Difference between revisions of "Country correction"

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(Added some words on fit function.)
(Changed estimated country sizes)
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== Result ==
 
== Result ==
This approach has been applied on the following countries:
+
This approach has been applied on the following countries with a linear function:
 
{| class="wikitable sortable"
 
{| class="wikitable sortable"
 
|-
 
|-
 
! Country !! Centroid city !! size !! spreadsheet
 
! Country !! Centroid city !! size !! spreadsheet
 
|-
 
|-
| Albania || Tirana || 158 || link
+
| Albania || Tirana || 100 || link
 
|-
 
|-
| Algeria || Algers || 777 || [https://docs.google.com/spreadsheets/d/1SVDKX-9fjYr_K6U9G6OQlM1j1-pIQfWwGTVCl-60hSY/ link]
+
| Algeria || Algers || 370 || [https://docs.google.com/spreadsheets/d/1SVDKX-9fjYr_K6U9G6OQlM1j1-pIQfWwGTVCl-60hSY/ link]
 
|-
 
|-
| Austria || Vienna ||  385 || [https://docs.google.com/spreadsheets/d/1joXvrjWDmabsyFqf4V6bBsmCJHp0fhCB5oAy8nOStRU/ link]
+
| Austria || Vienna ||  230 || [https://docs.google.com/spreadsheets/d/1joXvrjWDmabsyFqf4V6bBsmCJHp0fhCB5oAy8nOStRU/ link]
 
|-
 
|-
| Belgium || Brussels || 165 || [https://docs.google.com/spreadsheets/d/1-_DRQi9VUrV2o5oVRL01DUBz9iT3ZvVPlvxvz9O_ZLg link]
+
| Belgium || Brussels || 86 || [https://docs.google.com/spreadsheets/d/1-_DRQi9VUrV2o5oVRL01DUBz9iT3ZvVPlvxvz9O_ZLg link]
 
|-
 
|-
| Bosnia and Herzegovina || Zenica || 283 || link
+
| Bosnia and Herzegovina || Zenica || || link
 
|-
 
|-
 
|- Bulgaria || Sofia ||  || [https://docs.google.com/spreadsheets/d/193RBhO4Dnd4ZwPbepP2oeyF5PkOMDeoxszSNuMW8VrQ link]
 
|- Bulgaria || Sofia ||  || [https://docs.google.com/spreadsheets/d/193RBhO4Dnd4ZwPbepP2oeyF5PkOMDeoxszSNuMW8VrQ link]
 
|-
 
|-
| Croatia || Zagreb || 236 || link
+
| Croatia || Zagreb || 160 || link
 
|-
 
|-
 
| Czech Republic || Prague || || [https://docs.google.com/spreadsheets/d/1QlsggBo0dOK-gvXR3-wOeeIQOLDSQ6J9TAGijCZ0ENg/ link]
 
| Czech Republic || Prague || || [https://docs.google.com/spreadsheets/d/1QlsggBo0dOK-gvXR3-wOeeIQOLDSQ6J9TAGijCZ0ENg/ link]
 
|-
 
|-
| Denmark || Copenhagen || 271 || [https://docs.google.com/spreadsheets/d/1uB0MooOA0xT8z9bRfZ1iaKxNph1FQgeUby0HmXSOrKw link]
+
| Denmark || Copenhagen || 170 || [https://docs.google.com/spreadsheets/d/1uB0MooOA0xT8z9bRfZ1iaKxNph1FQgeUby0HmXSOrKw link]
 
|-
 
|-
| Estonia || Tallinn || 152 || [https://docs.google.com/spreadsheets/d/1nhs-FE32-n0taDLiNHxZ71VBGC2mYrBHjLlwI_PNMsQ/ link]
+
| Estonia || Tallinn || 120 || [https://docs.google.com/spreadsheets/d/1nhs-FE32-n0taDLiNHxZ71VBGC2mYrBHjLlwI_PNMsQ/ link]
 
|-
 
|-
 
| Finland || Helsinki ||  || [https://docs.google.com/spreadsheets/d/1OXHdXZDUJ9So5oSP67ZWzkDdSaQADQdZbDMnp7ekXcU/ link]
 
| Finland || Helsinki ||  || [https://docs.google.com/spreadsheets/d/1OXHdXZDUJ9So5oSP67ZWzkDdSaQADQdZbDMnp7ekXcU/ link]
 
|-
 
|-
| France || Paris || 1051 || [https://docs.google.com/spreadsheets/d/1-G7VVZDE7xH6yzhsVYpmTTnu3rtgvadMC7WX9yIJqPc link]
+
| France || Paris || 430 || [https://docs.google.com/spreadsheets/d/1-G7VVZDE7xH6yzhsVYpmTTnu3rtgvadMC7WX9yIJqPc link]
 
|-
 
|-
| Germany || Hannover || 577 || [https://docs.google.com/spreadsheets/d/1HSNFq2sJiRxarSvY_mHtEOiSIq9fwFAyTh9lA4DfgF4 link]
+
| Germany || Hannover || 260 || [https://docs.google.com/spreadsheets/d/1HSNFq2sJiRxarSvY_mHtEOiSIq9fwFAyTh9lA4DfgF4 link]
 
|-
 
|-
 
| Greece || Athens || || [https://docs.google.com/spreadsheets/d/1RN6YIwDWLgLrultpRt49D83s3UCeAuQErZb4Orriv-Q link]
 
| Greece || Athens || || [https://docs.google.com/spreadsheets/d/1RN6YIwDWLgLrultpRt49D83s3UCeAuQErZb4Orriv-Q link]
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| Hungary || Budapest ||  || [https://docs.google.com/spreadsheets/d/16VZjIhacrZqKWNp95POnc2qKuLgpfTcIgs8Ygt6nxPI link]
 
| Hungary || Budapest ||  || [https://docs.google.com/spreadsheets/d/16VZjIhacrZqKWNp95POnc2qKuLgpfTcIgs8Ygt6nxPI link]
 
|-
 
|-
| Iceland || Reykjavik || 132 || [https://docs.google.com/spreadsheets/d/1skWHDUfRtpaUkjXy-WiCWhqGBI8st-FB9sjcMaIRiCc link]
+
| Iceland || Reykjavik || 87 || [https://docs.google.com/spreadsheets/d/1skWHDUfRtpaUkjXy-WiCWhqGBI8st-FB9sjcMaIRiCc link]
 
|-
 
|-
 
| Ireland || Dublin || || [https://docs.google.com/spreadsheets/d/15KY_dUl_3PB_taWZNkfdhcv9RhX7YgcyUC21aNADOdE link]
 
| Ireland || Dublin || || [https://docs.google.com/spreadsheets/d/15KY_dUl_3PB_taWZNkfdhcv9RhX7YgcyUC21aNADOdE link]
 
|-
 
|-
| Italy || Rome || 1226 || [https://docs.google.com/spreadsheets/d/19GxxwjgUrsMB522Vv_3zUCg-bJVyg054WwMK5S3tkP0 link]
+
| Italy || Rome || 520 || [https://docs.google.com/spreadsheets/d/19GxxwjgUrsMB522Vv_3zUCg-bJVyg054WwMK5S3tkP0 link]
 
|-  
 
|-  
| Latvia || Riga || || [https://docs.google.com/spreadsheets/d/1Ls57Onx80PpDggjztZgjOMDc0ikybXH2Rv7hsIIIav8/ link]
+
| Latvia || Riga || 77 || [https://docs.google.com/spreadsheets/d/1Ls57Onx80PpDggjztZgjOMDc0ikybXH2Rv7hsIIIav8/ link]
 
|-  
 
|-  
| Lithuania || Kaunas || || [https://docs.google.com/spreadsheets/d/1gz49-FMuaVvFIro2QgoIaxot24ysm1k_2fn6RJJxLF4 link]
+
| Lithuania || Kaunas || 120 || [https://docs.google.com/spreadsheets/d/1gz49-FMuaVvFIro2QgoIaxot24ysm1k_2fn6RJJxLF4 link]
 
|-
 
|-
 
| Montenegro || Bijelo Polje || || link   
 
| Montenegro || Bijelo Polje || || link   
 
|-
 
|-
| Morocco || Temara || 419 || link
+
| Morocco || Temara || 230 || link
 
|-
 
|-
| Netherlands || Utrecht || 137 || [https://docs.google.com/spreadsheets/d/1x8Vfb2ZIjsTmb0lRrO-8YHC6NKmgc58HtP_cNSjeOQY link]
+
| Netherlands || Utrecht || 72 || [https://docs.google.com/spreadsheets/d/1x8Vfb2ZIjsTmb0lRrO-8YHC6NKmgc58HtP_cNSjeOQY link]
 
|-
 
|-
| Norway || Skien || 455 || [https://docs.google.com/spreadsheets/d/1e3vPPWMyJu6k5rdbqDC9EGgOCgmAmsGZ2JO1oMrCbXw/edit link]
+
| Norway || Skien || 300 || [https://docs.google.com/spreadsheets/d/1e3vPPWMyJu6k5rdbqDC9EGgOCgmAmsGZ2JO1oMrCbXw/edit link]
 
|-
 
|-
| Poland || Łódź || || [https://docs.google.com/spreadsheets/d/1wBNuc3qItIouZHKLI-c9TrJcL2skF-T6sw_Yh1gPxM4 link]
+
| Poland || Łódź || 140 || [https://docs.google.com/spreadsheets/d/1wBNuc3qItIouZHKLI-c9TrJcL2skF-T6sw_Yh1gPxM4 link]
 
|-
 
|-
| Portugal || Lisboa || 228 || [https://docs.google.com/spreadsheets/d/1DBTu9pNtdLhf0hBPGqnYbLYXnxhAkX0f7eDcRBIrZGU link]
+
| Portugal || Lisboa || 140 || [https://docs.google.com/spreadsheets/d/1DBTu9pNtdLhf0hBPGqnYbLYXnxhAkX0f7eDcRBIrZGU link]
 
|-
 
|-
| Romania || Bucharest || 568 || [https://docs.google.com/spreadsheets/d/1V-39ygo6LszL2PWHUVi8VFtci1CExjpQLN7Y2w-nUXQ link]
+
| Romania || Bucharest || 300 || [https://docs.google.com/spreadsheets/d/1V-39ygo6LszL2PWHUVi8VFtci1CExjpQLN7Y2w-nUXQ link]
 
|-
 
|-
| Slovakia || Banská Bystrica || 254 || [https://docs.google.com/spreadsheets/d/1lTXNbUIM5ATG1C0TpzsgmtGnHFBqt0m2PBtRvVul0XE/ link]
+
| Slovakia || Banská Bystrica || 78 || [https://docs.google.com/spreadsheets/d/1lTXNbUIM5ATG1C0TpzsgmtGnHFBqt0m2PBtRvVul0XE/ link]
 
|-
 
|-
| Slovenia || Ljubljana || 119 || [https://docs.google.com/spreadsheets/d/1CVV7NGr2XZ-iYhE4c48Vm7WBhXPOxa79XrdV5GVck5E/ link]
+
| Slovenia || Ljubljana || 66 || [https://docs.google.com/spreadsheets/d/1CVV7NGr2XZ-iYhE4c48Vm7WBhXPOxa79XrdV5GVck5E/ link]
 
|-
 
|-
| Spain || Madrid || 653 || [https://docs.google.com/spreadsheets/d/1Zf0ks3MiWOHbh9CSNiZQwW3yy9jW3l7qFahGYBH-uc8 link]
+
| Spain || Madrid || 430 || [https://docs.google.com/spreadsheets/d/1Zf0ks3MiWOHbh9CSNiZQwW3yy9jW3l7qFahGYBH-uc8 link]
 
|-
 
|-
| Sweden || Nörrköping || 393 || [https://docs.google.com/spreadsheets/d/16kjE6_IIoqiOHdFB-x1rpJiEesRbNqhwXSv8HTyy_NQ link]
+
| Sweden || Nörrköping || 270 || [https://docs.google.com/spreadsheets/d/16kjE6_IIoqiOHdFB-x1rpJiEesRbNqhwXSv8HTyy_NQ link]
 
|-
 
|-
| Switzerland || Olten || 158 || [https://docs.google.com/spreadsheets/d/1VJ08fAdkbvnKAFDnn1RnNXQxWn9nzTK1y5GJ5AJFa1Y link]
+
| Switzerland || Olten || 120 || [https://docs.google.com/spreadsheets/d/1VJ08fAdkbvnKAFDnn1RnNXQxWn9nzTK1y5GJ5AJFa1Y link]
 
|-
 
|-
 
| Tunisia || Tunis ||  || link
 
| Tunisia || Tunis ||  || link
 
|-
 
|-
| United Kingdom || Coventry || 347 || [https://docs.google.com/spreadsheets/d/1xbNe-QDLIZt6h1HvLAa4jzTQoyifdLaiTr4UgaqbHNk link]
+
| United Kingdom || Coventry || 210 || [https://docs.google.com/spreadsheets/d/1xbNe-QDLIZt6h1HvLAa4jzTQoyifdLaiTr4UgaqbHNk link]
 
|-
 
|-
 
| European Union || Munich ||  || link
 
| European Union || Munich ||  || link
 
|-
 
|-
| Bouches du Rhône || Marseille || 25 || link
+
| Bouches du Rhône || Marseille || 22 || link
 
|}
 
|}
  

Revision as of 14:53, 6 March 2021

This page explores how the size of the country can be taken into account in the determination of the eco-score transport bonus.

Bonus approach

The eco-score approach intends to give a bonus to locally produced (and purchased) products. This bonus is +15, which is equal to a transport score of 100. This bonus is however now given to any product produced/purchased in France. No account has been taken of the very large size of France and impact of transport within the country.

Can this approach be adapted, so that the size of a country is taken into account?

Maximum bonus

It would be logic to give the maximum bonus (transport score if 100) only to very locally production and purchase. Ideally this will imply an area as small as possible, i.e. a city or very small country. Production and purchase that occurs in a country such as Andorra, Monaco, Liechtenstein or San Marino could be viewed as having a transportation score of 100.

No bonus

In the current calculation the no bonus (transportation score 0) is (arbitrarily) set at a distance of 2000 km. This distance covers roughly the size of Europe.

Centroids to the rescue

Is it possible to use the centroid calculations in determining the (transportation) size of a country?

The weighted sum for a country that consists of single city will be zero. This can then correspond to a transportation (bonus) score of 100. This means it is preferred to have no transportation.

The weighted sum of the major cities in the European Union (or larger area) could be used to define the transportation score of 0. This means a maximum transportation impact.

From Any weighted sum in between it is now possible to calculate a country transportation score. The larger the country, the lower the country transportation score. This country transportation score can be used to determine the maximum bonus for a country.

The centroid approach can also be used to calculate the country transportation size. We just have to add all cities, so that the entire population is covered. The resulting weighted distance is the size we are looking for.

In practice this approach is not feasible. It is just to much work to (to do by hand a least). So we need a way to get a reasonable approximation. For the calculation of the centroids a limited number of cities are used. We could try to extrapolate this data to get the transportation country size.

Approach

In the figure the results for Maroc are shown.

The population road-distance weighted transportation size of Maroc

The cumulative population weighted distances are plotted against the cumulative population ratios. Each added city adds a point, increasing the cumulative population ratio and the cumulative distance. If the cumulative population ratio is 1, we have covered the entire population. And the corresponding cumulative distance is the value we are looking for.

Instead of adding all the cities, we could fit a line to the data of a few city points. The cumulative distance of the fit at a population ratio of 1, is then again the value we are looking for.

The function to fit must behave nicely with extrapolations. This excludes complex functions with many parameters. Or functions which behave not regular outside the fitted points (polynomials).

This leaves the following functions:

  • linear - results in average values;
  • logarithmic - results in smaller values;
  • power functions - results in larger values;

In the graph for Maroc a logarithmic function is used. The largest cities are not used in the fit calculation, as these ones seem not to follow the curve. They would bias the fit to much, when we use so few points. The fit will result in a transportation size of 419 km. Compare this to a maximum actual distance of about 1000 km.

Result

This approach has been applied on the following countries with a linear function:

Country Centroid city size spreadsheet
Albania Tirana 100 link
Algeria Algers 370 link
Austria Vienna 230 link
Belgium Brussels 86 link
Bosnia and Herzegovina Zenica link
Croatia Zagreb 160 link
Czech Republic Prague link
Denmark Copenhagen 170 link
Estonia Tallinn 120 link
Finland Helsinki link
France Paris 430 link
Germany Hannover 260 link
Greece Athens link
Hungary Budapest link
Iceland Reykjavik 87 link
Ireland Dublin link
Italy Rome 520 link
Latvia Riga 77 link
Lithuania Kaunas 120 link
Montenegro Bijelo Polje link
Morocco Temara 230 link
Netherlands Utrecht 72 link
Norway Skien 300 link
Poland Łódź 140 link
Portugal Lisboa 140 link
Romania Bucharest 300 link
Slovakia Banská Bystrica 78 link
Slovenia Ljubljana 66 link
Spain Madrid 430 link
Sweden Nörrköping 270 link
Switzerland Olten 120 link
Tunisia Tunis link
United Kingdom Coventry 210 link
European Union Munich link
Bouches du Rhône Marseille 22 link

Comments

Some observations on individual countries.

  • Iceland - the weighted distance graph contains several steps, due to the addition of cities far from the centroid. This introduces strange fits, if we use all cities So only the 9 (of 20) smaller cities have been used in the fit;

Conclusion

The graph below shows the malus for each country based on population road-distance weighted transportation distance. The location of the circles is on the country centroid.

The transportation malus for each country (or territory).

Some observations:

  • France and Italy have the largest malus. In order to cover the entire population a large distance is required;
  • Bouches du Rhône has the smallest malus of this set;