electricsheepafrica/africa-unep-wdpca-mli

Protected and Conserved Areas (WDPCA) in Mali

Publisher: The UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) · Source: HDX · License: cc-by-igo · Updated: 2026-03-15

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Abstract

The World Database on Protected and Conserved Areas (WDPCA) combines the formerly separate World Database on Protected Areas (WDPA) and World Database on Other Effective Area-based Conservation Measures (WD-OECM). The WDPCA is the most comprehensive global database of marine and terrestrial protected areas and other effective area-based conservation measures, updated on a monthly basis, and is one of the key global biodiversity datasets being widely used by scientists, businesses, governments, international secretariats, and others to inform planning, policy decisions, and management.

The WDPCA is part of the Protected Planet Initiative, a joint product of the UN Environment Programme and the International Union for Conservation of Nature (IUCN). The compilation and management of the WDPCA is carried out by the UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC), in collaboration with governments and other stakeholders. Data and information on the world's protected and conserved areas compiled in the WDPCA is used for reporting on progress towards reaching Target 3 of the Kunming-Montreal Global Biodiversity Framework, which calls for 30% of the world’s land and waters to be effectively conserved by 2030.

Additionally, the WDPCA is used for reporting to the UN to track progress towards the 2030 Sustainable Development Goals, tracking of core indicators of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), and providing information for other international assessments and reports including the Global Biodiversity Outlook. UNEP-WCMC and IUCN periodically release the Protected Planet Report on the status of the world's protected and conserved areas.

Many platforms are incorporating the WDPCA to provide integrated information to diverse users, including businesses and governments, in a range of sectors. For example, the WDPCA is included in the Integrated Biodiversity Assessment Tool (IBAT), an innovative decision support tool that gives commercial users easy access to up-to-date information that allows them to identify biodiversity risks and opportunities within a project boundary.

The reach of the WDPCA is further enhanced by the UN Biodiversity Lab as well as services developed by other parties, such as the Global Forest Watch and the Digital Observatory for Protected Areas, which provide decision makers with access to monitoring and alert systems that allow whole landscapes to be managed better. Together, these applications of the WDPCA demonstrate the growing value and significance of the Protected Planet initiative.

Each row in this dataset represents individual-level records. Data was last updated on HDX on 2026-03-15. Geographic scope: MLI.

Curated into ML-ready Parquet format by Electric Sheep Africa.

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Dataset Characteristics

Domain	Water, sanitation and hygiene (wash)
Unit of observation	Individual-level records
Rows (total)	136
Columns	39 (12 numeric, 27 categorical, 0 datetime)
Train split	108 rows
Test split	27 rows
Geographic scope	MLI
Publisher	The UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC)
HDX last updated	2026-03-15

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Variables

Geographic — site_type (PA), desig_type (National, International), status_yr (range 1935.0–2016.0), gov_type, own_type and 4 others.

Identifier / Metadata — objectid (range 1240.0–241911.0), site_id (range 2321.0–555703870.0), site_pid (range 2321.0–555703870.0), name_eng (Gourma Elephant Reserve, Sayes, Fanzana), name (Réserve partielle de faune dite des Eléphants du Gourma, Forêt classée de Sayes, Forêt classée de Fanzana) and 3 others.

Other — desig (Forêt Classée, Réserve de faune, Zone d'Intérêt Cynégétique), desig_eng (Classified Forest, Total Wildlife Reserve, Hunting Area), iucn_cat (IV, VI, II), int_crit (Not Applicable, (ii);(iii);(v);(vi);(viii), (v);(vii)), realm (Terrestrial) and 17 others.

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-unep-wdpca-mli")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

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Schema

Column	Type	Null %	Range / Sample Values
objectid	int64	0.0%	1240.0 – 241911.0 (mean 213011.8456)
site_id	int64	0.0%	2321.0 – 555703870.0 (mean 510753904.5882)
site_pid	int64	0.0%	2321.0 – 555703870.0 (mean 510753904.5882)
site_type	object	0.0%	PA
name_eng	object	0.0%	Gourma Elephant Reserve, Sayes, Fanzana
name	object	0.0%	Réserve partielle de faune dite des Eléphants du Gourma, Forêt classée de Sayes, Forêt classée de Fanzana
desig	object	0.0%	Forêt Classée, Réserve de faune, Zone d'Intérêt Cynégétique
desig_eng	object	0.0%	Classified Forest, Total Wildlife Reserve, Hunting Area
desig_type	object	0.0%	National, International
iucn_cat	object	0.0%	IV, VI, II
int_crit	object	0.0%	Not Applicable, (ii);(iii);(v);(vi);(viii), (v);(vii)
realm	object	0.0%	Terrestrial
rep_m_area	float64	0.0%	0.0 – 0.0 (mean 0.0)
gis_m_area	float64	0.0%	0.0 – 0.0 (mean 0.0)
rep_area	float64	0.0%	0.0 – 41195.0 (mean 827.9486)
gis_area	float64	0.0%	1.3405 – 40801.9785 (mean 731.1303)
no_take	object	0.0%	Not Applicable
no_tk_area	float64	0.0%	0.0 – 0.0 (mean 0.0)
status	object	0.0%
status_yr	int64	0.0%	1935.0 – 2016.0 (mean 1962.6544)
restrict	object	0.0%
gov_type	object	0.0%
verif	object	0.0%
inlnd_wtrs	object	0.0%
own_type	object	0.0%
mang_auth	object	0.0%
mang_plan	object	0.0%
cons_obj	object	0.0%
supp_info	object	0.0%
metadataid	int64	0.0%	946.0 – 2123.0 (mean 1977.4706)
prnt_iso3	object	0.0%
iso3	object	0.0%
govsubtype	object	0.0%
ownsubtype	object	0.0%
oecm_asmt	object	0.0%
shape_area	float64	0.0%	0.0001 – 3.4314 (mean 0.0614)
shape_length	float64	0.0%	0.0551 – 22.3551 (mean 0.8159)
esa_source	object	0.0%
esa_processed	object	0.0%

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Numeric Summary

Column	Min	Max	Mean	Median
objectid	1240.0	241911.0	213011.8456	241843.5
site_id	2321.0	555703870.0	510753904.5882	555703802.5
site_pid	2321.0	555703870.0	510753904.5882	555703802.5
rep_m_area	0.0	0.0	0.0	0.0
gis_m_area	0.0	0.0	0.0	0.0
rep_area	0.0	41195.0	827.9486	66.25
gis_area	1.3405	40801.9785	731.1303	58.9088
no_tk_area	0.0	0.0	0.0	0.0
status_yr	1935.0	2016.0	1962.6544	1950.0
metadataid	946.0	2123.0	1977.4706	1984.0
shape_area	0.0001	3.4314	0.0614	0.0049
shape_length	0.0551	22.3551	0.8159	0.3373

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Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (N/A, null, none, -, unknown, no data, #N/A) were unified to NaN. The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

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Limitations

• Data originates from The UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) and has not been independently validated by ESA.
• Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_unep_wdpca_mli,
  title     = {Protected and Conserved Areas (WDPCA) in Mali},
  author    = {The UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC)},
  year      = {2026},
  url       = {https://data.humdata.org/dataset/unep_wdpca_mli},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.