Küresel İnsan Değişikliği veri kümesi (gHM), küresel olarak karasal alanlardaki insan değişikliğinin 1 kilometrekare çözünürlükte kümülatif bir ölçüsünü sağlar. gHM değerleri 0,0-1,0 aralığındadır ve belirli bir konumun (piksel) değiştirilen oranını, belirli bir insan değişikliği türü veya "stres faktörü" ile ilişkili tahmini değişiklik yoğunluğunu tahmin ederek hesaplanır.
2016 civarında 5 büyük insan kaynaklı stres faktörü, 13 ayrı veri kümesi kullanılarak haritalandırıldı:
insan yerleşimi (nüfus yoğunluğu, yerleşim alanları)
tarım (ekili alan, hayvancılık)
ulaşım (ana, tali ve iki şeritli yollar; demiryolları)
madencilik ve enerji üretimi
elektrik altyapısı (güç hatları, gece ışıkları)
Ek metodolojik ayrıntılar için lütfen makaleyi inceleyin.
Bu öğe, Earth Engine'de kullanılmak üzere WGS84'e yeniden yansıtıldı.
Kennedy, C.M., J.R. Oakleaf, D.M. Theobald, S. Baruch-Murdo ve J. Kiesecker. 2019. Ortayı yönetmek: Küresel insan müdahalesi eğimine dayalı olarak koruma önceliklerinde değişim.
Global Change Biology 00:1-16. doi:10.1111/gcb.14549
Küresel İnsan Değişikliği veri kümesi (gHM), küresel olarak karasal alanların insan tarafından değiştirilmesinin 1 kilometrekare çözünürlükte kümülatif bir ölçüsünü sağlar. gHM değerleri 0,0-1,0 aralığındadır ve belirli bir konumun (piksel) değiştirilen oranını tahmin ederek, değişikliğin tahmini yoğunluğunu hesaplayarak belirlenir.
[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)"]]
