taiwan, and the payment card format of the contingent valuation method was employed to evaluate the ecological value. The results showed that the visitors had an annual WTP of $22.01 per person. However, when samples with protest responses were excluded, the WTP rose to $24.58. By considering the total number of visitors of a year, the total ecological value was $1,426,964.14/year and reached $1,593,257.31/year after excluding the protest samples. This study also analyzed participants’ within-variable socioeconomic background (e.g., gender and education) and discovered that male participants who are aged 60 years or older, with an education level of senior/vocational high school, and those who visited green spaces two to three times per week presented a high WTP score on average. A Tobit regression model was employed for examination, and the results indicated that participants’ education and frequency of visiting green spaces significantly influenced their WTP for the ecological conservation of the Sinhua Forest Park.

Flood‐prone area mapping using GIS‐based analytical hierarchy frameworks for Ibadan city, Nigeria

AbstractFlood is one of the highly pronounced ruinous naturally occurring environmental hazards in which human lives and properties are gravely endangered. This study assessed areas prone to flood in Ibadan City, Nigeria. The study applied two multi‐criteria analysis approach—Analytical Hierarchy Process (AHP) and the Fuzzy Analytical Hierarchy Process (FAHP) with the aid of GIS. Ten geomorphological physical characteristics agreed upon by experts as the major factors influencing the susceptibility of an area to floods formed the criteria maps used in this study. The natural breaks and geometrical interval clustering techniques were utilised to group the final flood‐prone area maps into five categories—very low, low, moderate, high, and very high. The result indicated that over 50% of the study area either have low or moderate susceptibility to flooding. The clustering techniques showed some slight differences in the flood classifications where natural breaks consistently grouped more areas into the “very high” category and relatively fewer areas to “very low” category in comparison to the geometrical interval technique. Overall, at least 451 km2 (about 15% of Ibadan) is highly or very highly prone to floods, and these areas are mainly concentrated in the urban and semi‐urban regions of the study area. The findings and maps developed in this study would adequately serve as a planning guide for the policymakers on urban development and flood risk management to achieve sustainable development and management.

Innovative Methods in Sustainable Urban Development and Water Management

Innovative methods presently affect all sectors of the national economy contributing to the progress and overall development of the economy, and the living standard worldwide. Innovations are equally necessary both in the private and in public sectors therefore, the original innovative ideas in each sector are greatly accepted. Similar concept is significant for companies dealing with urban water management. New methods are available mainly for capturing and reusing of rainwater in urban areas which leads to a positive impact on sustainable urban water management regarding today's water scarcity problems. This article describes some of the most popular innovative methods and examples used for rainwater harvesting, recycling and reuse. As a result, the evaluation of the most suitable water harvesting techniques related to sustainable water management, and their application in the city of Brno in Czech Republic are described.

Identification and analysis of urban functional area in Hangzhou based on OSM and POI data.

The accurate identification of urban functional areas is of great significance for optimizing urban spatial structure, rationally allocating spatial elements, and promoting the sustainable development of the city. This paper proposes a method to precisely identify urban functional areas by coupling Open Street Map (OSM) and Point of Interest (POI) data. It takes the central urban area of Hangzhou as a case study to analyze the spatial distribution characteristics of the functional areas. The results show that: (1) The central urban areas of Hangzhou are divided into 21 functional areas (6 single functional areas, 14 mixed functional areas and 1 comprehensive functional area). (2) The single functional areas and the mixed functional areas show the geographical distribution characteristics of the looping stratification, which means “Core-periphery” differentiation is obvious, and the comprehensive functional area is relatively scattered. (3) The mixed degree of regional function with ecological function and production function is low while comprehensive functional areas are usually associated with higher potential and vitality. (4) The identification results are in great agreement with the actual situation of Hangzhou central urban area, and the method is feasible. Therefore, this paper can provide a reference for urban development planning and management.

Unveiling transit mobility structure towards sustainable cities: An integrated graph embedding approach

Detecting urban mobility structure, i.e., segmenting urban areas into disjoint clusters with similar mobility patterns, can facilitate our understanding of how a city is organized and how different parts of a city interact with each other, which underpin informed decision-making in achieving sustainable urban transportation development and resilient society. In this study, we propose to tackle a novel transit mobility structure detection problem, which hinges on high-level mobility patterns that characterize collective movement dynamics across the study region. To this end, we propose a machine learning-based approach to discover meaningful urban mobility structure using big transit data. We contend that both transit mobility patterns and local urban function information should be considered during the detection of transit mobility structure. By integrating different sources of urban data, we model the network of transit mobility as an attributed graph: local static urban functions are described by attributed features for graph nodes whereas travel dynamics are captured via a transit mobility pattern matrix. Similarities of both attributed features and transit mobility patterns are jointly embedded to derive compact low-dimensional vector representations via graph auto-encoder. Mobility structure is then extracted using unsupervised clustering and gap statistics. The proposed approach is capable of synthesizing both mobility and static information in a data-driven manner, preserving original urban topological structure and resident movement dynamics. The proposed approach was evaluated using real-world transit data collected in Shenzhen City, China. Experimental results and analyses demonstrate that the proposed approach has the applicability of unveiling meaningful transit mobility structure in large metropolitan areas. The detected mobility community maps present a holistic overview of public transit movement structure, enabling decision makers to make informed decisions on sustainable urban development and transit management.

A four-stage approach to re-associating fragmented and commingled human remains

Bioarchaeological and forensic anthropological methods are limited in their ability to re-associate human skeletal remains that have been both fragmented and commingled. Although many methods for individualizing commingled remains exist, they are rendered ineffective when the level of fragmentation is high. In these contexts, human remains are often approached similarly to faunal assemblages, regarded as sets of fragmented elements rather than as groups of fragments representing an individual. This paper introduces a new, four-stage approach to identifying discrete individuals from unintentionally fragmented and commingled human remains and salvaging information from highly disturbed cemetery contexts. These stages include documentation, grouping, analysis, and evaluation, each incorporating multiple methods so as to be applicable to a wide variety of assemblages or data availability. Through this process, quantitative analyses are used to evaluate qualitative groupings. This method is applicable to skeletal collections of varying levels of preservation. To demonstrate its application, we apply this methodology to an Early Neolithic (7560–6660 HPD cal. BP) hunter-gatherer cemetery, Moty-Novaia Shamanka (MNS), located in the Cis-Baikal region of Siberia, Russia. MNS was destroyed in the 1990s for urban development and flood management, leaving the ancient skeletal remains severely fragmented and commingled. Our results identified five discrete individual groupings from 1245 human bone fragments, and eight further groupings of related fragments. Through a process of elimination, it was determined that these groupings represented at least seven distinct people. The methodological approach of this study challenges our perception of the informative value of fragmented and commingled human remains and provides an example of how future studies could approach individualization in situations where most context has been lost.