Find research datasets worth reusing

opencc-by-4.0Jan 2021View details →

qdgc Eritrea

QDGC tables delivered in geopackage file - - - - - - - - - - - - - - - - - - - - - - QDGC represents a way of making (almost) equal area squares covering a specific area to represent specific qualities of the area covered. The squares themselves are based on the degree squares covering earth. Around the equator we have 360 longitudinal lines , and from the north to the south pole we have 180 latitudinal lines. Together this gives us 64800 segments or tiles covering earth. Within each geopackage file you will find a number of tables with these names: -tbl_qdgc_01 -tbl_qdgc_02 -tbl_qdgc_03 -tbl_qdgc_04 -tbl_qdgc_05 -etc The attributes for each table are: qdgc Unique Quarter Degree Grid Cell reference string area_reference Country level_qdgc QDGC level cellsize degrees decimal degree for the longitudal and latitudal length of the cell lon_center Longitude center of the cell lat_center Latitudal center of the cell area_km2 Calculated area for the cell geom Geometry Metadata -------- Geodata GCS_WGS_1984 Datum: D_WGS_1984 Prime Meridian: 0 Areas are calculated with different versions of Albers Equal Area Conic using the PostGIS function st_area. For the African continent I have used Africa Albers Equal Area Conic which will look like this: - st_area(st_transform(geom, 102022))/1000000) Licensing --------- Creative Commons Attribution 4.0 International Conditions ---------- Delivered to the user as-is. No guarantees. If you find errors, please tell me and I will try to fix it. Suggestions for improvements can be addressed to the github repository: https://github.com/ragnvald/qdgc Thankyou -------- The work has over the years been supported and received advice and moral support from many organisations and stakeholders. Here are some of them: - Tanzania Wildlife Research Institute - Dept of Biology, NTNU, Norway - Norwegian Environment Agency - Eivin Røskaft, Steven Prager, Howard Frederick, Julian Blanc, Honori Maliti, Paul Ramsey References ---------- * http://en.wikipedia.org/wiki/QDGC * http://www.mindland.com/wp/projects/quarter-degree-grid-cells/about-qdgc/ * http://en.wikipedia.org/wiki/Lambert_azimuthal_equal-area_projection * http://www.safe.com Ragnvald Larsen Trondheim 23rd of January, 2021 ragnvald@mindland.com www.mindland.com

opencc-by-sa-4.0Dec 2023View details →

Infrastructure Climate Resilience Assessment Data Starter Kit for Eritrea

This starter data kit collects extracts from global, open datasets relating to climate hazards and infrastructure systems. These extracts are derived from global datasets which have been clipped to the national scale (or subnational, in cases where national boundaries have been split, generally to separate outlying islands or non-contiguous regions), using Natural Earth (2023) boundaries, and is not meant to express an opinion about borders, territory or sovereignty. Human-induced climate change is increasing the frequency and severity of climate and weather extremes. This is causing widespread, adverse impacts to societies, economies and infrastructures. Climate risk analysis is essential to inform policy decisions aimed at reducing risk. Yet, access to data is often a barrier, particularly in low and middle-income countries. Data are often scattered, hard to find, in formats that are difficult to use or requiring considerable technical expertise. Nevertheless, there are global, open datasets which provide some information about climate hazards, society, infrastructure and the economy. This "data starter kit" aims to kickstart the process and act as a starting point for further model development and scenario analysis. Hazards: <ul> <li>coastal and river flooding (Ward et al, 2020; Baugh et al, 2024)</li> <li>extreme heat and drought (Russell et al 2023, derived from Lange et al, 2020)</li> <li>tropical cyclone wind speeds (Russell 2022, derived from Bloemendaal et al 2020 and Bloemendaal et al 2022)</li> </ul> Exposure: <ul> <li>population (Schiavina et al, 2023)</li> <li>built-up area (Pesaresi et al, 2023)</li> <li>roads (OpenStreetMap, 2025)</li> <li>railways (OpenStreetMap, 2025)</li> <li>power plants (Global Energy Observatory et al, 2018)</li> <li>power transmission lines (Arderne et al, 2020)</li> </ul> Contextual information: <ul> <li>elevation (European Union and ESA, 2021)</li> <li>land-use and land cover (Copernicus Climate Change Service and Climate Data Store, 2019)</li> <li>administrative boundaries from geoBoundaries (Runfola et al., 2020)</li> </ul> The spatial intersection of hazard and exposure datasets is a first step to analyse vulnerability and risk to infrastructure and people. To learn more about related concepts, there is a free short course available through the Open University on <a href="https://www.open.edu/openlearncreate/course/view.php?id=12278">Infrastructure and Climate Resilience</a>. This <a href="https://opsis.eci.ox.ac.uk/courses/2-infra-for-resil/">overview of the course</a> has more details. These Python libraries may be a useful place to start analysis of the data in the packages produced by this workflow: <ul> <li> <a href="https://github.com/tomalrussell/snkit"><code>snkit</code></a> helps clean network data </li> <li> <a href="https://github.com/nismod/snail"><code>nismod-snail</code></a> is designed to help implement infrastructure exposure, damage and risk calculations </li> </ul> The <a href="https://github.com/nismod/open-gira"><code>open-gira</code></a> repository contains a larger workflow for global-scale open-data infrastructure risk and resilience analysis. For a more developed example, some of these datasets were key inputs to a regional climate risk assessment of current and future flooding risks to transport networks in East Africa, which has a related online visualisation tool at <a href="https://east-africa.infrastructureresilience.org/">https://east-africa.infrastructureresilience.org/</a> and is described in detail in Hickford et al (2023). References <ul> <li> Arderne, Christopher, Nicolas, Claire, Zorn, Conrad, & Koks, Elco E. (2020). Data from: Predictive mapping of the global power system using open data [Dataset]. In Nature Scientific Data (1.1.1, Vol. 7, Number Article 19). Zenodo. DOI: <a href="https://doi.org/10.5281/zenodo.3628142">10.5281/zenodo.3628142</a> </li> <li> Baugh, Calum; Colonese, Juan; D'Angelo, Claudia; Dottori, Francesco; Neal, Jeffrey; Prudhomme, Christel; Salamon, Peter (2024): Global river flood hazard maps. European Commission, Joint Research Centre (JRC) [Dataset] PID: <a href="http://data.europa.eu/89h/jrc-floods-floodmapgl_rp50y-tif">data.europa.eu/89h/jrc-floods-floodmapgl_rp50y-tif</a> </li> <li> Bloemendaal, Nadia; de Moel, H. (Hans); Muis, S; Haigh, I.D. (Ivan); Aerts, J.C.J.H. (Jeroen) (2020): STORM tropical cyclone wind speed return periods. 4TU.ResearchData. [Dataset]. DOI: <a href="https://doi.org/10.4121/12705164.v3">10.4121/12705164.v3</a> </li> <li> Bloemendaal, Nadia; de Moel, Hans; Dullaart, Job; Haarsma, R.J. (Reindert); Haigh, I.D. (Ivan); Martinez, Andrew B.; et al. (2022): STORM climate change tropical cyclone wind speed return periods. 4TU.ResearchData. [Dataset]. DOI: <a href="https://doi.org/10.4121/14510817.v3">10.4121/14510817.v3</a> </li> <li> Copernicus Climate Change Service, Climate Data Store, (2019): Land cover classification gridded maps from 1992 to present derived from satellite observation. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: <a href="https://doi.org/10.24381/cds.006f2c9a">10.24381/cds.006f2c9a</a> (Accessed on 09-AUG-2024) </li> <li> Copernicus DEM - Global Digital Elevation Model (2021) DOI: <a href="https://doi.org/10.5270/ESA-c5d3d65">10.5270/ESA-c5d3d65</a> (produced using Copernicus WorldDEM™-90 © DLR e.V. 2010-2014 and © Airbus Defence and Space GmbH 2014-2018 provided under COPERNICUS by the European Union and ESA; all rights reserved) </li> <li> Global Energy Observatory, Google, KTH Royal Institute of Technology in Stockholm, Enipedia, World Resources Institute. (2018) Global Power Plant Database. Published on Resource Watch and Google Earth Engine; <a href="http://resourcewatch.org/">resourcewatch.org/</a> </li> <li> Hickford et al (2023) Decision support systems for resilient strategic transport networks in low-income countries – Final Report. Available online: <a href="https://transport-links.com/hvt-publications/final-report-decision-support-systems-for-resilient-strategic-transport-networks-in-low-income-countries">https://transport-links.com/hvt-publications/final-report-decision-support-systems-for-resilient-strategic-transport-networks-in-low-income-countries</a> </li> <li> Lange, S., Volkholz, J., Geiger, T., Zhao, F., Vega, I., Veldkamp, T., et al. (2020). Projecting exposure to extreme climate impact events across six event categories and three spatial scales. Earth's Future, 8, e2020EF001616. DOI: <a href="https://doi.org/10.1029/2020EF001616">10.1029/2020EF001616</a> </li> <li> Natural Earth (2023) Admin 0 Map Units, v5.1.1. [Dataset] Available online: <a href="https://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-details/">www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-0-details</a> </li> <li> OpenStreetMap contributors, Russell T., Thomas F., nismod/datapkg contributors (2025) Road and Rail networks derived from OpenStreetMap. [Dataset] Available at <a href="https://global.infrastructureresilience.org">global.infrastructureresilience.org</a> </li> <li> Pesaresi M., Politis P. (2023): GHS-BUILT-S R2023A - GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975-2030) European Commission, Joint Research Centre (JRC) PID: <a href="http://data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea">data.europa.eu/89h/9f06f36f-4b11-47ec-abb0-4f8b7b1d72ea</a>, doi:10.2905/9F06F36F-4B11-47EC-ABB0-4F8B7B1D72EA </li> <li> Runfola D, Anderson A, Baier H, Crittenden M, Dowker E, Fuhrig S, et al. (2020) geoBoundaries: A global database of political administrative boundaries. PLoS ONE 15(4): e0231866. DOI: <a href="https://doi.org/10.1371/journal.pone.0231866">10.1371/journal.pone.0231866</a>. </li> <li> Russell, T., Nicholas, C., & Bernhofen, M. (2023). Annual probability of extreme heat and drought events, derived from Lange et al 2020 (Version 2) [Dataset]. Zenodo. DOI: <a href="https://doi.org/10.5281/zenodo.8147088">10.5281/zenodo.8147088</a> </li> <li> Schiavina M., Freire S., Carioli A., MacManus K. (2023): GHS-POP R2023A - GHS population grid multitemporal (1975-2030). European Commission, Joint Research Centre (JRC) PID: <a href="http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe">data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe</a>, doi:10.2905/2FF68A52-5B5B-4A22-8F40-C41DA8332CFE </li> <li> Ward, P.J., H.C. Winsemius, S. Kuzma, M.F.P. Bierkens, A. Bouwman, H. de Moel, A. Díaz Loaiza, et al. (2020) Aqueduct Floods Methodology. Technical Note. Washington, D.C.: World Resources Institute. Available online at: <a href="https://www.wri.org/publication/aqueduct-floods-methodology">www.wri.org/publication/aqueduct-floods-methodology</a>. </li> </ul>

opencc-by-4.0Dec 2023View details →

Transport Starter Data Kit: Historical socio-transport data for Eritrea

This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.

opencc-zeroAug 2024View details →

National Checklists: Eritrea Species List

Data from: GBIF.org (23 January 2025) GBIF Occurrence Download <a href="https://doi.org/10.15468/dl.vd2ajk" target="_blank" rel="noopener">https://doi.org/10.15468/dl.vd2ajk</a>

opencc-by-4.0Apr 2021View details →

CCG Starter Data Kit: Eritrea

A starter data kit for Eritrea

zenodo36/100

SKS measurements and null measurements for seismic stations in Eritrea and Yemen

These files relate to "Channelized mantle flow through the Afar Triple Junction and around the Arabian plate: evidence from seismic anisotropy" by Gauntlett et al. (2024). Original seismic waveforms are from the Eritrea Seismic Project (<a href="https://doi.org/10.7914/sn/5h_2011">Hammond et al., 2011</a>) and the Young Conjugate Margins Lab in the Gulf of Aden network (<a href="10.7914/SN/XW_2009">Leroy et al., 2007</a>) and are publicly available through<a href="http://service.iris.edu/fdsnws/dataselect/1/">EarthScope Data Services</a>. The repository consists of three files: <ol> <li>SKS_ALL.csv</li> <li>SKS_NULL_ALL.csv</li> <li>stations_all.csv</li> </ol> The first file provides individual shear-wave splitting results reported in the study for the SKS phase. The columns are as follows:  <ul> <li>Station longitude</li> <li>Station latitude</li> <li>Orientation of the fast split shear wave (φ)</li> <li>Time delay between the fast and slow shear waves (dt)</li> <li>Error in phi</li> <li>Error in dt</li> <li>Event longitude</li> <li>Event latitude</li> <li>Event backazimuth</li> <li>Distance in degrees from event-station</li> <li>Event code</li> <li>Station name</li> </ul> The second file provides information on null results reported in the study, where no shear-wave splitting is observed for the SKS phase. The columns are as follows:  <ul> <li>Station longitude</li> <li>Station latitude</li> <li>Event longitude</li> <li>Event latitude</li> <li>Event backazimuth</li> <li>Distance in degrees from event-station</li> <li>Event code</li> <li>Station name</li> </ul> The station file contains the station name, the station latitude, station longitude and station elevation in km above sea level.

opencc-by-4.0Apr 2024View details →

zenodo36/100

State of Eritrea

[Eritrea](https://en.wikipedia.org/wiki/Eritrea) is a country in the Horn of Africa region of Eastern Africa, with its capital (and largest city) at Asmara. It is bordered by Ethiopia in the south, Sudan in the west, and Djibouti in the southeast. The northeastern and eastern parts of Eritrea have an extensive coastline along the Red Sea. The nation has a total area of approximately 117,600 km2 (45,406 sq mi), and includes the Dahlak Archipelago and several of the Hanish Islands. Source: Objaverse 1.0 / Sketchfab

opencc-byJan 2022View details →

opennotspecifiedOct 2019View details →

Subspecies and Distribution. . p. perforatus E. Geoffroy Saint-Hilaire, 1818 — Nile Valley in Egypt and N Sudan. . p. haedinusThomas, 1915 - Middle East (Israel, Arabian Peninsula, and S Iran) E to India, and E Africa from Djibouti to Kenya (including Lamu I) and Tanzania; it may also occur in Eritrea. . p. senegalensis Desmarest, 1820 - scattered localities in W Africa, from S Mauritania, Senegal, and Guinea-Bissau E to NW Nigeria and W Cameroon; it may occur in Guinea and Ivory Coast. . p. sudani Thomas, 1915 — C & S Sudan, South Sudan, Uganda, and S through the Congo Basin to N & E Botswana, S Zimbabwe, and NE South Africa in Emballonuridae

Subspecies and Distribution. . p. perforatus E. Geoffroy Saint-Hilaire, 1818 — Nile Valley in Egypt and N Sudan. . p. haedinusThomas, 1915 - Middle East (Israel, Arabian Peninsula, and S Iran) E to India, and E Africa from Djibouti to Kenya (including Lamu I) and Tanzania; it may also occur in Eritrea. . p. senegalensis Desmarest, 1820 - scattered localities in W Africa, from S Mauritania, Senegal, and Guinea-Bissau E to NW Nigeria and W Cameroon; it may occur in Guinea and Ivory Coast. . p. sudani Thomas, 1915 — C & S Sudan, South Sudan, Uganda, and S through the Congo Basin to N & E Botswana, S Zimbabwe, and NE South Africa

opennotspecifiedOct 2019View details →

Distribution. Extent of this species' dis tribution is not yet known; recorded with certainty in Morocco, Senegal, Saudi Ara bia, and Yemen. It is thought to be con tinuously distributed from Mauritania and Senegal E to South Sudan, Ethiopia, and Eritrea. However, boundary between this species and the morphologically identical H. coffer is not known. in Family Hipposideridae (Old World Leaf-nosed Bats)

Distribution. Extent of this species' dis tribution is not yet known; recorded with certainty in Morocco, Senegal, Saudi Ara bia, and Yemen. It is thought to be con tinuously distributed from Mauritania and Senegal E to South Sudan, Ethiopia, and Eritrea. However, boundary between this species and the morphologically identical H. coffer is not known.

dryad32/100

Data from: The elephants of Gash-Barka, Eritrea: nuclear and mitochondrial genetic patterns

Eritrea has one of the northernmost populations of African elephants. Only about 100 elephants persist in the Gash-Barka administrative zone. Elephants in Eritrea have become completely isolated, with no gene flow from other elephant populations. The conservation of Eritrean elephants would benefit from an understanding of their genetic affinities to elephants elsewhere on the continent and the degree to which genetic variation persists in the population. Using dung samples from Eritrean elephants, we examined 18 species-diagnostic single nucleotide polymorphisms in 3 nuclear genes, sequences of mitochondrial HVR1 and ND5, and genotyped 11 microsatellite loci. The sampled Eritrean elephants carried nuclear and mitochondrial DNA markers establishing them as savanna elephants, with closer genetic affinity to Eastern than to North Central savanna elephant populations, and contrary to speculation by some scholars that forest elephants were found in Eritrea. Mitochondrial DNA diversity was relatively low, with 2 haplotypes unique to Eritrea predominating. Microsatellite genotypes could only be determined for a small number of elephants but suggested that the population suffers from low genetic diversity. Conservation efforts should aim to protect Eritrean elephants and their habitat in the short run, with restoration of habitat connectivity and genetic diversity as long-term goals.

opencc-zeroDec 2012View details →

opennotspecifiedDec 2010View details →

FIGURE 4 in A new species of Danakilia (Teleostei, Cichlidae) from Lake Abaeded in the Danakil Depression of Eritrea (East Africa)

FIGURE 4. Danakilia dinicolai (a) wild caught female and (b) wild caught male. Specimens not preserved or measured.

opennotspecifiedDec 2010View details →

FIGURE 3 in A new species of Danakilia (Teleostei, Cichlidae) from Lake Abaeded in the Danakil Depression of Eritrea (East Africa)

FIGURE 3. Lower pharyngeal jaw (dorsal, posterior and lateral views), left mandible and isolated tooth in (a) Danakilia dinicolai, (b) Danakilia franchettii, (c) Iranocichla hormuzensis. Elements drawn in corresponding scale for each species. Posterior neurocranium and anterior vertebral elements, arrows indicate inferior vertebral apophysis of (d) Iranocichla hormuzensis.

opennotspecifiedDec 2010View details →

FIGURE 1 in A new species of Danakilia (Teleostei, Cichlidae) from Lake Abaeded in the Danakil Depression of Eritrea (East Africa)

FIGURE 1. Scatter plot of PC1 vs. PC2. Danakilia franchettii (black stars), Danakilia dinicolai (grey stars).

Subspecies and Distribution. Vr. rueppellii Schinz, 1825 — Egypt and Sudan (Nubian Desert). V. r. caesia Thomas & Hinton, 1921 — N & W Africa. V. r. cyrenaica Festa, 1921 — SW Egypt, Lybia, extreme NW Sudan. V. r. sabaea Pocock, 1934 — Arabian Peninsula and Middle East. V. r. somaliae Thomas, 1918 — Eritrea, Ethiopia, and Somalia. V. r. zarudny: Birula, 1913 — Baluchistan in Afghanistan, Iran, and Pakistan. in Canidae

Subspecies and Distribution. Vr. rueppellii Schinz, 1825 — Egypt and Sudan (Nubian Desert). V. r. caesia Thomas & Hinton, 1921 — N & W Africa. V. r. cyrenaica Festa, 1921 — SW Egypt, Lybia, extreme NW Sudan. V. r. sabaea Pocock, 1934 — Arabian Peninsula and Middle East. V. r. somaliae Thomas, 1918 — Eritrea, Ethiopia, and Somalia. V. r. zarudny: Birula, 1913 — Baluchistan in Afghanistan, Iran, and Pakistan.

Subspecies and Distribution. P. ¢. enistata Sparrman, 1783 — E African coast (S Egypt, Sudan, Eritrea, Djibouti, Ethiopia, Somalia, Kenya, NE Uganda to C Tanzania). P. c. septentrionalis Rothschild, 1902 — most of S Africa (S Angola, S Zambia, SW Mozambique, Namibia, Botswana, Zimbabwe, Swaziland, Lesotho, and South Africa). in Hyaenidae

Subspecies and Distribution. P. ¢. enistata Sparrman, 1783 — E African coast (S Egypt, Sudan, Eritrea, Djibouti, Ethiopia, Somalia, Kenya, NE Uganda to C Tanzania). P. c. septentrionalis Rothschild, 1902 — most of S Africa (S Angola, S Zambia, SW Mozambique, Namibia, Botswana, Zimbabwe, Swaziland, Lesotho, and South Africa).

Subspecies and Distribution. I. a. albicauda Cuvier, 1829 — Senegal to E Sudan, Eritrea, and N Somalia; also Arabian Peninsula. I. a. dialeucos Hollister, 1916 — N Kenya, S Somalia, and S Ethiopia. I. a. grandis Thomas, 1890 — S Angola, Zambia, S Tanzania to South Africa. I. a. ibeana Thomas, 1904 — DR Congo to C Kenya. I. a. loandae Thomas, 1904 — N Angola and S DR Congo. I. a. loempo Temminck, 1853 — W Africa (Guinea). in Herpestidae

Subspecies and Distribution. I. a. albicauda Cuvier, 1829 — Senegal to E Sudan, Eritrea, and N Somalia; also Arabian Peninsula. I. a. dialeucos Hollister, 1916 — N Kenya, S Somalia, and S Ethiopia. I. a. grandis Thomas, 1890 — S Angola, Zambia, S Tanzania to South Africa. I. a. ibeana Thomas, 1904 — DR Congo to C Kenya. I. a. loandae Thomas, 1904 — N Angola and S DR Congo. I. a. loempo Temminck, 1853 — W Africa (Guinea).

Distribution. Senegal and Gambia E to Eritrea and Somalia and then SW to PR Congo, Angola, and NE Namibia, and S to E South Africa. in Herpestidae

Distribution. Senegal and Gambia E to Eritrea and Somalia and then SW to PR Congo, Angola, and NE Namibia, and S to E South Africa.

Subspecies and Distribution. G. m. maculata Gray, 1830 — Ethiopia and Eritrea. G. m. letabae Thomas & Schwann, 1906 — W, C & E Africa, also in Angola, NE Namibia, Botswana, and SW Zambia. G. m. mossambica Matschie, 1902 — Mozambique and South Africa. G. m. zambesiana Matschie, 1902 — Malawi and Zimbabwe. in Viverridae

Subspecies and Distribution. G. m. maculata Gray, 1830 — Ethiopia and Eritrea. G. m. letabae Thomas & Schwann, 1906 — W, C & E Africa, also in Angola, NE Namibia, Botswana, and SW Zambia. G. m. mossambica Matschie, 1902 — Mozambique and South Africa. G. m. zambesiana Matschie, 1902 — Malawi and Zimbabwe.