{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "<table class=\"ee-notebook-buttons\" align=\"left\">\n", " <td><a target=\"_blank\" href=\"https://github.com/giswqs/earthengine-py-notebooks/tree/master/Image/set_image_properties.ipynb\"><img width=32px src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /> View source on GitHub</a></td>\n", " <td><a target=\"_blank\" href=\"https://nbviewer.jupyter.org/github/giswqs/earthengine-py-notebooks/blob/master/Image/set_image_properties.ipynb\"><img width=26px src=\"https://upload.wikimedia.org/wikipedia/commons/thumb/3/38/Jupyter_logo.svg/883px-Jupyter_logo.svg.png\" />Notebook Viewer</a></td>\n", " <td><a target=\"_blank\" href=\"https://colab.research.google.com/github/giswqs/earthengine-py-notebooks/blob/master/Image/set_image_properties.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /> Run in Google Colab</a></td>\n", "</table>" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Install Earth Engine API and geemap\n", "Install the [Earth Engine Python API](https://developers.google.com/earth-engine/python_install) and [geemap](https://geemap.org). The **geemap** Python package is built upon the [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet) and [folium](https://github.com/python-visualization/folium) packages and implements several methods for interacting with Earth Engine data layers, such as `Map.addLayer()`, `Map.setCenter()`, and `Map.centerObject()`.\n", "The following script checks if the geemap package has been installed. If not, it will install geemap, which automatically installs its [dependencies](https://github.com/giswqs/geemap#dependencies), including earthengine-api, folium, and ipyleaflet." ] }, { "cell_type": "code", "metadata": {}, "source": [ "# Installs geemap package\n", "import subprocess\n", "\n", "try:\n", " import geemap\n", "except ImportError:\n", " print('Installing geemap ...')\n", " subprocess.check_call([\"python\", '-m', 'pip', 'install', 'geemap'])" ], "outputs": [], "execution_count": null }, { "cell_type": "code", "metadata": {}, "source": [ "import ee\n", "import geemap" ], "outputs": [], "execution_count": null }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Create an interactive map \n", "The default basemap is `Google Maps`. [Additional basemaps](https://github.com/giswqs/geemap/blob/master/geemap/basemaps.py) can be added using the `Map.add_basemap()` function. " ] }, { "cell_type": "code", "metadata": {}, "source": [ "Map = geemap.Map(center=[40,-100], zoom=4)\n", "Map" ], "outputs": [], "execution_count": null }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Add Earth Engine Python script " ] }, { "cell_type": "code", "metadata": {}, "source": [ "# Add Earth Engine dataset\n", "def addDate(image):\n", " # parse date stored in 'system:index'\n", " date = ee.Date(image.get('system:index'))\n", "\n", " # format date, see http:#www.joda.org/joda-time/apidocs/org/joda/time/format/DateTimeFormat.html\n", " str = date.format('YYYY-mm-dd')\n", "\n", " return image.set({'Date': str})\n", "\n", "\n", "# point = ee.Geometry.Point(-122.262, 37.8719)\n", "# start = ee.Date('2014-06-01')\n", "# finish = ee.Date('2014-10-01')\n", "\n", "# filteredCollection = ee.ImageCollection('LANDSAT/LC08/C01/T1') \\\n", "# .filterBounds(point) \\\n", "# .filterDate(start, finish) \\\n", "# .sort('CLOUD_COVER', True)\n", "\n", "filteredCollection = ee.ImageCollection('users/sdavidcomer/L7maskedNDVIdated')\n", "\n", "# Bring in image collection\n", "# ndvi = ee.ImageCollection('users/sdavidcomer/L7maskedNDVIdated')\n", "\n", "# Map addDate over image collection\n", "result = filteredCollection.map(addDate)\n", "print(result.first().get('Date').getInfo())\n" ], "outputs": [], "execution_count": null }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Display Earth Engine data layers " ] }, { "cell_type": "code", "metadata": {}, "source": [ "Map.addLayerControl() # This line is not needed for ipyleaflet-based Map.\n", "Map" ], "outputs": [], "execution_count": null } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.1" } }, "nbformat": 4, "nbformat_minor": 4 }