CroScalar: An Integrated Framework for Cross-Scale Spatio-Temporal Modeling
Topics: Spatial Analysis & Modeling
, Geographic Information Science and Systems
, Cartography
Keywords: Spatio-temporal analysis; Multi-Scale; GIS; MAUP
Session Type: Virtual Paper Abstract
Day: Saturday
Session Start / End Time: 2/26/2022 09:40 AM (Eastern Time (US & Canada)) - 2/26/2022 11:00 AM (Eastern Time (US & Canada))
Room: Virtual 34
Authors:
Yi Qiang, University of South Florida
Barbara Buttenfield, University of Colorado - Boulder
Nodari Sitchinava, University of Hawaii - Manoa
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Abstract
The representations of space and time are fundamental to GIScience and data mining of diverse geospatial data collected at different resolutions. The choice of analytic scales (both spatial and temporal) to a large extent determines the insights that can be gained. The importance of scale has been epitomized in the well-known modifiable areal unit problem (MAUP) and its temporal equivalent. However, multi-scale analysis for spatio-temporal data remain a challenge for prevalent GISystems, which represent geospatial data represented as flat layers at pre-determined resolutions and spatial analysis tools only operate at a single scale. To discover patterns and relationships that are prominent in different scales, inefficient “trial-and-error” approaches are typically used to determine the appropriate resolution, aggregation units and search bandwidth for data analyses and modeling. This presentation will introduce an analytical framework that organize space, time, spatial scale and temporal scale unified and hierarchical structure. By visualizing and analyzing variations of data in the scale dimensions, the nested relationships and patterns at multiple spatial and temporal scales can be better quantified and understand. This presentation will also demonstrate a series of applications of the framework in time series analysis, spatial pattern detection, and land cover change modeling.
CroScalar: An Integrated Framework for Cross-Scale Spatio-Temporal Modeling
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Virtual Paper Abstract
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