Satellite imagery and data can help track population density, deforestation, housing availability, methane emissions, light pollution and more. But with over 6,000 currently active public satellites, the amount of data available can be overwhelming for researchers, and the computational power needed to process the imagery exceeds the capability of most commercially available computers.
Esther Rolf wants to change that. A postdoctoral fellow with the Harvard Data Science Initiative (HDSI) and Center for Research on Computation and Society (CRCS) at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), Rolf co-designed MOSAIKS, a system that combines machine learning with satellite imagery to sift through terabytes of data to easily and quickly generate net data sets and maps. MOSAIKS stands for “Multi-task Observation using Satellite Imagery and Kitchen Sinks,” referring to kitchen sink statistical regressions in which many variables are combined in a single analysis.
MOSAIKS is easy to access – all you need is an email address to register. A standard laptop can run it, and it currently has registered users from at least 18 countries and 48 academic institutions.
Rolf’s research recently received the United Nations’ “Strategic Development Goals Digital Gamechanger Award'' in the “Planet” category. The award recognizes digital products and technologies working to advance the UN’s Strategic Development Goals, a set of 17 objectives created in 2015 to guide global development over the ensuing 15 years. The goals include “no poverty,” “quality education,” “clean water and sanitation,” “affordable and clean energy,” “and sustainable cities and communities.”
@HCRCS