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Spatial Analysis Using Big Data

- Methods and Urban Applications

Om Spatial Analysis Using Big Data

Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems. The methods represent a cluster of potentially transformational socio-economic modeling tools that allow researchers to capture real-time and high-resolution information to potentially reveal new socioeconomic dynamics within urban populations. Each method, written by leading exponents of the discipline, uses real-time urban big data to solve research problems in spatial science. Urban applications of these methods are provided in unsurpassed depth, with chapters on surface temperature mapping, view value analysis, community clustering and spatial-social networks, among many others. Reviews some of the most powerful and challenging modern methods to study big data problems in spatial scienceProvides computer codes written in R, MATLAB and Python to help implement methodsApplies these methods to common problems observed in urban and regional economics

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  • Språk:
  • Engelsk
  • ISBN:
  • 9780128131275
  • Bindende:
  • Paperback
  • Sider:
  • 302
  • Utgitt:
  • 2. november 2019
  • Dimensjoner:
  • 152x229x0 mm.
  • Vekt:
  • 520 g.
  Gratis frakt
Leveringstid: 2-4 uker
Forventet levering: 16. mars 2026

Beskrivelse av Spatial Analysis Using Big Data

Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems. The methods represent a cluster of potentially transformational socio-economic modeling tools that allow researchers to capture real-time and high-resolution information to potentially reveal new socioeconomic dynamics within urban populations. Each method, written by leading exponents of the discipline, uses real-time urban big data to solve research problems in spatial science. Urban applications of these methods are provided in unsurpassed depth, with chapters on surface temperature mapping, view value analysis, community clustering and spatial-social networks, among many others.
Reviews some of the most powerful and challenging modern methods to study big data problems in spatial scienceProvides computer codes written in R, MATLAB and Python to help implement methodsApplies these methods to common problems observed in urban and regional economics

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