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Spatial Analysis Using Big Data: Methods and Urban Applications (Spatial Econometrics and Spatial Statistics) - Softcover
Synopsis
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 science
- Provides computer codes written in R, MATLAB and Python to help implement methods
- Applies these methods to common problems observed in urban and regional economics
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About the Authors
Yoshiki Yamagata is the Head of Global Carbon Project International Office at the Center for Global Environmental Research, National Institute for Environmental Studies.He received his Ph.D. degree in System Science from the University of Tokyo, Japan.His research interests include Urban Resilience, Urban Analytics, and Urban Systems.
Hajime Seya received his Ph.D. degree in engineering from University of Tsukuba. His research interests include urban transportation planning, regional science, geographical information science, integrated land-use-transport modeling, and spatial statistics/econometrics. Seya has published 33 papers.
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