ee_export_assets_to_gcs.ipynb

ee_export_assets_to_gcs.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyMmmnx/Z/FAaB+ohovdAWd7",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/jdbcode/29b22546c97b7d395bceaab2180b0921/ee_export_assets_to_gcs.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "CI99N3bWbG7E"
      },
      "outputs": [],
      "source": [
        "import ee\n",
        "\n",
        "ee.Authenticate()\n",
        "ee.Initialize(project='your-project-id')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "assets_path = 'projects/your-project-id/assets/'\n",
        "bucket_name = 'your-bucket-name'"
      ],
      "metadata": {
        "id": "x8ZHGTq_cf-S"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "assets = ee.data.listAssets({'parent': assets_path})\n",
        "\n",
        "assets = assets['assets']\n",
        "\n",
        "tables = []\n",
        "images = []\n",
        "for asset in assets:\n",
        "    if asset['type'] == 'TABLE':\n",
        "        tables.append(asset)\n",
        "    elif asset['type'] == 'IMAGE':\n",
        "        images.append(asset)\n",
        "\n",
        "print('tables', tables)\n",
        "print('images', images)"
      ],
      "metadata": {
        "id": "o2sc_5qTc83D"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for table in tables:\n",
        "    task = ee.batch.Export.table.toCloudStorage(\n",
        "        collection=ee.FeatureCollection(table['id']),\n",
        "        description=table['id'].split('/')[-1],  # Use asset name as description\n",
        "        bucket=bucket_name,\n",
        "        fileNamePrefix=table['id'].split('/')[-1],  # Use asset name as prefix\n",
        "        fileFormat='SHP',\n",
        "    )\n",
        "\n",
        "    task.start()\n",
        "    print(f\"Exporting {table['id']} to gs://{bucket_name}/{table['id'].split('/')[-1]}.shp\")\n"
      ],
      "metadata": {
        "id": "H1nLYLxWmlOL"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for image in images:\n",
        "    # Get projection information\n",
        "    projection = ee.Image(image['id']).projection()\n",
        "    crs = projection.crs()\n",
        "    crsTransform = projection.getInfo()['transform']  # Get transform from getInfo()\n",
        "\n",
        "    task = ee.batch.Export.image.toCloudStorage(\n",
        "        image=ee.Image(image['id']),\n",
        "        description=image['id'].split('/')[-1],\n",
        "        bucket=bucket_name,\n",
        "        fileNamePrefix=image['id'].split('/')[-1],\n",
        "        region=ee.Image(image['id']).geometry(),\n",
        "        crs=crs,\n",
        "        crsTransform=crsTransform,\n",
        "        maxPixels=1e13,\n",
        "        fileFormat='GeoTIFF',\n",
        "    )\n",
        "\n",
        "    task.start()\n",
        "    print(f\"Exporting {image['id']} to gs://{bucket_name}/{image['id'].split('/')[-1]}.tif\")"
      ],
      "metadata": {
        "id": "yg38DgrUmn9b"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}