split map with 'custom' image collection?

[rodrigo-j-goncalves]

I'm trying to show a split map using this tutorial but I want to use ESRI_Global-LULC_10m_TS in both half-maps (i.e. different periods). When I try to do that, I get the error that the maps shown can only be one of the following set (see below).
Is it possible to add this image collection to the 'allowed maps'?

ValueError: left_layer must be one of the following: OpenStreetMap, Esri.WorldStreetMap, Esri.WorldImagery, Esri.WorldTopoMap, FWS NWI Wetlands, FWS NWI Wetlands Raster, NLCD 2021 CONUS Land Cover, NLCD 2019 CONUS Land Cover, NLCD 2016 CONUS Land Cover, NLCD 2013 CONUS Land Cover, NLCD 2011 CONUS Land Cover, NLCD 2008 CONUS Land Cover, NLCD 2006 CONUS Land Cover, NLCD 2004 CONUS Land Cover, NLCD 2001 CONUS Land Cover, USGS NAIP Imagery, USGS NAIP Imagery False Color, USGS NAIP Imagery NDVI, USGS Hydrography, USGS 3DEP Elevation, ESA Worldcover 2020, ESA Worldcover 2020 S2 FCC, ESA Worldcover 2020 S2 TCC, ESA Worldcover 2021, ESA Worldcover 2021 S2 FCC, ESA Worldcover 2021 S2 TCC, BasemapAT.basemap, BasemapAT.grau, BasemapAT.highdpi, BasemapAT.orthofoto, BasemapAT.overlay, BasemapAT.surface, BasemapAT.terrain, CartoDB.DarkMatter, CartoDB.DarkMatterNoLabels, CartoDB.DarkMatterOnlyLabels, CartoDB.Positron, CartoDB.PositronNoLabels, CartoDB.PositronOnlyLabels, CartoDB.Voyager, CartoDB.VoyagerLabelsUnder, CartoDB.VoyagerNoLabels, CartoDB.VoyagerOnlyLabels, CyclOSM, Esri.AntarcticBasemap, Esri.AntarcticImagery, Esri.ArcticImagery, Esri.ArcticOceanBase, Esri.ArcticOceanReference, Esri.DeLorme, Esri.NatGeoWorldMap, Esri.OceanBasemap, Esri.WorldGrayCanvas, Esri.WorldPhysical, Esri.WorldShadedRelief, Esri.WorldTerrain, FreeMapSK, Gaode.Normal, Gaode.Satellite, HikeBike.HikeBike, HikeBike.HillShading, JusticeMap.americanIndian, JusticeMap.asian, JusticeMap.black, JusticeMap.hispanic, JusticeMap.income, JusticeMap.multi, JusticeMap.nonWhite, JusticeMap.plurality, JusticeMap.white, MtbMap, NASAGIBS.ASTER_GDEM_Greyscale_Shaded_Relief, NASAGIBS.BlueMarble, NASAGIBS.BlueMarble3031, NASAGIBS.BlueMarble3413, NASAGIBS.ModisAquaBands721CR, NASAGIBS.ModisAquaTrueColorCR, NASAGIBS.ModisTerraAOD, NASAGIBS.ModisTerraBands367CR, NASAGIBS.ModisTerraBands721CR, NASAGIBS.ModisTerraChlorophyll, NASAGIBS.ModisTerraLSTDay, NASAGIBS.ModisTerraSnowCover, NASAGIBS.ModisTerraTrueColorCR, NASAGIBS.ViirsEarthAtNight2012, NASAGIBS.ViirsTrueColorCR, NLS, OPNVKarte, OneMapSG.Default, OneMapSG.Grey, OneMapSG.LandLot, OneMapSG.Night, OneMapSG.Original, OpenAIP, OpenFireMap, OpenRailwayMap, OpenSeaMap, OpenSnowMap.pistes, OpenStreetMap.BZH, OpenStreetMap.BlackAndWhite, OpenStreetMap.CH, OpenStreetMap.DE, OpenStreetMap.HOT, OpenStreetMap.Mapnik, OpenTopoMap, SafeCast, Stadia.AlidadeSmooth, Stadia.AlidadeSmoothDark, Stadia.OSMBright, Stadia.Outdoors, Stadia.StamenTerrain, Stadia.StamenTerrainBackground, Stadia.StamenTerrainLabels, Stadia.StamenTerrainLines, Stadia.StamenToner, Stadia.StamenTonerBackground, Stadia.StamenTonerLabels, Stadia.StamenTonerLines, Stadia.StamenTonerLite, Stadia.StamenWatercolor, Stamen.Terrain, Stamen.TerrainBackground, Stamen.TerrainLabels, Stamen.Toner, Stamen.TonerBackground, Stamen.TonerHybrid, Stamen.TonerLabels, Stamen.TonerLines, Stamen.TonerLite, Stamen.TopOSMFeatures, Stamen.TopOSMRelief, Stamen.Watercolor, Strava.All, Strava.Ride, Strava.Run, Strava.Water, Strava.Winter, SwissFederalGeoportal.JourneyThroughTime, SwissFederalGeoportal.NationalMapColor, SwissFederalGeoportal.NationalMapGrey, SwissFederalGeoportal.SWISSIMAGE, USGS.USImagery, USGS.USImageryTopo, USGS.USTopo, WaymarkedTrails.cycling, WaymarkedTrails.hiking, WaymarkedTrails.mtb, WaymarkedTrails.riding, WaymarkedTrails.skating, WaymarkedTrails.slopes, nlmaps.grijs, nlmaps.luchtfoto, nlmaps.pastel, nlmaps.standaard, nlmaps.water or a string url to a tif file.

[giswqs]

The collection has over 5000 elements. You need to do some pre-processing before you can use split map.

import ee
import geemap
m = geemap.Map()
esri_lulc_ts= ee.ImageCollection("projects/sat-io/open-datasets/landcover/ESRI_Global-LULC_10m_TS")
year_2017 = esri_lulc_ts.filterDate('2017-01-01','2017-12-31').mosaic().remap([1,2,4,5,7,8,9,10,11],[1,2,3,4,5,6,7,8,9])
year_2023 = esri_lulc_ts.filterDate('2023-01-01','2023-12-31').mosaic().remap([1,2,4,5,7,8,9,10,11],[1,2,3,4,5,6,7,8,9])
lengend_dict = geemap.builtin_legends['ESRI_LandCover_TS']
vis_params = {"min": 1, "max": 9, "palette": list(lengend_dict.values())}
layer_2017 = geemap.ee_tile_layer(year_2017, vis_params, '2017')
layer_2023 = geemap.ee_tile_layer(year_2023, vis_params, '2023')
m.split_map(layer_2017, layer_2023)
m

[rodrigo-j-goncalves]

It works great, thank you!!!