Methods

All of the data sources used to create Project Badweyn are fully cited in the informational pages associated with the map categories. Analysis of and changes to data by Secure Fisheries, besides purely aesthetic choices, are described here. We limited the spatial extent of data analyzed and displayed to the Somali region. Analyses were executed in ESRI ArcMap 10.3.1 unless otherwise indicated.

Maritime Boundaries

The shoreline shapefile (version 2.3.5) was obtained from the Global Self-consistent, Hierarchical, High-resolution Geography (GSHHG) Database (http://www.soest.hawaii.edu/wessel/gshhg/). We used that shoreline as the baseline for creating a 24 NM buffer to display boundaries of the 24 NM Territorial Sea.

The data to create the line for Claimed Territorial Waters (1972-2014) was downloaded from www.marineregions.org (version 9). The outline is displayed without changes. A line showing the area claimed by Kenya was included in the downloaded data. We removed that line in order to show the Somali claim clearly. We depict that line and the area contested by Kenya in the EEZ Contested Areas map.  

The line for the Exclusive Economic Zone (2014) and the polygons for the EEZ Contested Areas were created using the coordinates published by the United Nations (http://www.un.org/depts/los/LEGISLATIONANDTREATIES/STATEFILES/SOM.htm) without changes.

Coastal Habitats

A recent, original survey of Somali coastal habitats does not exist. We relied on publicly available datasets downloaded from the internet. Please see the following sources for detailed methodology for the creation of these datasets:

Coastal Fishes, Highly Migratory Fishes, Invertebrates

These layers show the percent likelihood that a given fish or invertebrate group of economic importance are present in Somali waters and the surrounding region. We used AquaMaps (http://www.aquamaps.org/) to obtain predicted geographical ranges for species in 18 groups of economically important fishes and invertebrates. AquaMaps assigns presence probabilities (Pp) across a global distribution based on how well an area meets the environmental suitability for a species. The species we chose to include were based on a literature review and interviews with Somali fishers and experts as part of the research for Secure Fisheries’ report, Securing Somali Fisheries (http://securefisheries.org/report/securing-somali-fisheries) . For each species, we downloaded the native range data that had been reviewed for AquaMaps by an expert. We used the computer generated data when reviewed data were unavailable.

For each species range dataset, probabilities were designated to the center of global half-degree latitude and longitude cells. We combined the species into 18 groups to determine probabilities of presence off the Somali coast for each group. In order to calculate the probability that any species (i) in a group exists in a given cell, we calculated the absence probability (Pa) from the presence probability for each species, or Pa,i. Multiplying together all the probabilities of absence for a particular cell calculated the total probability that none of the species in a group exist in that cell (Total Pa). Total presence probability, or the probability that any of the species or combination of species in the group exists in the cell, is the inverse of the total absence probability.

For each group, presence probabilities were transformed into percentages rounded to the nearest whole percent. To simplify the visualization, the data were grouped into bins of 20 percentage points and represented as color-coded polygons.

Human Activities

Landing Sites

Maps of Somali landing sites exist in a variety of publications for different time periods and regions, but we created the first comprehensive, up-to-date map of artisanal landing sites along the Somali coast. For this purpose, we defined landings sites as places where small, artisanal Somali boats bring their catch to shore. These are most often on beaches where fishers pull their boats onto the land accompanied by mooring sites in the water just off the beach. To identify landing sites, we searched satellite imagery for small boats on the beach or moored in the sea. Because we have not been able to ground truth these locations or the actual numbers of active fishing vessels, the counts associated with each site are approximations.

To create the map of landing sites, we used plugins for Google and Bing satellite imagery in QGIS, a free and open source Geographic Information System software program (www.qgis.org). At a zoom of around 1:2000, we scanned the Somali shoreline for small boats, starting at the northwestern border with Djibouti and covering the entire coastline to the southern border with Kenya. Where boats were found, the coastline was marked with a point to record latitude and longitude, and the name of the site was recorded if it was documented in the Google maps, or from consultation with Somalis or the United Nations Food and Agriculture Organization. The number of boats on the beach or within approximately 100m of the shoreline was counted in both Bing and Google images. If boats were visible on the water but there was no obvious landing or mooring site nearby, they were considered active, working boats and were not counted because their landing location was unknown.

The date of each Google image was obtained by loading the sites into Google Earth and zooming in to each location until the date of the image was visible. For Bing images, the date of the image was obtained by finding each location on the Bing Aerial Imagery Analyzer for OpenStreetMap (http://mvexel.dev.openstreetmap.org/bing/). When there was a range of dates given by the imagery analyzer, the earliest date was used. To get one number of boats to include in the data visualization, we used the most recent image if the dates were more than 5 years apart. If they were less than 5 years apart, we used the image with the most boats. This decision rule was based on balancing using the most up-to-date image while recognizing that vessels move regularly. Occasionally, this resulted in a site that had zero boats. In that case, the site remained on the map, but further investigation will be necessary to determine if it is an active, defunct, or temporary landing site.

Size of landing sites was classified by the number of boats. Each site was placed in one of four categories: 0-5 boats, 6-30 boats, 31-60 boats, and 61-210 boats. These designations were determined by the natural breaks in the histogram of number of boats and color coded and sized accordingly.

Foreign Fishing Areas – Highly Migratory Species

We created a simplistic representation of the intensity of foreign fishing for highly migratory species off the Somali coast by aggregating the purse seine catch data from the Indian Ocean Tuna Commission’s public database (http://iotc.org/data/datasets). These data are reported in 1 degree latitude and longitude cells. We summed the data in each cell over the entire time period available to clearly show the area of greatest catch. For the visualization, each cell was placed in one of five categories determined by the natural breaks in the histogram of catch and color coded accordingly.

Foreign Fishing Areas – Coastal Species

The map of foreign fishing for coastal species shows estimated areas of trawling based on parameters from the analysis of South Korean trawling vessels off the coast of Somalia published in Securing Somali Fisheries. Those vessels were found to be fishing only off the coast of Puntland, and our analysis found that they fish in areas shallower than 100m. Our research and personal communications indicate that other trawling vessels fish in the southern Somali waters near the border with Kenya and along the northern coast in the Gulf of Aden off Somaliland. Assuming that the trawling vessels operating in Somali waters are of similar or smaller size and use similar fishing gear, we created a polygon depicting the area from the shoreline to the 100m depth contour as a visualization of the potential trawling area in those regions. It is important to note that these areas are not actual trawling areas, but are theoretical fishing grounds given the limited information available.

We are not displaying the range of foreign gillnetters because we do not have reliable accounts of where those vessels operate, although they do fish in Somali waters and are responsible for a large proportion of the foreign catch of coastal species. For more information on those vessels, see Securing Somali Fisheries.

Shipping Traffic Density

In order to visualize the density of shipping traffic in the Horn of Africa region, we used automatic identification system (AIS) data, provided by ExactEarth (www.exactearth.com) for January-April 2016, for all non-fishing vessels in our area of interest. These data are satellite detections of vessels that broadcast identifying information and their position at intervals while they are in transit, anchored, or docked. To show the areas used most frequently by moving vessels, we excluded any points that had an associated speed over ground of zero in order to eliminate vessels that were anchored or in port. There were 49,617 total detections over the entire area and time period.

To display the density of shipping traffic, rather than individual ship detections as points, a 100 x 100 cell fishnet (grid of squares) was created for the area of interest. The AIS data were joined to the fishnet by spatial location to calculate the number of ship detections in each square of the grid. For the visualization, each square was placed in one of five categories determined by the natural breaks in the histogram of detection density and color coded accordingly. Squares that do not contain color contained little or no shipping traffic (0 or 1 detection).

Ports

The ports displayed are major ports designated as such in the Somalia Joint Needs Assessment by the United Nations (http://www.somali-jna.org/downloads/SJNAICR090906%20-%20Infrust%20Part%20I.pdf).

Go To Project Badweyn Overview and Interactive Map