Maus, Victor; Kuschnig, Nikolas; Luckeneder, Sebastian; Giljum, Stefan (2021): A set of essential variables for modelling environmental impacts of global mining land use [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.928573
Always quote citation above when using data! You can download the citation in several formats below.
Abstract:
This repository provides a set of essential variables to support research on forest loss driven by mining. All variables have been resampled to 30 arcsec spatial resolution (approximately 1 by 1 km at the equator) and are encoded in Geographic Tagged Image File Format (GeoTIFF). The grid extends from the longitude −180 to 180 degrees and from the latitude −90 to 90 degrees in the geographical reference system WGS84. Cells over water have no-data values. Below we describe the list of variables, sources, and processing
steps.area_of_mines_circa_2018.tif: mining area in square metres. This layer was derived from a global-scale data set of mining polygons [Maus et al., 202a,b0] available from [doi:10.1594/PANGAEA.910894] under CC BY-SA 4.0 license. The mining area for each 30 arcsec grid was calculated intersecting cells and mining
polygons.distance_to_mine_circa_2018.tif: distance to the nearest mine in metres. This layer was derived by calculating the Euclidean distance between each grid cell's centroid to the centroid of the closest grid cell with mine presence, i.e. cells where
area_of_mines_circa_2018.tif > 0.area_of_forest_cover_circa_2000.tif: area of forest cover in square metres. This layer was derived from the Global Forest Change (GFC) dataset [Hansen et al., 2013] version 1.7 available from [https://earthenginepartners.appspot.com/science-2013-global-forest/download_v1.7.html] under CC BY 4.0 license. We aggregated the GFC data from 1 arcsec to our 30 arcsec grid cells by summing the area of forest cover pixels weighted by their surface intersection with the 30 arcsec
cells.area_of_forest_cover_within_mines_circa_2000.tif: area of forest cover in square metres. This layer was derived using the same methods as
area_of_forest_cover_circa_2000.tif; however, it only includes forest area intersecting mining polygons, i.e. the on-site forest cover circa
2000.area_of_forest_cover_loss_yearly_from_2001_to_2019.tif: area of forest cover loss in square metres. This GeoTIFF file has 19 layers (one layer per year) starting from 2000. We aggregated the GFC data from 1 arcsec to our 30 arcsec grid cells by summing the area of forest loss pixels weighted by their surface intersection with the 30 arcsec
cells.ecoregions2017_code.tif: an integer with the ecoregions code (ECO_ID) rasterized from the Ecoregion 2017 polygons [Dinerstein et al., 2017; Resolve, 2017], which is available from [https://ecoregions2017.appspot.com/] under CC BY 4.0 license. The polygons were rasterized to a 30 arcsec grid by the major class present. The ecoregion class names corresponding to the GeoTIFF file values are available in the auxiliary file
ecoregions_2017_concordance_tbl.csv, which contains the following variables ECO_ID, ECO_NAME, BIOME_NUM, BIOME_NAME, where ECO_ID is a unique identifier.
The layers available from this repo can be stacked together with other variables essential for land-use modelling. Some of these variables are openly available at the same spatial extent and resolution, for example, grided population [NASA, 2018], elevation and slope [Amatulli et al., 2018a,b].
Supplement to:
Giljum, Stefan; Maus, Victor; Kuschnig, Nikolas; Luckeneder, Sebastian; Tost, Michael; Sonter, Laura; Bebbington, Anthony (accepted): A pantropical assessment of deforestation caused by industrial mining. Proceedings of the National Academy of Sciences, https://doi.org/10.1073/pnas.2118273119
Related to:
Resolve. Ecoregions (2017). http://ecoregions2017.appspot.com
NASA – Socioeconomic Data and Applications Center. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 (2018). Center for International Earth Science Information Network, Columbia University, https://doi.org/10.7927/H49C6VHW
Amatulli, Giuseppe; Domisch, Sami; Tuanmu, Mao-Ning; Parmentier, Benoit; Ranipeta, Ajay; Malczyk, Jeremy; Jetz, Walter (2018): A suite of global, cross-scale topographic variables for environmental and biodiversity modeling. Scientific Data, 5, 180040, https://doi.org/10.1038/sdata.2018.40
Amatulli, Giuseppe; Domisch, Sami; Tuanmu, Mao-Ning; Parmentier, Benoit; Ranipeta, Ajay; Malczyk, Jeremy; Jetz, Walter (2018): A suite of global, cross-scale topographic variables for environmental and biodiversity modeling, links to files in GeoTIFF format. PANGAEA, https://doi.org/10.1594/PANGAEA.867115
Dinerstein, Eric; Olson, David; Joshi, Anup; Vynne, Carly; Burgess, Neil D; Wikramanayake, Eric; Hahn, Nathan; Palminteri, Suzanne; Hedao, Prashant; Noss, Reed; Hansen, Matt; Locke, Harvey; Ellis, Erle C; Jones, Benjamin; Barber, Charles Victor; Hayes, Randy; Kormos, Cyril; Martin, Vance; Crist, Eileen; Sechrest, Wes; Price, Lori; Baillie, Jonathan E M; Weeden, Don; Suckling, Kierán; Davis, Crystal; Sizer, Nigel; Moore, Rebecca; Thau, David; Birch, Tanya; Potapov, Peter; Turubanova, Svetlana; Tyukavina, Alexandra; de Souza, Nadia; Pintea, Lilian; Brito, Jos C; Llewellyn, Othman A; Miller, Anthony G; Patzelt, Annette; Ghazanfar, Shahina A; Timberlake, Jonathan; Klöser, Heinz; Shennan-Farpón, Yara; Kindt, Roeland; Barnekow Lillesø, Jens-Peter; van Breugel, Paulo; Graudal, Lars; Voge, Maianna; Al-Shammari, Khalaf F; Saleem, Muhammad (2017): An Ecoregion-Based Approach to Protecting Half the Terrestrial Realm. BioScience, 67(6), 534-545, https://doi.org/10.1093/biosci/bix014
Hansen, M C; Potapova, R V; Moore, R; Hancher, M; Turubanova, S A; Tyukavina, Alexandra; Thau, D; Stehman, Stephen V; Goetz, S J; Loveland, T R; Kommareddy, A; Egorov, A; Chini, L; Justice, C O; Townshend, J R G (2013): High-Resolution Global Maps of 21st-Century Forest Cover Change. Science, 342(6160), 850-853, https://doi.org/10.1126/science.1244693
Maus, Victor; Giljum, Stefan; Gutschlhofer, Jakob; da Silva, Dieison M; Probst, Michael; Gass, Sidnei L B; Luckeneder, Sebastian; Lieber, Mirko; McCallum, Ian (2020): A global-scale data set of mining areas. Scientific Data, 7(1), 289, https://doi.org/10.1038/s41597-020-00624-w
Maus, Victor; Giljum, Stefan; Gutschlhofer, Jakob; da Silva, Dieison M; Probst, Michael; Gass, Sidnei L B; Luckeneder, Sebastian; Lieber, Mirko; McCallum, Ian (2020): Global-scale mining polygons (Version 1). PANGAEA, https://doi.org/10.1594/PANGAEA.910894
Project(s):
Funding:
Horizon 2020 (H2020), grant/award no. 725525: Spatially explicit material footprints: fine-scale assessment of Europe's global environmental and social impacts
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | File name | File name | Maus, Victor | |||
| 2 | Binary Object | Binary | Maus, Victor | |||
| 3 | Comment | Comment | Maus, Victor |
License:
Creative Commons Attribution-ShareAlike 4.0 International (CC-BY-SA-4.0)
Size:
17 data points