Big Pixel Initiative Develops Remote Sensing Analysis

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Researchers at the University of California San Diego’s Big Pixel Initiative are using unique tools to map urban areas around the globe, potentially revolutionizing large-scale analysis of urbanization. Using Google Earth Engine, they developed and tested new machine-learning approaches that use high-resolution satellite data to detect and map settlements around the world.

These methods will allow for the creation of a high-resolution map of all inhabited locations and for a better understanding of how cities expand and evolve. They provide, for the first time, a reliable and comprehensive open-source data for detecting and mapping urban areas through satellite images.

With the hope to provide a tool that can identify urbanization and industrialization to other researchers, the authors found there is currently no reliable open-source dataset to automatically detect urban areas and to validate the existing maps that currently exist. They explain that urbanization is a fundamental force that shapes almost all dimensions of the modern world, from land cover and land use around cities to economics and policy making. However, the rate and magnitude of these changes have not yet been mapped globally with sharp precision.

Goldblatt and the team constructed a unique dataset of 21,030 manually classified image samples representing different forms of built-up and not built-up land cover in India. These samples were then used for supervised image classification designed to detect urban areas, performing the analysis in cloud-based Google Earth Engine. Their goal in part is to use high-resolution satellite-data to create a continuous map of the urbanization process; for the first time looking extensively over time and over large-scale areas.

Founded by Hanson and Albert Yu-Min Lin of the Qualcomm Institute, the Big Pixel Initiative’s mission is to develop advanced geospatial capacity to address the world’s greatest challenges. The initiative was launched in 2015 by unique, two-year access to DigitalGlobe Foundation data, and then expanded to include analysis on the Google Earth Engine platform.

In working with geoscientists across campus and experts at Google, Hanson is leading the university’s efforts to measure urbanization worldwide using satellite imagery. “We want to be able to measure how cities grow and expand on the whole planet as closest to real time as we can, by using the vast amounts of satellite imagery that are coming online,” Hanson said.

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