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GISCorps & DHN collaboration for the 2016 Refugee & Migrant Crisis PDF Print E-mail

GISCorps & DHN collaboration for the 2016 Refugee & Migrant Crisis

With millions of people fleeing hardship and violence in Syria as well as many other countries, the humanitarian community is facing significant challenges. Coordinating the response to such a massive, long-term humanitarian situation across the many national, international, and local response actors requires collaboration and partnership. It also requires interoperable data so that everyone can have a common understanding of the crisis.

In response to this need the Digital Humanitarian Network (DHN) and GISCorps collaborated with UN and NGO organizations to map Communications infrastructure & to create and share Common Operational Datasets (CODs) for the European response.  In this case the CODs were focused on the administrative boundaries for the affected countries.  These are important as they are used by the humanitarian community to develop reference maps and other thematic maps to assist coordination and implementation of humanitarian operations.  They are the standard and agreed datasets for producing maps and managing geographic information.

The GISCorps team supported by DHN:

  1. Provided mapping support for a number of countries including Croatia, FYROM, Greece, Serbia, Slovenia and Jordan. The mapping support included creating
    • Country overview maps
    • Operational maps showing the status of sites in terms of the availability of Communications infrastructure
  2. Downloaded, cleaned and organized European Administrative Boundary Data to create the Common Operational Datasets for the European response

Mapping Support  

The biggest challenges encountered for this work were:

  • Ensuring that we were using agreed UN symbology wherever possible
  • Automating the process of using icons as labels and changing the colors of the icons to communicate changes to the status of sites

UN Symbology

The resources that were found to help with this were:

  1. The MapAction ocha_icons_user_guide_v2.0.pdf containing Unicode lookups on p10

 

Code for Auto labelling ArcGIS Maps using varied icon colors to depict site status

 

The challenge here was to use the icons described above as labels that varied in color depending on operational status of the infrastructure being mapped.

This was achieved using the following procedures:

  • Open the Layer Properties in ArcGIS and go to the Labeling Tab
  • Click on the Expression button, go to the Expression box, tick the Advanced box and change the Parser to VBScript
  • The following code can then be used (it requires us of Maplex):
Function FindLabel ( [Site_Name] , [FNeed_IntW] , [FNeed_Chrg] , [FNeed_Elec] , [FNeed_Mrki]  )templabel = [Site_Name] & vbNewLine
If( [FNeed_IntW] = "High") Thentemplabel = templabel & "<CLR red='230'> <FNT name='humanitarian-webfont' size = '20'> </FNT></CLR>"ElseIf( [FNeed_IntW] = "Medium") Thentemplabel = templabel & "<CLR red='230' green ='152'> <FNT name='humanitarian-webfont' size = '20'> </FNT></CLR>"End IfIf( [FNeed_Chrg] = "High") Thentemplabel = templabel & "<CLR red='230'> <FNT name='humanitarian-webfont' size = '20'></FNT></CLR>"ElseIf( [FNeed_Chrg] = "Medium") Thentemplabel = templabel & "<CLR red='230' green ='152'> <FNT name='humanitarian-webfont' size </CLR>"End IfIf( [FNeed_Elec] = "High") Thentemplabel = templabel & "<CLR red='230'> <FNT name='ESRI Default Marker' size = '20'>d</FNT></CLR>"ElseIf( [FNeed_Elec] = "Medium") Thentemplabel = templabel & "<CLR red='230' green ='152'> <FNT name='ESRI Default Marker' size = '20'>d</FNT></CLR>"End IfFindLabel = templabel

End Function

Common Operational Dataset Support 

This part of the project was done in support of the Regional Information Management Working Group for Europe (RIMWG-E), and aimed to make available the Administrative Boundary datasets (and other key datasets) for all countries affected by the European Refugee and Migrant Crisis.  This required finding authoritative sources of data, performing the necessary cleaning and organizing of the data (including ensuring that each dataset matched up with the names and codes being used by in-country humanitarian teams).

The achievements for this project included:

  • Data for 58 countries was downloaded from EuroGeographics and organized
  • Data for 3 countries was made publically available on HDX – see this blog post referring to the first 2 datasets that were published.  More recently, datasets for Turkey have been published including Administrative Boundaries, Roads, Rivers, Settlements and Camps 
  • Data for a further 2 countries is published internally for use by the Regional Information Management Working Group for Europe

This part of the project was subject to many delays as it required a long chain of feedback between in-country and remote teams.  The work for this project is still ongoing, but at a rate that can currently be handled without the need for ongoing GISCorps support.  However, if workload increases, it would be good to be able to call on the support of GISCorps again, and therefore the following notes have been made to help communication during future collaborations related to Common Operational Datasets.

Information about Common Operational Datasets (CODs) can be found here.  Whilst there are a number of types of Common Operational Datasets, the most frequently and urgently needed tend to be the Administrative Names and Boundaries for the country that has been affected by the emergency.  Generally administrative boundaries are hierarchical with Administrative level 1 being the first subdivision within a country, administrative level 2 being the next subdivision (usually nested within the boundaries of the administrative level 1 areas), and so on.  The key points to remember about Administrative boundary CODs are as follows:

1. There are naming conventions for the datasets which aim to make understanding the content easy for users before they even open the dataset.  The dataset naming is structured as follows:

  • Three letter ISO code_
  • admn(=Administrative Boundaries)_
  • adm1/2/3/4(=Admin boundary level)_
  • py(=Polygon)_
  • Source(add as many sources as needed)_
  • date_
  • pp(this relates to the permissions for sharing the data – pp=data and derived products can be made publicly available) 

  Examples: SRB_admn_adm0_py_EuroGeoGraphics_2015_pp.shp or

  SRB_bsm_admn_adm1_py_EuroGeoGraphics_GADM_2015_pp.shp

2. The datasets must contain the name of each administrative area, plus a ‘pcode’, which is a unique identifier for each area.  The datasets also tend to contain the names and pcodes for all higher level administrative areas (e.g. the administrative 1 dataset will contain the name and pcode for the country, plus the names and pcodes for all administrative level 1 areas.  The administrative level 2 dataset will contain the name and pcode for the country, plus the names and pcodes for all administrative level 1 areas, plus the names and pcodes for all administrative level 2 areas).  The pcode generally follows a structure as follows:

  • Three letter ISO code
  • A unique number for each area

Often the pcodes are also hierarchical, so that, for example in Serbia you might have SRB01 as the unique identifier for an administrative level 1 area.  You might then have SRB0101 for an administrative level 2 area.  Having the code hierarchical like this makes it easier for users to easily understand the hierarchy, as they will know that SRB0101 is within SRB01.