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 Human Footprint (HFP) provides a measure of the direct and indirect human pressures on the environment globally in years 1993 and 2009. It is derived from remotely-sensed and bottom-up survey information compiled on eight measured variables. This represents not only the most current information of its type, but also the first temporally-consistent set of Human Footprint maps. Data on human pressures were acquired or developed for: 1) built environments, 2) population density, 3) electric infrastructure, 4) crop lands, 5) pasture lands, 6) roads, 7) railways, and 8) navigable waterways. Pressures were then overlaid to create the standardized Human Footprint maps for all non-Antarctic land areas. The Human Footprint maps find a range of uses as proxies for human disturbance of natural systems and can provide an increased understanding of the human pressures that drive macro-ecological patterns, as well as for tracking environmental change and informing conservation science and application. HFP values range from 0 (no human impact) to 50 (heavily human impacted).<br><br>See: <a href=""https://www.nature.com/articles/ncomms12558"">Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11</a>.<br/><br>Data can also be downloaded from <a href=""https://datadryad.org/resource/doi:10.5061/dryad.052q5"">Dryad<a/>.<br/>

This analysis of 35 years’ worth of satellite data (at approximately 25 square kilometer resolution at the equator) provides a comprehensive record of global land-change dynamics during the period 1982–2016. Contrary to the prevailing view that forest area has declined globally — tree cover has increased by 2.24 million km2 (+7.1% relative to the 1982 level), largely the result of a net loss in the tropics being outweighed by a net gain in the extratropics. Global bare ground cover has decreased by 1.16 million km2 (−3.1%), most notably in agricultural regions in Asia. Of all land changes, 60% are associated with direct human activities and 40% with indirect drivers such as climate change. Land-use change exhibits regional dominance, including tropical deforestation and agricultural expansion, temperate reforestation or afforestation, cropland intensification and urbanization. Consistently across all climate domains, montane systems have gained tree cover and many arid and semi-arid ecosystems have lost vegetation cover.<br><br>For full details see: <a href="https://doi.org/10.1038/s41586-018-0411-9">Song, X.-P., Hansen, M.C., Stehman, S.V., Potapov, P.V., Tyukavina, A., Vermote, E.F., Townshend, J.R., 2018. Global land change from 1982 to 2016. Nature 1</a><br/>.

EcoDRR global classification scheme based on spatial combination of ecosystem coverage and natural hazard physical exposure. The ecosystem data-set contains area percentage of each considered ecosystem in a 100 square kilometer cell. For a specific ecosystem, a 0.01 degree resolution raster of coverage real area is generated. In the case of forest coverage, the classification of the source datasets was grouped in three classes: woodland, open forest and closed forest. The quality of ecosystem in a 100 km2 grid cell is expressed as its area percentage, considering only cell land area for forest ecosystem. Sources: This dataset describes the current status of land areas that could potentially be forested according to climate (includes forest, open forest, woodlands). Intact forests and Fragmented/managed forests were not considered to need restoration. Potential forest lands that are currently non-forest were assumed to be deforested. Forest lands with significantly reduced canopy coverage were considered to be partially deforested (for example, potential closed forest with canopy coverage less than 45%). Both deforested and partially deforested lands considered to be restoration opportunity areas. Credit: Peter Potapov, Lars Laestadius, and Susan Minnemeyer. 2011. Global map of forest cover and condition. World Resources Institute: Washington, DC. Online at www.wri.org/forest-restoration-atlas.

The Generalized Normalised Difference Vegetation Index (GNDVI) is a modification of the Normalised Difference Vegetation Index (NDVI), which has been proposed by Weicheng Wu (2014) for the assessment of dryland environments due to the inadequacy of the NDVI in these areas. The Generalised Normalised Difference Vegetation Index (GNDVI) 2010 presents a wider outlook of the environmental effects of illegal artisanal small-scale gold mining (galamsey) in the Northwest region of Ghana. However, vegetation displacement in the area cannot entirely be attributed to galamsey. There has been a fast urban growth that is leading to vegetation clearance. The question is, can the trends of urban growth and vegetation depletion be associated to illegal mining? These are some of the scientific questions that these data will help to address. This notwithstanding, how could the looming large-scale gold mining excerbate the observed trends of environmental and land cover change in the Northwest region of Ghana? These data help to address all these relevant questions.

This shows a decade landscape perspective of the emerging Northwest mining region after the Rio De Jeneiro Conference on Sustainable Development with a focus on environmental resources. This data would highlight the appreciable contributions of illegal mining and the begining of large-scale exploration activities in the area. The trends and patterns of these actitivities' interactions with biodiversity can be observed and monitored for impact remediation in the area. The environmental responsiveness and mining generating carbon stock concentrations can be monitored as well. The activities of illegal mining in relation to the environment, water and vegetation can be tracked and regulated.

List of GRID core datasets

The Shuttle Radar Topography Mission (SRTM) was flown aboard the space shuttle Endeavour February 11-22, 2000. The National Aeronautics and Space Administration (NASA) and the National Geospatial-Intelligence Agency (NGA) participated in an international project to acquire radar data which were used to create the first near-global set of land elevations. Endeavour orbited Earth 16 times each day during the 11-day mission, completing 176 orbits. SRTM successfully collected radar data over 80% of the Earth's land surface between 60° north and 56° south latitude with data points posted every 1 arc-second (approximately 30 meters). SRTM 1 Arc-Second Global elevation data offer worldwide coverage of void filled data at a resolution of 1 arc-second (30 meters) and provide open distribution of this high-resolution global data set. Some tiles may still contain voids. Users should check the coverage map in EarthExplorer to verify if their area of interest is available. Please note that tiles above 50° north and below 50° south latitude are sampled at a resolution of 2 arc-second by 1 arc-second.

EcoDRR global classification scheme based on spatial combination of ecosystem coverage and natural hazard physical exposure. The ecosystem data-set contains area percentage of each considered ecosystem in a 100 square kilometer cell. For a specific ecosystem, a 0.01 degree resolution raster of coverage real area is generated. In the case of forest coverage, the classification of the source datasets was grouped in three classes: woodland, open forest and closed forest. The quality of ecosystem in a 100 km2 grid cell is expressed as its area percentage, considering only cell land area for forest ecosystem. Sources: This dataset describes the current status of land areas that could potentially be forested according to climate (includes forest, open forest, woodlands). Intact forests and Fragmented/managed forests were not considered to need restoration. Potential forest lands that are currently non-forest were assumed to be deforested. Forest lands with significantly reduced canopy coverage were considered to be partially deforested (for example, potential closed forest with canopy coverage less than 45%). Both deforested and partially deforested lands considered to be restoration opportunity areas. Credit: Peter Potapov, Lars Laestadius, and Susan Minnemeyer. 2011. Global map of forest cover and condition. World Resources Institute: Washington, DC. Online at www.wri.org/forest-restoration-atlas.

This analysis of 35 years’ worth of satellite data (at approximately 25 square kilometer resolution at the equator) provides a comprehensive record of global land-change dynamics during the period 1982–2016. Contrary to the prevailing view that forest area has declined globally — tree cover has increased by 2.24 million km2 (+7.1% relative to the 1982 level), largely the result of a net loss in the tropics being outweighed by a net gain in the extratropics. Global bare ground cover has decreased by 1.16 million km2 (−3.1%), most notably in agricultural regions in Asia. Of all land changes, 60% are associated with direct human activities and 40% with indirect drivers such as climate change. Land-use change exhibits regional dominance, including tropical deforestation and agricultural expansion, temperate reforestation or afforestation, cropland intensification and urbanization. Consistently across all climate domains, montane systems have gained tree cover and many arid and semi-arid ecosystems have lost vegetation cover.<br><br>For full details see: <a href="https://doi.org/10.1038/s41586-018-0411-9">Song, X.-P., Hansen, M.C., Stehman, S.V., Potapov, P.V., Tyukavina, A., Vermote, E.F., Townshend, J.R., 2018. Global land change from 1982 to 2016. Nature 1</a><br/>.