docs/ImageCollection/image_collection_overview.ipynb

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    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://githubtocolab.com/giswqs/gee-tutorials/blob/master/ImageCollection/image_collection_overview.ipynb)"
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    "**Getting Started with Earth Engine ImageCollection**\n",
    "\n",
    "As illustrated in the [Get Started section](https://developers.google.com/earth-engine/guides/getstarted) and the [ImageCollection Information section](https://developers.google.com/earth-engine/guides/ic_info), Earth Engine provides a variety of convenience methods for filtering image collections. Specifically, many common use cases are handled by `imageCollection.filterDate()`, and `imageCollection.filterBounds()`. For general purpose filtering, use `imageCollection.filter()` with an ee.Filter as an argument. The following example demonstrates both convenience methods and `filter()` to identify and remove images with bad registration from an `ImageCollection`:"
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ee\n",
    "import geemap"
   ]
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  {
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   "source": [
    "Map = geemap.Map()\n",
    "Map"
   ]
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   "source": [
    "## Get collection size"
   ]
  },
  {
   "cell_type": "code",
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   "outputs": [],
   "source": [
    "collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR')"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "print(collection.size().getInfo())"
   ]
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   "source": [
    "## Get the first image"
   ]
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   "outputs": [],
   "source": [
    "image = collection.first()\n",
    "geemap.image_props(image).getInfo()"
   ]
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    "Map.addLayer(image, {}, \"First image\")\n",
    "Map.centerObject(image, 6)\n",
    "Map"
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   "source": [
    "## Filter by dates\n",
    "\n",
    "https://developers.google.com/earth-engine/apidocs/ee-imagecollection-filterdate"
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   "source": [
    "collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR') \\\n",
    "    .filterDate('2020-01-01', '2020-12-31')"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(collection.size().getInfo())"
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   "cell_type": "code",
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   "outputs": [],
   "source": [
    "image2 = collection.first()\n",
    "Map.addLayer(image2, {}, \"Another image\")\n",
    "Map.centerObject(image2, 6)\n",
    "Map"
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter by location\n",
    "\n",
    "https://developers.google.com/earth-engine/apidocs/ee-imagecollection-filterbounds"
   ]
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  {
   "cell_type": "code",
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   "source": [
    "roi = ee.Geometry.Point(-122.4488, 37.7589)"
   ]
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   "cell_type": "code",
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   "source": [
    "collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR') \\\n",
    "    .filterDate('2020-01-01', '2020-12-31') \\\n",
    "    .filterBounds(roi)"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(collection.size().getInfo())"
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   "cell_type": "code",
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   "outputs": [],
   "source": [
    "Map = geemap.Map()\n",
    "image = collection.first()\n",
    "\n",
    "vis_param = {'min': 0, \n",
    "             'max': 2000, \n",
    "             'bands': ['B5', 'B4', 'B3'], \n",
    "             'gamma': 1.5}\n",
    "\n",
    "Map.addLayer(image, vis_param, \"First mage\")\n",
    "Map.centerObject(image, 8)\n",
    "\n",
    "Map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter by metadata\n",
    "\n",
    "https://developers.google.com/earth-engine/apidocs/ee-imagecollection-filtermetadata"
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   "cell_type": "code",
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   "source": [
    "collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR') \\\n",
    "    .filterDate('2020-01-01', '2020-12-31') \\\n",
    "    .filterBounds(ee.Geometry.Point(-122.4488, 37.7589)) \\\n",
    "    .filterMetadata('CLOUD_COVER', 'less_than', 10) \\\n",
    "    .sort(\"CLOUD_COVER\")"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map = geemap.Map()\n",
    "image = collection.first()\n",
    "\n",
    "vis_param = {'min': 0, \n",
    "             'max': 2000, \n",
    "             'bands': ['B5', 'B4', 'B3'], \n",
    "             'gamma': 1.5}\n",
    "\n",
    "Map.addLayer(image, vis_param, \"First mage\")\n",
    "Map.centerObject(image, 8)\n",
    "\n",
    "Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "geemap.image_props(image).getInfo()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get image collection properties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_SR') \\\n",
    "    .filterDate('2020-01-01', '2020-12-31') \\\n",
    "    .filterBounds(ee.Geometry.Point(-122.4488, 37.7589)) \\\n",
    "    .filterMetadata('CLOUD_COVER', 'less_than', 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "collection.aggregate_array('CLOUD_COVER').getInfo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "collection.aggregate_array('system:id').getInfo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "collection.aggregate_mean('CLOUD_COVER').getInfo()"
   ]
  }
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