DOI: 10.5061/dryad.n5tb2rbs1
title: Data from: Detailed temporal mapping of global human modification from 1990 to 2017

description: Data on the extent, patterns, and trends of human land use are critically
 important to support global and national priorities for conservation and
 sustainable development. To inform these issues, we created a series of
 detailed global datasets for 1990, 2000, 2010, 2015, and 2017 to evaluate
 temporal and spatial trends of land use modification of terrestrial lands
 (excluding Antarctica). Our novel datasets are detailed (0.09 km2
 resolution), temporally consistent (for 1990-2015), comprehensive (11
 change stressors, 14 current), robust (using an established framework and
 incorporating classification errors and parameter uncertainty), and
 strongly validated. We also provide a dataset for ~2017 with 14 stressors
 for an even more comprehensive dataset. Also provided is a
 land/water mask to support subsequent analyses. Please also be sure to
 check your spam folder if you do not receive an email with the link from
 Dryad, which is provided because of the large file size.
description: Detailed global datasets for 1990, 2000, 2010, and 2015 for land
 use modification of terrestrial lands (excluding Antarctica) are provided
 here. These data were calculated using the degree of human modification
 approach that combines the proportion of a pixel of a given stressor (i.e.
 footprint) times the intensity of that stressor (ranging from 0 to
 1.0). Our novel datasets are detailed (0.09 km2 resolution), temporally
 consistent (for 1990-2015), comprehensive (11 change stressors, 14
 current), robust (using an established framework and incorporating
 classification errors and parameter uncertainty), and strongly validated.
 We also provide a dataset for ~2017 with 14 stressors for an even more
 comprehensive dataset, but it should not be used to calculate change with
 the other datasets (1990-2015). Also provided is a land/water mask (~2015
 conditions) to support subsequent analyses. The file
 gHM_landLakeReservoirOcean300m.zip provides a land/water mask, and
 differentiates land, ocean, lakes, and reservoirs to allow subsequent
 analyses to support subsequent analyses. We also provide 5 datasets
 representing major stressor groups (i.e. built-up, ag/timber,
 energy/mining, transportation/corridors, and human intrusion) that are
 components of the full dataset that contains all stressors.
description: The file naming convention for the zip-files that contain the
 datasets provided here is as follows:
 gHM_landLakeReservoirOcean300m.zip - contains TIFs at 300 m
 resolution to represent the following classes: 1=land, 2=lake (natural
 water bodies), 3=reservoirs (water bodies created by dams), and
 4=ocean. gHMv1_300m_1990_change.zip - contains TIFs at
 300 m resolution for calculating change between 1990 and 2000, 2010, or
 2015. gHMv1_300m_2000_change.zip - contains TIFs at 300
 m resolution for calculating change between 2000 and 1990, 2010, or
 2015. gHMv1_300m_2010_change.zip - contains TIFs at 300
 m resolution for calculating change between 2010 and 1990, 2000, or
 2015. gHMv1_300m_2015_change.zip - contains TIFs at 300
 m resolution for calculating change between 2015 and 1990, 2000, or
 2010. gHMv1_300m_2017_static.zip - contains TIFs at 300
 m resolution that contains all stressors that represents ~2017 conditions.
 This is NOT to be used to compare to other "change"
 datasets. gHMv1_1000m_2017_static_stressors.zip -
 contains TIFs at 1000 m resolution, where each major stressor group is
 separate: "static_builtup" (urban & built-up),
 "static_ag" (agriculture and biological harvesting of forests),
 "static_energy" (energy production and mining),
 "static_trans" (transportation & service corridors), and
 "static_intrusion" (human intrusions, natural system
 modifications, and pollution).  The original values of
 the datasets ranged from 0.0 to 1.0, where 0.0 is no human modification
 and 1.0 is full or complete human modification. These values were
 represented as 32-bit floating point values, but were converted to a
 16-bit integer to reduce file size, by multiplying by 32767. Note that to
 obtain the terrestrial portions of the globe, these datasets will need to
 be masked by the gHM_landLakeReservoirOcean300m dataset using values 2 and
 4 to set NO DATA values. Datasets are in EPSG 3857 coordinates and the
 extent of longitude/latitude is -180, -75, 180, 85.