Der globale Datensatz zur menschlichen Modifikation (global Human Modification, gHM) bietet ein kumulatives Maß für die menschliche Modifikation von Landflächen weltweit mit einer Auflösung von 1 km². Die gHM-Werte liegen zwischen 0,0 und 1,0. Sie werden berechnet, indem der Anteil eines bestimmten Orts (Pixel), der verändert wird, sowie die geschätzte Intensität der Änderung, die mit einer bestimmten Art der menschlichen Modifikation oder „Belastung“ verbunden ist, geschätzt werden.
Fünf wichtige anthropogene Stressfaktoren um 2016 wurden anhand von 13 einzelnen Datasets kartiert:
Kennedy, C.M., J.R. Oakleaf, D.M. Theobald, S. Baruch-Murdo und J. Kiesecker. 2019. Managing
the middle: A shift in conservation priorities based on the global human modification gradient.
Global Change Biology 00:1–16. doi:10.1111/gcb.14549
Der globale Datensatz zur menschlichen Modifikation (global Human Modification, gHM) bietet ein kumulatives Maß für die menschliche Modifikation von Landflächen weltweit mit einer Auflösung von 1 km². Die gHM-Werte liegen zwischen 0,0 und 1,0 und werden berechnet, indem der Anteil eines bestimmten Standorts (Pixel), der geändert wird, die geschätzte Intensität der Änderung in Verbindung mit einem …
[null,null,[],[[["\u003cp\u003eThe Global Human Modification (gHM) dataset provides a cumulative measure of human impact on terrestrial lands globally at a 1-kilometer resolution.\u003c/p\u003e\n"],["\u003cp\u003egHM values range from 0.0 to 1.0, representing the proportion and intensity of modification caused by human activities.\u003c/p\u003e\n"],["\u003cp\u003eFive major anthropogenic stressors are considered: human settlement, agriculture, transportation, mining/energy production, and electrical infrastructure.\u003c/p\u003e\n"],["\u003cp\u003eThis dataset was created by Conservation Science Partners and is available for the year 2016.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is licensed under CC-BY-NC-SA-4.0 and can be accessed and analyzed using Google Earth Engine.\u003c/p\u003e\n"]]],["The Global Human Modification dataset (gHM) quantifies human impact on terrestrial lands at a 1km resolution, ranging from 0.0-1.0, for the year 2016. It assesses modification by estimating the proportion and intensity of human-induced changes. Five primary stressors are considered: settlements, agriculture, transportation, mining/energy, and electrical infrastructure. Data was re-projected to WGS84 for Earth Engine. The dataset, available via `ee.ImageCollection(\"CSP/HM/GlobalHumanModification\")`, is provided by Conservation Science Partners and distributed under a CC-BY-NC-SA-4.0 license.\n"],null,["# CSP gHM: Global Human Modification\n\nDataset Availability\n: 2016-01-01T00:00:00Z--2016-12-31T00:00:00Z\n\nDataset Provider\n:\n\n\n [Conservation Science Partners](https://www.csp-inc.org/)\n\nCadence\n: 1 Year\n\nTags\n:\n [csp](/earth-engine/datasets/tags/csp) [fragmentation](/earth-engine/datasets/tags/fragmentation) [human-modification](/earth-engine/datasets/tags/human-modification) [landcover](/earth-engine/datasets/tags/landcover) [landscape-gradient](/earth-engine/datasets/tags/landscape-gradient) [population](/earth-engine/datasets/tags/population) [stressors](/earth-engine/datasets/tags/stressors) \ntnc \n\n#### Description\n\nThe global Human Modification dataset (gHM) provides a cumulative measure of human modification\nof terrestrial lands globally at 1 square-kilometer resolution. The gHM\nvalues range from 0.0-1.0 and are calculated by estimating the proportion of a given location\n(pixel) that is modified, the estimated intensity of modification\nassociated with a given type of human modification or \"stressor\".\n5 major anthropogenic stressors circa 2016 were mapped using 13\nindividual datasets:\n\n- human settlement (population density, built-up areas)\n- agriculture (cropland, livestock)\n- transportation (major, minor, and two-track roads; railroads)\n- mining and energy production\n- electrical infrastructure (power lines, nighttime lights)\n\nPlease see the paper for additional methodological details.\nThis asset was re-projected to WGS84 for use in Earth Engine.\n\n### Bands\n\n\n**Pixel Size**\n\n1000 meters\n\n**Bands**\n\n| Name | Units | Min | Max | Pixel Size | Description |\n|-------|-------|-----|-----|------------|---------------------------|\n| `gHM` | km\\^2 | 0 | 1 | meters | global Human Modification |\n\n### Terms of Use\n\n**Terms of Use**\n\n[CC-BY-NC-SA-4.0](https://spdx.org/licenses/CC-BY-NC-SA-4.0.html)\n\n### Citations\n\nCitations:\n\n- Kennedy, C.M., J.R. Oakleaf, D.M. Theobald, S. Baruch-Murdo, and J. Kiesecker. 2019. Managing\n the middle: A shift in conservation priorities based on the global human modification gradient.\n Global Change Biology 00:1-16. [doi:10.1111/gcb.14549](https://doi.org/10.1111/gcb.14549)\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.ImageCollection('CSP/HM/GlobalHumanModification');\n\nvar visualization = {\n bands: ['gHM'],\n min: 0.0,\n max: 1.0,\n palette: ['0c0c0c', '071aff', 'ff0000', 'ffbd03', 'fbff05', 'fffdfd']\n};\n\nMap.centerObject(dataset);\n\nMap.addLayer(dataset, visualization, 'Human modification');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/CSP/CSP_HM_GlobalHumanModification) \n[CSP gHM: Global Human Modification](/earth-engine/datasets/catalog/CSP_HM_GlobalHumanModification) \nThe global Human Modification dataset (gHM) provides a cumulative measure of human modification of terrestrial lands globally at 1 square-kilometer resolution. The gHM values range from 0.0-1.0 and are calculated by estimating the proportion of a given location (pixel) that is modified, the estimated intensity of modification associated with a ... \nCSP/HM/GlobalHumanModification, csp,fragmentation,human-modification,landcover,landscape-gradient,population,stressors \n2016-01-01T00:00:00Z/2016-12-31T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://www.csp-inc.org/)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/CSP_HM_GlobalHumanModification)"]]
