wildfire-analyser 0.2.6

Python library for post-fire assessment and wildfire analysis using Google Earth Engine.

wildfire-analyser

Python project for analyzing wildfires in natural reserves.

Installation and Usage

Follow the steps below to install and test wildfire-analyser inside an isolated environment:

mkdir /tmp/test
cd /tmp/test

python3 -m venv venv
source venv/bin/activate

pip install wildfire-analyser

Required Files Before Running the Client

Before running the client, you must prepare two items:

---

1. Add a GeoJSON polygon

Create a folder named polygons in the project root and place your ROI polygon file inside it:

/tmp/test/
├── polygons/
│   └── your_polygon.geojson
└── venv/

An example GeoJSON file is available in the repository.

---

2. Create the .env file with GEE authentication data

In the project root, add a .env file containing your Google Earth Engine authentication variables.

A .env template is also available in the GitHub repository.

/tmp/test/
├── .env
├── polygons/
└── venv/

---

Running the Client

After adding the .env file and your GeoJSON polygon:

python3 -m wildfire_analyser.client \
   --roi polygons/canakkale_aoi_1.geojson \
   --start-date 2023-07-01 \
   --end-date 2023-07-21 \
   --deliverables-all \
   --days-before-after 1

Possible options for --deliverables are: RGB_PRE_FIRE, RGB_POST_FIRE, NDVI_PRE_FIRE, NDVI_POST_FIRE, NBR_PRE_FIRE, NBR_POST_FIRE, DNDVI, DNBR, RBR, BURN_SEVERITY_MAP, RGB_PRE_FIRE_VISUAL, RGB_POST_FIRE_VISUAL, DNBR_VISUAL, RBR_VISUAL, BURN_SEVERITY_VISUAL, BURNED_AREA_STATISTICS,

This will start the analysis process, generate visual thumbnail links for use by the frontend, and save the scientific GeoTIFF images to the GCP bucket. All links will be displayed in the terminal.

for help, type:

python3 -m wildfire_analyser.client --help

You should see something like this:

usage: client.py [-h] --roi ROI --start-date START_DATE --end-date END_DATE
                 [--deliverables DELIVERABLES [DELIVERABLES ...]] [--deliverables-all]
                 [--days-before-after DAYS_BEFORE_AFTER]

Post-fire assessment using Google Earth Engine

options:
  -h, --help            show this help message and exit
  --roi ROI             Path to ROI GeoJSON file
  --start-date START_DATE
                        Start date (pre-fire) in YYYY-MM-DD format
  --end-date END_DATE   End date (post-fire) in YYYY-MM-DD format
  --deliverables DELIVERABLES [DELIVERABLES ...]
                        List of deliverables to generate. Example: --deliverables RGB_PRE_FIRE DNBR
  --deliverables-all    Generate all available deliverables
  --days-before-after DAYS_BEFORE_AFTER
                        Number of days before and after the event date to search imagery (default: 30)

Setup Instructions for Developers

1. Clone the repository

git clone [e-mail]:camargo-advanced/wildfire-analyser.git
cd wildfire-analyser

2. Create a virtual environment

python3 -m venv venv

3. Activate the virtual environment

source venv/bin/activate

4. Install dependencies Make sure the virtual environment is activated, then run:

pip install -r requirements.txt

5. Configure environment variables Copy your version of .env file to the root folder with your GEE authentication credentials. A template file .env.template is provided as an example.

6. Run the sample client application

python3 -m wildfire_analyser.client \
   --roi polygons/canakkale_aoi_1.geojson \
   --start-date 2023-07-01 \
   --end-date 2023-07-21 \
   --deliverables-all \
   --days-before-after 1

Useful Commands

• Deactivate the virtual environment:

deactivate

• **Build a new PyPi lib and publish **:

rm -rf dist/*
python -m build
twine upload dist/*