非洲2019年数字地球耕地范围地图

var filtered = ee.ImageCollection("projects/sat-io/open-datasets/DEAF/CROPLAND-EXTENT/filtered")
var mask = ee.ImageCollection("projects/sat-io/open-datasets/DEAF/CROPLAND-EXTENT/mask");
var prob = ee.ImageCollection("projects/sat-io/open-datasets/DEAF/CROPLAND-EXTENT/prob");
var validation = ee.FeatureCollection("projects/sat-io/open-datasets/DEAF/CROPLAND-EXTENT/validation");

/*
|Band ID |Description               |Value range|Data type|NoData/Fill value|
|--------|--------------------------|-----------|---------|-----------------|
|mask    |crop extent (pixel)       |0 - 1      |uint8    |0                |
|prob    |crop probability (pixel)  |0 - 100    |uint8    |0                |
|filtered|crop extent (object-based)|0 - 1      |uint8    |0                |

Notes Probability
prob: This band displays the prediction probabilities for the 'crop' class. 
As this service uses a random forest classifier, the prediction probabilities refer to
the percentage of trees that voted for the random forest classification.
For example, if the model had 200 decision trees in the random forest, 
and 150 of the trees voted ‘crop’, the prediction probability is 150 / 200 x 100 = 75 %.
Thresholding this band at > 50 % will produce a map identical to mask.
*/
Map.setCenter(25.35, 4.19,4)

//Convert to single images
var mask = mask.mosaic()
var filtered = filtered.mosaic()
var prob = prob.mosaic()

Map.addLayer(mask.updateMask(mask.gt(0)),{min:0,max:1,palette:['70a54c']},'Crop extent mask')
Map.addLayer(filtered.updateMask(filtered.gt(0)),{min:0,max:1,palette:['70a54c']},'Crop extent mask- Filtered',false)
Map.addLayer(prob,{min:0,max:100},'Crop extent mask Prediction Prob',false)
Map.addLayer(validation,{},'Crop extent mask Validation points',false)