Quantitative estimates of collective geo-tagged human activities in response to typhoon Hato using location-aware big data
Location-aware big data from social media have been widely used to quantitatively characterize natural disasters and disaster-induced losses. It is not clear how human activities collectively respond to a disaster. In this study, we examined the collective human activities in response to Typhoon Hat...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2020-09-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/17538947.2019.1645894 |
| _version_ | 1797678582854582272 |
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| author | Zhang Liu Yunyan Du Jiawei Yi Fuyuan Liang Ting Ma Tao Pei |
| author_facet | Zhang Liu Yunyan Du Jiawei Yi Fuyuan Liang Ting Ma Tao Pei |
| author_sort | Zhang Liu |
| collection | DOAJ |
| description | Location-aware big data from social media have been widely used to quantitatively characterize natural disasters and disaster-induced losses. It is not clear how human activities collectively respond to a disaster. In this study, we examined the collective human activities in response to Typhoon Hato at multi spatial scales using aggregated location request data. We proposed a Multilevel Abrupt Changes Detection (MACD) methodological framework to detect and characterize the abrupt changes in location requests in response to Typhoon Hato. Results show that, at the grid level, most anomaly grids were located within a radius of 53 km around the typhoon trajectory. At the city level, there are significant spatial difference in terms of the human activity recovery duration (230 h on average). At the subnational level, the absolute magnitude of abrupt location request changes is strongly correlated with the typhoon-induced economic losses and the population affected. |
| first_indexed | 2024-03-11T23:02:00Z |
| format | Article |
| id | doaj.art-ce354f9d8a394b0c925cbd08642ccd4b |
| institution | Directory Open Access Journal |
| issn | 1753-8947 1753-8955 |
| language | English |
| last_indexed | 2024-03-11T23:02:00Z |
| publishDate | 2020-09-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj.art-ce354f9d8a394b0c925cbd08642ccd4b2023-09-21T14:57:08ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552020-09-011391072109210.1080/17538947.2019.16458941645894Quantitative estimates of collective geo-tagged human activities in response to typhoon Hato using location-aware big dataZhang Liu0Yunyan Du1Jiawei Yi2Fuyuan Liang3Ting Ma4Tao Pei5State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of SciencesState Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of SciencesState Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of SciencesDepartment of Geography, Western Illinois UniversityState Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of SciencesState Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of SciencesLocation-aware big data from social media have been widely used to quantitatively characterize natural disasters and disaster-induced losses. It is not clear how human activities collectively respond to a disaster. In this study, we examined the collective human activities in response to Typhoon Hato at multi spatial scales using aggregated location request data. We proposed a Multilevel Abrupt Changes Detection (MACD) methodological framework to detect and characterize the abrupt changes in location requests in response to Typhoon Hato. Results show that, at the grid level, most anomaly grids were located within a radius of 53 km around the typhoon trajectory. At the city level, there are significant spatial difference in terms of the human activity recovery duration (230 h on average). At the subnational level, the absolute magnitude of abrupt location request changes is strongly correlated with the typhoon-induced economic losses and the population affected.http://dx.doi.org/10.1080/17538947.2019.1645894human responsetyphoonnatural disasterlocation-aware datarapid disaster assessment |
| spellingShingle | Zhang Liu Yunyan Du Jiawei Yi Fuyuan Liang Ting Ma Tao Pei Quantitative estimates of collective geo-tagged human activities in response to typhoon Hato using location-aware big data International Journal of Digital Earth human response typhoon natural disaster location-aware data rapid disaster assessment |
| title | Quantitative estimates of collective geo-tagged human activities in response to typhoon Hato using location-aware big data |
| title_full | Quantitative estimates of collective geo-tagged human activities in response to typhoon Hato using location-aware big data |
| title_fullStr | Quantitative estimates of collective geo-tagged human activities in response to typhoon Hato using location-aware big data |
| title_full_unstemmed | Quantitative estimates of collective geo-tagged human activities in response to typhoon Hato using location-aware big data |
| title_short | Quantitative estimates of collective geo-tagged human activities in response to typhoon Hato using location-aware big data |
| title_sort | quantitative estimates of collective geo tagged human activities in response to typhoon hato using location aware big data |
| topic | human response typhoon natural disaster location-aware data rapid disaster assessment |
| url | http://dx.doi.org/10.1080/17538947.2019.1645894 |
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