WildfireDroughtFlood (Winter)

Satellite Analysis for California, USA

Name: Satalyse
Author: Satalyse

California faces compound climate risk, drought stress driving vegetation dryness across the Sierra Nevada and Coast Ranges, and wildfire activity that has expanded dramatically in size and season length. The state is also the USA's largest agricultural producer, making crop health monitoring, irrigation efficiency, and drought risk scoring all high-value satellite applications.

36.78°, -119.42°

Mediterranean with dry summers (May–Oct) that produce extreme vegetation moisture deficits, the primary driver of high wildfire risk and crop irrigation dependency.

What you can analyze here

The Satalyse API covers every major satellite analysis type for California, USA. These endpoints are most relevant for this location:

Risk Scoring

POST /api/v1/satellite/score-risk

Feature Extraction

POST /api/v1/satellite/extract-features

Change Detection

POST /api/v1/satellite/detect-changes

Code example

This snippet is pre-filled with California, USA's coordinates and calls the Risk Scoring endpoint.

california_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            [-119.45, 36.75],
11            [-119.39, 36.75],
12            [-119.39, 36.81],
13            [-119.45, 36.81],
14            [-119.45, 36.75]
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 California, USA

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