Alas landscape modeling by remote sensing image analysis and geographic ontology: study case of central Yakutia (Russia)

Approaches of geographic ontologies can help to overcome the problems of ambiguity and uncertainty of remote sensing data analysis for modeling the landscapes as a multidimensional geographic object of research. Image analysis based on the geographic ontologies allows to recognize the elementary cha...

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Main Authors: Gadal, Sébastien, Zakharov, Moisei, Kamičaitytė, Jūratė, Danilov, Yuri
Format: Article in Journal/Newspaper
Language:English
Published: 2020
Subjects:
Online Access:http://ktu.lvb.lt/KTU:ELABAPDB62528202&prefLang=en_US
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author Gadal, Sébastien
Zakharov, Moisei
Kamičaitytė, Jūratė
Danilov, Yuri
author_facet Gadal, Sébastien
Zakharov, Moisei
Kamičaitytė, Jūratė
Danilov, Yuri
author_sort Gadal, Sébastien
collection LAEI VL (Lithuanian Institute of Agrarian Economics Virtual Library)
description Approaches of geographic ontologies can help to overcome the problems of ambiguity and uncertainty of remote sensing data analysis for modeling the landscapes as a multidimensional geographic object of research. Image analysis based on the geographic ontologies allows to recognize the elementary characteristics of the alas landscapes and their complexity. The methodology developed includes three levels of geographic object recognition: (1) the landscape land cover classification using Support Vector Machine (SVM) and Spectral Angle Mapper (SAM) classifiers; (2) the object-based image analysis (OBIA) used for the identification of alas landscape objects according to their morphologic structures using the Decision Tree Learning algorithm; (3) alas landscape’s identification and categorization integrating vegetation objects, territorial organizations, and human cognitive knowledge reflected on the geo-linguistic object-oriented database made in Central Yakutia. The result gives an ontology-based alas landscape model as a system of geographic objects (forests, grasslands, arable lands, termokarst lakes, rural areas, farms, repartition of built-up areas, etc.) developed under conditions of permafrost and with a high sensitivity to the climate change and its local variabilities. The proposed approach provides a multidimensional reliable recognition of alas landscape objects by remote sensing images analysis integrating human semantic knowledge model of Central Yakutia in the subarctic Siberia. This model requires to conduct a multitemporal dynamic analysis for the sustainability assessment and land management.
format Article in Journal/Newspaper
genre permafrost
Subarctic
Yakutia
Siberia
termokarst
genre_facet permafrost
Subarctic
Yakutia
Siberia
termokarst
id ftlitinstagrecon:oai:elaba:62528202
institution Open Polar
language English
op_collection_id ftlitinstagrecon
op_relation http://ktu.lvb.lt/KTU:ELABAPDB62528202&prefLang=en_US
op_source GISTAM 2020: proceedings of the 6th international conference on geographical information systems theory, applications and management, May 7-9, 2020 / edited by C. Grueau, R. Laurini, L. Ragia, Setúbal : Scitepress - Science and technology publications, 2020, p. 112-118
ISSN 2184-500X
ISBN 9789897584251
publishDate 2020
record_format openpolar
spelling ftlitinstagrecon:oai:elaba:62528202 2025-01-17T00:16:53+00:00 Alas landscape modeling by remote sensing image analysis and geographic ontology: study case of central Yakutia (Russia) Gadal, Sébastien Zakharov, Moisei Kamičaitytė, Jūratė Danilov, Yuri 2020 http://ktu.lvb.lt/KTU:ELABAPDB62528202&prefLang=en_US eng eng http://ktu.lvb.lt/KTU:ELABAPDB62528202&prefLang=en_US GISTAM 2020: proceedings of the 6th international conference on geographical information systems theory, applications and management, May 7-9, 2020 / edited by C. Grueau, R. Laurini, L. Ragia, Setúbal : Scitepress - Science and technology publications, 2020, p. 112-118 ISSN 2184-500X ISBN 9789897584251 geographic ontology image analysis knowledge database image processing alas landscape remote sensing info:eu-repo/semantics/article 2020 ftlitinstagrecon 2021-12-02T00:56:44Z Approaches of geographic ontologies can help to overcome the problems of ambiguity and uncertainty of remote sensing data analysis for modeling the landscapes as a multidimensional geographic object of research. Image analysis based on the geographic ontologies allows to recognize the elementary characteristics of the alas landscapes and their complexity. The methodology developed includes three levels of geographic object recognition: (1) the landscape land cover classification using Support Vector Machine (SVM) and Spectral Angle Mapper (SAM) classifiers; (2) the object-based image analysis (OBIA) used for the identification of alas landscape objects according to their morphologic structures using the Decision Tree Learning algorithm; (3) alas landscape’s identification and categorization integrating vegetation objects, territorial organizations, and human cognitive knowledge reflected on the geo-linguistic object-oriented database made in Central Yakutia. The result gives an ontology-based alas landscape model as a system of geographic objects (forests, grasslands, arable lands, termokarst lakes, rural areas, farms, repartition of built-up areas, etc.) developed under conditions of permafrost and with a high sensitivity to the climate change and its local variabilities. The proposed approach provides a multidimensional reliable recognition of alas landscape objects by remote sensing images analysis integrating human semantic knowledge model of Central Yakutia in the subarctic Siberia. This model requires to conduct a multitemporal dynamic analysis for the sustainability assessment and land management. Article in Journal/Newspaper permafrost Subarctic Yakutia Siberia termokarst LAEI VL (Lithuanian Institute of Agrarian Economics Virtual Library)
spellingShingle geographic ontology
image analysis
knowledge database
image processing
alas landscape
remote sensing
Gadal, Sébastien
Zakharov, Moisei
Kamičaitytė, Jūratė
Danilov, Yuri
Alas landscape modeling by remote sensing image analysis and geographic ontology: study case of central Yakutia (Russia)
title Alas landscape modeling by remote sensing image analysis and geographic ontology: study case of central Yakutia (Russia)
title_full Alas landscape modeling by remote sensing image analysis and geographic ontology: study case of central Yakutia (Russia)
title_fullStr Alas landscape modeling by remote sensing image analysis and geographic ontology: study case of central Yakutia (Russia)
title_full_unstemmed Alas landscape modeling by remote sensing image analysis and geographic ontology: study case of central Yakutia (Russia)
title_short Alas landscape modeling by remote sensing image analysis and geographic ontology: study case of central Yakutia (Russia)
title_sort alas landscape modeling by remote sensing image analysis and geographic ontology: study case of central yakutia (russia)
topic geographic ontology
image analysis
knowledge database
image processing
alas landscape
remote sensing
topic_facet geographic ontology
image analysis
knowledge database
image processing
alas landscape
remote sensing
url http://ktu.lvb.lt/KTU:ELABAPDB62528202&prefLang=en_US