Data for detailed temporal mapping of global human modification from 1990 to 2017 ...
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, 1995, 2000, 2005, 2010, 2015, and 2017 to eval...
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ftdatacite:10.5281/zenodo.3963012 2023-07-23T04:15:37+02:00 Data for detailed temporal mapping of global human modification from 1990 to 2017 ... Theobald, David M. Kennedy, Christina Chen, Bin Oakleaf, James Baruch-Mordo, Sharon Kiesecker, Joe 2023 https://dx.doi.org/10.5281/zenodo.3963012 https://zenodo.org/record/3963012 unknown Zenodo https://dx.doi.org/10.5194/essd-2019-252 https://dx.doi.org/10.5281/zenodo.3963013 https://dx.doi.org/10.5281/zenodo.4681361 https://dx.doi.org/10.5281/zenodo.4737841 https://dx.doi.org/10.5281/zenodo.4913396 https://dx.doi.org/10.5281/zenodo.5234144 https://dx.doi.org/10.5281/zenodo.5236125 https://dx.doi.org/10.5281/zenodo.5338803 https://dx.doi.org/10.5281/zenodo.7534895 Open Access Creative Commons Attribution 1.0 Generic https://creativecommons.org/licenses/by/1.0/legalcode cc-by-1.0 info:eu-repo/semantics/openAccess land use global change human modification land cover change ecological integrity naturalness connectivity dataset Dataset 2023 ftdatacite https://doi.org/10.5281/zenodo.396301210.5194/essd-2019-25210.5281/zenodo.396301310.5281/zenodo.468136110.5281/zenodo.473784110.5281/zenodo.491339610.5281/zenodo.523414410.5281/zenodo.523612510.5281/zenodo.533880310.5281/zenodo.7534895 2023-07-03T20:01:44Z 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, 1995, 2000, 2005, 2010, 2015, and 2017 to evaluate temporal changes and spatial patterns of land use modification of terrestrial lands (excluding Antarctica). 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 km^2 resolution), temporally consistent (for 1990-2015, every 5 years), 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 that represents ~2017 conditions and has 14 stressors for an even more ... : The datasets provided here contain revisions to the 1990, 1995, 2000, 2005, 2010, 2015 (change) and 2017 (static) datasets. Analyses that used previous versions should be re-run using these v1.5 data. The file naming convention for the zip-files that contain the datasets provided here is as follows: gHMv_5_xx_yyyyz_300m_60land, where: xx is the stressor type. xx = '' for overall stressor (major stressors are combined); xx = 'AG' for agricultural and timber harvest; xx = 'BU' for built-up areas; xx = 'EX' for extractive (energy.& mining); xx = 'HI' for human intrusion; xx = 'NS' for natural system modification and xx = 'TI' for transportation and linear infrastructure. yyyy is the conditions estimated for a given year: 1990, 1995, 2000, 2005, 2010, 2015, or 2017. z is an indicator for change vs. static, z = 'c' for datasets using only temporally consistent data to support temporal change analyses, z = '' for 2017 that contains additional stressors that represents the most comprehensive estimates, but ... Dataset Antarc* Antarctica DataCite Metadata Store (German National Library of Science and Technology) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
topic |
land use global change human modification land cover change ecological integrity naturalness connectivity |
spellingShingle |
land use global change human modification land cover change ecological integrity naturalness connectivity Theobald, David M. Kennedy, Christina Chen, Bin Oakleaf, James Baruch-Mordo, Sharon Kiesecker, Joe Data for detailed temporal mapping of global human modification from 1990 to 2017 ... |
topic_facet |
land use global change human modification land cover change ecological integrity naturalness connectivity |
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, 1995, 2000, 2005, 2010, 2015, and 2017 to evaluate temporal changes and spatial patterns of land use modification of terrestrial lands (excluding Antarctica). 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 km^2 resolution), temporally consistent (for 1990-2015, every 5 years), 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 that represents ~2017 conditions and has 14 stressors for an even more ... : The datasets provided here contain revisions to the 1990, 1995, 2000, 2005, 2010, 2015 (change) and 2017 (static) datasets. Analyses that used previous versions should be re-run using these v1.5 data. The file naming convention for the zip-files that contain the datasets provided here is as follows: gHMv_5_xx_yyyyz_300m_60land, where: xx is the stressor type. xx = '' for overall stressor (major stressors are combined); xx = 'AG' for agricultural and timber harvest; xx = 'BU' for built-up areas; xx = 'EX' for extractive (energy.& mining); xx = 'HI' for human intrusion; xx = 'NS' for natural system modification and xx = 'TI' for transportation and linear infrastructure. yyyy is the conditions estimated for a given year: 1990, 1995, 2000, 2005, 2010, 2015, or 2017. z is an indicator for change vs. static, z = 'c' for datasets using only temporally consistent data to support temporal change analyses, z = '' for 2017 that contains additional stressors that represents the most comprehensive estimates, but ... |
format |
Dataset |
author |
Theobald, David M. Kennedy, Christina Chen, Bin Oakleaf, James Baruch-Mordo, Sharon Kiesecker, Joe |
author_facet |
Theobald, David M. Kennedy, Christina Chen, Bin Oakleaf, James Baruch-Mordo, Sharon Kiesecker, Joe |
author_sort |
Theobald, David M. |
title |
Data for detailed temporal mapping of global human modification from 1990 to 2017 ... |
title_short |
Data for detailed temporal mapping of global human modification from 1990 to 2017 ... |
title_full |
Data for detailed temporal mapping of global human modification from 1990 to 2017 ... |
title_fullStr |
Data for detailed temporal mapping of global human modification from 1990 to 2017 ... |
title_full_unstemmed |
Data for detailed temporal mapping of global human modification from 1990 to 2017 ... |
title_sort |
data for detailed temporal mapping of global human modification from 1990 to 2017 ... |
publisher |
Zenodo |
publishDate |
2023 |
url |
https://dx.doi.org/10.5281/zenodo.3963012 https://zenodo.org/record/3963012 |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
https://dx.doi.org/10.5194/essd-2019-252 https://dx.doi.org/10.5281/zenodo.3963013 https://dx.doi.org/10.5281/zenodo.4681361 https://dx.doi.org/10.5281/zenodo.4737841 https://dx.doi.org/10.5281/zenodo.4913396 https://dx.doi.org/10.5281/zenodo.5234144 https://dx.doi.org/10.5281/zenodo.5236125 https://dx.doi.org/10.5281/zenodo.5338803 https://dx.doi.org/10.5281/zenodo.7534895 |
op_rights |
Open Access Creative Commons Attribution 1.0 Generic https://creativecommons.org/licenses/by/1.0/legalcode cc-by-1.0 info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5281/zenodo.396301210.5194/essd-2019-25210.5281/zenodo.396301310.5281/zenodo.468136110.5281/zenodo.473784110.5281/zenodo.491339610.5281/zenodo.523414410.5281/zenodo.523612510.5281/zenodo.533880310.5281/zenodo.7534895 |
_version_ |
1772176506977517568 |