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

Master Brief Summary • 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 an...

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Bibliographic Details
Main Author: Lemenkova, Polina
Other Authors: Ocean University of China (OUC)
Format: Review
Language:English
Published: HAL CCSD 2012
Subjects:
Image classification
Satellite imagery
Landsat TM
Image processing Image recognition
Clustering Analysis
Land cover change
Landscape analysis
SIG Systèmes d'information géographique
SIG et modélisation spatiale
SIG et aménagement
envir
geo
Arctic
Bovanenkovo
Yamal Peninsula
permafrost
Tundra
Online Access:https://doi.org/10.6084/m9.figshare.7435373.v1
https://hal.archives-ouvertes.fr/cel-01973028/file/Lemenkova_etal_Present_Yamal2012.pdf
https://hal.archives-ouvertes.fr/cel-01973028
Description
Summary:Master Brief Summary • 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. Methodology Technical tools: The RS data processing was performed in ILWIS GIS software. Research method: Image interpretation applied to Landsat TM scenes, and supervised classification. Geographic location: Yamal Peninsula, north Russia. 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.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.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.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.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. ...

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