Global Man-made Impervious Surface (GMIS) Dataset From Landsat

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About this dataset

Abstract and Limitations of Use: The Global Man-made Impervious Surface (GMIS) Dataset From Landsat consists of global estimates of fractional impervious cover derived from the Global Land Survey (GLS) Landsat dataset for the target year 2010. The GMIS dataset consists of two components: 1) global percent of impervious cover; and 2) per-pixel associated uncertainty for the global impervious cover. These layers are co-registered to the same spatial extent at a common 30m spatial resolution. The spatial extent covers the entire globe except Antarctica and some small islands. This dataset is one of the first global, 30m datasets of man-made impervious cover to be derived from the GLS data for 2010 and is a companion dataset to the Global Human Built-up And Settlement Extent (HBASE) dataset. The dataset is expected to have a rather broad spectrum of users, from those wishing to examine/study the fine details of urban land cover over the globe at full 30m resolution to global modelers trying to understand the climate/environmental impacts of man-made surfaces at continental to global scales. For example, the data are applicable to local modeling studies of urban impacts on the energy, water, and carbon cycles, as well as analyses at the individual country level.   Intended Use: To provide high spatial resolution estimates of global man-made imperviousness for the target year 2010, derived from global 30m Landsat satellite data and a companion dataset to the Global Human Built-up And Settlement Extent (HBASE) dataset. Because this is a historical dataset, this item does not follow a routine update frequency.  Variables:Human Built-up and Settlement Extents (HBASE)  Probability of HBASE Class  Legend:  Color Legend Label Description   255: NoData/Clouds/Shadow The GMIS dataset consists of two components: 1) global percent of impervious cover; and 2) per-pixel associated uncertainty for the global impervious cover.    200: Not HBASE   90 - 100   80 - 90   80 - 90   70 - 80   60 - 70   50 - 60   40 - 50   30 - 40   20 - 30   10 - 20   0 - 10 Citation: Global Man-made Impervious Surface (GMIS) Dataset From Landsat. Brown de Colstoun, E. C., C. Huang, P. Wang, J. C. Tilton, B. Tan, J. Phillips, S. Niemczura, P.-Y. Ling, and R. E. Wolfe. (2017). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4P55KKF  Publication References: Documentation for the Global Man-made Impervious Surface (GMIS) Dataset From Landsat. Center for International Earth Science Information Network - CIESIN - Columbia University. (2017). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4JD4TVQ Global Human Built-up And Settlement Extent (HBASE) Dataset From Landsat. Wang, P., C. Huang, E. C. Brown de Colstoun, J. C. Tilton, and B. Tan. (2017). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4DN434S Contact: For inquiries about this service, please contact ciesin.info@ciesin.columbia.edu or post/view questions on the Earthdata Forum.

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Global Human Built-up And Settlement Extent (HBASE) Dataset From Landsat

Abstract and Limitations of Use: The Global Human Built-up And Settlement Extent (HBASE) Dataset from Landsat is a global map of HBASE derived from the Global Land Survey (GLS) Landsat dataset for the target year 2010. The HBASE dataset consists of two layers: 1) the HBASE mask; and 2) the pixel-wise probability of HBASE. These layers are co-registered to the same spatial extent at a common 30m spatial resolution. The spatial extent covers the entire globe except Antarctica and some small islands. This dataset is one of the first global, 30m datasets of urban extent to be derived from the GLS data for 2010 and is a companion dataset to the Global Man-made Impervious Surface (GMIS) dataset. The HBASE mask was created for post-processing of the GMIS dataset, but can also be utilized by users needing a binary map. The dataset is expected to have a rather broad spectrum of users, from those wishing to examine/study the fine details of urban land cover over the globe at full 30m resolution to global modelers trying to understand the climate/environmental impacts of man-made surfaces at continental to global scales. For example, the data are applicable to local modeling studies of urban impacts on the energy, water, and carbon cycles, as well as analyses at the individual country level.   Intended Use: To provide high spatial resolution estimates of global urban extent derived from global 30m Landsat satellite data for the target year 2010 and a companion dataset to the Global Man-made Impervious Surface (GMIS) dataset. Because this is a historical dataset, this item does not follow a routine update frequency. Variables:Human Built-up and Settlement Extents (HBASE)  Probability of HBASE Class Legend:Color Legend Label Description       255: NoData/Clouds/Shadow The HBASE dataset consists of two layers: 1) the HBASE mask; and 2) the pixel-wise probability of HBASE. These layers are co-registered to the same spatial extent at a common 30m spatial resolution. It identifies pixel values as a HBASE class or not.   202: Road   201: HBASE   200: Not HBASE Citation: Global Human Built-up And Settlement Extent (HBASE) Dataset From Landsat. Wang, P., C. Huang, E. C. Brown de Colstoun, J. C. Tilton, and B. Tan. (2017). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4DN434S  Publication References:  Global Man-made Impervious Surface (GMIS) Dataset From Landsat. Brown de Colstoun, E. C., C. Huang, P. Wang, J. C. Tilton, B. Tan, J. Phillips, S. Niemczura, P.-Y. Ling, and R. E. Wolfe. (2017). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4P55KKF Documentation for the Global Human Built-up And Settlement Extent (HBASE) Dataset From Landsat. Center for International Earth Science Information Network - CIESIN - Columbia University. (2017). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H48W3BCM    Contact: For inquiries about this service, please contact ciesin.info@ciesin.columbia.edu or post/view questions on the Earthdata Forum.

Buildings and infrastructure · NASA_Earthdata
Global Land Cover Mapping and Estimation Yearly 30 m V001

NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Land Cover Mapping and Estimation (GLanCE) annual 30 meter (m) Version 1 data product provides global land cover and land cover change data derived from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI). These maps provide the user community with land cover type, land cover change, metrics characterizing the magnitude and seasonality of greenness of each pixel, and the magnitude of change. GLanCE data products will be provided using a set of seven continental grids that use Lambert Azimuthal Equal Area projections parameterized to minimize distortion for each continent. Currently, North America, South America, Europe, Oceania, and Africa are available. This dataset includes global land cover and land cover change data for the period 2001 to 2019. Africa is extended through 2021. GLanCE is useful for a wide range of applications, including ecosystem, climate, and hydrologic modeling; monitoring the response of terrestrial ecosystems to climate change; carbon accounting; and land management. The GLanCE data product provides seven layers: the land cover class, the estimated day of year of change, integer identifier for class in previous year, median and amplitude of the Enhanced Vegetation Index (EVI2) in the year, rate of change in EVI2, and the change in EVI2 median from previous year to current year. A low-resolution browse image representing EVI2 amplitude is also available for each granule. Known Issues * Version 1.0 of the data set does not include Quality Assurance, Leaf Type or Leaf Phenology. These layers are populated with fill values. These layers will be included in future releases of the data product. * All GLnanCE granules should contain 7 products except the year 2001, which contain 4, as there are no change products (chgDate, EVI2chg, prevClass) for the initial year of data. * Science Data Set (SDS) values may be missing, or of lower quality, at years when land cover change occurs. This issue is a by-product of the fact that Continuous Change Detection and Classification (CCDC) does not fit models or provide synthetic reflectance values during short periods of time between time segments. * The accuracy of mapping results varies by land cover class and geography. Specifically, distinguishing between shrubs and herbaceous cover is challenging at high latitudes and in arid and semi-arid regions. Hence, the accuracy of shrub cover, herbaceous cover, and to some degree bare cover, is lower than for other classes. * Due to the combined effects of large solar zenith angles, short growing seasons, lower availability of high-resolution imagery to support training data, the representation of land cover at land high latitudes in the GLanCE product is lower than in mid latitudes. * Shadows and large variation in local zenith angles decrease the accuracy of the GLanCE product in regions with complex topography, especially at high latitudes. * Mapping results may include artifacts from variation in data density in overlap zones between Landsat scenes relative to mapping results in non-overlap zones. * Regions with low observation density due to cloud cover, especially in the tropics, and/or poor data density (e.g. Alaska, Siberia, West Africa) have lower map quality. * Artifacts from the Landsat 7 Scan Line Corrector failure are occasionally evident in the GLanCE map product. * High proportions of missing data in regions with snow and ice at high elevations result in missing data in the GLanCE SDSs. * The GlanCE data product tends to modestly overpredict developed land cover in arid regions.

Imagery and land cover · LPCLOUD
Gridded Population of the World, Version 4 (GPWv4) - Population Density, Revision 11

Abstract and Limitations of Use: The Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 consists of estimates of human population density (number of persons per square kilometer) based on counts consistent with national censuses and population registers, for the years 2000, 2005, 2010, 2015, and 2020. A proportional allocation gridding algorithm, utilizing approximately 13.5 million national and sub-national administrative Units, was used to assign population counts to 30 arc-second grid cells. The population density rasters were created by dividing the population count raster for a given target year by the land area raster. The data files were produced as global rasters at 30 arc-second (~1 km at the equator) resolution. 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Because this is a historical dataset, this item does not follow a routine update frequency.   Intended Use: To provide estimates of population density for the years 2000, 2005, 2010, 2015, and 2020, based on counts consistent with national censuses and population registers, as raster data to facilitate data integration.  Legend:ColorLegend LabelDescription 1000 Estimates of human population (number of persons per pixel) consistent with national censuses and population registers with respect to relative spatial distribution, but adjusted to match the 2015 Revision of the United Nation's World Population Prospects (UN WPP) country totals for the years 2000, 2005, 2010, 2015, and 2020. 250 - 1000 25 - 250 5 - 25 1 - 5  No DataCitation: Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. Center for International Earth Science Information Network - CIESIN - Columbia University. (2018). NASA Socioeconomic Data and Applications Center (SEDAC). 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Center for International Earth Science Information Network - CIESIN - Columbia University. (2018). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4F47M65 Contact:For inquiries about this service, please contact ciesin.info@ciesin.columbia.edu or post/view questions on the Earthdata Forum.

Population · NASA_Earthdata
Gridded Population of the World, Version 4 (GPWv4) - Population Count Adjusted to Match 2015 Revision of UN WPP Country Totals, Revision 11

Abstract and Limitations of Use: The Gridded Population of the World, Version 4 (GPWv4): Population Count Adjusted to Match 2015 Revision of UN WPP Country Totals, Revision 11 consists of estimates of human population (number of persons per pixel) consistent with national censuses and population registers with respect to relative spatial distribution, but adjusted to match the 2015 Revision of the United Nation's World Population Prospects (UN WPP) country totals for the years 2000, 2005, 2010, 2015, and 2020.A proportional allocation gridding algorithm, utilizing approximately 13.5 million national and sub-national administrative Units, was used to assign population counts to 30 arc-second grid cells. The data files were produced as global rasters at 30 arc-second (~1 km at the equator) resolution. 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Because this is a historical dataset, this item does not follow a routine update frequency.   Intended Use: To provide estimates of population count for the years 2000, 2005, 2010, 2015, and 2020, consistent with national censuses and population registers with respect to relative spatial distribution, but adjusted to match United Nations country totals.  Legend:ColorLegend LabelDescription 1000 Estimates of human population (number of persons per pixel) consistent with national censuses and population registers with respect to relative spatial distribution, but adjusted to match the 2015 Revision of the United Nation's World Population Prospects (UN WPP) country totals for the years 2000, 2005, 2010, 2015, and 2020. 250 - 1000 25 - 250 5 - 25 1 - 5 Citation: Gridded Population of the World, Version 4 (GPWv4): Population Count Adjusted to Match 2015 Revision of UN WPP Country Totals, Revision 11. Center for International Earth Science Information Network - CIESIN - Columbia University. 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Population · NASA_Earthdata
Global Forest Cover Change Tree Cover Multi-Year Global 30m V003

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Biodiversity · LPCLOUD
Global Forest Cover Change Forest Cover Change Multi-Year Global 30m V001

The Land Processes Distributed Active Archive Center (LP DAAC) archives and distributes Global Forest Cover Change (GFCC) data products through the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program. The GFCC Forest Cover Change Multi-Year Global dataset provides estimates of changes in forest cover from 1990 to 2000 and from 2000 to 2005 at 30 meter spatial resolution. The GFCC30FCC product represents a global record of fine-scale changes in forest dynamics between observation periods. The forest cover change product was generated from the GFCC Tree Cover (GFCC30TC) product which is based on Global Land Survey (GLS) data acquired by the Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensors. Each forest cover product has two GeoTIFF files associated with it; a change map file and a change probability file. Data follow the Worldwide Reference System-2 tiling scheme. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD).

Biodiversity · LPCLOUD

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