Africa · Climate & Environment
Collection
Climate, weather, and environment data for Africa. Includes IBTrACS storm tracks, flood/drought indices, and CLIMADA risk data. • 248 items • Updated
Datasets:
objectid int64 | site_id int64 | site_pid int64 | site_type string | name_eng string | name string | desig string | desig_eng string | desig_type string | iucn_cat string | int_crit string | realm string | rep_m_area float64 | rep_area float64 | no_take string | no_tk_area float64 | status string | status_yr int64 | restrict string | gov_type string | own_type string | mang_auth string | mang_plan string | cons_obj string | supp_info string | verif string | inlnd_wtrs string | metadataid int64 | prnt_iso3 string | iso3 string | govsubtype string | ownsubtype string | oecm_asmt string | esa_source string | esa_processed string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
4,899 | 902,371 | 902,371 | PA | Moyen Niger II | Zone Humide du Moyen Niger II | Wetland of International Importance (Ramsar Site) | Wetland of International Importance (Ramsar Site) | International | Not Reported | (i);(ii);(iii);(iv);(vii);(viii) | Terrestrial | 0 | 658.5 | Not Applicable | 0 | Designated | 2,004 | Not Restricted | Federal or national ministry or agency | State | Direction de la Faune, de la Chasse et des Parcs et Réserves (DFC/PR) | Management plan is not implemented and not available | Not Applicable | Not Applicable | State Verified | Not Reported | 1,856 | NER | NER | Not Applicable | Not Applicable | Not Applicable | HDX | 2026-04-04 |
Protected and Conserved Areas (WDPCA) in Niger
Publisher: The UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) · Source: HDX · License: cc-by-igo · Updated: 2026-03-03
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 2026-03-03. Geographic scope: NER.
Curated into ML-ready Parquet format by Electric Sheep Africa.
Dataset Characteristics
| Domain | Water, sanitation and hygiene (wash) |
| Unit of observation | Individual-level records |
| Rows (total) | 1 |
| Columns | 35 (8 numeric, 27 categorical, 0 datetime) |
| Train split | 0 rows |
| Test split | 0 rows |
| Geographic scope | NER |
| Publisher | The UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) |
| HDX last updated | 2026-03-03 |
Variables
Geographic — site_type (PA), desig_type (International), status_yr (range 2004.0–2004.0), gov_type, own_type and 4 others.
Identifier / Metadata — objectid (range 4899.0–4899.0), site_id (range 902371.0–902371.0), site_pid (range 902371.0–902371.0), name_eng (Moyen Niger II), name (Zone Humide du Moyen Niger II) and 3 others.
Other — desig (Wetland of International Importance (Ramsar Site)), desig_eng (Wetland of International Importance (Ramsar Site)), iucn_cat (Not Reported), int_crit ((i);(ii);(iii);(iv);(vii);(viii)), realm (Terrestrial) and 13 others.
Quick Start
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-unep-wdpca-ner")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()
print(train.shape)
train.head()
Schema
| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
objectid |
int64 | 0.0% | 4899.0 – 4899.0 (mean 4899.0) |
site_id |
int64 | 0.0% | 902371.0 – 902371.0 (mean 902371.0) |
site_pid |
int64 | 0.0% | 902371.0 – 902371.0 (mean 902371.0) |
site_type |
object | 0.0% | PA |
name_eng |
object | 0.0% | Moyen Niger II |
name |
object | 0.0% | Zone Humide du Moyen Niger II |
desig |
object | 0.0% | Wetland of International Importance (Ramsar Site) |
desig_eng |
object | 0.0% | Wetland of International Importance (Ramsar Site) |
desig_type |
object | 0.0% | International |
iucn_cat |
object | 0.0% | Not Reported |
int_crit |
object | 0.0% | (i);(ii);(iii);(iv);(vii);(viii) |
realm |
object | 0.0% | Terrestrial |
rep_m_area |
float64 | 0.0% | 0.0 – 0.0 (mean 0.0) |
rep_area |
float64 | 0.0% | 658.5 – 658.5 (mean 658.5) |
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% | 2004.0 – 2004.0 (mean 2004.0) |
restrict |
object | 0.0% | |
gov_type |
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% | |
verif |
object | 0.0% | |
inlnd_wtrs |
object | 0.0% | |
metadataid |
int64 | 0.0% | 1856.0 – 1856.0 (mean 1856.0) |
prnt_iso3 |
object | 0.0% | |
iso3 |
object | 0.0% | |
govsubtype |
object | 0.0% | |
ownsubtype |
object | 0.0% | |
oecm_asmt |
object | 0.0% | |
esa_source |
object | 0.0% | |
esa_processed |
object | 0.0% |
Numeric Summary
| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
objectid |
4899.0 | 4899.0 | 4899.0 | 4899.0 |
site_id |
902371.0 | 902371.0 | 902371.0 | 902371.0 |
site_pid |
902371.0 | 902371.0 | 902371.0 | 902371.0 |
rep_m_area |
0.0 | 0.0 | 0.0 | 0.0 |
rep_area |
658.5 | 658.5 | 658.5 | 658.5 |
no_tk_area |
0.0 | 0.0 | 0.0 | 0.0 |
status_yr |
2004.0 | 2004.0 | 2004.0 | 2004.0 |
metadataid |
1856.0 | 1856.0 | 1856.0 | 1856.0 |
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.
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.
Citation
@dataset{hdx_africa_unep_wdpca_ner,
title = {Protected and Conserved Areas (WDPCA) in Niger},
author = {The UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC)},
year = {2026},
url = {https://data.humdata.org/dataset/unep_wdpca_ner},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.
- Downloads last month
- 65