electricsheepasia/asia-owid-area-burned-wildfires-by-type
Area Burned Wildfires By Type | Asia (Our World in Data) ๐ 1,104 observations ยท 48 Asia countries ยท 2002โ2024 ยท Repackaged by Electric Sheep Asia TL;DR This dataset contains 1,104 observations of Area Burned Wildfires By Type data across 48 Asia countries, spanning 2002โ2024. About the source Source: Our World in Data Publisher: Our World in Data License: cc-by-4.0 Topic: Area Burned Wildfires By Type Geographic coverage 48โฆ See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-owid-area-burned-wildfires-by-type.
Area Burned Wildfires By Type | Asia (Our World in Data)
๐ 1,104 observations ยท 48 Asia countries ยท 2002โ2024 ยท Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)
TL;DR
This dataset contains 1,104 observations of Area Burned Wildfires By Type data across 48 Asia countries, spanning 2002โ2024.
About the source
- Source: Our World in Data
- Publisher: Our World in Data
- License: cc-by-4.0
- Topic: Area Burned Wildfires By Type
Geographic coverage
48 Asia countries ยท top rows shown below, sorted by row count:
Schema
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepasia/asia-owid-area-burned-wildfires-by-type")
df = ds["train"].to_pandas()
print(df.head())Filter to one country
indonesia = df[df["country_iso3"] == "IDN"]Time-series for a single indicator
sample = df.sort_values("year")
sample.plot(x="year", y="Shrublands and grasslands")Citation
@misc{asia_owid_area_burned_wildfires_by_type_2024,
title = {Area Burned Wildfires By Type | Asia (Our World in Data)},
author = {Our World in Data},
year = {2024},
url = {https://ourworldindata.org/grapher/area-burned-wildfires-by-type},
publisher = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-owid-area-burned-wildfires-by-type}}
}License
Released under cc-by-4.0.
Original data ยฉ Our World in Data. When using this dataset, please cite both the original source above and the Electric Sheep Asia repackaging.
About Electric Sheep
Electric Sheep Asia is part of the Electric Sheep mission: a unified, ML-ready data layer for Asia on HuggingFace. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.
Browse the full collection: huggingface.co/electricsheepasia
Provenance: ingested 2026-06-02 via the Electric Sheep pipeline. Source URL: https://ourworldindata.org/grapher/area-burned-wildfires-by-type
