SpaceX Launch Sites Proximities

Part of the capstone project "Using Data Science Concepts to Optimize Rocket Launches", which, in turn, was part of the IBM Data Science Professional Certificate. (Notebook link: https://github.com/Francis-Calingo/IBM-Capstone-Data-Science-for-Rocket-Science/blob/main/SpaceY_FoliumMap.ipynb)

In this hypothetical scenario, I served the role of a data scientist for the fictional startup aeronautical company, SpaceY, who aims to compete with SpaceX. In this research, I was tasked with scraping data on SpaceX to help determine factors such as launch sites and types of rockets that optimizes the success of rocket launches. For the geospatial portion of the project, I generated several Folium maps in Jupyter Notebook to analyze the spatial relations of SpaceX's launch sites.

Data collection and prep:

!pip3 install folium
!pip3 install wget
!pip3 install pandas

import folium
import wget
import pandas as pd

from folium.plugins import MarkerCluster
from folium.plugins import MousePosition
from folium.features import DivIcon

spacex_csv_file=wget.download('https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DS0321EN-SkillsNetwork/datasets/spacex_launch_geo.csv')
spacex_df=pd.read_csv(spacex_csv_file)

spacex_df = spacex_df[['Launch Site', 'Lat', 'Long', 'class']]
launch_sites_df = spacex_df.groupby(['Launch Site'], as_index=False).first()
launch_sites_df = launch_sites_df[['Launch Site', 'Lat', 'Long']]
launch_sites_df

Map 1: Locations of SpaceX's 4 launch sites

# Start location is NASA Johnson Space Center
nasa_coordinate = [29.559684888503615, -95.0830971930759]
site_map = folium.Map(location=nasa_coordinate, zoom_start=10)

# Create a blue circle at NASA Johnson Space Center's coordinate with a popup label showing its name
circle = folium.Circle(nasa_coordinate, radius=1000, color='#d35400', fill=True).add_child(folium.Popup('NASA Johnson Space Center'))
# Create a blue circle at NASA Johnson Space Center's coordinate with a icon showing its name
marker = folium.map.Marker(
    nasa_coordinate,
    # Create an icon as a text label
    icon=DivIcon(
        icon_size=(20,20),
        icon_anchor=(0,0),
        html='<div style="font-size: 12; color:#d35400;"><b>%s</b></div>' % 'NASA JSC',
        )
    )
site_map.add_child(circle)
site_map.add_child(marker)

# Then initialize the map
site_map = folium.Map(location=nasa_coordinate, zoom_start=5)
# For each launch site, add a Circle object based on its coordinate (Lat, Long) values. In addition, add Launch site name as a popup label
for index, record in launch_sites_df.iterrows():
    # TODO: Create and add a folium.Circle object
    coordinate = [record['Lat'], record['Long']]
    # Create a blue circle at NASA Johnson Space Center's coordinate with a popup label showing its name
    circle = folium.Circle(coordinate, radius=1000, color='#d35400', fill=True).add_child(folium.Popup(record['Launch Site']))
    marker = folium.map.Marker(
        coordinate,
        # Create an icon as a text label
        icon=DivIcon(
            icon_size=(20,20),
            icon_anchor=(0,0),
            html='<div style="font-size: 12; color:#d35400;"><b>%s</b></div>' % record['Launch Site'],
            )
        )
    site_map.add_child(circle)
    site_map.add_child(marker)

site_map

The sites were concentrated in the coastal part of Southern California and Florida, possibly due to safety considerations in the event of a failed launch, which allows debris to have a better chance of falling into the ocean rather than highly populated centres.

Map 2-3: Two of 4 launch sites that mark the success/failed launches for each site on the map

marker_cluster = MarkerCluster()

# Apply a function to check the value of `class` column
# If class=1, marker_color value will be green
# If class=0, marker_color value will be red
def assign_marker_color(launch_outcome):
    if launch_outcome == 1:
        return 'green'
    else:
        return 'red'

spacex_df['marker_color'] = spacex_df['class'].apply(assign_marker_color)
spacex_df.tail(10)

# Function to assign color to launch outcome
def assign_marker_color(launch_outcome):
    if launch_outcome == 1:
        return 'green'
    else:
        return 'red'

spacex_df['marker_color'] = spacex_df['class'].apply(assign_marker_color)
spacex_df.tail(10)

# Add marker_cluster to current site_map
site_map.add_child(marker_cluster)

# for each row in spacex_df data frame
# create a Marker object with its coordinate
# and customize the Marker's icon property to indicate if this launch was successed or failed,
# e.g., icon=folium.Icon(color='white', icon_color=row['marker_color']
for index, record in spacex_df.iterrows():
    ls_name = record['Launch Site']
    ls_lat  = record['Lat']
    ls_long = record['Long']
    coordinate = [ls_lat, ls_long]

    #rint('{}\t{}\t{}'.format(ls_name, ls_lat, ls_long))

    # TODO: Create and add a Marker cluster to the site map
    # marker = folium.Marker(...)
    marker = folium.map.Marker(coordinate, icon=folium.Icon(color='white', icon_color=record['marker_color'],icon_anchor=(0,0), html='<div style="font-size: 12; color:#d35400;"><b>%s</b></div>' % ls_name, ))
    marker_cluster.add_child(marker)

site_map

# Add marker_cluster to current site_map
site_map.add_child(marker_cluster)

# for each row in spacex_df data frame
# create a Marker object with its coordinate
# and customize the Marker's icon property to indicate if this launch was successed or failed,
# e.g., icon=folium.Icon(color='white', icon_color=row['marker_color']
for index, record in spacex_df.iterrows():
    # TODO: Create and add a Marker cluster to the site map
    # marker = folium.Marker(...)
    marker_cluster.add_child(marker)

site_map

Based on the Folium map, KSC LC-39A site is the most successful site (Map 2).

Map 4: Distances between a launch site to its proximities

# Add Mouse Position to get the coordinate (Lat, Long) for a mouse over on the map
formatter = "function(num) {return L.Util.formatNum(num, 5);};"
mouse_position = MousePosition(
    position='topright',
    separator=' Long: ',
    empty_string='NaN',
    lng_first=False,
    num_digits=20,
    prefix='Lat:',
    lat_formatter=formatter,
    lng_formatter=formatter,
)

site_map.add_child(mouse_position)
site_map

# Calculate the distance between two points on the map based on their Lat and Long values using the following method:

from math import sin, cos, sqrt, atan2, radians

def calculate_distance(lat1, lon1, lat2, lon2):
    # approximate radius of earth in km
    R = 6373.0

    lat1 = radians(lat1)
    lon1 = radians(lon1)
    lat2 = radians(lat2)
    lon2 = radians(lon2)

    dlon = lon2 - lon1
    dlat = lat2 - lat1

    a = sin(dlat / 2)**2 + cos(lat1) * cos(lat2) * sin(dlon / 2)**2
    c = 2 * atan2(sqrt(a), sqrt(1 - a))

    distance = R * c
    return distance

# find coordinate of the closest coastline
# e.g.,: Lat: 28.56367  Lon: -80.57163
# distance_coastline = calculate_distance(launch_site_lat, launch_site_lon, coastline_lat, coastline_lon)
distance = calculate_distance(28.57468,-80.65229,28.573255 ,-80.646895)
distance

# Create and add a folium.Marker on your selected closest coastline point on the map
# Display the distance between coastline point and launch site using the icon property
# for example
# distance_marker = folium.Marker(
#    coordinate,
#    icon=DivIcon(
#        icon_size=(20,20),
#        icon_anchor=(0,0),
#        html='<div style="font-size: 12; color:#d35400;"><b>%s</b></div>' % "{:10.2f} KM".format(distance),
#        )
#    )
coordinate = [28.57468,-80.65229]
distance_marker = folium.Marker(
    coordinate,
    icon=DivIcon(
        icon_size=(20,20),
        icon_anchor=(0,0),
        html='<div style="font-size: 12; color:#d35400;"><b>%s</b></div>' % "{:10.2f} KM".format(distance),
    )
)
site_map.add_child(distance_marker)
site_map

 Create a `folium.PolyLine` object using the coastline coordinates and launch site coordinate
# lines=folium.PolyLine(locations=coordinates, weight=1)
coordinates=[[28.57468,-80.65229],[28.573255 ,-80.646895]]
lines=folium.PolyLine(locations=coordinates, weight=1)
site_map.add_child(lines)

# Create a marker with distance to a closest city, railway, highway, etc.
# Draw a line between the marker to the launch site

coordinates=[[28.52361, -80.64857],[28.573255 ,-80.646895]]
lines=folium.PolyLine(locations=coordinates, weight=1)
site_map.add_child(lines)

distance_marker = folium.Marker(
    coordinates[0],
    icon=DivIcon(
        icon_size=(20,20),
        icon_anchor=(0,0),
        html='<div style="font-size: 12; color:#d35400;"><b>%s</b></div>' % "{:10.2f} KM".format(calculate_distance(28.52361, -80.64857,28.573255 ,-80.646895)),
    )
)
site_map.add_child(distance_marker)

Here is the aforementioned KSC LC-39A and its distance to the nearest parking lots. A few highways and roads are within the vicinity of the site, suggesting that despite its relative isolation, it is still served well by good road infrastructure.

Plug-ins used

tags

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