By:
Sarah Antos, World Bank and Syed Raza, Digital Impact Alliance
| 12.21.2017
Read Time:
4 minutes
How will satellites change the world?
DigitalGlobe has made sustainable development a key priority. Whether it’s automated mapping of millions of households across the world or uncovering lost archaeological sites from ancient civilizations, DigitalGlobe continues to put our technology at work to See a better world.
That said, there is still so much untapped potential in using satellite imagery to solve global development and humanitarian questions. And since DigitalGlobe has the keys to the time machine, we’re unlocking our 100+ petabyte imagery library to spur even more innovation in support of the Sustainable Development Goals.
DigitalGlobe, with support from Amazon Web Services, has launched our GBDX for Sustainability Challenge. As part of the Challenge, DigitalGlobe is looking for new ideas to address some of the world’s most pressing challenges from food security to disaster response to poverty elimination and more. Teams should submit their concept notes by January 12 to be considered. Select teams will be awarded access to our geospatial big data platform, GBDX, and our image library over the course of two months to realize their projects. For more information and how to apply for the Challenge, check out our website.
Concept notes will be reviewed by a panel of expert judges from USAID, Gates Foundation, World Economic Forum, Digital Impact Alliance, and the World Bank. We recently caught up with two of our judges, Sarah Antos from the World Bank’s Geospatial Operational Support Team and Syed Raza from the Digital Impact Alliance, on their thoughts about the Challenge.
What are some of the ways the World Bank is using geospatial big data/satellite imagery/machine learning?
I am part of the Geospatial Operational Support Team (GOST) at the Bank, and we are just beginning to explore ways in which we can use GBDX- to predict rural roads, count rooftops, estimate poverty, and detect land cover change in special economic zones, to name a few. In a new project, we are experimenting with the car counter algorithm to detect passenger cars vs large buses or trucks. We then compare that vehicle count to pollution data collected around the city on the same day. Using this data, we plan to explore the relationship between vehicle density and pollution levels. – Sarah
What are some of the ways DIAL is using geospatial big data/satellite imagery/machine learning?
We are utilizing geospatial data and/ or doing geospatial data analysis on a number of projects. As of right now the focus is on population estimations per catchment area, with the goal of developing public services. We are also utilizing satellite imagery to inform some of our crop modeling work, and development of yield estimations based on population movements and imagery analytics. – Syed
What’s your favorite kind of data to integrate/analyze alongside satellite imagery?
I am really interested in how people will start integrating street view images with satellite images. Both sources seem to be getting better and better at creating 3D models of the environment around us, and as the price of such technology begins to drop – I think we will see more innovative combinations. – Sarah
What do you find most valuable about the GBDX platform for sustainability initiatives?
I think the power of GBDX is its ability to measure change overtime. Given the size of the imagery archive, and the relatively low cost of processing large amounts of data, GBDX gives us an opportunity to scale up our smaller pilot projects. – Sarah
The UN called for a “data revolution” to support the SDGs – how do you think we’re doing so far?
There is momentum but we have some ways to go. There is too much fragmentation amongst data communities and we haven’t ensured private sector participation in the same manner as other sectors have. And then – there is the overall capacity issue. – Syed
What types of projects would you like to see come out of the Challenge?
Use cases for geospatial and mobile network data – data fusion, data integration, combined analytics/ visualizations, etc. Common standards (input and output formats) for using geospatial data – Syed
I would love to see examples of case studies that I had previously thought were impossible. I want to be proven wrong! – Sarah