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SATELLITE MONITORING of ESTONIAN LANDSCAPES Kiira Aaviksoo and Andrus Meiner Estonian Environment Information Centre Mustamäe tee 33, Tallinn 10616 ESTONIA,

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Presentation on theme: "SATELLITE MONITORING of ESTONIAN LANDSCAPES Kiira Aaviksoo and Andrus Meiner Estonian Environment Information Centre Mustamäe tee 33, Tallinn 10616 ESTONIA,"— Presentation transcript:

1 SATELLITE MONITORING of ESTONIAN LANDSCAPES Kiira Aaviksoo and Andrus Meiner Estonian Environment Information Centre Mustamäe tee 33, Tallinn ESTONIA,

2 BACKGROUND §1994: Estonian Environmental Monitoring Program l Landscape monitoring was not present in the program. The proposal for development of methodology for landscape monitoring was submitted §1996: Subprogram: Monitoring of Landscapes l Landscape monitoring was organized by three monitoring projects, incl. Remote Sensing of Landscapes §2000: Subprogram: Monitoring of Nature biodiversity l Project: Satellite Monitoring of Landscapes

3 INITIAL TASKS §to elaborate hierarchical land cover classification scheme, which supports on local level pecularities of Estonian landscapes and corresponds on regional level with internationally applied analogues §to produce satellite maps of recent (90/2000s) and historical (80s) environmental conditions §to determine the change of land cover and landscape diversity §to bring forth ongoing trends on class level and give the prognosis

4 PRESENT STATE OF SATELLITE MONITORING §6 monitoring sites l Soomaa, Saarejärve, Alam-Pedja, Lahemaa, Vilsandi, Karula §Sites consist of the core area and the buffer zone l the core area is one of the permanent national monitoring sites with mostly natural and semi-natural land cover types, usually a protected area l the buffer is the 3 km wide zone around the core area, containing different land cover types §Resources l 2 fulltime employees l Landsat TM imagery, aerial photos, topographic maps, training areas l Pentium workstations 128Mb RAM, Windows 98 l PCI EASI/PACE, ARC/INFO, Idrisi, ArcView, Fragstats

5 LOCATION OF MONITORING SITES Lahemaa NP Vilsandi NP Soomaa NP Alam-Pedja NR Karula NP Saarejärve integrated monitoring area

6 RESULTS I §After 5 years of monitoring work, 4481 km2 (10%) of Estonia has been monitored §Classification system developed so far has: l I level - 8 landscape types l II level- 21 land cover classes l III level - 58 land cover types, with additional IV level subtypes §Mapping accuracy was enhanced by integrating GIS in spectral-based image processing (masking) §Estimation of landscape diversity l used parameters show increase in landscape fragmentation, especially in the buffer zones l the main reason is increase of patch number and decrease of their area

7 RESULTS II §Main trends in monitoring areas (and in Estonian nature as a whole) can be brought forth: l afforestation l the increasing of coniferous stands in forests (hypothesis) l the decreasing of clear-cut areas in core areas and increasing in buffer zones l the increasing of grassland at the expense of arable land l the increasing of fallow land at the expense of abandoned fields and cultivated grasslands l the overgrowing of natural grasslands and fallow land with shrubs and young trees l the decreasing of arable lands

8 CHARACTERIZATION OF METHODOLOGY illustrated by Vilsandi monitoring area: §Total area is 467 km 2, core area 51% and buffer 49% §Average count of land cover patches was: l 8531 (> 1 ha: 2082) in 1980s, and l (> 1 ha: 2272) in 1990s §Mean patch size (without water in 1986 and 1998): l core area / 5.3 ha l buffer zone / 9.96 ha §In total were mapped 36 land cover (sub)types §Accuracy of change map: overall = 84%, KIA = 73% §Field work on 84 sites (LC description, GPS, photo) §Problematic land cover types: l alvar grasslands, fallow lands, wooded meadows, shrublands

9 METHODOLOGY I Processing the satellite imagery §Elaboration of classification scheme l III and IV level - mapping (map) l II level - for monitoring land cover and diversity (map) §Classification masks l forest and natural grasslands l mires (fens, swamps, bogs) l agricultural areas (crops, cultivated grasslands) l water surfaces §Image processing l pre-processing (geometric correction) l histogram normalisation of two dates l pre-classification (hybrid classification with ancillary data) l ground truth (filed visit of training areas, GPS, photography) l final classification under masks and accuracy assessment

10 LAND COVER TYPES (III, IV level) in Vilsandi (1986 and 1998)

11 LAND COVER CLASSES (II level) in Vilsandi (1986 and 1998)

12 METHODOLOGY II Estimation of landscape diversity §Landscape diversity parameters: l Measured parameters general: count, average, maximum and total size, perimeters l Computed parameters representing shape: edge index, shape index representing neighbourhood: mean distance between patches of the same class diversity metrics: Shannon diversity index (only landscape level) l Minimum size of patch for diversity analysis - 1 ha

13 FRAGMENTATION (arable land)

14 METHODOLOGY III Change detection §Change (or stability) of each class within the monitoring area - comparison of classification results for 2 dates l change database computed: 2 attributes per pixel (T 1 and T 2 ) l tally matrix: class changes (off-diagonal elements) and no-changes (diagonal) pixels l percent changes per class §Change in landscape diversity - comparison of diversity metrics for 2 dates l core area l buffer zone l change statistics §Change prognosis

15 MAIN TRENDS IN LAND COVER CLASSES Vilsandi monitoring area , %

16 AREAS OF LAND COVER CLASSES IN VILSANDI 1986, 1998, 2010* §Land cover class l 2 - coastal reedbed l 3 - barren coast l 4 - till coast with sparse vegetation l 5 - natural grassland l 6 - open mire l 7 - treed mire, mire forest l 8 - alvar grassland l 9 - coniferous (juniper) shrubland l 10 - coniferous forest l 11 - deciduous forest l 12 - mixed forest l 13 - arable land l 14 - cultivated grassland l 15 - fallow land l 16 - settlement, artificial areas ]V 2010 = M 8698 * V 98

17 ADVANTAGES AND DISADVANTAGES of SATELLITE REMOTE SENSING §Satellite remote sensing is a good tool for regular searching and updating of landscape state information §Digital satellite remote sensing data have direct input to GIS l congruous with raster and vector coverages §Landsat TM and ETM satellite data have the best quality/cost ratio for environmental monitoring l good spectral, temporal, spatial and radiometric resolution l 0.30 EEK/km 2 ) §Satellite maps in context of GIS help to resolve the problems of everyday tasks in management qualitative maps (land cover) quantitative (statistical) data §Landsat satellite data is greatly dependent from: l clouds l water content in soil and vegetation §Satellite mapping does not replace geobotanic mapping §Spectral and spatial resolution is too rough for detail habitat mapping

18 WHY MASKS? §Spectral signatures of land cover types are too similar §Number of classes and accuracy of map is too small §Spectral similarity was avoided by using GIS coverages as binary masks

19 NORMALIZATION OF TWO SATELLITE IMAGES OF THE SAME FENOLOGICAL STATE §Landsat TM l l §Normalisation of histograms around mean using value of standard deviation §normalisation by channel pairs l TM and TM a.s.o


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