Recent guidance on environmental modeling and global land-cover validation stresses the need for a probability-based design. Additionally, spatial balance has also been recommended as it ensures more efficient sampling, which is particularly relevant for understanding land use change. In this paper I describe a global sample design and database called the Global Grid (GG) that has both of these statistical characteristics, as well as being flexible, multi-scale, and globally comprehensive. The GG is intended to facilitate collaborative science and monitoring of land changes among local, regional, and national groups of scientists and citizens, and it is provided in a variety of open source formats to promote collaborative and citizen science. Since the GG sample grid is provided at multiple scales and is globally comprehensive, it provides a universal, readily-available sample. It also supports uneven probability sample designs through filtering sample locations by user-defined strata. The GG is not appropriate for use at locations above ±85° because the shape and topological distortion of quadrants becomes extreme near the poles. Additionally, the file sizes of the GG datasets are very large at fine scale (resolution ~600 m × 600 m) and require a 64-bit integer representation.

README for Global Grid DatasetGG_CSV_L2_L13_201605277z archive (2.4GB) of text files in CSV format containing the Global Grid for levels 2 thru 13. Please see README file for further information on naming conventions and variables included in the files.GGe_L147z archive (3.8GB) in CSV format containing the Global Grid for eastern hemisphere, level 14.GGw_L147z archive (3.8GB) in CSV format containing the Global Grid for western hemisphere, level 14.GG_KML_201606037z archive (1.3MB) in KML format containing the Global Grid for eastern and western hemispheres at level 10 that represents terrestrial (land) locations stratified across the urban to rural gradient used in Figure 3 of Theobald 2016 paper.