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UC 2017 Tech Sessions and Demo Theater sessions
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‎talks/uc2017/Mapping, Visualization, and Analysis Using ArcGIS API for Python/constructing_drive_time_based_service_areas.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Constructing drive time based service areas\n",
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"This sample shows how the `network` module of the ArcGIS API for Python can be used to construct service areas. In this sample, we generate service areas for two of the fire stations in central Tokyo, Japan. We later observe how the service area varies by time of day for a fire station in the city of Los Angeles."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"heading_collapsed": true
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},
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"source": [
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"### Service areas\n",
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"A network service area is a region that encompasses all accessible streets (that is, streets that are within a specified impedance). For instance, the 5-minute service area for a point on a network includes all the streets that can be reached within five minutes from that point.\n",
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"\n",
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"Service areas also help evaluate accessibility. Concentric service areas show how accessibility varies. Once service areas are created, you can use them to identify how much land, how many people, or how much of anything else is within the neighborhood or region.\n",
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"\n",
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"![](http://desktop.arcgis.com/en/arcmap/latest/extensions/network-analyst/GUID-0166E6A5-CDEC-4A03-A022-F4A6EB7F9EAD-web.png)\n",
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"\n",
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"Service area solver provides functionality for finding out how far a vehicle could go within a specified time or distance limit. \n",
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"\n",
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"## Connect to the GIS\n",
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"Establish a connection to your organization which could be an ArcGIS Online organization or an ArcGIS Enterprise. To be able to run the code in this sample notebook, you would need to provide credentials of a user within an ArcGIS Online organization."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"hidden": true
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},
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"outputs": [],
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"source": [
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"from datetime import datetime\n",
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"from IPython.display import HTML\n",
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"import pandas as pd\n",
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"from arcgis.gis import GIS\n",
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"\n",
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"user_name = 'arcgis_python'\n",
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"password = 'P@ssword123'\n",
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"my_gis = GIS('https://www.arcgis.com', user_name, password)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"heading_collapsed": true
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},
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"source": [
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"### Create a Network Layer"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"hidden": true
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},
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"outputs": [],
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"source": [
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"import arcgis.network as network"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"hidden": true
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},
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"outputs": [],
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"source": [
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"service_area_url = my_gis.properties.helperServices.serviceArea.url\n",
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"service_area_url"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"hidden": true
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},
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"outputs": [],
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"source": [
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"sa_layer = network.ServiceAreaLayer(service_area_url, gis=my_gis)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"heading_collapsed": true
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},
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"source": [
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"## Create fire station facility layer"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"hidden": true
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},
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"source": [
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"We obtained the coordinates of two fire stations in Tokyo. We construct `Feature` and `FeatureSet` objects to represent them."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"hidden": true
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},
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"outputs": [],
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"source": [
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"fire_station_1_coord = '139.546910,35.695729'\n",
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"fire_station_2_coord = '139.673726,35.697988'\n",
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"\n",
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"from arcgis.features import Feature, FeatureSet\n",
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"\n",
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"f1 = Feature(geometry={'x':float(fire_station_1_coord.split(',')[0]),\n",
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" 'y':float(fire_station_1_coord.split(',')[1])})\n",
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"\n",
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"f2 = Feature(geometry={'x':float(fire_station_2_coord.split(',')[0]),\n",
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" 'y':float(fire_station_2_coord.split(',')[1])})\n",
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"\n",
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"fire_station_fset = FeatureSet([f1,f2], geometry_type='esriGeometryPoint', \n",
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" spatial_reference={'latestWkid': 4326})"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"hidden": true
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},
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"source": [
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"Let us display the fire stations on a map"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"hidden": true
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},
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"outputs": [],
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"source": [
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"map1 = my_gis.map('Tokyo', zoomlevel=12)\n",
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"map1"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"hidden": true
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},
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"outputs": [],
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"source": [
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"fire_truck_symbol = {\"type\":\"esriPMS\",\n",
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" \"url\":\"http://static.arcgis.com/images/Symbols/SafetyHealth/FireTruck.png\",\n",
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" \"contentType\": \"image/png\", \"width\":20, \"height\":20}\n",
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"\n",
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"map1.draw(fire_station_fset, symbol=fire_truck_symbol)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"heading_collapsed": true
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},
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"source": [
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"## Compute the service area"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"hidden": true
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},
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"outputs": [],
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"source": [
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"travel_modes = sa_layer.retrieve_travel_modes()\n",
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"truck_mode = [t for t in travel_modes['supportedTravelModes'] if t['name'] == 'Trucking Time'][0]\n",
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"\n",
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"result = sa_layer.solve_service_area(fire_station_fset, default_breaks=[5,10,15], \n",
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" travel_direction='esriNATravelDirectionFromFacility',\n",
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" travel_mode=truck_mode)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"hidden": true
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},
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"source": [
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"#### Read the result back as a `FeatureSet`\n",
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"The `result` variable contains the service area as a dictionary. We inspect its keys and construct `Feature` and `FeatureSet` objects out of it to display in the map"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"hidden": true
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},
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"outputs": [],
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"source": [
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"result.keys()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"hidden": true
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},
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"outputs": [],
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"source": [
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"result['saPolygons'].keys()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"hidden": true
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},
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"outputs": [],
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"source": [
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"poly_feat_list = []\n",
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"for polygon_dict in result['saPolygons']['features']:\n",
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" f1 = Feature(polygon_dict['geometry'], polygon_dict['attributes'])\n",
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" poly_feat_list.append(f1)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"hidden": true
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},
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"outputs": [],
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"source": [
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"service_area_fset = FeatureSet(poly_feat_list, \n",
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" geometry_type=result['saPolygons']['geometryType'],\n",
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" spatial_reference= result['saPolygons']['spatialReference'])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"hidden": true
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},
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"source": [
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"Let us inspect the service area as a Pandas `DataFrame` to understand the attribute information"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"hidden": true
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},
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"outputs": [],
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"source": [
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"service_area_fset.df"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"hidden": true
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},
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"source": [
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"### Visualize the service area on the map\n",
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"From the DataFrame above, we know, there are 3 service area polygons for each fire station. The drive times are given as a range between `FromBreak` and `ToBreak` columns. Let us use this information to visualize the polygons with different colors and appropriate popup messags on the map"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"hidden": true
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},
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"outputs": [],
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"source": [
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"colors = {5: [0, 128, 0, 90], \n",
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" 10: [255, 255, 0, 90], \n",
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" 15: [255, 0, 0, 90]}\n",
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"\n",
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"fill_symbol = {\"type\": \"esriSFS\",\"style\": \"esriSFSSolid\",\n",
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" \"color\": [115,76,0,255]}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"hidden": true
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},
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"outputs": [],
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"source": [
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"for service_area in service_area_fset.features:\n",
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" \n",
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" #set color based on drive time\n",
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" fill_symbol['color'] = colors[service_area.attributes['ToBreak']]\n",
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" \n",
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" #set popup\n",
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" popup={\"title\": \"Service area\", \n",
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" \"content\": \"{} minutes\".format(service_area.attributes['ToBreak'])}\n",
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" \n",
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" map1.draw(service_area.geometry, symbol=fill_symbol, popup=popup)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"hidden": true
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},
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"source": [
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"Click the drive time areas to explore their attributes. Because the content of the pop-ups may include HTML source code, it is also possible to have the pop-up windows include other resources such as tables and images."
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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