# ILWIS GIS for monitoring landscapes in tundra ecosystems: Yamal peninsula, Russia

Polina Lemenkova

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To cite this version:

Polina Lemenkova. ILWIS GIS for monitoring landscapes in tundra ecosystems: Yamal peninsula, Russia. Master. Serbia. 2012. cel-01973028

HAL Id: cel-01973028

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Submitted on 8 Jan 2019

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Distributed under a Creative Commons CC0 - Public Domain Dedication 4.0 International License
ILWIS GIS FOR MONITORING
LANDSCAPES IN TUNDRA ECOSYSTEMS:
YAMAL PENINSULA, RUSSIA

POLINA LEMENKOVA

DRESDEN UNIVERSITY OF TECHNOLOGY (TU DRESDEN)

✉: Polina.Lemenkova@mailbox.tu-dresden.de

THIS PRESENTATION IS MADE USING LATEX

MAY 30, 2012

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# Outline

## Introduction

Research aim

Research objective

## Study area

Geographic location

Environmental settings

## Methods

Remote Sensing

Data capture

Data processing

ILWIS GIS

Supervised classification

Thematic mapping

## Results

Thematic maps

Assessment of areas

## Discussion

Résumé

Conclusion

Thanks

References
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# Brief Summary

## Brief Summary

### Research aim:

* distribution of various land cover types in Yamal Peninsula

* monitoring changes in tundra landscapes

* analysis of the landscape dynamics during the past two decades (1988-2011).

### Data:

Landsat TM scenes for 1988 and 2011 years.

### Originality:

Application of ILWIS GIS spatial analysis tools and Landsat imagery for Bovanenkovo region in Yamal.

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# Brief Summary

## Brief Summary

### Research aim:

* distribution of various land cover types in Yamal Peninsula

* monitoring changes in tundra landscapes

* analysis of the landscape dynamics during the past two decades (1988-2011).

### Data:

Landsat TM scenes for 1988 and 2011 years.

### Originality:

Application of ILWIS GIS spatial analysis tools and Landsat imagery for Bovanenkovo region in Yamal.

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# Brief Summary

## Brief Summary

### Research aim:

* distribution of various land cover types in Yamal Peninsula

* monitoring changes in tundra landscapes

* analysis of the landscape dynamics during the past two decades (1988-2011).

### Data:

Landsat TM scenes for 1988 and 2011 years.

### Originality:

Application of ILWIS GIS spatial analysis tools and Landsat imagery for Bovanenkovo region in Yamal.

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# Brief Summary

## Methodology

### Technical tools:

The RS data processing was performed in ILWIS GIS software: Fig.1

### Research method:

Image interpretation applied to Landsat TM scenes, and supervised classification

<figure><img src="image_23.png" /><figcaption>Figure: 1. ILWIS GIS.</figcaption></figure>

Source: www.ilwis.org/

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# Brief Summary

## Methodology

Technical tools:

The RS data processing was performed in ILWIS GIS software: Fig.1

## Research method:

Image interpretation applied to Landsat TM scenes, and supervised classification

<figure><img src="image_29.png" /><figcaption>Figure: 1. ILWIS GIS.</figcaption></figure>

Source: www.ilwis.org/

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# Research Area

## Geographic location: Yamal Peninsula, north Russia

<figure><img src="image_31.png" /><figcaption>(a) Geographic location of Yamal Peninsula Map source: google.com</figcaption></figure>

<figure><img src="image_32.png" /><figcaption>(b) Location of the study area on Yamal (western coast). Source: Bruce Forbes</figcaption></figure>
# Environment of Yamal, part 1

## Yamal Peninsula: geomorphology

Specific climatic-environmental settings of Yamal Peninsula: flat geomorphology, elevations < 90 m. Processes:

* seasonal flooding,

* active erosion processing,

* permafrost distribution and

* intensive local landslides formation.

<figure><img src="image_33.png" /><figcaption>Figure: 4. Landscapes of Yamal. Source: http://pixtale.net/</figcaption></figure>
# Environment of Yamal, part 2

## Yamal Peninsula: environmental settings

One of the typical process in Yamal tundra: cryogenic landslides. Landslides affect local ecosystem structure, because they change vegetation types recovering after the disaster.

<figure><img src="image_34.png" /><figcaption>Figure: 5. Landscapes of Yamal.</figcaption></figure>
# Landscapes of Yamal Peninsula

## Land cover classes: 1-4 from 11

<figure><img src="image_35.png" /><figcaption>(a) Type 1. Shrub tundra.
Source: www.novaonline.nvcc.edu/</figcaption></figure>

<figure><img src="image_36.png" /><figcaption>(b) 2. Dwarf willows.
from: www.travel languist.com</figcaption></figure>

<figure><img src="image_37.png" /><figcaption>(c) Type 3. Arctic willows.
Source: http://nature-plants.com</figcaption></figure>

<figure><img src="image_38.png" /><figcaption>(d) 4. Sparse short shrub tundra.
(www.polarfield.com)</figcaption></figure>
# Landscapes of Yamal Peninsula (continue)

## Land cover classes (5-8 from 11)

<figure><img src="image_39.png" /><figcaption>(e) Type 5. Dry grass heath tundra. (from polarfield.com)</figcaption></figure>

<figure><img src="image_40.png" /><figcaption>(f) 6. Sedge grass tundra.
Source: arcticatlas.org</figcaption></figure>

<figure><img src="image_41.png" /><figcaption>(g) 7. Dry short shrub tundra. (www.arcticatlas.org)</figcaption></figure>

<figure><img src="image_42.png" /><figcaption>(h) Sphagnum moss.
Source: google.com</figcaption></figure>
# Landscapes of Yamal Peninsula (continue)

## Land cover classes (9 to 11 from 11)

<figure><img src="image_43.png" /><figcaption>(i) Type 9. Dry short shrub sedge tundra.</figcaption></figure>

Source: www.britannica.com

<figure><img src="image_44.png" /><figcaption>(j) Type 10. Wetlands.</figcaption></figure>

Source: google.com

<figure><img src="image_45.png" /><figcaption>(k) Type 11. Short shrub tundra.</figcaption></figure>

(Image source: www.arctic-predators.uit.no)

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TECHNISCHES
UNIVERSITAT
DRESDEN
# Human activities on Yamal: part 1

## Yamal Peninsula: reindeer herding

The most typical anthropogenic activity on Yamal Peninsula is reindeer herding (Fig.3). Yamal is a homeland for ca 5000 nomadic Nenets tribes migrating with herds up to 1200 km annually.

<figure><img src="image_47.png" /><figcaption>(l) Tundra landscape: reindeer herds. Source: environmentalresearchweb.org</figcaption></figure>

<figure><img src="image_48.png" /><figcaption>(m) Typical scene of reindeer grazing. Photo: Bryan Alexander</figcaption></figure>

Herding is natural process. However, it may have negative effects: pasture overgrazing and pressure on vegetation coverage.
# Human activities on Yamal: part 2

## Yamal Peninsula: gas exploration

Yamal Peninsula is a place where the gas field "Bovanenkovo" is being explored (Fig.3). Geological gas exploration cause serious anthropogenic pressure on the environment. Indirectly it also includes additional construction of roads, settlements, human facilities, etc.

<figure><img src="image_49.png" /><figcaption>(n) Yamal: scheme of gas exploration.
(www.reindeerblog.org)</figcaption></figure>

<figure><img src="image_50.png" /><figcaption>(o) View on the gas exploration station.
Photo: http://barentsobserver.com</figcaption></figure>

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TECHNISCHE
UNIVERSITAT
DRESDEN
# Research Methods: Step 1.

## Data pre-processing

a) import .img into ASCII raster format (GDAL).

After converting, each image contained collection of 7 raster bands

b) visual color and contrast enhancement

c) geographic referencing of Landsat scenes, initially based on WGS 1984 datum: UTM (Universal Transverse Mercator) Projection, Eastern Zone 42, Northern Zone W, (Georeference Corner Editor, ILWIS).

d) crop of study area The area of interest (AOI) was identified and cropped on the raw images. This area shows Bovanenkovo region in a large scale and best represents typical tundra landscapes.
# Research Methods: Step 1.

## Data pre-processing

a) import .img into ASCII raster format (GDAL).
After converting, each image contained collection of 7 raster bands

b) **visual color and contrast enhancement**

c) geographic referencing of Landsat scenes, initially based on WGS 1984 datum: UTM (Universal Transverse Mercator) Projection, Eastern Zone 42, Northern Zone W, (Georeference Corner Editor, ILWIS).

d) crop of study area The area of interest (AOI) was identified and cropped on the raw images. This area shows Bovanenkovo region in a large scale and best represents typical tundra landscapes.
# Research Methods: Step 1.

## Data pre-processing

a) import .img into ASCII raster format (GDAL).

After converting, each image contained collection of 7 raster bands

b) visual color and contrast enhancement

c) geographic referencing of Landsat scenes, initially based on WGS 1984 datum: UTM (Universal Transverse Mercator) Projection, Eastern Zone 42, Northern Zone W, (Georeference Corner Editor, ILWIS).

d) crop of study area The area of interest (AOI) was identified and cropped on the raw images. This area shows Bovanenkovo region in a large scale and best represents typical tundra landscapes.
# Research Methods: Step 1.

## Data pre-processing

a) import .img into ASCII raster format (GDAL).

After converting, each image contained collection of 7 raster bands

b) visual color and contrast enhancement

c) geographic referencing of Landsat scenes, initially based on WGS 1984 datum: UTM (Universal Transverse Mercator) Projection, Eastern Zone 42, Northern Zone W, (Georeference Corner Editor, ILWIS).

d) **crop of study area** The area of interest (AOI) was identified and cropped on the raw images. This area shows Bovanenkovo region in a large scale and best represents typical tundra landscapes.
# Research Methods: Step 2.

## Image classification

* The key research method is supervised classification (Minimal Distance), which is based on the spatial analysis of spectral signatures of object variables, i.e. vegetation types.

* The classes sampling was performed using Sample Set tool in ILWIS GIS.

* The training pixels for each land cover type were selected as representative samples and stored as classification key.

* Requirement for training pixels: they have contrasting colors, visually visible and distinguishable on the image.

<figure><img src="image_52.png" /></figure>

TECHNISCHE
UNIVERSITAT
DRESDEN
# Research Methods: Step 3.

## Thematic mapping

Layouts of main research results represent maps of the land cover classes.

The created domain Land classes includes legend with representation colors visualizing each category.

<figure><img src="image_53.png" /><figcaption>Figure: 21. Thematic mapping</figcaption></figure>
# GIS Mapping (1988)

Classified study area (from image 1988)

<figure><img src="image_54.png" /><figcaption>## Landsat TM scene</figcaption></figure>

Figure: 22. Landsat TM, 1988

<figure><img src="image_55.png" /></figure>

Figure: 23. Map of land cover classes, 1988

<figure><img src="image_56.png" /></figure>

TECHNISCHES
UNIVERSITAT
DRESDEN
# GIS Mapping (2011)

Classified study area (from image 2011)

<figure><img src="image_57.png" /><figcaption>## Landsat TM scene</figcaption></figure>

Figure: 24. Landsat TM, 2011

<figure><img src="image_58.png" /></figure>

Figure: 25. Land cover classes

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TECHNISCHES
UNIVERSITAT
DRESDEN
# Results

## Land cover classes: assessment of changes

<table><caption>Table: 1. Statistics on land cover classes, Bovanenkovo region, Yamal</caption><thead><tr><th>Land Cover Class</th><th>1988, # pixels</th><th>2011, # pixels</th><th>1988, ha</th><th>2011, ha</th></tr></thead><tbody><tr><td>Shrub tundra</td><td>220447</td><td>168226</td><td>1146.3244</td><td>874.7752</td></tr><tr><td>Short shrub tundra</td><td>165079</td><td>270158</td><td>858.4108</td><td>1404.8216</td></tr><tr><td>Willows</td><td>193645</td><td>457004</td><td>1006.954</td><td>2376.4208</td></tr><tr><td>Tall willows</td><td>103954</td><td>71952</td><td>540.5608</td><td>374.1504</td></tr><tr><td>Sparse short shrub tundra</td><td>176511</td><td>759380</td><td>917.8572</td><td>3948.776</td></tr><tr><td>Dry grass heath</td><td>641420</td><td>231719</td><td>3335.384</td><td>1204.9388</td></tr><tr><td>Sedge grass tundra</td><td>27545</td><td>57052</td><td>143.234</td><td>296.6704</td></tr><tr><td>Dry short shrub tundra</td><td>8984</td><td>16993</td><td>46.7168</td><td>88.3636</td></tr><tr><td>Wet peatland</td><td>761231</td><td>531809</td><td>3958.4012</td><td>2765.4068</td></tr><tr><td>Peatland (sphagnum)</td><td>120328</td><td>93979</td><td>625.7056</td><td>488.6908</td></tr><tr><td>Dry short shrub-sedge tundra</td><td>173693</td><td>92242</td><td>903.2036</td><td>479.6584</td></tr></tbody></table>

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# Discussion

## Environmental Analysis

Results show:

* overall increase of woody vegetation (willows and shrubs)

* decrease of peatlands, grass and heath areas.

This illustrates environmental process of greening in Arctic, i.e. the unnatural increase of woody plants. The gradual changes in patterns and distribution of plant species affect landscape structure in Yamal. Triggering factors:

* complex environmental changes in Arctic

* local cryogenic processes (e.g. successive change in vegetation recovering after cryogenic landslides)
# Résumé

## Summary

* Current research details changes in spatial distribution of land cover types in selected area of western Yamal Peninsula

* The time span covers past 2 decades (1988 - 2011)

* The research is technically performed by means of ILWIS GIS, based on spatial analysis of classified Landsat TM images.

* The results of spatial analysis are presented as thematic maps illustrating changes in land cover types on Yamal Peninsula. GIS mapping is based on the image classification.

* As a result of climate and environmental impacts, there are detected changes in the vegetation structure.

* Main outcome: overall increase in woody plants, e.g. "short shrub tundra", "sparse short shrub tundra" and "dry short shrub tundra"), and slight decrease in grasses, heath and peatland.

* There is process of greening detected in Yamal tundra. It indicates structural variations in ecosystems.

<figure><img src="image_61.png" /></figure>
# Conclusion

...to conclude:

* GIS-based mapping (e.g. ILWIS GIS) is important tool for the landscape monitoring and management.

* Processing of remote sensing data (e.g. Landsat TM scenes) by means of GIS improves technical aspects of the landscape studies.

* Application of RS data is especially important for studies of northern ecosystems, since it enables to perform spatial analysis of remotely located areas in Arctic regions.

* Spatial analysis of land cover types can help to detect local environmental changes.

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# Acknowledgement

## Thanks

The financial support of this research has been provided by the Fellowship of the Center for International Mobility (CIMO) of Finland. Contract No. TM-10-7124 (Decision 9.11.2010).

This research was done at the Arctic Center, University of Lapland.

I thank my scientific chief Prof. Dr. Bruce C. Forbes from the Arctic Center and colleague Dr. Timo Kumpula from the University of Eastern Finland for our collaboration.

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# Bibliography (selected)

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Forbes, B.C., Fauria, M.M., and Zetterberg, P. (2010).

Russian Arctic warming and greening are closely tracked on tundra shrub willows.

*Global Change Biology*, **16** (5), 1542-1554.

<figure><img src="image_65.png" /></figure>

Forbes, B.C. and McKendrick, J.D. (2002).

Polar tundra. Handbook of Ecological Restoration, 2. Restoration in Practice. Ed. Perrow, M., and Davy, A.J. Cambridge:

*Cambridge University Press*, 355-375.

<figure><img src="image_66.png" /></figure>

Kumpula, T., Pajunen, A., Kaarlejrvi, E., and Forbes, B.C., (2011).

Land use and land cover change in Arctic Russia: Ecological and social implications of industrial development.

*Global Environmental Change* **21**, 550-562.

<figure><img src="image_67.png" /></figure>

Leibman, M.O. and Kizyakov, A.I., (2007).

Cryogenic Landslides of the Yamal and Yugorsky Peninsula (Kriogenniey opolzni Yamala Yugorskovo poluostrova). Moscow: Earth Cryosphere Institute, Siberian Branch, Russian Academy of Science (in Russian)

<figure><img src="image_68.png" /></figure>

Rees, W.G., Williams, M., and Vitebsky, P. (2003).

Mapping land cover change in a reindeer herding area of the Russian Arctic using Landsat TM and ETM+ imagery and indigenous knowledge.

*Remote Sensing of Environment*, **85**, 441-452.
The End

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