Spatial data science for data driven urban planning: The youth economic discomfort index for Rome

Today, a consistent segment of the world’s population lives in urban areas, and this proportion will vastly increase in the next decades. Therefore, understanding the key trends in urbanization, likely to unfold over the coming years, is crucial to the implementation of sustainable urban strategies. In parallel, the daily amount of digital data produced will be expanding at an exponential rate during the following years. The analysis of various types of data sets and its derived applications have incredible potential across different crucial sectors such as healthcare, housing, transportation, energy, and education. Nevertheless, in city development, architects and urban planners appear to rely mostly on traditional and analogical techniques of data collection. This paper investigates the prospective of the data science field, appearing to be a formidable resource to assist city managers in identifying strategies to enhance the social, economic, and environmental sustainability of our urban areas. The collection of different new layers of information would definitely enhance planners' capabilities to comprehend more in-depth urban phenomena such as gentrification, land use definition, mobility, or critical infrastructural issues. Specifically, the research results correlate economic, commercial, demographic, and housing data with the purpose of defining the youth economic discomfort index. The statistical composite index provides insights regarding the economic disadvantage of citizens aged between 18 years and 29 years, and results clearly display that central urban zones and more disadvantaged than peripheral ones. The experimental set up selected the city of Rome as the testing ground of the whole investigation. The methodology aims at applying statistical and spatial analysis to construct a composite index supporting informed data-driven decisions for urban planning.

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Geographic Information Systems (GIS) in Urban Planning

European Journal of Interdisciplinary Studies ◽

10.26417/ejis.v1i1.p85-92 ◽

2015 ◽

Vol 1 (1) ◽

pp. 85

Author(s):

Sonila Xhafa ◽

Albana Kosovrasti

Keyword(s):

Sustainable Development ◽

Information Systems ◽

Geographic Information Systems ◽

Urban Planning ◽

Urban Space ◽

Spatial Data ◽

Urban Areas ◽

Geographic Information ◽

Social Infrastructure ◽

Urban Centers

Geographic information systems can be defined as a intelligent tool, to which it relates techniques for the implementation of processes such as the introduction, recording, storage, handling, processing and generation of spatial data. Use of GIS in urban planning helps and guides planners for an orderly development of settlements and infrastructure facilities within and outside urban areas. Continued growth of the population in urban centers generates the need for expansion of urban space, for its planning in terms of physical and social infrastructures in the service of the community, based on the principles of sustainable development. In addition urbanization is accompanied with numerous structural transformations and functional cities, which should be evaluated in spatial context, to be managed and planned according to the principles of sustainable development. Urban planning connects directly with land use and design of the urban environment, including physical and social infrastructure in service of the urban community, constituting a challenge to global levels. Use of GIS in this field is a different approach regarding the space, its development and design, analysis and modeling of various processes occurring in it, as well as interconnections between these processes or developments in space.

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A GRASS ROOT ORIENTED URBAN PLANNING APPROACH TO UPLIFT THE SOCIO-ECONOMIC FACET OF A CITY USING 2D AND 3D GIS: CASE STUDY ON MEHMEDABAD CITY, INDIA

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-4-73-2018 ◽

2018 ◽

Vol IV-4 ◽

pp. 73-80

Author(s):

S. Gupta ◽

C. Shah ◽

D. Shah ◽

P. Deore ◽

S. Majumdar ◽

...

Keyword(s):

Urban Planning ◽

Urban Areas ◽

Planning Process ◽

City Development ◽

3D Gis ◽

Manual Intervention ◽

Ground Survey ◽

Recent Developments ◽

Grass Root ◽

2D And 3D

<p><strong>Abstract.</strong> Being a developing nation, India is facing an array of problems owing to the huge population shift from rural to urban areas, thereby leading to an increasing urbanisation trend since the 1980s. As a result, the process of urban planning in India is extremely tedious and requires lots of manual intervention. Although the recent developments in GIS have immensely helped urban planners, extensive ground survey is still a big challenge in the context of Indian cities. In this work, the study area has been chosen as Mehmedabad which is a Tier-3 city in the state of Gujarat. A rigorous grass root oriented ground survey involving each and every household of Mehmedabad has been utilised for both requirement elicitation and site-suitability purposes. With the aid of both 2D and 3D GIS, a city development plan has been proposed for the year 2031. The planning process incorporated population projection, water supply demand, sewage discharge and road network analysis for building robust development control regulations which were essential to improve the socio-economic aspects of Mehmedabad. Additionally, cost estimations for each of the proposed sectors have been carried out so as to maintain an appropriate budget for uplifting the existing infrastructures of the city.</p>

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CITY-FORMING ELEMENT AS A UNIT OF STUDY AND ANALYSIS OF URBAN AREAS STATE AND CONVERSION PROCESS

URBAN CONSTRUCTION AND ARCHITECTURE ◽

10.17673/vestnik.2016.04.20. ◽

2016 ◽

Vol 6 (4) ◽

pp. 107-111

Author(s):

Tatiana V. FILANOVA ◽

Kirill E. NIKONOV

Keyword(s):

Urban Planning ◽

Urban Studies ◽

Urban Areas ◽

Conversion Process ◽

Actual State ◽

City Development ◽

Planning Decisions ◽

The City ◽

Transformation Processes

The paper views the possibility of urban studies from the position of selected city-forming elements, whose quality and value characteristics are the indicators of actual state and transformation processes of urban areas. These elements become key elements to determine the vector of city development and urban planning forecast allows to evaluate and to monitor urban planning decisions. This city awareness permits to identify the values criteria of designed objects (spaces) and their grounds, presenting certain requirements for development of diff erent urban areas. Integration of the city-forming elements reveals a «complicated» relationship between the various parts of the city than is commonly believed today.

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Decomposition of Water Footprint of Food Consumption in Typical East Chinese Cities

Sustainability ◽

10.3390/su13010409 ◽

2021 ◽

Vol 13 (1) ◽

pp. 409

Author(s):

Ruogu Huang ◽

Xiangyang Li ◽

Yang Liu ◽

Yaohao Tang ◽

Jianyi Lin

Keyword(s):

Food Consumption ◽

Urban Areas ◽

Water Footprint ◽

Utilization Efficiency ◽

Diet Shift ◽

City Development ◽

Intensity Effect ◽

Consumption Level ◽

Positive Effects ◽

Per Capita

Water scarcity has put pressure on city development in China. With a particular focus on urban and rural effects, logarithmic mean Divisia index decomposition (LMDI) was used to analyze the water footprint per capita (WFP) of food consumption in five East China cities (Beijing, Tianjin, Shanghai, Qingdao, and Xiamen) from 2008 to 2018. Results show that the WFP of food consumption exhibited an upward tendency among all cities during the research period. Food consumption structure contributed the most to the WFP growth, mainly due to urban and rural residents’ diet shift toward a livestock-rich style. Except in Beijing, the food consumption level mainly inhibited the WFP growth due to the decrease in food consumption level per capita in urban areas. Urbanization had less influence on WFP growth for two megacities (Beijing and Shanghai) due to the strictly controlled urban population inflow policy and more positive effects for other cities. The water footprint intensity effect among cities was mainly due to uneven water-saving efficiency. Meanwhile, Beijing and Tianjin have achieved advancement in water utilization efficiency.

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The INSESS-COVID19 Project. Evaluating the Impact of the COVID19 in Social Vulnerability While Preserving Privacy of Participants from Minority Subpopulations

Applied Sciences ◽

10.3390/app11073110 ◽

2021 ◽

Vol 11 (7) ◽

pp. 3110

Author(s):

Karina Gibert ◽

Xavier Angerri

Keyword(s):

Social Vulnerability ◽

Data Science ◽

Policy Design ◽

Data Driven ◽

Informed Decision Making ◽

Technological Infrastructure ◽

Moderate Number ◽

Reliable Diagnosis ◽

Multivariate Relationships ◽

The Impact

In this paper, the results of the project INSESS-COVID19 are presented, as part of a special call owing to help in the COVID19 crisis in Catalonia. The technological infrastructure and methodology developed in this project allows the quick screening of a territory for a quick a reliable diagnosis in front of an unexpected situation by providing relevant decisional information to support informed decision-making and strategy and policy design. One of the challenges of the project was to extract valuable information from direct participatory processes where specific target profiles of citizens are consulted and to distribute the participation along the whole territory. Having a lot of variables with a moderate number of citizens involved (in this case about 1000) implies the risk of violating statistical secrecy when multivariate relationships are analyzed, thus putting in risk the anonymity of the participants as well as their safety when vulnerable populations are involved, as is the case of INSESS-COVID19. In this paper, the entire data-driven methodology developed in the project is presented and the dealing of the small subgroups of population for statistical secrecy preserving described. The methodology is reusable with any other underlying questionnaire as the data science and reporting parts are totally automatized.

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Prediction of Socio-Economic Indicators for Urban Planning Using VHR Satellite Imagery and Spatial Analysis

Remote Sensing ◽

10.3390/rs12111730 ◽

2020 ◽

Vol 12 (11) ◽

pp. 1730 ◽

Cited By ~ 2

Author(s):

Gebhard Warth ◽

Andreas Braun ◽

Oliver Assmann ◽

Kevin Fleckenstein ◽

Volker Hochschild

Keyword(s):

Spatial Analysis ◽

Urban Planning ◽

Urban Areas ◽

Residential Buildings ◽

Dynamic Change ◽

Training Data ◽

Infrastructure Planning ◽

Economic Point ◽

Steady Growth ◽

Building Typology

Ongoing urbanization leads to steady growth of urban areas. In the case of highly dynamic change of municipalities, due to the rates of change, responsible administrations often are challenged or struggle with capturing present states of urban sites or accurately planning future urban development. An interest for urban planning lies on socio-economic conditions, as consumption and production of disposable goods are related to economic possibilities. Therefore, we developed an approach to generate relevant parameters for infrastructure planning by means of remote sensing and spatial analysis. In this study, the single building defines the spatial unit for the parameters. In the case city Belmopan (Belize), based on WorldView-1 data we manually define a city covering building dataset. Residential buildings are classified to eight building types which are locally adapted to Belmopan. A random forest (RF) classifier is trained with locally collected training data. Through household interviews focusing on household assets, income and educational level, a socio-economic point (SEP) scaling is defined, which correlates very well with the defined building typology. In order to assign socio-economic parameters to the single building, five socio-economic classes (SEC) are established based on SEP statistics for the building types. The RF building type classification resulted in high accuracies. Focusing on the three categories to describe residential socio-economic states allowed high correlations between the defined building and socio-economic points. Based on the SEP we projected a citywide residential socio-economic building classification to support supply and disposal infrastructure planning.

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Measuring Walkability with GIS—Methods Overview and New Approach Proposal

Sustainability ◽

10.3390/su13041883 ◽

2021 ◽

Vol 13 (4) ◽

pp. 1883

Author(s):

Agnieszka Telega ◽

Ivan Telega ◽

Agnieszka Bieda

Keyword(s):

Spatial Data ◽

Urban Areas ◽

Modern World ◽

Single Family ◽

New Approach ◽

Parks And Recreation ◽

Gis Tools ◽

Point Data ◽

Pedestrian Infrastructure ◽

Gis Methods

Cities occupy only about 3% of the Earth’s surface area, but half of the global population lives in them. The high population density in urban areas requires special actions to make these areas develop sustainably. One of the greatest challenges of the modern world is to organize urban spaces in a way to make them attractive, safe and friendly to people living in cities. This can be managed with the help of a number of indicators, one of which is walkability. Of course, the most complete analyses are based on spatial data, and the easiest way to implement them is using GIS tools. Therefore, the goal of the paper is to present a new approach for measuring walkability, which is based on density maps of specific urban functions and networks of generally accessible pavements and paths. The method is implemented using open-source data. Density values are interpolated from point data (urban objects featuring specific functions) and polygons (pedestrian infrastructure) using Kernel Density and Line Density tools in GIS. The obtained values allow the calculation of a synthetic indicator taking into account the access by means of pedestrian infrastructure to public transport stops, parks and recreation areas, various attractions, shops and services. The proposed method was applied to calculate the walkability for Kraków (the second largest city in Poland). The greatest value of walkability was obtained for the Main Square (central part of the Old Town). The least accessible to pedestrians are, on the other hand, areas located on the outskirts of the city, which are intended for extensive industrial areas, single-family housing or large green areas.

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Attending to data: Exploring the use of attendance data within the datafied school

Research in Education ◽

10.1177/0034523720984200 ◽

2021 ◽

pp. 003452372098420

Author(s):

Neil Selwyn ◽

Luci Pangrazio ◽

Bronwyn Cumbo

Keyword(s):

Secondary Schools ◽

Empirical Data ◽

Qualitative Studies ◽

Digital Data ◽

Data Driven ◽

School Staff ◽

Digital Form ◽

Student Attendance ◽

Contemporary Schooling

Contemporary schooling is seen to be altering significantly in light of a combined ‘digitisation’ and ‘datafication’ of key processes. This paper examines the nature and conditions of the datafied school by exploring how a relatively prosaic and longstanding school metric (student attendance data) is being produced and used in digital form. Drawing on empirical data taken from in-depth qualitative studies in three contrasting Australian secondary schools, the paper considers ‘anticipatory’, ‘analytical’ and ‘administrative’ aspects of how digitally-mediated attendance data is produced, used and imagined by school staff. Our findings foreground a number of constraints, compromises and inconsistencies that are usually glossed-over in enthusiasms for ‘data-driven’ education. It is argued that these findings highlight the messy realities of schools’ current relationships with digital data, and the broader logics of school datafications.

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CONTEMPORARY DIRECTIONS OF URBAN PLANNING IN THE REVIEW OF GRADUATION THESIS OF THE NEW GENERATION

СОВРЕМЕННАЯ АРХИТЕКТУРА МИРА ◽

10.25995/niitiag.2020.13.2.028 ◽

2019 ◽

Author(s):

И.Г. Федченко

Keyword(s):

Urban Planning ◽

Public Space ◽

Participatory Design ◽

The Arctic ◽

Transport Systems ◽

University Graduates ◽

City Development ◽

Semantic Categories ◽

Space Projects ◽

The City

В статье представлен обзор тематики выпускных квалификационных работ по градостроительству, представленных на Международный смотр-конкурс дипломных проектов архитектурных вузов, проводимый Межрегиональной общественной организацией содействия архитектурному образованию (МООСАО) в 2018 и 2019 годах. Проведенный анализ позволил сформулировать современные направления развития градостроительного знания по смысловым категориям проектов: технологические проекты; стратегические проекты различных уровней; проекты развития урбанизированных территорий; проекты уникальных тематик (освоение космоса, Арктики, концепции города будущего, проекты на территориях зарубежных государств). The article provides an overview of the topics of diploma works on urban planning submitted to the International Review Competition of architectural projects of university graduates held by the Interregional Public Organization for the Promotion of Architectural Education in 2018 and 2019. The analysis made it possible to formulate a generalization of topics into semantic categories: technological projects (technologies for urban planning, environmental-friendly planning, participatory design); strategic projects of various levels (the development of agglomerations and resettlement systems, strategies for the development of cities and historical centers, the modernization of transport systems, as well as projects to form the “nuclei” of economic growth); urban development projects (reconstruction of existing buildings, renovation of communal and warehouse areas of the city, development of disturbed territories, public space projects under the federal program “Formation of a comfortable urban environment”); projects of unique topics (space exploration, the Arctic, the concept of the city of the future, projects in foreign countries).

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DATA-DRIVEN DISCOVERY OF MATERIAL STATES IN COMPOSITES UNDER FATIGUE LOADS

10.12783/asc36/35783 ◽

2021 ◽

Author(s):

MUTHU RAM ELENCHEZHIAN ◽

VAMSEE VADLAMUDI ◽

RASSEL RAIHAN ◽

KENNETH REIFSNIDER

Keyword(s):

Domain Knowledge ◽

Data Science ◽

Damage Tolerance ◽

Electrochemical Impedance ◽

Research Work ◽

Rate Of Change ◽

Data Driven ◽

Develop Model ◽

Damage Development ◽

Fatigue Loads

Our community has a widespread knowledge on the damage tolerance and durability of the composites, developed over the past few decades by various experimental and computational efforts. Several methods have been used to understand the damage behavior and henceforth predict the material states such as residual strength (damage tolerance) and life (durability) of these material systems. Electrochemical Impedance Spectroscopy (EIS) and Broadband Dielectric Spectroscopy (BbDS) are such methods, which have been proven to identify the damage states in composites. Our previous work using BbDS method has proven to serve as precursor to identify the damage levels, indicating the beginning of end of life of the material. As a change in the material state variable is triggered by damage development, the rate of change of these states indicates the rate of damage interaction and can effectively predict impending failure. The Data-Driven Discovery of Models (D3M) [1] aims to develop model discovery systems, enabling users with domain knowledge but no data science background to create empirical models of real, complex processes. These D3M methods have been developed severely over the years in various applications and their implementation on real-time prediction for complex parameters such as material states in composites need to be trusted based on physics and domain knowledge. In this research work, we propose the use of data-driven methods combined with BbDS and progressive damage analysis to identify and hence predict material states in composites, subjected to fatigue loads.

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