1.12. (Exercise) Hurricane Track Analysis#
Can you quickly find out which US states hurricane Florence passed through using GeoPandas?
Image source: NASA Worldview
Tip
Installing GeoPandas
Please run the following code blocks in this section to:
Install the GeoPandas’s dependencies and GeoPandas
Download and unzip the data used in this notebook
Import GeoPandas and other required modules for the notebook
#Install GeoPandas' dependencies
!pip install --upgrade pyshp
!pip install --upgrade shapely
!pip install --upgrade descartes
!pip install --upgrade rtree
Requirement already satisfied: pyshp in /Users/itam/miniconda3/lib/python3.12/site-packages (3.0.2.post1)
Requirement already satisfied: shapely in /Users/itam/miniconda3/lib/python3.12/site-packages (2.1.2)
Requirement already satisfied: numpy>=1.21 in /Users/itam/miniconda3/lib/python3.12/site-packages (from shapely) (2.3.1)
Requirement already satisfied: descartes in /Users/itam/miniconda3/lib/python3.12/site-packages (1.1.0)
Requirement already satisfied: matplotlib in /Users/itam/miniconda3/lib/python3.12/site-packages (from descartes) (3.10.3)
Requirement already satisfied: contourpy>=1.0.1 in /Users/itam/miniconda3/lib/python3.12/site-packages (from matplotlib->descartes) (1.3.2)
Requirement already satisfied: cycler>=0.10 in /Users/itam/miniconda3/lib/python3.12/site-packages (from matplotlib->descartes) (0.12.1)
Requirement already satisfied: fonttools>=4.22.0 in /Users/itam/miniconda3/lib/python3.12/site-packages (from matplotlib->descartes) (4.58.5)
Requirement already satisfied: kiwisolver>=1.3.1 in /Users/itam/miniconda3/lib/python3.12/site-packages (from matplotlib->descartes) (1.4.8)
Requirement already satisfied: numpy>=1.23 in /Users/itam/miniconda3/lib/python3.12/site-packages (from matplotlib->descartes) (2.3.1)
Requirement already satisfied: packaging>=20.0 in /Users/itam/miniconda3/lib/python3.12/site-packages (from matplotlib->descartes) (23.2)
Requirement already satisfied: pillow>=8 in /Users/itam/miniconda3/lib/python3.12/site-packages (from matplotlib->descartes) (11.3.0)
Requirement already satisfied: pyparsing>=2.3.1 in /Users/itam/miniconda3/lib/python3.12/site-packages (from matplotlib->descartes) (3.2.3)
Requirement already satisfied: python-dateutil>=2.7 in /Users/itam/miniconda3/lib/python3.12/site-packages (from matplotlib->descartes) (2.9.0.post0)
Requirement already satisfied: six>=1.5 in /Users/itam/miniconda3/lib/python3.12/site-packages (from python-dateutil>=2.7->matplotlib->descartes) (1.17.0)
Requirement already satisfied: rtree in /Users/itam/miniconda3/lib/python3.12/site-packages (1.4.1)
#Install GeoPandas
!pip install --upgrade geopandas
Collecting geopandas
Using cached geopandas-1.1.1-py3-none-any.whl.metadata (2.3 kB)
Requirement already satisfied: numpy>=1.24 in /Users/itam/miniconda3/lib/python3.12/site-packages (from geopandas) (2.3.1)
Collecting pyogrio>=0.7.2 (from geopandas)
Using cached pyogrio-0.11.1.tar.gz (287 kB)
Installing build dependencies ... ?25l-
\
|
/
-
done
?25h Getting requirements to build wheel ... ?25l-
done
?25h Preparing metadata (pyproject.toml) ... ?25l-
error
error: subprocess-exited-with-error
× Preparing metadata (pyproject.toml) did not run successfully.
│ exit code: 1
╰─> [28 lines of output]
Traceback (most recent call last):
File "/Users/itam/miniconda3/lib/python3.12/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 353, in <module>
main()
File "/Users/itam/miniconda3/lib/python3.12/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 335, in main
json_out['return_val'] = hook(**hook_input['kwargs'])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/itam/miniconda3/lib/python3.12/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 149, in prepare_metadata_for_build_wheel
return hook(metadata_directory, config_settings)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/private/var/folders/7l/4c3bq00s0r994qdpmp2gfm6r0000gq/T/pip-build-env-her3mem8/overlay/lib/python3.12/site-packages/setuptools/build_meta.py", line 374, in prepare_metadata_for_build_wheel
self.run_setup()
File "/private/var/folders/7l/4c3bq00s0r994qdpmp2gfm6r0000gq/T/pip-build-env-her3mem8/overlay/lib/python3.12/site-packages/setuptools/build_meta.py", line 317, in run_setup
exec(code, locals())
File "<string>", line 154, in <module>
File "<string>", line 129, in get_gdal_config
File "<string>", line 85, in get_gdal_config
File "<string>", line 39, in read_response
File "/Users/itam/miniconda3/lib/python3.12/subprocess.py", line 466, in check_output
return run(*popenargs, stdout=PIPE, timeout=timeout, check=True,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/itam/miniconda3/lib/python3.12/subprocess.py", line 548, in run
with Popen(*popenargs, **kwargs) as process:
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/itam/miniconda3/lib/python3.12/subprocess.py", line 1026, in __init__
self._execute_child(args, executable, preexec_fn, close_fds,
File "/Users/itam/miniconda3/lib/python3.12/subprocess.py", line 1953, in _execute_child
raise child_exception_type(errno_num, err_msg, err_filename)
FileNotFoundError: [Errno 2] No such file or directory: 'gdal-config'
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed
× Encountered error while generating package metadata.
╰─> See above for output.
note: This is an issue with the package mentioned above, not pip.
hint: See above for details.
?25h
import pooch
# Download the data used in this notebook
data = pooch.retrieve('https://unils-my.sharepoint.com/:u:/g/personal/tom_beucler_unil_ch/EZQnP79VVtROtOlxw5QpfoYBtPG54sb4CZ2vzlg0bKkPew?download=1',
known_hash='200a740d0e448aa9e4e03d8a9965a70f228442a2da28d804c8e2337d0ef9749e',
processor=pooch.Unzip()
)
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
Cell In[3], line 1
----> 1 import pooch
2 # Download the data used in this notebook
3 data = pooch.retrieve('https://unils-my.sharepoint.com/:u:/g/personal/tom_beucler_unil_ch/EZQnP79VVtROtOlxw5QpfoYBtPG54sb4CZ2vzlg0bKkPew?download=1',
4 known_hash='200a740d0e448aa9e4e03d8a9965a70f228442a2da28d804c8e2337d0ef9749e',
5 processor=pooch.Unzip()
6 )
ModuleNotFoundError: No module named 'pooch'
data
['/Users/itam/Library/Caches/pooch/3d43e48bb7d0d0370db00be3096108fe-EZQnP79VVtROtOlxw5QpfoYBtPG54sb4CZ2vzlg0bKkPew.unzip/florence.csv',
'/Users/itam/Library/Caches/pooch/3d43e48bb7d0d0370db00be3096108fe-EZQnP79VVtROtOlxw5QpfoYBtPG54sb4CZ2vzlg0bKkPew.unzip/gz_2010_us_040_00_5m.json',
'/Users/itam/Library/Caches/pooch/3d43e48bb7d0d0370db00be3096108fe-EZQnP79VVtROtOlxw5QpfoYBtPG54sb4CZ2vzlg0bKkPew.unzip/__MACOSX/._gz_2010_us_040_00_5m.json',
'/Users/itam/Library/Caches/pooch/3d43e48bb7d0d0370db00be3096108fe-EZQnP79VVtROtOlxw5QpfoYBtPG54sb4CZ2vzlg0bKkPew.unzip/__MACOSX/._florence.csv']
References:
Geopandas official website: Introduction to GeoPandas https://geopandas.org/en/stable/getting_started/introduction.html
Automating GIS process https://autogis-site.readthedocs.io/en/latest/notebooks/L2/01-geopandas-basics.html
Use Data for Earth and Environmental Science in Open Source Python https://www.earthdatascience.org/courses/use-data-open-source-python/
The Shapely User Manual https://shapely.readthedocs.io/en/stable/manual.html
Geospatial Analysis with Python and R https://kodu.ut.ee/~kmoch/geopython2020/index.html
Introduction to Geospatial Data in Python https://www.datacamp.com/tutorial/geospatial-data-python
Exercise’s Instructions
Apply GeoPandas to read in the geospatial data, plot, and analyse the track of Hurricane Florence from August 30th to September 18th 2018.
Either write your own code, or fill in the blanks in the hidden cells 🙂
1.12.1. Q1) import geopandas, pandas#
#Import GeoPandas (as gpd), pandas, and matplotlib
# And ignore warnings
import warnings
warnings.filterwarnings('ignore')
#@markdown Fill in the blank code. Double-click here to reveal
#Import GeoPandas (as gpd), pandas, and matplotlib
import geopandas as gpd
import pandas as pd
import matplotlib.pyplot as plt
1.12.2. Q2) Read a Shapefile with GeoPandas’s read_file function#
# Find the index of the country file
countryindex = next(i for i, f in enumerate(data) if 'gz_2010_us_040_00_5m.json' in f)
# Find the index of the Florence cyclone
florenceindex = next(i for i, f in enumerate(data) if 'florence.csv' in f)
# Read data with the geopandas function
path = data[countryindex]
# Use geopandas to read the file and call it country
country = gpd.read_file(path)
#@markdown Fill in the blank code. Double-click here to reveal
# Read data with the geopandas function
path = data[0]
country = gpd.read_file(path)
1.12.3. Q3) Have a look at the data, what type of geometries does the data contain?#
# Print out the first few lines of the data
#@markdown Fill in the blank code. Double-click here to reveal
# The method to see the first few lines of the data
country.head()
| GEO_ID | STATE | NAME | LSAD | CENSUSAREA | geometry | |
|---|---|---|---|---|---|---|
| 0 | 0400000US01 | 01 | Alabama | 50645.326 | MULTIPOLYGON (((-88.12466 30.28364, -88.08681 ... | |
| 1 | 0400000US02 | 02 | Alaska | 570640.950 | MULTIPOLYGON (((-166.10574 53.98861, -166.0752... | |
| 2 | 0400000US04 | 04 | Arizona | 113594.084 | POLYGON ((-112.53859 37.00067, -112.53454 37.0... | |
| 3 | 0400000US05 | 05 | Arkansas | 52035.477 | POLYGON ((-94.04296 33.01922, -94.04304 33.079... | |
| 4 | 0400000US06 | 06 | California | 155779.220 | MULTIPOLYGON (((-122.42144 37.86997, -122.4213... |
1.12.4. Q4) Have a look at the data on a map using GeoPandas’s .plot() method. Exclude Alaska and Hawaii by the attribute ‘NAME’ and Pandas’s .isin() method. Specify the figsize to be 30 x 20.#
# Plot the US states (Alaska and Hawaii excluded)
#@markdown Fill in the blank code. Double-click here to reveal
# Plot the US states (Alaska and Hawaii excluded)
country[country[____].isin([____,____]) == False].____(figsize=(30,20))
data
['/Users/itam/Library/Caches/pooch/3d43e48bb7d0d0370db00be3096108fe-EZQnP79VVtROtOlxw5QpfoYBtPG54sb4CZ2vzlg0bKkPew.unzip/florence.csv',
'/Users/itam/Library/Caches/pooch/3d43e48bb7d0d0370db00be3096108fe-EZQnP79VVtROtOlxw5QpfoYBtPG54sb4CZ2vzlg0bKkPew.unzip/gz_2010_us_040_00_5m.json',
'/Users/itam/Library/Caches/pooch/3d43e48bb7d0d0370db00be3096108fe-EZQnP79VVtROtOlxw5QpfoYBtPG54sb4CZ2vzlg0bKkPew.unzip/__MACOSX/._gz_2010_us_040_00_5m.json',
'/Users/itam/Library/Caches/pooch/3d43e48bb7d0d0370db00be3096108fe-EZQnP79VVtROtOlxw5QpfoYBtPG54sb4CZ2vzlg0bKkPew.unzip/__MACOSX/._florence.csv']
# Read in the hurricane florence data, change the longitude, and have a look at the hurricane florence dataframe
tc_path = data[florenceindex]
florence = pd.read_csv(tc_path)
florence = florence.drop(['AdvisoryNumber', 'Forecaster', 'Received'], axis=1)
florence['Long'] = 0 - florence['Long']
florence.head(3)
| Date | Lat | Long | Wind | Pres | Movement | Type | Name | |
|---|---|---|---|---|---|---|---|---|
| 0 | 08/30/2018 11:00 | 12.9 | -18.4 | 30 | 1007 | W at 12 MPH (280 deg) | Potential Tropical Cyclone | Six |
| 1 | 08/30/2018 14:00 | 12.9 | -19.0 | 30 | 1007 | W at 12 MPH (280 deg) | Potential Tropical Cyclone | Six |
| 2 | 08/30/2018 17:00 | 12.9 | -19.4 | 30 | 1007 | W at 9 MPH (280 deg) | Potential Tropical Cyclone | Six |
1.12.5. Q5) Create a GeoDataFrame from florence DataFrame#
# Create a geodataframe from the hurricane florence dataframe
#@markdown Fill in the blank code. Double-click here to reveal
# Create a geodataframe from the hurricane florence dataframe
gdf_florence = gpd.____(florence, geometry=gpd.____(florence.Long, florence.Lat))
# Have a look at the hurricane geodataframe
gdf_florence.head(2)
1.12.6. Q6) Plot the US states map (without Alaska, Hawaii) and hurricane florence together#
# Plot to see the hurricane overlay over the US map
# And plot the hurricane position on top with red color to stand out:
#@markdown Fill in the blank code. Double-click here to reveal
# Plotting to see the hurricane overlay the US map:
fig, ax = plt.subplots(1, figsize=(30,20))
base = country[country[____].isin([____,____]) == False].____(ax=ax, color='#3B3C6E')
# plotting the hurricane position on top with red color to stand out:
gdf_florence.____(ax=base, color='darkred', marker="*", markersize=10)
1.12.7. Q7) What’s the coordinate reference system of the data?#
# Check the coordinate reference system of the geodataframe
#@markdown Fill in the blank code. Double-click here to reveal
# Check the coordinate reference system of the geodataframe
country.____
1.12.8. Q8) Which states are passed by the hurricane?#
Hint
One approach may be plot and see the trajectory of the hurricane on the US map. Other approaches are more than welcome.
# Plot the US states without Alaska and Hawaii, then
# Annotate the US states with their names, then
# Select the hurricane trajectory points inside the US boundary with the overlay operation, then
# Plot the hurricane trajectory inside US boundary
#@markdown Fill in the blank code. Double-click here to reveal
# Plot the US states without Alaska and Hawaii
df = country[country[____].isin([____,____]) == False]
ax = df.plot(figsize=(30,20))
# Annotate the US states with their names
_ = df.apply(lambda x: ax.____(s=x['NAME'], xy=x.geometry.centroid.coords[0], ha='center'), axis=1)
# Select the hurricane trajectory points inside the US boundary with the overlay operation
res_intersection = gdf_florence.____(country, how='intersection')
# Plot the hurricane trajectory inside US boundary
____.plot(ax=ax, color='red', marker="*", markersize=25)