South America is part of Region 6 (Central and South America) for the World Energy Assessment. The geologic map of South America was digitized so that we could use the geology as a general guide to draw the boundaries of the geologic provinces of South America.

Layers for World History GeoInquiries lesson "Latin America – The Age of Revolutions."

ArcGIS Online Map Service created by Esri to provide access to: (1) Latin American and Caribbean 2015 Water Extent and (2) Latin American and Caribbean Water Bodies. The first dataset reflects the accumulation of the daily MODIS Surface Water detection product 3D3OT that is provided by the NASA’s MODIS Near Real-Time Global Flood Mapping Project, implementing the water detection algorithm of Dartmouth Flood Observatory (DFO). The dataset was produced by DFO for The Latin American Bank (CAF). The second dataset, the SRTM Water Body Data, is a by-product of the data editing performed by NGA to produce the finished SRTM Digital Terrain Elevation Data Level 2 (DTED® 2). In accordance with the DTED® 2 specification, the terrain elevation data have been edited to portray water bodies that meet minimum capture criteria. Ocean, lake and river shorelines were identified and delineated. Lake elevations were set to a constant value. Ocean elevations were set to zero. Rivers were stepped down monotonically to maintain proper flow. After this processing was done, the shorelines from the one arc second (approx. 30-meter) DTED® 2 were saved as vectors in ESRI 3-D Shapefile format. The dataset was produced by the USGS EROS for CAF. The data are hosted as tile layers in ArcGIS Online to improve performance. The water bodies layer is represented in dark blue and the water extent (aka flooding) in light blue. The original data can be downloaded from https://www.geosur.info.

This resource includes three hydrographic geospatial datasets for South America including: Rivers, Watersheds, and Basin area. These datasets were developed at Brigham Young University by using standard terrain analysis tool in ArcGIS to extract features from digital elevation model data provided by Esri. The datasets were created for the purpose of supporting GEOGLOWS (http://www.geoglows.org) forecasting using ECMWF (https://www.ecmwf.int) ensemble weather/hydrologic model and the RAPID river routing model (http://rapid-hub.org). These datasets are provided free of charge for use for any purpose. If you use these data, please reference this HydroShare resource using the information provided in "How to Cite" at the bottom of this HydroShare landing page.

This dataset comprises four distinct shapefiles, which were used to demonstrate how glacier ELA is affected by volcanic thermal conditions, in the Andes, South America. With the exception of ''139_Remapped_Glaciers.shp'', the shapefiles are obtained from existing, open access data from the Randolph Glacier Inventory (RGI 6.0) and the Global Volcanism Program 2013, but with the addition of information, in the shapefile''s attribute table, relevant to the study of the interaction between glaciers and volcanoes, as obtained via the GIS analysis of these datasets. The ''600_RGI_Glaciers.shp'' shapefile comprises 600 (land-terminating, no debris-covered, > 0.1 km2) glacier polygons, which are located within 15 km from a Holocene (erupted in the past 10,000 years) volcano in South America. Crucially, the equilibrium line altitude (i.e., the elevation on the glacier where the surface mass balance, measured over 1 yr, is zero) and distance to the nearest volcano for each glacier is reported in the attribute table. The ''37_GVP_Volacanoes.shp'' shapefile contains points for 37 South America Holocene volcanoes which have glaciers both within 1 km (volcanic-glaciers), and between 1 and 15 km (proximal glaciers). For each volcano, the difference in ELA between volcanic (<1km from volcano) and proximal (1-15 km) glaciers is reported in the attribute table, along with mean temperature and precipitation. The ''139_Remapped_Glaciers.shp'' shapefile provides detailed and updated (relative to RGI) mapping of glaciers (as polygons) that are located within 15 km from 13 South America Holocene volcanoes for which thermal anomaly is known. The ELA of these glaciers is calculated and reported in the attribute table. The ''13_AVTOD_Volacanoes.shp'' shapefile comprises the points for 13 Holocene volcanoes that have glaciers both within 1 km (volcanic-glaciers), and between 1 and 15 km (proximal glaciers) from their centre, as well as recorded thermal anomaly. The glacier ELA and volcano thermal data provided in the attribute table allows us to establish the quantitative relationship between volcanoes and glaciers.

A detailed description of the study based on this dataset is provided in Howcutt et al. (2023).

This project and data were supported by the NERC Global Partnerships Seedcorn fund (NE/W003724/1).

This raster GIS dataset contains 30 meter cells depicting wetlands in a hydrobasin. This base dataset is a combination of three globally available datasets creating a new dataset is that is inclusive of both finer-resolution data while accounting for a wide range of wetland sizes. The three source datasets are: 1) CW-WTD 500 m dataset resampled to 30 m. – Wetland dataset built from a composite wetland-water table depth (Tootchi 2019), 2) CCI (Climate Change Initiative) data resampled from 300 m to 30 m - CCI defined wetlands as “…mixed classes of flooded areas with tree covers, shrubs, or herbaceous covers plus inland water bodies” and 3) Global Surface Water (GSW) 30-m (Pekel et al. 2016) – A pixel was considered a wetland if it had at least one inundation event over a 32-year range.

This feature layer provides access to OpenStreetMap (OSM) waterways data for South America, which is updated every 15 minutes with the latest edits. This hosted feature layer view is referencing a hosted feature layer of OSM line (way) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file. This feature layer view includes waterway features defined as a query against the hosted feature layer (i.e. waterway is not blank).In OSM, a waterway describes rivers, streams and ditches with a flow of water from one place to another. These features are identified with a waterway tag. There are hundreds of different tag values for waterway used in the OSM database. In this feature layer, unique symbols are used for several of the most popular waterway types, while lesser used types are grouped in an "other" category.Zoom in to large scales (e.g. City level or 1:80k scale) to see the waterway features display. You can click on a feature to get the name of the waterway (if available). The name of the waterway will display by default at large scales (e.g. Street level of 1:5k scale). Labels can be turned off in your map if you prefer.Create New LayerIf you would like to create a more focused version of this waterway layer displaying just one or two waterway types, you can do that easily! Just add the layer to a map, copy the layer in the content window, add a filter to the new layer (e.g. waterway is dam), rename the layer as appropriate, and save layer. You can also change the layer symbols or popup if you like. Esri may publish a few such layers (e.g. streams and rivers) that are ready to use, but not for every type of waterway.Important Note: if you do create a new layer, it should be provided under the same Terms of Use and include the same Credits as this layer. You can copy and paste the Terms of Use and Credits info below in the new Item page as needed.

This dataset contains the Digital Elevation Model (DEM) for South America from the Hydrologic Derivatives for Modeling and Analysis (HDMA) database. The data were developed and distributed by processing units. There are 10 processing units for South America. The distribution files have the number of the processing unit appended to the end of the zip file name (e.g. sa_dem_3.zip contains the DEM data for unit 3-2). The HDMA database provides comprehensive and consistent global coverage of raster and vector topographically derived layers, including raster layers of digital elevation model (DEM) data, flow direction, flow accumulation, slope, and compound topographic index (CTI); and vector layers of streams and catchment boundaries. The coverage of the data is global (-180º, 180º, -90º, 90º) with the underlying DEM being a hybrid of three datasets: HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales), Global Multi-resolution Terrain Eleva ...

This is a preview of the HISAR dataset (Hydrologic Indices of South American Rivers).

The HISAR dataset is freely available for non-commercial use. The files provided are (i) drainage line shapefile with river reaches as represented by the MGB model and 73 attributes corresponding to hydrologic indices derived from simulated time series; (ii) gauge points shapefile with 73 attributes corresponding to hydrologic indices derived from observed time series; (iii) maps with hydrologic indices, (iv) maps with information of the error of some indices and (v) the scripts used to calculate the indices. This database provides a spatial view of the variability of the river flow regime characteristics.

The line shapefile has 33,749 river reaches with an average length of 15 km and drainage area > 1000 km². The ESRI shapefile also has the attributes of drainage area (Upst_Area_ in km²), length (Ltr_Km_ in km), UC (corresponding catchment attribute from hydrological modelling), HYear_min (starting month of the hydrological year of minimum flow) and HYear_max (starting month of the hydrological year of maximum flow). A value of -9999999 is used as a symbol of ‘no data’.

Some river reaches do not have all hydrologic indices calculated, due to series of streamflows that could not meet specific criteria. For instance, the baseflow recession constant was automatically calculated using at least five consecutive days of decreasing streamflow, all of which below the Q90 (streamflow value that is exceeded 90% of the time), and this condition was not found in all cases.

The gauge points shapefile has 1329 points with 73 attributes corresponding to hydrologic indices derived from observed time series. The drainage area of the gauges ranging from 1,000 to 4,703,503 km2. The ESRI shapefile also has the attributes of code, name, latitude (lat), longitude (long), drainage area (Upst_Area_ in km²), Country were the gauge point are located, HYear_min (starting month of the hydrological year of minimum flow) and HYear_max (starting month of the hydrological year of maximum flow). A value of -9999999 is used as a symbol of ‘no data’.

For more information about HISAR dataset see the journal article DOI: in preparation.

This shapefile provides a worldwide geographic division by merging the World Continents division proposed by Esri Data and Maps (2024) to the Global Oceans and Seas version 1 division proposed by the Flanders Marine Institute (2021). Though divisions of continents and oceans/seas are available, the combination of both in a single shapefile is scarce.

The Continents and Oceans/Seas shapefile was carefully processed to remove overlaps between the inputs, and to fill gaps (i.e., areas with no information) by spatially joining these gaps to neighbour polygons. In total, the original world continents input divides land areas into 8 categories (Africa, Antarctica, Asia, Australia, Europe, North America, Oceania, and South America), while the original oceans/seas input divides the oceans/seas into 10 categories (Arctic Ocean, Baltic Sea, Indian Ocean, Mediterranean Region, North Atlantic Ocean, North Pacific Ocean, South Atlantic Ocean, South China and Easter Archipelagic Seas, South Pacific Ocean, and Southern Ocean). Therefore, the resulting world geographic division has 18 possible categories.

References

Esri Data and Maps (2024). World Continents. Available online at https://hub.arcgis.com/datasets/esri::world-continents/about. Accessed on 05 March 2024.

Flanders Marine Institute (2021). Global Oceans and Seas, version 1. Available online at https://www.marineregions.org/. https://doi.org/10.14284/542. Accessed on 04 March 2024.

The Andes Mountains of South America host significant porphyry copper deposits. The region is the major global source of copper and an area of active mining, exploration, and development. The Andes region was included in USGS global compilations of porphyry deposits published by Singer and others in 2005 and 2008. Since that time, many new discoveries and new resource data have become available. This compilation includes new and updated location, references, and grade and tonnage data for porphyry copper deposits in the Andes along with grade and tonnage data from the previous compilations. The data release includes a data table, references, and shapefiles of porphyry copper locations and political boundaries.

Mineral resource occurrence data covering the world, most thoroughly within the U.S. This database contains the records previously provided in the Mineral Resource Data System (MRDS) of USGS and the Mineral Availability System/Mineral Industry Locator System (MAS/MILS) originated in the U.S. Bureau of Mines, which is now part of USGS. The MRDS is a large and complex relational database developed over several decades by hundreds of researchers and reporters. While database records describe mineral resources worldwide, the compilation of information was intended to cover the United States completely, and its coverage of resources in other countries is incomplete. The content of MRDS records was drawn from reports previously published or made available to USGS researchers. Some of those original source materials are no longer available. The information contained in MRDS was intended to reflect the reports used as sources and is current only as of the date of those source reports. Consequently MRDS does not reflect up-to-date changes to the operating status of mines, ownership, land status, production figures and estimates of reserves and resources, or the nature, size, and extent of workings. Information on the geological characteristics of the mineral resource are likely to remain correct, but aspects involving human activity are likely to be out of date.

A new edition of the Geological Map of South America (GMSA) at a scale of 1:5 M was developed by the Subcommission for South America of the Commission for the Geological Map of the World (CGMW), approved by the CGMW General Assembly held in Oslo (Norway), during the 33rd International Geological Congress.

This third version has been prepared with the cooperation of the Ibero–American Association of Geology and Mining Surveys (ASGMI), the geological surveys of Argentina, Brazil, Chile, Colombia, Ecuador, Peru, and Uruguay; and several additional universities and research institutes that are mentioned in the collaborators information.

The subcommission followed a methodology for integrating the geological information from each country as follows: first, a new code was generated for each chronostratigraphic unit according to the proposed legend, by using digital layers provided by the geological survey of each country; second, symbology and colors were created with patterns representative of rock type and colors depicting the ages; and third, a map with coded units was prepared at a scale of 1:5 M.

With the objective of generalization and linking units by hand, the GMSA was printed at a scale of 1:3 M with the new codification. Next, the GMSA was scanned and georeferenced in order to generalize the geological units, faults and folds at a scale of 1:5 M. Once this was done, and despite the small–scale of the GMSA, the chronostratigraphic units, faults and folds on the map were adjusted with the aid of shaded relief images (STRM from NASA) in order to improve the matching between relief and the mapped geological units. Finally, the geology between countries was harmonized. It is worth noting that the updating of the GMSA was done through consultation of internationally indexed published papers.

The map is based on a Polyconic Projection (Latitude × Longitude), centered on Meridian –59°, WGS–1984 datum; data for offshore areas were taken from the Tectonic Map of South America at a scale of 1:5.9 M (Cordani et al., 2016); the Sea Floor Topography from GEBCO 08 Grid, version 20100927; and the Crustal Age Grid: NCEI/NOAA. |categoría:Mapas Nacionales |cobertura:Nacional.

World Continents represents the boundaries for the continents of the world. It provides a basemap layer of the continents, delivering a straightforward method of selecting a small multicountry area for display or study.This layer is best viewed out beyond a scale of 1:3,000,000. The original source was extracted from the ArcWorld Supplement database in 2001 and updated as country boundaries coincident to regional boundaries change. To download the data for this layer as a layer package for use in ArcGIS desktop applications, refer to World Continents.

Shapefile des chemins de fer en Amérique du Sud entre 1900 et 1920 basé sur la cartographie historique de différentes bibliothèques. Shapefiles tous les 20 ans en raison de l'impossibilité de trouver des cartographies historiques chaque année.

The Soil and Terrain database for Latin America and the Caribbean (SOTERLAC), version 2.0, at scale 1:5 million, replaces version 1.02. The update includes changes in the GIS file and in the attributes database. The topographic base of the SOTERLAC map was adapted to a version congruent to the Digital Chart of the World. The SOTERLAC attribute database has changed in respect to the number of ... pedon attributes that can be stored. Contrary to the preceding, compact version, version 2.0 can accommodate all pedon attributes considered in a 1:1 million scale SOTER database. SOTERLAC forms a part of the ongoing activities of ISRIC, FAO and UNEP to update the world's baseline information on natural resources.The project involved collaboration with national soil institutes from the countries in the region as well as individual experts

This dataset displays level 0 world administrative boundaries. It contains countries as well as non-sovereign territories (like, for instance, French overseas).

The rivers of South America are derived from the World Wildlife Fund's (WWF) HydroSHEDS drainage direction layer and a stream network layer.The drainage direction layer was created from NASA's Shuttle Radar Topographic Mission (SRTM) 15-second Digital Elevation Model (DEM).The raster stream network was determined by using the HydroSHEDS flow accumulation grid, with a threshold of about 100 km² upstream area.

The stream network dataset consists of the following information: the origin node of each arc in the network (FROM_NODE), the destination of each arc in the network (TO_NODE), the Strahler stream order of each arc in the network (STRAHLER), numerical code and name of the major basin that the arc falls within (MAJ_BAS and MAJ_NAME); - area of the major basin in square km that the arc falls within (MAJ_AREA); - numerical code and name of the sub-basin that the arc falls within (SUB_BAS and SUB_NAME); - area of the sub-basin in square km that the arc falls within (SUB_AREA); - numerical code of the sub-basin towards which the sub-basin flows that the arc falls within (TO_SUBBAS) (the codes -888 and -999 have been assigned respectively to internal sub-basins and to sub-basins draining into the sea). The attributes table now includes a field named "Regime" with tentative classification of perennial ("P") and intermittent ("I") streams.

Supplemental Information:

This dataset is developed as part of a GIS-based information system on water resources for South America. It has been published in the framework of the AQUASTAT - programme of the Land and Water Division of the Food and Agriculture Organization of the United Nations.

Contact points:

Metadata contact: AQUASTAT FAO-UN Land and Water Division

Contact: Jippe Hoogeveen FAO-UN Land and Water Division

Contact: Livia Peiser FAO-UN Land and Water Division

Data lineage:

The linework of the map was obtained by converting the stream network to a feature dataset with the Hydrology toolset in ESRI ArcGIS.The Flow Direction and Stream Order grids were derived from hydrologically corrected elevation data with a resolution of 15 arc-seconds.The elevation dataset was part of a mapping product, HydroSHEDS, developed by the Conservation Science Program of World Wildlife Fund.Original input data had been obtained during NASA's Shuttle Radar Topography Mission (SRTM).

Online resources:

Download - Rivers of South America (ESRI shapefile)

For general information regarding the HydroSHEDS data product

For HydroSHEDS dataset download and technical information

This is a shapefile of the geographic limits proposed by Morrone (2014) based on occurrence data of endemic animals and plants of Latin America and the Caribbean.

70 Latin American cities were selected for the index, including cities in Latin America with population greater than 750,000 according to the report conducted by the United Nations Population Division (UNPD 2011). Urban area definitions follow the United Nation’s Population Division (UNPD 2011). For urban extent, we used the Global Rural-Urban Mapping Project (GRUMP) urban extents based on nighttime light imagery and ancillary datasets (CIESIN et al. 2004, Balk 2009). Cities with connected GRUMP urban extents, such as Maracay, Caracas, and Valencia (Colombia), were divided based on the Global Administrative Database (GADM 2012) which defines municipal urban administrative areas. Havana was not included in the GRUMP dataset, and thus its urban extent was also defined with GADM (2012).

For riverine flooding, the unit of analysis was the city “floodshed†, comprised of all watersheds in the upstream contributing area to the urban extent of that city. Urban extents were defined by the GRUMP 2000 data set, and floodsheds delineated based on the HydroSHEDs digital elevation model. Additional watersheds were added to city floodsheds in special cases where a downstream river posed flooding threats to a city (e.g., Rio Jaqui for Porto Alegre, Brazil). A total of 780 watersheds were analyzed for 70 cities.