The natural world has multiple, sometimes conflicting, sometimes synergistic, values to society when viewed through the lens of the Sustainable Development Goals (SDGs), Spatial mapping of nature's contributions to the SDGs has the potential to support the implementation of SDG strategies through sustainable land management and conservation of ecosystem services. Such mapping requires a range of spatial data. This paper examines the use of remote sensing and spatial ecosystem service modelling to examine nature's contribution to targets under SDG 6, also highlighting synergies with other key SDGs and trade-offs with agriculture. We use a wide range of remotely sensed and globally available datasets (for land cover, climate, soil, population, agriculture) alongside the existing and widely used spatial ecosystem services assessment tool, Co$tingNature. With these we identify priority areas for sustainable management to realise targets under SDG 6 (water) at the country scale for Madagascar and at the basin scale for the Volta basin, though the application developed can be applied to any country or major basin in the world. Within this SDG 6 priority areas footprint, we assess the synergies and trade-offs provided by this land for SDG 15 (biodiversity) and SDG 13 (climate action) as well as SDG 2 (zero hunger). Results highlight the co-benefits of sustainably managing nature's contribution to SDG 6, such as the protection of forest cover (for SDG target 15.2), carbon storage as a contribution to the Paris climate agreement and nationally determined contributions (SDG 13) and biodiversity (for SDG target 15.5) but also trade-offs with the zero hunger goal (for SDG 2). Such analyses allow for better understanding of land management requirements for realising multiple SDGs through protection and restoration of green infrastructure. We provide a freely available tool, within the Co$tingNature platform, based on a variety of remotely sensed products, that can be used by SDG practitioners to carry out similar analyses and inform decision-making at national or sub-national levels globally.
Remote Sensing of Environment, Volume 239, 15 March 2020,