disasters

An automated workflow for generating disaster response maps and layouts over a user-defined AOI using NASA-JPL OPERA products.

Overview

This tool streamlines the generation of data to support disaster response efforts using NASA-JPL OPERA products. It automates the discovery, download, mosaicking, differencing (if applicable), and visualization of products related to:

• Flooding (e.g., DSWx-HLS, DSWx-S1)
• Wildfires (e.g., DIST-ALERT-HLS)
• Landslides (e.g., DIST-ALERT-HLS, RTC)
• Earthquakes (e.g., CSLC, DISP) (coming soon)

The output includes ready-to-share maps and analysis-ready GeoTIFFs for any user-defined region and event type. Currently flood, wildfire, and landslide are supported (earthquakes coming soon).

Development setup

Requirements

• Python 3.9+
• Mamba or Conda
• Git

We recommend using Mamba for faster environment setup.

Prerequisite installs

1. Download source code:

git clone https://github.com/cmspeed/disasters

2. Navigate to and install dependencies, using the included environment.yml file:

cd disasters
mamba env create --file environment.yml
mamba activate disasters

The provided environment.yml file sets up a fully functional environment with all required packages.

Usage

Example: Generate flood maps over Lake Mead, Nevada using the two most recent OPERA products

python disaster.py -b 35 37 -115 -113 -o LakeMead -m flood -n 2 -lt "Lake Mead Floods"

Example: Generate fire impact maps over New Mexico using the five (default) most recent OPERA products

python disaster.py -b 32 34 -106.5 -104 -o NM_Fires -m fire -lt "New Mexico Fires, June 2025"

Example: Generate fire impact maps over a wildfire in Quebec using the most recent 30 OPERA products (prior to 07-31-2023), filtered to remove disturbance prior to 05-15-2023

python disaster.py -b 48 49.5 -77.5 -74.4 -o QuebecFires -m fire -d 2023-07-31 -n 30 -lt "Quebec Wildfire, Summer 2023" -fd 2023-05-15

Example: Generate landslide impact maps over a landslide in Brazil in February 2023

python disaster.py -b -24 -23.5 -45.75 -45.5 -o test_landslide_mode -m landslide -lt "Brazil Landslides, Feb. 2023" -fd 2023-02-01 -d 2023-03-01 -zb -23.783 -23.733 -45.733 -45.683

Example: Generate flood maps over Jamaica for Hurricane Melissa in October 2025

In this example, misclassified snow/ice classified pixels (likely sediment-rich water) are reclassified to open water using the DIST-HLS Confidence layer. Note: All snow/ice/sediment-rich water pixels are not reclassified using this approach.

python disaster.py -b 17.3 18.8 -78.6 -75.6 -m flood -o hurricane_melissa_Oct2025 -rc -lt "Hurricane Melissa, Oct. 2025"

Example: Generate disturbance maps over Jamaica for Hurricane Melissa in October 2025

In this example, a filter data (-fd) of October 28, 2025 (coinciding with hurricane landfall) is applied. All disturbance prior to this date is filtered out of the final mosaics.

python disaster.py -b 17.3 18.8 -78.6 -75.6 -m fire -o hurricane_melissa_Oct2025 -lt "Hurricane Melissa, Oct. 2025" -fd 2025-10-28

Command-line Arguments

Argument	Required	Description
-b, --bbox	Yes	Bounding box: South North West East (space-separated floats)
-o, --output_dir	Yes	Output directory or prefix for storing results
-m, --mode	Yes	Disaster mode: flood, fire, or earthquake
-d, --event-date	No	Specifies the end date (YYYY-MM-DD) for the OPERA product search. The script will find the 'N' most recent products available on or before this date (where 'N' is set by --number-of-dates argument). Defaults to 'today'.
-n, --number_of_dates	No	Number of most recent dates to process (default: 5)
-lt, --layout_title	Yes	Title of PDF layout generated for each product
-fd, --filter_date	No	Date to use as filter in fire mode to remove all disturbance preceding filter_date
-rc, --reclassify_snow_ice	No	Flag to reclassify false snow/ice positives as water in DSWx-HLS products ONLY. (Default: False)
-zb, --zoom_box	No	Zoom bounding box: South North West East (space-separated floats)

Disaster Modes

The -m / --mode argument determines which disaster type to process and which NASA OPERA products and data layers are used.

Mode	OPERA Products	Layer(s)	Description
flood	DSWx-HLS, DSWx-S1	WTR, BWTR	Detects surface water using optical (HLS) and SAR (S1) observations
fire	OPERA_L3_DIST-ALERT-HLS_V1, DIST-ALERT-S1 (coming soon)	VEG-ANOM-MAX, VEG-DIST-STATUS	Identifies vegetation disturbance and anomalies from wildfire events
landslide	OPERA_L3_DIST-ALERT-HLS_V1, OPERA_L2_RTC-S1_V1	VEG-ANOM-MAX, VEG-DIST-STATUS, RTC-VV, RTC-VH	Identifies vegetation disturbance and anomalies from landslides events
earthquake	CSLC, DISP, RTC-S1 (coming soon)	(coming soon)	Maps surface displacement and SAR backscatter changes related to seismic activity

Output

For each valid product and date:

• Mosaicked GeoTIFF file
• Reprojected WGS84 version of the mosaic
• Difference maps for water products for all available date pairs
• Quicklook PNG map with legend and colorbar
• Layout in PDF format including PNG map and explanation

Products are organized in a timestamped subdirectory under your specified --output_dir.

Contributing

Contributions are welcome! Please open an issue or submit a pull request.