Commit 189e7dee authored by Sarah Heidekorn's avatar Sarah Heidekorn
Browse files

add new notebook

about forest/wood inofrmation in four canadian cities
parents
{
"cells": [
{
"cell_type": "markdown",
"id": "inside-matthew",
"metadata": {},
"source": [
"# ohsome green regions (via tree related tags)\n",
"\n",
"Welcome back to the ohsome Region of the month format where you can learn and get inspired about potential applications of the ohsome api. This time we used jupyter notebook and for our analysis and looked at trees, more precisely forests, in four different canadian cities (Edmonton, Halifax, Ottawa and Vancouver) looking for the green region of the month which means there will be a winner announced at the end of this blogpost. \n",
"\n",
"This time around the analysis will be done via jupyter notebook using the python programming language."
]
},
{
"cell_type": "markdown",
"id": "appropriate-balloon",
"metadata": {},
"source": [
"**1. Data**\n",
"\n",
"As always there is no request without input information and, concerning the boundaries of the request, you can get a GeoJSON with region boundaries here. This file will be used as spatial input to add the information of the boundaries of your request.\n",
"\n",
"\n",
"**2: Import of libraries**\n",
"\n",
"At first you'll have to import libraries that help you handling the data later on. This includes a range of things be it sending the get/post request itself or plotting the output data.\n",
"\n",
"_e.g.: numpy for stats, pandas for analytics or json for simply handling json-files as you will see further down in the code_"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "overall-iraqi",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" <script type=\"text/javascript\">\n",
" window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
" if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
" if (typeof require !== 'undefined') {\n",
" require.undef(\"plotly\");\n",
" requirejs.config({\n",
" paths: {\n",
" 'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
" }\n",
" });\n",
" require(['plotly'], function(Plotly) {\n",
" window._Plotly = Plotly;\n",
" });\n",
" }\n",
" </script>\n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# import of useful libraries for the analysis (e.g. pandas -> analysis, \n",
"# json -> for handling json responses)\n",
"\n",
"import pandas as pd\n",
"import geopandas as gpd\n",
"import numpy as np\n",
"import json\n",
"import geojson\n",
"import requests\n",
"import plotly\n",
"import IPython\n",
"import matplotlib.pyplot as plt\n",
"\n",
"\n",
"# for generating interactive graphs\n",
"import plotly.graph_objs as go\n",
"\n",
"from IPython.display import *\n",
"from geojson import MultiPolygon\n",
"\n",
"plotly.offline.init_notebook_mode(connected=True)"
]
},
{
"cell_type": "markdown",
"id": "silent-medicare",
"metadata": {},
"source": [
"**3: Defining a function and the spatial & temporal boundaries**\n",
"\n",
"Then you'll have to define the spatial and temporal boundaries of the request you intend to send. Begin by defining a variable for the ohsome api as well as a function to help building your request.\n",
"Below you will realize that two functions have been defined as there will be two different types of requests, quite similar to the ones sent in the [ohsome street network analysis](http://k1z.blog.uni-heidelberg.de/2021/01/18/ohsome-street-network-analysis-part-1/). But more information is to be found in the next step of this blogpost."
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "specialized-henry",
"metadata": {},
"outputs": [],
"source": [
"ohsome_api = \"https://api.ohsome.org/v1\"\n",
"\n",
"# defining a function for the filter definition\n",
"def elements(agg,**params):\n",
" res = requests.post(ohsome_api+\"/elements\"+agg,params)\n",
" return res\n",
"\n",
"def users(agg,**params):\n",
" resU = requests.post(ohsome_api+\"/users\"+agg,params)\n",
" return resU\n",
"\n",
"# defining the areas# defining the spatial boundaries:\n",
"#with open(\"yourpath/marchregions.geojson\") as f: #your path: insert the path to your file\n",
"with open(\"/Users/sheidekorn/Desktop/March21/geojsons/marchregions.geojson\") as f:\n",
" regions = json.load(f)\n",
" regions = json.dumps(regions)\n",
"#display(regions) # optional -> if you want to check wether your operation worked\n",
"\n",
"# defining time intervals\n",
"t_mon = \"2008-01-01/2021-02-01/P1M\"\n"
]
},
{
"cell_type": "markdown",
"id": "secret-salmon",
"metadata": {},
"source": [
"**4: Requests**\n",
"\n",
"In the code below is dealing with how you can phrase your exact request. To keep it simple and get a first look at the data the request only asks for the overall density of wood/forest in the regions of interest.\n",
"\n",
"\n",
"For this months analysis you can request the data by using the following conditions:\n",
"\n",
"For the forest dataset:\n",
"\n",
"_endpoint\t->\t/elements/area/density/groupBy/boundary_\n",
"\n",
"_timestamp \t->\t2008-01-01/2021-02-01/P1M_\n",
"\n",
"_filter\t\t->\t(landuse=forest or nature=wood) and geometry:polygon_\n",
"\n",
"\n",
"For the user dataset:\n",
"\n",
"_endpoint\t\t->\t/users/groupBy/boundary_\n",
"\n",
"_timestamp\t\t->\t2008-01-01/2021-02-01/P1M_\n",
"\n",
"_filter\t\t ->\tlanduse=forest or nature=wood_"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "greater-eligibility",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"'https://api.ohsome.org/v1/elements/area/density/groupBy/boundary'"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 864x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# defining and plotting request/path to natural_trees.txt?\n",
"def area():\n",
" filter='(landuse=forest or natural=wood) and geometry:polygon'\n",
" res = elements(\"/area/density/groupBy/boundary\"\n",
" ,filter=filter\n",
" ,bpolys=regions\n",
" ,time=t_mon)\n",
" display(res.url)\n",
" green = res.json()\n",
" #display(body)\n",
" df = pd.DataFrame()\n",
" for groupBy in green['groupByResult']:\n",
" series = pd.Series({row['timestamp']:row['value'] for row in groupBy['result']})\n",
" df[groupBy['groupByObject']] = series\n",
" df.set_index(pd.to_datetime(df.index),inplace=True)\n",
" df.to_pickle(\"./df_density.pkl\")\n",
" df.plot(figsize=(12,10), fontsize=11)\n",
"area()"
]
},
{
"cell_type": "markdown",
"id": "editorial-scotland",
"metadata": {},
"source": [
"**Analysis Part 1 - Density**\n",
"\n",
"Above you can see the result of said request as well as the POST-request itself.\n",
"\n",
"When looking at the plot of the output dataset it is pretty safe to say that Edmonton has the lowest density of forest/wood information given when comparing it to the other regions. Although this might be part of low mapping activities too, it might as well be related to local oil and gas production areas or farmland which reduced the amount of forest. Another factor could be the general geographic connection to the Prairies Ecozone.\n",
"\n",
"Furthermore it is worth mentioning that all cities, except Vancouver, only really added their forest information around 2010 and 2011 (Edmonton). \n",
"Interestingly enough the density values for Vancouver, though starting to increase the earliest, remain quite low for the period between 2011-2013 and only cross parts with the Ottawa- and Halifax-values around 2017. Additionally there is a strong increase in density in the early 2013 months. _(potential reason?)_\n",
"\n",
"Ottawa and Halifax both begin hold increasing information starting around the same period in 2010 and cross each other several times until Ottawa finally takes its place at the top in 2018. Density wise it (Ottawa) is the winner looking at the overall development of density throughout the years. However, it has a short … where it decreases in density between 2016 and 2017. _(potential reasons?)_"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "potential-intent",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>region</th>\n",
" <th>mean</th>\n",
" <th>median</th>\n",
" <th>min</th>\n",
" <th>max</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Vancouver</td>\n",
" <td>204006.882405</td>\n",
" <td>260064.895</td>\n",
" <td>614.07</td>\n",
" <td>319494.75</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Halifax</td>\n",
" <td>223159.972215</td>\n",
" <td>296758.975</td>\n",
" <td>0.00</td>\n",
" <td>324080.16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Edmonton</td>\n",
" <td>28518.290506</td>\n",
" <td>32828.065</td>\n",
" <td>0.00</td>\n",
" <td>49962.98</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Ottawa</td>\n",
" <td>234835.112468</td>\n",
" <td>316338.055</td>\n",
" <td>1942.07</td>\n",
" <td>330267.47</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" region mean median min max\n",
"0 Vancouver 204006.882405 260064.895 614.07 319494.75\n",
"1 Halifax 223159.972215 296758.975 0.00 324080.16\n",
"2 Edmonton 28518.290506 32828.065 0.00 49962.98\n",
"3 Ottawa 234835.112468 316338.055 1942.07 330267.47"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<AxesSubplot:ylabel='region'>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x576 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df_density = pd.read_pickle(\"./df_density.pkl\")\n",
"\n",
"val = {'region':['Vancouver', 'Halifax', 'Edmonton', 'Ottawa'], \n",
"'mean': [204006.8824050633, 223159.97221518986, 28518.290506329115, 234835.11246835446], \n",
"'median': [260064.895, 296758.975, 32828.065, 316338.055], 'min':[614.07, 0.0, 0.0, 1942.07], \n",
"'max':[319494.75, 324080.16, 49962.98, 330267.47]}\n",
"val_density = pd.DataFrame(val)\n",
"\n",
"#df_density.plot(kind='box', figsize=(12,10), fontsize=9)\n",
"display (val_density)\n",
"val_density.plot.barh(0, figsize=(12,8))\n",
"\n",
"\n",
"#The table was created by searching for the mean, median, minimum and maximum values of each region.\n",
"#You can do it with numpy, like so:\n",
"#Ottawa, Ontario:\n",
"#Oarray = df_density['Ottawa']\n",
"#OttMean = np.mean(Oarray)\n",
"#OttMedian = np.median(Oarray)\n",
"#OttMin = np.min(Oarray)\n",
"#OttMax = np.max(Oarray)\n",
"#display(\"Ottawa\")\n",
"#display(OttMean, OttMedian, OttMin, OttMax) #-> to look at the values"
]
},
{
"cell_type": "markdown",
"id": "therapeutic-allen",
"metadata": {},
"source": [
"Users:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "middle-fisher",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"'https://api.ohsome.org/v1/users/count/groupBy/boundary'"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
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"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"Empty DataFrame\n",
"Columns: []\n",
"Index: []"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x936 with 4 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"def groupBy():\n",
" filter='landuse=forest or natural=wood'\n",
" resU = users(\"/count/groupBy/boundary\"\n",
" ,filter=filter \n",
" ,bpolys=regions\n",
" ,time=t_mon)\n",
" display(resU.url)\n",
" green_u = resU.json()\n",
" #display(green_u)\n",
" df = pd.DataFrame()\n",
" display(df)\n",
" for groupBy in green_u['groupByResult']:\n",
" series = pd.Series({row['fromTimestamp']:row['value'] for row in groupBy['result']})\n",
" df[groupBy['groupByObject']] = series\n",
" df.set_index(pd.to_datetime(df.index),inplace=True)\n",
" df.to_pickle(\"./df_users.pkl\")\n",
" df.plot(kind='line', subplots=True, sharex=False, sharey=True, figsize=(10,13), fontsize=9)\n",
"groupBy()"
]
},
{
"cell_type": "markdown",
"id": "confidential-purchase",
"metadata": {},
"source": [
"**Analysis Part 2 - Users**\n",
"\n",
"\n",
"When looking at the minimum value of the user data output all the regions have the value 0, so during the time span looked at there were periods where there were no users of the request-tags at all.\n",
"Again, Edmonton hat the lowest values (mean, median & maximum) which might be yet another reason for the overall lower values in density of tree related polygon-tags.\n",
"\n",
"Halifax and Ottawa both have the same maximum value yet Ottawa is higher in mean as well as median. And the highest overall user-values are to be found in Vancouver.\n",
"\n",
"All regions but Edmonton have outliers which is in accord with the density values of Edmonton. These outliers are all unusually high user numbers and never unusually low because the lowest common value is 0 and it is quite tricky to get a negative amount of users.\n",
"\n",
"\n",
"\n",
"Vancouver:only very short timespans of complete user inactivity,\n",
"\t\t increasing trend „observable“ although the line is rather \t\t\t\t \n",
"\t\t zackig; quite strong variation in monthly user activity;\n",
"\t\t peak around Mid 2020\n",
"\n",
"Ottawa: 3 times of minor user activity until 2009; increasing trend \t\n",
"\t\t tendencies until 2018 with times of lower user activity between \t\t \n",
" 2014-Mid 2015\n",
"\n",
"Edmonton: almost no user activity from 2008- End 2010, 2 minor peaks in \t\t \t\n",
"\t\t 2008; for certain time periods going back to low to no user \n",
"\t\t activity; peak is reached by the end of 2017 but after still \t\n",
"\t\t some quite high values; phase of rather low values around the \n",
"\t\t beginning of 2016\n",
"\n",
"Halifax: until mid 2010 almost no user activity apart from a very short \n",
"\t\t peak in the very beginning; Peaks around the beginning until \n",
"\t\t mid 2017 und at the end of 2020"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "liable-victim",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>region</th>\n",
" <th>mean</th>\n",
" <th>median</th>\n",
" <th>min</th>\n",
" <th>max</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Vancouver</td>\n",
" <td>7.191083</td>\n",
" <td>6.0</td>\n",
" <td>0.0</td>\n",
" <td>25.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Halifax</td>\n",
" <td>2.878981</td>\n",
" <td>2.0</td>\n",
" <td>0.0</td>\n",
" <td>13.0</td>\n",
" </tr>\n",