Nigeria GIS data

GLIDEnumbers are GLobal unique IDEntifiers for Disasters. Each disaster is registered in a record that contains a GLIDEnumber that uniquely identifies it and allows information to be interoperable across multiple disaster information sources, both structured and textual. Accessing disaster information can be a time consuming and laborious task. Not only is data scattered but frequently identification of the disaster can be confusing in countries with many disaster events and across borders. To address both of these issues, Asian Disaster Reduction Center (ADRC) proposed a globally common Unique ID code for disasters. Among the institutions using actively GLIDEnumbers are UN-OCHA (ReliefWeb, FSCC, HDX), UNDRR, UNDP, WMO, IFRC, FAO, the European Commission and the Centre for Research on the Epidemiology of Disasters (CRED), among many others. Country datasets are only produced for countries with at least one GLIDE event since 1 January 2022. The global dataset contains all events available from the GLIDE API, including those not assigned to a country.

Raster representing a location score for intensive, closed, and semi-closed catfish farming systems using photovoltaic (PV) alternative energy, using ponds, tanks, RAS, flow through and recirculation in Nigeria. Produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. Intensive aquaculture is characterized by high densities and artificial feed input. Closed or semi-closed techniques are less dependent on natural or physical geographical criteria. Require less water since it reuses/recirculates, can be placed indoors or in compounds, and are produced with artificial materials. Adoption is limited by poor and unreliable energy distribution networks, PV potential is introduced as an intensification criterion, to supply operational needs (pumps, aerators). The score is achieved by processing sub-model outputs characterizing natural geography, infrastructure, and demand factors: Considered criteria. a. Market accessibility - major urban areas. b. Water Balance - precipitation/evapotranspiration. c. Inputs - Crop and livestock d. Slope - terrain suitability. e. Farm-gate sales - based on population density classification. f. Photovoltaic (PV) energy potential. The location score consists of a simple arithmetic weighted sum of normalized/scaled grids, theoretically varying from 0 to 100: (“Accessibility MajorUrbanAreas” X 0.5) + (“PVPotential” X 0.15) + (“CropsInput” X 0.1) + (“LivestockInput” X 0.10) + ("Slope " X 0.05) + (”FarmgateSales” X 0.05) ("WaterBalance" X 0.2) **Data publication:** 2021-11-08 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) Distributor: [Nelson Ribeiro](mailto:nelson.rosasribeirofilho@fao.org) **Data lineage:** Data sources, FAO Hand-in-Hand Geospatial Platform and OpenStreetMap (open data) including the following datasets: a. Market Accessibility (urban areas) - OpenStreetMap and Human Population Density 2020 WorldPop2020 (Urban areas = pop density>1600 habitants/km² AND area>50km²) b. Farm-gate sales Human Population Density 2020 – WorldPop2020: Class 4 - Very suitable: 150-300 [h/km²] Class 3 – Moderately suitable: 25-149 [h/km²] Class 2 – Marginally suitable: 1-24 [h/km²] Class 1 – Unsuitable: 300 [h/km²] c. Water Balance: WaPOR precipitation and evapotranspiration monthly time-series from 2009 to 2020 for calculating a mean water balance layer modelling values: (Precipitation *1.1) - (evapotranspiration*1.3) d. Slope - terrain suitability - Watershed DEM 30s, classification. Class 4 - Very suitable: 8 e. Input crops GAEZ (CropAggGAEZ). f. Input livestock – GLW: weighted animal density aggregate g. Urban areas = pop density>1600 habitants/km² AND area>50km² - Human Population Density 2020 – WorldPop2020 h. World Bank: World - Photovoltaic Power Potential (PVOUT) GIS Data, (Global Solar Atlas) **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Download raster TIF location score for intensive closed/semi-closed catfish farming systems, using photovoltaic power in Nigeria.

Raster representing location score for intensive, closed, and semi-closed catfish farming systems using ponds, tanks, RAS, flow through and recirculation in Nigeria Produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. Intensive aquaculture is characterized by high densities and artificial feed input. Closed or semi-closed techniques are less dependent on natural or physical geographical criteria. Require less water since it reuses/recirculates, can be placed indoors or in compounds, and are produced with artificial materials. The score is achieved by processing sub-model outputs characterizing natural geography, infrastructure, and demand factors: Considered criteria. a. Market accessibility - major urban areas. b. Water Balance - precipitation/evapotranspiration. c. Inputs - Crop and livestock d. Slope - terrain suitability. e. Farm-gate sales - based on population density classification. The location score consists of a simple arithmetic weighted sum of normalized/scaled grids, theoretically varying from 0 to 100: (“Accessibility MajorUrbanAreas” X 0.5) + ("WaterBalance" X 0.2) + (“CropsInput” X 0.1) + (“LivestockInput” X 0.10) + ("Slope " X 0.05) + (”FarmgateSales” X 0.05) **Data publication:** 2021-11-08 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) Distributor: [Nelson Ribeiro](mailto:nelson.rosasribeirofilho@fao.org) **Data lineage:** Data sources, FAO Hand-in-Hand Geospatial Platform and OpenStreetMap (open data) including the following datasets: a. Market Accessibility (urban areas) - OpenStreetMap and Human Population Density 2020 WorldPop2020 (Urban areas = pop density>1600 habitants/km² AND area>50km²) b. Farm-gate sales Human Population Density 2020 – WorldPop2020: Class 4 - Very suitable: 150-300 [h/km²] Class 3 – Moderately suitable: 25-149 [h/km²] Class 2 – Marginally suitable: 1-24 [h/km²] Class 1 – Unsuitable: 300 [h/km²] c. Water Balance: WaPOR precipitation and evapotranspiration monthly time-series from 2009 to 2020 for calculating a mean water balance layer modelling values: (Precipitation *1.1) - (evapotranspiration*1.3) d. Slope - terrain suitability - Watershed DEM 30s, classification. Class 4 - Very suitable: 8 e. Input crops GAEZ (CropAggGAEZ). f. Input livestock – GLW: weighted animal density aggregate g. Urban areas = pop density>1600 habitants/km² AND area>50km² - Human Population Density 2020 – WorldPop2020 **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Download raster TIF file - Intensive, closed and semi-closed, fish farming systems location score: African Catfish (Nigeria - ~1km)

Accessibility to major maritime ports is modelled as raster-based travel time/cost analysis. This 1km resolution raster dataset is part of FAO's Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (optimal location). **Data publication:** 2021-11-01 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement Produced using OpenStreetMap data for road, railways, cities; FAO Inland Waters in Africa; FAO Major Rivers in Africa; FAO Maritime Ports **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Download raster (TIF) accessibility travel time/cost to major maritime ports in Nigeria

Accessibility to major urban areas is modelled as raster-based travel time/cost analysis, computed considering the following thresholds: urban>1600 habitants/km², area>50km² (totaling 52 urban regions). Accessibility is calculated using roads intersection points with urban areas polygons (639 access points). This 1km resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (or optimal location) **Data publication:** 2021-11-01 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) **Data lineage:** lineage statement Produced using OpenStreetMap data for road, railways, cities; FAO Inland Waters in Africa; FAO Major Rivers in Africa; WorpPop2020 population density. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Download raster (TIF) accessibility travel time/cost to major urban areas in Nigeria.

Raster representing final recommended locations for intensive, closed, and semi-closed catfish farming systems using ponds, tanks, RAS, flow through and recirculation in Nigeria. The dataset is produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. Intensive aquaculture is characterized by high densities and artificial feed input. Closed or semi-closed techniques are less dependent on natural or physical geographical criteria. Require less water since it reuses/recirculates, can be placed indoors or in compounds, and are produced with artificial materials. The score is achieved by processing sub-model outputs characterizing natural geography, infrastructure, and demand factors: Considered criteria. a. Market accessibility - major urban areas. b. Water Balance - precipitation/evapotranspiration. c. Inputs - Crop and livestock d. Slope - terrain suitability. e. Farm-gate sales - based on population density classification. The location score consists of a simple arithmetic weighted sum of normalized/scaled grids, theoretically varying from 0 to 100: (“Accessibility MajorUrbanAreas” X 0.5) + ("WaterBalance" X 0.2) + (“CropsInput” X 0.1) + (“LivestockInput” X 0.10) + ("Slope " X 0.05) + (”FarmgateSales” X 0.05) Final location mapping applies constraints and exclusive criteria, are selected considering the top 95th percentile, and the resulting raster is classified in 3 equal intervals. Applied constraints and exclusive criteria are: a. Urban areas b. Protected areas c. Dams and Large Water Bodies. a. Mobile broadband coverage b. Maximum distance to major roads (~2km: 0.018 degree) **Data publication:** 2021-11-11 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) Distributor: [Nelson Ribeiro](mailto:nelson.rosasribeirofilho@fao.org) **Data lineage:** lineage statement Data sources, FAO Hand-in-Hand Geospatial Platform and OpenStreetMap (open data) including the following datasets a. Market Accessibility (urban areas) - OpenStreetMap and Human Population Density 2020 WorldPop2020 (Urban areas = pop density>1600 habitants/km² AND area>50km² b. Farm-gate sales Human Population Density 2020 – WorldPop2020 Class 4 - Very suitable: 150-300 h/km² Class 3 – Moderately suitable: 25-149 [h/km² Class 2 – Marginally suitable: 1-24 [h/km² Class 1 – Unsuitable: 300 [h/km² c. Water Balance: WaPOR precipitation and evapotranspiration monthly time-series from 2009 to 2020 for calculating a mean water balance layer modelling values: (Precipitation *1.1) - (evapotranspiration*1.3 d. Slope - terrain suitability - Watershed DEM 30s, classification. Class 4 - Very suitable: 8 e. Input crops GAEZ (CropAggGAEZ). f. Input livestock – GLW: weighted animal density aggregate g. Urban areas = pop density>1600 habitants/km² AND area>50km² - Human Population Density 2020 – WorldPop2020 h. Protected areas - UNEP-WCMC and IUCN (2021), Protected Planet. i. Mobile broadband connectivity – Mobile Broadband Coverage 2021 - Collins Bartholomew Mobile Coverage Explorer derived. **Resource constraints:** This work is made available under the [Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Download raster (TIF) for intensive closed/semi-closed catfish farming systems in Nigeria.

Raster representing a location score for intensive, closed, and semi-closed catfish farming systems using photovoltaic (PV) alternative energy, using ponds, tanks, RAS, flow through and recirculation in Nigeria. Produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. Intensive aquaculture is characterized by high densities and artificial feed input. Closed or semi-closed techniques are less dependent on natural or physical geographical criteria. Require less water since it reuses/recirculates, can be placed indoors or in compounds, and are produced with artificial materials. Adoption is limited by poor and unreliable energy distribution networks, PV potential is introduced as an intensification criterion, to supply operational needs (pumps, aerators). The score is achieved by processing sub-model outputs characterizing natural geography, infrastructure, and demand factors: Considered criteria. a. Market accessibility - major urban areas. b. Water Balance - precipitation/evapotranspiration. c. Inputs - Crop and livestock d. Slope - terrain suitability. e. Farm-gate sales - based on population density classification. f. Photovoltaic (PV) energy potential. The location score consists of a simple arithmetic weighted sum of normalized/scaled grids, theoretically varying from 0 to 100: (“Accessibility MajorUrbanAreas” X 0.5) + (“PVPotential” X 0.15) + (“CropsInput” X 0.1) + (“LivestockInput” X 0.10) + ("Slope " X 0.05) + (”FarmgateSales” X 0.05) ("WaterBalance" X 0.2) Final location mapping applies constraints and exclusive criteria, are selected considering the top 95th percentile, and the resulting raster is classified in 3 equal intervals. Applied constraints and exclusive criteria are: a. Urban areas b. Protected areas c. Dams and Large Water Bodies. a. Mobile broadband coverage b. Maximum distance to major roads (~2km: 0.018 degree) **Data publication:** 2021-11-11 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) Distributor: [Nelson Ribeiro](mailto:nelson.rosasribeirofilho@fao.org) **Data lineage:** lineage statement Data sources, FAO Hand-in-Hand Geospatial Platform and OpenStreetMap (open data) including the following datasets a. Market Accessibility (urban areas) - OpenStreetMap and Human Population Density 2020 WorldPop2020 (Urban areas = pop density>1600 habitants/km² AND area>50km² b. Farm-gate sales Human Population Density 2020 – WorldPop2020 Class 4 - Very suitable: 150-300 h/km² Class 3 – Moderately suitable: 25-149 [h/km² Class 2 – Marginally suitable: 1-24 [h/km² Class 1 – Unsuitable: 300 [h/km² c. Water Balance: WaPOR precipitation and evapotranspiration monthly time-series from 2009 to 2020 for calculating a mean water balance layer modelling values: (Precipitation *1.1) - (evapotranspiration*1.3 d. Slope - terrain suitability - Watershed DEM 30s, classification. Class 4 - Very suitable: 8 e. Input crops GAEZ (CropAggGAEZ). f. Input livestock – GLW: weighted animal density aggregate g. Urban areas = pop density>1600 habitants/km² AND area>50km² - Human Population Density 2020 – WorldPop2020 h. World Bank: World - Photovoltaic Power Potential (PVOUT) GIS Data, (Global Solar Atlas i. Protected areas - UNEP-WCMC and IUCN (2021), Protected Planet. j. Mobile broadband connectivity – Mobile Broadband Coverage 2021 - Collins Bartholomew Mobile Coverage Explorer derived. **Resource constraints:** This work is made available under the [Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Download raster TIF for final location, intensive closed/semi-closed catfish farming systems using photovoltaic power in Nigeria,

Raster representing a potential/suitability score for non-intensive and integrated, small-scale, African Catfish and Nile Tilapia fish farming systems, using ponds and small water bodies (SWB), in consumption-based poverty above the national average regions of Nigeria. Produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. Non-intensive aquaculture systems are considered based on natural food supply from SWB or ponds, from integrated systems (crop/livestock byproducts or waste), or with complementary feeding resourcing to on-farm or locally produced feed. The score results from combining sub-model outputs that characterize natural geographical and economical factors: 1. farm-gate sales - based on population density classification 2. Water balance - precipitation/evapotranspiration 3. Soil/slope suitability. 4. Inputs - Crop and livestock byproducts Considered constraints or exclusive criteria are: 1. Urban areas 2. Protected areas 3. Poverty above the national average It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("WaterBalance" X 0.5) + ("Soil/Slope " X 0.25) + (“Byproducts” X 0.125) + (”FarmgateSales” X 0.125) **Data publication:** 2021-11-01 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) Distributor: [Nelson Ribeiro](mailto:nelson.rosasribeirofilho@fao.org) **Data lineage:** lineage statement Data sources, FAO Hand-in-Hand Geospatial Platform and OpenStreetMap (open data) including the following datasets 1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km. * Farm-gate sales Class 4 - Very suitable: 150-300 [h/km² Class 3 – Moderately suitable: 25-149 [h/km² Class 2 – Marginally suitable: 1-24 [h/km² Class 1 – Unsuitable: 300 [h/km² * constraint 'urban areas' = pop density>1600 habitants/km² AND area>50km² 2. Nigeria consumption-based poverty map for 2010 - WorldPop - proportion of residents living on less than $1.25 a day (Tatem et al., 2013 3. WaPOR_2 * Water Balance: precipitation and evapotranspiration monthly time-series (2009 to 2020) mean water balance modelling values: (Precipitation *1.1) - (evapotranspiration*1.3 4. Soil/Slope - (1.5X soils) + Slope. Soil data from FAO (soil suitability for ponds), slope Watershed DEM 30s classification. Class 4 - Very suitable: 8 5. GAEZ v4 Theme 5: Actual Yield and Production - Major crops aggregate production selected using FAOSTAT average 2015/2019 - Cassava, Yams, Maize, Oil palm fruit, Rice ,Vegetables, Sorghum. 6. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 2010) - Chicken and duck. 7. UNEP-WCMC and IUCN (2021), Protected Planet: The World Database on Protected Areas (WDPA) and World Database on Other Effective Area-based Conservation Measures (WD-OECM) [Online], May 2021, Cambridge, UK: UNEP-WCMC and IUCN. Available at: www.protectedplanet.net. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Download Raster TIF non-intensive fish farming systems location score for poverty above the average regions in Nigeria.

Vector map representing potential/suitability score state average, for non-intensive and integrated, small-scale, African Catfish and Nile Tilapia, freshwater fish farming systems using ponds and small water bodies (SWB) in Nigeria. The dataset is produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. Non-intensive aquaculture systems are considered based on natural food supply from SWB or ponds, from integrated systems (crop/livestock byproducts or waste), or with complementary feeding resourcing to on-farm or locally produced feed. The score results from combining sub-model outputs that characterize natural geographical and economical factors: 1. farm-gate sales - based on population density classification 2. Water balance - precipitation/evapotranspiration 3. Soil/slope suitability. 4. Inputs - Crop and livestock byproducts Considered constraints or exclusive criteria are: 1. Urban areas 2. Protected areas It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("WaterBalance" X 0.5) + ("Soil/Slope " X 0.25) + (“Byproducts” X 0.125) + (”FarmgateSales” X 0.125) **Data publication:** 2021-11-08 **Contact points:** Metadata Contact: [FAO-DATA](mailto:FAO-Data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:nelson.rosasribeirofilho@fao.org) Distributor: [Nelson Ribeiro](mailto:nelson.rosasribeirofilho@fao.org) **Data lineage:** lineage statement Lineage Data sources, FAO Hand-in-Hand Geospatial Platform and OpenStreetMap (open data) including the following datasets 1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km. * Farm-gate sales Class 4 - Very suitable: 150-300 [h/km² Class 3 – Moderately suitable: 25-149 [h/km² Class 2 – Marginally suitable: 1-24 [h/km² Class 1 – Unsuitable: 300 [h/km² * constraint 'urban areas' = pop density>1600 habitants/km² AND area>50km² 2. WaPOR_2 * Water Balance: precipitation and evapotranspiration monthly time-series (2009 to 2020) mean water balance modelling values: (Precipitation *1.1) - (evapotranspiration*1.3 3. Soil/Slope - (1.5X soils) + Slope. Soil data from FAO (soil suitability for ponds), slope Watershed DEM 30s classification. Class 4 - Very suitable: 8 4. GAEZ v4 Theme 5: Actual Yield and Production - Major crops aggregate production selected using FAOSTAT average 2015/2019 - Cassava, Yams, Maize, Oil palm fruit, Rice ,Vegetables, Sorghum. 5. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 2010) - Chicken and duck. 6. UNEP-WCMC and IUCN (2021), Protected Planet: The World Database on Protected Areas (WDPA) and World Database on Other Effective Area-based Conservation Measures (WD-OECM) [Online], May 2021, Cambridge, UK: UNEP-WCMC and IUCN. Available at: www.protectedplanet.net. 7. UN-GIS SALB: Nigeria administrative boundaries. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Download vector map (SHP) for state average, non-intensive, pond and small water bodies fish farming systems in Nigeria (catfish and tilapia).

Raster representing potential/suitability score for non-intensive and integrated, small-scale, African Catfish and Nile Tilapia, freshwater fish farming systems, using ponds and small water bodies (SWB) in Nigeria. Produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location. Non-intensive aquaculture systems are considered based on natural food supply from SWB or ponds, from integrated systems (crop/livestock byproducts or waste), or with complementary feeding resourcing to on-farm or locally produced feed. The score results from combining sub-model outputs that characterize natural geographical and economical factors: 1. farm-gate sales - based on population density classification 2. Water balance - precipitation/evapotranspiration 3. Soil/slope suitability. 4. Inputs - Crop and livestock byproducts It consists of an arithmetic weighted sum of normalized grids (0 to 100): ("WaterBalance" X 0.5) + ("Soil/Slope " X 0.25) + (“Byproducts” X 0.125) + (”FarmgateSales” X 0.125) **Data publication:** 2021-11-01 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Nelson Ribeiro](mailto:Nelson.RosasRibeiroFilho@fao.org) Distributor: [Nelson Ribeiro](mailto:nelson.rosasribeirofilho@fao.org) **Data lineage:** lineage statement Data sources, FAO Hand-in-Hand Geospatial Platform and OpenStreetMap (open data) including the following datasets 1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km. * Farm-gate sales Class 4 - Very suitable: 150-300 h/km² Class 3 – Moderately suitable: 25-149 [h/km² Class 2 – Marginally suitable: 1-24 [h/km² Class 1 – Unsuitable: 300 [h/km² 2. WaPOR_2 * Water Balance: precipitation and evapotranspiration monthly time-series (2009 to 2020) mean water balance modelling values: (Precipitation *1.1) - (evapotranspiration*1.3 3. Soil/Slope - (1.5X soils) + Slope. Soil data from FAO (soil suitability for ponds), slope Watershed DEM 30s classification. Class 4 - Very suitable: 8 4. GAEZ v4 Theme 5: Actual Yield and Production - Major crops aggregate production selected using FAOSTAT average 2015/2019 - Cassava, Yams, Maize, Oil palm fruit, Rice ,Vegetables, Sorghum. 5. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 2010) - Chicken and duck. **Resource constraints:** This work is made available under the [Creative Commons Attribution 4.0 International license (CC-BY 4.0) **Online resources:** Download Raster TIF for non-intensive fish farming systems location score in Nigeria.

geoBoundaries ADM2 boundaries for Nigeria: 774 units, representing 2022. Source: GRID3.

Point locations of airports, airstrips and airfields in Nigeria. Each feature includes the facility name, type, elevation and runway information where available. Use this layer for aviation planning, accessibility analysis, emergency response logistics, and transport network mapping.

Point locations of named places in Togo, including populated places, streams and other features. Each row is one place with its name, coordinates, feature class and code, administrative units, population, elevation and timezone. Published by Orion Terrametrics.

Point locations of named places in Nigeria, including streams and populated places. Each feature records a name, coordinates, feature class and code, administrative units, population, elevation, and timezone. Published by Orion Terrametrics.

OpenStreetMap contains roughly 205 km of roads in this region. Based on AI-mapped estimates, this is approximately 44 % of the total road length in the dataset region. The average age of data for the region is 3 years ( Last edited 3 months ago ) and 5% of roads were added or updated in the last 6 months. Read about what this summary means : indicators , metrics This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['highway'] IS NOT NULL Features may have these attributes: - name - highway - surface - smoothness - width - lanes - oneway - bridge - layer - source This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

Nigeria Admin Level 2 boundaries created by the Bill & Melinda Gates foundation. The boundaries were made by mapping all settlements, and then using the Ward Level 2 admin attributes and the ESRI Thiessen polygons tool to create boundaries at each admin level.

This report explores food insecurity in Nigeria in the context of urbanization and demographic change. A comparison of changing acute food security measures (IPC) from January and February 2010-2018 accompanies the report. The authors, Jordan Burnett, Leah Nadel, Victoria Santiago, and Arline Tarazona, completed their research in partial fulfillment of Public Health coursework in Medical Geography, for Spring 2018, at Drew University. Dr. Lisa Jordan edited the report and supplemented their work with additional spatial data.

This dataset contains a zipped shapefile and eight (8) individual CSV files each detailing progress monitoring on key Nutrition Sector indicators, focusing on the three north eastern Nigeria states of Borno, Yobe and Adamawa affected by the crisis, as of July 2018. The data is presented at Local Government Area (LGA) level or Admin 2. The resources include the following: Combined data on all of the Nutrition Indicators; Blanket Supplementary Feeding Programme for Children under 5 years; Blanket Supplementary Feeding Programme (BSFP) for Pregnant and Lactating Women (PLW); Infant and Young Child Feeding (IYCF); Micro-nutrient Powders (MNP); Outpatient Therapeutic Programme (OTP) Admissions; North East Nigeria Nutrition Partner Operational Presence as of July 2018; Stablization Center (SC) Admissions as of July 2018.

North East Nigeria Camp Management partner operational presence by Local Government Area or LGA (Admin 2). Dataset covers partner operational presence in the three crisis-affected states of Borno, Yobe and Adamawa, up to LGA level; Camp Coordination and Camp Management (CCCM) coverage by Local Government Area or LGA (Admin 2). Includes number of households covered and not covered; total households and individuals covered, percentage and overall coverage in the three crisis-affected states of Borno, Yobe and Adamawa, up to LGA level; Camp Coordination and Camp Management (CCCM) and Emergency Shelter and Non-Food Items (ESNFI) activity coverage up to Local Government Area or LGA (Admin 2) level in the three crisis-affected states of Borno, Yobe and Adamawa. Also includes Camp Management partner operational presence by LGA, as of June 2018.

Dataset covers Shelter and Non-food Items needs severity mapping by Local Government Area (LGA) as of June 2018. Dataset covers Borno, Yobe and Adamawa, the three crisis-affected states; Shelter needs severity mapping by Local Government Area (LGA) as of June 2018. Dataset covers Borno, Yobe and Adamawa, the three crisis-affected states; Non-food Items needs severity mapping by Local Government Area (LGA) as of June 2018. The zipped shapefile covers Borno, Yobe and Adamawa, the three crisis-affected states; and a CSV dataset containing Shelter and Non-food Items (NFI) needs severity mapping combined, by Local Government Area (LGA) as of June 2018, covering the three crisis-affected states of Borno, Yobe and Adamawa.

Both the shapefile and CSV feature North East Nigeria Health Sector Humanitarian Partner Operational Presence by Local Government Area in Borno, Yobe and Adamawa, the three crisis-affected states - as of June 2018.

A mapping of the population settlements in Borno State, north east Nigeria as of June 2018, based on the Displacement Tracking Matrix

The zipped shapefile presents data on the health facility rehabilitation status in Borno, the most crisis-affected state in north east Nigeria, as of June 2018.

Health Resources Availability Mapping System (HeRAMS) E-Atlas, with a focus on the mapping of who's doing what where, when and for whom, in Adamawa State of north east Nigeria as of June 2018.

Safe male circumcision coverage in Borno state, the most crisis-affected state in north eastern Nigeria as of June 2018

The zipped shapefile presents Mobile Health Teams mapping data in the three crisis-affected states of Borno, Yobe and Adamawa in north east Nigeria, as of June 2018.

Flood-affected populations by settlement type as of June 2018. The dataset presents the data to LGA level (Admin 2) in all the three crisis-affected states of north eastern Nigeria, thus Borno, Yobe and Adamawa. The affected populations include households and individuals. The settlement types include Households in IDP Camps, Households in Host Communities and provides a computation of affected people by settlement type; Camp flood risk mapping as of June 2018. The dataset presents the data to LGA level (Admin 2) in IDP camps across all the three crisis-affected states of north eastern Nigeria, thus Borno, Yobe and Adamawa; Host Community flood risk analysis and mapping as of June 2018. Also includes a CSV file on Flood-affected populations by settlement type as of June 2018.

Designated institutions to provide learning spaces and learning environments for the teaching of students. This data has been extracted from GRID3 Nigeria site

Nigeria Roads (Primary and Secondary roads. Data from OSM)

Nigeria Railways (data from OSM)

This is a geometrical shapefile of water point data for eleven (11) hot spot Local Government Areas and describes the water point location type (broadly IDP Camps or Host Communities). Data contains water source details such as nature of the water source, yield, operating hours, facility type, daily yield, and adequacy. The data was collected by UNICEF Data Focal Persons during a water point baseline assessment conducted in March 2019. Data contained in this file is at water point level.

This zipped geometrical dataset contains shapefile on child protection case management reach in Adamawa State, in the first quarter of 2019. This is part of the Child Protection in Emergencies support in response to the crisis in north east Nigeria.

The zipped geometrical dataset contains a shapefile on the reach of mine risk education services to children in Adamawa State, in the first quarter of 2019. The provision of Mine Risk Education is part of the overall Child Protection in Emergencies support in response to the humanitarian crisis in north east Nigeria.

The zipped geometrical dataset contains a shapefile on the reach of psycho-social support services to children in Adamawa State, in the first quarter of 2019. The provision of psycho-social support to children is part of the overall Child Protection in Emergencies support services in response to the humanitarian crisis in north east Nigeria.

The zipped geometrical dataset contains a shapefile on the reach of social-economic assistance to children and adolescents who have suffered from grave child rights violations, including former children associated with armed groups (CAAG) in Borno and Adamawa States. The provision of socio-economic reintegration support to children and adolescents is one of the indicators upon which the Child Protection in Emergencies Working Group is directing its humanitarian response efforts in response to the crisis north east Nigeria.

This zipped geometrical dataset contains shapefile on child protection case management reach in Borno and Yobe States, in the first quarter of 2019. This is part of the Child Protection in Emergencies support in response to the crisis in north east Nigeria.