Data provided in this dataverse is collected, acquired and processed within the EnerSHelF (Energy Supply for Healthcare Facilities in Ghana) project financed by the German Federal Ministry of Education and Research (BMBF). Funding period: 01.06.2019 – 31.03.2023. BMBF funding grant number 03SF0567C. For additional information, please visit: https://enershelf.de/
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31 to 40 of 46 Results
Mar 9, 2023 - I Geospatial Analysis
Cader, Catherina; Andrade, Andrés, 2023, "Population Settlements in Ghana", https://doi.org/10.7910/DVN/FLBK2M, Harvard Dataverse, V1
This dataset contains all population settlements in Ghana used in this study, based on the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) and High Resolution Settlement Layer (HRSL) data. Columns and their unit are: 1) type (BUA, SSA, or hamlet), 2) "Area_km2" [km^2], 3) "Region", 4) "District", 5) "Pop2020" as absolute...
Unknown - 8.8 MB - MD5: e484185845715597086a2101b0117864
Geopackage with all selected settlements, from SSAs to Hamlets, which were used for the pre-feasibility analysis in this study. All settlements are taken from GRID3 data created by the Center for International Earth Science Information Network (CIESIN), at Columbia University.
Unknown - 65.6 MB - MD5: b200cc8911642dfe42122f6ff2cb0a81
Geopackage with Built-up areas in Ghana, i.e. areas with moderately-to-densely-spaced buildings, a visible grid of streets and blocks, and areas greater than 0,4 square kms (CIESIN, 2020).
Unknown - 732.1 MB - MD5: f6924a1416709ddf77b057961acbcd47
Geopackage with hamlets in Ghana, i.e. a collection of several compounds or sleeping houses in isolation from small settlements or urban areas (CIESIN, 2020)
Unknown - 171.3 MB - MD5: 094b63ecf404c856810207d852cd17eb
Geopackage with small settlement areas in Ghana, i.e. settled areas of permanently inhabited structures and compounds of a few hundred to a few thousand inhabitants, characterised by having 50 or more buildings and not being a BUA (CIESIN, 2020).
Mar 9, 2023 - Offgridders input data
MS Excel Spreadsheet - 750.7 KB - MD5: 1f7809d18c710fa2cc224fcbbf835f3b
Mar 9, 2023 - Offgridders input data
MS Excel Spreadsheet - 750.8 KB - MD5: 5914defaf1ab82557c6560c61cade313
Comma Separated Values - 194.7 KB - MD5: 827193aef565fea17883995d7f0e3d51
Comma Separated Values - 643.1 KB - MD5: e3093f4a97aa90b0e2a7d3fb60cac11c
MS Excel Spreadsheet - 13.6 KB - MD5: 3ac9a998741c4bc3372e7e0db3ae828b
https://github.com/rl-institut/RAMP/blob/dev/docs/input_parameters.md
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