The Big Pixel Initiative is developing geospatial capacity to address our world’s greatest challenges at scale. Founded in partnership at UC San Diego’s Qualcomm Institute and School of Global Policy and Strategy, we have partnered with the DigitalGlobe Foundation to grow a living, learning laboratory related to everything spatial, to investigate and design best practices in geospatial data visualization, user experience interfaces, and design techniques for scientific discovery and decision-making.
The Big Pixel Team has partnered with the DigitalGlobe Foundation to explore academic uses for their Global Base Map (GBM), a current high-resolution base map for the planet. This resource enables a unique opportunity to address large scale persistent challenges in the world by combining our assets in geospatial analysis, crowdsourced field data science, data design and visualization, cognitive science and computer graphics.
This initiative is designing research methods for scalable satellite image ingestion, processing, computing and visualization for the next generation of global change research in geospatial big data. We are developing tools in computer vision, machine learning, GIS, remote sensing and crowd-sourcing.
More and more we have the need for dynamic interactive analysis; less pre-digested static results and more interactive visualizations. The design for this lab is growing a living, learning collaborative lab for researchers to perform inherently multidisciplinary research, which will be driven by the evident need by our partners to create this space, cultivating design and function together. Our pilot projects are in the fields of public health, economics and ecology.
Hogeun Park, Postdoctoral Fellow, GPS
Over the last two decades, India has experienced rapid development of infrastructure. While this trend has been continued, our understanding of the impacts of new infrastructures has not been fully developed yet. In this research, particularly, we focused on addressing “Do roads increase or decrease divergence in economic outcomes within and between urban markets? To address this question, we utilize diverse approaches including Geographical Information System (GIS), Remote Sensing (RS), and econometrics. By synthesizing multiple methods, we re-visited the old question in economic geography.
Hogeun Park, Postdoctoral Fellow, GPS
While frequency and severity of extreme climate events have been intensified, our understanding of how these climate events affect human society is limited. By using cases of Hurricane in the Southern part of US from 2000 and present, we aimed to understand how different socio-economic factors and extreme climate events interact. Further, we proposed to develop a model to understand different resiliency contingent on different socio-economic characteristics. Through the interdisciplinary approaches combining Satellite imagery, Census, and multiple auxiliary spatial data, our research is enabled to explore the impacts of extreme climate events across multiple spatiotemporal scales.
Ran Goldblatt, postdoctoral researcher, School of Global Policy and Strategy
With satellite imagery and cloud-based computational platforms, Ran Goldblatt builds maps to confirm that land cover indicates urbanization, across space and time. Beginning with India, Goldblatt has built a new dataset consisting of 21,030 polygons that he manually classified as “built-up” or “not built-up,” and these categories are used for image classification and detection of urban areas. This data is then analyzed in Google Earth Engine, including also boundaries of built-up areas against the intensity of nighttime light. The goal is to geocode a database of all public and private businesses in India to analyze the relationship between industrialization and urbanization.
Kilian Heilmann Ph.D. candidate, Department of Economics; Diego Vera-Cossio, Ph.D. candidate, Department of Economics; and Wei You, Ph.D. candidate, Department of Economics
Employing high-resolution satellite imagery, Kilian Heilmann, Diego Vera-Cossio and Wei You identify and measure the growth of slums around the world, caused by rapid urbanization in developing countries that pulls millions of migrants into low-quality, informal housing settlements with limited access to public services. Despite widespread study of urbanization, little is known about the extent and the growth of these vibrant urban zones. This project aims to provide researchers with consistent data on urban development over time that allow the study of slums at a global scale and the formulation of policies to alleviate poverty.
Ran Goldblatt, postdoctoral researcher, School of Global Policy and Strategy; Victoria Xie, Ph.D. candidate, Department of Economics
How did the global commodity boom of the 2000s affect land use and forest management around the world? Because the mines that are the source of these commodities often are in remote locations, little is known about the connection between mineral extraction and the surrounding environment. So far, the relation between mining activities and land cover dynamics has been addressed mostly through local observational analysis. In this project, Global Policy and Strategy researchers employ a spatial and temporal lens, by collecting proprietary data on more than 30,000 mines located around the world and matching the location of these mines to high-resolution satellite imagery from the year 2000 forward. This allows a granular study of the relationship between exploration of different mining commodities and loss of forest cover worldwide, as well as the spatial distribution of global mines in relation to changes in land use patterns, socio-economic variables and other physical attributes.
David Kline, associate project scientist, Scripps Institution of Oceanography (SIO); Robert Frouin, research scientist, SIO; Daniel Conley, Ph.D. candidate, SIO; Gordon Hanson, professor, School of Global Policy and Strategy; Ran Goldblatt, postdoctoral researcher, School of Global Policy and Strategy; Di Dai, research assistant, School of Global Policy and Strategy
David Kline and his colleagues are all eyes—via remote sensing—on what the National Oceanic and Atmospheric Administration recently declared the third large-scale coral bleaching event in recorded history. By use of satellite imagery, the team aims to replace the current, highly labor-intensive monitoring practices with a mapping of shallow reefs from space. The goal is to develop tools to quantify bleaching episodes through remote sensing (i.e., satellite imagery) and then to build detection algorithms that help estimate the extent and severity of bleaching, with hopes to transform coral reef management and conservation.
Jennifer Burney, assistant professor, School of Global Policy and Strategy
Using high-resolution satellite imagery and advanced big data analysis tools, Jennifer Burney is turning to the trees to gauge the health of semi-arid ecosystems, which are home to the world’s poorest populations and areas most affected by climate change. Prototyping this assessment tool in Sertão, Brazil, Burney develops tree density maps for a specified region that will then be “ground-truthed” and linked to farm-level management data. The ultimate goal is to use this novel technique across the world’s semi-arid regions to provide high-resolution indicators of overall ecosystem health, and to help identify best locations for joint productivity and conservation interventions.
Director, Big Pixel
Jennifer Burney is an environmental scientist whose research focuses on simultaneously achieving global food security and mitigating climate change. She designs, implements and evaluates technologies for poverty alleviation and agricultural adaptation, and studies the links between “energy poverty” — the lack of access to modern energy services — and food or nutrition security, the mechanisms by which energy services can help alleviate poverty, the environmental impacts of food production and consumption, and climate impacts on agriculture.