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66 results for “Guinea-Bissau”
Infrastructure Climate Resilience Assessment Data Starter Kit for Guinea-Bissau
<p> This starter data kit collects extracts from global, open datasets relating to climate hazards and infrastructure systems. </p> <p> 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. </p> <p> 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. </p> <p>Hazards:</p> <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> <p>Exposure:</p> <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> <p>Contextual information:</p> <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> <p> The spatial intersection of hazard and exposure datasets is a first step to analyse vulnerability and risk to infrastructure and people. </p> <p> 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. </p> <p> These Python libraries may be a useful place to start analysis of the data in the packages produced by this workflow: </p> <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> <p> 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. </p> <p> 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). </p> <p><strong>References</strong></p> <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>
Transport Starter Data Kit: Historical socio-transport data for Guinea-Bissau
<p>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.</p>
EEG data collected with Emotiv device in people with epilepsy and controls in Guinea-Bissau and Nigeria
<p>Electroencephalography (EEG) data collected in people with epilepsy (N=163) and healthy controls (N=138) in two difficult-to-reach areas in rural Guinea-Bissau and Nigeria. Five minutes of fourteen channel resting-state EEG data were acquired with a portable, low-cost consumer-grade EEG recording headset. Experiments started either with two minutes of eyes closed or two minutes of eyes open which was randomized across participants. The order of the experiment is clarified in the meta-data files.</p> <p>A study describing an using this data can be found here:https://www.biorxiv.org/content/early/2018/05/17/324954.</p>
Fig. 3 in On the African Whip Scorpion, Etienneus africanus (Hentschel, 1899) (Thelyphonida: Thelyphonidae), with a Redescription Based on New Material from Guinea-Bissau and Senegal
Fig. 3. Map of West Africa, plotting the known locality records of Etienneus africanus (Hentschel, 1899).
Fig. 11 in On the African Whip Scorpion, Etienneus africanus (Hentschel, 1899) (Thelyphonida: Thelyphonidae), with a Redescription Based on New Material from Guinea-Bissau and Senegal
Fig. 11. Subtropical forest habitat of Etienneus africanus (Hentschel, 1899). A. Guinea-Bissau: 19 km S of Bambadinca. B. Senegal: 3 km W of Kedougou on road to Salemata.
Guinea-Bissau
[Guinea-Bissau](https://en.wikipedia.org/wiki/Guinea-Bissau) is a country in West Africa that covers 36,125 square kilometres (13,948 sq mi) with an estimated population of 1,726,000. It borders Senegal to the north and Guinea to the south-east. Source: Objaverse 1.0 / Sketchfab
Data from: Estimating the effective population size across space and time in the Critically Endangered western chimpanzee in Guinea-Bissau: Challenges and implications for conservation management
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Miniaturised laboratorial equipment as a solution to implement conservation genetics tools and education in West African countries with limited infrastructures: an application to the study of illegal wildlife trade in Guinea-Bissau
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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
FIGURE 7 in Notes on tiger beetles from Guinea-Bissau, with description of a new species of Cylindera Westwood (Insecta: Coleoptera, Cicindelidae) *
FIGURE 7. Number of species of tiger beetles by U.T.M. 10x10 Km square in Guinea-Bissau. In green, U.T.M. squares with more than ten species.
FIGURE 3 in Notes on tiger beetles from Guinea-Bissau, with description of a new species of Cylindera Westwood (Insecta: Coleoptera, Cicindelidae) *
FIGURE 3. Cylindera (Ifasina) gulbenkiana n. sp. (male holotype): a) labrum, b) Pronotum, and c) right elytron.
FIGURE 1 in Notes on tiger beetles from Guinea-Bissau, with description of a new species of Cylindera Westwood (Insecta: Coleoptera, Cicindelidae) *
FIGURE 1. Geographical distribution map (U.T.M. 10x10 Km squares) of the species of tiger beetles in Guinea-Bissau using the code numbers of Table 1. The localities (red code numbers) are given from left to right and top to bottom in each 100x100 km square. Localities are numbered sequentially from 1 to 46.
FIGURE 1 in Butterflies of Guinea-Bissau: VIII. New data, new reports, corrections and biodiversity (Lepidoptera: Papilionoidea)
FIGURE 1. Map of Guinea-Bissau with centroids of the 10 km UTM squares containing the localities where butterflies have been recorded: black centroids include the localities prospected in this study, open centroids include those from previous studies, and grey centroids include localities from both the present and former studies. White dotted areas represent Protected Areas.
FIGURES 1–4. Chilocoris serratus n in Chilocoris serratus n. sp., the first burrower bug species (Hemiptera: Heteroptera: Cydnidae) recorded in Guinea-Bissau with an annotated checklist of the Afrotropical species of the genus Chilocoris Mayr, 1865
FIGURES 1–4. Chilocoris serratus n. sp.: (1) body, dorsal view; (2) head, dorsal view; (3) lateral margin of pronotum, dorsal view; (4) basal two thirds of costal margin of corium, dorsal view.
Figs. 3–4 in Myriochila (Monelica) Confluentesubtilis (W. Horn, 1914) (Coleoptera: Carabidae: Cicindelinae): Elevation To Species Status And New Record For Guinea-Bissau
Figs. 3–4. Myriochila species, aedeagi, lateral view. 3) Myriochila confluentesubtilis; 4) M. vicina vicina.
FIGURE 1 in Ground beetles of the subfamily Lebiinae (Carabidae) of Guinea-Bissau: description of three new species and faunistic notes
FIGURE 1. Habitus of Lebiinae species. (a) Arsinoe aguiari n. sp. (dorsal view), holotype male, Coli (Quebo), TOB, ASC; (b) Dontolobus bivari n. sp. (dorsal view), holotype male, Coli (Quebo), TOB, ASC; (c) Lasiocera schwarzi n. sp. (dorsal view), female, Banhinda, CAC, ASC; (d) Lasiocera asmara (dorsal view) plus labels, paratype, Eritreia, MRAC; (e) Lasiocera mirei (dorsal view) plus labels, paratype, Cameroon, MRAC; (f) Lasiocera nitidula (dorsal view) plus labels, female, Central African Republic, MRAC.
FIGURE 2 in Ground beetles of the subfamily Lebiinae (Carabidae) of Guinea-Bissau: description of three new species and faunistic notes
FIGURE 2. Aedeagus of: Arsinoe aguiari n. sp. (a), median lobe and right paramere (lateral views) (b), median lobe (dorsal view); Dontolobus bivari n. sp. (c), median lobe and right paramere (lateral views) (d), median lobe (dorsal view).
Distribution. Restricted to three disjunct populations in SE Senegal, N Guinea, and SW Mali, and perhaps E Guinea-Bissau; N Cameroon, SW Chad, and maybe E & C Nigeria; and Central African Republic, SE Chad, SW Sudan, and maybe NE DR Congo and NW Uganda. in Bovidae
Distribution. Restricted to three disjunct populations in SE Senegal, N Guinea, and SW Mali, and perhaps E Guinea-Bissau; N Cameroon, SW Chad, and maybe E & C Nigeria; and Central African Republic, SE Chad, SW Sudan, and maybe NE DR Congo and NW Uganda.
Distribution. SE Senegal, extreme SW Mali, Guinea-Bissau, Guinea, NW Sierra Leone, Liberia, Ivory Coast, S Burkina Faso, Ghana, Togo, Benin, extreme S Niger, W & C Nigeria, N Cameroon, S Chad, Central African Republic, S & E Sudan, N DR Congo, lowland parts of W Ethiopia, Uganda (not extreme S), NW Kenya (Lake Turkana region). in Bovidae
Distribution. SE Senegal, extreme SW Mali, Guinea-Bissau, Guinea, NW Sierra Leone, Liberia, Ivory Coast, S Burkina Faso, Ghana, Togo, Benin, extreme S Niger, W & C Nigeria, N Cameroon, S Chad, Central African Republic, S & E Sudan, N DR Congo, lowland parts of W Ethiopia, Uganda (not extreme S), NW Kenya (Lake Turkana region).
Distribution. Discontinuous and limited to wetland environments in the Congo Basin N and W of the range of the Zambezi Sitatunga in S Benin (Porto Novo), S Nigeria, Cameroon, Central African Republic, Equatorial Guinea, Gabon, Republic of the Congo, N DR Congo; also several isolated populations in W Africa (Senegal, Gambia & Guinea-Bissau), NE Nigeria and W Chad, and perhaps extreme S Ghana. Maps and distributional information here are provisional pending future research. in Bovidae
Distribution. Discontinuous and limited to wetland environments in the Congo Basin N and W of the range of the Zambezi Sitatunga in S Benin (Porto Novo), S Nigeria, Cameroon, Central African Republic, Equatorial Guinea, Gabon, Republic of the Congo, N DR Congo; also several isolated populations in W Africa (Senegal, Gambia & Guinea-Bissau), NE Nigeria and W Chad, and perhaps extreme S Ghana. Maps and distributional information here are provisional pending future research.
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