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26 pages, 2377 KiB

Open AccessArticle

A Pricing Model for Urban Rental Housing Based on Convolutional Neural Networks and Spatial Density: A Case Study of Wuhan, China

by Hang Shen, Lin Li, Haihong Zhu and Feng Li

ISPRS Int. J. Geo-Inf. 2022, 11(1), 53; https://doi.org/10.3390/ijgi11010053 - 11 Jan 2022

Cited by 9 | Viewed by 3167

Abstract

With the development of urbanization and the expansion of floating populations, rental housing has become an increasingly common living choice for many people, and housing rental prices have attracted great attention from individuals, enterprises and the government. The housing rental prices are principally [...] Read more.

With the development of urbanization and the expansion of floating populations, rental housing has become an increasingly common living choice for many people, and housing rental prices have attracted great attention from individuals, enterprises and the government. The housing rental prices are principally estimated based on structural, locational and neighborhood variables, among which the relationships are complicated and can hardly be captured entirely by simple one-dimensional models; in addition, the influence of the geographic objects on the price may vary with the increase in their quantities. However, existing pricing models usually take those structural, locational and neighborhood variables as one-dimensional inputs into neural networks, and often neglect the aggregated effects of geographical objects, which may lead to fluctuating rental price estimations. Therefore, this paper proposes a rental housing price model based on the convolutional neural network (CNN) and the synthetic spatial density of points of interest (POIs). The CNN can efficiently extract the complex characteristics among the relevant variables of housing, and the two-dimensional locational and neighborhood variables, based on the synthetic spatial density, effectively reflect the aggregated effects of the urban facilities on rental housing prices, thereby improving the accuracy of the model. Taking Wuhan, China, as the study area, the proposed method achieves satisfactory and accurate rental price estimations (coefficient of determination (R²) = 0.9097, root mean square error (RMSE) = 3.5126) in comparison with other commonly used pricing models. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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21 pages, 13545 KiB

Open AccessArticle

Commuter Mobility Patterns in Social Media: Correlating Twitter and LODES Data

by Andreas Petutschnig, Jochen Albrecht, Bernd Resch, Laxmi Ramasubramanian and Aleisha Wright

ISPRS Int. J. Geo-Inf. 2022, 11(1), 15; https://doi.org/10.3390/ijgi11010015 - 30 Dec 2021

Cited by 5 | Viewed by 3113

Abstract

The Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) are an important city planning resource in the USA. However, curating these statistics is resource-intensive, and their accuracy deteriorates when changes in population and urban structures lead to shifts in commuter patterns. Our study area [...] Read more.

The Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics (LODES) are an important city planning resource in the USA. However, curating these statistics is resource-intensive, and their accuracy deteriorates when changes in population and urban structures lead to shifts in commuter patterns. Our study area is the San Francisco Bay area, and it has seen rapid population growth over the past years, which makes frequent updates to LODES or the availability of an appropriate substitute desirable. In this paper, we derive mobility flows from a set of over 40 million georeferenced tweets of the study area and compare them with LODES data. These tweets are publicly available and offer fine spatial and temporal resolution. Based on an exploratory analysis of the Twitter data, we pose research questions addressing different aspects of the integration of LODES and Twitter data. Furthermore, we develop methods for their comparative analysis on different spatial scales: at the county, census tract, census block, and individual street segment level. We thereby show that Twitter data can be used to approximate LODES on the county level and on the street segment level, but it also contains information about non-commuting-related regular travel. Leveraging Twitter’s high temporal resolution, we also show how factors like rush hour times and weekends impact mobility. We discuss the merits and shortcomings of the different methods for use in urban planning and close with directions for future research avenues. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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20 pages, 5098 KiB

Open AccessArticle

Integration Development of Urban Agglomeration in Central Liaoning, China, by Trajectory Gravity Model

by Ruren Li, Shoujia Li and Zhiwei Xie

ISPRS Int. J. Geo-Inf. 2021, 10(10), 698; https://doi.org/10.3390/ijgi10100698 - 14 Oct 2021

Cited by 5 | Viewed by 1954

Abstract

Integration development of urban agglomeration is important for regional economic research and management. In this paper, a method was proposed to study the integration development of urban agglomeration by trajectory gravity model. It can analyze the gravitational strength of the core city to [...] Read more.

Integration development of urban agglomeration is important for regional economic research and management. In this paper, a method was proposed to study the integration development of urban agglomeration by trajectory gravity model. It can analyze the gravitational strength of the core city to other cities and characterize the spatial trajectory of its gravitational direction, expansion, etc. quantitatively. The main idea is to do the fitting analysis between the urban axes and the gravitational lines. The correlation coefficients retrieved from the fitting analysis can reflect the correlation of two indices. For the different cities in the same year, a higher value means a stronger relationship. There is a clear gravitational force between the cities when the value above 0.75. For the most cities in different years, the gravitational force between the core city with itself is increasing by years. At the same time, the direction of growth of the urban axes tends to increase in the direction of the gravitational force between cities. There is a clear tendency for the trajectories of the cities to move closer together. The proposed model was applied to the integration development of China Liaoning central urban agglomeration from 2008 to 2016. The results show that cities are constantly attracted to each other through urban gravity. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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20 pages, 6038 KiB

Open AccessArticle

Exploring the Influence Mechanism of Attractiveness on Wuhan’s Urban Commercial Centers by Modifying the Classic Retail Model

by Zhuoran Shan, Zhe Wu and Man Yuan

ISPRS Int. J. Geo-Inf. 2021, 10(10), 652; https://doi.org/10.3390/ijgi10100652 - 28 Sep 2021

Cited by 5 | Viewed by 2663

Abstract

The attractiveness of commercial centers is one of the core issues in urban and rural planning research. To deepen the theoretical understanding of attractiveness and optimize modeling, we empirically analyzed the factors and mechanisms influencing the attractiveness of Wuhan’s commercial centers by improving [...] Read more.

The attractiveness of commercial centers is one of the core issues in urban and rural planning research. To deepen the theoretical understanding of attractiveness and optimize modeling, we empirically analyzed the factors and mechanisms influencing the attractiveness of Wuhan’s commercial centers by improving the classic retail model and testing the age differentiation of mechanisms. The results indicate the following: (1) there is an obvious attractiveness gap in the commercial centers examined, and six have not met their planning expectations; (2) intensive and abundant shopping services, domestic services, sports and leisure services, and medical care services all promote attractiveness, but their impact on customers of different ages varies greatly. For young consumers, shopping services have the greatest effect on attractiveness, whereas for middle-aged and elderly consumers, sports and leisure services have the greatest effect; (3) the accumulation of length of development increases the likelihood of young people’s patronage, but the effect is weak; (4) traffic resistance shows a stable inhibitory effect, and middle-aged and elderly people are more sensitive to travel time than youth; (5) improving the retail model is effective, and the model is more powerful in explaining young consumers. This research also puts forward policy recommendations for the commercial centers’ industry configuration, new and old combinations, and traffic accessibility, and then proposes planning countermeasures for Wuhan’s city- and-county-level commercial center layout, local commercial land morphology organization, and the construction optimization of commercial centers that have not met expectations. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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24 pages, 3378 KiB

Open AccessArticle

Towards Culture-Aware Smart and Sustainable Cities: Integrating Historical Sources in Spatial Information Infrastructures

by Bénédicte Bucher, Carola Hein, Dorit Raines and Valérie Gouet Brunet

ISPRS Int. J. Geo-Inf. 2021, 10(9), 588; https://doi.org/10.3390/ijgi10090588 - 4 Sep 2021

Cited by 3 | Viewed by 3040

Abstract

This article addresses the integration of cultural perspectives in the smart city discourse and in the implementation of the UN Agenda 2030; it does so specifically with respect to land patterns and land use. We hope to increase the ability of relevant stakeholders, [...] Read more.

This article addresses the integration of cultural perspectives in the smart city discourse and in the implementation of the UN Agenda 2030; it does so specifically with respect to land patterns and land use. We hope to increase the ability of relevant stakeholders, including scientific communities working in that field, to handle the complexity of the current urban challenges. Culture is understood here in the broadest sense of the word, including the values and conceptualizations of the world, and the modes of technological creation and control of the environment. This concept of culture varies among stakeholders, depending, in particular, on their activities, on the place they live in, and also depending on their scientific background. We propose to complement existing targets that are explicitly related to culture in the UN and UNESCO agendas for 2030, and introduce a target of culture awareness for city information infrastructures. We show that, in the specific case of land patterns and land use, these new targets can be approached with historical data. Our analysis of the related core functionalities is based on interviews with practitioners, draws on insights from the humanities, and takes into account the readiness of the existing technologies. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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31 pages, 9866 KiB

Open AccessEditor’s ChoiceArticle

Automatic Delineation of Urban Growth Boundaries Based on Topographic Data Using Germany as a Case Study

by Oliver Harig, Robert Hecht, Dirk Burghardt and Gotthard Meinel

ISPRS Int. J. Geo-Inf. 2021, 10(5), 353; https://doi.org/10.3390/ijgi10050353 - 20 May 2021

Cited by 16 | Viewed by 5498

Abstract

Urban Growth Boundary (UGB) is a growth management policy that designates specific areas where growth should be concentrated in order to avoid urban sprawl. The objective of such a boundary is to protect agricultural land, open spaces and the natural environment, as well [...] Read more.

Urban Growth Boundary (UGB) is a growth management policy that designates specific areas where growth should be concentrated in order to avoid urban sprawl. The objective of such a boundary is to protect agricultural land, open spaces and the natural environment, as well as to use existing infrastructure and public services more efficiently. Due to the inherent heterogeneity and complexity of settlements, UGBs in Germany are currently created manually by experts. Therefore, every dataset is linked to a specific area, investigation period and dedicated use. Clearly, up-to-date, homogeneous, meaningful and cost-efficient delineations created automatically are needed to avoid this reliance on manually or semi-automatically generated delineations. Here, we present an aggregative method to produce UGBs using building footprints and generally available topographic data as inputs. It was applied to study areas in Frankfurt/Main, the Hanover region and rural Brandenburg while taking full account of Germany’s planning and legal framework for spatial development. Our method is able to compensate for most of the weaknesses of available UGB data and to significantly raise the accuracy of UGBs in Germany. Therefore, it represents a valuable tool for generating basic data for future studies. Application elsewhere is also conceivable by regionalising the employed parameters. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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19 pages, 3900 KiB

Open AccessArticle

Are Electric Vehicles Reshaping the City? An Investigation of the Clustering of Electric Vehicle Owners’ Dwellings and Their Interaction with Urban Spaces

by Jing Kang, Changcheng Kan and Zhongjie Lin

ISPRS Int. J. Geo-Inf. 2021, 10(5), 320; https://doi.org/10.3390/ijgi10050320 - 10 May 2021

Cited by 7 | Viewed by 4092

Abstract

With the rapid development of electric vehicles (EVs) around the world, debates have arisen with regard to their impacts on people’s lifestyles and urban space. Mining spatio-temporal patterns from increasingly smart city sensors and personal mobile devices have become an important approach in [...] Read more.

With the rapid development of electric vehicles (EVs) around the world, debates have arisen with regard to their impacts on people’s lifestyles and urban space. Mining spatio-temporal patterns from increasingly smart city sensors and personal mobile devices have become an important approach in understanding the interaction between human activity and urban space. In this study, we used location-based service data to identify EV owners and capture the distribution of home and charging stations. The research goal was to investigate that how the urban form in regions under rapid urbanization is driven by EV use, from a geographical perspective. Using a case study of the expanding metropolis of Beijing, GIS-based spatial statistical analysis was conducted to characterize the spatial-pattern of the homes of EV owners as well as their charging preferences. Our results indicate that the spatial clustering of the homes of EV owners in non-urban central areas—suburban areas—is significantly higher than that in urban central areas. According to the records of visits to charging stations, the spatial interaction distance between the dwellings of EV owners and their visits to charging stations exhibits significant distance attenuation characteristics. 88% of EV owners in this research travels within 40 km (Euclidean distance) between housing and charging stations. At the same time, there were significant differences in the spatial patterns between working days and non-working days which are affected by commuting activities. The three types of urban spatial interaction patterns were identified and categorized by visualization. This transformation to EV use in the city influences several aspects of people’s decisions and behaviors in life. Understanding the impacts will provide valuable information for the development of EVs and their implications in the electrification of transportation, smart planning, and sustainable urbanization. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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20 pages, 6485 KiB

Open AccessArticle

Learning from the Informality. Using GIS Tools to Analyze the Structure of Autopoietic Urban Systems in the “Smart Perspective”

by Valerio Di Pinto, Antonio M. Rinaldi and Francesco Rossini

ISPRS Int. J. Geo-Inf. 2021, 10(4), 202; https://doi.org/10.3390/ijgi10040202 - 25 Mar 2021

Cited by 4 | Viewed by 3566

Abstract

This paper explores the link between the current vision of the “smart city” and the notion of urban autopoiesis understood as self-organized/managed urban systems. It seeks to highlight how the use of GIS analysis, applied to the study of informal settlements, can provide [...] Read more.

This paper explores the link between the current vision of the “smart city” and the notion of urban autopoiesis understood as self-organized/managed urban systems. It seeks to highlight how the use of GIS analysis, applied to the study of informal settlements, can provide useful information to understand the smart city paradigm. The paper argues the key idea that a smart city should not be seen only as a high-tech urban environment because the transition to smartness will need major changes in its inner structure. Using a combination of quantitative and qualitative GIS analysis methods, this study examines the case of the BaSECo Compound, one of the densest informal settlements in Metro Manila (Philippines), with the aim of both generating a comprehensive morphological analysis of this dynamic urban area as well as contributing to the configurational theory of the smart city. The results suggest that the analysis of autopoietic urban systems could expand our understanding of how the structure of the city could evolve to accommodate the needs of its citizens and creating more resilient and inclusive communities. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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22 pages, 5778 KiB

Open AccessArticle

Artificial Neural Network Model Development to Predict Theft Types in Consideration of Environmental Factors

by Eunseo Kwon, Sungwon Jung and Jaewook Lee

ISPRS Int. J. Geo-Inf. 2021, 10(2), 99; https://doi.org/10.3390/ijgi10020099 - 22 Feb 2021

Cited by 4 | Viewed by 3515

Abstract

Crime prediction research using AI has been actively conducted to predict potential crimes—generally, crime locations or time series flows. It is possible to predict these potential crimes in detail if crime characteristics, such as detailed techniques, targets, and environmental factors affecting the crime’s [...] Read more.

Crime prediction research using AI has been actively conducted to predict potential crimes—generally, crime locations or time series flows. It is possible to predict these potential crimes in detail if crime characteristics, such as detailed techniques, targets, and environmental factors affecting the crime’s occurrence, are considered simultaneously. Therefore, this study aims to categorize theft by performing k-modes clustering using crime-related characteristics as variables and to propose an ANN model that predicts the derived categorizations. As the prediction of theft types allows people to estimate the features of the possibly most frequent thefts in random areas in advance, it enables the efficient deployment of police and the most appropriate tactical measures. Dongjak District was selected as the target area for analysis; thefts in the district showed four types of clusters. Environmental factors, representative elements affecting theft occurrence, were used as input data for a prediction model, while the factors affecting each cluster were derived through multiple linear regression analysis. Based on the results, input variables were selected for the ANN model training per cluster, and the model was implemented to predict theft type based on environmental factors. This study is significant for providing diversity to prediction methods using ANN. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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18 pages, 56610 KiB

Open AccessArticle

Independent Map Enhancement for a Spatial Road Network: Fundamental Applications and Opportunities

by Sultan Alamri

ISPRS Int. J. Geo-Inf. 2021, 10(1), 8; https://doi.org/10.3390/ijgi10010008 - 27 Dec 2020

Cited by 5 | Viewed by 3409

Abstract

In many developing cities, the improvement of transport infrastructure is usually accompanied by major road construction and maintenance. This paper presents approaches and opportunities using peer-to-peer updating to improve spatial road networks undergoing construction and maintenance, which in turn will improve traffic flow [...] Read more.

In many developing cities, the improvement of transport infrastructure is usually accompanied by major road construction and maintenance. This paper presents approaches and opportunities using peer-to-peer updating to improve spatial road networks undergoing construction and maintenance, which in turn will improve traffic flow and benefit cities overall. In many cities, the spatial road network requires maintenance, and these works often require traffic detours. With the current GPS (Global Positioning System) services, there is a noticeable delay in the updating of many spatial road networks. Thus, when a driver plans a trip to a certain location (such as Starbucks), his/her usual route may have changed, but the spatial road network in the GPS has not been updated. This can affect the user in many ways. For example, a trip that usually takes five minutes might now take half an hour, taking into account the additional time required to find alternative roads and possibly encountering more unexpected road closures, until the driver reaches his/her destination. This paper addresses this issue by proposing solutions that offer several advantages including a new peer-to-peer updating mechanism that helps to direct the driver to another route when road changes occur. Moreover, the peer-to-peer updating mechanism can enable the independent monitoring of road conditions and the updating of maps for newly-constructed roads, as well as the analysis of road congestions, traffic density, and people movements at certain times. Note that this work focuses on the conceptual ideas and approaches intended to improve independent maps, and the detailed algorithms have been left for future work. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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17 pages, 12526 KiB

Open AccessArticle

Research on Large-Scale Urban Shrinkage and Expansion in the Yellow River Affected Area Using Night Light Data

by Wenhui Niu, Haoming Xia, Ruimeng Wang, Li Pan, Qingmin Meng, Yaochen Qin, Rumeng Li, Xiaoyang Zhao, Xiqing Bian and Wei Zhao

ISPRS Int. J. Geo-Inf. 2021, 10(1), 5; https://doi.org/10.3390/ijgi10010005 - 24 Dec 2020

Cited by 20 | Viewed by 3907

Abstract

As the land use issue, caused by urban shrinkage in China, is becoming more and more prominent, research on urban shrinkage and expansion has become particularly challenging and urgent. Based on the points of interest (POI) data, this paper redefines the scope, quantity, [...] Read more.

As the land use issue, caused by urban shrinkage in China, is becoming more and more prominent, research on urban shrinkage and expansion has become particularly challenging and urgent. Based on the points of interest (POI) data, this paper redefines the scope, quantity, and area of natural cities by using threshold methods, which accurately identify the shrinkage and expansion of cities in the Yellow River affected area using night light data in 2013 and 2018. The results show that: (1) there are 3130 natural cities (48,118.75 km²) in the Yellow River affected area, including 604 shrinking cities (8407.50 km²) and 2165 expanding cities (32,972.75 km²). (2) The spatial distributions of shrinking and expanding cities are quite different. The shrinking cities are mainly located in the upper Yellow River affected area, except for the administrative cities of Lanzhou and Yinchuan; the expanding cities are mainly distributed in the middle and lower Yellow River affected area, and the administrative cities of Lanzhou and Yinchuan. (3) Shrinking and expanding cities are typically smaller cities. The research results provide a quick data supported approach for regional urban planning and land use management, for when regional and central governments formulate the outlines of urban development monitoring and regional planning. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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22 pages, 5948 KiB

Open AccessArticle

Rural–Urban Transition of Hanoi (Vietnam): Using Landsat Imagery to Map Its Recent Peri-Urbanization

by Giovanni Mauro

ISPRS Int. J. Geo-Inf. 2020, 9(11), 669; https://doi.org/10.3390/ijgi9110669 - 12 Nov 2020

Cited by 11 | Viewed by 5841

Abstract

The current trend towards global urbanization presents new environmental and social challenges. For this reason, it is increasingly important to monitor urban growth, mainly in those regions undergoing the fastest urbanization, such as Southeast Asia. Hanoi (Vietnam) is a rapidly growing medium-sized city: [...] Read more.

The current trend towards global urbanization presents new environmental and social challenges. For this reason, it is increasingly important to monitor urban growth, mainly in those regions undergoing the fastest urbanization, such as Southeast Asia. Hanoi (Vietnam) is a rapidly growing medium-sized city: since new economic policies were introduced in 1986, this area has experienced a rapid demographic rise and radical socio-economic transformation. In this study, we aim to map not only the recent urban expansion of Hanoi, but also of its surroundings. For this reason, our study area consists of the districts within a 30km radius of the city center. To analyze the rural–urban dynamics, we identified three hypothetical rings from the center: the core (within a 10 km radius), the first ring (the area between 10 and 20 km) and, finally, the outer zone (over 20 km). To map land use/land cover (LULC) changes, we classified a miniseries of Landsat images, collected approximately every ten years (1989, 2000, 2010 and 2019). To better define the urban dynamics, we then applied the following spatial indexes: the rate of urban expansion, four landscape metrics (the number of patches, the edge length, the mean patch area and the largest patch index) and the landscape expansion index. The results show how much the city’s original shape has changed over the last thirty years: confined for hundreds of years in a limited space on the right bank of the Red River, it is now a fringed city which has developed beyond the river into the surrounding periurban areas. Moreover, the region around Hanoi is no longer solely rural: in just thirty years, urbanization has converted this territory into an industrial and commercial region. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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27 pages, 4612 KiB

Open AccessEditor’s ChoiceArticle

Supporting Policy Design for the Diffusion of Cleaner Technologies: A Spatial Empirical Agent-Based Model

by Caterina Caprioli, Marta Bottero and Elena De Angelis

ISPRS Int. J. Geo-Inf. 2020, 9(10), 581; https://doi.org/10.3390/ijgi9100581 - 1 Oct 2020

Cited by 14 | Viewed by 3497

Abstract

Renewable energy resources and energy-efficient technologies, as well as building retrofitting, are only some of the possible strategies that can achieve more sustainable cities and reduce greenhouse gas emissions. Subsidies and incentives are often provided by governments to increase the number of people [...] Read more.

Renewable energy resources and energy-efficient technologies, as well as building retrofitting, are only some of the possible strategies that can achieve more sustainable cities and reduce greenhouse gas emissions. Subsidies and incentives are often provided by governments to increase the number of people adopting these sustainable energy efficiency actions. However, actual sales of green products are currently not as high as would be desired. The present paper applies a hybrid agent-based model (ABM) integrated with a Geographic Information System (GIS) to simulate a complex socio-economic-architectural adaptive system to study the temporal diffusion and the willingness of inhabitants to adopt photovoltaic (PV) systems. The San Salvario neighborhood in Turin (Italy) is used as an exemplary case study for testing consumer behavior associated with this technology, integrating social network theories, opinion formation dynamics and an adaptation of the theory of planned behavior (TPB). Data/characteristics for both buildings and people are explicitly spatialized with the level of detail at the block scale. Particular attention is given to the comparison of the policy mix for supporting decision-makers and policymakers in the definition of the most efficient strategies for achieving a long-term vision of sustainable development. Both variables and outcomes accuracy of the model are validated with historical real-world data. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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26 pages, 44915 KiB

Open AccessEditor’s ChoiceArticle

Emergency Department Overcrowding: A Retrospective Spatial Analysis and the Geocoding of Accesses. A Pilot Study in Rome

by Cristiano Pesaresi, Giuseppe Migliara, Davide Pavia and Corrado De Vito

ISPRS Int. J. Geo-Inf. 2020, 9(10), 579; https://doi.org/10.3390/ijgi9100579 - 30 Sep 2020

Cited by 6 | Viewed by 5918

Abstract

The overcrowding of first aid facilities creates considerable hardship and problems which have repercussions on patients’ wellbeing, the time needed for a diagnosis, and on the quality of the assistance. The basic objective of this contribution, based on the data collected by the [...] Read more.

The overcrowding of first aid facilities creates considerable hardship and problems which have repercussions on patients’ wellbeing, the time needed for a diagnosis, and on the quality of the assistance. The basic objective of this contribution, based on the data collected by the Hospital Policlinico Umberto I in Rome (Lazio region, Italy), is to carry out a territorial screening of the municipality using GIS applications and spatial analyses aimed at reducing—in terms of triage—code white (inappropriate) attendances, after having identified the areas of greatest provenance of improperly used emergency room access. Working in a GIS environment and using functions for geocoding, we have tested an experimental model aimed at giving a close-up geographical-sanitary look at the situation: recognizing the territorial sectors in Rome which contribute to amplifying the Policlinico Umberto I emergency room overcrowding; leading up to an improvement of the situation; promoting greater awareness and knowledge of the services available on the territory, a closer relationship between patient and regular doctor (general practitioner, GP) or Local Healthcare Unit and a more efficient functioning of the emergency room. In particular, we have elaborated a “source” map from which derive all the others and it is a dot map on which all the codes white have been geolocalized on a satellite image through geocoding. We have produced three sets made up of three digital cartographic elaborations each, constructed on the census sections, the census areas and the sub-municipal areas, according to data aggregation, for absolute and relative values, and using different templates. Finally, following the same methodology and steps, we elaborated another dot map about all the codes red to provide another kind of information and input for social utility. In the near future, this system could be tested on a platform that spatially analyzes the emergency department (ED) accesses in near-real-time in order to facilitate the identification of critical territorial issues and intervene in a shorter time to regulate the influx of patients to the ED. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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16 pages, 12850 KiB

Open AccessArticle

Mapping Brick Kilns to Support Environmental Impact Studies around Delhi Using Sentinel-2

by Prakhar Misra, Ryoichi Imasu, Sachiko Hayashida, Ardhi Adhary Arbain, Ram Avtar and Wataru Takeuchi

ISPRS Int. J. Geo-Inf. 2020, 9(9), 544; https://doi.org/10.3390/ijgi9090544 - 11 Sep 2020

Cited by 18 | Viewed by 7733

Abstract

Cities lying in the Indo-Gangetic plains of South Asia have the world’s worst anthropogenic air pollution, which is often attributed to urban growth. Brick kilns, facilities for producing fired clay-bricks for construction are often found at peri-urban region of South Asian cities. Although [...] Read more.

Cities lying in the Indo-Gangetic plains of South Asia have the world’s worst anthropogenic air pollution, which is often attributed to urban growth. Brick kilns, facilities for producing fired clay-bricks for construction are often found at peri-urban region of South Asian cities. Although brick kilns are significant air pollutant emitters, their contribution in under-represented in air pollution emission inventories due to unavailability of their distribution. This research overcomes this gap by proposing publicly available remote sensing dataset based approach for mapping brick-kiln locations using object detection and pixel classification. As brick kiln locations are not permanent, an open-dataset based methodology is advantageous for periodically updating their locations. Brick kilns similar to Bull Trench Kilns were identified using the Sentinel-2 imagery around the state of Delhi in India. The unique geometric and spectral features of brick kilns distinguish them from other classes such as built-up, vegetation and fallow-land even in coarse resolution imagery. For object detection, transfer learning was used to overcome the requirement of huge training datasets, while for pixel-classification random forest algorithm was used. The method achieved a recall of 0.72, precision of 0.99 and F1 score of 0.83. Overall 1564 kilns were detected, which are substantially higher than what was reported in an earlier study over the same region. We find that brick kilns are located outside urban areas in proximity to outwardly expanding built-up areas and tall built structures. Duration of brick kiln operation was also estimated by analyzing the time-series of normalized difference vegetation index (NDVI) over the brick kiln locations. The brick kiln locations can be further used for updating land-use emission inventories to assess particulate matter and black carbon emissions. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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20 pages, 4061 KiB

Open AccessArticle

Spatial Mismatch between the Supply and Demand of Urban Leisure Services with Multisource Open Data

by Yue Deng, Jiping Liu, An Luo, Yong Wang, Shenghua Xu, Fu Ren and Fenzhen Su

ISPRS Int. J. Geo-Inf. 2020, 9(8), 466; https://doi.org/10.3390/ijgi9080466 - 22 Jul 2020

Cited by 9 | Viewed by 4422

Abstract

Understanding the balance between the supply and demand of leisure services (LSs) in urban areas can benefit urban spatial planning and improve the quality of life of residents. In cities in developing countries, the pursuit of rapid economic growth has ignored residents’ demand [...] Read more.

Understanding the balance between the supply and demand of leisure services (LSs) in urban areas can benefit urban spatial planning and improve the quality of life of residents. In cities in developing countries, the pursuit of rapid economic growth has ignored residents’ demand for LSs, thereby leading to a high demand for and short supply of these services. However, due to the lack of relevant research data, few studies have focused on the spatial mismatch in the supply and demand of LSs in urban areas. As typical representatives of multisource geographic data, social sensing data are readily available at various temporal and spatial scales, thus making social sensing data ideal for quantitative urban research. The objectives of this study are to use openly accessible datasets to explore the spatial pattern of the supply and demand of LSs in urban areas and then to depict the relationship between the supply and demand by using correlation analysis. Therefore, taking Beijing, China, as an example, the LS supply index (SI) and societal needs index (SNI) are proposed based on open data to reflect the supply and demand of LSs. The results show that the spatial distribution of the LS supply and demand in Beijing varies with a concentric pattern from the urban center to suburban areas. There is a strong correlation between the supply and demand of commercial and multifunctional services in Chaoyang, Fengtai, Haidian and Shijingshan, but there is no obvious correlation between the supply and demand of ecological and cultural services in Beijing. Especially in Dongcheng and Xicheng, there is no obvious correlation between the supply and demand of all services. The proposed approach provides an effective urban LS supply and demand evaluation method. In addition, the research results can provide a reference for the construction of “happy cities” in China. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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21 pages, 7559 KiB

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Spatiotemporal Variation of Urban Heat Islands for Implementing Nature-Based Solutions: A Case Study of Kurunegala, Sri Lanka

by Manjula Ranagalage, Sujith S. Ratnayake, DMSLB Dissanayake, Lalit Kumar, Hasula Wickremasinghe, Jagathdeva Vidanagama, Hanna Cho, Susantha Udagedara, Keshav Kumar Jha, Matamyo Simwanda, Darius Phiri, ENC Perera and Priyantha Muthunayake

ISPRS Int. J. Geo-Inf. 2020, 9(7), 461; https://doi.org/10.3390/ijgi9070461 - 21 Jul 2020

Cited by 31 | Viewed by 6590

Abstract

Changes in the urban landscape resulting from rapid urbanisation and climate change have the potential to increase land surface temperature (LST) and the incidence of the urban heat island (UHI). An increase in urban heat directly affects urban livelihoods and systems. This study [...] Read more.

Changes in the urban landscape resulting from rapid urbanisation and climate change have the potential to increase land surface temperature (LST) and the incidence of the urban heat island (UHI). An increase in urban heat directly affects urban livelihoods and systems. This study investigated the spatiotemporal variation of the UHI in the Kurunegala urban area (KUA) of North-Western Province, Sri Lanka. The KUA is one of the most intensively developing economic and administrative capitals in Sri Lanka with an urban system that is facing climate vulnerabilities and challenges of extreme heat conditions. We examined the UHI formation for the period 1996–2019 and its impact on the urban-systems by exploring nature-based solutions (NBS). This study used annual median temperatures based on Landsat data from 1996 to 2019 using the Google Earth Engine (GEE). Various geospatial approaches, including spectral index-based land use/cover mapping (1996, 2009 and 2019), urban-rural gradient zones, UHI profile, statistics and grid-based analysis, were used to analyse the data. The results revealed that the mean LST increased by 5.5 °C between 1996 and 2019 mainly associated with the expansion pattern of impervious surfaces. The mean LST had a positive correlation with impervious surfaces and a negative correlation with the green spaces in all the three time-points. Impacts due to climate change, including positive temperature and negative rainfall anomalies, contributed to the increase in LST. The study recommends interactively applying NBS to addressing the UHI impacts with effective mitigation and adaptation measures for urban sustainability. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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23 pages, 73630 KiB

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A Citizen-Centric Approach for the Improvement of Territorial Services Management

by Monica Sebillo, Giuliana Vitiello, Michele Grimaldi and Antonio De Piano

ISPRS Int. J. Geo-Inf. 2020, 9(4), 223; https://doi.org/10.3390/ijgi9040223 - 7 Apr 2020

Cited by 16 | Viewed by 3459

Abstract

In the last decade, there has been a growing awareness that the involvement of citizens in decision making can produce an immediate and positive impact on actions to be taken, as they are the real owners of knowledge about the place where they [...] Read more.

In the last decade, there has been a growing awareness that the involvement of citizens in decision making can produce an immediate and positive impact on actions to be taken, as they are the real owners of knowledge about the place where they live. By collecting and geolocating data through smartphones and the Internet, citizens in fact can help decision makers both create sharable spatio-temporal information about objects and phenomena and interpret territorial dynamics. However, although such a role has been definitely recognized, the lack of a homogeneous paradigm for structuring the sensing process, managing the geo big data produced and handling services makes it difficult to exploit such a potentiality. In this paper, we describe a citizen-centric approach conceived to build territorial knowledge useful to provide decision makers with a timely and reliable picture of the status of a given territory. In particular, a visual representation of geospatial knowledge is described, which summaries context-sensitive information about a territory and its citizens, thus improving the land monitoring tasks. An information system, SAFE, is finally presented, which consists of a Web and a mobile component to manage citizen supplied data to be integrated for building reliable dynamic scenarios. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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18 pages, 3555 KiB

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A Data-Driven Framework for Walkability Measurement with Open Data: A Case Study of Triple Cities, New York

by Chengbin Deng, Xiaoyu Dong, Huihai Wang, Weiying Lin, Hao Wen, John Frazier, Hung Chak Ho and Louisa Holmes

ISPRS Int. J. Geo-Inf. 2020, 9(1), 36; https://doi.org/10.3390/ijgi9010036 - 9 Jan 2020

Cited by 14 | Viewed by 5995

Abstract

Walking is the most common, environment-friendly, and inexpensive type of physical activity. To perform in-depth walkability analysis, one option is to objectively evaluate different aspects of built environment related to walkability. In this study, we proposed a computational framework for walkability measurement using [...] Read more.

Walking is the most common, environment-friendly, and inexpensive type of physical activity. To perform in-depth walkability analysis, one option is to objectively evaluate different aspects of built environment related to walkability. In this study, we proposed a computational framework for walkability measurement using open data. Three major steps of this framework include the web scrapping of publicly available online data, determining varying weights of variables, and generating a synthetic walkability index. The results suggest three major conclusions. First, the proposed framework provides an explicit mechanism for walkability measurement. Second, the synthetic walkability index from this framework is comparable to Walk Score, and it tends to have a slightly higher sensitivity, especially in highly walkable areas in urban core. Third, this framework was effectively applied in a metropolitan area that contains three small cities that together represent a small, old shrinking region, which extends the topical area in the literature. This framework has the potential to quantify walkability in any city, especially cities with a small population where walkability has rarely been studied, or those having no quantification indicator. For such areas, researchers can calculate the synthetic walkability index based on this framework, to assist urban planners, community leaders, health officials, and policymakers in their practices to improve the walking environment of their communities. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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15 pages, 2049 KiB

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The Unbalanced Analysis of Economic Urbanization—A Case Study of Typical Cities in China

by Xiangyang Cao, Bingzhong Zhou, Yishao Shi and Xiaowen Pei

ISPRS Int. J. Geo-Inf. 2020, 9(1), 13; https://doi.org/10.3390/ijgi9010013 - 25 Dec 2019

Cited by 6 | Viewed by 3461

Abstract

In the process of economic urbanization, because of competition among cities, agglomerations and polarization of regional economies are produced. This paper studies the urban polarization with Chinese characteristics and the regional economic urbanization, which include the imbalance under the influence of different geographical [...] Read more.

In the process of economic urbanization, because of competition among cities, agglomerations and polarization of regional economies are produced. This paper studies the urban polarization with Chinese characteristics and the regional economic urbanization, which include the imbalance under the influence of different geographical factors between the east and west of China and the imbalance under the comprehensive influence of natural and human factors in the province. The urban economic polarization index (UEPI) is constructed to describe the regional imbalance caused by the economic polarization of capital cities in China. The purpose is to explore the polarization of provincial capitals in their respective provinces and to reveal the strength and evolution of their role in the imbalance of economic urbanization. Then, combined with relevant analysis of natural and socio-economic background data, the induced factors and the mechanism of urban polarization are diagnosed. The results show the following: (1) The UEPI can accurately measure the polarization level of provincial capitals through the calculation of typical cities. (2) Based on the UEPI, capital cities can be divided into four categories, which include inapparent, obvious, prominent, and striking. Different cities have different effects on the imbalance in economic urbanization. (3) The main inducing factors of urban polarization are the resource environment, policy system, industrial structure, investment, scientific and technological innovation, location, and extroversion. The policy system is often an important link that integrates and adjusts various factors to form a comprehensive driving mechanism. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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17 pages, 5656 KiB

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Ranking of Illegal Buildings Close to Rivers: A Proposal, Its Implementation and Preliminary Validation

by Paolino Di Felice

ISPRS Int. J. Geo-Inf. 2019, 8(11), 510; https://doi.org/10.3390/ijgi8110510 - 11 Nov 2019

Cited by 8 | Viewed by 3166

Abstract

Illegal buildings (IBs) are a dramatic problem in developing countries due to the population explosion, but, at the same time, they represent an unsolved issue in several states usually called advanced (as, for instance, Italy). To protect the environment, and hence, people, land [...] Read more.

Illegal buildings (IBs) are a dramatic problem in developing countries due to the population explosion, but, at the same time, they represent an unsolved issue in several states usually called advanced (as, for instance, Italy). To protect the environment, and hence, people, land authorities must respond to the challenge of IBs by demolishing them. However, in countries where the phenomenon is extended, it is indispensable to provide those figures with an IT tool that returns to them an order of demolition. Through remote sensing methods, suspicious buildings can be identified with a good approximation, but they are all ex aequo. The research summarized in this paper formalizes a two-steps method to deal with a specific category of IBs, namely, those that are close to rivers. These buildings are of special interest to land authorities because people living or simply working inside them are exposed to the flood hazard that each year claims many victims all over the world. The first step of the method computes the census of the IBs located close to rivers, while the second step computes the ranking of these buildings. The ranking may be used as the IBs demolition order. In the paper, it is also proposed the structure of a Spatial DataBase (briefly, SDB) that is suitable to store the input data necessary to solve the problem, as well as the final ranking. Spatial SQL queries against the SDB implement the proposed two-steps method. A real case study was carried out to make a preliminary validation of the method. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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Review

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31 pages, 2078 KiB

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Strengthening Participation Using Interactive Planning Support Systems: A Systematic Review

by Johannes Flacke, Rehana Shrestha and Rosa Aguilar

ISPRS Int. J. Geo-Inf. 2020, 9(1), 49; https://doi.org/10.3390/ijgi9010049 - 15 Jan 2020

Cited by 32 | Viewed by 7062

Abstract

Interactive Planning Support Systems (PSS) implemented on a maptable are deemed suitable to support participatory planning processes. They are supposed to facilitate exchange of knowledge between stakeholders, consensus building among them, and group-learning processes. In this systematic review, based on 16 case studies [...] Read more.

Interactive Planning Support Systems (PSS) implemented on a maptable are deemed suitable to support participatory planning processes. They are supposed to facilitate exchange of knowledge between stakeholders, consensus building among them, and group-learning processes. In this systematic review, based on 16 case studies using interactive PSS, we analyze how these have contributed to the goal of strengthening stakeholder participation. To this end, we first elicit details of the interactive PSS and the related participatory processes. In the second step, we analyze how and what the studies report, as the impacts on participation. Results show that tools and applications have become more sophisticated over time and goals of the studies changed from collaboratively designing interventions to observing and understanding how the application of such tools contributes to improved plan outcomes and group-based learning. All interactive PSS succeeded to facilitate intensive stakeholder collaboration. However, many studies lack a proper framework for investigating its impacts on participation and therefore assess these rather incidentally based on implicit assumptions. Thus, a significant outcome of this review is an evaluation framework, which allows the structural assessment of the impacts of interactive PSS on stakeholder participation. Full article

(This article belongs to the Special Issue Geo-Information Science in Planning and Development of Smart Cities)

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