- Dataset Availability
- 2019-01-01T00:00:00Z–2019-12-31T00:00:00
- Dataset Provider
- Biopama programme
- Earth Engine Snippet
-
ee.ImageCollection("BIOPAMA/GlobalOilPalm/v1")Sign up for Earth Engine
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- Tags
Description
The dataset is a 10m global industrial and smallholder oil palm map for 2019. It covers areas where oil palm plantations were detected. The classified images are the output of a convolutional neural network based on Sentinel-1 and Sentinel-2 half-year composites.
See article for additional information.
Bands
Bands
| Name | Pixel Size | Description |
|---|---|---|
classification |
10 meters | Oil Palm class description |
classification Class Table
| Value | Color | Description |
|---|---|---|
| 1 | #ff0000 | Industrial closed-canopy oil palm plantations |
| 2 | #ef00ff | Smallholder closed-canopy oil palm plantations |
| 3 | #696969 | Other land covers and/or uses that are not closed-canopy oil palm. |
Terms of Use
Terms of Use
Citations
Adrià, Descals, Serge, Wich, Erik, Meijaard, David, Gaveau, Stephen, Peedell, & Zoltan, Szantoi. (2021, January 27). High resolution global industrial and smallholder oil palm map for 2019 (Version v1). Zenodo. doi:10.5281/zenodo.4473715
DOIs
Explore in Earth Engine
// Import the dataset; a collection of composite granules from 2019.
var dataset = ee.ImageCollection('BIOPAMA/GlobalOilPalm/v1');
// Select the classification band.
var opClass = dataset.select('classification');
// Mosaic all of the granules into a single image.
var mosaic = opClass.mosaic();
// Define visualization parameters.
var classificationVis = {
min: 1,
max: 3,
palette: ['ff0000','ef00ff', '696969']
};
// Create a mask to add transparency to non-oil palm plantation class pixels.
var mask = mosaic.neq(3);
mask = mask.where(mask.eq(0), 0.6);
// Display the data on the map.
Map.addLayer(mosaic.updateMask(mask),
classificationVis, 'Oil palm plantation type', true);
Map.setCenter(-3.0175, 5.2745,12);