Rankings

Danish municipalities with the most fields

Ranking of field counts across Danish municipalities. Based on Crop Pulse 2026.

Provisional 2026 data

Top 15

Danish municipalities with the most fields
Data behind the chart: Danish municipalities with the most fields

Municipality rankings

Danish municipalities with the most fields · 2026
RankMunicipalityValue
1Viborg23,459
2Ringkøbing-Skjern19,825
3Herning18,797
4Varde18,364
5Vejle17,062
6Tønder16,911
7Aalborg16,013
8Hjørring15,111
9Aabenraa14,298
10Thisted14,024
View all 90 municipalities
Danish municipalities with the most fields · 2026
RankMunicipalityValue
1Viborg23,459
2Ringkøbing-Skjern19,825
3Herning18,797
4Varde18,364
5Vejle17,062
6Tønder16,911
7Aalborg16,013
8Hjørring15,111
9Aabenraa14,298
10Thisted14,024
11Vejen12,620
12Esbjerg12,044
12Vesthimmerlands12,044
14Jammerbugt11,921
15Holstebro11,865
16Silkeborg11,442
17Skive11,095
18Haderslev11,087
19Randers10,671
20Syddjurs10,551
21Faaborg-Midtfyn10,341
22Brønderslev10,298
23Guldborgsund10,100
24Ikast-Brande10,099
25Mariagerfjord10,094
26Frederikshavn9,333
27Rebild9,318
28Lolland9,053
29Hedensted8,841
30Norddjurs8,832
31Næstved8,669
32Holbæk8,537
33Kolding8,427
34Vordingborg8,067
35Assens8,003
36Kalundborg7,933
37Favrskov7,930
38Sønderborg7,850
39Billund7,816
40Horsens7,800
41Bornholm7,454
42Slagelse7,332
43Lemvig6,856
44Nordfyns6,681
45Skanderborg6,511
46Svendborg6,012
47Morsø5,801
48Aarhus5,623
49Odsherred5,502
50Sorø4,470
51Middelfart4,452
52Faxe4,405
53Langeland4,315
54Gribskov3,915
55Lejre3,853
56Frederikssund3,811
57Nyborg3,805
58Ringsted3,797
59Struer3,784
60Odense3,579
61Odder3,088
62Kerteminde2,779
63Køge2,694
64Stevns2,687
65Samsø2,670
66Hillerød2,609
67Ærø2,469
68Roskilde2,250
69Egedal2,049
70Læsø1,647
71Fredensborg1,536
72Halsnæs1,340
73Fredericia1,281
74Helsingør1,201
75Høje-Taastrup618
76Fanø602
77Allerød596
78Greve484
79Solrød441
80Furesø436
81Rudersdal378
82Tårnby259
83Hørsholm235
84Dragør219
85Ballerup207
86Ishøj205
87Lyngby-Taarbæk124
88Albertslund121
89Vallensbæk33
90København20

Method and caveats

How the figures are calculated

Declared area is allocated by proportional overlap and largest remainder. A field is counted once in the municipality containing its largest overlap.

Effective crop diversity is exp(Shannon), calculated from classified area in the broad editorial crop groups.

All years use the pinned 2026 DAGI municipality boundaries. The national figure is calculated from unique fields and is not the sum of municipalities.

The crop groups are openlanddata presentation groups, not an official SGAV classification.

The figures describe aggregate declared areas for each year and cannot be used to track crop rotation on individual fields.

Sources and terms

Use the data yourself

CC0 1.0 · You may copy, adapt and share the data, including commercially. Credit is good practice, but is not required by CC0.

Suggested credit: SGAV, Marker

CC0 is documented in the official catalogue for the WFS layer. Its application to the matching ZIP file has not been separately confirmed.

Terms reviewed: 2026-09-07. Processing and calculations: openlanddata.

Use the data yourself

CC BY 4.0 · You may copy, adapt and share the data, including commercially. Credit the source, link the licence and describe your changes.

Attribution: Klimadatastyrelsen · DAGI · CC BY 4.0

Municipal snapshot retrieved on 15 July 2026. Boundaries and municipality assignment are used in our calculations.

Terms reviewed: 2026-09-07. Processing and calculations: openlanddata.

crop-pulse-collection:marker:3ea695a370bbe768c077dcbfdb3f248ef34aee0154bdca56812df0c2f156ac99

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