George Büttner et al.:Institute of Geodesy, Cartography and Remote Sensing (FÖMI)

Remote Sensing CentreBudapest, HungaryButtner@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 databaseTechnical solutions

Results

GSDI 6 Conference "From Global to local"September 16-19, 2002

Budapest, Hungary

Why Land Cover is needed?

• Quantitative basis to develop a sustainable land use systems• A basic data layer in any environmental modelling:

hydrology, flood protectionsoil erosionagricultureregional development, integrated environmental assessmenttelecommunication…..

• There is a need for standardised data sets in order to model trans-boundary phenomena and foster international cooperation

Why to use Remote Sensing?

Topographic map (1975) Tuzla (B-H) IRS-1C & SPOT Pan (1998)

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 km2

CLC in Europe: • Support from various European programmes• 26 countries (1985-1998)• an update has started (CLC2000)

Purpose: To provide quantitative, consistentand comparable information on land cover

CORINE = Co-ordination of Information on the EnvironmentCORINE = Co-ordination of Information on the Environment

Land cover: biophysical coverage of the Earth’s surface (changes > 1 year)

CORINE Land Cover - methodology

Input:Landsat TM satellite imagephotomaps (scale 1 : 100 000)

Method:

Output:

Visual interpretation with computer assistance,use of ancillary information (maps, air-photos),field checking

Digital database including 44 categoriesin five groups: - artificial surfaces - agriculture - forest and semi-natural vegetation - wetlands - water bodies

The “BIBLE”: CORINE Land Cover Technical Guide (1994)

Major applications of CORINE Land Cover

• Crop mapping and yield forecast (FÖMI)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-????)

SPOT EUROPEAN SALES NETWORK SEMINAR, BUDAPEST, JUNE 3-4, 1999

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 tomask non-arable land areas out of the classification

CORINE Land Cover - HungaryApplication in regional crop monitoring

Pest

Békés

Fejér

Zala

Vas

SomogyBács-KiskunTolna

Heves

Baranya

Hajdú-Bihar

Veszprém

Csongrád

Nográd

Borsod-Abaúj-Zemplén

Jász-Nagykun-Szolnok

Szabolcs-Szatmár-Bereg

Győr-Moson-Sopron

Komárom-Esztergom

Budapest

P artia l d ata o f th e farm sA d d ition a l grou n d su rvey

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

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)

1 : 100 000 1 : 50 000

Eger

NE Hungary

•Better geometrical resolution•Better thematic resolution•More precise delineation•Actual (1998/99)

Comparison of CLC100 and CLC50

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)

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

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)

PHOTOINTERPRETATION - an example

PHOTOINTERPRETATION - example of a multitemporal imagery

98.08.18

99.08.01 92.08.2999.04.27

97.07.10

Separation of annual crops and plantations

Multitemporal imagery - an example

SPOT-4: 1998 Landsat TM: 1990

Temporal dynamics supports identification

INTERNAL QUALITY CONTROL

• Remarks on polygon level in file (errors, uniform understanding of nomenclature)• Printed protocol

Status of CLC50 (December 2002)

•

RESULTS

Budapest

RESULTS

Balaton

Thanks for your attention !

Aggtelek National Park