Using Twitter for tasking remote-sensing data collection and damage assessment: 2013 Boulder flood case study

TLDR

Remote‑sensing imagery is critical for assessing damage during large‑scale environmental hazards such as hurricanes and severe weather. The study presents a method that uses social‑media data to prioritize remote‑sensing image collection during disasters. The approach monitors Twitter in real time to task commercial satellites for high‑resolution imagery, then fuses those images with social‑media and other data to evaluate transportation infrastructure damage, as shown in the 2013 Colorado floods.

Abstract

A new methodology is introduced that leverages data harvested from social media for tasking the collection of remote-sensing imagery during disasters or emergencies. The images are then fused with multiple sources of contributed data for the damage assessment of transportation infrastructure. The capability is valuable in situations where environmental hazards such as hurricanes or severe weather affect very large areas. During these types of disasters it is paramount to 'cue' the collection of remote-sensing images to assess the impact of fast-moving and potentially life-threatening events. The methodology consists of two steps. First, real-time data from Twitter are monitored to prioritize the collection of remote-sensing images for evolving disasters. Commercial satellites are then tasked to collect high-resolution images of these areas. Second, a damage assessment of transportation infrastructure is carried out by fusing the tasked images with contributed data harvested from social media such as Flickr and Twitter, and any additional available data. To demonstrate its feasibility, the proposed methodology is applied and tested on the 2013 Colorado floods with a special emphasis in Boulder County and the cities of Boulder and Longmont.