Pan-Arctic, Regional and Local Land Cover Products

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1 Pan-Arctic, Regional and Local Land Cover Products Marcel Urban (1), Stefan Pöcking (1), Sören Hese (1) & Christiane Schmullius (1) (1) Friedrich-Schiller University Jena, Department of Earth Observation, Grietgasse 6, Jena, Germany ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 1

2 Outline 1 Pan Arctic and Regional Land Cover 1 Objectives 2 Input Data 3 Synergistic Land Cover Map 4 Validation 5 Outlook 2 Local Land Cover 1 Local Land Classification 2 Cluster Analysis 3 Validation 4 Outlook ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 2

3 Pan Arctic and Regional Land Cover Objectives user feedback has shown the requirements for observation variables for land cover on pan boreal scale: area cover percentage of vegetation physiognomy/barren improvement of existing land cover information pan-arctic land cover dataset as model input with different spatial resolutions global and regional land cover products were used in a harmonization approach to meet the user requirements a harmonization can be understood as a process whereby the similarities between existing datasets are emphasized and inconsistencies are reduced ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 3

4 pan-arctic Land Cover Assessment Pan Arctic and Regional Land Cover Input Data version 1 of pan-arctic harmonized land cover dataset was generated by using existing global land cover products from different sources products have different legends, spatial and temporal resolutions challenging issue is to harmonize these products Tab. 1: Overview of global land cover product. data products spatial resolution temporal resolution time series GlobCover m once 2005/2006 MODIS Land Cover 500 m yearly SYNMAP 1 km once 1990 /2000 MODIS VCF 500 m yearly ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 4

5 Pan Arctic and Regional Land Cover Synergistic Land Cover Map MODIS LC GlobCover Synmap MODIS VCF Fig. 1: Methodology for a harmonization of global land cover products. ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 5

Pan Arctic and Regional Land Cover Synergistic Land Cover Map Color composite showing percentage area of trees, shrubs, herbaceous & barren Layer 1: Layer 2: Layer 3: Layer 4: %- tree cover %- shrub

6 Pan Arctic and Regional Land Cover Synergistic Land Cover Map Color composite showing percentage area of trees, shrubs, herbaceous & barren Layer 1: Layer 2: Layer 3: Layer 4: %- tree cover %- shrub cover (including low to tall-shrubs) %- herbaceous cover (including the erect-dwarf and prostrate-shrub tundra) %- barren and graminoid tundra (including surface water) Fig. 2: Pan-Arctic land cover product (Version 1). ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 6

Pan Arctic and Regional Land Cover Synergistic Land Cover Map dominant vegetation types calculated from synergy product class 1: class 2: class 3: class 4: trees shrubs (including low to tallshrubs)

7 Pan Arctic and Regional Land Cover Synergistic Land Cover Map dominant vegetation types calculated from synergy product class 1: class 2: class 3: class 4: trees shrubs (including low to tallshrubs) herbaceous (including the erect-dwarf and prostrateshrub tundra) barren and graminoid tundra (including surface water) Fig. 3: Dominant Vegetation extracted from pan-arctic synergy product. ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 7

8 Pan Arctic and Regional Land Cover Validation Validation Zone Description Status Zone 1 Zone 2 Zone 3 Taiga-Tundra Transition Zone Arctic coastline (Tundra) Boreal Region (Taiga) completed in progress in progress Fig. 4: Validation sites of the Taiga-Tundra transition zone of the pan-arctic land cover product (Yakutia, Russia; Canada; Alaska). ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 8

9 Pan Arctic and Regional Land Cover Validation Fig. 5: Landsat Classification for on Validation sites of the Taiga-Tundra transition zone (Yakutia, Russia). ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 9

10 Validation Fig. 6: zonal statistic analysis for validation approach based on 1km fishnet over pan-arctic land cover product. ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 10

11 Pan Arctic and Regional Land Cover Validation Error-matrices for the component [I] trees, [II] shrub, [III] herbaceous and [IV] barren (I) Trees Pan-Arctic Land Cover Product < 25 % % % > 75 % Producer s Accuracy (II) Shrub Pan-Arctic Land Cover Product < 25 % % % > 75 % Producer s Accuracy < 25 % < 25 % Landsat % % Landsat % % NA > 75 % NA > 75 % NA User s Accuracy NA Overall Accuracy [%] 44.7 User s Accuracy NA NA Overall Accuracy [%] 67.5 Landsat (III) Herbaceous Pan-Arctic Land Cover Product < 25 % % % > 75 % Producer s Accuracy < 25 % % % NA > 75 % NA User s Accuracy NA NA Overall Accuracy [%] 55 Landsat (IV) Barren Pan-Arctic Land Cover Product < 25 % % % > 75 % Producer s Accuracy < 25 % % % NA > 75 % NA User s Accuracy NA NA Overall Accuracy [%] 87.9 ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 11

GlobCover 2009 and Landsat-Data (Yakutia, Russia).

12 Pan Arctic and Regional Land Cover Validation Fig. 7: Comparison of pan-arctic land cover product, GlobCover 2009 and Landsat-Data (Yakutia, Russia). ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 12

13 Pan Arctic and Regional Land Cover Outlook Lesson learned from pan-arctic land cover validation integration of tree line to exclude tree cover misclassification in tundra areas to improve pan-arctic land cover product in higher latitudes integration of coarse resolution regional products (Russian Land Cover, North American Land Cover) Validation of Taiga and Tundra zones separately ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 13

14 Local Land Cover Classification Ice Snow Clouds Fig. 8: Data Coverage of local testsites. ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 14

Subsetting Mosaicing Cluster Analysis Image Segmentation Fig.

15 Local Land Cover Classification Pre-processing chain Raw Data Import Geometric correction Layer stacking Atmospheric Correction (ATCOR 2) Cloudmasking / Subsetting Mosaicing Cluster Analysis Image Segmentation Fig. 9: Methodology for local land cover classification. ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 15

16 Cluster Analysis (Lena Delta) Class decriptions taken from Schneider et al Class Wet, sedge- and moss dominated tundra Moist grass- and moss dominated tundra Moist to dry dwarf shrub-dominated tundra Dry moss-, sedge- and dwarf shrub dominated tundra Mainly non-vegetated Water Description nearly continuous cover of sedges and other hydrophilic graminoids growing in shallow water or mosses continuous vegetation cover of grasses, mosses and dwarf shrubs dominated by dwarf willows, on moist sites cotton grass occurs. Seasonal inundations of these areas result in a high content of nutrients in the soils and a dense vegetation cover sand as predominant substrate, found often close to cliffs, vegetation cover can vary barren or partially vegetated, mostly sandy include the open water of lakes, rivers, streams and coastal waters Fig. 10: Spectral plots of the land cover classes (Band 1: Blue, Band 2: Green, Band 3: Red, Band 4: Rededge, Band 5: NIR). ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 16

17 Local Land Cover Classification (Lena Delta) Fig. 13: Image subset NIR, red, green (upper left), composed image objects (upper right), clustered image subset with 12 classes (lower left) and clustered image subset with 20 classes (lower right). ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 17

18 Local Land Cover Classification (Lena Delta) Fig. 11: process tree for local land cover classification. ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 18

19 Local Land Cover Classification (Lena Delta) Fig. 12: class hierarchy with target classes at level 1 below. ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 19

20 Validation Tab. 2: Validation of the local land cover product. Reference Land Cover classification AWI (Schneider et al. 2009) Water RapidEye Land Cover Classification ( ) Mainly non-vegetated Dry moss-, sedge- and dwarf shrub dominated tundra Wet, sedge- and moss dominated tundra Moist to dry dwarf shrub-dominated tundra Moist grass- and moss dominated tundra sum users accuracy Water ,82 Mainly nonvegetated ,69 Dry moss-, sedgeand dwarf shrub ,74 dominated tundra Wet, sedge- and moss dominated ,84 tundra Moist to dry dwarf shrub-dominated ,66 tundra Moist grass- and moss dominated ,72 tundra sum producers accuracy 0,94 0,90 0,74 0,76 0,90 0,53 overall 0,78 ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 20

21 Outlook Classification of local test sites: Lena Delta: nearly completed (add shallow water class) North slope: cluster analysis & development of object based processing tree Yakutsk: reference data will be available in February/March, GIS data missing MacKenzie/Trout lake: no detailed class descriptions available All sites: expansion of classification area (mosaics) ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 21

22 Thanks for your attention! ESA DUE Permafrost 2 nd User Workshop March 2011 Fairbanks, Alaska 22

Chapter 7 Part III: Biomes

Chapter 7 Part III: Biomes Biomes Biome: the major types of terrestrial ecosystems determined primarily by climate 2 main factors: Temperature and precipitation Depends on latitude or altitude; proximity