{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "Zonal statistics\n", "================\n", "\n", "Quite often you have a situtation when you want to summarize raster datasets based on vector geometries, such as calculating the average elevation of specific area.\n", "\n", "[Rasterstats](https://github.com/perrygeo/python-rasterstats) is a Python module that does exactly that, easily.\n", "\n", "- Let's start by reading the data:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import rasterio\n", "from rasterio.plot import show\n", "from rasterstats import zonal_stats\n", "import osmnx as ox\n", "import geopandas as gpd\n", "import os\n", "import matplotlib.pyplot as plt\n", "\n", "%matplotlib inline\n", "\n", "# File path\n", "data_dir = \"L5_data\"\n", "dem_fp = os.path.join(data_dir, \"Helsinki_DEM2x2m_Mosaic.tif\")\n", "\n", "# Read the Digital Elevation Model for Helsinki\n", "dem = rasterio.open(dem_fp)\n", "dem" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Good, now our elevation data is in read mode.\n", "\n", "Next, we want to calculate the elevation of two neighborhoods located in Helsinki, called Kallio and Pihlajamäki, and find out which one of them is higher based on the elevation data. We will use a package called [OSMnx](https://github.com/gboeing/osmnx) to fetch the data from OpenStreetMap for those areas.\n", "\n", "- Specify place names for Kallio and Pihlajamäki that Nominatim can identify https://nominatim.openstreetmap.org/, and retrieve the " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "geopandas.geodataframe.GeoDataFrame" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Keywords for Kallio and Helsinki in such format that they can be found from OSM\n", "kallio_q = \"Kallio, Helsinki, Finland\"\n", "pihlajamaki_q = \"Pihlajamäki, Malmi, Helsinki, Finland\"\n", "\n", "# Retrieve the geometries of those areas using osmnx\n", "kallio = ox.gdf_from_place(kallio_q)\n", "pihlajamaki = ox.gdf_from_place(pihlajamaki_q)\n", "\n", "# Reproject to same coordinate system as the\n", "kallio = kallio.to_crs(crs=dem.crs)\n", "pihlajamaki = pihlajamaki.to_crs(crs=dem.crs)\n", "\n", "type(kallio)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As we can see, now we have retrieved data from OSMnx and they are stored as GeoDataFrames.\n", "\n", "- Let's see how our datasets look by plotting the DEM and the regions on top of it" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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3r2iafgLinqO9UCYuQErChzdHhBBJ0Vmooc9o6CDEdQVVsjQtDCQCaHzk6b5h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kra2lGvJGQ7FU1Pxj4Cnwy0No7v48vVrEOX6cZjUyFJmLlF1Y5oVqOK8lhyNT1Dtm+ZPBPRvye6\nudouPE2VBTNvRPfWgZnVIijW3uCNCY3K812vT1WCeqPuu+tjLWq6NBttmQlxBI3FjAu8MfjU4NJI\ndGl6BuU88w3BitpEExVWoIPzBpdH4KOuk7f5hzPMuBR4myYwXgRxJBBB3bFbWjBCu6cRPqn8uxMl\nC/CzbE+6u60OTzKRm4MZy36rTYB+WD2HN0NjKnxfH2manibftR1p2SeREJLbJFsWWV7u4D6g5F0O\nt9JDlRYije3H4qfpPclRQz00zDc1s6uq05uNpp7scJGc8hk8KnAxRUjbQeVFy6jdU1YOn2gmz0Ss\nfb4iOVyUpMoGzaHa0gxTmn5EcliR7hb4SIAGQr0TiJ8uG3RRCfDf+U5ryBvdNQiTiRD5k4mjGmjR\nkyoW+1RdNjSrKWYuRAE1rwPLJ5y/d/eg94c0g9QDLzAfR8IECV6OWI9d7zN9LiM5kjlWNLP4SJHv\nuE6BThcWHfYY0mHVlGsRvVuFkHqdw2aiv1P3pTspqnSCCqr7QVndhU5gI7PK9GAxAmh9UnTjw2vD\nnjMJsplhn2kq180KdeNJjpzgREvJeh9J57ceSOntI0W6K+iWtiR88IlcBis8OFE7Wta8xmuFyyO8\n0ZSrEXe/VTq00RRULTYL88uKwR3ZI6pSQO4+0ah5C57wtHbzurLUw5hkLlDNJjMMb1Q0/Yho2qCs\nAyOfQTmhwRWXU/KtEpwISHeyqZUwdcT42AVi+fFxTX1lRDyuqYfxYpQTGrLOQDUyZHtyE/SJYfJs\nAiph+GYRpG+argI7L1DhqdIkknGBguRsro8KPo+AzO+Uoh7GZDu1WNgNI8FlpqJBJLQz37XzW/aC\n7FMqzLyWFTg2AQOryPcs/VuO5FAwoy3bwuYEIL8kWtSqEijRhW1D1140WQeqU3OXVr+U2SrA+sqR\noRoYijUTuKKhHGu/XuXI9mrye/I5VQs2OHFhdufuIaumXevffz7nQXGgscR7BXre0PQj7n1I1OCH\nb0C+7RnekNK9d9dTrAp0bn416wb9Ppamj6oXmGEzrQRbbR3Vaky1EhHNpfGjQxVgplWn1qesJ9ut\nZEVzHptHsh+tLMVmTLlqSA4XRrvHvn6W0PQjcKLn267KeMj2bVAGbNFMDh/LqhoVwSWuF8vvNsyF\n3+WDnhbeo8oa18ukwogjaYAsR93InqP104gMyV6BSyMRkeqb0LyQDmJyJKJf3ighHm/PaAYxZlrL\nvq9qUEpRXerTupPp2pMdhCzx0KSaJpdRwuRFi88c0V7EymsweSHsvcaLj9gqOSQHAoRoZ3ZNrrv2\nvjh6qU55MD3ynaxLq+2qS5kZmlqG8T5uge6nJOJS5WE3hzT9mPTt/WMvMfvT+98H6Ekh5eFkDkox\neXZEuq8Y3JQbgTPy3ZNxgOZd1iSHmvllRZ33GNyu0JWjWku7RtuxVchBtjUniYVIrYPqvnK2Kyvb\nUtgcBYRRP8EU8ruvVpLO7lA5jyobTloEHnzNOvmO6A/ZXDC2LhaKoHKtLKfp9rE2NUQzwW23VEId\nS2NBNe7Uvftp8XQlKMgvoQgzveXkXC59W1oUSFJbx+Ra2mEs42mgi5VBwS9oqs43EqIDQ7I16Qi9\n7bEE+wliouuoRhHeKBxCCk8PBKzeu2WYX5XZ7PQ5Rf+mkIjLVehtSdIVa4IuykMjBUQJwlSuu0s3\nmabYFNpVOhYQgdee+boM7LWFbK9BVxaXGvSsWpT2J2K51PNGU1ySgb7vpajx/OHnfNkoyAstr39L\nqoZyRaqKwV3LfE3T23Ed2iqeK5IjRz2IiKbSyJm+0CPbrWVL0RLhlZLxSQz1eoYpLGZShs9+PBEE\nLABmUlKv5bhI/E+juRUs8VySczmB6qsrJEcWM18QBpT1mLA3bXJZ3dub4/xKGKMoOrqbMwqXxTJ6\n6b27gp47qufXULUjvnsoCdWOFQI0zScR1UYuw3QlglTOaJKJC9KbMrpI9gXJ4vJIGDOOAHlrZ6ge\nZ3SHHIpmltkljUs0IPQxb2Rumd0Tm3UpqYVEvKwCr61ieKPqSiwAXTuOXkzJ9hzTZyKaXJTrBfvr\nmW1KQ8imYO6CUws+q2uxsSdB7qeEso5kvyK5ffBoJzwRfunRyzpoO9HZPYxu1JhZQ+blhmMzUaDX\npaXpRbhUY0rPfDOmyVPWPjehXEtI705lRORa7OtCtd0r2ffqStBM1eWedGkbR7I9xWXRAiOrWhWE\n4+egWkkkqWfS6FGh6tG13FQXhs8em2mSA5F5salBNZamb7C5waWaaLo00jtHPPUJmtzYxw+C608c\nMXtxJDIVN46EhjavyN6qMZcG1MMYXYtmkbYEGU6LKsUBzJSeaiUhOlhaVYLtuU1Nd1du+qZTnMdD\nuaYZ3LKsfcFy9NKChykwNMQ8diw3BEENnfELDsma7QbRqyO5w++9X37NupIRRnpkybZFkFo1jiiU\n2y2QWzX3r6LHztk5k9On8QL80ZakznUawy4CpUWQe3zNEM0N/buKdHuGsoZoWge1Q1mBbSJbgWIt\nkMLXUjEtgg7ep2dBNSxUL8o5mkEMxESTmvFzMf2tIES+O0Evg1O8R58oPb1W9F7fF3B8HlOP0jCD\ndsdWwRbPm21Xcl1UAkLBe6K5qNK3HeCLxFOfoABqEhKqrDCFo1qNmL+wQv56QMZ4j5nWmNLKKGCe\ndQRrm2jSsC/qUDJJUANoh9xKd92/JjfH7rymFPWFuh9EyQqPa+0LA9BdN55yRTF9HlZfhWxXLtx2\nzliPDPHYEhWecqTpbzVdKe0S3eFzlYN839G7OZV9WStdEpnue6qTe/KlqJ5bI7m1f+bzJ8MNMuF9\nWic3KueYXl8TQbbAyKlHUA+8uJQ5YQd5E3CrSuGNodhMmG2KVEi1Iuc9ORStpHbF77SOTlYCWhON\n64D+0vTvNcTjhuhw/tBqAWRMhNY0/RiX6CAQJ+VtZ80R0EvxUYXNRaRa1yJ+Fs2kIWVK1/UFovPZ\nsgDvJuh9kb69R3Ivxa5kzN67TrJfEe3P0EUlQ2YN+ZZnfkVW3ZY9j/XEOzPsMJXBdClYTp+l4D3T\n5zLprA41gzvNAp8bzHuarPXWFAifqJIjHVkL2aEDJSr39VDQKi5o6UYTAb0PblXMLyUB/+tC+QyD\n25bpFUM89eR3C1E0MHTk9XZl4yErZwsqP2+Y3TF2pS8zxQCa3/qwEUFpRSfAHR8F9NAsoKasky2C\n9kyuZcw3NPWI7rzYdNEthUVydntRkPlEaCLp2mL7MfH2lGh/tvQBjahDnPZdtcJuDqWTbAncUEj3\nKqqVGJsadC1qDfUoElfyQKzomopBOkZZ2b50sEzFuefI7yboKaGKksg5cDnVaiK/iKM5qsXdzWuy\ne1BuZETjClU7keKwHp/oIBDWDtktPsguNqkQuts7bzSHugc+VsHLUyRTmp50X20mZZOuFelhsNiz\nUvY2fRmulyPN8GZFq7iQb4uau64s8UG4UJqIaO6IJ9IU8lpJE6W9SOrmoWUtLGFtLxBt57bVKoon\nqjP4rYeIZKiB0duiXpEcVt17bU+I1q0A2sI9m6AiodHGoGygEAa0kagaaLzW+FTGW9HBkgqCdTJu\nOyM5Aapra4yfT6mGitHbTTCY0h0QXuQ4ZZ5brGpWXy+lAqhCN9x74kmDMxrlA5g+3DilEfduk+jx\noqqJtmuiwxg7SCmfW5GGRSF8UT2rSbWiGSYiGjZtiI4K+YW0TYBQooEkzvxSQnIkjR2bSkkXzySz\nXCEXqpl58m1HtaIxM8HTKid33nTsmG1q4qmiGimRPZm6AGsT3SRdebKdQlaixmHKkuiw6JLRR61w\n1RIqSOsFvO+c7f8LhfdgHbPrG+hSytp0D8p1T++OWM3r2pPuLCWR9hxcz+jtOHavmED/C4yUqaju\nN7kh3g62CzqgdCKNC6yRvffnwpWtPbheEBeH4ZszVFmfWc5Xz62x9/40OJ1D0xPTp1bbqAVoCDIN\nVt6UMZAPekfKOmkcAaaRldcZjQkQPznH766gTyaqGrNXo8sMO0iZXevTf+Ooa0gYpWTVDJFuTaBa\n8AZVVeOTmHhvLoY5K6YjbovXp0hlNJnqIHum8lL6jdtVmAVo3osESJOL7ImyQVun0NhURMzSXWRV\nbyN0o2ncAnOstawkkTk3u/9RooUKqsaK30sWd8io/k3hrA7uCLPGx0YgfaFMHb1Vsf31qWwB+iLp\n0u5dm0yTH9X4PEYdNdSbPXRtqVaSIP6miOcywurdq9GVQ5cNthdjswiyiLi2983B6ysrNP1IlBhz\nOd+mFMVFlKJYlyZeMpEVP5oJo0n8dVTXOFLeo9v3GS343EhjglmUOucpP1eCKqVWgZ8BvlpOD/+p\n9/53lFI/AvxngAV+2Xv/XyqlfgD460tv/1rgg977Tyulfht4BmjbnN/hvb+nlEqBnwe+AdgFvtd7\n/2b42T8E/K3w+h/33v9cePxl4BeBDeAPgB/03i/qoyccaloQNY44M5RXB6RbUxl2TyuYsZihnoRw\nKSUwM61J9kvqfq+jf3XNIutDaauZXjb0dhz5PWkeOROc1PwCn9syVuqe2AzoGmwhQPj5uqJJB+Q7\nAXIYK9LdUpovWSSYYB2s8tr5pFGy/4wjKC/QwTjvuVsaW9jg05keyLyzNVE2jevcznyk8bEM/Vtp\nUGVl7hzNRawtKqRU17NK5ESso1pNqfuadK+ExrHyqlwOelx0DSHTVunG3NckKl9c5+B60qnxt7aN\nLbjDJrojZ6tGkE/JpO6EwoQkrkUQzPuQiItMFKC8lTn8ORpUcP4V9B8Av+q9/26lVAL0lFIfAb4L\n+ID3vlRKXQbw3n8U+CiAUuprgF/y3n966Vg/4L3/5Inj/2Vg33t/XSn1fcDfA75XKbUO/BjwIeTG\n8AdKqY977/fDa37Ce/+LSqn/ORzjJ8/5fR4tyor4qKK4JINoXVnq9ZxoUi/a+8ubf2PwWRy6ilBs\nZujG0+Q6GDUpopl095pMd9YN06tSUpUrinLDk9+TLm88XeBtm574tEQzkeSsYhX8R0Qw28VRp4Q/\nvdKjty2A+PxwjmqRUoE0rWobZEnCanca1O8c4fNUqockRs3vJ3ib0jJ8Q3xV64GIPKeHkmx6HkAT\nYS5ZrWfMLkf0thxNJnPhttSPJ42wTgpZAZuNAWZaUY8SoZ4huFfKB9yvT+4/g3RNKxoOwhBKJo6o\ncJQrpuvay3fxFGuG5KBCFwHc0NpeLB0TRweMuViLTeKhCaqUWgH+FPCXAMIqVSml/irwd733ZXj8\n3ilv/35klXtYfBfw34Z/fwz4R0opBfxZ4Ne993vhs/w68J1KqV8E/gzwF8J7fi68/51NUAS2lgHV\nZo/4sAxSlgmxUZhxCVUtCJvG4dJYGkahTT/fjNCNp9iQgbtqYL4uM9FyHZIjQqNnYU0hsp0BkKBa\nq3YVXL6kVFbBscsbRbEh2j42laRPJp5k4jtbC7uSY46KrlHSyXi4xep/niT1aQxaM782pPfFHQCa\nUYbyKZMXevS2SuJ7E2lAtfPfQUxUeqIS4omQDrR1qEqQO+VmTjypUaWlGhmqkWL0tmXjsy5gZkUW\nVVlHvFd0CRhtHwGQv1aQg2CtqzMqgTOeq55bpR6I5Is3Ikye7ouA2OSZiHQszKBqCKO3pCxe+dJM\niBBFvRj3VOFnKAXlGSoUF4jzgOVfBraBf6KU+pRS6meUUn3gfcC3KaU+oZT6l0qpD5/y3u8FfuHE\nYz+nlPq0Uuq/DkkI8BxwA8B73wCHSOnaPR7iZnhsAzgIr11+/L5QSv0VpdQnlVKfrOzDYWkPjbpB\nzWtJzsZhjqrjQ2vvUfMKO8pCB1d0esbPp52ZkZRHbTdW7AL7twXELt1bsaZochlFmCI4c3kCX9F3\nTJbkyBPPPaYGvCjLj18KGq46WEIo6SAXa4bxSz2qKwOqZ0fB3TpcAu3nb9X2HgBF85GIpR195So+\nUkxfuYQb5thexPyK8DybzDB531pHTHDDnNnlhHKkyPbElKgt/3TYG88vL0gM8WjIhBcAACAASURB\nVNiS7zqSo4bsXtltB3Qte8kWjnfqn6Lq/k3rnKY1PktFh/fE65vLI4rNmPSg6bSJ83t1IIhrsf9Q\nsqWI5sICSncKot1pp+9738+fl2d/vgvs+c+ToBHwQeAnvfdfD0yBvxEeXwe+Gdlz/tOlhEMp9U3A\nzHv/R0vH+gHv/VcB3xb+/OC5P+kjhvf+p7z3H/Lefygx+RM5puvFuDQSbZkwUtFl092Z7cagI+zq\nWU25ZoILmmBPdUNnVxBPpCFkUwEp9G/7kJSS9MWGUNOKdR3gbF6aS8j+zcWtpImsutk9Gcs0/TBv\nU1JOikq7ohoqps8kNJnBDhKaUbYkZBUiXHBnhWosqqgY/eE22dacbHsuxkgBOKErT1RY0oOa+pIw\nXIqrfcrgS1qNDMlRI+CPSSWrj3MMbpQdTC/bmjG4FRzWqkZExAvXqeydJ7xW3fhINRZVinzJyYjv\nHjJ4Y0LdN+S7lny7WZK3EZBBuSpVTzx12ARhybQNpgD0mL13k/qZ1XN9tvPGefagN4Gb3vtPhP9/\nDEnQm8A/89574PeUUg7YRFZbgO/jxOrpvb8V/h4rpf5X4BuR5tAt4HngplIqAlaQZtEt4E8vHeIa\n8NvhuVWlVBRW0WvhtQ+Oc3LwHhbVWtpJb0b7c6LSinas95AmmL0pRIbx+9cYvnrA6PUZR+/pUQ0F\nPdTkodt66KkGinQq0pyt9m16ZNG1E2euZqGT02RygRvnqUPH0CYBwD8TzG089ZibguFVNrivNSIF\nKQ0mQeLEM0WtI2GzjEu5kLWSUvecQ3RlHWZvgs/EdCreL8QO3nnplCIKBLER/GpvR7w3lROvm2Od\nZq0lWVu6XtUQ36sFjVQ0xI1DDVMZYcwriEy35z2rHD95k3lQ2W72p/SR8t5HGm+00MuUCL1l+47k\noCF7a/++47hegq4b8htHqOLJ9ikfuoJ67+8CN5RSr4SHvh34LPBLwEcAlFLvAxJgJ/xfA9/D0v5T\nKRUppTbDv2Pg3wPa1fXjwA+Ff3838Jsh8X8N+A6l1JpSag34DuDXwnO/FV5LeO+/ONc3jh9/spTu\nlSLqfDhHFaU0AeqG+uoKtp90d9T8bsH+B9aYX81Ixk4MeMNKp6zQxlqfF7wYGtWDgNjRsPJGQf+u\nJd1viGZW2CdWhLDiqRfn7ErGNO1YLZkKDnd4wxLPfFcaR4UXwHcpcpUgnUibKXY/tLYYt4TS1l/g\nPKmikj+TuXyPfiwqEZOK/PYUnybMNyKB6B2UJPuyMvpYQB22L6Wtcm7hgBbEnVtupqoaEfAqmq5j\nXm/2qK+uUD2/9tDPeBpX1eepfI7IMHvfJaGRHcy6Vdob2SrkO5bhF4/IX989NcltJnjrJ52ccP4u\n7o8AHw0d3NeB/wQpdX9WKfVHQAX8UEgckKbSDe/960vHSIFfC8lpgP8T+Onw3D8G/hel1GvAHrL6\n4r3fU0r9beD3w+v++7ZhBPxXwC8qpX4c+FQ4xgPDR5r68oD41iMyMULo/QnpvManZskpWncuacW1\nEdmNQ9mjVp5ixbDypTnlSiYq5JauNW8TWU3juUhnuEhRDTSQ0Ls5I6sEQtbarysr0pWm9qT7C2SR\n1Qs/0P5WgKUdOsbPmzCa8ESzhblwVIhXSHpvDm3nMXRygQdics8K8bCZoyvReOpmrl5mka1Haiu6\nJmgeOtftbvV0Mq7ACX8X6xalainKDHaYUawnQV1CY9NN8td2zvxsp3FVm9UcfMb+Kz1WvziX/WFj\nMftTDBDtRdiVXNQbHkCri/bn2LU+0c742OM+T6Fu8HmC7SXEW4cXPqfnStAwJvnQKU/9xTNe/9vI\n3nT5sSky5zzt9QXw58947meBnz3l8deREvncYRONah5jKL/UAWw28gV8DOSCikRuUlnP/MVVSYZc\nJBl9sCBoMoJAlzRJTNWa9XjyHVkt5peE/+iNplpPsKkmOVShfITkqKYaGREX0wtgfTIO+F5FJ6Dc\nv2Nlf1t5lBeDpdb4yUzD/q8O4tnt9zjHmMWu9U+96FVRoesGkphmlGF70aI54hcNEmW9yHmagJ89\nYe4Lp98k2gZVuSkYXZTAI838+NikJV8/KKbPiuzn6usF8e500dFe+vknk+5kNJdHmL0pbiNfyJWG\ncFmEig007pGSE54yJJHydCvRhSKOZC/UKgIqJaOB6VKC1sHGMHQNk4OS+ZVMGkPKkG1XZLs142sp\naN/pCykHPg4qCbU0V0ZvCBLGzGtUEzN52aCuaHQNa68KjG92RdP0YPa8Jd7TDG5Ih9jU0uG1sSIq\nHVEhoxkfXMGFewnpTrFISpbYIH5R5j4o2uT0WoUOaYxPY8zuWMrAeYkapiTb0umcvnIpIIkizKxG\nhZtCG3YlEw/Rygm6J4mpnl0VJf9gmzB7sd8ZCMfjhnhqRKlw5o6xbB42Jppf36RYj8jv1R0u+mRy\nnid8HBHdkxGPmTXUV4fEd8eyXfD+mJ7uo8ZTlaC6duj9yblf73spzVouLHuEeqSP5hBH3eytfZ2a\nlahpgQKSsTAmetYzvjYkmTiOXsrIdy3rnzlg/N6RvE+Bmbvg7ykgeldronmFDvsvU8re1SsREatH\nEdXQkBx5Zlfl50dzwYa2Sd/6wtS5ph4o8sMa3wiLP9uz9G5OOrMkICCJAlY3YIcVD79g7UofH2tc\nGsmec9rAWr8b3bQXLxBkP/2xqkN5v+hHuaAoWNQyNx5lVGsJ8bjpNGqzewLw7+wN12PZIkyPJ4Gy\nDjfMTy1Ld7/1KumBY/D2HD1vMIeny7ScJ5ZXS1U1qMRgV3JxIijOR0B4WDxVCXoRJrvdHFKPEuKD\ncjFoHyYkB9P7ECpn2SLo/QnP/FZJeXVIPK4o11PUtEA3wyCdYjGVOHx7o6nWkgWG2rbQQRi+XTF9\nNibdF/BBut+w85GYpu+Ix7CyWxA7y3Ba8ydvfY5Lfp/n93Z44XCH58c7DKuC33n2ffy1f/uHhemf\nxwKqWKKPeaVE8uQc58inQd821lTrWdCeVdRRQrorGOWTSKLeF7ZxvexYW7K83Ce9JwlixqETHhQt\n4q1Dor2oW83bFc5HBoymfHbUqeGfLB+9VtLp5f5S15RCJli+eTyJKJ4ZEB8KTLEeJcSTGtPYR9rL\nL8dTlaDniljI2iIKpbD9WEjZO3OSG2eTlX1PJP5PJmuzkpPszZm+OGDwBXl/tl2JK1kvIhq3pj+W\n+EjsC04DUutaSrn+rSlf4e/xH3z8LT584zW+4dbrZPbhq937924xe8YIRrct/wLUr1oR2ZD5tQG9\nNw4fuAd1vUyqitrS9GOOXozob1nKoQmyLRnJgcFv9u47X6oWUWzlHONX1kj3g5lyKzcSGxHsWnr9\nsZ896qFqS73ZEyrdZi43mvZcXx5J1bE/xQ1SptcGKOvpvyqTv/qZVXp3yieenHZ9QHxUyQioZfAN\nYvQ8fjdBn2T4foZPIgFbOwde2vD5zfGDcZ0guqzDlOQEQyLaPqJ4aZ18q6C6OiS5sU+0dYjPUnQl\ngAddSXOo86YEiDTeR0RHcgGOn0947rP3+Eef+ymeqY93oWdxQqMMVRTRaGHL/E9/4s/x2vObXNvf\n4+//84/y9vCSNI8akaLsyNfOkRzIz8hvSEOkvaiWmx7li+uYqfhnthKdfpQQT6WLOr8stoHJ2FKN\nYqoVQ3TYQx/NumNhNHpW0GwOybZLoknV4V59pLG9hKioTy0N7Vq/M/uN7xzh86SDGHbn+t4RbtRj\n/8NXmV/SuAjWP7f4vU2ezxi89QTQZPd9OB/MiyshRTSOZiVFFbVUG0o98gjm3QSFTn5TFTVqXuFG\nOT42JDfPKe+hFEfvHZKMLWaYYfaO73Oztw/AOczyW+oGs1dSvGeDpKjxscFFuoO9iVxkAG57z/of\nj/l3tn6/S85//vI382+ufgX/1/vfx/bGUAAQGR2o3KbQ9B0/+hu/CsBnBy+w+npDcm9CqxHbMTCU\n6gjnICXsMl/SbgxRtcP2Y46u91n9zAFuIN3laO4pVjW6ElTT+FpEvuPobVVdcrbflxp8lgintrIL\nU6a6wQ1SoiNpqnSNp16Kmlf4POHo+pBqpLjyG3fkeKfsL6tnV5k+lzG7IiwYF8He+xN6X5Tn137v\n7vl+nxeMY/tYrVClImkrKedR9aMzhJ6uBD1L77W12AuGs8f8Wx4WWuNGOfl2LeoKp7X2l6lFrfNX\nGMintyed/btNNWrqw7hG+JE40eaZvNTna/74LQB+/H1/nl/5mm+kHEmCpPvBel1JJ1hXgFP88G/9\nNt/y1hfZj/v8UvpBBq/uy4Xfuml73zWHjp2PE2F2xxhkFXTxKhiFzcSisRpqGRHtO45eFM3g3u1i\n4S3anvp2NbZCrlZ1fWxlaccZs/duYipHNK6o1jPKlSGjL47FZKlvmL7/Ev3PS8m63AgqXtrg6KWE\nck3MjJXzJGPonSWwdsGwG0PM7oNHLrAgY3tYkOTPMfI5K56uBD0RdnPYQd3QGpJYLt6gJ3SucA6b\nRdhMEx/6hzdZnKN+blXAEsYICskodKSpB9IUadJIRJWVwmcKXTQM3pzyUiUl3Zd6z5DfKah7Oab2\nmAOxOhzcdjJeKRz/+ac/zvd/4V8B8BPP/rscasEhq3mJH2RiU+9918zxuWgn+UijJ6c3vVTdkN0a\n45IAgetrsgNLti37r3iSgPOYcYmeFfe9t/37rH2Z62XUA0P++TFeKZpcMMI2j4knDasH1bH9eXuu\n3ahHNKnAJ0G1UAAiLlbiFv4YFLr2c50nOZej/Xm+lTQ9r1vSiXi6EnR5ddAaFxvMpML1Yqo12W+m\nuwVuNROd3HNGvHVENMkkuauHNAXShHhnBmkSVlJkSF9KR9crmdW6RMSuTdFg+zGjnQOuNEdUynBz\ntIkuHINbFcV6TDRzpNaLsp9u+Duf/Hm+cV/qul++9A18Yv39UrKWteBmg27PseQkQPaWPur4ay+T\n7lTE+/PgAm5R8xIzLzGHU3SxQj2KBTg+KzGHc+rNwX3JeVbYlf6x8lBZy8qntvBZgkIwsPFcqHLx\nzkzK8GbBWVXzUjCzQ7m59O81gRGkOXpBLu2rXzh8rOQEzv19TovWFsTnqchxTi52rKcrQZfDOeI7\nBxBHHF5fZ3bZMHqrQRc15vBijQS71l8M98ezB7/4lGaT8p5qXUjgLhVDo1YUzCUJ0bzh+UYQjom3\n/Bef/hhDU/N/PP9BPnF0XQb5SYTLIj609fkuOQH+IH9ZRhTLJZZRqMDqaIHuy1E9t4ZLNHVPE6dG\nMK8Dmb8ObhREe4K6ibcOibdEJiSaFuA88c6E6vm1B3a8z4pli3mXxqSHwgNt98bl5T57X5ly6TOL\njrob5JK4tSfbmlNuZNQ9xcobdVcKvxPRavWeJ/lVY6XEn1+8UfT0mSedfMgY4okj33G4RDF7cbRI\nNn2+02PGRZBW1Od+z3K4JBLETCMWDbOrCU2msZmmXJXW0u1olf+7fx2AP3f0Gb5t/3P8N5/5Bb72\n9qsCrzuaoWcVn8lf5EvZle7Yf+vtjzGw84W8iffHBvg+kj1pe26ayyNM0aBLSzJeWCC4WImjV6tn\ntBTx1iG+l2JXcornV6ShtD448/tWz67i0/i+fWr3mYzBjhLSvZJ0p5TubWpIt2ekh57ZFVnx7Vof\nIk3dj/CxDu7mjv6dmt6bjwatO28o6y60Mqt5+Ugr+dO7goZQ3lMPDemhJd2aCVC73SOdUzfGDTJU\nbXGD+NEobUZ1GGFvlEifaLCRqCbgYGJyfnrzT/O7/evEvuEj08/z1bOb/M2tj/Oj1/4i2/0N2a8p\nzd9+/j/kR+/8Cl8/eRMNTHTWfa5lSJvP04V3SWsutCtdXh1HKOupRzG6Dnq6zp+KTfVGo8dzVBUI\n11od62T7yBwbnZh5QAut5kSnSX4asbCPq5AEocOsGsfKl+aLz7o/xQ0ysnvS6dbzGrM/feyS9rzh\n8/RUaZcnGU99glJWrPzhjqwwZ8lkPCT0/gTShOTmAb6fLZTqz/v+ozkMM1wSkRzUJAdQjyJREChD\n4irFnWSNO8kaaM2vXP4w/8MbH+UDs7f56bd/ll+6/E3878/8CV6Z3+R7bv0rvq4QIYrXsiuCEY5O\nb1J0Hd2QuN3F3VjieYluhuhJ8UCsavseVdZEp7xuOQHbEQp10wEGfGSor4xE9RDR/NWVlLc+lrmu\nV0AU9p6NrNBmb3JsT2dX+ujGinudtY+Er71QOPdYHdrzxLsJCmAtbpBCGqMftoc8K8Le8kLJ2dof\nBk9S7YQB4RONmTvKUUyMo1YRkKOaVCwLlMJ5z9958T/ir938Zb51/AW+b+tf831b//q+H3HXCO73\ntOG/mpeQp8dA8yfjot3Lk1E9u0q9EounzI0jmTcvK9rHEfNrQw5fjinXxDU8PfD09ytpBoUmiy4q\ncYkzWlQX7P1JYQ6nZ2JwHyfcIOuIAMvxjt8AeDdBu9BFg+slsgJOC/m7au73D32iP1RLkgbJETsQ\nFy2vBDhvKk85NOR7jZjvliLfqazMRg+jPv/dV3wvrxS3+Us3f5MPTt5gqhN+4cqf5Lc//LWsf37M\nG2YDb05X2Tutszh95RIuUQxeO3wi5Vu8O2X63AaDt+cC0QtAifLaKrqyTJ/Lgu2FaDF5jchqTioB\nMrQWDhr0LOCHvT+zs9omZ7M5xPZiosPysQDxIEJx1ph3fLU8LZ7eBG0BA22UFXqpw+rSCN9LjrFW\nnmgoJWghLyWfyyLqYUR8VOMyMYHVjSffazBFsGcfJaQzcexWwepA1ZYvmCv8zZf+AtFAYUvYf2VV\nZDp7nnjmyG9PMackm5qXx1ZOuzFkfikiPbLYfkI0LyWJI/1Iq1L9zGpnF6+rhiZLadb7bH+gx+qX\nhDxgE9Fc6t9xxFORutQtV5QwVulYLkpWz3PcNKOdMVwesf/VI0ZvJveZPnXGTueMx01yn8bHFA7P\nG09vgj6kAaRn9THHrLadrw8fsQReCj/I8UpRt0yQWIjkdV9sHdAKlygO3hORHHoGdxvM3KFtIDgr\nhQ+f3/VTcbDWmnoKbpDQ26o646TWC3MZV3tWc6PYzMh3G4pVQ/Nyn14vJn1778J6rvProm6gixq/\nGpPfmuJjTbkWY2MRgT58OaYeKYZvO9J9KEeK3rYjmjshX0daKpggd4LRC7zzOe0Pzd6U4Y2oc9Je\njpPJeVHntouGT6KFWdUF4ukas1wgVFEuZpbeo8czgd49bqQJ5eUezWrooHrE/TpS5Nti/GsTHWRB\noB4pyhVDPTJC9m6dyELoaYlPY8pnB2IUpEV5wcwasYpwcoEfQ++cwVOMxzVNJurp+Xb9SGZJzeaQ\ng6+I8VmCN5pkv0KXNeVmxtHzhiaTREzG8t2VA7xgiFtZ0mIzweYxLo07ahveYwcp0+eycyvnqcaS\nvr330H20XR+IYNk7GI+6L356V9AHRdu8WQ5jMA+Rv3hgtFZ3ZUWyXwrV7FAIyNE0oloTY1gQq7tG\nGUZvN8G6Xrqf+a6lGSTiF9K6k4UVJj4oaUYpTW6o+5renRLlodhMGOwfX/XPgtoltw+I9wS48Kjs\ni3qUMLxh2f2GDTZ+d0vK915Kcljz7G+MOfq3VqkGiv6dhnJFM3lWS4JOPOWqIZqJkJluUlSTkO4W\nmFLIBGZSMnzjyRs8nSQ3tOG1wq32RRnhnexFPCDeTdAT0bptK5DVqqoFlvcQutlDY8lqQO9P0EcL\nb0pVx8QBgO4SLZKU3lMPZBZpKk/v1lwA6pFGldIk6kADzuHyiHI1RnlPPBFeYrJXkNb2QsnWvrZ4\naYPszd0LfcXyhXVM6dj7ypS1LwoYvr48BA3VMKY3FrmWfFeUInyE2FWUwUyq8JTrYmFhE0VxxeCS\nnMGk7FA40RPu0D4o2g5ySyL//yLeLXFPRIeltW4xF33c5Dwtlr1BqhqzMybenwuBO4hrqSbImHiY\nPZtTbsQyG4x0EM3W3dA+OijItkuRUCkdTW6weXx+0P9S+DwlvXkx5UOvFdtfl1EPIvp3LdFcwP5m\nXqNqJ6vl9RVWPn+Irj3zyzHR3ONCBdv0RPgs2/EM7jiSsaW3I2LVLo9lHPMVG/hIGC311ZUzP0t9\ndQU36omCw2OG2Z+942CEB8W7K+jJaCy+n6IeBRH0COHWBgJ0iGV1bIYJurTY1ND0dKBZ6eCtAk0q\nJW5+Txy9iINjVtUQHXmRvLSLDqg0kGTe6LLkXN3IR7ogte7sEuOJkzmlCY2exDB6Y87Re3Ka1Yxi\nzVD3VfBIhWpViY1f0PC1MUTjmmgq31HPKlwvIX9Dmji6ctIdPkHv9FmCHaQ0g5jD6z2SsaN/8/75\n5Xljfn2TaFyfys65aPg8hfIMOuID4qlLULs+EOWCswAFYV/neumjgxbOijgSZMySLIqqLXZ9IDSq\nxnUXX7pfUq72JDl1gP4lC+hf0zfoWpzJdPu5HeiiXjhRe8/8PRtS7u7MaFZTimd6pHtiseDSCFWL\nWLSqHw95oxrL5qePFnQ7K2ZM4l9T4lPD+u/vcPiBzU4l32aEclbsKeq+ABWiuRds8kTghQSMs+ul\n6GlBduuowwMf60g3FpdGND1pdGXb5YXZI8uRv7aDXekzf2FIuhM/VILzgeEcdnNI04svtHV4uhJU\na3RRS4Ik8cIn0/tFZ1SLEFY0rtHn+X1ojU/izmLurGiurMjopraQJth+gu3HkiAevAtEbe/FpHc9\nJTlceHy6SKFrRd2Xi89rRdOPMKWiGSTEhwU+NuhJhZ4V3Vgluy2J4noJqvEyZ400bjXDzBoBRmCC\nLfvjRSvFOX3lEtNnIkZviaSJrqSxo+qG3u0ClxiiwhAVmvlmGAcV0Lq35ds1ehrOpw7z4sahnMOu\n9wUvTNi/z8vuu6rG4hJNPLZMLxuizYSmH90njXKh73Q4pf+YM1AIMMh7NSaNH/7ipXi6EtT7xepV\n1dIIatE83kNV43opdd+gaycdvCOB1t3nJwnSmY0MGIUb9h644kZbh9jNoejBGhXMdxyuJ3xKlmau\nJqxuPm4pTVpsU2JJTpsuPCzrXoRLFahMHnPi6t0RpItKZEamZaCdgU8Ntpd0EEPVuCcGW/NxRDS3\nDG4JCWG2aRjcCeZHRpPcPsBnCc17VsX6Yt/TFIvqwGtwiV4gpoK1vcKKJE0S0WwOjyn5LXdY07f3\n8XnCoGdoco0ONo4+jjj66g1WPrX1WN/vJIf1zPNwxqz5ouf5qUvQ+8IERFFwmHY96YSWa7EAtld6\ncjdfTlAtnT0faZT1FFf7NH1D77YRycmyOTWhdTtrc3QEaDOWi1A0iIS0rLzC58EjRYvpkY/FgAjr\niSeBAhZMgOfrIjWSHNSL77Q062yTtC0/1cx2LmLt808q6ksDonFJdAjFMz2SsZfZaiE/u73AB5+9\nB191mXJFE09AJ6Kd67WiGhmKD6wyerMg2pmggkWEaixmd4w+Iaw9e+8ms8sxg9sVYsEYMXj9iPlz\nA7Ltlvca07vzePtIOD+i6Ek1lp6uBD0rWkevupH54maCrjzVSoyujIwqvAgr432wLbCQRDTDhPHz\nMfVAUQ36DG9ERAeloEaW2DE+S+/TnfU6AB+cQxFuFA7AY4pGOrWxPmad0HqbuEjcy5T1ZAdywdpU\n4+IEc4rFXpuEPkuOUeKeZHI2l0foJnyHSBOPG5L9ChcAFEQGPS261SW/PSXdjaiHQtPzGibPRign\n1hXleoKuchH4XppVnmy02ACusIkmuzcjPhJli96X9kXqM0+xvYSD9/ZYf0yx6i93vJug1i0u2DQJ\nindi01f3RNXAFJZoyQzIa42KDN4oqpVYXLAPZSQy34zpNf4+WJcqSkgTfLBY90YdX9HbxPdBLCwk\nowqGtd5oXB4teZsId7QeGtHYjTXegGpAXR2S3B2fWk51q+k74MTlUoONNUkdVrqgDgiCMHJZgi6q\nxUxRKcys7uw4bB7T3xIvUxtL5TB5oUe+U1Fd3yS7MxG7DWOoLw9xsSa9Oya7V2LmNfVaxuxaH5tq\n0oOM9O4EVTcUzwzQjWf0dsn8uT796eNbMny54t0EXcbkBiVw5fvoBvBiBzi/kpJFWnRxllfBkNi9\nrRpvAgOl9JhZdTpxu6xQSYzL46DxKiUtddMJX/sw29TzWnRiD+ciNLY5CMAFFhA+L0P++Yah7im0\nlVVIOUO+HjP63P6pifhOJCdAfHdMFEedheDyDSLaGdNcHtFkvW7/qI/m0tgZyP5Z1RZdNoKW6hnK\nFU0yddS9CB8pimcGmCLn4L0p0cyT7zTUl/pEhwJkEKnLFSbPJtJHWO+RTgqyt/a7rm+iFfP3rNP7\nwjsnh/Ik490EXY5wYUVTS7keE5We6XMaEHexZi0n3l0YKGE9yaFchLpsRIR6VovfpdbH2DFdVDWm\nqGR1JJS+sQlymGFFtdKwinenHZLJJZpqaDClNFLEF9TR5KIBGxW+G1ekB55st6be6JPcWnyGk8oG\nTzp8Fh+XUznRKInuHWHX+gvRr/azOLFOSA4rzKRElw3pXUu6mndGwKrw2NQwu5qQ7Unnu+kFYbVZ\ngwpyLNGkxsUpXnuSWwfsfuvV4OotDalst8Y/AjznpHPZlyveTdBTIprWFBvSDteVlJPK0XETvVIi\njULQIworatt4Uc7RjLIzYVpeK7EybNkpwRAIowTG18YSkinZnqKrnKZnqFYivJGOrTMstIMUqJsQ\nTxt0ZbF5dIzA/OUu69S8vK+cNvvT+zRm9awgu9Fg13o0q3lw4K4xkxJzVFJd6RON5VyYStOkimzf\nUq4YbGpIDjRaKXyayHH9gGyvZvr+TZo8ADx6irIB3UQMX724P+y7WNz/H4VNDS4SG4OVNz26Ct6W\nTUgkTZih2mOUNFo9ozgXxcCzoh3rGA3WixGw9bBsCQ/HMMCqccQ7E/RKHkpbse/TjcdU4tI9uxyR\nHlqazEDPML0cEV2JWfsDGbtMX7nU+ZS8E3FexsZpyJ5mc4A5LPCpEZXCTVo7/QAAFRVJREFUPEFN\n5tRXV9ClZXqtR//mLMiiGKZXIvpbDdG8QTdO3j+Vc7X5ezuijt+kxJOG6dWE9NALla0Q1f6TGxAf\nOsPNpRHKe5pejCnEWa2dnQs211BeW70wTvlR4+lMUGNOn2sinUgfafKdGuU8unLSVSwsumpQzuHi\nWFbQSOEbJ0nq3MKd+mGyJy0vM0uDZGTrnu0XnikgyZnE3TjHB1hffFB2TaNk7IjmDdUoJt9u0LUj\nOZS5ajRLguKdlGfvZHKeFefd73Y3tJkkiy4qWWmLBlVbeo1DT0tiBXW/R+9eI3v+HXHcbnoR0UGo\nFMpaYI1Fg5rXDJzcWHVlpSF1ilwKBCHzREPlmDyXEM8ikrHF64xonouDulJftuSEpzVBw1ztZNRX\nV4QGNqkxsxqXRUTWi0u0FSNZGov2Hm8MPtUys0RLkp63DEqTzry29Ujpwh1/XetA1qSGeH9OeaVP\nPTAkhyKNqbzHxhpdOaJpgyktal6DUUQHJU1msCvZY2NJv5zRdqrN7hi7MUSP593qHBUVyTDp3NKP\nrg8YfXHM/FJMPMmIwg2hXhekVDwrSE58dx9HAu7/tquYyrPxO3fFu/TekTByqob+Vi2qhgODrjx1\nL8IcVZjD06lprpcJQKSxT7RL/nQm6GmJlMS41FCNjFjJzSvMrMT3UswsdCSrOiBbPBjAiTSKsg5K\ni4qjs48PxxKzjVZV79jj7ea1rMQzpmpQkTwYH5S4OKPpGfKjCgsYpzD7VWcr72ODyyNBKzmPj748\nwP93Ik4rh7M3dsUtDch6KXaUsPaZhRqCG/VItqZn3pRU3bD/jVfpbduuyQcwe98lwUKvZLLFmYjf\njo8NZnrcDKqNtuFVXekDEO8V8vuMdFcWP048nQl6WlQ18UFBNF2AB/AeNZkf3684JyUyAkb30Ckt\neMwxhM59EcYs7QjGL/2tlmainVZtmoR/+y6JzaQkC6W0LhrwsfxMH8ATkcFHMdNrOcMvNqKk9wiU\ns4vGg/xPHkdOxI0WFoat1CYsmjbm8H7gwWmJdOyzxhH9OyWq8UTb4+5npDtzmqEQ1stVQ7mSM3pj\nho/UMayyT2O8MehZwdHXXsJr0A1kexXNaoouLNHh/IkQy8/VcFZKrSqlPqaU+rxS6nNKqW8Jj/9I\neOyPlVL/Y3jsB5RSn17645RSXxee+wal1P+jlHpNKfUPVeB0KaVSpdT/Fh7/hFLqpaWf/UNKqS+G\nPz+09PjL4bWvhffe72Fw0ZMR9Iaq1RSfnv9wLjZiKORYzD/NGfIoVX08YTRd8nWJujyeaUWajwrZ\n91Y1qrRdUurg+K2KCtUIOdvsjkmOwr62qB4ZZ9uuUucJt9KjuTw69bmLJqcb9Zhf36S+skKzknaP\nn6V8cFqcZmkBApjAaKLdObOrKT6JZc58dQWzNyGa1NhEk4zFwLlcT4nvHB2XiVEKnxrm1zcZvnrI\n8LUJvTtz4lsHJDcPiLcOn1iJe96J0D8AftV7/37gA8DnlFIfAb4L+ID3/quAvw/gvf+o9/7rvPdf\nB/wg8Ib3/tPhOD8J/DDw3vDnO8PjfxnY995fB34C+HsASql14MeAbwK+EfgxpdRaeM/fA34ivGc/\nHOOB0fppPCjMzpj8tZ0Hs1O8l05u29DR4DKD64k72nnU5buS1rHo1C4nZyiHW+AC1QI6qIry2P+P\nHTfsr3pf2H5sSNtFRgvFFRFCO885flC4YY7LIsEZJ1oaM48QPjn95jK71qN4diiEgVQFBlDRdXHN\nzhGmcqQ7JemhRVeO6fs28JmM3ZrLI7kJ7k/J3tijvNpHWUt070jAI09Y1f6hZ1MptQL8KeAfA3jv\nK+/9AfBXgb/rvS/D4/dOefv3A78YjvMMMPLe/6733gM/D/z74XXfBfxc+PfHgG8Pq+ufBX7de7/n\nvd8Hfh34zvDcnwmvJby3PdbZ38U63NrZniHnjiVqGoCLNE1PZnItTA/9gCSt6s6fs70RqLq5b3/a\nxRm/dLs5vN8LxtpuHPDlDpsL0+RRwmuFz1OaYRDSth6sl+pk1Lvw8c4qc0ef3kIHG4n1372LHs+Y\nX98kuX0gKg1KbDh8JMJt3iiSgwrbT6ieX8MbzcE3XJExjnXkr+8+Fuf0od/jHK95GdgG/olS6lNK\nqZ9RSvWB9wHfFsrMf6mU+vAp7/1e4BfCv58Dbi49dzM81j53A8B73wCHwMby4yfeswEchNeePNaD\n40ntx0LOiLZt2Eee3HM8qEwuq+OlbGS6ZPWDPPBCvcDmzhgJmZ1xd7Oor4gESPsZZtfXF4p4Iexa\n/7zf7sIhfFUn0MRHCa1pRgL5c5khnsh8s12R7Fr/2E3HDfNH/qzpW3sL8Ibz5K8JX7Qeye8rGpck\nt/ZJ92uimSU6KIjuHeGMphrFjL54Os75nYjzJGgEfBD4Se/91wNT4G+Ex9eBbwb+OvBP2z0lgFLq\nm4CZ9/6PnvinvkAopf6KUuqTSqlPVnZ+M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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot the Polygons on top of the DEM\n", "ax = kallio.plot(facecolor=\"None\", edgecolor=\"red\", linewidth=2)\n", "ax = pihlajamaki.plot(ax=ax, facecolor=\"None\", edgecolor=\"blue\", linewidth=2)\n", "\n", "# Plot DEM\n", "show((dem, 1), ax=ax)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Which one is higher? Kallio or Pihlajamäki? We can use zonal statistics to find out!**\n", "\n", "- First we need to get the values of the dem as numpy array and the affine of the raster" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# Read the raster values\n", "array = dem.read(1)\n", "\n", "# Get the affine\n", "affine = dem.transform" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- Now we can calculate the zonal statistics by using the function zonal_stats." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\rasterstats\\io.py:294: UserWarning: Setting nodata to -999; specify nodata explicitly\n", " warnings.warn(\"Setting nodata to -999; specify nodata explicitly\")\n" ] } ], "source": [ "# Calculate zonal statistics for Kallio\n", "zs_kallio = zonal_stats(\n", " kallio, array, affine=affine, stats=[\"min\", \"max\", \"mean\", \"median\", \"majority\"]\n", ")\n", "\n", "# Calculate zonal statistics for Pihlajamäki\n", "zs_pihla = zonal_stats(\n", " pihlajamaki,\n", " array,\n", " affine=affine,\n", " stats=[\"min\", \"max\", \"mean\", \"median\", \"majority\"],\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Okey. So what do we have now?" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[{'min': -2.1760001182556152, 'max': 37.388999938964844, 'mean': 12.759059456081534, 'median': 11.267999649047852, 'majority': 0.3490000069141388}]\n", "[{'min': 8.73799991607666, 'max': 46.30400085449219, 'mean': 24.560033970865877, 'median': 24.17300033569336, 'majority': 10.41100025177002}]\n" ] } ], "source": [ "print(zs_kallio)\n", "print(zs_pihla)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Super! Now we can see that Pihlajamäki seems to be slightly higher compared to Kallio." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.9.7" } }, "nbformat": 4, "nbformat_minor": 4 }