Key Risk Drivers Map

Use the Key Risk Drivers Map to visualize multiple layers of FEWS NET and partner data, contextualizing the impact of various risks in selected locations.

Creating a Key Risk Drivers Map

Use the following guidelines to create and modify a Key Risk Drivers Map.

1. Select a data layer

Select one of the following data layers to display on the map:

ACLED: Numbers and types of individual conflicts by approximate location from ACLED.

CROSS_BORDER_MOVEMENT: Numbers of individuals who have migrated by their approximate location of origin and current country location. This option displays IOM data for Sudan from May 2023 to September 2023.

SSP245_DAYS_MONTHLY: Monthly days of extreme heat using the SSP245 future emission scenario.

SSP585_DAYS_MONTHLY: Monthly days of extreme heat using the SSP585 future emission scenario.

SSP245_PEOPLE_MONTHLY: Monthly human exposure to extreme heat days count using the SSP245 future emission scenario.

SSP585_PEOPLE_MONTHLY: Monthly human exposure to extreme heat days count using the SSP585 future emission scenario.

SSP245_DAYS_ANNUAL: Annual days of extreme heat using the SSP245 future emission scenario.

SSP585_DAYS_ANNUAL: Annual days of extreme heat using the SSP585 future emission scenario.

SSP245_PEOPLE_ANNUAL: Annual human exposure to extreme heat days count using the SSP245 future emission scenario.

SSP585_PEOPLE_ANNUAL: Annual human exposure to extreme heat days count using the SSP585 future emission scenario.

DTM_INTERNAL_MIGRATION: Numbers of internally displaced people by their approximate location of origin and current location as reported by IOM.

NO_DATA: Select this option if you do not want to show a data layer.

MIGRATION_FLOW: Numbers of internally displaced people by their approximate location of origin and current location as reported by IOM. This option displays data for Sudan from April 2023 to April 2024, and for Mozambique from May 2021 to August 2023. Use the DTM_INTERNAL_MIGRATION option to visualize the most up-to-date migration data for a wide range of countries.

2. Select a base layer

Select one of the following base layers to display on the map:

No_data: Select this option if you do not want to show a base layer.

ficml1: FEWS NET’s IPC 3.1 Acute Food Insecurity Classifications for the most recent near term projection period.

population: LandScan population estimates per square kilometer from 2022.

flood_detection: Most recent 5 day VIIRS composite data for inferred moisture type and floodwater fraction.

chirps_2023: CHIRPS 3-monthly anomaly in millimeters for July-September 2023.

chirps_2015: CHIRPS 3-monthly anomaly in millimeters for July-September 2015.

ndvi_2023: NDVI EVIIRS pentad percent of mean for October 16-25, 2023.

ndvi_2015: NDVI EVIIRS pentad percent of mean for October 16-25, 2015.

ssp_observed: Observed heat exposure in million people days 2000-2016.

ssp245: Projected heat exposure in million people days using the SSP245 future emission scenario. As this option contains less detailed data, using the SSP245 base layers options described above is recommended.

ssp585: Projected heat exposure in million people days using the SSP585 future emission scenario. As this option contains less detailed data, using the SSP585 base layers options described above is recommended.

trade_flow: Trade flow between key market centers. Available for Sudan. After generating the map, use the dropdown in the map header to choose between millet grain, sorghum, or wheat grain trade flow.

3. Select geography

Select either one or more countries or a geographic group.

Countries: Select one or more countries using the ISO 3166-1 alpha-2 two letter codes in the dropdown list.

Geographic group: Select a geographic group using the extended M.49 code from the dropdown list.

The codes for FEWS NET’s primary geographic groups are shown in the table below.

4. Generate the map

Click Generate to view the chart.

To change the data on the map, you can remove and add filters and click Update chart.

Saving the visualization

After creating the Key Risk Drivers Map, you can save it to your account for future reference using the Save visualization button in the upper right side of the page. Enter a Title and Description in the popup and click Save visualization. You can access saved visualizations from the Visualizations tab in the top header.

Interacting with the map

You can interact with the Key Risk Drivers Map in several ways:

• Change the date: Select a date from the timeline to change the period date of the data layer. The timeline is not available for base layers.

• View details: Click on an area on the map to see details for the data layer you selected.

  • For bubbles covering multiple conflicts or areas of displacement, you must first zoom in until the smallest available point displays.

  • For migration flow maps, you can also click on an arrow between bubbles to view the number of displaced individuals and households for a migration flow.

• Reposition the map: Click and drag to reposition the map. This can be helpful when viewing the pop up window that appears after selecting a point on the map.

• Zoom in/out: Use the zoom buttons and zoom in and out of the map.

• Full screen: Click the full screen button to view the map in full screen.

Visualization link

Use the Copy link button to copy the URL of the data visualization. The link can be used to open the data visualization in a new tab or window, and the parameters can be added or edited directly within the URL.

About partner data

Conflict

Armed Conflict Location & Event Data Project (ACLED) data on conflict events is ingested weekly and is subject to change, as reporting delays and corrections to past data are common due to challenges gathering conflict data.

The reported coordinates for conflict events are matched to the Admin 2 level where available in the FEWS NET Data Warehouse. Otherwise, the data is stored at the Admin 1 or Admin 0 level. Conflict events are displayed on the map using the coordinates provided by ACLED.

Migration

International Organization for Migration (IOM) releases migration flow data on an ad hoc basis. This data includes the approximate origin location and number of people that left their homes due to conflict, and the approximate current location and number of internally displaced people.

Extreme heat

Extreme heat days are defined as days with Wet Bulb Globe Temperatures (WBGT) of 30°C/86°F or higher. WBGT humid-heat temperatures incorporate both air temperatures and relative humidity, with more humid areas having higher values than less humid areas with the same air temperature. Areas that are hot and humid are considered more hazardous to human and animal health.

Person-days refers to the total number of days of extreme heat experienced in a year multiplied by the population in a given geography that experienced such heat. This number is divided by one million to provide million person-days per year.

Shared Socioeconomic Pathways (SSPs) refer to climate change scenarios of projected socioeconomic global changes up to 2100 as defined in the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report. SSPs are used to derive greenhouse gas emissions scenarios with different climate policies:

• SSP245 uses a “middle of the road” emission set of assumptions to inform its heat projections, reflecting a more optimistic scenario. This scenario assumes an additional radiative forcing of 4.5 W/m² by the year 2100 and reflects a medium pathway of emission scenarios in current literature.

• SSP585 uses higher emission assumptions and reflects a hotter, more pessimistic scenario. This scenario assumes an additional radiative forcing of 8.5 W/m² by the year 2100 and represents the highest emission scenarios in current literature. 

The 2016 extreme heat data shows observed data averaged from 2007 to 2016 provided by the Climate Hazards Center Coupled Model Intercomparison Project Phase 6 (CHC-CMIP6). 

The 2030 and 2050 extreme heat data shows projected data from the Climate Hazards Center Coupled Model Intercomparison Project Phase 6 (CHC-CMIP6).

Flooding

Flood detection data is provided by NOAA VIIRS. The relationship between flooding and food security is complex, and flood detection data are provided as a base layer for situational awareness. While some food production systems are reliant on flood water for irrigation, floods can also impact food security by damaging infrastructure.

Drought

The Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) rainfall Dataset is used for trend analysis and seasonal drought monitoring. CHIRPS anomaly data refers to the difference between current rainfall and the historical average in millimeters.

The Landsat Normalized Difference Vegetation Index (NDVI) Dataset captures the vegetative health for the October 16 to October 25 pentad. The NDVI percent of mean compares the current composite to the historical average conditions. Values between 95 and 105 indicate average conditions, values below 95 represent below average vegetation conditions, and values above 105 represent above average conditions.

CHIRPS and NDVI data from two El Niño years, 2023 and 2015, is included to enable comparison.