Metro Extracts are chunks of OpenStreetMap data clipped to the rectangular region surrounding a particular city or region of interest. Data is available for locations around the world. To download the OSM data, go to the Metro Extracts download page at https://mapzen.com/data/metro-extracts/. The page has a map showing the available downloads, as well as a filter box and an alphabetical list of city names below it.

A global map of built-up presence derived from backscattered information of Sentinel1 images. Both the GHS BUILT-UP GRID (LDS) as derived from Landsat image collections and the GlobeLand30 (GLC30) were used for training of the Symbolic Machine Learning (SML) classifier. 20m of resolution - Spherical Mercator (EPSG:3857) Dataset name (size): GHS_BUILT_S12016NODSM_GLOBE_R2016A_3857_20 Legend: 0 = no built-up 1 = built-up

LandScan Global Population Database 2011. Population counts at 30 arc second resolution. Using an innovative approach with Geographic Information System and Remote Sensing, ORNL's LandScan™ is the community standard for global population distribution. At approximately 1 km resolution (30" X 30"), LandScan is the finest resolution global population distribution data available and represents an ambient population (average over 24 hours). The LandScan algorithm, an R&D 100 Award Winner, uses spatial data and imagery analysis technologies and a multi-variable dasymetric modeling approach to disaggregate census counts within an administrative boundary. Since no single population distribution model can account for the differences in spatial data availability, quality, scale, and accuracy as well as the differences in cultural settlement practices, LandScan population distribution models are tailored to match the data conditions and geographical nature of each individual country and region

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.

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. Indeed, this has been very appropriate and effective in mapping the vegetative cover of the Northwest region of Ghana, which is a semi-arid zone. The GNDVI of 1990 seeks to validate the land cover patterns that existed in the area with regard to biodiversity and land use. This data sets the baseline analysis of the emerging Northwest mining region of Ghana, which would enhance the monitoring of sustainable mining

Landsat tm7 sensor. RGB raster map using bands 5-3-1. Date 2018-01-02. Edited in Grass GIS 7.2.2. Editings: - gdal_fillnodata for the satellite images from 2003 to 2018. - i.landsat.toar for DN to kind of reflectance transformation in order to later perform supervised classification of the imageries. - RGB raster map from bands 5-3-1. Image downloaded from www.earthexplorer.usgs.gov.

Landsat tm7 sensor. RGB raster map using bands 5-3-1. Date 2009-03-14. Edited in Grass GIS 7.2.2. Editings: - gdal_fillnodata for the satellite images from 2003 to 2018. - i.landsat.toar for DN to kind of reflectance transformation in order to later perform supervised classification of the imageries. - RGB raster map from bands 5-3-1. Image downloaded from www.earthexplorer.usgs.gov.

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) of 2000 shows the trends and patterns of vegetation health and degradation in the area. The data further shows the elements contributing to the fast approaching dessertification of the area. The data further sets the baseline analysis and the amount of cost-benefit analysis that must be triggered in view of the fast approaching dessertification and looming large-scale mining in the Northwest Region of Ghana

World Roads provides a base map layer for the roads and ferries of the world. They are a subset of DeLorme World Base Map 2015 (DWBM).

2010 estimates of total number of people per grid square across Africa South America and Asia, with national totals adjusted to match UN population division estimates, 2012 revision (http://esa.un.org/wpp/)