popexposure 1.0.0.dev17

A package for finding the number of people residing near environmental hazards

popexposure: Functions to estimate the number of people living near environmental hazards

Overview

popexposure is an open-source Python package providing fast, memory-efficient, and consistent estimates of the number of people living near environmental hazards, enabling environmental scientists to assess population-level exposure to environmental hazards based on residential proximity. Methodological details can be found in McBrien et al (2025). Extensive documentation can be found on in our quick start tutorial.

Installation

The easiest way to install popexposure is via the latest pre-compiled binaries from PyPI with:

pip install popexposure

You can build popexposure from source as you would any other Python package with:

git clone https://github.com/heathermcb/popexposure
cd popexposure
python -m pip install .

Tutorials

A number of tutorials providing worked examples using popexposure can be found in our tutorials folder.

Quickstart

import glob
import pandas as pd
import popexposure as ex

# Set paths
my_pop_raster_path = "my_pop_raster.tif"
admin_units_path = "my_admin_units.geojson"

# Instantiate estimator
pop_est = ex.PopEstimator(pop_data = my_pop_raster_path, admin_data= my_admin_units.geojson)

# List of years and corresponding hazard file paths
years = [2016, 2017, 2018]
hazard_paths = [
    "hazard_2016.geojson",
    "hazard_2017.geojson",
    "hazard_2018.geojson"
]

# Find total num ppl residing <= 10km of each hazard in each year
exposed_list = []

for year, hazard_path in zip(years, hazard_paths):
    # Estimate exposed population
    exposed = pop_est.est_exposed_pop(
        hazard_specific=False,  # set to True if you want per-hazard results
        hazards=hazard_path,
    )
    exposed['year'] = year
    exposed_list.append(exposed)

exposed_df = pd.concat(exposed_list, axis=0)

# Save output
exposed_df.to_parquet("pop_exposed_to_hazards.parquet")

Available methods

Function	Overview	Inputs	Outputs
PopEstimator	Main class for estimating population exposure; initializes with population and optional admin data	pop_data (raster path), admin_data (GeoJSON or shapefile path)	PopEstimator object
est_exposed_pop	Estimates number of people living within a specified distance of hazards	hazards (GeoJSON/shapefile), hazard_specific (bool)	DataFrame with exposed population counts by hazard/admin unit
est_total_pop	Estimates total population in administrative units	None (uses data provided at initialization)	DataFrame with total population per administrative unit

Getting help and contributing

If you have any questions, a feature request, or would like to report a bug, please open an issue. We also welcome any new contributions and ideas. If you want to add code, please submit a pull request and we will get back to you when we can. Thanks!

Citing this package

Please cite our paper McBrien et al (2025).

Authors

• Heather McBrien
• Joan A. Casey
• Lawrence Chillrud
• Nina M. Flores
• Lauren B. Wilner

References

Our package is a fancy wrapper for the package exactextract.