1. Pilot studies on the provision of harmonized land use/land cover statistics: Synergies between LUCAS and the national systems
Norway
Erik Engelien
Division for Natural resources and Environmental Statistics,
Statistics Norway

2. Outline Data sources Methodology
LUCAS classes (and data/statistics) vs. national classes
Micro data access
Remaining work
Part B Integration of in-situ surveys with LUCAS

3. Data sources Statistics Norway’s land use/ land cover map
Land use within built up areas and land cover
Standard classification (based on existing standards and map legends)
Based on existing map data bases and registers
Automatic geoprocessing
Supplementary data sources
Register of applications to production subsidies
Map of protected areas
Other sources
National forest survey
National survey adaptation to LUCAS 2003 (Ar18x18)

4. Data sources AR-STAT- land cover
Norwegian Forest and Landscape Institute (NFLI)
Based on: AR5, AR50 and AR-mountain

5. Delimitation of built-up land
Transport
Woodland
Open firm ground
Chosen land plots N
Utilisation rate on property is too low. Buffer represents land use.

6. Data sources - Statistics Norway’s land use/ land cover map
Ground property map
Building- and address register
Land cover map (AR-STAT)
National map series (1: : )

7. Standard classification

8. Methodology – LUCAS adaptation
Land use/ land cover map as basis
Supplementary data, statistics and reprocessed data
Convert to LUCAS classes
Aggregate statistics with land use/ land cover map as total sum
Statistics of crops on county level (NUTS 3)
Residential: Combination of ground property, land cover, building.
Forestry: Forest in combination with protected areas

9. Update regime AR-STAT new national data set every 3. year
AR5 (below tree line) update continuously by municipalities and every 5-7 year by NFLI
AR50/ AR Mountain (above tree line) periodical update
Cadastre (ground property, buildings, addresses)
Continuously updated
National map series
Buildings, roads continuously
Other updated each 3-10 years (air photography, built-up areas markedly more often)
National statistics on land use/ cover updated yearly

10. Which LUCAS classes are difficult to cover, or covered with some adaptation? I
Land cover main classes:
Grassland/ bare land/ shrub land within built up areas
We will use proportional distribution by land use class
Woodland
Temporarily unstocked areas within forest should be excluded
We use statistics on tree age by NUTS 2/3 for allocation to F bare land
Land use classes (2-digit level):
U330 Under construction is not part of our classification
Exists map data, but probably not very good, but will be explored further
Building date
U340 Commerce, finance and business
Public administration is in part included
land use is based on building function and in some cases (especially land use 3-digit level) not 100 per cent compatibility between national classes and LUCAS

11. Which LUCAS classes are difficult to cover, or covered with some adaptation? II
Land cover 2-digit level:
D10 Shrubland with sparse treecover (included in D20)
E10 Grassland with sparse treecover (included in E20)
F20 Sand (included in F10)
B40 Dry pulses, vegetables and flowers
Includes rutabaga and carrots which should have been B20
Flowers is included in B80 because we can not separate in data
B80 Other permanent crops
Not able to separate forest tree nurseries and flowers, which are included
C10 Broadleaved woodland, C20 Coniferous woodland, C30 Mixed woodland
Same classes in national map database but somewhat different limits of criteria
H20 Coastal wetlands
Not on map or statistics

12. Which LUCAS classes are difficult to cover, or covered with some adaptation? III
Land cover 3-digit level:
More discrepancies arise for this detailed level and need for more supplementary data e.g.:
Number of floors
Further division of woodland
Land use 3-digit level:
Several of the classes would need reprocessing
Difficult to cover:
U220 Industry and manufacturing (may use business register to obtain NACE, but geocoding…)
U410 Abandoned areas

13. Micro data access Regulated by The Statistics Act
Statistics Norway has free access to all relevant registers and map databases for producing official statistics.
“Norway Digital”

14. Remaining work Implement methodology Produce results
Describe feasibility of subsequent data delivery
Our approach aims at building a system which can be run cost effectively in conjunction with the national statistical system
Make final report

15. Part B: Integration of in-situ surveys with LUCAS
By National Forest and Landscape Institute
Public agency under Ministry of Agriculture and Food

16. Norwegian in situ survey:
Based on LUCAS 2003
18 x 18 km grid = 1100 sample points

17. Norwegian in situ survey:
10 SSUs (as LUCAS 2003)
Differences:
Focus: Outfields
Wall-to-wall field survey
of the entire PSU (0,9 km2)
New LUCAS attributes not included
Implementation period: 10 years
Key message:
The Norwegian in situ survey is based on LUCAS 2003 methodology, but
the Norwegian focus on the country’s outfield resources in areas where access is
difficult (and costly) has resulted in a different development of the survey

18. How different can the adaptation be and what is most important?
Data content
Sampling
Timing