An object-based semantic classification method of high resolution satellite imagery using ontology

Geographic Object-Based Image Analysis (GEOBIA) techniques have become increasingly popular in recent years and are able to incorporate and develop ontology model within the classification process. They have been claimed to represent a paradigm shift in remote sensing interpretation. Nevertheless, i...

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Tác giả chính:	Gu, H.Y.
Định dạng:	BB
Ngôn ngữ:	eng
Thông tin xuất bản:	2020
Chủ đề:	Land-Cover Classification Expert rule Machine learning Semantic Web Rule Language Web Ontology Language Semantic Network Model Ontology Geographic Object-based Image Analysis
Truy cập trực tuyến:	http://tailieuso.tlu.edu.vn/handle/DHTL/4432
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spelling	oai:localhost:DHTL-44322020-03-30T02:14:12Z An object-based semantic classification method of high resolution satellite imagery using ontology Gu, H.Y. Land-Cover Classification Expert rule Machine learning Semantic Web Rule Language Web Ontology Language Semantic Network Model Ontology Geographic Object-based Image Analysis Geographic Object-Based Image Analysis (GEOBIA) techniques have become increasingly popular in recent years and are able to incorporate and develop ontology model within the classification process. They have been claimed to represent a paradigm shift in remote sensing interpretation. Nevertheless, it is lack of formal expression and objective modelling of the whole process of GEOBIA, and lack of the study of semantic classification method using ontology. A major reason is the complexity of the process of GEOBIA. The study has put forward an object-based semantic classification method of high resolution satellite imagery using ontology that aims to fully exploit the advantages of ontology to GEOBIA. A detailed workflow has been introduced that has three steps: ontology modelling, initial classification based on data-driven machine learning method, and semantic classification based on knowledgedriven expert rules method. The whole process of GEOBA is organized organically and expressed explicitly using ontology, and the semantic relations are expressed in the formal language that the computer could operate. Image objects are classified based on ontology model and using machine learning method and expert rules. From the result it is well understood that the method enhances the existing GEOBIA techniques with the help of the ontology, which expresses and organizes the whole process of GEOBIA, and establishes their relations, and provides semantic meaning for GEOBIA. In particular, we found that it provides an ontology model and method for further classifications and large scale applications, and the method using ontology is suitable for automatic classification. https://proceedings.utwente.nl/374/1/Gu-An%20Object-based%20Semantic%20Classification%20Method%20of%20High%20Resolution%20Satellite%20Imagery%20Using%20Ontology-1187.pdf 2020-02-18T02:25:23Z 2020-02-18T02:25:23Z 2016 20190117144841.0 130605s2016 BB In: GEOBIA 2016 : Solutions and Synergies., 14 September 2016 - 16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC) . http://tailieuso.tlu.edu.vn/handle/DHTL/4432 eng
institution	Trường Đại học Thủy Lợi
collection	DSpace
language	eng
topic	Land-Cover Classification Expert rule Machine learning Semantic Web Rule Language Web Ontology Language Semantic Network Model Ontology Geographic Object-based Image Analysis
spellingShingle	Land-Cover Classification Expert rule Machine learning Semantic Web Rule Language Web Ontology Language Semantic Network Model Ontology Geographic Object-based Image Analysis Gu, H.Y. An object-based semantic classification method of high resolution satellite imagery using ontology
description	Geographic Object-Based Image Analysis (GEOBIA) techniques have become increasingly popular in recent years and are able to incorporate and develop ontology model within the classification process. They have been claimed to represent a paradigm shift in remote sensing interpretation. Nevertheless, it is lack of formal expression and objective modelling of the whole process of GEOBIA, and lack of the study of semantic classification method using ontology. A major reason is the complexity of the process of GEOBIA. The study has put forward an object-based semantic classification method of high resolution satellite imagery using ontology that aims to fully exploit the advantages of ontology to GEOBIA. A detailed workflow has been introduced that has three steps: ontology modelling, initial classification based on data-driven machine learning method, and semantic classification based on knowledgedriven expert rules method. The whole process of GEOBA is organized organically and expressed explicitly using ontology, and the semantic relations are expressed in the formal language that the computer could operate. Image objects are classified based on ontology model and using machine learning method and expert rules. From the result it is well understood that the method enhances the existing GEOBIA techniques with the help of the ontology, which expresses and organizes the whole process of GEOBIA, and establishes their relations, and provides semantic meaning for GEOBIA. In particular, we found that it provides an ontology model and method for further classifications and large scale applications, and the method using ontology is suitable for automatic classification.
format	BB
author	Gu, H.Y.
author_facet	Gu, H.Y.
author_sort	Gu, H.Y.
title	An object-based semantic classification method of high resolution satellite imagery using ontology
title_short	An object-based semantic classification method of high resolution satellite imagery using ontology
title_full	An object-based semantic classification method of high resolution satellite imagery using ontology
title_fullStr	An object-based semantic classification method of high resolution satellite imagery using ontology
title_full_unstemmed	An object-based semantic classification method of high resolution satellite imagery using ontology
title_sort	object-based semantic classification method of high resolution satellite imagery using ontology
publishDate	2020
url	http://tailieuso.tlu.edu.vn/handle/DHTL/4432
work_keys_str_mv	AT guhy anobjectbasedsemanticclassificationmethodofhighresolutionsatelliteimageryusingontology AT guhy objectbasedsemanticclassificationmethodofhighresolutionsatelliteimageryusingontology
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An object-based semantic classification method of high resolution satellite imagery using ontology

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