notebooks/imagecollection/mosaicSameDay.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mosaic Same Day\n",
    "Images inside an ImageCollection that where taken in the same day are fusioned into one image using a reducer (default: mean). The resulting images will have 2 properties only:\n",
    "\n",
    "- system:time_start\n",
    "- system:footprint (this will contain the fusioned geometries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ee\n",
    "ee.Initialize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from geetools import tools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geedatasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ipygee as ui"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map = ui.Map()\n",
    "Map.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sat = geedatasets.sentinel.Sentinel2SR()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "vis = sat.visualization('NSR')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "p = ee.Geometry.Point([-72, -42])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "col = sat.collection().filterBounds(p).filterDate('2019-01-01', '2019-05-01')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ui.eprint(col.size())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get dates\n",
    "def get_dates(col):\n",
    "    dates = ee.List(col.toList(col.size()).map(lambda img: ee.Image(img).date().format()))\n",
    "    return dates\n",
    "\n",
    "ui.eprint(get_dates(col))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "mosaics = tools.imagecollection.mosaicSameDay(col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ui.eprint(mosaics.size())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ui.eprint(get_dates(mosaics))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map.addImageCollection(col.limit(2), vis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map.addLayer(mosaics.first(), sat.visualization('NSR'), 'Day 1 mosaicked')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Map.addLayer(mosaics.first().geometry(), name='Footprint day 1 mosaicked')"
   ]
  }
 ],
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