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first published week of: 10/16/2017
Satellite imagery of Puerto Rico, before and after Hurricane Maria
After the winds and rains of Hurricane Maria swept through Puerto Rico, the island was left in darkness. Electrical power generation was cut for 100 percent of households, cell phone towers went offline, and the airport and other ports closed operations, pending damage and safety reviews. In the days that followed, many municipalities, particularly in the interior, were entirely out of contact.
How severely were they affected? Had the flood waters receded? Were structures still intact?
Direct Relief regularly supports the network of non-profit Federally Qualified Health Centers (FQHCs) in Puerto Rico, which often serves the role of first responder for low-income and uninsured people in times of disaster.
Deploying Digital Humanitarians
One of the first, somewhat experimental, steps was to expand Direct Relief’s analytics and mapping capacity by activating the Digital Humanitarian Network (DHN). The DHN is a confederation of professionals working in humanitarian aid, data analytics and information technology, which helps ensure a reasonably efficient process for building response capacity with digital volunteers.
In this case, DHN was acting as the managing connection for humanitarian agencies to Planet, one of the world’s leading remote sensing companies. Planet operates a network of small satellites that capture images of Earth’s land area every single day. It was also one of the first sources of data for determining post-hurricane conditions in Puerto Rico.
Remote sensing is the use of non-localized sensor technology, usually a camera, to collect data and analyze conditions at some point on the planet’s surface. If you’re unable to be physically present to observe an area, then it may still be possible to use orbital or other technologies to examine it from a great distance. Planet has built a fluid online interface that allows users to filter and select imagery based on the type of sensors available, the amount of cloud cover in the imagery, the data and time it was taken, and the proportion of an area of interest covered by that single image. By dragging and dropping images into an online comparison tool, we could determine at least general conditions in that place relative to a pre-storm, undamaged baseline image.
Read full story at Direct Relief…