scholarly journals Uncovering the Relationship between Human Connectivity Dynamics and Land Use

2020 ◽  
Vol 9 (3) ◽  
pp. 140 ◽  
Author(s):  
Olivera Novović ◽  
Sanja Brdar ◽  
Minučer Mesaroš ◽  
Vladimir Crnojević ◽  
Apostolos N. Papadopoulos
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Community Structure ◽  
Dynamic Change ◽  
Base Station ◽  
Phone Call ◽  
Mobile Phone Data ◽  
Data Set ◽  
Human Dynamics ◽  
The City

CDR (Call Detail Record) data are one type of mobile phone data collected by operators each time a user initiates/receives a phone call or sends/receives an sms. CDR data are a rich geo-referenced source of user behaviour information. In this work, we perform an analysis of CDR data for the city of Milan that originate from Telecom Italia Big Data Challenge. A set of graphs is generated from aggregated CDR data, where each node represents a centroid of an RBS (Radio Base Station) polygon, and each edge represents aggregated telecom traffic between two RBSs. To explore the community structure, we apply a modularity-based algorithm. Community structure between days is highly dynamic, with variations in number, size and spatial distribution. One general rule observed is that communities formed over the urban core of the city are small in size and prone to dynamic change in spatial distribution, while communities formed in the suburban areas are larger in size and more consistent with respect to their spatial distribution. To evaluate the dynamics of change in community structure between days, we introduced different graph based and spatial community properties which contain latent footprint of human dynamics. We created land use profiles for each RBS polygon based on the Copernicus Land Monitoring Service Urban Atlas data set to quantify the correlation and predictivennes of human dynamics properties based on land use. The results reveal a strong correlation between some properties and land use which motivated us to further explore this topic. The proposed methodology has been implemented in the programming language Scala inside the Apache Spark engine to support the most computationally intensive tasks and in Python using the rich portfolio of data analytics and machine learning libraries for the less demanding tasks.

Biclustering for uncovering spatial-temporal patterns in telecom data

2021 ◽  
Author(s):  
Nastasija Grujić ◽  
Sanja Brdar ◽  
Olivera Novović ◽  
Nikola Obrenović ◽  
Miro Govedarica ◽  
...  
Keyword(s):  
Clustering Algorithm ◽  
Activity Patterns ◽  
Base Station ◽  
Capital City ◽  
Mobile Phone Data ◽  
Data Mining Technique ◽  
Activity Data ◽  
Data Set ◽  
Space And Time ◽  
The City

<p>Understanding human dynamics is of crucial importance for managing human activities for sustainable development. According to the United Nations, 68% of people will live in cities by 2050. Therefore, it is important to understand human footprints in order to develop policies that will improve the lives in urban and suburban areas. Our study aims at detecting spatial-temporal activity patterns from mobile phone data provided by a telecom service provider. To be more precise we used the activity data set which contains the amount of sent/received SMS, calls, as well as internet usage per radio-base station in defined time-stamps. The case study focus is on the capital city of Serbia, Belgrade, which has have nearly 2 million inhabitants and included the month of February 2020 in the analysis. We applied the biclustering (spectral co-clustering) algorithm on the telecom data to detect locations in the city that behave similarly in the specific time windows. Biclustering is a data mining technique that is being used for finding homogeneous submatrices among rows and columns of a matrix, widely used in text mining and gene expression data analysis.  Although, there are no examples in the literature of the algorithm usage on location-based data for urban application, we have seen the potential due to its ability to detect clusters in a more refined way, during a specific period of time that could not otherwise be detected with global clustering approach. To prepare the data for the algorithm appliance, we normalized each type of activity (SMS/Call In/Out and Internet activity) and aggregated the total activity on each antenna per hour. We transformed the data into the matrix, where rows were presenting the antennas, and columns the hours. The algorithm was applied for each day separately. On average number of discovered biclusters was 5, usually corresponding to regular based activities, such as work, home, commuting, and free time, but also to the city’s nightlife. Our results confirmed that urban spaces are the function of space and time. They revealed different functionalities of the urban and suburban parts in the city. We observed the presence of patterned behavior across the analyzed days. The type of day dictated the spatial-temporal activities that occurred. We distinguished different types of days, such as working days (Monday to Thursday), Fridays, weekends, and holidays. These findings showed the promising potential of the biclustering algorithm and could be utilized by policymakers for precisely detecting activity clusters across space and time that correspond to specific functions of the city.</p>

scholarly journals Exploring Urban Spatial Feature with Dasymetric Mapping Based on Mobile Phone Data and LUR-2SFCAe Method

2018 ◽  
Vol 10 (7) ◽  
pp. 2432 ◽  
Author(s):  
Lingbo Liu ◽  
Zhenghong Peng ◽  
Hao Wu ◽  
Hongzan Jiao ◽  
Yang Yu
Keyword(s):  
Land Use ◽  
Spatial Heterogeneity ◽  
Mobile Phone ◽  
Census Data ◽  
Base Station ◽  
Distance Decay ◽  
Base Stations ◽  
Mobile Phone Data ◽  
Dasymetric Mapping ◽  
Spatial Feature

Dasymetric mapping of high-resolution population facilitates the exploration of urban spatial feature. While most relevant studies are still challenged by weak spatial heterogeneity of ancillary data and quality of traditional census data, usually outdated, costly and inaccurate, this paper focuses on mobile phone data, which can be real-time and precise, and also strengthens spatial heterogeneity by its massive mobile phone base stations. However, user population recorded by mobile phone base stations have no fixed spatial boundary, and base stations often disperse in extremely uneven spatial distribution, this study defines a distance-decay supply–demand relation between mobile phone user population of gridded base station and its surrounding land patches, and outlines a dasymetric mapping method integrating two-step floating catchment area method (2SFCAe) and land use regression (LUR). The results indicate that LUR-2SFCAe method shows a high fitness of regression, provides population mapping at a finer scale and helps identify urban centrality and employment subcenters with detailed worktime and non-worktime populations. The work involving studies of dasymetric mapping based on LUR-2SFCAe method and mobile phone data proves to be encouraging, sheds light on the relationship between mobile phone users and nearby land use, brings about an integrated exploration of 2SFCAe in LUR with distance-decay effect and enhances spatial heterogeneity.

scholarly journals Políticas públicas e desenvolvimento urbano sustentável

2004 ◽  
Vol 9 ◽  
Author(s):  
Paulo Rolando De LIMA ◽  
Eduardo L. KRÜGER
Keyword(s):  
Land Use ◽  
Sustainable Development ◽  
Spatial Distribution ◽  
Public Policies ◽  
Sustainable Cities ◽  
Agenda 21 ◽  
Urban Sustainable Development ◽  
Environmental Objectives ◽  
The City ◽  
Future Condition

Considerando que o processo de desenvolvimento urbano implica na multiplicação dos impactos ambientais decorrentes do assentamento humano sobre a área de influência da cidade e a existência de diretrizes de ação visando à promoção da sustentabilidade urbana na Agenda 21 brasileira, bem como nas disposições do Estatuto da Cidade, especialmente no que se refere aos objetivos da política urbana, garantia do direito a cidades sustentáveis, planejamento do desenvolvimento urbano, estudo de impacto de vizinhança e ao Plano Diretor, o trabalho aponta possibilidades de efetivação destas diretrizes e dispositivos legais no gerenciamento urbano por meio de políticas públicas locais no âmbito dos transportes, habitação e uso do solo. Tais políticas deverão estar dirigidas a objetivos ambientais definidos em função do grau de qualidade ambiental urbana presente e da eqüidade da sua distribuição espacial, visando a uma situação futura desejada. Public policies and urban sustainable development Abstract Considering that urban development is directly related to the spreading of environmental impacts caused by human settlements within city limits and the existence of directives in the Brazilian Agenda 21 regarding the promotion of urban sustainability, as well as the content of the City Statute regarding urban policies towards sustainable cities and urban planing, this study presents possibilities of implementing directives and legal measures for urban management by means of local public policies concerning transportation, habitation and land use. Such policies should be directed towards environmental objectives, defined with regard to the present urban environmental quality and spatial distribution, aiming at a desired future condition.

scholarly journals The time varying network of urban space uses in Milan

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Alba Bernini ◽  
Amadou Lamine Toure ◽  
Renato Casagrandi
Keyword(s):  
Land Use ◽  
Mobile Phone ◽  
Urban Space ◽  
Temporal Analysis ◽  
Mobile Phone Data ◽  
Natural Environments ◽  
Urban Structure ◽  
Land Uses ◽  
Population Mobility ◽  
The City

AbstractIn a metropolis, people movements design intricate patterns that change on very short temporal scales. Population mobility obviously is not random, but driven by the land uses of the city. Such an urban ecosystem can interestingly be explored by integrating the spatial analysis of land uses (through ecological indicators commonly used to characterize natural environments) with the temporal analysis of human mobility (reconstructed from anonymized mobile phone data). Considering the city of Milan (Italy) as a case study, here we aimed to identify the complex relations occurring between the land-use composition of its neighborhoods and the spatio-temporal patterns of occupation made by citizens. We generated two spatially explicit networks, one static and the other temporal, based on the analysis of land uses and mobile phone data, respectively. The comparison between the results of community detection performed on both networks revealed that neighborhoods that are similar in terms of land-use composition are not necessarily characterized by analogous temporal fluctuations of human activities. In particular, the historical concentric urban structure of Milan is still under play. Our big data driven approach to characterize urban diversity provides outcomes that could be important (i) to better understand how and when urban spaces are actually used, and (ii) to allow policy makers improving strategic development plans that account for the needs of metropolis-like permanently changing cities.

Ozarks land use data set; Greenwood, Miss.; Ark.; La. (Ark. only)

1975 ◽  
Author(s):  
G. L. Loelkes ◽  
I.L. Hardin ◽  
E.C. Napier ◽  
M.J. Chambers ◽  
Eldon Jessen ◽  
...  
Keyword(s):  
Land Use ◽  
Data Set

Ozarks land use data set; McAlester, Okla.; Ark.

1975 ◽  
Author(s):  
G. L. Loelkes ◽  
I.L. Hardin ◽  
E.C. Napier ◽  
M.J. Chambers ◽  
Eldon Jessen ◽  
...  
Keyword(s):  
Land Use ◽  
Data Set

Pzarks land use data set; Memphis, Tenn.; Ark.; Mo. (Ark. only)

1975 ◽  
Author(s):  
G. L. Loelkes ◽  
I.L. Hardin ◽  
E.C. Napier ◽  
M.J. Chambers ◽  
Eldon Jessen ◽  
...  
Keyword(s):  
Land Use ◽  
Data Set

Ozarks land use data set; New Orleans, La.

1975 ◽  
Author(s):  
G. L. Loelkes ◽  
I.L. Hardin ◽  
E.C. Napier ◽  
M.J. Chambers ◽  
Eldon Jessen ◽  
...  
Keyword(s):  
Land Use ◽  
New Orleans ◽  
Data Set

Optimal Land Use Analysis Using Lindenmayer Grammars

2013 ◽  
Vol 8 (2) ◽  
pp. 163-175
Author(s):  
Urszula Żukowska ◽  
Grażyna Kalewska
Keyword(s):  
Land Use ◽  
Urban Development ◽  
Computer Program ◽  
L System ◽  
L Systems ◽  
The City

In today's world, when it is so important to use every piece of land for a particular purpose, both economically and ecologically, identifying optimal land use is a key issue. For this reason, an analysis of the optimal land use in a section of the city of Olsztyn, using the L-system Urban Development computer program, was chosen as the aim of this paper. The program uses the theories of L-systems and the cartographic method to obtain results in the form of sequences of productions or maps. For this reason, the first chapters outline both theories, i.e. the cartographic method to identify optimal land use and Lindenmayer grammars (called L-systems). An analysis based on a fragment of the map of Olsztyn was then carried out. Two functions were selected for the analysis: agricultural and forest-industrial. The results are presented as maps and sequences in individual steps.

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