Quick Response for Emergency Mapping - 65 km2 Mapped in Two Days

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Quick Response for Emergency Mapping - 65 km2 Mapped in Two Days

When flash floods and heavy rainfall struck the Eastern Front of the UAE, the Al Ain Municipality commissioned FEDS to map the flood-affected areas. Flash floods cause damage to buildings, infrastructure, and local flora and fauna. Drones provide excellent visibility with exceptional data accuracy and can obtain this data in an extremely short amount of time. Using Drone data, Al Ain Municipality could quickly assess the affected areas and make informed decisions. With the greater visibility, they could plan and execute effective relief operations.
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Using Drone data, Al Ain Municipality could quickly assess the affected areas and make informed decisions. With the greater visibility, they could plan and execute effective relief operations.

Team FEDS had to survey and map a total of eight flood affected sites measuring 65 km2. One of the sites is Al Khaznah, a major highway that connects Al Ain to the capital Abu Dhabi, a massive corridor to map, measuring 50 km in length and 500 m in width.

Having to cover such an enormous corridor, our team used senseFly eBeeX fixed-wing drones. Our highly experienced drone team selected this drone for its customized Corridor Mapping feature; using this we could reduce the flight time by 30%. Time in this project was incredibly valuable as the mapping needed to be completed in the fastest time possible to preserve data integrity.

A significant outcome of flood mapping is identifying low lying areas where the flood water will flow towards and collect. In the event of another flood, the low lying areas would be affected the most, and action must be taken to mitigate that risk. The FEDS team had a limited amount of time to capture this data since the pools of water would disperse quickly and if delayed too long they low lying areas would be unidentifiable. 


Our highly experienced drone team use eBee X drone for its customized Corridor Mapping feature; using this we could reduce the flight time by 30%.

Using traditional surveying methods was out of the question. A survey by satellite would be expensive and inaccurate and conducting a terrestrial survey at a recently flooded area would be too dangerous. Mapping by drone would be the most effective solution to capture the data within a short amount of time available while ensuring high levels of accuracy.

Powered by preparation and backed up by experience, Team FEDS worked with determination and finished all eight areas’ flights within two days. It was a real challenge to cover huge sites within the short time period, but with our fleet of high-tech drones and team of experts, we could complete the project on time. The FEDS team concluded the Al Khaznah corridor with aGSD of 2 - 3 cm GSD, a horizontal accuracy up to 6 cm and a vertical accuracy of 9 cm with 18,335 total images.

Digital Surface Models (DSM) and Orthomosaic imagery were generated from the images collected then submitted to the clients. It was a challenge to preserve accuracy since photos taken of the floodwater from above would contain reflections that make stitching the images difficult, but with a touch of manual editing Team FEDS were able to process it without a hitch. Similar to the flight, the data is processed in batches respective to the sites. 



Corridor Map

Team FEDS provided the clients with detailed and high-resolution DSMs and Orthomosaic imagery using this the Al Ain Municipality could decisively assess problem areas and act accordingly. With the quick turnover and precise readings, the client was extremely satisfied to have the survey completed faster than ever before and with data that offered unparalleled visibility.

Without the inclusion of drone technology, it would have been impossible to have both quick and accurate data. It would have led to the flood being inaccurately analyzed, costing more in future damage due to inadequate mitigation and planning. Using Drone Technology, Team FEDS could map the flooding cost-effectively and capture data that is highly accurate and relevant.
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