AUTHOR=Halabisky Meghan , Yuan Fang , Adimou Ghislain , Birchall Eloise , Boamah Edward , Burton Chad , Chong Ee-Faye , Hall Lisa , Jorand Cedric , Leith Alex , Lewis Adam , Mamane Bako , Mar Fatou , Moghaddam Negin , Ongo David , Rebelo Lisa-Maria 

TITLE=A dynamic surface water extent service for Africa developed through continental-scale collaboration

JOURNAL=Frontiers in Environmental Science

VOLUME=12

YEAR=2024

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2024.1251315

DOI=10.3389/fenvs.2024.1251315

ISSN=2296-665X

ABSTRACT=<p>Spatially explicit, near real time information on surface water dynamics is critical for understanding changes in water resources, and for long-term water security planning. The distribution of surface water across the African continent since 1984 and updated as every new Landsat scene becomes available is presented here, and validated for the continent for the first time. We applied the Water Observations from Space (WOfS) algorithm, developed and well-tested in Australia, to every Landsat scene acquired over Africa since the mid 1980s to provide spatial information on surface water dynamics over the past 30+ years. We assessed the accuracy of WOfS using aerial and satellite imagery. Four regional geospatial organisations, coordinated through the Digital Earth Africa Product Development Task Team, conducted the validation campaign and provided both the regional expertise and experience required for a continental-scale validation effort. We assessed whether the point was wet, dry, or cloud covered, for each of the 12 months in 2018, resulting in 34,800 labelled observations. As waterbodies larger than 100 <inline-formula id="inf1"><mml:math id="m1" xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mrow><mml:mi mathvariant="normal">k</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> are easy to identify with Landsat resolution data and can thus boost accuracy, these were masked out. The resulting overall accuracy of the water classification was 82%. WOfS in Africa is expected to be used by ministries and departments of agriculture and water across the continent, by international organisations, academia, and the private sector. A large-scale collaborative effort, which included regional and technical skills spanning two continents was required to create a service that is regionally accurate and is both hosted on, and implemented operationally from, the African continent.</p>