The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVI-3/W1-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-3/W1-2022, 15–20, 2022
https://doi.org/10.5194/isprs-archives-XLVI-3-W1-2022-15-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-3/W1-2022, 15–20, 2022
https://doi.org/10.5194/isprs-archives-XLVI-3-W1-2022-15-2022
 
22 Apr 2022
22 Apr 2022

EFFECT ASSESSMENT OF LARGE-SCALE EVENTS VIA SPATIOTEMPORAL APPROACH

X. Chai1, X. Guo2, J. Xiao1, and J. Jiang2 X. Chai et al.
  • 1Beijing Unistrong Science & Technology Co., Ltd, 100176 Beijing, China
  • 2Beijing University of Civil Engineering and Architecture, 102616 Beijing, China

Keywords: Effect Assessment, Co-location Analysis, Difference-in-Differences (DID), Spatiotemporal Big-data

Abstract. Together with rapid development of location-based services and big-data platforms especially in urban areas, huge amount of spatiotemporal data are collected without properly used; on the other hand, state-of-the-art quantitative policy effect assessment techniques usually require panel data as input. To solve both issues, this paper follows the following approach: obtaining panel data by aggregating spatiotemporal data and feeding them to the effect assessment module. With the help of high-performance computing techniques which are able to deal with huge amount of data, we build framework Aggr-analysis which applies clustering algorithms to shrink the raw data set and find associations between different data sets via co-location analysis. Finally, we prove the effectiveness by an example: analysis of resident activities during the COVID-19 Pandemic. We apply Aggr-analysis to process the share-bike usage data and POI (Point Of Interest) data in Beijing, then obtain the panel data required by DID (Difference-in-Differences) method. Supplemented with environmental data, we conclude the net effect of the COVID-19 breakout on society and economy - the pandemic has reduced the overall resident mobility by 64.8% within two months.