1. George Büttner et al.: Institute of Geodesy, Cartography and Remote Sensing (FÖMI) Remote Sensing Centre Budapest, Hungary Buttner@rsc.fomi.hu Construction of a large scale (1:50k) land cover database in Hungary Contents: The EU CORINE Land Cover in Hungary Applications, the need for a better national database Technical solutions Results GSDI 6 Conference "From Global to local" September 16-19, 2002 Budapest, Hungary

2. Why Land Cover is needed? Quantitative basis to develop a sustainable land use systems A basic data layer in any environmental modelling: hydrology, flood protection soil erosion agriculture regional development, integrated environmental assessment telecommunication ….. There is a need for standardised data sets in order to model trans- boundary phenomena and foster international cooperation

3. Why to use Remote Sensing? Topographic map (1975)Tuzla (B-H) IRS-1C & SPOT Pan (1998)

4. CORINE Land Cover project initiated by the European Commission working scale - 1 : 100 000 minimum mapping unit: 25 ha 28 countries are involved, 4.43 million km 2 CLC in Europe: Support from various European programmes 26 countries (1985-1998) an update has started (CLC2000) Purpose: To provide quantitative, consistent and comparable information on land cover CORINE = Co-ordination of Information on the Environment Land cover: biophysical coverage of the Earth’s surface (changes > 1 year)

5. CORINE Land Cover - methodology Input: Landsat TM satellite image photomaps (scale 1 : 100 000) Method: Output: Visual interpretation with computer assistance, use of ancillary information (maps, air-photos), field checking Digital database including 44 categories in five groups: - artificial surfaces - agriculture - forest and semi-natural vegetation - wetlands - water bodies The “BIBLE”: CORINE Land Cover Technical Guide (1994)

6. Major applications of CORINE Land Cover Crop mapping and yield forecast (FÖMI) Regional planning (VÁTI) Regional planning (VÁTI) Development of EU-conform land-use strategy (U. Gödöllő) Development of EU-conform land-use strategy (U. Gödöllő) Catchment based environment modelling (FÖMI-Vituki Consult) Catchment based environment modelling (FÖMI-Vituki Consult) Flood protection planning (VITUKI Consult) Flood protection planning (VITUKI Consult) Nature protection (MoE) Nature protection (MoE) Telecommunication network panning (Mannessmann, Ericsson) Telecommunication network panning (Mannessmann, Ericsson) Support: CLC100:1993-1997 CLC50: MoARD and ???? (1999-????)

7. Aims: identification of crops based on high resolution, multitemporal satellite imagery providing thematic crop maps crop area measurement Contractor: Ministry of Agriculture and Regional Development (an operational activity) Implemented by: FÖMI Method: supervised classification of satellite images The CORINE Land Cover database is used to mask non-arable land areas out of the classification CORINE Land Cover - Hungary Application in regional crop monitoring

8. NEEDS FOR DETAILED LAND COVER Planning sustainable land use (e.g. converting arable land to grassland and forest land) Integrated landuse management for landscape, soil and hydrological conservation areas Network of Environmentally Sensitive Areas (agri-environment protection) Rural development Habitats Directive (nature protection) To support Hungary’s accession to the EU: Legal background: 2339/1996.(XII.6) Government Resolution

9. CLC50 preparations Acquisition of SPOT-4 imagery for the entire country, summer 1998-99 High precision orthorectification: RMSE<10 méter Nomenclature development (national needs, EU compatibility) Development of a computer assisted photointerpretation tool (ArcView/ InterView)

10. 1 : 100 0001 : 50 000 Eger NE Hungary Better geometrical resolution Better thematic resolution More precise delineation Actual (1998/99) Comparison of CLC100 and CLC50

11. CLC50 processing chain Data preparations (FÖMI) Photointerpretation (team) Internal quality control (FÖMI) Field work (team) External quality control (nature protection, agricultural inspectorate) Data integration (FÖMI)

12. CLC50 - NOMENCLATURE 2. Agriculture (21 items): Arable land (small / large fields), irrigated arable land, greenhouses, rice fields, vineyards, orchards, berries, hop plantations, intensive pastures with / without trees and shrubs, agricultural mosaics, farmsteads, agriculture with natural formations (5 types) 1. Artificial surfaces (26 items): Residential, industrial, commercial, traffic, mines, dumps, construction, parks, cemeteries, sport, leisure, recreation 3. Forests and semi-natural vegetation (22 items) Broadleaved / coniferous / mixed forests with continuous / discontinous canopy; on dry / wet area; forest plantations; natural grassland with / without trees and shrubs; young stands and clearcuts; bushy woodlands; nurseries, damaged forests, bare rocks, sparse vegetation on sand/ rocks/ salines; burnt areas 4. Wetlands (4) Fresh water marshes, saline-alkaline marshes; explored / unexplored peat bogs 5. Water bodies (6) Rivers, channels, permanent lakes, salt affected lakes; reservoirs, fish ponds

13. COMPUTER ASSISTED PHOTOINTERPRETATION Aims: optimal combination of capabilities of human expert and computer easy zoom of imagery application of multitemporal imagery precise delineation of polygons easy corrections automatic checking of polygon codes automatic checking of polygon geometry (area, average width) possibility to use comments and remarks on polygon level (a tool for „discussion”) on-line nomenclature controlled conversion into polygon topology data exchange via e-mail Realisation: ArcView 3.1/3.2 macro package (InterView)

14. PHOTOINTERPRETATION - an example

15. PHOTOINTERPRETATION - example of a multitemporal imagery 98.08.18 99.08.0192.08.2999.04.27 97.07.10 Separation of annual crops and plantations

16. Multitemporal imagery - an example SPOT-4: 1998Landsat TM: 1990 Temporal dynamics supports identification

17. INTERNAL QUALITY CONTROL Remarks on polygon level in file (errors, uniform understanding of nomenclature) Printed protocol

18. Status of CLC50 (December 2002)

19. RESULTS Budapest

20. RESULTS Balaton

21. Thanks for your attention ! Aggtelek National Park