Raster math between image collection and image in GEE - use .map function?

Question

I am currently working with a raster file which shows peatlands in the Congo Basin and the ESA/CCI/FireCCI/5_1 image collection (images for each month between 2001-2019). My end goal is to create visual thumbnails of seasonal (blocks of 3 months) burn area over the peatlands and charts, as well as derive inter-annual trends between the same three months across all years.

Current challenge: I have tried to use the multiply operator between the fire image collection and the peatlands image and it doesn't work between an image and an image collection. I am trying to create a new fire image collection over the peatlands only.

A pixel value of 1 indicates peat in the peatlands image and I have reclassified the fire image collection so that 1 indicates land cover that has been burnt.

Annotated code developed so far below:

//Add layers
 
GretaMap_extent = ee.FeatureCollection("users/n/Vector_peats");//vector of extent of peatland map
PeatlandMap_Greta = ee.Image("users/n/peat_nopeat"); //peatland map

// Visualize FireCCI51 from 2001-2019
var dataset = ee.ImageCollection('ESA/CCI/FireCCI/5_1')
                  .filterDate('2001-01-01', '2019-12-31')
                  .filterBounds(GretaMap_extent)
                  .map(function(image){return image.clip(GretaMap_extent)}) ;  
                  
print(dataset);
var burnedArea = dataset.select('LandCover');//all burned pixels are classified according to LandCover

//Palette for Burn Area
var baVis = {
  min: 0,
  max: 180,
  palette: [
    'ffff64', 'aaf0f0', 'dcf064', 'c8c864', '006400', '00a000', '003c00', '285000', '788200',
    '8ca000', 'be9600', '966400', 'ffb432', 'ffdcd2', 'ffebaf', '009678', '00dc82'
  ]
};

//Palette for peatland map
var peatlandsvis = {
  min: 0,
  max: 1,
  palette: ['white', 'fuchsia']
};
//only keep pixels with a value of 1 (peat)
var onlyPeat = PeatlandMap_Greta.updateMask(
  PeatlandMap_Greta.neq(0) // Only keep pixels where values don't equal zero
);

//visualize peat and burn pixels together
Map.setCenter(30, 0, 6.1);
Map.addLayer(burnedArea, baVis, 'Burned Area');
Map.addLayer(onlyPeat, peatlandsvis, 'Peatlands Map');

//Reclassify the LandCover because I'm only interested in the burn pixels, not their land cover
var reclassify = function(image) {
  return image.remap(
    [0, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 170, 180],//land cover values
    [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],//recode all to 1
    null,//mask out all other values, which shouldn't exist anyways 
    'LandCover');//band name
};
var new_ds = burnedArea.map(reclassify);// new variable which applies reclassification to burnedArea
print(new_ds);
Map.addLayer(new_ds);//I think this worked. Not sure? 

//Now: how to only show fire on peatlands?

Answer 1

Replace "multiply an image collection by an image" with "multiply each image in the image collection by an image" and you already have the tool you need: .map().

var burnedPeat = burnedArea.map(function (burnImage) {
  return burnImage.multiply(onlyPeat);
});

Answer 2

This is the additional code I added to my original code posted above

// projection of final raster: 250m is the resolution of the fire data
var reproj_params = {crs:'EPSG:4326',scale:250}; 
//map the reprojected new_ds fire image collection over the peatlands to see peatland fires only
var burntPeat = new_ds.map(function(image) {
  return image.multiply(onlyPeat.reproject(reproj_params));
});
Map.addLayer(burntPeat, {palette:'red'}, 'BurntPeat');
print(burntPeat);