Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 2.281 IF 2.281
  • IF 5-year value: 2.693 IF 5-year
    2.693
  • CiteScore value: 2.43 CiteScore
    2.43
  • SNIP value: 1.193 SNIP 1.193
  • IPP value: 2.31 IPP 2.31
  • SJR value: 0.965 SJR 0.965
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 73 Scimago H
    index 73
  • h5-index value: 40 h5-index 40
Discussion papers
https://doi.org/10.5194/nhess-2019-136
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-136
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 03 Jun 2019

Research article | 03 Jun 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Urban anomalies in response to rainstorms based on smartphone location data: a case study of eight cities in China

Jiawei Yi1,2, Yunyan Du1,2, Fuyuan Liang3, Tao Pei1,2, Ting Ma1,2, and Chenghu Zhou1,2 Jiawei Yi et al.
  • 1State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
  • 2University of Chinese Academy of Sciences, Beijing, China
  • 3Department of Geography, Western Illinois University, Macomb, IL, USA

Abstract. This study explored city residents’ collective geo-tagged behaviors in response to rainstorms using the number of location request (NLR) data generated by smartphone users. We examined the rainstorms, flooding, NLR anomalies, as well as the associations among them in eight selected cities across the mainland China. The time series NLR clearly reflects cities’ general diurnal rhythm and the total NLR is moderately correlated with the total city population. Anomalies of NLR were identified at both the city and grid scale using the S-H-ESD method. Analysis results manifested that the NLR anomalies at the city and grid levels are well associated with rainstorms, indicating city residents request more location-based services (e.g. map navigation, car hailing, food delivery, etc.) when there is a rainstorm. However, sensitivity of the city residents’ collective geo-tagged behaviors in response to rainstorms varies in different cities as shown by different peak rainfall intensity thresholds. Significant high peak rainfall intensity tends to trigger city flooding, which lead to increased location-based requests as shown by positive anomalies on the time series NLR.

Jiawei Yi et al.
Interactive discussion
Status: open (until 29 Jul 2019)
Status: open (until 29 Jul 2019)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement
Jiawei Yi et al.
Jiawei Yi et al.
Viewed  
Total article views: 216 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
184 31 1 216 0 0
  • HTML: 184
  • PDF: 31
  • XML: 1
  • Total: 216
  • BibTeX: 0
  • EndNote: 0
Views and downloads (calculated since 03 Jun 2019)
Cumulative views and downloads (calculated since 03 Jun 2019)
Viewed (geographical distribution)  
Total article views: 143 (including HTML, PDF, and XML) Thereof 142 with geography defined and 1 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved  
No saved metrics found.
Discussed  
No discussed metrics found.
Latest update: 18 Jun 2019
Publications Copernicus
Download
Short summary
This paper exploited the advantages of smartphone location data to study the human responses to rainstorm disasters. Intense rainstorms disrupt city residents’ behaviors as reflected in anomalies of location-based service request. Anomaly identification from fine-scale smartphone location data facilitates monitoring social responses to rainstorms. Resident’s collective geo-tagged behaviors in different cities show different sensitivities to rainstorms.
This paper exploited the advantages of smartphone location data to study the human responses to...
Citation