Ais traffic

Vessel Traffic Example¶

Using moving pandas with the TransMAP REST API

In [ ]:

# Source ref: https://github.com/anitagraser/movingpandas-examples/blob/main/analysis-examples/2-ship-data.ipynb

make_url = lambda uri: "https://oak.cast.uark.edu/{0}".format(uri)

# Source ref: https://github.com/anitagraser/movingpandas-examples/blob/main/analysis-examples/2-ship-data.ipynb make_url = lambda uri: "https://oak.cast.uark.edu/{0}".format(uri)

In [ ]:

%matplotlib inline

%matplotlib inline

In [ ]:

from IPython.core.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))

from IPython.core.display import display, HTML display(HTML(""))

In [ ]:

import requests
import numpy as np
import pandas as pd
import geopandas
from shapely.geometry import Point, LineString, Polygon
from datetime import datetime, timedelta
import matplotlib.pyplot as plt
import movingpandas as mpd

import warnings
warnings.simplefilter("ignore")

import requests import numpy as np import pandas as pd import geopandas from shapely.geometry import Point, LineString, Polygon from datetime import datetime, timedelta import matplotlib.pyplot as plt import movingpandas as mpd import warnings warnings.simplefilter("ignore")

In [ ]:

mpd.__version__
def make_date(year: int, month: int, day: int, hour: int = 0, minute: int = 0, second: int = 0):
    return datetime(year, month, day, hour, minute, second).strftime("%Y-%m-%dT%H:%M:%S")

mpd.__version__ def make_date(year: int, month: int, day: int, hour: int = 0, minute: int = 0, second: int = 0): return datetime(year, month, day, hour, minute, second).strftime("%Y-%m-%dT%H:%M:%S")

In [ ]:

ais_data = requests.get(make_url('ais/vessels'), params={
    "limit": 50000,
    "start_date": make_date(2020, 5, 29),
    "end_date": make_date(2020, 5, 30)
})
ais_data.raise_for_status()

ais_data = requests.get(make_url('ais/vessels'), params={ "limit": 50000, "start_date": make_date(2020, 5, 29), "end_date": make_date(2020, 5, 30) }) ais_data.raise_for_status()

In [ ]:

df = pd.DataFrame(ais_data.json())
df

df = pd.DataFrame(ais_data.json()) df

In [ ]:

df2 = pd.DataFrame(df.location.tolist(), index= df.index)
gpdf = geopandas.GeoDataFrame(df, geometry=geopandas.points_from_xy(df2[0], df2[1]))

df2 = pd.DataFrame(df.location.tolist(), index= df.index) gpdf = geopandas.GeoDataFrame(df, geometry=geopandas.points_from_xy(df2[0], df2[1]))

In [ ]:

gpdf.set_crs('epsg:4326')

gpdf.set_crs('epsg:4326')

In [ ]:

gpdf.plot()

gpdf.plot()

In [ ]:

gpdf['t'] = pd.to_datetime(gpdf['BaseDateTime'], format='%Y-%m-%dT%H:%M:%S')

gpdf['t'] = pd.to_datetime(gpdf['BaseDateTime'], format='%Y-%m-%dT%H:%M:%S')

In [ ]:

gpdf = gpdf.set_index('t')

gpdf = gpdf.set_index('t')

In [ ]:

gpdf['SOG'].hist(bins=10, figsize=(15, 3))

gpdf['SOG'].hist(bins=10, figsize=(15, 3))

In [ ]:

print("Original size: {} rows".format(len(gpdf)))
gpdf = gpdf[gpdf.SOG>0]
print("Reduced to {} rows after removing 0 speed records".format(len(gpdf)))
gpdf['SOG'].hist(bins=10, figsize=(15,3))

print("Original size: {} rows".format(len(gpdf))) gpdf = gpdf[gpdf.SOG>0] print("Reduced to {} rows after removing 0 speed records".format(len(gpdf))) gpdf['SOG'].hist(bins=10, figsize=(15,3))

In [ ]:

gpdf['VesselType'] = gpdf['VesselType'].astype(float)
gpdf['VesselType'].value_counts().plot(kind='bar', figsize=(15,3))

gpdf['VesselType'] = gpdf['VesselType'].astype(float) gpdf['VesselType'].value_counts().plot(kind='bar', figsize=(15,3))

In [ ]:

%%time
MIN_LENGTH = 0.02 # degrees - May need to reproject to use meters
traj_collection = mpd.TrajectoryCollection(gpdf, 'MMSI', min_length=MIN_LENGTH)
print("Finished creating {} trajectories".format(len(traj_collection)))

%%time MIN_LENGTH = 0.02 # degrees - May need to reproject to use meters traj_collection = mpd.TrajectoryCollection(gpdf, 'MMSI', min_length=MIN_LENGTH) print("Finished creating {} trajectories".format(len(traj_collection)))

In [ ]:

traj_collection = mpd.MinTimeDeltaGeneralizer(traj_collection).generalize(tolerance=timedelta(minutes=1))
# this is looking for a specific 't' index

traj_collection = mpd.MinTimeDeltaGeneralizer(traj_collection).generalize(tolerance=timedelta(minutes=1)) # this is looking for a specific 't' index

In [ ]:

shiptype_to_color = {'Passenger': 'blue', 'HSC': 'green', 'Tanker': 'red', 'Cargo': 'orange'}
# Should be changed to map to these codes: https://coast.noaa.gov/data/marinecadastre/ais/VesselTypeCodes2018.pdf
traj_collection.plot(column='VesselType', column_to_color=shiptype_to_color, linewidth=1, capstyle='round')

shiptype_to_color = {'Passenger': 'blue', 'HSC': 'green', 'Tanker': 'red', 'Cargo': 'orange'} # Should be changed to map to these codes: https://coast.noaa.gov/data/marinecadastre/ais/VesselTypeCodes2018.pdf traj_collection.plot(column='VesselType', column_to_color=shiptype_to_color, linewidth=1, capstyle='round')

In [ ]:

passenger = traj_collection
passenger.hvplot(title='Passenger ferries', line_width=2)

passenger = traj_collection passenger.hvplot(title='Passenger ferries', line_width=2)

In [ ]:

In [ ]:

---

Last update: 2022-09-26