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 are a key requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Crowdsourcing has been shown to provide accurate, timely and cost-effective data complementing traditional methods of in-situ data acquisition. Here we describe the global land cover and land use in-situ 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 of great relevance for the scientific community that is focused on calibration and validation of global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general.