Esse conjunto de dados contém informações sobre a mudança anual da área de superfície impermeável global de 1985 a 2018 com uma resolução de 30 m. A mudança de permeável para impermeável foi determinada usando uma abordagem combinada de classificação supervisionada e verificação de consistência temporal. Pixels impermeáveis são definidos como acima de 50% de impermeabilidade. O ano da transição (de permeável para impermeável) pode ser identificado pelo valor do pixel, que varia de 34 (ano: 1985) a 1 (ano: 2018). Por exemplo, a superfície impermeável em 1990 pode ser revelada como o valor do pixel maior que 29 (consulte a tabela de pesquisa). Esse conjunto de dados é temporalmente consistente, seguindo a conversão de pervious (por exemplo, não urbano) para impervious (por exemplo, urbano) monotonicamente. Para mais informações sobre a abordagem de mapeamento e a avaliação, consulte Mapas anuais da área artificial impermeável global (GAIA) entre 1985 e 2018 (Gong et al. 2020).
Bandas
Tamanho do pixel 30 metros
Bandas
Nome
Mín.
Máx.
Tamanho do pixel
Descrição
change_year_index
1*
34*
metros
Ano da transição de permeável para impermeável. De 34 (ano: 1985) a 1 (ano: 2018)
Gong, P., Li, X., Wang, J., Bai, Y., Chen, B., Hu, T., ... & Zhou, Y. (2020).
Mapas anuais da área artificial impermeável global (GAIA, na sigla em inglês) entre 1985 e 2018.
Remote Sensing of Environment, 236, 111510.
Esse conjunto de dados contém informações sobre a mudança anual da área de superfície impermeável global de 1985 a 2018 com uma resolução de 30 m. A mudança de permeável para impermeável foi determinada usando uma abordagem combinada de classificação supervisionada e verificação de consistência temporal. Pixels impermeáveis são definidos como acima de 50% de impermeabilidade. O ano da transição…
[null,null,[],[[["\u003cp\u003eThe FROM-GLC GAIA dataset provides annual change information of global impervious surface area at a 30m resolution from 1985 to 2018.\u003c/p\u003e\n"],["\u003cp\u003eIt identifies the year of transition from pervious (e.g., non-urban) to impervious (e.g., urban) surfaces using a combined approach of supervised classification and temporal consistency checking.\u003c/p\u003e\n"],["\u003cp\u003ePixel values represent the year of change, ranging from 34 (1985) to 1 (2018), allowing for the analysis of impervious surface expansion over time.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is freely available for research, education, and non-profit use under a Creative Commons Attribution 4.0 International License.\u003c/p\u003e\n"],["\u003cp\u003eUsers can access and analyze this dataset using the Google Earth Engine platform.\u003c/p\u003e\n"]]],[],null,["# Tsinghua FROM-GLC Year of Change to Impervious Surface\n\nDataset Availability\n: 1985-01-01T00:00:00Z--2018-12-31T00:00:00Z\n\nDataset Provider\n:\n\n\n [Tsinghua University](http://data.ess.tsinghua.edu.cn/)\n\nTags\n:\n [built](/earth-engine/datasets/tags/built) [population](/earth-engine/datasets/tags/population) [tsinghua](/earth-engine/datasets/tags/tsinghua) [urban](/earth-engine/datasets/tags/urban) \n development \nimpervious \n\n#### Description\n\nThis dataset contains annual change information of global impervious surface area from 1985 to\n2018 at a 30m resolution. Change from pervious to impervious was determined using a combined\napproach of supervised classification and temporal consistency checking. Impervious pixels are\ndefined as above 50% impervious. The year of the transition (from pervious to impervious) can\nbe identified from the pixel value, ranging from 34 (year: 1985) to 1 (year: 2018). For\nexample, the impervious surface in 1990 can be revealed as the pixel value greater than 29\n(see the lookup table). This dataset is temporally consistent, following the conversion from\npervious (e.g., non-urban) to impervious (e.g., urban) monotonically. For more information\nabout the mapping approach and assessment, see\n[Annual maps of global artificial impervious area (GAIA) between 1985 and 2018\n(Gong et al. 2020)](https://doi.org/10.1016/j.rse.2019.111510).\n\n### Bands\n\n\n**Pixel Size**\n\n30 meters\n\n**Bands**\n\n| Name | Min | Max | Pixel Size | Description |\n|---------------------|-----|------|------------|-------------------------------------------------------------------------------------------------|\n| `change_year_index` | 1\\* | 34\\* | meters | Year of the transition from from pervious to impervious. From 34 (year: 1985) to 1 (year: 2018) |\n\n\\* estimated min or max value\n\n**change_year_index Class Table**\n\n| Value | Color | Description |\n|-------|---------|-------------|\n| 1 | #014352 | 2018 |\n| 2 | #1a492c | 2017 |\n| 3 | #071ec4 | 2016 |\n| 4 | #b5ca36 | 2015 |\n| 5 | #729eac | 2014 |\n| 6 | #8ea5de | 2013 |\n| 7 | #818991 | 2012 |\n| 8 | #62a3c3 | 2011 |\n| 9 | #ccf4fe | 2010 |\n| 10 | #74f0b9 | 2009 |\n| 11 | #32bc55 | 2008 |\n| 12 | #c72144 | 2007 |\n| 13 | #56613b | 2006 |\n| 14 | #c14683 | 2005 |\n| 15 | #c31c25 | 2004 |\n| 16 | #5f6253 | 2003 |\n| 17 | #11bf85 | 2002 |\n| 18 | #a61b26 | 2001 |\n| 19 | #99fbc5 | 2000 |\n| 20 | #188aaa | 1999 |\n| 21 | #c2d7f1 | 1998 |\n| 22 | #b7d9d8 | 1997 |\n| 23 | #856f96 | 1996 |\n| 24 | #109c6b | 1995 |\n| 25 | #2de3f4 | 1994 |\n| 26 | #9a777d | 1993 |\n| 27 | #151796 | 1992 |\n| 28 | #c033d8 | 1991 |\n| 29 | #510037 | 1990 |\n| 30 | #640c21 | 1989 |\n| 31 | #31a191 | 1988 |\n| 32 | #223ab0 | 1987 |\n| 33 | #b692ac | 1986 |\n| 34 | #2de3f4 | 1985 |\n\n### Terms of Use\n\n**Terms of Use**\n\nThis work is licensed under a Creative Commons Attribution 4.0 International License.\n\u003chttps://creativecommons.org/licenses/by/4.0/\u003e\n\n### Citations\n\nCitations:\n\n- Gong, P., Li, X., Wang, J., Bai, Y., Chen, B., Hu, T., ... \\& Zhou, Y. (2020).\n Annual maps of global artificial impervious area (GAIA) between 1985 and 2018.\n Remote Sensing of Environment, 236, 111510.\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.Image('Tsinghua/FROM-GLC/GAIA/v10');\n\nvar visualization = {\n bands: ['change_year_index'],\n min: 0,\n max: 34,\n palette: [\n '014352', '1a492c', '071ec4', 'b5ca36', '729eac', '8ea5de',\n '818991', '62a3c3', 'ccf4fe', '74f0b9', '32bc55', 'c72144',\n '56613b', 'c14683', 'c31c25', '5f6253', '11bf85', 'a61b26',\n '99fbc5', '188aaa', 'c2d7f1', 'b7d9d8', '856f96', '109c6b',\n '2de3f4', '9a777d', '151796', 'c033d8', '510037', '640c21',\n '31a191', '223ab0', 'b692ac', '2de3f4',\n ]\n};\n\nMap.setCenter(-37.62, 25.8, 2);\n\nMap.addLayer(dataset, visualization, 'Change year index');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/Tsinghua/Tsinghua_FROM-GLC_GAIA_v10) \n[Tsinghua FROM-GLC Year of Change to Impervious Surface](/earth-engine/datasets/catalog/Tsinghua_FROM-GLC_GAIA_v10) \nThis dataset contains annual change information of global impervious surface area from 1985 to 2018 at a 30m resolution. Change from pervious to impervious was determined using a combined approach of supervised classification and temporal consistency checking. Impervious pixels are defined as above 50% impervious. The year of the transition ... \nTsinghua/FROM-GLC/GAIA/v10, built,population,tsinghua,urban \n1985-01-01T00:00:00Z/2018-12-31T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/http://data.ess.tsinghua.edu.cn/)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/Tsinghua_FROM-GLC_GAIA_v10)"]]
