Harmonize TOA

Merging Landsat and sentinel-2 can be troublesome because of different sensor characteristics. This paper did a crosswalk between the different sensor and provides some numbers to harmonize the two.

Use the code below and find an example here


var bandNamesOut = ['blue','green','red','nir','swir1','swir2'];
var bandNamesl8 = ['B2','B3','B4','B5','B6','B7'];
var bandNamesS2 = ['B2','B3','B4','B8','B11','B12']

// data from table 4: Empirical cross sensor comparison of Sentinel-2A and 2B MSI, Landsat-8 OLI, and Landsat-7 ETM+
//top of atmosphere spectral characteristics over the conterminous United States
var slopes = [1.0946,1.0043,1.0524,0.8954,1.0049,1.0002];
var intercepts = [-0.0107,0.0026,-0.0015,0.0033,0.0065,0.0046];

s2 = s2.filterBounds(geometry).filterDate("2018-12-01","2018-12-21").sort("CLOUDY_PIXEL_PERCENTAGE")
var imgs2 = ee.Image(s2.first()).select(bandNamesS2,bandNamesOut).divide(10000).float()
print(imgs2)
Map.addLayer(imgs2,{min:0,max:0.3000,bands:"red,green,blue"},"sentinel 2")

l8 = l8.filterBounds(geometry).filterDate("2018-12-01","2018-12-21").sort("CLOUD_COVER")
var imgl8 = ee.Image(l8.first()).select(bandNamesl8,bandNamesOut)
Map.addLayer(imgl8,{min:0,max:0.3000,bands:"red,green,blue"},"landsat 8 original")

var imgl8 = ee.Image(l8.first()).select(bandNamesl8,bandNamesOut).multiply(slopes).add(intercepts).float();
Map.addLayer(imgl8,{min:0,max:0.3000,bands:"red,green,blue"},"landsat 8 image")
print(imgl8)

var merged = ee.ImageCollection([imgs2,imgl8]).mean()
Map.addLayer(merged ,{min:0,max:0.3000,bands:"red,green,blue"},"merged image")
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