Robust Land Use Characterization of Urban Landscapes using Cell Phone Data
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Transcript of Robust Land Use Characterization of Urban Landscapes using Cell Phone Data
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Robust Land Use Characterization
of Urban Landscapes using Cell Phone Data
June 12, 2011
Vctor Soto & Enrique Fras-Martnez
TELEFNICA I+D
Introduction
01
Telefnica I+D
Goal: Land use of urban areas using Call Details Records.
Preliminaries
02
Telefnica I+D
Cell Phone Network
Cell Phone networks are built using Base Transceiver Stations (BTS).
Each BTS will be characterized by a feature vector that describes the calling behavior area.
CDR dataset
Our Dataset
1 month of phone call interactions.
1100 Base Transceiver Stations.
Each CDR contains: phoneSource | phoneDestiny | btsSource | btsDestiny | DD/MM/YYYY | hh:mm:ss | d
Phone number are encrypted to anonymize user identities.
Activity Signature
03
Telefnica I+D
Representations
Activity signature vectors are built: each component contains the number of managed calls by the BTS in 5-minute intervals.
Land Use Identification
04
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Methodology (I)
Detect the number of fuzzy clusters c in the signatures dataset using subtractive clustering.
Robust Land Use Analysis
05
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Why Robust Land Usage?
Land uses in urban landscapes are not well defined
One lot can show several land uses at different degrees.
Often real and planned land uses won't match.
The key:
Fuzzy c-means returns the membership degree of each object to the class representatives. These membership indices can be used to filter robust land uses.
Filtering process
Filtering process
Validation
06
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Cluster 1: Industrial & Office
Cluster 2: Business & Commercial
Cluster 3: Nightlife
Cluster 4: Leisure & Transport
Cluster 5: Residential
Conclusions & Future Work
07
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Specific uses for City Halls.
Questions?
Telefnica I+D