25 November 2019
When the first Earthrise was televised just over 50 years ago, we humans saw what a fragile, shimmering bauble it is we cling to. Since then, images snapped in space and from satellites keep us updated on the biosphere’s progress under what, it has to be said, is our poor stewardship to date.
Consider the public and political outcry over the recent Amazon fires. Earth observation (EO) satellite data provided enough powerful authority to move public opinion, create new policies and, hopefully, it will also ultimately help better manage land use. Such valuable satellite images are also providing timely evidence of a plethora of land use changes that will help citizens and governments act to achieve the UN Sustainable Development Goals (SDGs).
To support action on sustainable development and climate change, EO data are being transformed into useful tools and services. According to Dmitry Shchepashchenko, an IIASA Ecosystems Services and Management Program researcher and coauthor of a comprehensive paper overviewing the new tools and services available to land watchers, the challenge is interpreting this overwhelming flow of data accurately.
“We use very high resolution (VHR) satellite imagery to keep an eye on Earth. The more free imagery is available, the better we can monitor and alert,” he says.
Low orbit is now filled with what are basically high-resolution cameras that are recording the planet’s changing patterns and informing us how Earth is being transformed moment to moment. The cost of acquiring these images has also been radically reduced since the 1970s and many are available to users at no cost.
A turn of the century engineering challenge – to fit a satellite in a box the size of a hand-sized toy – determined the diminutive size of many of these satellites. Its success resulted in the launch of thousands of tiny “CubeSats” that are inexpensive to make and launch. The basic ingredients are a camera, a smart phone processor, solar panels, and some batteries.
© NASA Goddard's Conceptual Image Lab/B. Monroe
Silicon Valley also has hundreds of cameras peering down on us, providing wider coverage and making it feasible to study all visible human activities and its impacts including deforestation, pollution, and congestion. All thanks to the new abundance of daily snapshots.
Human analysis and machine learning algorithms allow us to evaluate subtle info at scale. Key to processing this unprecedented volume of data are algorithms. It is these machine learning systems that are aiding us to decide if we are burning down the house, as it were. Such algorithms however need to be trained with the help of human input, which is where an army of crowd-sourced human eyes and brains come in.
“New sources of open satellite imagery have emerged over the last fifteen years and we use crowdsourcing, experts, and citizen scientists to map and monitor different things, including land cover and land use, human impact, and disasters,” notes Shchepashchenko.
This development has led to new tools for visual interpretation of VHR imagery such as Geo-Wiki, Collect Earth and more recently LACOWiki, which, according to Shchepashchenko’s findings, are collectively opening up the visual interpretation of satellite imagery to crowdsourcing and nonscientific use.
Director of the UN Office for Outer Space Affairs, Simonetta Di Pippo, agrees that these new tools and the satellites themselves are invaluable.
“The role of EO in supporting the achievement of the SDGs is huge. It helps monitor and evaluate the status of projects in remote or dangerous locations, contributing to efficiency in the use of anti-poverty resources. It provides early warnings about risks of food and water shortages, helps us track biodiversity, and hence to design better strategies for protecting it,” she says. “EO also monitors climate change, measuring variables such as the melting of ice, forest loss or desertification, along with environmental factors that contribute to the spread of diseases, and the extent of disease outbreaks.”
Deforestation in Brazil's Amazon rainforest. Left: 1992 Landsat image. Right: 2006 ASTER image of the same region. © NASA/GSFC/METI/ERSDAC/JAROS, and U.S./Japan ASTER Science Team
IIASA Acting Water Program Director Yoshihide Wada, for example, found satellite data an invaluable resource when investigating severe water stress in northern India. The results of his studies provide insight into better water management approaches for food and water security in the country.
“Outside of Europe, Japan, and the USA, there is very limited water use or hydrology data globally,” he says. “Satellite observations are filling this spatial gap as well as the real-time data for global coverage.”
Left: Changes in the monsoon season precipitation (mm) during 1980–2013. Right: Cumulative departure of precipitation from long-term mean (1980–2013) for 2002–2013.
Because of serious depletion of groundwater, India is facing poor water quality and severe food security issues. By analyzing local well data over the last decade in tandem with satellite studies of monsoon patterns, Wada and his team found that groundwater storage has declined in northern India at the rate of one or two centimeters per year between 2002 and 2013. For the first time, the study also found a link between the declining rains in the North and Indian Ocean warming. According to the paper, groundwater storage will decline as temperatures rise in the ocean.
“Satellite observation will be a key tool to monitor water resources like groundwater in India where the data is not readily available. However, the satellite orbits are far, which makes spatial accuracy rather poor,” he says. “It is expected that this will improve, but it will take time. It is important to have on site measurements to verify the satellite observations at some locations.”
Vital in the arsenal in the fight to keep the biosphere human-friendly, IIASA is helping to weaponize such images to halt biosphere destruction. Without such data, we would truly be in the dark.
By Michael Fitzpatrick
Last edited: 20 November 2019
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Schepaschenko D ORCID: https://orcid.org/0000-0002-7814-4990, See L, Lesiv M, Bastin J-F, Mollicone D, Tsendbazar N-E, Bastin L, McCallum I, et al. (2019). Recent Advances in Forest Observation with Visual Interpretation of Very High-Resolution Imagery. Surveys in Geophysics 40 (4): 839-862. DOI:10.1007/s10712-019-09533-z.
Asoka A, Gleeson T, Wada Y ORCID: https://orcid.org/0000-0003-4770-2539, & Mishra V (2017). Relative contribution of monsoon precipitation and pumping to changes in groundwater storage in India. Nature Geoscience 10 (2): 109-117. DOI:10.1038/ngeo2869.
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