On October 24, 2012, while the country was still recovering from the 2010 earthquake and cholera outbreak, heavy rains associated with Hurricane Sandy struck Haiti. The country was hit hard by three days of continuous rains: the Grey river in Port-au-Prince, among others burst its banks, houses were destroyed and at least 54 people died during the storm.
Readily operational, the International Organization for Migration (IOM) and the OpenStreetMap Community of Haiti (COSMHA) reacted promptly to the disaster. Both had a local response capacity in place: IOM to support the ongoing relief work following the earthquake, COSMHA because it is a locally based community of Haitian volunteers. One of the first actions was to assess the extent of damage. As soon as the area was accessible (on Sunday, 28 October, four days after the beginning of the emergency), the teams deployed an IOM drone for a damage assessment over two communes along the Grey River. Applying a before-and-after comparison methodology, they precisely evaluated the damages in the flood zone.
The Aerial Imagery Reconnaissance Unit, known as the AIR Unit is the only one of its kind in the world. The AIR Unit responds to incidents on a nearly daily basis, from aerial imaging of incidents to carrying out search and rescue with thermal cameras.
To determine if a drone would add value to the firefighting teams and gauge whether or not it was possible to justify the cost, the GMFRS began by running an initial trial with a drone and a few trained pilots. The GMFRS initially had temporary contracts with drone companies to lease equipment. Firefighters were trained to operate the drone and analyse the data collected.
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Between May and June 2014, the RMA team deployed MD4-1000 Multicopter Microdrones along with two types of sensors—a high-resolution digital camera and a near infrared (NiR) camera. The microdrone has a flight time of up to 88 minutes (depending on load and battery) and a flight radius of up to 40 kilometres.
The RMA team logged a total of 20 flights (both manual and autonomous) from 13 locations in urban and semi-urban areas. The flight times ranged from 25 to 30 minutes and captured 200 to 500 images at a resolution of 2-5 cm on each flight. The temperature ranged from 20°C to 25°C with a maximum wind speed of up to 7 metres per second where the flights were carried out. Flights were rescheduled when wind speeds reached more than 12 metres per second. The team did not map the entire risk area since the size of the suspected hazardous area before the disaster was 1 207 square kilometres.
One of the main challenges to planning and post-disaster recovery activities in Nepal is that the quality of readily available satellite imagery is too low to really be useful given how dense Kathmandu and other cities are. Among others, the Nepali organization Kathmandu Living Labs has been interested in exploring the possibility of getting imagery at much higher spatial resolution much more frequently without being dependent on an external company that may or may not provide the satellite imagery at a discount. At the same time, Kathmandu University has been experimenting with the use of drones for agricultural purposes and other specific mapping tasks such as mapping of landslides, so there has been an ongoing interest in exploring alternative mapping solutions in Nepal.
After the 7.8 earthquake in 2015, the lack of high-resolution and up-to-date imagery became much more acute as communities and non-governmental organizations worked with images of insufficient quality. This case study focuses on the benefits that were derived from a mapping exercise that was conducted in Panga as part of a three-day training organized by UAViators in collaboration with Kathmandu University and Kathmandu Living Labs. Initially, UAViators and their technology partners became involved with the aim of providing training sessions and field missions using mapping drones and to demonstrate the potential of drones for humanitarian use. Following the local advice from Kathmandu University staff, the field activities focused on mapping Panga, which was particularly affected by the earthquake. Earthquake damage rendered 578 out of 1 334 buildings uninhabitable, and left 310 families living in corrugated galvanized iron sheet temporary shelters.