2021
DOI: 10.1111/area.12719
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The utility of Google Trends as a tool for evaluating flooding in data‐scarce places

Abstract: Google Trends (GT) offers a historical database of global internet searches with the potential to complement conventional records of environmental hazards, especially in regions where formal hydrometeorological data are scarce. We evaluate the extent to which GT can discern heavy rainfall and floods in Kenya and Uganda during the period 2014 to 2018. We triangulate counts of flood searches from GT with available rainfall records and media reports to build an inventory of extreme events. The Spearman rank corre… Show more

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Cited by 21 publications
(9 citation statements)
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References 37 publications
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“…Without improvements in urban drainage systems and development control, these would translate into more frequent surface water floods. Future research could explore the use of social media and crowdsourced flood information to stratify downscaling predictors and extreme rainfall events (Wang et al 2018;Thompson et al 2022). With longer and more accurate media records, it may be possible to develop more skilful downscaling of extreme rainfall linked to floodgenerating episodes.…”
Section: Discussionmentioning
confidence: 99%
“…Without improvements in urban drainage systems and development control, these would translate into more frequent surface water floods. Future research could explore the use of social media and crowdsourced flood information to stratify downscaling predictors and extreme rainfall events (Wang et al 2018;Thompson et al 2022). With longer and more accurate media records, it may be possible to develop more skilful downscaling of extreme rainfall linked to floodgenerating episodes.…”
Section: Discussionmentioning
confidence: 99%
“…(2017) demonstrate the utility of machine learning for linking drought impacts and metrics which could potentially better handle the complex, multithreshold relationships found here, including accounting for nonbinary impact series. Other impact datasets could be explored to supplement use of newspaper articles including historical inventories, such as harvest volumes, and/or records of impacts on online social media platforms such as Twitter, which facilitates a near real‐time analysis of impacts as has been demonstrated for flooding events (Basnyat et al ., 2017; Thompson et al ., 2021). Our analysis has shown that drought indices and article counts do not always coincide (as was the case for the 1945 and 1921 droughts).…”
Section: Discussionmentioning
confidence: 99%
“…Big data technologies can be used to assess the perception of risk in the population and stimulate preparedness measures such as the purchase of insurance policies to compensate for losses [62]. This could be achieved by analyzing data coming from various sources, such as social media (Facebook, Twitter), machine learning, crowdsourcing, sensors, and disaster organizations within a country, using big data technologies.…”
Section: Discussionmentioning
confidence: 99%