Modelling Landscape Changes and Detecting Land Cover Types by Means of Remote Sensing Data and ILWIS GIS.

Bulletin of the Ufa State Petroleum Technological Uni- versity 1. Information Technologies. Problems and Solutions (ed Enikeev, F. U.) 265–271. issn: 2500-2996 (2015). The emphasis of this article is placed on the technical application of the remote sensing tools and methods for studies of vegetatio...

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Main Author: Lemenkova, Polina
Format: Text
Language:unknown
Published: figshare 2018
Subjects:
Online Access:https://dx.doi.org/10.6084/m9.figshare.7439219.v1
https://figshare.com/articles/Modelling_Landscape_Changes_and_Detecting_Land_Cover_Types_by_Means_of_Remote_Sensing_Data_and_ILWIS_GIS_/7439219/1
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spelling ftdatacite:10.6084/m9.figshare.7439219.v1 2023-05-15T18:45:33+02:00 Modelling Landscape Changes and Detecting Land Cover Types by Means of Remote Sensing Data and ILWIS GIS. Lemenkova, Polina 2018 https://dx.doi.org/10.6084/m9.figshare.7439219.v1 https://figshare.com/articles/Modelling_Landscape_Changes_and_Detecting_Land_Cover_Types_by_Means_of_Remote_Sensing_Data_and_ILWIS_GIS_/7439219/1 unknown figshare https://dx.doi.org/10.6084/m9.figshare.7439219 Creative Commons Zero v1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/legalcode cc0-1.0 CC0 Geography 60302 Biogeography and Phylogeography FOS Biological sciences 160401 Economic Geography FOS Social and economic geography Physical Geography 160403 Social and Cultural Geography Text article-journal Journal contribution ScholarlyArticle 2018 ftdatacite https://doi.org/10.6084/m9.figshare.7439219.v1 https://doi.org/10.6084/m9.figshare.7439219 2021-11-05T12:55:41Z Bulletin of the Ufa State Petroleum Technological Uni- versity 1. Information Technologies. Problems and Solutions (ed Enikeev, F. U.) 265–271. issn: 2500-2996 (2015). The emphasis of this article is placed on the technical application of the remote sensing tools and methods for studies of vegetation coverage in northern ecosystems. The study area is located in Yamal peninsula, the Russian Federation. Landsat imagery covering study area in 1988, 2001 and 2011 has been analyzed using ILWIS GIS. The image processing was performed using semi-automated method of image interpretation. The remote sensing data classification from ILWIS menu enabled to map vegetation coverage over research area, which helped to identify land cover types and distribution in Yamal. Results show that Landsat TM imagery with 30 m mesh spacing is useful for landscape mapping and the interpretation of the vegetation cover types. Text Yamal Peninsula DataCite Metadata Store (German National Library of Science and Technology) Yamal Peninsula ENVELOPE(69.873,69.873,70.816,70.816)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Geography
60302 Biogeography and Phylogeography
FOS Biological sciences
160401 Economic Geography
FOS Social and economic geography
Physical Geography
160403 Social and Cultural Geography
spellingShingle Geography
60302 Biogeography and Phylogeography
FOS Biological sciences
160401 Economic Geography
FOS Social and economic geography
Physical Geography
160403 Social and Cultural Geography
Lemenkova, Polina
Modelling Landscape Changes and Detecting Land Cover Types by Means of Remote Sensing Data and ILWIS GIS.
topic_facet Geography
60302 Biogeography and Phylogeography
FOS Biological sciences
160401 Economic Geography
FOS Social and economic geography
Physical Geography
160403 Social and Cultural Geography
description Bulletin of the Ufa State Petroleum Technological Uni- versity 1. Information Technologies. Problems and Solutions (ed Enikeev, F. U.) 265–271. issn: 2500-2996 (2015). The emphasis of this article is placed on the technical application of the remote sensing tools and methods for studies of vegetation coverage in northern ecosystems. The study area is located in Yamal peninsula, the Russian Federation. Landsat imagery covering study area in 1988, 2001 and 2011 has been analyzed using ILWIS GIS. The image processing was performed using semi-automated method of image interpretation. The remote sensing data classification from ILWIS menu enabled to map vegetation coverage over research area, which helped to identify land cover types and distribution in Yamal. Results show that Landsat TM imagery with 30 m mesh spacing is useful for landscape mapping and the interpretation of the vegetation cover types.
format Text
author Lemenkova, Polina
author_facet Lemenkova, Polina
author_sort Lemenkova, Polina
title Modelling Landscape Changes and Detecting Land Cover Types by Means of Remote Sensing Data and ILWIS GIS.
title_short Modelling Landscape Changes and Detecting Land Cover Types by Means of Remote Sensing Data and ILWIS GIS.
title_full Modelling Landscape Changes and Detecting Land Cover Types by Means of Remote Sensing Data and ILWIS GIS.
title_fullStr Modelling Landscape Changes and Detecting Land Cover Types by Means of Remote Sensing Data and ILWIS GIS.
title_full_unstemmed Modelling Landscape Changes and Detecting Land Cover Types by Means of Remote Sensing Data and ILWIS GIS.
title_sort modelling landscape changes and detecting land cover types by means of remote sensing data and ilwis gis.
publisher figshare
publishDate 2018
url https://dx.doi.org/10.6084/m9.figshare.7439219.v1
https://figshare.com/articles/Modelling_Landscape_Changes_and_Detecting_Land_Cover_Types_by_Means_of_Remote_Sensing_Data_and_ILWIS_GIS_/7439219/1
long_lat ENVELOPE(69.873,69.873,70.816,70.816)
geographic Yamal Peninsula
geographic_facet Yamal Peninsula
genre Yamal Peninsula
genre_facet Yamal Peninsula
op_relation https://dx.doi.org/10.6084/m9.figshare.7439219
op_rights Creative Commons Zero v1.0 Universal
https://creativecommons.org/publicdomain/zero/1.0/legalcode
cc0-1.0
op_rightsnorm CC0
op_doi https://doi.org/10.6084/m9.figshare.7439219.v1
https://doi.org/10.6084/m9.figshare.7439219
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