<![CDATA[Hydrometeorological disasters continue to increase, both in frequency and intensity, thereby necessitating rapid disaster information with high spatial resolution. Official data often requires a lengthy verification process, making it unable to fully capture on-the-ground conditions in detail at the time of the event. This study analyzes the spatiotemporal patterns of flash flood impacts based on Instagram crowdsourced data from the Pauh, Padang City. The method used is quantitative descriptive analysis, utilizing posts during the disaster period. The data was validated based on time, location, and content relevance, then analyzed using a Geographic Information System. The results show that Instagram is capable of recording the distribution of affected areas, the progression of disaster conditions, and community dynamics from the event phase through the post-disaster phase in a rapid, detailed, and contextual manner.]]>
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