Kaisu Harju Finnish Environment Institute Eurostat March 13th 2018 Provision of Harmonised Land Use Information – LUCAS and National Systems EUROSTAT Grants 2015 Kaisu Harju Finnish Environment Institute Eurostat March 13th 2018

Grants 2015 Project: Provision of Harmonised Land Use Information – LUCAS and National Systems Goal: To study how to get LUCAS compatible statistical data using national data sources Focus on land use, continuation of the work started in Eurostat Grants 2014 (land cover) Project duration: 1.1.2016 – 30.6.2017 Consortium Finnish Environment Institute SYKE (coordination) and Natural Resources Institute Finland LUKE Kaisu harju, SYKE 6.7.2019

Tasks WP1: Inventory of existing national data sources on land use Comparability of national datasets and Lucas LU classification Specific LUCAS LU classification for grant 2015 –projects was used WP2: Methodology development and calculation of results A method for data integration and statistical data production was developed and tested using a pilot areas Statistical tables for year 2012 were produced for 3 selected NUTS3 areas WP3: Quality assessment and feasibility study The results were evaluated using Lucas 2012 field observations and selected NFI 2016 survey results The feasibility of future updates using proposed and tested approach was evaluated including access and use conditions of the national datasets

Inventory of national data sources and their comparability to LUCAS land use classification Good availability of the national registers, spatial datasets and in-situ surveys Most datasets have full national coverage and they also cover all LUCAS LU classes in main level Some data gaps: detailed levels of secondary and tertiary production classes and abandoned areas Buildings and other topographic map layers Road and Rail network Forests, Fields Protected areas, national parks and willdernes reserves Land cover data Lakes and rivers 4 Etc.

LUCAS Land Use Classification for Grants 2015 Primary production U110 Agriculture U120 Forestry U130 MiningAndQuarrying U140 AquacultureAndFishing U150 OtherPrimaryProduction U200 SecondaryProduction U210 RawIndustry U220 HeavyEndProductIndustry U230 LightEndProductIndustry U240 EnergyProduction U250 OtherIndustry U300 TertiaryProduction U310 CommercialServices U320 FinancialProfessionalAndInformationServices U330 CommunityServices U340 CulturalEntertainmentAndRecreationalServices U400 TransportNetworksLogisticsAndUtilities U410 TransportNetworks U420 LogisticalAndStorageServices U430 Utilities U500 ResidentialUse (includes other compatible use) U600 OtherUses U610 Transitional use U620 Abandoned areas U630 Natural areas not in other economic use U6xx Other U111 CommercialAgriculturalProduction U112 FarmingInfrastructure U113 AgriculturalProductionForOwnConsumption U241 Nuclear based energy production U242 Fossil fuel based energy production U243 Biomass based energy production U244 Renewable energy production U411 RoadTransport U412 RailwayTransport U413 AirTransport U414 WaterTransport U415 OtherTransportNetwork U431 ElectricityGasAndThermalPowerDistributionServices U432 WaterAndSewageInfrastructure U621 Abandoned industrial** U622 Abandoned commercial** U623 Abandoned residential** U624 Other abandoned  HILUCS definitions of LU classes were followed

Methodology development and calculation of results The methodology for producing LUCAS compatible land use data was based on combining different spatial data layers into one spatial land use data layer High resolution (5 m * 5m) spatial data about land use  each pixel representing only one land use class LUCAS LU statistic calculated based on this data

Results of the Pilot Areas Results were calculated for three NUTS3-areas representing various conditions in Finland FI1C1 Southest Finland: urban center, agricultural areas FI197 Pirkanmaa: forests, agricultural areas, large lakes and also urban center FI1D7 Lappi: sparsely populated, protected areas and wilderness reserves, large national parks, specific feature: reindeer husbandry

Spatial Data and Analysis in Producing Statistics Processing of high resolution spatial data is time consuming Spatial data enables easy calculation of areas for each land use class at different levels (regional/national/etc…) Spatial data enables further spatial analysis and joint use with other data sources Spatial data/map gives a visual interpretation the LU classification  how well it describes the real world Example: Both protected areas and inland water areas classified as ”natural areas not in other economic use”  Class for inland waters would be needed

Some Considerations about the classification Different land use functions are mixed, especially all tertiary sector classes It is challenging to define detailed tertiary sector land use information as areas. Different tertiary sector functions are mixed and they also overlap with both industrial and residential areas. In Finland the proportion of built-up area is small: especially challenging to produce reliable statistics about secondary and tertiary sectors at very detailed level Use of forest areas in Finland is versatile and defining one land use value is difficult: Forestry, recreation, berry picking, hunting etc. are overlapping uses of forests. Finland has very large inland water areas and the main use of water areas is difficult to define as they are used for fishing, recreation, water transport etc. at the same time. It would be useful to have a specific class for water areas in LU classification. The versatile use of forests and water areas is based on “everyman rights”, which refer to the right of everyone in Finland to enjoy outdoor pursuits regardless of who owns or occupies an area.

Conclusions and Some Feedback LUCAS land use classification had some problems from national point of view LUCAS and Copernicus programmes could support each other more E.g. LUCAS in situ data could not be used in validating Copernicus products, because data content was not sufficien for that purpose LUCAS grants was a good opportunity to study the usage of spatial data in producing statistics Open data policy enables the flexible usage of national datasets Using spatial data for producing statistics is a very interesting option.

Thank you! The name of the presenter, SYKE 6.7.2019