Datasets:

electricsheepasia
/

asia-owid-above-ground-biomass-in-forest-per-hectare

country_name string	country_iso3 string	year int64	Above-ground biomass in forest (tonnes per hectare) float64
Armenia	ARM	2,000	81.38
Armenia	ARM	2,010	80.06
Armenia	ARM	2,015	80.72
Armenia	ARM	2,016	80.72
Armenia	ARM	2,017	80.72
Armenia	ARM	2,018	80.72
Armenia	ARM	2,019	80.72
Armenia	ARM	2,020	80.72
Bangladesh	BGD	2,000	62.82
Bangladesh	BGD	2,010	62.82
Bangladesh	BGD	2,015	62.82
Bangladesh	BGD	2,016	62.82
Bangladesh	BGD	2,017	62.82
Bangladesh	BGD	2,018	62.82
Bangladesh	BGD	2,019	62.82
Bangladesh	BGD	2,020	62.82
Bhutan	BTN	2,000	269.32
Bhutan	BTN	2,010	269.32
Bhutan	BTN	2,015	269.32
Bhutan	BTN	2,016	269.32
Bhutan	BTN	2,017	269.32
Bhutan	BTN	2,018	269.32
Bhutan	BTN	2,019	269.32
Bhutan	BTN	2,020	269.32
Brunei	BRN	2,000	247
Brunei	BRN	2,010	247
Brunei	BRN	2,015	247
Brunei	BRN	2,016	247
Brunei	BRN	2,017	247
Brunei	BRN	2,018	247
Brunei	BRN	2,019	247
Brunei	BRN	2,020	247
Cambodia	KHM	2,000	69.3
Cambodia	KHM	2,010	69.3
Cambodia	KHM	2,015	69.3
Cambodia	KHM	2,016	69.3
Cambodia	KHM	2,017	69.3
Cambodia	KHM	2,018	69.3
Cambodia	KHM	2,019	69.3
Cambodia	KHM	2,020	69.3
China	CHN	2,000	54.54
China	CHN	2,010	55.72
China	CHN	2,015	60.75
China	CHN	2,016	61.76
China	CHN	2,017	62.52
China	CHN	2,018	63.26
China	CHN	2,019	64
China	CHN	2,020	64.72
Cyprus	CYP	2,000	27.73
Cyprus	CYP	2,010	34.44
Cyprus	CYP	2,015	38.64
Cyprus	CYP	2,016	39.3
Cyprus	CYP	2,017	39.94
Cyprus	CYP	2,018	40.62
Cyprus	CYP	2,019	41.26
Cyprus	CYP	2,020	41.93
East Timor	TLS	2,000	150
East Timor	TLS	2,010	150
East Timor	TLS	2,015	150
East Timor	TLS	2,016	150
East Timor	TLS	2,017	150
East Timor	TLS	2,018	150
East Timor	TLS	2,019	150
East Timor	TLS	2,020	150
Georgia	GEO	2,000	116.5
Georgia	GEO	2,010	119.34
Georgia	GEO	2,015	119.34
Georgia	GEO	2,016	119.34
Georgia	GEO	2,017	119.34
Georgia	GEO	2,018	119.34
Georgia	GEO	2,019	119.34
Georgia	GEO	2,020	119.34
India	IND	2,000	69.78
India	IND	2,010	67.61
India	IND	2,015	68.7
India	IND	2,016	68.7
India	IND	2,017	68.7
India	IND	2,018	68.7
India	IND	2,019	68.7
India	IND	2,020	68.7
Indonesia	IDN	2,000	178.33
Indonesia	IDN	2,010	179.01
Indonesia	IDN	2,015	178.95
Indonesia	IDN	2,016	178.89
Indonesia	IDN	2,017	178.95
Indonesia	IDN	2,018	178.95
Indonesia	IDN	2,019	178.95
Indonesia	IDN	2,020	178.95
Iran	IRN	2,000	137.17
Iran	IRN	2,010	138.44
Iran	IRN	2,015	138.44
Iran	IRN	2,016	138.31
Iran	IRN	2,017	138.2
Iran	IRN	2,018	137.99
Iran	IRN	2,019	137.78
Iran	IRN	2,020	137.67
Iraq	IRQ	2,000	52.88
Iraq	IRQ	2,010	52.69
Iraq	IRQ	2,015	52.46
Iraq	IRQ	2,016	52.21

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Above Ground Biomass In Forest Per Hectare | Asia (Our World in Data)

🌏 336 observations · 42 Asia countries · 2000–2020 · Repackaged by Electric Sheep Asia

TL;DR

This dataset contains 336 observations of Above Ground Biomass In Forest Per Hectare data across 42 Asia countries, spanning 2000–2020.

About the source

Source: Our World in Data
Publisher: Our World in Data
License: cc-by-4.0
Topic: Above Ground Biomass In Forest Per Hectare

Geographic coverage

42 Asia countries · top rows shown below, sorted by row count:

Country	Rows	First year	Last year
`ARE`	8	2000	2020
`ARM`	8	2000	2020
`BGD`	8	2000	2020
`BRN`	8	2000	2020
`BTN`	8	2000	2020
`CHN`	8	2000	2020
`CYP`	8	2000	2020
`GEO`	8	2000	2020
`IDN`	8	2000	2020
`IND`	8	2000	2020
`IRN`	8	2000	2020
`IRQ`	8	2000	2020
`ISR`	8	2000	2020
`JOR`	8	2000	2020
`JPN`	8	2000	2020
...	27 more countries

Schema

Column	Type	Description	Example
`country_name`	`string`	—	`Armenia`
`country_iso3`	`string`	—	`ARM`
`year`	`int64`	—	`2000`
`Above-ground biomass in forest (tonnes per hectare)`	`float64`	—	`81.38`

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepasia/asia-owid-above-ground-biomass-in-forest-per-hectare")
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="Above-ground biomass in forest (tonnes per hectare)")

Citation

@misc{asia_owid_above_ground_biomass_in_forest_per_hectare_2020,
  title        = {Above Ground Biomass In Forest Per Hectare | Asia (Our World in Data)},
  author       = {Our World in Data},
  year         = {2020},
  url          = {https://ourworldindata.org/grapher/above-ground-biomass-in-forest-per-hectare},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-owid-above-ground-biomass-in-forest-per-hectare}}
}

License

Released under cc-by-4.0.

Original data © 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/above-ground-biomass-in-forest-per-hectare

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