By Samuel Goulding, GEOINT Graduate, European Maritime Safety Agency, Lisboa, Portugal; Marco Painho, Ph.D., Nova Information Management, Universidade Nova de Lisboa, Portugal; Fernando Gil, MSc, CGP-GTM, Infraestruturas de Portugal, S.A, Almada, Portugal

Immigration is and always has been a factor that shapes politics, economics, and cultures at an international level. In Europe, the number of irregular entries along the continent’s external border reached a record high in 2014, registering around 280,000 migrants crossing the EU border illegally. As an EU member, Portugal has been very active in not only participating in joint operations, but also in the development of new methodologies for monitoring and detecting irregular migrants, mainly through the testing of drones from a Portuguese airbase in the southern part of the country (the Algarve).

At the national level, Portugal does not have a problem with immigration, but this article seeks to evaluate the Portuguese coast to determine its permeability to irregular entry via the sea. This evaluation was developed as a possible future tool that Portuguese border guards could use to identify the most critical areas along the Portuguese shoreline. Though it is not the case right now, Portugal could become the next country of entry for migrants leaving North Africa due to the ever-increasing levels of monitoring, detection, and overall security on the Mediterranean Sea.

Portugal’s coastline is 943 kilometers long, but for this analysis, we are only taking into account the south and southwest coastline (the Algarve and Alentejo regions), assuming an individual trying to enter Portuguese territory from the North of Africa would try a disembark in this area.

Methodology

The permeability model, named MARFRONT, was developed by determining the friction levels an adult would encounter when entering Portugal through its coast. It is important to mention that friction and permeability levels are inversely correlated. The model was computed based on a Multicriteria Evaluation (MCE) and couples two methodologies developed for the EU by the Joint Research Centre (JRC) and the European Union Satellite Centre (SATCEN).

The methodology developed by JRC, called Model EU25,[1] had the objective of determining the permeability of land borders at a European level by combining three criteria that represented a group of variables and would directly influence the friction experienced by an individual crossing the border unlawfully by foot. On the other hand, the model developed by SATCEN in 2017, called the Geospatial Vulnerability Indicator (GVI),[2] is a model intended for the same purpose, but at a more local level.

The MARFRONT model is a coupling of both methodologies presented above in terms of techniques, variables, and criteria, but is adapted to the Portuguese reality using national data sources at a 30-meter resolution. It is important to note that data and information about the sea, mainly average sea conditions and depth, would be of great value for this model, but was not incorporated due to the simultaneous unavailability of data at our scale of analysis and time restrictions. Portugal is currently developing new geospatial products for the Portuguese sea that will be available in 2020, which could greatly improve this model.

Every criterion is a combination of variables that have been normalized by a reclassification based on a linear function that varies between 0 and 1, and directly influence border permeability. The weights defined for each criterion had an exploratory basis, with the goal of understanding how each criterion or groups of criteria impacted the outputs based on different scenarios.

Data

The data layers include:

  • Railways (OpenStreetMap, 2019).
  • Roads (OpenStreetMap, 2019).
  • Land Cover/Use (Direção Geral do Território, 2015).
  • Digital Terrain Model (Direção Geral do Território, 2015).
  • Resident Population by Administrative Subsection (Instituto Nacional de Estatística, 2011).
  • Border Control Points (BCPs) (Official Journal of the European Union, 2013).
  • Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (National Oceanic and Atmospheric Administration (NOAA) 2019).

Border Permeability

In general, “permeability” is a term borrowed from the physical sciences, where it has the precise meaning of a process that measures the ease with which a fluid goes through a material. Boundary permeability is the product of the line characteristics (the outcome of legal, geographical, historical, and social factors) and the pressures on this line from people, goods, capital, ideas, and so on. The higher the permeability, the easier it will be to traverse that boundary. This term is often used in environmental studies, mainly geology. In this case, border permeability refers specifically to the factors that directly influence the capability of a human being to cross the border line.

Border permeability can transcend physical barriers and be alternatively identified by social integration, economic flow, or political relationships.[3]

In this article, we are determining the friction of the physical barriers that directly impact border permeability by creating and combining a group of criteria, defined by variables, in order to compute MARFRONT’s different outputs.

The MARFRONT Model

With all variables normalized, four criteria were identified, each representing factors that influence the success of an adult entering Portuguese territory undetected through the coastline. These criteria are:

  1. Security area.
  2. Hide capability.
  3. Communication network density indicator.
  4. Terrain permeability.

The concept of mobility is a central issue when determining border permeability due to it being a factor that directly correlates with the success/failure of crossing the border undetected. Because of its importance, two of the criteria focus more on this issue: terrain permeability (TP) and communication network density indicator (CNDI). Both these criteria were created and developed based on SATCEN’s methodology. The CNDI, which varies between 0 and 1, determines how easily and quickly an individual can reach a road or railway from the coastline. This was determined by the density of communication networks and distance of each road and railway segment from the border. The higher the CNDI, the closer to the border and the denser the communication networks.

On the other hand, TP determines how easily an individual crosses the terrain based on slope, land use, and roads. The criterion provides an overview of how permeable the terrain is accounting only for geographic parameters. Land use and slope was classified from 1 to 5 based on empirical levels of difficulty defined in SATCEN’s methodology. The CNDI was used in this criterion as a variable to represent the access to roads and railways from the coast.

Hide capability is the criterion that determines where along the coast are the best or worst areas to hide from detection when entering irregularly. To determine this criterion, we used the same approach as in Model EU25, which assumed an adult, to evade detection, would want to avoid densely populated areas, flat areas, and lights at night, and would try to seek areas with more vegetation.

Figure 1. Detailed results for the MARFRONT model for the equal weights case.

Security in area is an important criterion because it heavily influences the friction levels regarding border permeability along the Portuguese coast. This criterion is based on the location of the border control points (BCPs) and the cost distance from these to the coastline, based on the variable TP already determined. This means the closer the entry point is to the BCP, and the more permeable ground there is en route to the entry point, the higher the level of security will be.

All criteria were combined in a weighted linear combination (WLC) with empirically assigned weights based on different scenarios that could determine more importance to one criterion compared to another. Table 1 shows the four different weight combinations for each output.

Table 1. Criteria weights in each weighted linear combination (WLC) output.

Results and Conclusion

Based on the MARFRONT model and its variations, represented by assigning different weights to the criteria, we observed the statistics listed in Table 2 regarding the different outputs.

Table 2. Results, in percentage and square kilometers, for high permeability and low permeability by multicriteria evaluation.

This led us to draw the following main conclusions:

  • The four variations used in the multicriteria analysis are a good representation of the range of permeability that the same variables allow us to represent.
  • In general, the Alentejo coast is more permeable than the Algarve coast (Figure 1).

This led us to choose the Equal Weights methodology for a more local and detailed analysis, because it represents a better distribution of the data along our area of interest. Of all the combinations, this was the one that had the most balanced spatial representation at an administrative level. Building a model remains a choice between realism (mimics reality), precision (quantitatively correct), and generality (application to different places).[4] So, for this model, the importance given to each criterion can be adjusted to the reality of each scenario.

Based on this output ( Figure 1), and at a more detailed level, we were also able to conclude:

  • The most permeable regions of Coastal Alentejo are in the north of Grândola County and in the south of Odemira County.
  • The most permeable regions of Coastal Algarve are in the north of Aljezur County, which forms a continuous area of high permeability with Odemira County in southern Alentejo.
  • Within this continuous area, six potential entry points were identified where an individual could easily make the transition from sea to land.

In short, according to the MARFRONT model, the southwest Portuguese shoreline is the most permeable of the region under analysis. Within these areas, we identified the six most critical sections within the most permeable areas. Although these are not the only possible points of entry, they’re the easiest paths through the natural cliff barrier that surrounds most of the Portuguese coast, and therefore are assumed to be the main points of entry of an irregular immigrant within this area.

Lastly, it is important to note that the introduction of BCPs along the coastline has an increasing effect on the friction represented spatially, and thus reduces permeability. This is obvious in Table 2, where the Algarve, because of the higher number of BCPs, has a larger area of low permeability when more weight is given to the security factors. At a European level, with the recent migration crisis, the monitoring and control of the entry points for irregular migrants has been one of the main factors that has contributed to the diminishing flow of this type of activity.

Apart from physical constraints like barriers and BCPs, we should also consider Europe’s footsteps, for example, creating legal corridors for desperate individuals who have the right to claim asylum so they can do so without risking their lives. This is an effective way of channeling irregular migration in a controlled manner. This is not only safer, but more efficient, because it creates a mechanism through which member states can legitimately and easily control and monitor increased migration.

If Portugal ever experiences a migration crisis, like other EU members have in the past and present, the first step would be to implement more monitor-and-control capabilities at critical points of entry. The MARFRONT model represents a potential first step in identifying the critical areas and entry points, and could thus enable the introduction of new BCPs to monitor and control the irregular flow of people.


  1. N. Stephenne and M. Pesaresi. Spatial Permiability Model at the European Union Land Border. 2006. Joint Research Centre (JRC).
  2. European Union Satelite Centre. Geospatial Vulnerability Service: Tier-1 Production Methodology, 1–13. (2017). (Task Reference: R17060 to R17064).
  3. Cigdem Varol and Emrah Söylemez. Border Permeability and drivers Of CrossBorder Cooperation in the Turkish and EU Border Region. KnE Social Sciences. 2017. 1. 87. 10.18502/kss.v1i2.649.
  4. R. Levins. “The Strategy of Model Building in Population Biology. American Scientist. 1966: 54(4):421-431.

Related


Posted by USGIF