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... |
Mar 9, 2023 -
Population Settlements in Ghana
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. |
Mar 9, 2023 -
Population Settlements in Ghana
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). |
Mar 9, 2023 -
Population Settlements in Ghana
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) |
Mar 9, 2023 -
Population Settlements in Ghana
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
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Mar 9, 2023 -
Offgridders input data
MS Excel Spreadsheet - 750.8 KB -
MD5: 5914defaf1ab82557c6560c61cade313
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Mar 9, 2023 -
Offgridders energy system modelling results
Comma Separated Values - 194.7 KB -
MD5: 827193aef565fea17883995d7f0e3d51
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Mar 9, 2023 -
Offgridders energy system modelling results
Comma Separated Values - 643.1 KB -
MD5: e3093f4a97aa90b0e2a7d3fb60cac11c
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Mar 9, 2023 -
Demand estimation tool (RAMP) input data
MS Excel Spreadsheet - 13.6 KB -
MD5: 3ac9a998741c4bc3372e7e0db3ae828b
https://github.com/rl-institut/RAMP/blob/dev/docs/input_parameters.md |