3 Methodological note

The project involved three major steps:

  1. Refining the shop classification used in the RSV database and cleaning the database accordingly
  2. Geocoding the RSV database in order to produce a georeferenced database
  3. Mapping the georeferenced database onto an online mapping application

3.1 Data cleaning and altered shop classification

3.1.1 Presentation of the data from RSV

3.1.1.1 The perimeter covered by the RSV database

Data have been provided by Rannsóknasetur verslunarinnar in an Excel Spreadsheet. Data includes the shop inventory from 2015, 2019 and June 2020 with the following variables:

  • Ár
  • Fyrirtæki
  • Heimilisfang
  • Numer
  • Gata
  • Meginflokkur
  • Undirflokkur

It is worth noticing that the shop inventories do not cover the same perimeter over the three years (see the mapping of each year on Figure 3.1). Especially, the streets of Grandi are not included in the 2015 survey. No shop was identified on Njálsgata in 2015. The total number of shops in the database for the entire area is therefore not comparable. For sake of comparison, the statistics presented in this report do not include Grandi.

2015 2019 2020
Grandagarður 0 73 108
Fiskislóð 0 72 68
Hafnartorg 0 4 28
Hólmaslóð 0 21 20
Garðastræti 0 16 14
Njálsgata 0 12 12
Eyjarslóð 0 11 11
Lindargata 0 6 6
Sölvhólsgata 0 4 5
Hallveigarstígur 0 4 3
Kárastígur 0 3 2
Veghúsastígur 0 1 1
Aðalstræti 0 1 0
Perimeter covered by the survey

Figure 3.1: Perimeter covered by the survey

3.1.1.2 The classification used by the RSV datase

The RSV database is based on a two-level classification:

  • Category 1: Meginflokkur (3 categories in 2015; 4 categories in 2019 and 2020 - vacancy were not reported in 2015).
  • Category 2: Undirflokkur (50 categories).
Shop classification used by RSV

Figure 3.2: Shop classification used by RSV

As shown in the following table, in the original version of the database, ‘Önnur þjónustustarfsemi’ was the most represented category of shop (all year included) which can bias the interpretation of statistics. To avoid this pitfall, all the shops that were falling into this category have been reclassified in a better-suited category. Besides, several shops were not assigned any categories (#N/A or #REF).

Undirflokkur Count Percentage
Önnur þjónustustarfsemi 465 13.7
Matsölustaður 273 8.0
Föt og skór 263 7.8
Gistiheimili 176 5.2
Önnur verslun 162 4.8
Stofnanir/Samtök/Félög 129 3.8
Bar/Skemmtistaður 120 3.5
Arkitekt 114 3.4
Skyndibiti 112 3.3
Gjafa- og minjagripir 92 2.7
Lögfræðiþjónusta 85 2.5
Kaffi 80 2.4
Úr og skart 80 2.4
Ráðgjöf 72 2.1
Ráðuneiti/Embætti/svið 72 2.1
Ferðamannaþjónusta 71 2.1
Hárgreiðsla 71 2.1
#N/A 66 1.9
Hugbúnaðargerð 65 1.9
Önnur menning 65 1.9
60 1.8
Listasafn 58 1.7
Auglýsingar og markaðsþjónusta 53 1.6
Fasteignir og leiga 46 1.4
Útgáfufélag 44 1.3
Matur 42 1.2
Kvikmynda- og tónlistagerð 40 1.2
Heilbrigðisþjónusta 39 1.1
Bækur, tónlist 37 1.1
Ljósmyndastofa 36 1.1
Sálfræðiaðstoð 35 1.0
Viðgerðir/Þrif 35 1.0
Hönnun 32 0.9
Búsáhöld 28 0.8
Gallerí 27 0.8
Tannlækningar 27 0.8
Önnur veitingastarfsemi 25 0.7
Snyrtivöruverslun 19 0.6
Leikhús / Kvikmyndir 18 0.5
Gleraugnaverslun 17 0.5
Fræðslusetur 14 0.4
Raftæki, tölvur 10 0.3
Hannyrðaverslun 9 0.3
Tómt 3 0.1
#REF! 2 0.1
Augnlæknir 1 0.0
Önnur þjónusta 1 0.0
Sálfræði aðstoð 1 0.0

3.1.2 Data cleaning : a new shop classification

The first step of this project has therefore consisted in a significant cleaning of the database to (1) complete missing data, (2) refine the shop classification and (3) reassign the proper category to most of the shops that were previously falling into the “Önnur þjónustustarfsemi” category. The websites https://ja.is and https://www.skatturinn.is/ have been used to allocate the appropriate category to these shops. Figure 3.3 and the following table show the new classification and the statistics after data cleaning.

The new shop classification is largely inspired by the one implemented by the Parisian planning agency (APUR). This institution has created an observatory of businesses and shops in early 2000s.1 This observatory mainly relies on a periodical survey of all the shop in Paris, which fuels a georeferenced and open-access database of the retail structures in Paris. For each address, the survey mentions the name of the shop and its type, following a detailed three-level classification (see appendix).

New shop classification

Figure 3.3: New shop classification

Here are the new statistics after data cleaning:

Category 3 Count Percentage
Restaurant 273 8.0
Clothes and shoes 263 7.8
Other service activities 194 5.7
Tourism accommodation 179 5.3
Institutions / Organizations / Associations 168 5.0
Other shop 162 4.8
Bar / Entertainment 122 3.6
Architect 117 3.4
Fast food 112 3.3
Vacancy 102 3.0
Advice 92 2.7
Gifts and souvenirs 92 2.7
Other cultural activity 92 2.7
Legal services 87 2.6
Tourist services 81 2.4
Café 80 2.4
Software development 80 2.4
Watches and jewelry 80 2.4
Ministry / Office / Division 72 2.1
Hairdressing 71 2.1
Advertising and marketing services 60 1.8
Art Museum 59 1.7
Real estate and rent 51 1.5
Publishing company 50 1.5
Film and music production 42 1.2
Food 42 1.2
Photography studio 40 1.2
Health care 39 1.1
Books, music 37 1.1
Repairs / Cleaning 37 1.1
Bank and financial service 36 1.1
Psychological assistance 36 1.1
Design 34 1.0
Household utensils 33 1.0
Other restaurant activities 33 1.0
Gallery 32 0.9
Dentistry 29 0.9
Other company service 23 0.7
Training center 20 0.6
Cosmetics store 19 0.6
Eyewear store 18 0.5
Other personal services 18 0.5
Theater / Movies 18 0.5
Electronics, computers 11 0.3
Gas station 9 0.3
Male hair shop 9 0.3
Gambling 8 0.2
Car rental 7 0.2
Car repair 6 0.2
Other medical practice 6 0.2
Beauty salon 5 0.1
Carwash 2 0.1
Other car-related company 2 0.1
Eye doctor 1 0.0
Taxi 1 0.0

3.2 Geocoding the database

Since the main purpose of the project is to provide a spatial analysis of shop changes in Miðborg, a key step was to geocode (i.e., to assign geographical coordinates) to each shop listed in the database in order to be able to map shops in a GIS. The geocoding process has been implemented with ArcGIS Pro (License: Sorbonne University, Faculté des Lettres). The database was split into three sub databases (one for 2015, one for 2019 and one for 2020), each of them was geocoded. A specific shapefile has been created for each sub-category of shop.

3.3 Mapping the georeferenced database onto an online mapping application

The geographical information produced through the geocoding process has been displayed on an online application available at that link: https://fl-su.maps.arcgis.com/apps/webappviewer/index.html?id=9dd7e923a6ca472fadabcf3f20d3617d

The application provides different tools:

  • Display: Choose what layers you want to see on the map by clicking on the layer button .
  • Explore:
    • To get more information about a peculiar shop or street, just click on the shop or street and a pop-up window will open.
    • You can use the select button to get some statistics about some subcategories of shop for a specific sub-area. Just draw on the map the area that you are interested in and a pop-up window will appear and the counting for the categories of shop you are interested in.
    • You can also display diagrams showing the number of shops for each category by clicking on the diagram button.
  • Export: You can export the map as a *.pdf or other format by clicking on the print button.