Global Human Footprint (Geographic), v2 (1995 – 2004)

Global Human Footprint Index is the relative human influence in each terrestrial biome expressed as a percentage. The purpose is to provide an updated map of anthropogenic impacts on the environment in geographic projection which can be used in wildlife conservation planning, natural resource management, and research on human-environment interactions. Dataset Summary The Global Human Footprint Index Dataset of the Last of the Wild Project, Version 2, 2005 (LWP-2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1-kilometer grid cells, created from nine global data layers covering human population pressure (population density), human land use and infrastructure (built-up areas, nighttime lights, land use/land cover), and human access (coastlines, roads, railroads, navigable rivers). A value of zero represents the least influenced- the “most wild” part of the biome with value of 100 representing the most influenced (least wild) part of the biome. The dataset is produced by the Wildlife Conservation Society (WCS) and the Columbia University Center for International Earth Science Information Network (CIESIN). Recommended Citation Wildlife Conservation Society - WCS, and Center for International Earth Science Information Network - CIESIN - Columbia University. 2005. Last of the Wild Project, Version 2, 2005 (LWP-2): Global Human Footprint Dataset (Geographic). Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://dx.doi.org/10.7927/H4M61H5F. Accessed DAY MONTH YEAR.

Overview This map layer prepared by the Commission for Environmental Cooperation (CEC) shows the direct influence of humans on terrestrial ecosystems across North America. The Human Influence Index (HII) is based on population density, built-up areas, roads, railroads, navigable rivers, coastlines, land use/land cover, and nighttime lights. HII values range from 0 to 64, with 0 representing no human influence and 64 representing maximum human influence, based on all eight measures of human influence. The data layer was compiled by the Wildlife Conservation Society (WCS) and the Center for International Earth Science Information Network (CIESIN).  Geographic Coverage The coverage spans terrestrial areas of North America, including Canada, Mexico, and the United States. Data Sources and Licensing Commission for Environmental Cooperation (CEC). The Last of the Wild, Version Two. 2005. Global human influence index (HII). Wildlife Conservation Society (WCS), and Center for International Earth Science Information Network (CIESIN). The data is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing redistribution and adaptation with appropriate attribution. Update frequency: Not planned Limitations of use: Acknowledgment of the Wildlife Conservation Society (WCS) and the Center for International Earth Science Information Network (CIESIN) is appreciated in products derived from these data. Vintage: 2005 Applications (Intended Use) Conservation planning and identification of low-impact/wilderness areas. Assessing human pressure on biomes and ecoregions across North America. Supporting natural resource management and sustainability research. Cross-border environmental cooperation and policy-making among North American nations. Files Download

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.

To produce the Forest Landscape Integrity Index (FLII), four data sets were combined representing: (i) forest extent; (ii) ‘observed’ pressure from high impact, localized human activities for which spatial datasets exist, specifically: infrastructure, agriculture, and recent deforestation; (iii) ‘inferred’ pressure associated with edge effects, and other diffuse processes, (e.g. activities such as hunting and selective logging) modelled using proximity to observed pressures; and iv) anthropogenic changes in forest connectivity due to forest loss. These datasets were combined to produce an index score for each forest pixel (300m), with the highest scores reflecting the highest forest integrity, and applied to forest extent for the start of 2019. Globally consistent parameters were used for all elements (i.e. parameters do not vary geographically). All calculations were conducted in Google Earth Engine. Displays forest condition as a continuous index determined by degree of anthropogenic modification

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.

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. To enable faster global processing, and in support of research commUnities, the 30 arc-second count data were aggregated to 2.5 arc-minute, 15 arc-minute, 30 arc-minute and 1 degree resolutions to produce density rasters at these resolutions. 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). DOI: https://doi.org/10.7927/H49C6VHW   Publication References:Gridded Population of the World, Version 3 (GPWv3): Population Density Grid. Center for International Earth Science Information Network - CIESIN - Columbia University, and Centro Internacional de Agricultura Tropical - CIAT. (2005). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4XK8CG2 Gridded Population of the World, Version 4 (GPWv4): Population Density. Center for International Earth Science Information Network - CIESIN - Columbia University. (2016). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4NP22DQ Taking Advantage of the Improved Availability of Census Data: A First Look at the Gridded Population of the World, Version 4. Doxsey-Whitfield, E., K. MacManus, S. B. Adamo, L. Pistolesi, J. Squires, O. Borkovska and S. R. Baptista. (2015). . DOI: https://doi.org/10.1080/23754931.2015.1014272 Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 10. Center for International Earth Science Information Network - CIESIN - Columbia University. (2017). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4DZ068D Gridded Population of the World, Version 4 (GPWv4): Administrative Unit Center Points with Population Estimates, Revision 11. Center for International Earth Science Information Network - CIESIN - Columbia University. (2018). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4BC3WMT Gridded Population of the World, Version 4 (GPWv4): Data Quality Indicators, Revision 11. Center for International Earth Science Information Network - CIESIN - Columbia University. (2018). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H42Z13KG Gridded Population of the World, Version 4 (GPWv4): Land and Water Area, Revision 11. Center for International Earth Science Information Network - CIESIN - Columbia University. (2018). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4Z60M4Z Gridded Population of the World, Version 4 (GPWv4): National Identifier Grid, Revision 11. Center for International Earth Science Information Network - CIESIN - Columbia University. (2018). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4TD9VDP Gridded Population of the World, Version 4 (GPWv4): Population Count, Revision 11. Center for International Earth Science Information Network - CIESIN - Columbia University. (2018). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4JW8BX5 Documentation for the Gridded Population of the World, Version 4 (GPWv4), Revision 11. Center for International Earth Science Information Network - CIESIN - Columbia University. (2018). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H45Q4T5F Gridded Population of the World, Version 4 (GPWv4): Basic Demographic Characteristics, Revision 11. Center for International Earth Science Information Network - CIESIN - Columbia University. (2018). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H46M34XX 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. (2018). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4PN93PB Gridded Population of the World, Version 4 (GPWv4): Population Density Adjusted to Match 2015 Revision UN WPP Country Totals, Revision 11. 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.