Source: The map is published on UNEP's South Sudan: First State of Environment and Outlook Report 2018 with a source identified as University of Maryland, 2018, no date indicated. The UNEP's report could be found <a href="https://www.unenvironment.org/resources/report/south-sudan-first-state-environment-and-outlook-report-2018" target="_blank"> here </a> <br><br>There are no reliable data on the extent of forests in South Sudan, since a detailed forest survey and inventory has never been carried out. Analyses based on remote sensing exist, which provide different estimates, but they have not been verified on the ground, so the accuracy of such products is unknown. The map is a satellite image that suggests the total area of tree cover in South Sudan is almost 20,000,000 ha (19,166,700 ha or 191,667 km2), which represents about 30 per cent of the country’s total land area (<a href="https://www.cbd.int/doc/world/ss/ss-nr-05-en.pdf" target="_blank"> MOE, 2015 </a>). This includes natural forests and woodlands, tropical moist forests on the hills, in the mountains and in the Nile-Congo watershed, and forests in National Parks and game reserves.

Source: Map created by EPI (Elephant Protection Initiative) with data from CIESIN, Columbia University, USA. The map is published on UNEP's South Sudan: First State of Environment and Outlook Report 2018, using data from WCS. The UNEP's report could be found <a href="https://www.unenvironment.org/resources/report/south-sudan-first-state-environment-and-outlook-report-2018" target=_blank> here </a> <br><br> The map shows the population distribution in South Sudan. Jonglei is the most populous area, with 16 per cent of the total population, and Western Bahr el Ghazal is the least populous area with only 4 per cent of the total. The highest population densities are along the Nile River and their tributaries.

Source: ESA (European Space Agency), retrieved <a href="http://due.esrin.esa.int/page_globcover.php" target="_blank"> here </a> <br><br>Most of the country is covered with natural and semi-natural vegetation with variable tree density. Vegetation cover is mostly high in the southwest, with thick tropical forests in the Greater Equatoria region, and low in the southeast and north, where semi-arid savannah dominates. Grasslands, aquatic vegetation and open water occupy the wetter regions. A large part of South Sudan is covered by the Sudd swamp, a conglomeration of smaller wetlands.

Source: The map is published on UNEP's South Sudan: First State of Environment and Outlook Report 2018, using data from WCS. The UNEP's report could be found <a href="https://www.unenvironment.org/resources/report/south-sudan-first-state-environment-and-outlook-report-2018" target="_blank"> here </a> <br><br>The map shows the location and distribution of South Sudan’s principal wetlands, the most important of which are the Sudd and Machar swamps.

Source: Bastiaanssen, W., Karimi, P., Rebelo, L.-M., Duan, Z., Senay, G., Muthuwatte, L., & et al. (6). (2014). Earth Observation Based Assessment of the Water Production and Water Consumption of Nile Basin Agro-Ecosystems. Remote Sensing, 6(11), 10306-10334. doi:10.3390/rs61110306 <br><br>The vast wetlands in Southern Sudan are characterised by huge evaporation rates from the Sudd, Bahr el Ghazal and the Sobat sub-basins (Mohamed, Bastiaanssen, & Savenije, 2004). About half of the flow into the White Nile is lost mainly to evaporation and transpiration in the wetlands of South Sudan (FAO, 2011) and approximately half of the Bahr el Jebel flow is lost to evaporation (NBI, 2016). In total, long-term evaporation is thought to account for water losses as high as 85 per cent of the total inflows into the Sudd wetlands (Senay, Velpur, Bohma, Demissie, & Gebremkhael, 2014). Analysis of the rate of water loss to evapotranspiration in the Sudd wetlands found that the central part of the Sudd (not counting the seasonally flooded pastures surrounding the wetlands) has evapotranspiration rates between 1,500 and 2,000 mm/yr.

This data represents the 30 meters Digital Elevation Model (DEM) from Shuttle Radar Topography Mission (SRTM). This data-set was derived through mosaicking of individual SRTM tiles for a particular country and clipping the mosaicked tiles using the country boundary extent.