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: Lecture
Language:English
Published: HAL CCSD 2012
Subjects:
Online Access:https://hal.archives-ouvertes.fr/cel-01973028
https://hal.archives-ouvertes.fr/cel-01973028/document
https://hal.archives-ouvertes.fr/cel-01973028/file/Lemenkova_etal_Present_Yamal2012.pdf
https://doi.org/10.6084/m9.figshare.7435373.v1
id ftccsdartic:oai:HAL:cel-01973028v1
record_format openpolar
institution Open Polar
collection Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe)
op_collection_id ftccsdartic
language English
topic 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
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION
ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION
ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering/I.5.3.0: Algorithms
ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS
ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.1: Image processing software
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.0: Image displays
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation/I.4.6.1: Pixel classification
ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models
ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering
[SDE.ES]Environmental Sciences/Environmental and Society
[SDE.MCG]Environmental Sciences/Global Changes
[SDE.IE]Environmental Sciences/Environmental Engineering
[INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
[SHS.GEO]Humanities and Social Sciences/Geography
[SHS.ENVIR]Humanities and Social Sciences/Environmental studies
spellingShingle 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
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION
ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION
ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering/I.5.3.0: Algorithms
ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS
ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.1: Image processing software
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.0: Image displays
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation/I.4.6.1: Pixel classification
ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models
ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering
[SDE.ES]Environmental Sciences/Environmental and Society
[SDE.MCG]Environmental Sciences/Global Changes
[SDE.IE]Environmental Sciences/Environmental Engineering
[INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
[SHS.GEO]Humanities and Social Sciences/Geography
[SHS.ENVIR]Humanities and Social Sciences/Environmental studies
Lemenkova, Polina
ILWIS GIS for monitoring landscapes in tundra ecosystems : Yamal peninsula, Russia
topic_facet 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
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION
ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION
ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering/I.5.3.0: Algorithms
ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS
ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.1: Image processing software
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.0: Image displays
ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation/I.4.6.1: Pixel classification
ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models
ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering
[SDE.ES]Environmental Sciences/Environmental and Society
[SDE.MCG]Environmental Sciences/Global Changes
[SDE.IE]Environmental Sciences/Environmental Engineering
[INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
[SHS.GEO]Humanities and Social Sciences/Geography
[SHS.ENVIR]Humanities and Social Sciences/Environmental studies
description 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. ...
author2 Ocean University of China (OUC)
format Lecture
author Lemenkova, Polina
author_facet Lemenkova, Polina
author_sort Lemenkova, Polina
title ILWIS GIS for monitoring landscapes in tundra ecosystems : Yamal peninsula, Russia
title_short ILWIS GIS for monitoring landscapes in tundra ecosystems : Yamal peninsula, Russia
title_full ILWIS GIS for monitoring landscapes in tundra ecosystems : Yamal peninsula, Russia
title_fullStr ILWIS GIS for monitoring landscapes in tundra ecosystems : Yamal peninsula, Russia
title_full_unstemmed ILWIS GIS for monitoring landscapes in tundra ecosystems : Yamal peninsula, Russia
title_sort ilwis gis for monitoring landscapes in tundra ecosystems : yamal peninsula, russia
publisher HAL CCSD
publishDate 2012
url https://hal.archives-ouvertes.fr/cel-01973028
https://hal.archives-ouvertes.fr/cel-01973028/document
https://hal.archives-ouvertes.fr/cel-01973028/file/Lemenkova_etal_Present_Yamal2012.pdf
https://doi.org/10.6084/m9.figshare.7435373.v1
long_lat ENVELOPE(68.437,68.437,70.354,70.354)
ENVELOPE(69.873,69.873,70.816,70.816)
geographic Arctic
Bovanenkovo
Yamal Peninsula
geographic_facet Arctic
Bovanenkovo
Yamal Peninsula
genre Arctic
permafrost
Tundra
Yamal Peninsula
genre_facet Arctic
permafrost
Tundra
Yamal Peninsula
op_source https://hal.archives-ouvertes.fr/cel-01973028
Master. Serbia. 2012
op_relation info:eu-repo/semantics/altIdentifier/doi/10.6084/m9.figshare.7435373.v1
cel-01973028
https://hal.archives-ouvertes.fr/cel-01973028
https://hal.archives-ouvertes.fr/cel-01973028/document
https://hal.archives-ouvertes.fr/cel-01973028/file/Lemenkova_etal_Present_Yamal2012.pdf
doi:10.6084/m9.figshare.7435373.v1
op_rights http://creativecommons.org/publicdomain/zero/1.0/
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op_rightsnorm CC0
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op_doi https://doi.org/10.6084/m9.figshare.7435373.v1
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spelling ftccsdartic:oai:HAL:cel-01973028v1 2023-05-15T15:19:51+02:00 ILWIS GIS for monitoring landscapes in tundra ecosystems : Yamal peninsula, Russia Lemenkova, Polina Ocean University of China (OUC) 2012-05-29 https://hal.archives-ouvertes.fr/cel-01973028 https://hal.archives-ouvertes.fr/cel-01973028/document https://hal.archives-ouvertes.fr/cel-01973028/file/Lemenkova_etal_Present_Yamal2012.pdf https://doi.org/10.6084/m9.figshare.7435373.v1 en eng HAL CCSD info:eu-repo/semantics/altIdentifier/doi/10.6084/m9.figshare.7435373.v1 cel-01973028 https://hal.archives-ouvertes.fr/cel-01973028 https://hal.archives-ouvertes.fr/cel-01973028/document https://hal.archives-ouvertes.fr/cel-01973028/file/Lemenkova_etal_Present_Yamal2012.pdf doi:10.6084/m9.figshare.7435373.v1 http://creativecommons.org/publicdomain/zero/1.0/ info:eu-repo/semantics/OpenAccess CC0 PDM https://hal.archives-ouvertes.fr/cel-01973028 Master. Serbia. 2012 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 ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering/I.5.3.0: Algorithms ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.1: Image processing software ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.0: Image displays ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation/I.4.6.1: Pixel classification ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering [SDE.ES]Environmental Sciences/Environmental and Society [SDE.MCG]Environmental Sciences/Global Changes [SDE.IE]Environmental Sciences/Environmental Engineering [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC] [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] [SHS.GEO]Humanities and Social Sciences/Geography [SHS.ENVIR]Humanities and Social Sciences/Environmental studies info:eu-repo/semantics/lecture Lectures 2012 ftccsdartic https://doi.org/10.6084/m9.figshare.7435373.v1 2020-12-24T23:17:34Z 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. ... Lecture Arctic permafrost Tundra Yamal Peninsula Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) Arctic Bovanenkovo ENVELOPE(68.437,68.437,70.354,70.354) Yamal Peninsula ENVELOPE(69.873,69.873,70.816,70.816)