Risk indicators — quickstart (live)¶

The risk-indicators backend pulls country/admin-indexed risk screening from three sources behind one interface:

GFDRR ThinkHazard! — a hazard rating (Very low → High) per hazard type and admin division; public, no key.
INFORM Risk (JRC) — the composite humanitarian-risk index and its sub-dimensions, scored 0–10 per country; public, no key.
Global Forest Watch Data API — forest indicators and admin geometry; needs a free API key (covered in the Global Forest Watch notebook).

Unlike the raster backends there is no bounding box or grid — you name a dataset id in variables= and a country with country= (an ISO3 code), and you get back a tidy pandas.DataFrame. This notebook covers the two public sources (ThinkHazard! and INFORM), fetched live.

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import tempfile

import pandas as pd

from earthlens.earthlens import EarthLens

OUT = tempfile.mkdtemp()  # tabular downloads also write a CSV here
import tempfile

import pandas as pd

from earthlens.earthlens import EarthLens

OUT = tempfile.mkdtemp()  # tabular downloads also write a CSV here

ThinkHazard! — one hazard for a country¶

variables=["thinkhazard:flood_river"] selects the river-flood rating; country="KEN" names the country as an ISO3 code. The backend resolves that ISO3 to ThinkHazard's numeric ADM0 division code and returns one row with the qualitative level / level_title.

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flood = EarthLens(
    data_source="risk-indicators",
    variables=["thinkhazard:flood_river"],
    country="KEN",
    path=OUT,
).download()

flood
flood = EarthLens(
    data_source="risk-indicators",
    variables=["thinkhazard:flood_river"],
    country="KEN",
    path=OUT,
).download()

flood

2026-06-27 04:27:27 | INFO | pyramids.base.config | Logging is configured.

2026-06-27 04:27:29.305 | INFO     | earthlens.risk_indicators.backend:_log_citation:419 - RiskIndicators source citation: GFDRR ThinkHazard! — https://thinkhazard.org (public domain).

2026-06-27 04:27:29.310 | INFO     | earthlens.risk_indicators.backend:download:377 - RiskIndicators thinkhazard:flood_river: 1 row(s) written to C:\Users\main\AppData\Local\Temp\tmp062iwcx3\risk_thinkhazard_flood_river.csv.

Out[2]:

	country	admin_code	hazard	hazard_type	level	level_title
0	KEN	133	FL	River flood	HIG	High

The level is ThinkHazard's coded rating (VLO/LOW/MED/HIG) and level_title its human label; admin_code is the resolved ADM0 code (133 for Kenya). download() also wrote the row to a CSV under path.

All eleven hazards at once¶

The thinkhazard:all dataset returns every hazard ThinkHazard! screens for the division in a single call — handy for a quick risk profile.

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profile = EarthLens(
    data_source="risk-indicators",
    variables=["thinkhazard:all"],
    country="KEN",
    path=OUT,
).download()

print("hazards:", len(profile))
profile
profile = EarthLens(
    data_source="risk-indicators",
    variables=["thinkhazard:all"],
    country="KEN",
    path=OUT,
).download()

print("hazards:", len(profile))
profile

2026-06-27 04:27:29.640 | INFO     | earthlens.risk_indicators.backend:_log_citation:419 - RiskIndicators source citation: GFDRR ThinkHazard! — https://thinkhazard.org (public domain).

2026-06-27 04:27:29.643 | INFO     | earthlens.risk_indicators.backend:download:377 - RiskIndicators thinkhazard:all: 11 row(s) written to C:\Users\main\AppData\Local\Temp\tmp062iwcx3\risk_thinkhazard_all.csv.

hazards: 11

Out[3]:

	country	admin_code	hazard	hazard_type	level	level_title
0	KEN	133	FL	River flood	HIG	High
1	KEN	133	UF	Urban flood	HIG	High
2	KEN	133	CF	Coastal flood	HIG	High
3	KEN	133	EQ	Earthquake	MED	Medium
4	KEN	133	LS	Landslide	HIG	High
5	KEN	133	TS	Tsunami	MED	Medium
6	KEN	133	VA	Volcano	HIG	High
7	KEN	133	CY	Cyclone	VLO	Very low
8	KEN	133	DG	Water scarcity	MED	Medium
9	KEN	133	EH	Extreme heat	MED	Medium
10	KEN	133	WF	Wildfire	HIG	High

INFORM Risk — a composite country score¶

inform:risk is the headline INFORM composite index (0–10). The "inform" alias and the "risk-indicators" key both reach the same backend, so either works as data_source=.

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risk = EarthLens(
    data_source="inform",
    variables=["inform:risk"],
    country="KEN",
    path=OUT,
).download()

risk
risk = EarthLens(
    data_source="inform",
    variables=["inform:risk"],
    country="KEN",
    path=OUT,
).download()

risk

2026-06-27 04:27:29.955 | INFO     | earthlens.risk_indicators.backend:_log_citation:419 - RiskIndicators source citation: INFORM Risk Index, European Commission Joint Research Centre (JRC), Disaster Risk Management Knowledge Centre — https://drmkc.jrc.ec.europa.eu/inform-index.

2026-06-27 04:27:29.958 | INFO     | earthlens.risk_indicators.backend:download:377 - RiskIndicators inform:risk: 1 row(s) written to C:\Users\main\AppData\Local\Temp\tmp062iwcx3\risk_inform_risk.csv.

Out[4]:

	iso3	indicator_id	indicator_score	validity_year
0	KEN	INFORM	6.2	0

One row per country: indicator_score is the 0–10 composite (higher = more at risk), iso3 the country, validity_year the model release tag.

Omit country= and INFORM returns every country — the whole global table in one frame, ready to rank or join.

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world = EarthLens(
    data_source="inform",
    variables=["inform:risk"],
    path=OUT,
).download()

print("countries:", len(world))
world.sort_values("indicator_score", ascending=False).head(5)
world = EarthLens(
    data_source="inform",
    variables=["inform:risk"],
    path=OUT,
).download()

print("countries:", len(world))
world.sort_values("indicator_score", ascending=False).head(5)

2026-06-27 04:27:30.273 | INFO     | earthlens.risk_indicators.backend:_log_citation:419 - RiskIndicators source citation: INFORM Risk Index, European Commission Joint Research Centre (JRC), Disaster Risk Management Knowledge Centre — https://drmkc.jrc.ec.europa.eu/inform-index.

2026-06-27 04:27:30.276 | INFO     | earthlens.risk_indicators.backend:download:377 - RiskIndicators inform:risk: 191 row(s) written to C:\Users\main\AppData\Local\Temp\tmp062iwcx3\risk_inform_risk.csv.

countries: 191

Out[5]:

	iso3	indicator_id	indicator_score
156	SSD	INFORM	8.5
154	SOM	INFORM	8.1
187	YEM	INFORM	8.1
34	COD	INFORM	8.0
165	TCD	INFORM	7.9

The `country=` selector¶

country= is always an ISO3 code ("KEN", "NGA", "BRA", …). What happens to it depends on the source:

ThinkHazard! resolves the ISO3 to a GAUL 2015 ADM0 division code (the numeric key its API uses) via the catalog's bundled admin_codes: table. For a sub-national division, pass a raw admin_code= instead.
INFORM filters its global table to that one ISO3 (omit it for all countries, as above).
GFW uses the ISO3 as the SQL / geostore key (see the GFW notebook).

Takeaway¶

EarthLens(data_source="risk-indicators", variables=[<id>], country=<ISO3>) returns a tidy DataFrame — no bbox, no grid.
ThinkHazard! gives qualitative hazard ratings per division (thinkhazard:all for the full profile); INFORM gives 0–10 composite scores (omit country= for the whole world).
Both are public and keyless. The third source, Global Forest Watch, needs a free key — see the catalog & behaviour notebook for the full dataset list and the GFW notebook for the keyed forest indicators.