WildfireDroughtFlood (La Niña years)

Satellite Analysis for New South Wales, Australia

Name: Satalyse
Author: Satalyse

NSW experienced the Black Summer fires of 2019–2020, the most destructive wildfire season in Australian recorded history, burning over 5.5 million hectares. Satellite-derived vegetation dryness and fire risk scoring are now embedded in state government emergency planning, while insurers use pre-season risk assessments to manage portfolio exposure.

-33.47°, 150.64°

Temperate to semi-arid, with southern oscillation (La Niña/El Niño) driving multi-year drought and rainfall cycles that strongly influence vegetation fuel loads.

What you can analyze here

The Satalyse API covers every major satellite analysis type for New South Wales, Australia. These endpoints are most relevant for this location:

Risk Scoring

POST /api/v1/satellite/score-risk

Change Detection

POST /api/v1/satellite/detect-changes

Code example

This snippet is pre-filled with New South Wales, Australia's coordinates and calls the Risk Scoring endpoint.

new-south-wales_analysis.py

1"color:#c084fc">import requests
2
3response = requests.post(
4    "https://api.satalyse.dev/api/v1/satellite/score-risk",
5    headers={"Authorization": "Bearer sat_sk_live_..."},
6    json={
7        "geometry": {
8            "type": "Polygon",
9            "coordinates": [[
10            [150.61, -33.5],
11            [150.67, -33.5],
12            [150.67, -33.44],
13            [150.61, -33.44],
14            [150.61, -33.5]
15            ]]
16        },
17        "asset_type": "agricultural",
18        "location_context": "rural",
19        "risk_factors": ["wildfire"],
20        "time_horizon_days": 365
21    }
22)
23
24data = response.json()
25"color:#c084fc">print("color:#c084fc">f"Risk score:  {data['overall_risk_score']}/100")
26"color:#c084fc">print("color:#c084fc">f"Risk level:  {data['overall_risk_level']}")

Data sources used for New South Wales, Australia

Source	What it provides	Resolution
Sentinel-2	Multispectral optical imagery (NDVI, land cover)	10 m
Landsat 8	Long-term land surface reflectance and temperature	30 m
MODIS	Daily global coverage, fire, vegetation anomalies	250 m – 1 km
SRTM	Digital elevation model, terrain, slope, aspect	30 m
CHIRPS	Historical and near-real-time precipitation estimates	5 km
JRC Global Surface Water	Water presence history and seasonal flood extent	30 m