Geographic object-based image analysis (GEOBIA): emerging trends and future opportunities
Over the last two decades (since ca. 2000), Geographic Object-Based Image Analysis (GEOBIA) has emerged as a new paradigm to analyzing high-spatial resolution remote-sensing imagery. During this time, research interests have demonstrated a shift from the development of GEOBIA theoretical foundations...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2018-03-01
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| Series: | GIScience & Remote Sensing |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/15481603.2018.1426092 |
| _version_ | 1797679131227324416 |
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| author | Gang Chen Qihao Weng Geoffrey J. Hay Yinan He |
| author_facet | Gang Chen Qihao Weng Geoffrey J. Hay Yinan He |
| author_sort | Gang Chen |
| collection | DOAJ |
| description | Over the last two decades (since ca. 2000), Geographic Object-Based Image Analysis (GEOBIA) has emerged as a new paradigm to analyzing high-spatial resolution remote-sensing imagery. During this time, research interests have demonstrated a shift from the development of GEOBIA theoretical foundations to advanced geo-object-based models and their implementation in a wide variety of real-world applications. We suggest that such a rapid GEOBIA evolution warrants the need for a systematic review that defines the recent developments in this field. Therefore, the main objective of this paper is to elucidate the emerging trends in GEOBIA and discuss potential opportunities for future development. The emerging trends were found in multiple subfields of GEOBIA, including data sources, image segmentation, object-based feature extraction, and geo-object-based modeling frameworks. It is our view that understanding the state-of-the-art in GEOBIA will further facilitate and support the study of geographic entities and phenomena at multiple scales with effective incorporation of semantics, informing high-quality project design, and improving geo-object-based model performance and results. |
| first_indexed | 2024-03-11T23:09:57Z |
| format | Article |
| id | doaj.art-fd5783ee5b9243c6ac20d6e1c8f313b2 |
| institution | Directory Open Access Journal |
| issn | 1548-1603 1943-7226 |
| language | English |
| last_indexed | 2024-03-11T23:09:57Z |
| publishDate | 2018-03-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | GIScience & Remote Sensing |
| spelling | doaj.art-fd5783ee5b9243c6ac20d6e1c8f313b22023-09-21T12:34:14ZengTaylor & Francis GroupGIScience & Remote Sensing1548-16031943-72262018-03-0155215918210.1080/15481603.2018.14260921426092Geographic object-based image analysis (GEOBIA): emerging trends and future opportunitiesGang Chen0Qihao Weng1Geoffrey J. Hay2Yinan He3University of North Carolina at CharlotteIndiana State UniversityUniversity of CalgaryUniversity of North Carolina at CharlotteOver the last two decades (since ca. 2000), Geographic Object-Based Image Analysis (GEOBIA) has emerged as a new paradigm to analyzing high-spatial resolution remote-sensing imagery. During this time, research interests have demonstrated a shift from the development of GEOBIA theoretical foundations to advanced geo-object-based models and their implementation in a wide variety of real-world applications. We suggest that such a rapid GEOBIA evolution warrants the need for a systematic review that defines the recent developments in this field. Therefore, the main objective of this paper is to elucidate the emerging trends in GEOBIA and discuss potential opportunities for future development. The emerging trends were found in multiple subfields of GEOBIA, including data sources, image segmentation, object-based feature extraction, and geo-object-based modeling frameworks. It is our view that understanding the state-of-the-art in GEOBIA will further facilitate and support the study of geographic entities and phenomena at multiple scales with effective incorporation of semantics, informing high-quality project design, and improving geo-object-based model performance and results.http://dx.doi.org/10.1080/15481603.2018.1426092geographic object-based image analysis (geobia)emerging trendsdata sourcesimage segmentationobject-based feature extraction |
| spellingShingle | Gang Chen Qihao Weng Geoffrey J. Hay Yinan He Geographic object-based image analysis (GEOBIA): emerging trends and future opportunities GIScience & Remote Sensing geographic object-based image analysis (geobia) emerging trends data sources image segmentation object-based feature extraction |
| title | Geographic object-based image analysis (GEOBIA): emerging trends and future opportunities |
| title_full | Geographic object-based image analysis (GEOBIA): emerging trends and future opportunities |
| title_fullStr | Geographic object-based image analysis (GEOBIA): emerging trends and future opportunities |
| title_full_unstemmed | Geographic object-based image analysis (GEOBIA): emerging trends and future opportunities |
| title_short | Geographic object-based image analysis (GEOBIA): emerging trends and future opportunities |
| title_sort | geographic object based image analysis geobia emerging trends and future opportunities |
| topic | geographic object-based image analysis (geobia) emerging trends data sources image segmentation object-based feature extraction |
| url | http://dx.doi.org/10.1080/15481603.2018.1426092 |
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