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electricsheepasia/asia-aid-flows-unosat-live-web-map-m-6-0-afghanistan-ea

UNOSAT Live web map -M 6.0 Afghanistan Earthquake (31 August 2025) Publisher: United Nations Satellite Centre (UNOSAT) · Source: HDX · License: cc-by-sa · Updated: 2026-03-24 Abstract UNOSAT code: EQ20250901AFG, GDACS ID: 1498339 This application provides geospatial information on ongoing satellite based-assessment related with the 6.0 M magnitude earthquake in Afghanistan on the 31 August 2025 Important note: The boundaries and names shown, and the… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-aid-flows-unosat-live-web-map-m-6-0-afghanistan-ea.

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Dataset Card

UNOSAT Live web map -M 6.0 Afghanistan Earthquake (31 August 2025)

Publisher: United Nations Satellite Centre (UNOSAT) · Source: HDX · License: cc-by-sa · Updated: 2026-03-24


Abstract

UNOSAT code: EQ20250901AFG, GDACS ID: 1498339 This application provides geospatial information on ongoing satellite based-assessment related with the 6.0 M magnitude earthquake in Afghanistan on the 31 August 2025

Important note: The boundaries and names shown, and the designations used on this map do not imply official end

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2026-03-24. Geographic scope: AFG.

Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).


Dataset Characteristics

DomainDemographics and population
Unit of observationFirst-level administrative unit observations
Rows (total)22
Columns7 (4 numeric, 3 categorical, 0 datetime)
Train split17 rows
Test split4 rows
Geographic scopeAFG
PublisherUnited Nations Satellite Centre (UNOSAT)
HDX last updated2026-03-24

Variables

Geographic — province (Badakhshan, Baghlan, Ghazni), population_in_v_moderate_zone (range 124.85–1018709.3446), population_in_below_iv_light_zone (range 0.0–4192357.6848), population_in_below_iii_weak_zone (range 7020.1023–10960950.848).

Outcome / Measurement — total (range 19666.4974–17773523.9306).

Identifier / Metadata — esa_source (HDX), esa_processed (2026-05-06).


Quick Start

python
from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/asia-aid-flows-unosat-live-web-map-m-6-0-afghanistan-ea")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

Schema

ColumnTypeNull %Range / Sample Values
provinceobject4.5%Badakhshan, Baghlan, Ghazni
population_in_v_moderate_zonefloat6477.3%124.85 – 1018709.3446 (mean 407483.7378)
population_in_below_iv_light_zonefloat6431.8%0.0 – 4192357.6848 (mean 558981.0246)
population_in_below_iii_weak_zonefloat6418.2%7020.1023 – 10960950.848 (mean 1217883.4276)
totalfloat6418.2%19666.4974 – 17773523.9306 (mean 1974835.9923)
esa_sourceobject0.0%HDX
esa_processedobject0.0%2026-05-06

Numeric Summary

ColumnMinMaxMeanMedian
population_in_v_moderate_zone124.851018709.3446407483.7378384652.8841
population_in_below_iv_light_zone0.04192357.6848558981.0246225213.1753
population_in_below_iii_weak_zone7020.102310960950.8481217883.4276438303.368
total19666.497417773523.93061974835.9923674198.7684

Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snakecase. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. 3 column(s) with >80% missing values were removed: `populationinviiiseverezone`, `populationinviiverystrongzone, populationinvistrongzone`. 3 exact duplicate rows were removed. The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.


Limitations

  • —Data originates from United Nations Satellite Centre (UNOSAT) and has not been independently validated by ESA.
  • —Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
  • —The following columns have >20% missing values and should be treated with caution in modelling: population_in_v_moderate_zone, population_in_below_iv_light_zone.
  • —Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

Citation

bibtex
@dataset{hdx_asia_aid_flows_unosat_live_web_map_m_6_0_afghanistan_ea,
  title     = {UNOSAT Live web map -M 6.0 Afghanistan Earthquake (31 August 2025)},
  author    = {United Nations Satellite Centre (UNOSAT)},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/unosat-live-web-map-m-6-0-afghanistan-earthquake-31-august-2025},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.