Abstract: Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general

Land-management options for greenhouse gas removal (GGR) include afforestation or reforestation (AR), wetland restoration, soil carbon sequestration (SCS), biochar, terrestrial enhanced weathering (TEW), and bioenergy with carbon capture and storage (BECCS). We assess the opportunities and risks associated with these options through the lens of their potential impacts on ecosystem services (Nature's Contributions to People; NCPs) and the United Nations Sustainable Development Goals (SDGs). We find that all land-based GGR options contribute positively to at least some NCPs and SDGs. Wetland restoration and SCS almost exclusively deliver positive impacts. A few GGR options, such as afforestation, BECCS, and biochar potentially impact negatively some NCPs and SDGs, particularly when implemented at scale, largely through competition for land. For those that present risks or are least understood, more research is required, and demonstration projects need to proceed with caution. For options that present low risks and provide cobenefits, implementation can proceed more rapidly following no-regrets principles.