In this video we will show you how to download the newly released Global Landcover data by ESRI in collaboration with Impact Observatory. This dataset has been developed using the Sentinel-2 images of the year 2020. Around 400,000 Earth Observations has been used for generating the Global Land cover data. The satellite images is classified in 10 different classes.
Also, In the later part of the video it is shown, how to use the landcover data in google earth engine and how to export the data for your region of interest.
Credits (Attribution)
This dataset used in the video was produced by Impact Observatory for Esri. © 2021 Esri. This dataset is available under a Creative Commons BY-4.0 license and any copy of or work based on this dataset requires the following attribution: This dataset is based on the dataset produced for the Dynamic World Project by National Geographic Society in partnership with Google and the World Resources Institute.
Timeline of the video:
00:00 - Introduction
00:45 - Browse & Download ESRI 2020 Landcover data in GeoTiff format
09:25 - Access and Download ESRI 2020 Landcover data in Google Earth Engine
Link of the Website:
[ Ссылка ]
[ Ссылка ]
[ Ссылка ]
Google Earth Engine Code:
var esri_lulc2020= ee.ImageCollection("projects/sat-io/open-datasets/landcover/ESRI_Global-LULC_10m")
// Define a dictionary which will be used to make legend and visualize image on map
var dict = {
"names": [
"Water",
"Trees",
"Grass",
"Flooded Vegetation",
"Crops",
"Scrub/Shrub",
"Built Area",
"Bare Ground",
"Snow/Ice",
"Clouds"
],
"colors": [
"#1A5BAB",
"#358221",
"#A7D282",
"#87D19E",
"#FFDB5C",
"#EECFA8",
"#ED022A",
"#EDE9E4",
"#F2FAFF",
"#C8C8C8"
]};
Map.addLayer(esri_lulc2020.mosaic(), {min:1, max:10, palette:dict['colors']}, 'ESRI LULC 10m')
var clip = esri_lulc2020.mosaic().clip(table);
Map.addLayer(clip, {min:1, max:10, palette:dict['colors']}, 'ESRI LULC 10m');
Export.image.toDrive({
image: clip,
description: 'LULC',
scale: 10,
maxPixels: 1e13,
region: table
});
