ISBN:
9789811676499
Language:
English
Pages:
1 Online-Ressource(XVIII, 187 p. 106 illus., 95 illus. in color.)
Edition:
1st ed. 2022.
Series Statement:
Advances in 21st Century Human Settlements
Series Statement:
Springer eBook Collection
Parallel Title:
Erscheint auch als Geospatial data analytics and urban applications
Parallel Title:
Erscheint auch als
Parallel Title:
Erscheint auch als
Keywords:
Application software.
;
Geography.
;
Statistics .
;
Statistical physics.
;
Dynamical systems.
;
Public health.
;
Urban economics.
;
Stadt
;
Raumdaten
;
Datenanalyse
Abstract:
Introduction: Spatial Big Data and Urban Analytics -- Preferential Home Search in Urban Settings -- Air Quality Dynamics and Urban Heat Island effects during COVID-19 -- Mass Rapid Transit and Population Dynamics during Covid-19 in Singapore -- A Geospatial analysis of Tweets during Post-Circuit Breaker in Singapore -- Space-Time Analytics of New York City Shooting Incidents -- Spatial and Temporal patterns of Tourist Source Market Emissiveness: A Study of Shanghai, China -- Spatial Perspective of Crime Patterns in Chicago amid Covid-19 -- Geospatial analysis of Grab Trips in Singapore -- Ecological Vulnerability of Nyingchi, Tibet.
Abstract:
This book highlights advanced applications of geospatial data analytics to address real-world issues in urban society. With a connected world, we are generating spatial at unprecedented rates which can be harnessed for insightful analytics which define the way we analyze past events and define the future directions. This book is an anthology of applications of spatial data and analytics performed on them for gaining insights which can be used for problem solving in an urban setting. Each chapter is contributed by spatially aware data scientists in the making who present spatial perspectives drawn on spatial big data. The book shall benefit mature researchers and student alike to discourse a variety of urban applications which display the use of machine learning algorithms on spatial big data for real-world problem solving.
DOI:
10.1007/978-981-16-7649-9
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