L'ensemble de données mondial sur la modification humaine (gHM) fournit une mesure cumulative de la modification humaine des terres terrestres à l'échelle mondiale, avec une résolution de 1 km carré. Les valeurs gHM sont comprises entre 0,0 et 1,0. Elles sont calculées en estimant la proportion d'un emplacement donné (pixel) qui est modifié, ainsi que l'intensité estimée de la modification associée à un type donné de modification humaine ou de "facteur de stress".
Cinq principaux facteurs de stress anthropiques ont été cartographiés vers 2016 à l'aide de 13 ensembles de données individuels :
Établissements humains (densité de population, zones construites)
agriculture (cultures, élevage)
transport (routes principales, routes secondaires et chemins de fer)
Kennedy, C.M., J.R. Oakleaf, D.M. Theobald, S. Baruch-Murdo et 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
L'ensemble de données mondial sur la modification humaine (gHM) fournit une mesure cumulative de la modification humaine des terres terrestres à l'échelle mondiale, avec une résolution de 1 km carré. Les valeurs gHM sont comprises entre 0,0 et 1,0. Elles sont calculées en estimant la proportion d'un emplacement donné (pixel) qui est modifié, l'intensité estimée de la modification associée à un …
[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)"]]
