Calibrated solar resource of the 340 sub-prefectures (GHI, DNI, P50, P90)

Kuma ScienceAnnual340 sub-prefecturesSatellite calibrated on ground dataCC BY 4.0

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340 rows selected

This is the Parquet file the table reads. It opens in pandas, R, DuckDB or QGIS.

Parquet (78.7 KB) SHA-256 252c3b2e499353149c42bb6b04da363ce4ff051431574f159d9566c641d3d2dd

The Parquet file can be read straight from its URL, without downloading it first.

import pandas as pd

df = pd.read_parquet("https://kumascience.com/data/jeux/sous-prefectures-calees.parquet")
df.head()

library(arrow)

df <- read_parquet("https://kumascience.com/data/jeux/sous-prefectures-calees.parquet")
head(df)

INSTALL httpfs; LOAD httpfs;

SELECT *
FROM read_parquet('https://kumascience.com/data/jeux/sous-prefectures-calees.parquet')
LIMIT 10;

The layer is served by the Atlas map server. You can add it to QGIS or query it over WFS.

Layer: kuma_ouvert:v_sous_prefectures_cale_v3
WFS GetCapabilities: https://atlas.kumascience.com/geoserver/kuma_ouvert/ows?service=WFS&version=2.0.0&request=GetCapabilities
GeoJSON: https://atlas.kumascience.com/geoserver/kuma_ouvert/ows?service=WFS&version=2.0.0&request=GetFeature&typeNames=kuma_ouvert:v_sous_prefectures_cale_v3&outputFormat=application/json&count=10

CC BY 4.0. Atlas solaire de la Guinée, opéré par Kuma Science, CC BY 4.0.