Mapping Land Cover Changes Using Landsat TM: A Case Study of Yamal Ecosystems, Arctic Russia

This poster shows application of the GIS/RS techniques for satellite image processing aimed at land cover chang detection. The changes in land cover types in tundra landscapes (Yamal) are detected since 1988. The research method is supervised classification (Minimal Distance) of the Landsat TM scenes. The new approach of the current work is application of ILWIS GIS and RS tools for Bovanenkovo region. The research area is geographically located on the Bovanenkovo region, the north-western part of Yamal Peninsula, West Siberia, Russia (Fig.1). The Yamal Peninsula is a flat homogeneous lowland region with low-lying plains of heights <90m. Such geographic settings create specific local environmental conditions in the region. Thus, Yamal is the worlds largest high-latitude wetland system covering in total 900,000 km2 of peatlands, complex system of wetlands.

Methods. The research methods consist of image classification, spatial analysis and thematic mapping, technically performed in ILIWIS GIS. Research steps:

1. Data pre-processing: a) import .img into ASCII raster format (GDAL). After converting, each image contained collection of 7 Landsat raster bands b) visual color and contrast enhancement c) geographic referencing of Landsat scenes: UTM (Universal Transverse Mercator), Eastern Zone 42, Northern Zone W, WGS 1984 datum (Georeference Corner Editor, ILWIS).
2. Research area selection. The area of interest (AOI) was identified and cropped on the raw images (Fig.3). This area shows Bovanenkovo region in a large scale. The AOI area best represents typical tundra landscapes.
3. Image classification 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. They have contrasting colors, visually visible and distinguishable on the image. The defined classes include shrub tundra, willows, tall willows, short shrub tundra, sparse short shrub tundra, dry grass heath, sedge grass tundra, dry short shrub tundra, dry short shrub sedge tundra, wet peatland, peatland (sphagnum). The pixels were associated with land cover classes, using their DNs, similar to the key samples.
4. Thematic mapping: layout of main research results, represented as maps of the land cover classes. The created domain Land classes includes legend with representation colors visualizing each category.

The research data are orthorectified Landsat TM scenes covering north-west of Yamal. The images have a time span of 23 years: 1988-08-07 and 2011-07-14, taken in growing season when vegetation coverage is clearly visible.

The research output includes following results:

1. two thematic maps of land cover types in Bovanenkovo area, Yamal
2. calculation of the areas in ha of land cover types

Conclusion.

The GIS-based mapping of the northern ecosystems is important tool for the landscape monitoring and management. Processing of remote sensing data (e.g. Landsat TM scenes) by means of GIS (e.g. ILWIS) improves technical aspects of the landscape studies, since it enables assessment of spatio-temporal changes in vegetation coverage. Spatial analysis of land cover types in northern landscapes can help to detect local environmental changes in Arctic regions.
Current research details changes in the land cover types in Bovanenkovo region, Yamal Peninsula, during the past 2 decades. These results are received as a result of the spatial analysis of classified images. The GIS mapping is based on the results of the image classification. The research results presented in the current work illustrate spatial distribution of land cover types in the selected area. Analysis of the results shows noticeable overall increase of woody vegetation (willows and shrubs) and 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 plant species patterns and distribution affect landscape structure in Yamal ecosystems. The triggering factors for these processes could be complex environmental changes in Arctic, as well as local cryogenic processes (e.g. successive change in vegetation recovering after cryogenic landslides).