OpenScientia Planetary Computer

copernicus.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pystac_client\n",
    "import planetary_computer\n",
    "\n",
    "catalog = pystac_client.Client.open(\n",
    "    \"https://planetarycomputer.microsoft.com/api/stac/v1\",\n",
    "    modifier=planetary_computer.sign_inplace,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\user\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\pystac_client\\item_search.py:835: FutureWarning: get_items() is deprecated, use items() instead\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Returned 1 items\n"
     ]
    }
   ],
   "source": [
    "grand_canyon = [-112.15, 36.05]\n",
    "search = catalog.search(\n",
    "    collections=[\"cop-dem-glo-30\"],\n",
    "    intersects={\"type\": \"Point\", \"coordinates\": grand_canyon},\n",
    ")\n",
    "items = list(search.get_items())\n",
    "print(f\"Returned {len(items)} items\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['data', 'tilejson', 'rendered_preview']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(items[0].assets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import planetary_computer\n",
    "import rioxarray\n",
    "\n",
    "signed_asset = planetary_computer.sign(items[0].assets[\"data\"])\n",
    "data = (\n",
    "    rioxarray.open_rasterio(signed_asset.href)\n",
    "    .squeeze()\n",
    "    .drop(\"band\")\n",
    "    .coarsen({\"y\": 5, \"x\": 5})\n",
    "    .mean()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {

requirements.txt