Indicator based upon the Land-Use Harmonization 2 (LUH2) gridded global land use maps produced by advanced Earth System Models (ESM) which model the combined pressures of land use conversion and fossil fuel emissions on the carbon-climate system (Hurtt et al. in prep). The pressure data is derived from the History Database of the Global Environment (HYDE). Primary vegetation is defined as natural vegetation (either forest or non-forest) that has never been impacted by human activities (e.g. agriculture or wood harvesting) since the start of the time series (850). However, such areas may be indirectly impacted by humans, for instance, through hunting, pollution or the introduction of invasive alien species. They still represent modelled estimates, and the uncertainty associated with the land use present within each particular grid cell increases as we step back in time through the series.

WorldClim version 2 has average monthly climate data for minimum, mean, and maximum temperature and for precipitation for 1970-2000. You can download the variables (minimum temperature (°C), maximum temperature (°C), average temperature (°C), precipitation (mm), solar radiation (kJ m-2 day-1), wind speed (m s-1) and water vapor pressure (kPa)) for different spatial resolutions, from 30 seconds (~1 km2) to 10 minutes (~340 km2). Each download is a "zip" file containing 12 GeoTiff (.tif) files, one for each month of the year (January is 1; December is 12).

Future climate projections from the World Climate Research Programme's (WCRP's) CMIP3 multi-model dataset downscaled using the Worldclim 2.5-minute 20th century climate dataset. The CMIP3 multi-model datasets were used for the IPCC 4th Assessment Report. The B1 scenario assumes the most ecologically friendly future. The A1B scenario assumes future energy sources will be balanced between fossil-intensive and non-fossil energy sources. The A2 scenario is characterized by a future world still heavily dependent on fossil fuel consumption. All models are historical and future climate simulations collected from leading modeling centers around the world. The original model simulations are collected and achieved by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) to create the World Climate Research Programme's (WCRP's) phase 3 of the Coupled Model Intercomparison Project (CMIP3) multi-model dataset. The downscaled data were produced by Conservation International through collaboration with the Department of Geography, Center of Climatic Research, and Land Tenure Center at the University of Wisconsin and support from the National Center of Ecological Analysis and Synthesis.

The first 30 m resolution global land cover data set with 10 classes and for the year 2000 and 2010. Global Land Cover (GLC) information is fundamental for environmental change studies, land resource management, sustainable development, and many other societal benefits. Although GLC data exists at spatial resolutions of 300 m and 1000 m, a 30 m resolution mapping approach is now a feasible option for the next generation of GLC products. Since most significant human impacts on the land system can be captured at this scale, a number of researchers are focusing on such products. This paper reports the operational approach used in such a project, which aims to deliver reliable data products. Over 10,000 Landsat-like satellite images are required to cover the entire Earth at 30 m resolution. To derive a GLC map from such a large volume of data necessitates the development of effective, efficient, economic and operational approaches. Automated approaches usually provide higher efficiency and thus more economic solutions, yet existing automated classification has been deemed ineffective because of the low classification accuracy achievable (typically below 65%) at global scale at 30 m resolution. As a result, an approach based on the integration of pixel- and object-based methods with knowledge (POK-based) has been developed. Data citation: CHEN Jun et al.: 2015.Global land cover mapping at 30 m resolution: A POK-based operational approach. ISPRS Journal of Photogrammetry and Remote Sensing Volume 103, May 2015, Pages 7–27 http://dx.doi.org/10.1016/j.isprsjprs.2014.09.002 Available at: http://www.geodoi.ac.cn/WebEn/doi.aspx?Id=163