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[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2023-10-06 UTC."],[[["\u003cp\u003e\u003ccode\u003equalityMosaic()\u003c/code\u003e composites images in a collection based on a specified quality band, selecting the highest quality pixel for each location in the output mosaic.\u003c/p\u003e\n"],["\u003cp\u003eThe 'quality band' is a band within the image collection that represents the desired quality metric (e.g., cloud probability, NDVI).\u003c/p\u003e\n"],["\u003cp\u003eThe function returns a single image where each pixel is chosen from the input image with the highest value in the quality band at that location.\u003c/p\u003e\n"],["\u003cp\u003eYou can manipulate the quality band (e.g., inverting cloud probability) to prioritize different pixel selection criteria.\u003c/p\u003e\n"]]],[],null,["# ee.ImageCollection.qualityMosaic\n\nComposites all the images in a collection, using a quality band as a per-pixel ordering function.\n\n\u003cbr /\u003e\n\n| Usage | Returns |\n|----------------------------------------------|---------|\n| ImageCollection.qualityMosaic`(qualityBand)` | Image |\n\n| Argument | Type | Details |\n|--------------------|-----------------|-------------------------------------------------|\n| this: `collection` | ImageCollection | The collection to mosaic. |\n| `qualityBand` | String | The name of the quality band in the collection. |\n\nExamples\n--------\n\n### Code Editor (JavaScript)\n\n```javascript\n// The goal is to generate a best-pixel mosaic from a collection of\n// Sentinel-2 images where pixel quality is based on a cloud probability score.\n// The qualityMosaic() function selects the image (per-pixel) with the HIGHEST\n// quality-band-score to contribute to the resulting mosaic. All bands from the\n// selected image (per-pixel) associated with the HIGHEST quality-band-score\n// are included in the output.\n\n// A Sentinel-2 SR image collection (2 months of images at a specific point).\nvar col = ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')\n .filterBounds(ee.Geometry.Point(-103.19, 40.14))\n .filterDate('2020-07-01', '2020-09-01');\n\n// Because cloud probability ranges from 0 to 100 percent (low to high), we need\n// to invert the MSK_CLDPRB band values so that low cloud probability pixels\n// indicate high quality. Here, an inverting function is mapped over the\n// image collection, the inverted MSK_CLDPRB band is added as a \"quality\" band.\ncol = col.map(function(img) {\n var cldProb = img.select('MSK_CLDPRB');\n var cldProbInv = cldProb.multiply(-1).rename('quality');\n return img.addBands(cldProbInv);\n});\n\n// Image visualization settings.\nvar visParams = {\n bands: ['B4', 'B3', 'B2'],\n min: 0,\n max: 4500\n};\nMap.setCenter(-103.19, 40.14, 9);\nMap.addLayer(col, visParams, 'Collection (for series inspection)', false);\n\n// Generate a best-pixel mosaic from the image collection.\nvar img = col.qualityMosaic('quality');\nMap.addLayer(img, visParams, 'Best-pixel mosaic (by cloud score)');\n\n// To build the worst-pixel mosaic, according to cloud probability, use the\n// MSK_CLDPRB band as the quality band (the worst pixels have HIGHEST cloud\n// probability score).\nvar img = col.qualityMosaic('MSK_CLDPRB');\nMap.addLayer(img, visParams, 'Worst-pixel mosaic (by cloud score)', false);\n```\nPython setup\n\nSee the [Python Environment](/earth-engine/guides/python_install) page for information on the Python API and using\n`geemap` for interactive development. \n\n```python\nimport ee\nimport geemap.core as geemap\n```\n\n### Colab (Python)\n\n```python\n# The goal is to generate a best-pixel mosaic from a collection of\n# Sentinel-2 images where pixel quality is based on a cloud probability score.\n# The qualityMosaic() function selects the image (per-pixel) with the HIGHEST\n# quality-band-score to contribute to the resulting mosaic. All bands from the\n# selected image (per-pixel) associated with the HIGHEST quality-band-score\n# are included in the output.\n\n# A Sentinel-2 SR image collection (2 months of images at a specific point).\ncol = (\n ee.ImageCollection('COPERNICUS/S2_SR_HARMONIZED')\n .filterBounds(ee.Geometry.Point(-103.19, 40.14))\n .filterDate('2020-07-01', '2020-09-01')\n)\n\n# Because cloud probability ranges from 0 to 100 percent (low to high), we need\n# to invert the MSK_CLDPRB band values so that low cloud probability pixels\n# indicate high quality. Here, an inverting function is mapped over the\n# image collection, the inverted MSK_CLDPRB band is added as a \"quality\" band.\ndef invertCloudProbabilityBand(img):\n cldProb = img.select('MSK_CLDPRB')\n cldProbInv = cldProb.multiply(-1).rename('quality')\n return img.addBands(cldProbInv)\n\ncol = col.map(invertCloudProbabilityBand)\n\n# Image visualization settings.\nvis_params = {'bands': ['B4', 'B3', 'B2'], 'min': 0, 'max': 4500}\nm = geemap.Map()\nm.set_center(-103.19, 40.14, 9)\nm.add_layer(col, vis_params, 'Collection (for series inspection)', False)\n\n# Generate a best-pixel mosaic from the image collection.\nimg = col.qualityMosaic('quality')\nm.add_layer(img, vis_params, 'Best-pixel mosaic (by cloud score)')\n\n# To build the worst-pixel mosaic, according to cloud probability, use the\n# MSK_CLDPRB band as the quality band (the worst pixels have HIGHEST cloud\n# probability score).\nimg = col.qualityMosaic('MSK_CLDPRB')\nm.add_layer(img, vis_params, 'Worst-pixel mosaic (by cloud score)', False)\nm\n```"]]