Google Earth Engine Tutorial: Download ESRI Land Cover Data 10m

Google Earth Engine Tutorial: Download ESRI Land Cover Data 10m Using Google Earth Engine

Google Earth Engine (GEE) is a powerful platform for planetary-scale geospatial analysis. One of its key features is access to high-resolution datasets, such as the ESRI Land Cover 10m data. This tutorial guides you through the process of downloading this dataset using GEE’s JavaScript API and Python integration.

Step-by-Step Guide

1. Access Google Earth Engine: Open the GEE Code Editor at https://code.earthengine.google.com. Sign in with your Google account.

2. Import the Dataset: Use the following code snippet to load the ESRI Land Cover 10m dataset:

var landCover = ee.Image('ESRI/GlobalLandCover/10m');

3. Filter the Image Collection: If you’re working with a specific time range, filter the collection:

var filtered = landCover.filterDate('2020-01-01', '2020-12-31');

4. Export the Data: Define the export parameters and trigger the export:

Export.image.toDrive({
  image: filtered,
  description: 'ESRI_Land_Cover_10m',
  folder: 'GEE_Exports',
  fileNamePrefix: 'landcover',
  region: geometry,
  scale: 10,
  maxPixels: 1e10
});

5. Monitor the Export: Check the “Tasks” panel in the Code Editor for progress and download the file once completed.

Best Practices

Use Correct Geometry: Define a specific region (e.g., a polygon) to avoid exporting unnecessary areas.

Choose Appropriate Scales: The 10m resolution is ideal for detailed land cover analysis, but ensure your computational resources can handle large datasets.

Visualize Before Exporting: Use the Map.addLayer() function to visualize the data and confirm accuracy before exporting.

FAQ

What is the ESRI Land Cover 10m dataset?

The ESRI Land Cover 10m dataset provides global land cover classification at a 10-meter resolution, categorized into classes like forest, urban, water, and agricultural land.

How to access this dataset in GEE?

The dataset is available through the ESRI/GlobalLandCover/10m identifier. Load it using ee.Image() in the Code Editor.

Can I download this data in different formats?

Yes, GEE allows exporting to GeoTIFF, CSV, or other supported formats. Adjust the format parameter in the export function.

Why does my export fail with a ‘maxPixels’ error?

The error occurs due to data size limits. Increase the maxPixels parameter or reduce the area of interest to comply with GEE’s constraints.

How to handle multiple years of data?

Use filterDate() to select specific years. For yearly downloads, repeat the export process for each time period.

Is the dataset available in the Python API?

Yes, the dataset can be accessed via the Earth Engine Python API using ee.Image('ESRI/GlobalLandCover/10m').

What are the key land cover classes included?

The dataset includes classes such as ‘Trees’, ‘Grassland’, ‘Urban’, ‘Water’, ‘Barren’, and ‘Cropland’, based on the ESRI classification system.