Land SubsidenceFlash FloodingUrban Heat Island

Satellite Analysis for Mexico City, Mexico

Name: Satalyse
Author: Satalyse

Mexico City is built on an ancient lake bed and is sinking at 20–30 cm per year in some districts as aquifer extraction continues, one of the most dramatic urban subsidence events on Earth. Combined with flash flood risk from the surrounding mountains and loss of permeable surface to impervious urban cover, the metropolitan area represents a high-value target for risk scoring, change detection, and temporal surface deformation analysis.

19.43°, -99.13°

Highland subtropical with a wet season (May–Oct) when orographic rainfall causes frequent flash flooding; the dry season provides clear imagery windows for multi-temporal analysis.

What you can analyze here

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

Temporal Analysis

POST /api/v1/satellite/analyze-temporal-trends

Risk Scoring

POST /api/v1/satellite/score-risk

Change Detection

POST /api/v1/satellite/detect-changes

Anomaly Detection

POST /api/v1/satellite/detect-anomalies

Code example

This snippet is pre-filled with Mexico City, Mexico's coordinates and calls the Temporal Analysis endpoint.

mexico-city_analysis.py

1"color:#c084fc">import requests
2
3response = requests.post(
4    "https://api.satalyse.dev/api/v1/satellite/analyze-temporal-trends",
5    headers={"Authorization": "Bearer sat_sk_live_..."},
6    json={
7        "geometry": {
8            "type": "Polygon",
9            "coordinates": [[
10            [-99.16, 19.4],
11            [-99.1, 19.4],
12            [-99.1, 19.46],
13            [-99.16, 19.46],
14            [-99.16, 19.4]
15            ]]
16        },
17        "start_date": "2023-01-01",
18        "end_date":   "2025-01-01",
19        "interval": "monthly",
20        "metric": "NDVI",
21        "forecast_days": 90
22    }
23)
24
25data = response.json()
26trend = data["trend_analysis"]
27"color:#c084fc">print("color:#c084fc">f"Trend: {trend['overall_trend']}")
28"color:#c084fc">print("color:#c084fc">f"Rate o">f change: {trend['rate_of_change_per_month']:.4">f} / month")

Data sources used for Mexico City, Mexico

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