en-es
en-fr
en-sl
en
0.25
0.5
0.75
1.25
1.5
1.75
2
Scaling Laws of Cities
Published on Apr 03, 20171268 Views
Related categories
Chapter list
Scaling laws of cities00:00
New York City00:35
Ever-increasing complexity of cities - 101:03
Ever-increasing complexity of cities - 201:39
Increasing uncertainties in urban planning and design02:26
Growing availability of human activity data03:48
Content05:21
Urban Scaling Laws06:17
The scaling of socio-economic quantities with city size06:21
Greater population - „faster life and greater dividends“10:53
Network of human interactions as a unifying mechanism?12:15
Several papers on the topic13:08
Growing availability of human activity data13:16
Mobile phone data - exemplary data sources13:32
Inferring the interaction network15:13
Human interactions - 116:28
Human interactions - 217:01
Human interactions - 317:42
Human interactions - 418:06
Nodal clustering - 119:11
Nodal clustering - 219:54
Acceleration of spreading processes20:18
Potential ‚hidden‘ biases21:17
Urban Structure: Building Heights and Shapes22:31
Building functional cities23:18
Generating simple 3D city models24:08
Building heights - 125:42
Building heights - 226:06
Building heights - 326:34
Height prediction from urban scaling theory27:08
Building heights distribution28:08
Building shapes28:13
Urban Dynamics: Movement of People in Cities29:17
‚Collective‘ movements in cities29:42
Individual trajectories from mobile phone data - 130:13
Individual trajectories from mobile phone data - 232:09
Lets look into the data!32:33
Quantifying the attractiveness of locations - 133:07
Quantifying the attractiveness of locations - 234:16
Quantifying the attractiveness of locations - 334:53
Quantifying the attractiveness of locations - 436:00
Quantifying the attractiveness of locations - 536:24
Quantifying the attractiveness of locations - 637:11
Quantifying the attractiveness of locations - 739:01
Quantifying the attractiveness of locations - 839:51
Quantifying the attractiveness of locations - 940:45
Quantifying the attractiveness of locations - 1041:39
Quantifying the attractiveness of locations - 1142:49
Quantifying the attractiveness of locations - 1243:20
Quantifying the attractiveness of locations - 1343:27
Greater Boston43:36
Portugal44:21
Senegal45:03
Singapore45:38
Quantifying the attractiveness of locations - 1446:11
Locations with ‚anomalous‘ behavior - 146:26
Locations with ‚anomalous‘ behavior - 248:04
Application: Infrastructure design49:23
Electrification planning in developing countries49:43
Electrification rates in Senegal49:56
Using information from mobile phone infrastructure to facilitate electrification50:28
Mobile phone data as a proxy for electricity demand52:44
But not only…53:28
Electrification technology optioneering: techno-economic analysis54:20
Electrification recommendations54:46
Take home: urban ‚big‘ data - 155:34
Take home: urban ‚big‘ data - 255:39
Thank you!56:21