You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
The GLAD Global Land Cover and Land Use Change dataset quantifies changes in forest extent and height, cropland, built-up lands, surface water, and perennial snow and ice extent from the year 2000 to 2020 at 30-m spatial resolution. The global dataset derived from the GLAD Landsat Analysis Ready Data. Each thematic product was independently derived using state-of-the-art, locally and regionally calibrated machine learning tools. Each thematic layer was validated independently using a statistical sampling.
Data Download
Dataset already hosted as GEE asset, but with each epoch separated. The time series can be combined into a single image collection as follow:
var landmask = ee.Image("projects/glad/OceanMask").lte(1)
var m00 = ee.Image('projects/glad/GLCLU2020/v2/LCLUC_2000').updateMask(landmask).set('year', 2000);
var m05 = ee.Image('projects/glad/GLCLU2020/v2/LCLUC_2005').updateMask(landmask).set('year', 2005);
var m10 = ee.Image('projects/glad/GLCLU2020/v2/LCLUC_2010').updateMask(landmask).set('year', 2010);
var m15 = ee.Image('projects/glad/GLCLU2020/v2/LCLUC_2015').updateMask(landmask).set('year', 2015);
var m20 = ee.Image('projects/glad/GLCLU2020/v2/LCLUC_2020').updateMask(landmask).set('year', 2020);
// Create the image collection
var imageCollection = ee.ImageCollection([m00, m05, m10, m15, m20]);
The change between 2000 and 2020 can be assessed here: var change = ee.Image('projects/glad/GLCLU2020/v2/LCLUC').updateMask(landmask);
Dataset Reference
Potapov P., Hansen M.C., Pickens A., Hernandez-Serna A., Tyukavina A., Turubanova S., Zalles V., Li X., Khan A., Stolle F., Harris N., Song X.-P., Baggett A., Kommareddy I., Kommareddy A. (2022) The global 2000-2020 land cover and land use change dataset derived from the Landsat archive: first results. Frontiers in Remote Sensing [https://doi.org/10.3389/frsen.2022.856903] [Open PDF]
Earth Engine Snippet if dataset already in GEE
varlandmask=ee.Image("projects/glad/OceanMask").lte(1)varchange=ee.Image('projects/glad/GLCLU2020/v2/LCLUC').updateMask(landmask);varm00=ee.Image('projects/glad/GLCLU2020/v2/LCLUC_2000').updateMask(landmask);varm05=ee.Image('projects/glad/GLCLU2020/v2/LCLUC_2005').updateMask(landmask);varm10=ee.Image('projects/glad/GLCLU2020/v2/LCLUC_2010').updateMask(landmask);varm15=ee.Image('projects/glad/GLCLU2020/v2/LCLUC_2015').updateMask(landmask);varm20=ee.Image('projects/glad/GLCLU2020/v2/LCLUC_2020').updateMask(landmask);varvisParamMap={"min":0,"max":255,"palette":["FEFECC","FAFAC3","F7F7BB","F4F4B3","F1F1AB","EDEDA2","EAEA9A","E7E792","E4E48A","E0E081","DDDD79","DADA71","D7D769","D3D360","D0D058","CDCD50","CACA48","C6C63F","C3C337","C0C02F","BDBD27","B9B91E","B6B616","B3B30E","B0B006","609C60","5C985C","589558","549254","508E50","4C8B4C","488848","448544","408140","3C7E3C","387B38","347834","317431","2D712D","296E29","256B25","216721","1D641D","196119","155E15","115A11","0D570D","095409","065106","643700","643a00","643d00","644000","644300","644600","644900","654c00","654f00","655200","655500","655800","655a00","655d00","656000","656300","666600","666900","666c00","666f00","667200","667500","667800","667b00","ff99ff","FC92FC","F98BF9","F685F6","F37EF3","F077F0","ED71ED","EA6AEA","E763E7","E45DE4","E156E1","DE4FDE","DB49DB","D842D8","D53BD5","D235D2","CF2ECF","CC27CC","C921C9","C61AC6","C313C3","C00DC0","BD06BD","bb00bb","000003","000004","000005","BFC0C0","B7BDC2","AFBBC4","A8B8C6","A0B6C9","99B3CB","91B1CD","89AFD0","82ACD2","7AAAD4","73A7D6","6BA5D9","64A3DB","5CA0DD","549EE0","4D9BE2","4599E4","3E96E6","3694E9","2E92EB","278FED","1F8DF0","188AF2","1088F4","0986F7","55A5A5","53A1A2","519E9F","4F9B9C","4D989A","4B9597","499294","478F91","458B8F","43888C","418589","3F8286","3D7F84","3B7C81","39797E","37767B","357279","336F76","316C73","2F6970","2D666E","2B636B","296068","285D66","bb93b0","B78FAC","B48CA9","B189A6","AE85A2","AA829F","A77F9C","A47B99","A17895","9E7592","9A718F","976E8C","946B88","916885","8D6482","8A617F","875E7B","845A78","815775","7D5472","7A506E","774D6B","744A68","714765","de7cbb","DA77B7","D772B3","D46EAF","D169AB","CE64A8","CB60A4","C85BA0","C4579C","C15298","BE4D95","BB4991","B8448D","B54089","B23B86","AF3682","AB327E","A82D7A","A52976","A22473","9F1F6F","9C1B6B","991667","961264","000000","000000","000000","1964EB","1555E4","1147DD","0E39D6","0A2ACF","071CC8","030EC1","0000BA","0000BA","040464","0000FF","3051cf","000000","000000","000000","000000","000000","000000","000000","000000","000000","000000","000000","000000","000000","000000","000000","000000","000000","000000","000000","000000","547FC4","4D77BA","466FB1","4067A7","395F9E","335895","335896","335897","ff2828","ffffff","d0ffff","ffe0d0","ff7d00","fac800","c86400","fff000","afcd96","afcd96","64dcdc","00ffff","00ffff","00ffff","111133","000000"]};Map.addLayer(m00,visParamMap,'2000 land cover and land use')Map.addLayer(m05,visParamMap,'2005 land cover and land use')Map.addLayer(m10,visParamMap,'2010 land cover and land use')Map.addLayer(m15,visParamMap,'2015 land cover and land use')Map.addLayer(m20,visParamMap,'2020 land cover and land use')Map.addLayer(change,visParamMap,'2000-2020 land cover and land use change')
Enter license information
Creative Commons Attribution 4.0 International License
Keywords
Land Cover, Wetland, Forest
Code of Conduct
I agree to follow this project's Code of Conduct
The text was updated successfully, but these errors were encountered:
@samapriya
Data Download Link: Yes - It is not available for local download but is uploaded to GEE and is working as of 8/12/2024
Citation: Yes - reference DOI.
License for Use: Yes - data is available under CC BY 4.0.
Contact Details
pinkychow1010@gmail.com
Dataset description
The GLAD Global Land Cover and Land Use Change dataset quantifies changes in forest extent and height, cropland, built-up lands, surface water, and perennial snow and ice extent from the year 2000 to 2020 at 30-m spatial resolution. The global dataset derived from the GLAD Landsat Analysis Ready Data. Each thematic product was independently derived using state-of-the-art, locally and regionally calibrated machine learning tools. Each thematic layer was validated independently using a statistical sampling.
Data Download
Dataset already hosted as GEE asset, but with each epoch separated. The time series can be combined into a single image collection as follow:
The change between 2000 and 2020 can be assessed here:
var change = ee.Image('projects/glad/GLCLU2020/v2/LCLUC').updateMask(landmask);
Dataset Reference
Potapov P., Hansen M.C., Pickens A., Hernandez-Serna A., Tyukavina A., Turubanova S., Zalles V., Li X., Khan A., Stolle F., Harris N., Song X.-P., Baggett A., Kommareddy I., Kommareddy A. (2022) The global 2000-2020 land cover and land use change dataset derived from the Landsat archive: first results. Frontiers in Remote Sensing [https://doi.org/10.3389/frsen.2022.856903] [Open PDF]
Earth Engine Snippet if dataset already in GEE
Enter license information
Creative Commons Attribution 4.0 International License
Keywords
Land Cover, Wetland, Forest
Code of Conduct
The text was updated successfully, but these errors were encountered: