{ "cells": [ { "cell_type": "markdown", "id": "b8768c9d", "metadata": {}, "source": [ "# Understanding Visitor Use in U.S. National Parks Using Cellphone GPS data\n", "\n", "#### GEOG 489 2022 Spring Group Project\n", "\n", "#### Team members: Chang Cai, Eleanor Lynn Hollas, Jordan Victoria Parker, Piper Josephine Siblik\n" ] }, { "cell_type": "markdown", "id": "93428d45", "metadata": {}, "source": [ "## Part 1: presentation\n", "\n", "### 1. Project overview:\n", "#### 1.1 Project goals:\n", "\n", "* Validate SafeGraph data with traditional National Park Service (NPS) monthly visitor use counts\n", "* Investigate traffic congestion based on Safegraph data\n", "\n", "#### 1.2 Project motivation:\n", "* Real-time visitation data can help park manager in planning of infrastructure and mitigating the impact of overcrowding.\n", "* Current official visitation records are of limited granularity and are generally expensive to collect.\n", "* Safegraph data, which has previously been utilized to study human mobility patterns, could be used as a substitute for identifying spatial and temporal variation in visitation." ] }, { "cell_type": "markdown", "id": "445b3aaf", "metadata": {}, "source": [ "### 2. Implementation: \n", "\n", "#### 2.1 Data sources: \n", "| Name/source | Description | Format |\n", "| :-- | :-- | :-- |\n", "| POI visitor counts (Safegraph) | Contains information on the number of people that stop at POIs all over the US which can be downloaded by zipcode on the website. Data is gathered through location services on smartphones which offers a sample of the whole population. | ```location_name = \"Jordan Pond House\"```
```Placekey = \"zzy-222@64v-dvx-v75\"```
```naics_code = \"722511\"```
```latitude = 44.32057```
```longitude = -68.246385```
```date_range_start = 2020-06-01T00:00:00-04:00```
```visits_by_day = [0,2,3,5,6,3,5,19,38,4,5,6, …]```|\n", "| Park visitor counts (NPS) | Contains quality controlled data collected from park staff to get an accurate count of the total number of visitors at a park each month using the person-per-vehicle factor. This single csv file contains information for all the parks in the NPS. | ```ParkName = \"Acadia NP\"```
```UnitCode = \"ACAD\"```
```Year = 2019```
```Month = 1```
```RecreationVisits = \"10,520\"```|\n", "| Park boundaries (NPS) | Shapefile provided by the NPS that contains the boundaries of all parks in the NPS as multipolygons. | ```UNIT_CODE = \"ACAD\"```
```geometry = …```|\n", "| Entrance locations (NPS) | CSV file containing entrance locations of each park under investigation that was manually created using NPS websites for the park and google maps.|```unitCode = \"ACAD\"```
```entrance = \"hulls cove\"```
```lat_lon = 44.381534013388006, -68.06868817972637```|\n", "\n", "#### 2.2 Analysis:\n", "\n", "* Data cleaning\n", "\n", "* Data validation\n", "\n", "\n", "* Road network analysis\n", "\n" ] }, { "cell_type": "markdown", "id": "8eec92a4", "metadata": {}, "source": [ "### 3. Result discussion \n", "\n", "#### 3.1 Visually compare the Safegraph data with the NPS official visiation data:\n", "* __First difference correlation__ provides a more accurate assessment of correlation for non-stationary time series data because it considers the difference in value between one data point and the next. To determine how closely the Safegraph cell phone data captures National Park visitation we will be utilizing these first difference correlations. \n", "\n", " 1) Results from __Glacier__:\n", " ![](./img/monthly_GLAC.png)\n", " * The first difference correlation between the first difference of Safegraph and NPS monthly series is 0.8316. The first difference correlation is good but Safegraph overestimated the 2020’s visitation. \n", " * Glacier NP reported that due to their new visitor registration system they had no way of reporting non-recreational visits to the park for the summer of 2020 which would account for this discrepancy, as SafeGraph records all visitation regardless of recreational or not. \n", "\n", " 2) Results from __Great Smoky__:\n", " ![](./img/monthly_GRSM.png)\n", " * GRSM first difference correlation: 0.75. GRSM correlation is relatively strong but faces some issues with the Safe Graph data underrepresenting visitation during the fall months. \n", " * Due to closures in April 2020 for COVID you can see a severe drop in visitation for that month from both Safe Graph and NPS data. They reopened in May and the numbers increased rapidly from then on before falling back into normal trends. \n", " \n", " 3) Results from __Zion__:\n", " ![](./img/monthly_ZION.png)\n", " \n", " 4) Results from __Yellowstone__:\n", " ![](./img/monthly_YELL.png)\n", " * Yellowstone had a very good first-differenced correlation = 0.8816, hence more representative of the visitor population\n", " \n", " 5) Results from __Acadia__:\n", " ![](./img/monthly_ACAD.png)\n", " * With a correlation of first differences equal to .93, the Safe Graph and NPS data is shown to be highly correlated for this park. \n", " * The summer of 2021 is the worst fit, with no discernible reason for why the Safegraph data underestimates this time period. This is probably due to a multitude of factors, one being that since July 2021 the Acacia NP visitor calculation system has been non-functional and they have been using estimations. Another explanation could be explained through the dominance of the Jordan Pond House restaurant POI and the various ways that COVID 19 affected restaurant attendance. \n", " * This correlation might be taken with a grain of salt, considering it had the lowest number of POIs. With this in consideration, Yellowstone which has a higher number of POIs, also had a high first difference correlation and might be seen as a more credible example of SafeGraph data validation. \n" ] }, { "cell_type": "markdown", "id": "0204999e", "metadata": {}, "source": [ "#### 2.2 Comparing the KDE maps across years, we observe that the distribution of visitation derive from Safegraph changed due to multiple reasons.\n", "\n", "1) Results from __Glacier__: \n", "\n", "\n", "The safe graph data of Glacier is somewhat unstable due to the fact that:\n", "- A couple of POIs stopped reporting data in 2020. In total, there are 14 POIs found within the Glacier, but only 11 are reporting data in 2020.\n", "- This sudden drop in the number of “active” POIs can also be observed from the skinny cluster on 2020’s heatmap. \n", "\n", "2) Results from __Great Smoky__: \n", "\n", "\n", "99 POIS is the most abundant, providing more accurate spatial data:\n", "- You can observe the visitors expanding to the southern part of the park in more recent years/months, this trend is also visible in Yellowstone, another park with a large amount of POIs.\n", "\n", "3) Results from __Zion__: \n", "\n", "\n", "4) Results from __Yellowstone__: \n", "\n", "55 POIS is a robust sample, providing more trustworthy data.\n", "\n", "5) Results from __Acadia__: \n", "\n", "Only 10 POIs found within the park. If the number of POI is small, Safegraph data doesn’t seem to capture NPS visitation that well." ] }, { "cell_type": "markdown", "id": "0a593456", "metadata": {}, "source": [ "#### 3.3 Road network analysis\n", "For Great Smoky NP: Compare the interactive maps of Aug.1 2018 with that of Aug.1 2021. Did we observe an increase/decrease in the congestion in the road network after the pandemic?\n", "* Traffic conditions on Aug 02, 2018: __Click__ map of Aug 02, 2018\n", "* Traffic conditions on Aug 01, 2021: __Click__ map of Aug 01, 2021" ] }, { "cell_type": "markdown", "id": "4eaafbab", "metadata": {}, "source": [ "## Part 2: Code demo, an example of Glacier National Park" ] }, { "cell_type": "markdown", "id": "3c08d82f", "metadata": {}, "source": [ "### 1. Data cleaning (not run)\n", "- Input: \n", " - SafeGraph pattern dataset downloaded at the state level (`MT.csv`)\n", " - Park boundary (`nps_boundary.shp`)\n", "- Process: spatial subsetting, geocoding\n", "- Results: \n", " - Daily visiation time series of in-park POIs \n", " - A GeoJSON file that contains these in-park POIs for subsequent analysis\n", " \n", "```python\n", "# Load data and convert dataframe to geodataframe using lon and lat columns\n", "boundary = gpd.read_file('../raw_data/nps_boundary/nps_boundary.shp') # boundary shapefile\n", "boundary = boundary.set_index('UNIT_CODE') \n", "df = pd.read_csv('../raw_data/SafeGraph/MT.csv') # safegraph data\n", "gdf = gpd.GeoDataFrame(df, \n", " crs = \"EPSG:4269\",\n", " geometry = gpd.points_from_xy(df.sg_c__longitude, df.sg_c__latitude))\n", "\n", "# Geocode POIs with missing lot-lat info\n", "gdf_na = gdf[gdf['geometry'].is_empty] \n", "gdf_na[\"address\"] = gdf_na['sg_mp__street_address'] + ', ' + gdf_na['sg_mp__city'] + ', ' + gdf_na['sg_mp__region'] + ' ' + gdf_na['sg_mp__postal_code'].astype(int).astype(str)gdf_na['sg_mp__postal_code'].astype(int).astype(str)\n", "na_poi = gdf_na[['placekey', 'address']].drop_duplicates()\n", "geo = geocode(na_poi['address'], provider='nominatim', user_agent = 'autogis_xx')\n", "geo['geometry'].intersects(boundary.at[park, 'geometry']).sum() # check these POIs don't fall within park boundary, so disregard them\n", "\n", "# Subset POIs located within the park boundary of Glacier NP\n", "subset_gdf = gdf.loc[gdf['geometry'].intersects(boundary.at['GLAC', 'geometry'])]\n", "subset_gdf = subset_gdf.dropna(subset = ['sg_mp__visits_by_day']) # drop NA in the daily visitation column due to data error\n", "\n", "# Explode daily visitation column to multiple rows\n", "subset_gdf.sg_mp__visits_by_day = subset_gdf.sg_mp__visits_by_day.apply(literal_eval) # convert from string to JSON list\n", "subset_gdf = subset_gdf.explode('sg_mp__visits_by_day') # explode it vertically and have each row representing a day\n", "\n", "# Create date column to indicate the exact date of year\n", "subset_gdf['n_of_day'] = subset_gdf.groupby(['date_range_start','placekey']).cumcount()\n", "subset_gdf['date_range_start'] = pd.DatetimeIndex(subset_gdf.date_range_start) # convert from string to date\n", "subset_gdf['date'] = pd.DatetimeIndex(subset_gdf.date_range_start) + pd.to_timedelta(subset_gdf['n_of_day'], unit = 'd')\n", "\n", "# save a subset of POIs as GeoJSON file.\n", "subset_gdf.to_file('../clean_data/POI_GLAC.geojson', driver = 'GeoJSON')\n", "\n", "```" ] }, { "cell_type": "markdown", "id": "cc40c183", "metadata": {}, "source": [ "### 2. Data validation\n", "- Input: \n", " - GeoJSON file that contains POIs found within the Glacier park boundary (`GeoJSON`)\n", " - NPS monthly visitor counts (`nps_visit_2015_2021.csv`)\n", "- Tasks: temporal aggregation, merging\n", "- Results: \n", " - A time series plot comparing two data sources\n", " - A density plot to gauge the spatial dynamics" ] }, { "cell_type": "code", "execution_count": 1, "id": "f353d6e7", "metadata": {}, "outputs": [], "source": [ "# !pip install geoplot" ] }, { "cell_type": "code", "execution_count": 2, "id": "067c0990", "metadata": {}, "outputs": [], "source": [ "import geopandas as gpd \n", "import pandas as pd\n", "from geopandas.tools import geocode\n", "from ast import literal_eval\n", "import matplotlib.pyplot as plt\n", "import geoplot\n", "import osmnx as ox\n", "import networkx as nx\n", "from tqdm import tqdm, trange" ] }, { "cell_type": "markdown", "id": "ad8ce24d", "metadata": {}, "source": [ "Load the cleaned GeoJSON file:" ] }, { "cell_type": "code", "execution_count": 3, "id": "a4cc344e", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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date_range_startdate_range_endplacekeysg_c__parent_placekeysg_c__location_namesg_c__safegraph_brand_idssg_c__brandssg_c__top_categorysg_c__sub_categorysg_c__naics_code...sg_mp__popularity_by_daysg_mp__device_typesg_mp__normalized_visits_by_state_scalingsg_mp__normalized_visits_by_total_visitssg_mp__normalized_visits_by_total_visitorssg_mp__normalized_visits_by_region_naics_visitssg_mp__normalized_visits_by_region_naics_visitorsn_of_daydategeometry
02021-08-012021-09-01zzy-222@3wy-prx-xwkNoneJammer Joe's Grill and PizzeriaNoneNoneRestaurants and Other Eating PlacesFull-Service Restaurants722511.0...{'Monday': 10, 'Tuesday': 16, 'Wednesday': 12,...{'android': 29, 'ios': 22}1040.776280.0000130.0000370.0001250.00019402021-08-01T00:00:00POINT (-113.87642 48.61768)
12021-08-012021-09-01zzy-222@3wy-prx-xwkNoneJammer Joe's Grill and PizzeriaNoneNoneRestaurants and Other Eating PlacesFull-Service Restaurants722511.0...{'Monday': 10, 'Tuesday': 16, 'Wednesday': 12,...{'android': 29, 'ios': 22}1040.776280.0000130.0000370.0001250.00019412021-08-02T00:00:00POINT (-113.87642 48.61768)
22021-08-012021-09-01zzy-222@3wy-prx-xwkNoneJammer Joe's Grill and PizzeriaNoneNoneRestaurants and Other Eating PlacesFull-Service Restaurants722511.0...{'Monday': 10, 'Tuesday': 16, 'Wednesday': 12,...{'android': 29, 'ios': 22}1040.776280.0000130.0000370.0001250.00019422021-08-03T00:00:00POINT (-113.87642 48.61768)
32021-08-012021-09-01zzy-222@3wy-prx-xwkNoneJammer Joe's Grill and PizzeriaNoneNoneRestaurants and Other Eating PlacesFull-Service Restaurants722511.0...{'Monday': 10, 'Tuesday': 16, 'Wednesday': 12,...{'android': 29, 'ios': 22}1040.776280.0000130.0000370.0001250.00019432021-08-04T00:00:00POINT (-113.87642 48.61768)
42021-08-012021-09-01zzy-222@3wy-prx-xwkNoneJammer Joe's Grill and PizzeriaNoneNoneRestaurants and Other Eating PlacesFull-Service Restaurants722511.0...{'Monday': 10, 'Tuesday': 16, 'Wednesday': 12,...{'android': 29, 'ios': 22}1040.776280.0000130.0000370.0001250.00019442021-08-05T00:00:00POINT (-113.87642 48.61768)
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5 rows × 56 columns

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" ], "text/plain": [ " date_range_start date_range_end placekey sg_c__parent_placekey \\\n", "0 2021-08-01 2021-09-01 zzy-222@3wy-prx-xwk None \n", "1 2021-08-01 2021-09-01 zzy-222@3wy-prx-xwk None \n", "2 2021-08-01 2021-09-01 zzy-222@3wy-prx-xwk None \n", "3 2021-08-01 2021-09-01 zzy-222@3wy-prx-xwk None \n", "4 2021-08-01 2021-09-01 zzy-222@3wy-prx-xwk None \n", "\n", " sg_c__location_name sg_c__safegraph_brand_ids sg_c__brands \\\n", "0 Jammer Joe's Grill and Pizzeria None None \n", "1 Jammer Joe's Grill and Pizzeria None None \n", "2 Jammer Joe's Grill and Pizzeria None None \n", "3 Jammer Joe's Grill and Pizzeria None None \n", "4 Jammer Joe's Grill and Pizzeria None None \n", "\n", " sg_c__top_category sg_c__sub_category \\\n", "0 Restaurants and Other Eating Places Full-Service Restaurants \n", "1 Restaurants and Other Eating Places Full-Service Restaurants \n", "2 Restaurants and Other Eating Places Full-Service Restaurants \n", "3 Restaurants and Other Eating Places Full-Service Restaurants \n", "4 Restaurants and Other Eating Places Full-Service Restaurants \n", "\n", " sg_c__naics_code ... sg_mp__popularity_by_day \\\n", "0 722511.0 ... {'Monday': 10, 'Tuesday': 16, 'Wednesday': 12,... \n", "1 722511.0 ... {'Monday': 10, 'Tuesday': 16, 'Wednesday': 12,... \n", "2 722511.0 ... {'Monday': 10, 'Tuesday': 16, 'Wednesday': 12,... \n", "3 722511.0 ... {'Monday': 10, 'Tuesday': 16, 'Wednesday': 12,... \n", "4 722511.0 ... {'Monday': 10, 'Tuesday': 16, 'Wednesday': 12,... \n", "\n", " sg_mp__device_type sg_mp__normalized_visits_by_state_scaling \\\n", "0 {'android': 29, 'ios': 22} 1040.77628 \n", "1 {'android': 29, 'ios': 22} 1040.77628 \n", "2 {'android': 29, 'ios': 22} 1040.77628 \n", "3 {'android': 29, 'ios': 22} 1040.77628 \n", "4 {'android': 29, 'ios': 22} 1040.77628 \n", "\n", " sg_mp__normalized_visits_by_total_visits \\\n", "0 0.000013 \n", "1 0.000013 \n", "2 0.000013 \n", "3 0.000013 \n", "4 0.000013 \n", "\n", " sg_mp__normalized_visits_by_total_visitors \\\n", "0 0.000037 \n", "1 0.000037 \n", "2 0.000037 \n", "3 0.000037 \n", "4 0.000037 \n", "\n", " sg_mp__normalized_visits_by_region_naics_visits \\\n", "0 0.000125 \n", "1 0.000125 \n", "2 0.000125 \n", "3 0.000125 \n", "4 0.000125 \n", "\n", " sg_mp__normalized_visits_by_region_naics_visitors n_of_day \\\n", "0 0.000194 0 \n", "1 0.000194 1 \n", "2 0.000194 2 \n", "3 0.000194 3 \n", "4 0.000194 4 \n", "\n", " date geometry \n", "0 2021-08-01T00:00:00 POINT (-113.87642 48.61768) \n", "1 2021-08-02T00:00:00 POINT (-113.87642 48.61768) \n", "2 2021-08-03T00:00:00 POINT (-113.87642 48.61768) \n", "3 2021-08-04T00:00:00 POINT (-113.87642 48.61768) \n", "4 2021-08-05T00:00:00 POINT (-113.87642 48.61768) \n", "\n", "[5 rows x 56 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Load saved GeoJSON \n", "subset_gdf = gpd.read_file('./data/POI_GLAC.geojson')\n", "\n", "# load park boundary\n", "boundary = gpd.read_file('./data/nps_boundary.geojson')\n", "boundary = boundary.set_index('UNIT_CODE') \n", "\n", "# convert variable to propoer format\n", "subset_gdf['date_range_start'] = pd.DatetimeIndex(subset_gdf.date_range_start) # convert to datetime\n", "subset_gdf['sg_mp__visits_by_day'] = pd.to_numeric(subset_gdf['sg_mp__visits_by_day']) # convert to numeric\n", "subset_gdf.head()" ] }, { "cell_type": "markdown", "id": "e842d001", "metadata": {}, "source": [ "Aggreagate safegraph daily visitaiton to the park-month level: by `'date_range_start'`(column for year-month)" ] }, { "cell_type": "code", "execution_count": 4, "id": "dafe4c4e", "metadata": {}, "outputs": [], "source": [ "park_month = subset_gdf.groupby('date_range_start')['sg_mp__visits_by_day'].sum().to_frame()" ] }, { "cell_type": "markdown", "id": "de741665", "metadata": {}, "source": [ "Load NPS monthly visitor counts:" ] }, { "cell_type": "code", "execution_count": 5, "id": "ef3bbd5c", "metadata": {}, "outputs": [], "source": [ "nps = pd.read_csv('./data/nps_visit_2015_2021.csv')\n", "nps = nps[nps['UnitCode'] == 'GLAC'] # filter data for Glacier only\n", "nps['RecreationVisits'] = nps['RecreationVisits'].str.replace(\",\", \"\").astype(float) # convert to numeric data\n", "# Create a column to indicate year-month\n", "nps['date'] = pd.to_datetime(nps[['Year', 'Month']].assign(DAY = 1))" ] }, { "cell_type": "markdown", "id": "796a9efa", "metadata": {}, "source": [ "**Merge** Safegraph monthly data to NPS visitation:" ] }, { "cell_type": "code", "execution_count": 6, "id": "3272fec8", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ParkNameUnitCodeParkTypeRegionStateYearMonthRecreationVisitsNonRecreationVisitsRecreationHours...RecreationHoursTotalNonRecreationHoursTotalConcessionerLodgingTotalConcessionerCampingTotalTentCampersTotalRVCampersTotalBackcountryTotalNonRecreationOvernightStaysTotalMiscellaneousOvernightStaysTotalsg_mp__visits_by_day
2018-01-01Glacier NPGLACNational ParkIntermountainMT2018112222.01449,913...32,211,332118,373107,1560110,507109,56632,34901,17871
2018-02-01Glacier NPGLACNational ParkIntermountainMT2018211847.02448,261...32,211,332118,373107,1560110,507109,56632,34901,17861
2018-03-01Glacier NPGLACNational ParkIntermountainMT2018321758.01890,075...32,211,332118,373107,1560110,507109,56632,34901,178137
2018-04-01Glacier NPGLACNational ParkIntermountainMT2018428404.070120,797...32,211,332118,373107,1560110,507109,56632,34901,178168
2018-05-01Glacier NPGLACNational ParkIntermountainMT20185195116.03751,012,270...32,211,332118,373107,1560110,507109,56632,34901,1781072
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5 rows × 36 columns

\n", "
" ], "text/plain": [ " ParkName UnitCode ParkType Region State Year \\\n", "2018-01-01 Glacier NP GLAC National Park Intermountain MT 2018 \n", "2018-02-01 Glacier NP GLAC National Park Intermountain MT 2018 \n", "2018-03-01 Glacier NP GLAC National Park Intermountain MT 2018 \n", "2018-04-01 Glacier NP GLAC National Park Intermountain MT 2018 \n", "2018-05-01 Glacier NP GLAC National Park Intermountain MT 2018 \n", "\n", " Month RecreationVisits NonRecreationVisits RecreationHours ... \\\n", "2018-01-01 1 12222.0 14 49,913 ... \n", "2018-02-01 2 11847.0 24 48,261 ... \n", "2018-03-01 3 21758.0 18 90,075 ... \n", "2018-04-01 4 28404.0 70 120,797 ... \n", "2018-05-01 5 195116.0 375 1,012,270 ... \n", "\n", " RecreationHoursTotal NonRecreationHoursTotal \\\n", "2018-01-01 32,211,332 118,373 \n", "2018-02-01 32,211,332 118,373 \n", "2018-03-01 32,211,332 118,373 \n", "2018-04-01 32,211,332 118,373 \n", "2018-05-01 32,211,332 118,373 \n", "\n", " ConcessionerLodgingTotal ConcessionerCampingTotal TentCampersTotal \\\n", "2018-01-01 107,156 0 110,507 \n", "2018-02-01 107,156 0 110,507 \n", "2018-03-01 107,156 0 110,507 \n", "2018-04-01 107,156 0 110,507 \n", "2018-05-01 107,156 0 110,507 \n", "\n", " RVCampersTotal BackcountryTotal NonRecreationOvernightStaysTotal \\\n", "2018-01-01 109,566 32,349 0 \n", "2018-02-01 109,566 32,349 0 \n", "2018-03-01 109,566 32,349 0 \n", "2018-04-01 109,566 32,349 0 \n", "2018-05-01 109,566 32,349 0 \n", "\n", " MiscellaneousOvernightStaysTotal sg_mp__visits_by_day \n", "2018-01-01 1,178 71 \n", "2018-02-01 1,178 61 \n", "2018-03-01 1,178 137 \n", "2018-04-01 1,178 168 \n", "2018-05-01 1,178 1072 \n", "\n", "[5 rows x 36 columns]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "month_df = nps.set_index('date').join(park_month, how = 'inner') # Inner join by year-month column\n", "month_df['sg_mp__visits_by_day'] = pd.to_numeric(month_df['sg_mp__visits_by_day']) # convert to numeric\n", "month_df.head()" ] }, { "cell_type": "markdown", "id": "f3bedd60", "metadata": {}, "source": [ "#### 2.1 **Time series plot**: validate two datasets on the time dimension" ] }, { "cell_type": "code", "execution_count": 7, "id": "14c3ad27", "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "f, a = plt.subplots(figsize = (15, 8))\n", "month_df['sg_mp__visits_by_day'].plot(ax = a, color = 'mediumpurple', label = \"SafeGrpah\", lw = 3)\n", "plt.legend(loc = \"upper left\")\n", "a2 = a.twinx()\n", "month_df['RecreationVisits'].plot(ax = a2, linestyle = \"--\", alpha = .4, label = \"NPS data\", lw = 3)\n", "plt.legend(loc = \"upper right\")\n", "\n", "plt.legend()\n", "a.set(xlabel = \"Date\",\n", " ylabel = \"Monthly visitation estimated from SafeGrpah\",\n", " title = f\"Monthly visitation pattern SafeGraph vs. NPS data: GLAC\")\n", "a2.set(ylabel = \"NPS visitor use statistics\");" ] }, { "cell_type": "markdown", "id": "ed215428", "metadata": {}, "source": [ "In addition, calculate **Pearson correlation** between Safegraph and NPS monthly times series:" ] }, { "cell_type": "code", "execution_count": 8, "id": "99dca10f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The Pearson correlation between Safegraph and NPS data is 0.91.\n", "The Pearson correlation between first-differnced Safegraph and NPS data is 0.83.\n" ] } ], "source": [ "# calculate correlation\n", "corr = month_df['sg_mp__visits_by_day'].corr(month_df['RecreationVisits'])\n", "# calculate the correlation between first differnced time series\n", "corr_l1 = month_df[['sg_mp__visits_by_day', 'RecreationVisits']].diff().corr().iloc[0, 1]\n", "\n", "print(f'''The Pearson correlation between Safegraph and NPS data is {round(corr, 2)}.''')\n", "print(f'''The Pearson correlation between first-differnced Safegraph and NPS data is {round(corr_l1, 2)}.''')" ] }, { "cell_type": "markdown", "id": "cf2a6670", "metadata": {}, "source": [ "#### 2.2 **Density plot**: gauge the spatial dynamics of visitation derived from Safegraph over time" ] }, { "cell_type": "markdown", "id": "3190f157", "metadata": {}, "source": [ "Aggregate safegraph daily visitaiton to the POI-month level: by `'placekey'`(an indicator for POI) and`'date_range_start'`(column for month):" ] }, { "cell_type": "code", "execution_count": 9, "id": "e64f0383", "metadata": {}, "outputs": [], "source": [ "poi_month = subset_gdf.groupby(['placekey', 'date_range_start'])['sg_mp__visits_by_day'].sum().to_frame()" ] }, { "cell_type": "markdown", "id": "06412549", "metadata": {}, "source": [ "Extract geo-coordinates of each POI and merge to the newly created `poi_month`:" ] }, { "cell_type": "code", "execution_count": 10, "id": "3baadbdf", "metadata": {}, "outputs": [], "source": [ "lon_lat = subset_gdf[['placekey', 'geometry']].drop_duplicates().set_index('placekey')\n", "poi_month = poi_month.join(lon_lat, how = 'left').sort_values(by = \"date_range_start\") # merge & sort by date\n", "\n", "# Convert the dataframe to geodataframe:\n", "poi_month_gdf = gpd.GeoDataFrame(poi_month, \n", " crs = \"EPSG:4269\", \n", " geometry = poi_month.geometry)" ] }, { "cell_type": "markdown", "id": "5ad74485", "metadata": {}, "source": [ "For density plot, we focus on __peak visitation season (May to Oct)__. Here we select months to generate the density plot: " ] }, { "cell_type": "code", "execution_count": 11, "id": "fc6ec6c4", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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placekeydate_range_startsg_mp__visits_by_daygeometry
31zzy-225@3wy-prx-td92018-05-0155POINT (-113.87915 48.61743)
32zzy-222@3wy-q29-8vz2018-05-01315POINT (-113.99403 48.52759)
33zzy-226@3wy-prx-td92018-05-0138POINT (-113.87918 48.61740)
34zzw-222@3wy-q29-d9z2018-05-01279POINT (-113.99294 48.52874)
35zzy-224@3wy-prx-td92018-05-0125POINT (-113.87916 48.61739)
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" ], "text/plain": [ " placekey date_range_start sg_mp__visits_by_day \\\n", "31 zzy-225@3wy-prx-td9 2018-05-01 55 \n", "32 zzy-222@3wy-q29-8vz 2018-05-01 315 \n", "33 zzy-226@3wy-prx-td9 2018-05-01 38 \n", "34 zzw-222@3wy-q29-d9z 2018-05-01 279 \n", "35 zzy-224@3wy-prx-td9 2018-05-01 25 \n", "\n", " geometry \n", "31 POINT (-113.87915 48.61743) \n", "32 POINT (-113.99403 48.52759) \n", "33 POINT (-113.87918 48.61740) \n", "34 POINT (-113.99294 48.52874) \n", "35 POINT (-113.87916 48.61739) " ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "temp = poi_month_gdf.reset_index()\n", "temp = temp[temp['date_range_start'].dt.month.isin(range(5,10))]\n", "temp.head()" ] }, { "cell_type": "markdown", "id": "7750dda9", "metadata": {}, "source": [ "Density plot of monthly visits to Safegraph POIs overlayed with the Glacier boundary:" ] }, { "cell_type": "code", "execution_count": 12, "id": "5215f2de", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\simizicee\\AppData\\Local\\Temp\\ipykernel_37232\\3215083758.py:1: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", "\n", " proj = geoplot.crs.AlbersEqualArea(central_latitude = boundary[boundary.index == 'GLAC'].centroid.y[0],\n", "C:\\Users\\simizicee\\AppData\\Local\\Temp\\ipykernel_37232\\3215083758.py:2: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", "\n", " central_longitude = boundary[boundary.index == 'GLAC'].centroid.x[0])\n" ] }, { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "proj = geoplot.crs.AlbersEqualArea(central_latitude = boundary[boundary.index == 'GLAC'].centroid.y[0], \n", " central_longitude = boundary[boundary.index == 'GLAC'].centroid.x[0])\n", "months = temp['date_range_start'].unique()\n", "\n", "plt.figure(figsize = (20, 20))\n", "\n", "for idx, month in enumerate(months):\n", "\n", " ax = plt.subplot(4, 5, idx + 1, projection = proj)\n", " geoplot.kdeplot(temp[temp['date_range_start'] == month], \n", " # clip = boundary[boundary.index == 'GLAC'].geometry,\n", " shade = True, \n", " cmap = 'Reds', \n", " #thresh = 0.2, \n", " levels = 10,\n", " alpha = 0.8, \n", " projection = proj,\n", " #cbar = True,\n", " vmin = 0, \n", " #vmax = 309,\n", " ax = ax)\n", " geoplot.polyplot(boundary[boundary.index == 'GLAC'], ax = ax, zorder = 1)\n", " ax.set_title(month.astype('datetime64[M]')) # convert to year-month" ] }, { "cell_type": "markdown", "id": "00f411e5", "metadata": {}, "source": [ "### 3. Road network analysis\n", "- Input: \n", " - GeoJSON file that contains POIs found within the Glacier park boundary (`GeoJSON`)\n", " - Park boundary (`nps_boundary.shp`)\n", " - Geo-locations of park's entrance stations(`entrance_coord.csv`)\n", "- Tasks: temporal aggregation, merging\n", "- Results: \n", " - A time series plot comparing two data sources\n", " - A density plot to gauge the spatial dynamics" ] }, { "cell_type": "code", "execution_count": 13, "id": "31fbd39c", "metadata": {}, "outputs": [], "source": [ "from IPython.display import Image\n", "from IPython.display import HTML" ] }, { "cell_type": "markdown", "id": "2e54a929", "metadata": {}, "source": [ "Load entrance station locations:" ] }, { "cell_type": "code", "execution_count": 14, "id": "d9bd1799", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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unitCodeentrancelat_lonlatlongeometry
0GLACWest Entrance48.50642809317048, -113.987646266843548.50642809317048-113.9876462668435POINT (-113.98765 48.50643)
1GLACCamas48.58720431401561, -114.0331353757808748.58720431401561-114.03313537578087POINT (-114.03314 48.58720)
2GLACPolebridge48.78354575523783, -114.2805605171685548.78354575523783-114.28056051716855POINT (-114.28056 48.78355)
3GLACMany Glacier48.82248401654224, -113.5797412713674148.82248401654224-113.57974127136741POINT (-113.57974 48.82248)
4GLACSaint Mary's48.74693105028238, -113.4393334060942448.74693105028238-113.43933340609424POINT (-113.43933 48.74693)
5GLACTwo Medicine48.50504411336611, -113.3300049360015348.50504411336611-113.33000493600153POINT (-113.33000 48.50504)
6GLACWalton/Goat Lick48.25888956992005, -113.5750995022912548.25888956992005-113.57509950229125POINT (-113.57510 48.25889)
\n", "
" ], "text/plain": [ " unitCode entrance lat_lon \\\n", "0 GLAC West Entrance 48.50642809317048, -113.9876462668435 \n", "1 GLAC Camas 48.58720431401561, -114.03313537578087 \n", "2 GLAC Polebridge 48.78354575523783, -114.28056051716855 \n", "3 GLAC Many Glacier 48.82248401654224, -113.57974127136741 \n", "4 GLAC Saint Mary's 48.74693105028238, -113.43933340609424 \n", "5 GLAC Two Medicine 48.50504411336611, -113.33000493600153 \n", "6 GLAC Walton/Goat Lick 48.25888956992005, -113.57509950229125 \n", "\n", " lat lon geometry \n", "0 48.50642809317048 -113.9876462668435 POINT (-113.98765 48.50643) \n", "1 48.58720431401561 -114.03313537578087 POINT (-114.03314 48.58720) \n", "2 48.78354575523783 -114.28056051716855 POINT (-114.28056 48.78355) \n", "3 48.82248401654224 -113.57974127136741 POINT (-113.57974 48.82248) \n", "4 48.74693105028238 -113.43933340609424 POINT (-113.43933 48.74693) \n", "5 48.50504411336611 -113.33000493600153 POINT (-113.33000 48.50504) \n", "6 48.25888956992005 -113.57509950229125 POINT (-113.57510 48.25889) " ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "entry = pd.read_csv(f'./data/entrance_coord.csv')\n", "\n", "# split by \",\" to create lontitude and latitude columns\n", "lat = []\n", "lon = []\n", "\n", "for row in entry['lat_lon']:\n", " lat.append(row.split(',')[0]) # Split the row by comma and append\n", " lon.append(row.split(',')[1])\n", " \n", "# Create two new columns from lat and lon\n", "entry['lat'] = lat\n", "entry['lon'] = lon\n", "\n", "# convert to geodataframe\n", "entry_gdf = gpd.GeoDataFrame(entry, \n", " crs = \"EPSG:4269\",\n", " geometry = gpd.points_from_xy(entry.lon, entry.lat))\n", "\n", "# filter the entrance stations for Glacier\n", "entry_gdf = entry_gdf[entry_gdf.unitCode == 'GLAC'].reset_index(drop = True) \n", "entry_gdf" ] }, { "cell_type": "markdown", "id": "9079f799", "metadata": {}, "source": [ "(1) For parks with convex shape (Glacier, Yellowstone, Smokies), it's ideal to create a buffer around the park boudary and use this buffer to query osm road network." ] }, { "cell_type": "code", "execution_count": 15, "id": "445e5342", "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "(
, )" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# To create buffer, need to first project to UTM (unit: meters)\n", "buff = boundary.loc[['GLAC']].to_crs(epsg = 26912).buffer(8000) # For Glacier: NAD83 / UTM zone 12N\n", "buff = gpd.GeoDataFrame(geometry = gpd.GeoSeries(buff))\n", "\n", "# create network from that buffer\n", "G = ox.graph_from_polygon(buff.to_crs(epsg = 4326).geometry[0], network_type = 'drive', simplify = True)\n", "G = ox.project_graph(G, to_crs = 'epsg:4269') # Reproject\n", "ox.plot_graph(G)" ] }, { "cell_type": "markdown", "id": "5ad28571", "metadata": {}, "source": [ "(2) For parks with concave shape (Zion and Acadia), better to use the bounding box instead of a buffer." ] }, { "cell_type": "code", "execution_count": 16, "id": "10481e3c", "metadata": {}, "outputs": [], "source": [ "# # create bounding box based on park boundary\n", "# bound = boundary.loc[[park]].total_bounds \n", "# # Specify the coordinates of four bounds\n", "# north, south, east, west = bound[3], bound[1], bound[2], bound[0]\n", "# # create network from that bounding box\n", "# G = ox.graph_from_bbox(north, south, east, west, network_type = 'drive', simplify = True)\n", "# ox.plot_graph(G)" ] }, { "cell_type": "markdown", "id": "be012cef", "metadata": {}, "source": [ "Convert the OSM road network to GeoPandas GeoDataFrame:" ] }, { "cell_type": "code", "execution_count": 17, "id": "d5eb312f", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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osmidnamehighwayonewaylengthgeometrylanesrefmaxspeedbridgetunnel
uvkey
406568014085341405719884Lodgepole LoopresidentialFalse18.957LINESTRING (-113.43446 48.26584, -113.43420 48...NaNNaNNaNNaNNaN
4065681005533468NaNresidentialFalse257.073LINESTRING (-113.43446 48.26584, -113.43491 48...NaNNaNNaNNaNNaN
408853230[5719884, 5549846][Slippery Bill Road, Lodgepole Loop]residentialFalse248.138LINESTRING (-113.43446 48.26584, -113.43454 48...NaNNaNNaNNaNNaN
408534144065680105719884Lodgepole LoopresidentialFalse18.957LINESTRING (-113.43420 48.26584, -113.43446 48...NaNNaNNaNNaNNaN
4085351205546392NaNresidentialFalse426.384LINESTRING (-113.43420 48.26584, -113.43422 48...NaNNaNNaNNaNNaN
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" ], "text/plain": [ " osmid \\\n", "u v key \n", "40656801 40853414 0 5719884 \n", " 40656810 0 5533468 \n", " 40885323 0 [5719884, 5549846] \n", "40853414 40656801 0 5719884 \n", " 40853512 0 5546392 \n", "\n", " name highway \\\n", "u v key \n", "40656801 40853414 0 Lodgepole Loop residential \n", " 40656810 0 NaN residential \n", " 40885323 0 [Slippery Bill Road, Lodgepole Loop] residential \n", "40853414 40656801 0 Lodgepole Loop residential \n", " 40853512 0 NaN residential \n", "\n", " oneway length \\\n", "u v key \n", "40656801 40853414 0 False 18.957 \n", " 40656810 0 False 257.073 \n", " 40885323 0 False 248.138 \n", "40853414 40656801 0 False 18.957 \n", " 40853512 0 False 426.384 \n", "\n", " geometry \\\n", "u v key \n", "40656801 40853414 0 LINESTRING (-113.43446 48.26584, -113.43420 48... \n", " 40656810 0 LINESTRING (-113.43446 48.26584, -113.43491 48... \n", " 40885323 0 LINESTRING (-113.43446 48.26584, -113.43454 48... \n", "40853414 40656801 0 LINESTRING (-113.43420 48.26584, -113.43446 48... \n", " 40853512 0 LINESTRING (-113.43420 48.26584, -113.43422 48... \n", "\n", " lanes ref maxspeed bridge tunnel \n", "u v key \n", "40656801 40853414 0 NaN NaN NaN NaN NaN \n", " 40656810 0 NaN NaN NaN NaN NaN \n", " 40885323 0 NaN NaN NaN NaN NaN \n", "40853414 40656801 0 NaN NaN NaN NaN NaN \n", " 40853512 0 NaN NaN NaN NaN NaN " ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "nodes, edges = ox.graph_to_gdfs(G, nodes = True, edges = True, node_geometry = True)\n", "edges.head()" ] }, { "cell_type": "markdown", "id": "ee7ee74f", "metadata": {}, "source": [ "Choose a date that we would like to generate maps for. At the end of the day, we would like to compare the congestion conditions between the same time period of different years, such as the first Friday of August in 2018 vs. 2020." ] }, { "cell_type": "code", "execution_count": 18, "id": "031e0b20", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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placekeydatesg_c__location_namegeometrysg_mp__visits_by_day
0zzy-222@3wy-prx-xwk2018-08-02Jammer Joe's Grill and PizzeriaPOINT (-113.87642 48.61768)8
1zzw-222@3wy-q29-d9z2018-08-02Glacier Park Boat CompanyPOINT (-113.99294 48.52874)25
2zzy-222@3wy-pbb-bx52018-08-02Flathead Lake Biological StationPOINT (-113.98850 48.52306)0
3222-222@3wy-q23-b8v2018-08-02Glacier National ParkPOINT (-113.98663 48.50239)6
4222-222@3wy-q29-8y92018-08-02Schoolhouse GiftsPOINT (-113.99352 48.52658)7
5zzy-224@3wy-prx-td92018-08-02Lake Mcdonald Lodge and CabinsPOINT (-113.87916 48.61739)1
6zzy-223@3wy-q29-jjv2018-08-02Eddie's Cafe and GiftsPOINT (-113.98852 48.52305)0
7zzy-222@3wy-q29-8vz2018-08-02Lake McDonaldPOINT (-113.99403 48.52759)24
8zzw-222@3wy-m9q-mc52018-08-02Ptarmigan RoomPOINT (-113.36454 48.49155)0
9zzy-225@3wy-prx-td92018-08-02Lucke's LoungePOINT (-113.87915 48.61743)2
10zzy-226@3wy-prx-td92018-08-02Lake McDonald LodgePOINT (-113.87918 48.61740)3
11zzy-222@3wy-t6w-4352018-08-02Glacier ParkPOINT (-113.67304 48.79710)0
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" ], "text/plain": [ " placekey date sg_c__location_name \\\n", "0 zzy-222@3wy-prx-xwk 2018-08-02 Jammer Joe's Grill and Pizzeria \n", "1 zzw-222@3wy-q29-d9z 2018-08-02 Glacier Park Boat Company \n", "2 zzy-222@3wy-pbb-bx5 2018-08-02 Flathead Lake Biological Station \n", "3 222-222@3wy-q23-b8v 2018-08-02 Glacier National Park \n", "4 222-222@3wy-q29-8y9 2018-08-02 Schoolhouse Gifts \n", "5 zzy-224@3wy-prx-td9 2018-08-02 Lake Mcdonald Lodge and Cabins \n", "6 zzy-223@3wy-q29-jjv 2018-08-02 Eddie's Cafe and Gifts \n", "7 zzy-222@3wy-q29-8vz 2018-08-02 Lake McDonald \n", "8 zzw-222@3wy-m9q-mc5 2018-08-02 Ptarmigan Room \n", "9 zzy-225@3wy-prx-td9 2018-08-02 Lucke's Lounge \n", "10 zzy-226@3wy-prx-td9 2018-08-02 Lake McDonald Lodge \n", "11 zzy-222@3wy-t6w-435 2018-08-02 Glacier Park \n", "\n", " geometry sg_mp__visits_by_day \n", "0 POINT (-113.87642 48.61768) 8 \n", "1 POINT (-113.99294 48.52874) 25 \n", "2 POINT (-113.98850 48.52306) 0 \n", "3 POINT (-113.98663 48.50239) 6 \n", "4 POINT (-113.99352 48.52658) 7 \n", "5 POINT (-113.87916 48.61739) 1 \n", "6 POINT (-113.98852 48.52305) 0 \n", "7 POINT (-113.99403 48.52759) 24 \n", "8 POINT (-113.36454 48.49155) 0 \n", "9 POINT (-113.87915 48.61743) 2 \n", "10 POINT (-113.87918 48.61740) 3 \n", "11 POINT (-113.67304 48.79710) 0 " ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "day = '2018-08-02'\n", "\n", "# change variable type\n", "subset_gdf['date'] = pd.DatetimeIndex(subset_gdf.date) # convert string to datetime\n", "subset_gdf['sg_mp__visits_by_day'] = pd.to_numeric(subset_gdf['sg_mp__visits_by_day']) # convert to numeric\n", "\n", "# filter data by the chosen date\n", "poi_gdf = subset_gdf.loc[subset_gdf['date'] == day, \n", " ['placekey', 'date', 'sg_c__location_name', 'geometry', 'sg_mp__visits_by_day']].reset_index(drop = True)\n", "poi_gdf" ] }, { "cell_type": "markdown", "id": "8eede460", "metadata": {}, "source": [ "Plot entrance stations and POIs together with the park road network:" ] }, { "cell_type": "code", "execution_count": 19, "id": "5241d8fe", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Make this Notebook Trusted to load map: File -> Trust Notebook
" ], "text/plain": [ "" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "m = edges[edges.highway == 'secondary'].explore()\n", "poi_gdf.drop(['date'], axis = 1).explore(m = m, \n", " column = 'sg_mp__visits_by_day', \n", " cmap = \"RdBu_r\",\n", " marker_type = 'circle',\n", " marker_kwds = {'radius': 1000,\n", " 'fill': True\n", " }\n", " ) # POIs\n", "entry_gdf.explore(m = m, \n", " marker_type = 'marker'\n", " ) # entrances" ] }, { "cell_type": "code", "execution_count": 20, "id": "b657e597", "metadata": {}, "outputs": [], "source": [ "# A function helps you to find the nearest OSM node from a given GeoDataFrame (cr. Dr.Park)\n", "def find_nearest_osm(network, gdf):\n", " \"\"\"\n", " # This function helps you to find the nearest OSM node from a given GeoDataFrame\n", " # If geom type is point, it will take it without modification, but \n", " # IF geom type is polygon or multipolygon, it will take its centroid to calculate the nearest element. \n", " \n", " Input: \n", " - network (NetworkX MultiDiGraph): Network Dataset obtained from OSMnx\n", " - gdf (GeoDataFrame): stores locations in its `geometry` column \n", " \n", " Output:\n", " - gdf (GeoDataFrame): will have `nearest_osm` column, which describes the nearest OSM node \n", " that was computed based on its geometry column\n", " \n", " \"\"\"\n", " for idx, row in tqdm(gdf.iterrows(), total=gdf.shape[0]):\n", " if row.geometry.geom_type == 'Point':\n", " nearest_osm = ox.distance.nearest_nodes(network, \n", " X=row.geometry.x, \n", " Y=row.geometry.y\n", " )\n", " elif row.geometry.geom_type == 'Polygon' or row.geometry.geom_type == 'MultiPolygon':\n", " nearest_osm = ox.distance.nearest_nodes(network, \n", " X=row.geometry.centroid.x, \n", " Y=row.geometry.centroid.y\n", " )\n", " else:\n", " print(row.geometry.geom_type)\n", " continue\n", "\n", " gdf.at[idx, 'nearest_osm'] = nearest_osm\n", "\n", " return gdf" ] }, { "cell_type": "markdown", "id": "e50cee47", "metadata": {}, "source": [ "Find the nearest OSM node for each POI within the park:" ] }, { "cell_type": "code", "execution_count": 21, "id": "d05f934c", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████████████████████████████████████████████████████████████████████████████| 12/12 [00:00<00:00, 94.72it/s]\n" ] }, { "data": { "text/html": [ "
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placekeydatesg_c__location_namegeometrysg_mp__visits_by_daynearest_osm
0zzy-222@3wy-prx-xwk2018-08-02Jammer Joe's Grill and PizzeriaPOINT (-113.87642 48.61768)8960036734.0
1zzw-222@3wy-q29-d9z2018-08-02Glacier Park Boat CompanyPOINT (-113.99294 48.52874)25960035394.0
2zzy-222@3wy-pbb-bx52018-08-02Flathead Lake Biological StationPOINT (-113.98850 48.52306)041049461.0
3222-222@3wy-q23-b8v2018-08-02Glacier National ParkPOINT (-113.98663 48.50239)6960035763.0
4222-222@3wy-q29-8y92018-08-02Schoolhouse GiftsPOINT (-113.99352 48.52658)7960036264.0
5zzy-224@3wy-prx-td92018-08-02Lake Mcdonald Lodge and CabinsPOINT (-113.87916 48.61739)1960033938.0
6zzy-223@3wy-q29-jjv2018-08-02Eddie's Cafe and GiftsPOINT (-113.98852 48.52305)041049461.0
7zzy-222@3wy-q29-8vz2018-08-02Lake McDonaldPOINT (-113.99403 48.52759)24960036264.0
8zzw-222@3wy-m9q-mc52018-08-02Ptarmigan RoomPOINT (-113.36454 48.49155)0960034402.0
9zzy-225@3wy-prx-td92018-08-02Lucke's LoungePOINT (-113.87915 48.61743)2960033938.0
10zzy-226@3wy-prx-td92018-08-02Lake McDonald LodgePOINT (-113.87918 48.61740)3960033938.0
11zzy-222@3wy-t6w-4352018-08-02Glacier ParkPOINT (-113.67304 48.79710)0960035071.0
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" ], "text/plain": [ " placekey date sg_c__location_name \\\n", "0 zzy-222@3wy-prx-xwk 2018-08-02 Jammer Joe's Grill and Pizzeria \n", "1 zzw-222@3wy-q29-d9z 2018-08-02 Glacier Park Boat Company \n", "2 zzy-222@3wy-pbb-bx5 2018-08-02 Flathead Lake Biological Station \n", "3 222-222@3wy-q23-b8v 2018-08-02 Glacier National Park \n", "4 222-222@3wy-q29-8y9 2018-08-02 Schoolhouse Gifts \n", "5 zzy-224@3wy-prx-td9 2018-08-02 Lake Mcdonald Lodge and Cabins \n", "6 zzy-223@3wy-q29-jjv 2018-08-02 Eddie's Cafe and Gifts \n", "7 zzy-222@3wy-q29-8vz 2018-08-02 Lake McDonald \n", "8 zzw-222@3wy-m9q-mc5 2018-08-02 Ptarmigan Room \n", "9 zzy-225@3wy-prx-td9 2018-08-02 Lucke's Lounge \n", "10 zzy-226@3wy-prx-td9 2018-08-02 Lake McDonald Lodge \n", "11 zzy-222@3wy-t6w-435 2018-08-02 Glacier Park \n", "\n", " geometry sg_mp__visits_by_day nearest_osm \n", "0 POINT (-113.87642 48.61768) 8 960036734.0 \n", "1 POINT (-113.99294 48.52874) 25 960035394.0 \n", "2 POINT (-113.98850 48.52306) 0 41049461.0 \n", "3 POINT (-113.98663 48.50239) 6 960035763.0 \n", "4 POINT (-113.99352 48.52658) 7 960036264.0 \n", "5 POINT (-113.87916 48.61739) 1 960033938.0 \n", "6 POINT (-113.98852 48.52305) 0 41049461.0 \n", "7 POINT (-113.99403 48.52759) 24 960036264.0 \n", "8 POINT (-113.36454 48.49155) 0 960034402.0 \n", "9 POINT (-113.87915 48.61743) 2 960033938.0 \n", "10 POINT (-113.87918 48.61740) 3 960033938.0 \n", "11 POINT (-113.67304 48.79710) 0 960035071.0 " ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "poi_gdf = find_nearest_osm(G, poi_gdf)\n", "poi_gdf" ] }, { "cell_type": "markdown", "id": "3f93659e", "metadata": {}, "source": [ "Similarly, find the nearest OSM node for each entrance station:" ] }, { "cell_type": "code", "execution_count": 22, "id": "f6b7d7e3", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "100%|███████████████████████████████████████████████████████████████████████████████████| 7/7 [00:00<00:00, 113.20it/s]\n" ] }, { "data": { "text/html": [ "
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unitCodeentrancelat_lonlatlongeometrynearest_osm
0GLACWest Entrance48.50642809317048, -113.987646266843548.50642809317048-113.9876462668435POINT (-113.98765 48.50643)43157459.0
1GLACCamas48.58720431401561, -114.0331353757808748.58720431401561-114.03313537578087POINT (-114.03314 48.58720)957706395.0
2GLACPolebridge48.78354575523783, -114.2805605171685548.78354575523783-114.28056051716855POINT (-114.28056 48.78355)960034730.0
3GLACMany Glacier48.82248401654224, -113.5797412713674148.82248401654224-113.57974127136741POINT (-113.57974 48.82248)960037666.0
4GLACSaint Mary's48.74693105028238, -113.4393334060942448.74693105028238-113.43933340609424POINT (-113.43933 48.74693)41052104.0
5GLACTwo Medicine48.50504411336611, -113.3300049360015348.50504411336611-113.33000493600153POINT (-113.33000 48.50504)970994448.0
6GLACWalton/Goat Lick48.25888956992005, -113.5750995022912548.25888956992005-113.57509950229125POINT (-113.57510 48.25889)960035238.0
\n", "
" ], "text/plain": [ " unitCode entrance lat_lon \\\n", "0 GLAC West Entrance 48.50642809317048, -113.9876462668435 \n", "1 GLAC Camas 48.58720431401561, -114.03313537578087 \n", "2 GLAC Polebridge 48.78354575523783, -114.28056051716855 \n", "3 GLAC Many Glacier 48.82248401654224, -113.57974127136741 \n", "4 GLAC Saint Mary's 48.74693105028238, -113.43933340609424 \n", "5 GLAC Two Medicine 48.50504411336611, -113.33000493600153 \n", "6 GLAC Walton/Goat Lick 48.25888956992005, -113.57509950229125 \n", "\n", " lat lon geometry \\\n", "0 48.50642809317048 -113.9876462668435 POINT (-113.98765 48.50643) \n", "1 48.58720431401561 -114.03313537578087 POINT (-114.03314 48.58720) \n", "2 48.78354575523783 -114.28056051716855 POINT (-114.28056 48.78355) \n", "3 48.82248401654224 -113.57974127136741 POINT (-113.57974 48.82248) \n", "4 48.74693105028238 -113.43933340609424 POINT (-113.43933 48.74693) \n", "5 48.50504411336611 -113.33000493600153 POINT (-113.33000 48.50504) \n", "6 48.25888956992005 -113.57509950229125 POINT (-113.57510 48.25889) \n", "\n", " nearest_osm \n", "0 43157459.0 \n", "1 957706395.0 \n", "2 960034730.0 \n", "3 960037666.0 \n", "4 41052104.0 \n", "5 970994448.0 \n", "6 960035238.0 " ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "entry_gdf = find_nearest_osm(G, entry_gdf)\n", "entry_gdf" ] }, { "cell_type": "markdown", "id": "d9c771fe", "metadata": {}, "source": [ "#### Calculate the times that each edges has been passed through by visitors _on that day_:" ] }, { "cell_type": "code", "execution_count": 23, "id": "c194d29f", "metadata": {}, "outputs": [], "source": [ "edges['travel_times'] = 0\n", "\n", "for idx_p, row_p in poi_gdf.iterrows(): # loop for each POI\n", " \n", " length = []\n", " \n", " for idx_e, row_e in entry_gdf.iterrows(): # Loop for each entrance station\n", " \n", " # Calculate the shortest driving distance from every entrance station to a specific POI\n", " temp_length = nx.shortest_path_length(G = G, \n", " source = row_e['nearest_osm'], \n", " target = row_p['nearest_osm'], \n", " weight = 'length',\n", " method = 'dijkstra'\n", " )\n", " length.append(temp_length)\n", " \n", " # Find the nearest entrance station from that POI\n", " val, idx = min((val, idx) for (idx, val) in enumerate(length)) # get the position in the list with smallest number\n", " \n", " # Get shortest paths from the nearest entrances to that POI. Visitors are assumed to take this route to enter the park.\n", " start_route = nx.shortest_path(G = G, \n", " source = entry_gdf.loc[idx, 'nearest_osm'], \n", " target = row_p['nearest_osm'], \n", " weight = 'length',\n", " method = 'dijkstra'\n", " )\n", " \n", " for i in range(len(start_route) - 1):\n", " cum_sum = edges.loc[(edges.index.get_level_values('u') == start_route[i]) & (edges.index.get_level_values('v') == start_route[i+1]), 'travel_times'] + row_p['sg_mp__visits_by_day']\n", " edges.loc[(edges.index.get_level_values('u') == start_route[i]) & (edges.index.get_level_values('v') == start_route[i+1]), 'travel_times'] = cum_sum\n", " \n", " # Get shortest paths from the that POI to the nearest entrances. Visitors are assumed to take this route to exit the park.\n", " back_route = nx.shortest_path(G = G, \n", " source = row_p['nearest_osm'], \n", " target = entry_gdf.loc[idx, 'nearest_osm'], \n", " weight = 'length',\n", " method = 'dijkstra'\n", " )\n", " \n", " for i in range(len(back_route) - 1):\n", " cum_sum = edges.loc[(edges.index.get_level_values('u') == back_route[i]) & (edges.index.get_level_values('v') == back_route[i+1]), 'travel_times'] + row_p['sg_mp__visits_by_day']\n", " edges.loc[(edges.index.get_level_values('u') == back_route[i]) & (edges.index.get_level_values('v') == back_route[i+1]), 'travel_times'] = cum_sum" ] }, { "cell_type": "code", "execution_count": 24, "id": "88b208b5", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "count 2519.000000\n", "mean 0.344581\n", "std 4.246239\n", "min 0.000000\n", "25% 0.000000\n", "50% 0.000000\n", "75% 0.000000\n", "max 70.000000\n", "Name: travel_times, dtype: float64" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# A preview of the summary statistiscs\n", "edges.travel_times.describe() " ] }, { "cell_type": "markdown", "id": "ea03db9f", "metadata": {}, "source": [ "#### Now we are ready to visualize the congestion conditions: color code edges using Red/Yellow/Green palettes, based on the number of visitors who may pass through each road segment." ] }, { "cell_type": "code", "execution_count": 25, "id": "c58de81a", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Make this Notebook Trusted to load map: File -> Trust Notebook
" ], "text/plain": [ "" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "m = edges.explore(tiles = 'Stamen Terrain',\n", " column = 'travel_times', \n", " cmap = 'RdYlGn_r',\n", " scheme = 'NaturalBreaks',\n", " k = 5,\n", " vmin = 0,\n", " highlight = True,\n", " tooltip = ['name', 'travel_times'], # displayed upon hovering\n", " popup = True, # all columns displayed upon clicking\n", " legend_kwds = {\n", " 'caption': 'Congestion',\n", " 'scale': False,\n", " 'colorbar': False\n", " }\n", " )\n", "entry_gdf.explore(m = m, \n", " marker_type = 'marker',\n", " tooltip = ['entrance']\n", " ) # entrances" ] } ], "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": "3.8.12" } }, "nbformat": 4, "nbformat_minor": 5 }