Global Ecosystems Global Data
World Terrestrial Ecosystems
Global Coastal Units
Global Islands
Global Mountains
Global Ecological Land Units
USGS transitioned from its continental work into developing the data needed to address natural resource management from a global perspective. USGS is also responsible for the implementation of companion tools, called Explorers, to provide web-based visualization and query functionality for each new global dataset.
Development of these datasets is being done by the USGS in partnership with Esri and various other groups and is supported by the Group on Earth Observations (GEO), a consortium of over 100 nations that seek to promote earth observation for solving some of society's most difficult problems.
World Terrestrial Ecosystems
Ecosystems, distinct areas on the planet which differ based on their environmental settings and assemblages of organisms, provide the goods and services necessary for human survival. Knowing the types and locations of global ecosystems is the first step in ensuring the sustainable management needed to support healthy ecosystems.
The World Terrestrial Ecosystems (WTE) is a global raster dataset at a 250-meter spatial resolution identifying 431 ecosystem types including both ‘natural’ ecosystems (e.g., different kinds of forests, shrublands, grasslands, bare areas, etc.) and ‘converted’ landscapes (e.g., croplands, settlements). WTE’s were conceptualized and delineated as areas with unique combinations of climate setting, landforms, and vegetation/land cover. They were produced from a spatial combination of three input data layers; World Climate Regions (eighteen classes produced from thirty years of WorldClim v. 2.0 temperature and precipitation data), World Landforms (plains, hills, mountains, and tablelands produced from a DEM-derived Hammond landforms layer), and World Vegetation/Land Cover (8 classes produced from 2015 European Space Agency global land cover data).
The WTE data was produced in a joint effort by the USGS, Esri, and The Nature Conservancy and was also commissioned as part of the GEO Global Ecosystems Initiative (GEO ECO) tasked to produce consistent and innovative classification and mapping of global ecosystems at a finer spatial resolution than any existing eco-regionalization of the planet. And under the National Geospatial Data Asset (NGDA) Portfolio the WTE (NGDAID198) has replaced the Terrestrial Ecosystems of the Conterminous United States (NGDAID4) as an official geospatial dataset in the Biodiversity and Ecosystems theme.
Additional Information:
World Terrestrial Ecosystems (WTE) 2020 data
World Terrestrial Ecosystems Explorer (WTEE)
An assessment of the representation of ecosystems in global protected areas using new maps of World Climate Regions and World Ecosystems article
Global Coastlines
There is an astonishing variety of coastal settings on Earth caused by many factors, including tectonic history, climate regime, riverine influences, the action of waves and tides, and the erosion and deposition of materials that make up the Earth's crust.
The Global Coastline dataset is high-resolution map of the Earth's coastlines and a standardized global inventory of the ecological settings in which coastlines occur. It contains over 4 million 1 km or shorter coastal segments, each attributed with values from ten ecological settings representing the adjacent ocean, the adjacent land, and the coastline itself. The coastal segments were also classified into 81,000 coastal segment units (CSUs) using a unique combination of the values of the ten ecological settings from the Coastal and Marine Ecosystem Classification Standard (CMECS). And the 4 million segments were also clustered into a set of 16 global coastline groups which are similar in the aggregate ecological setting described by the ten variables.
The Global Shoreline Vector (GSV) dataset was used as the geospatial linework for this global segmentation, classification, and clustering effort. This linework, derived from 30-meter spatial resolution satellite imagery, was developed as part of the Global Islands effort exploring the location, shape and size, and name of the islands of the planet.
The Global Coastlines resource was developed by the USGS in partnership with Esri and the Marine Biodiversity Observation Network (MBON) and supports the GEO GECO tasked to develop global coastal ecosystems data.
Additional Information:
Global Ecological Classification of Coastal Segment Units data
Global Coastline Explorer (GCE)
Earth’s coastlines article
Global Islands
Every landmass, no matter how big, is surrounded by ocean waters, so island sizes range from continental to tiny rock outcrops. However, size is relative since there is no accepted standard for what separates big islands from small islands.
The Global Islands dataset groups 369,401 island polygons, derived from a new 30-meter resolution Global Shoreline Vector (GSV) dataset, into four size classes: continental mainlands, big islands, small islands, and very small islands. Continental mainlands are the single, very large polygons representing the five continental landmass interiors (North America, South America, Africa, Eurasia, and Australia). The remaining polygons are classified based on their actual size with Big Islands > 1 km2, Small Islands <= 1 km2 and >= .0036 km2, and Very Small Islands < .0036 km2. The GSV was produced during this effort to provide the spatial linework needed for the generation of the global polygons. The GSV is a 30-meter spatial resolution vector dataset derived by the semi-automated interpretation of 2014 satellite imagery in Google Earth Engine.
Developed by the USGS in partnership with Esri, Global Islands supported the GEO ECO to map standardized, robust, and practical global coastal ecosystems in three ecological zones: coastal land areas, nearshore coastal waters, and offshore coastal waters.
Additional Information:
Global Islands data
Global Island Explorer (GIE)
A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units article
Global Mountains
Although answers to questions "what is a mountain?" and "where are the mountains of the world?" might seem obvious and intuitive to many, there have been surprisingly few attempts to define and map the mountains of the Earth rigorously and consistently. However, three datasets have considerably advanced our understanding of the global distribution of mountains.
The first two global mountain datasets were derived from 1km DEMs, with the first being produced by Kapos et al., 2000 (herein referred to as K1), and the second by Körner et al., 2011 (herein referred to as K2). The K1 dataset defined six classes of mountains based on a combination of elevation, slope and relative relief derived from a 1 km DEM. The circular neighborhood analysis window (NAW) for computing the relative relief used a 5 pixel (~7 km) radius for an approximate NAW size of 150 km2. The K2 data layer, which was also based on 1 km DEM source, used ruggedness as the determining factor, where any relative relief greater than 200-meter in the approximately 9 km2 NAW was considered mountainous.
The third global mountain dataset, Karagulle et al., 2017 (herein referred to as K3), was developed by USGS, in partnership with Esri, the Center for Development and Environment of the University of Bern (CDE), the Global Mountain Biodiversity Assessment (GMBA), and the Mountain Research Initiative (MRI). This data was generated from a 250-meter DEM and feature-based extraction algorithms with variable NAW sizes to extract Hammond’s 16 global landform types. Then the final K3 product was produced by an automated extraction of the four Hammond landform types used to represent mountain classes.
The Global Mountain Explorer (GME) 2.0, the first global explorer developed by USGS, provided web-based browsing and visual comparisons of the K1, K2, and K3 characterizations of global mountain extents. This application supported part of a GEO initiative called GEO Mountains, GEO’s Global Network for Observations and Information in Mountain Environments and specifically addressed a task to accurately delineate and compare global mountain extent using data from three established approaches.
Additional Information:
Global Mountains data
Global Mountain Explorer 2.0
A New High-Resolution Map of World Mountains and an Online Tool for Visualizing and Comparing Characterizations of Global Mountain Distributions article
Global Ecological Land Units (ELUs)
An ecophysiographic classification of the Earth's surface is based on climate, landform, and geology to represent the physical setting and land cover to represent a biotic response to the physical setting. This concept demonstrates that when only land cover is mapped with its physical environment context, the resulting areas are better conceptualized as ecological land units rather than ecosystems, since less is known about the vegetation. In other words, when the description of an area emphasizes its biophysical features and notes associated image-derived land cover, that area is better regarded as an ecological land unit than an ecosystem.
In its first global effort the USGS developed a rich, spatially explicit database of global Ecological Land Units (ELUs) based on the geospatial combination of four global input layers - bioclimate, landform, lithology, and land cover – reconciled into a standard 250-meter raster framework. The bioclimates layer was a modified version of the Global Environmental Stratification (GEnS) dataset produced by Metzger in another GEOSS-commissioned effort. Since no DEM-derived global landforms layer existed, one was initially generated using the Missouri Resource Assessment Partnership (MoRAP) methodology applied to global 250-meter DEM data. The MoRAP algorithm, which uses slope and relative relief parameters, was subsequently improved with the addition of a profile parameter that improved the delineation of tablelands. The lithology layer was the Global Lithology Map (GLiM) that identifies 16 lithological classes at its most general level of classification. For the global land cover, the GlobCover 2009 product, collaboratively produced by the European Space Agency (ESA) and the Université Catholique de Louvain, was initially used. That product was then upgraded by the ESA to a Global Land Cover data layer, which represents the global distribution of 23 land cover classes as interpreted from 300-meter spatial resolution data from the MERIS satellite. The input data (bioclimate region, landform type, surficial lithology, and land cover) was then combined into a single 250-meter raster layer that had 106,959 unique combinations of attribute values. The final product was then produced by generalizing the number of initial attribute classes into a reduced set of 3,639 global ELUs.
This resource was developed by the USGS in partnership with Esri and supported the GEO GECO tasked to produce consistent and innovative classification and mapping of global ecosystems at a finer spatial resolution than any existing eco-regionalization of the planet.
Additional Information:
World Ecological Land Units (ELUs) 2015 data
Global Ecosystems Viewer
A new map of global ecological land units – An ecophysiographic stratification approach article
USGS transitioned from its continental work into developing the data needed to address natural resource management from a global perspective. USGS is also responsible for the implementation of companion tools, called Explorers, to provide web-based visualization and query functionality for each new global dataset.
Development of these datasets is being done by the USGS in partnership with Esri and various other groups and is supported by the Group on Earth Observations (GEO), a consortium of over 100 nations that seek to promote earth observation for solving some of society's most difficult problems.
World Terrestrial Ecosystems
Ecosystems, distinct areas on the planet which differ based on their environmental settings and assemblages of organisms, provide the goods and services necessary for human survival. Knowing the types and locations of global ecosystems is the first step in ensuring the sustainable management needed to support healthy ecosystems.
The World Terrestrial Ecosystems (WTE) is a global raster dataset at a 250-meter spatial resolution identifying 431 ecosystem types including both ‘natural’ ecosystems (e.g., different kinds of forests, shrublands, grasslands, bare areas, etc.) and ‘converted’ landscapes (e.g., croplands, settlements). WTE’s were conceptualized and delineated as areas with unique combinations of climate setting, landforms, and vegetation/land cover. They were produced from a spatial combination of three input data layers; World Climate Regions (eighteen classes produced from thirty years of WorldClim v. 2.0 temperature and precipitation data), World Landforms (plains, hills, mountains, and tablelands produced from a DEM-derived Hammond landforms layer), and World Vegetation/Land Cover (8 classes produced from 2015 European Space Agency global land cover data).
The WTE data was produced in a joint effort by the USGS, Esri, and The Nature Conservancy and was also commissioned as part of the GEO Global Ecosystems Initiative (GEO ECO) tasked to produce consistent and innovative classification and mapping of global ecosystems at a finer spatial resolution than any existing eco-regionalization of the planet. And under the National Geospatial Data Asset (NGDA) Portfolio the WTE (NGDAID198) has replaced the Terrestrial Ecosystems of the Conterminous United States (NGDAID4) as an official geospatial dataset in the Biodiversity and Ecosystems theme.
Additional Information:
World Terrestrial Ecosystems (WTE) 2020 data
World Terrestrial Ecosystems Explorer (WTEE)
An assessment of the representation of ecosystems in global protected areas using new maps of World Climate Regions and World Ecosystems article
Global Coastlines
There is an astonishing variety of coastal settings on Earth caused by many factors, including tectonic history, climate regime, riverine influences, the action of waves and tides, and the erosion and deposition of materials that make up the Earth's crust.
The Global Coastline dataset is high-resolution map of the Earth's coastlines and a standardized global inventory of the ecological settings in which coastlines occur. It contains over 4 million 1 km or shorter coastal segments, each attributed with values from ten ecological settings representing the adjacent ocean, the adjacent land, and the coastline itself. The coastal segments were also classified into 81,000 coastal segment units (CSUs) using a unique combination of the values of the ten ecological settings from the Coastal and Marine Ecosystem Classification Standard (CMECS). And the 4 million segments were also clustered into a set of 16 global coastline groups which are similar in the aggregate ecological setting described by the ten variables.
The Global Shoreline Vector (GSV) dataset was used as the geospatial linework for this global segmentation, classification, and clustering effort. This linework, derived from 30-meter spatial resolution satellite imagery, was developed as part of the Global Islands effort exploring the location, shape and size, and name of the islands of the planet.
The Global Coastlines resource was developed by the USGS in partnership with Esri and the Marine Biodiversity Observation Network (MBON) and supports the GEO GECO tasked to develop global coastal ecosystems data.
Additional Information:
Global Ecological Classification of Coastal Segment Units data
Global Coastline Explorer (GCE)
Earth’s coastlines article
Global Islands
Every landmass, no matter how big, is surrounded by ocean waters, so island sizes range from continental to tiny rock outcrops. However, size is relative since there is no accepted standard for what separates big islands from small islands.
The Global Islands dataset groups 369,401 island polygons, derived from a new 30-meter resolution Global Shoreline Vector (GSV) dataset, into four size classes: continental mainlands, big islands, small islands, and very small islands. Continental mainlands are the single, very large polygons representing the five continental landmass interiors (North America, South America, Africa, Eurasia, and Australia). The remaining polygons are classified based on their actual size with Big Islands > 1 km2, Small Islands <= 1 km2 and >= .0036 km2, and Very Small Islands < .0036 km2. The GSV was produced during this effort to provide the spatial linework needed for the generation of the global polygons. The GSV is a 30-meter spatial resolution vector dataset derived by the semi-automated interpretation of 2014 satellite imagery in Google Earth Engine.
Developed by the USGS in partnership with Esri, Global Islands supported the GEO ECO to map standardized, robust, and practical global coastal ecosystems in three ecological zones: coastal land areas, nearshore coastal waters, and offshore coastal waters.
Additional Information:
Global Islands data
Global Island Explorer (GIE)
A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units article
Global Mountains
Although answers to questions "what is a mountain?" and "where are the mountains of the world?" might seem obvious and intuitive to many, there have been surprisingly few attempts to define and map the mountains of the Earth rigorously and consistently. However, three datasets have considerably advanced our understanding of the global distribution of mountains.
The first two global mountain datasets were derived from 1km DEMs, with the first being produced by Kapos et al., 2000 (herein referred to as K1), and the second by Körner et al., 2011 (herein referred to as K2). The K1 dataset defined six classes of mountains based on a combination of elevation, slope and relative relief derived from a 1 km DEM. The circular neighborhood analysis window (NAW) for computing the relative relief used a 5 pixel (~7 km) radius for an approximate NAW size of 150 km2. The K2 data layer, which was also based on 1 km DEM source, used ruggedness as the determining factor, where any relative relief greater than 200-meter in the approximately 9 km2 NAW was considered mountainous.
The third global mountain dataset, Karagulle et al., 2017 (herein referred to as K3), was developed by USGS, in partnership with Esri, the Center for Development and Environment of the University of Bern (CDE), the Global Mountain Biodiversity Assessment (GMBA), and the Mountain Research Initiative (MRI). This data was generated from a 250-meter DEM and feature-based extraction algorithms with variable NAW sizes to extract Hammond’s 16 global landform types. Then the final K3 product was produced by an automated extraction of the four Hammond landform types used to represent mountain classes.
The Global Mountain Explorer (GME) 2.0, the first global explorer developed by USGS, provided web-based browsing and visual comparisons of the K1, K2, and K3 characterizations of global mountain extents. This application supported part of a GEO initiative called GEO Mountains, GEO’s Global Network for Observations and Information in Mountain Environments and specifically addressed a task to accurately delineate and compare global mountain extent using data from three established approaches.
Additional Information:
Global Mountains data
Global Mountain Explorer 2.0
A New High-Resolution Map of World Mountains and an Online Tool for Visualizing and Comparing Characterizations of Global Mountain Distributions article
Global Ecological Land Units (ELUs)
An ecophysiographic classification of the Earth's surface is based on climate, landform, and geology to represent the physical setting and land cover to represent a biotic response to the physical setting. This concept demonstrates that when only land cover is mapped with its physical environment context, the resulting areas are better conceptualized as ecological land units rather than ecosystems, since less is known about the vegetation. In other words, when the description of an area emphasizes its biophysical features and notes associated image-derived land cover, that area is better regarded as an ecological land unit than an ecosystem.
In its first global effort the USGS developed a rich, spatially explicit database of global Ecological Land Units (ELUs) based on the geospatial combination of four global input layers - bioclimate, landform, lithology, and land cover – reconciled into a standard 250-meter raster framework. The bioclimates layer was a modified version of the Global Environmental Stratification (GEnS) dataset produced by Metzger in another GEOSS-commissioned effort. Since no DEM-derived global landforms layer existed, one was initially generated using the Missouri Resource Assessment Partnership (MoRAP) methodology applied to global 250-meter DEM data. The MoRAP algorithm, which uses slope and relative relief parameters, was subsequently improved with the addition of a profile parameter that improved the delineation of tablelands. The lithology layer was the Global Lithology Map (GLiM) that identifies 16 lithological classes at its most general level of classification. For the global land cover, the GlobCover 2009 product, collaboratively produced by the European Space Agency (ESA) and the Université Catholique de Louvain, was initially used. That product was then upgraded by the ESA to a Global Land Cover data layer, which represents the global distribution of 23 land cover classes as interpreted from 300-meter spatial resolution data from the MERIS satellite. The input data (bioclimate region, landform type, surficial lithology, and land cover) was then combined into a single 250-meter raster layer that had 106,959 unique combinations of attribute values. The final product was then produced by generalizing the number of initial attribute classes into a reduced set of 3,639 global ELUs.
This resource was developed by the USGS in partnership with Esri and supported the GEO GECO tasked to produce consistent and innovative classification and mapping of global ecosystems at a finer spatial resolution than any existing eco-regionalization of the planet.
Additional Information:
World Ecological Land Units (ELUs) 2015 data
Global Ecosystems Viewer
A new map of global ecological land units – An ecophysiographic stratification approach article