Woods Hole, March 11th, 2022.
New Data Set Reveals Changing Face of Earth Over the Course of One Year in Unprecedented Detail
A new set of satellite radar derived images provide a novel view of the face of Earth in unprecedented detail, advancing understanding of natural and human changes that occur over the course of a year. Such information is crucial to improve decision-making at regional, national, and international levels, and to disaster planning and preparedness.
The data and images from the European Space Agency’s Sentinel 1A and 1B satellites and its analysis is being published in the Nature journal Scientific Data on Friday, March 11, by a team of scientists and engineers at Earth Big Data, LLC; Gamma Remote Sensing AG; NASA’s Jet Propulsion Laboratory (JPL); University of Houston; and NASA Goddard Space Flight Center.
“This is Earth as we’ve never seen it before,” said Josef Kellndorfer, founder of Earth Big Data, LLC, and lead author of the study. “This level of detail will enable a far more nuanced understanding of how our planet is changing throughout the year and beyond.”
Image 1: A false-color representation of the new Sentinel-1 data set depicts median seasonal backscatter of two SAR bands in red and green, and the global interferometric coherence measure in blue. Land dominated by vegetation (forests and seasonally active agricultural areas) appears green and deserts and permanent scatterers such as urban areas appear red and yellow. Seasonally shifting agricultural boundaries and phenologically wet regions are visible by comparing changes between images. (Earth Big Data 2021, contains modified Copernicus Data 2019-2020, processed by ESA.)
Image 2: A subset of the global Sentinel-1 data set shows the city of Paris (upper left of each image) and the seasonal interferometric coherence measure that, in the winter months over short periods, reveals high correlation (high coherence) for the agricultural land around Paris, while in the summer months, especially over longer time spans, the agricultural change from growing vegetation leads to low temporal correlation (low coherence) of subsequent images. As a result, the infrastructure of urban areas and permanent structures can readily be mapped, as can areas of agricultural activity that de-corelate quickly in time as vegetation grows. (Earth Big Data 2021, contains modified Copernicus Data 2019-2020, processed by ESA.)