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Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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Sensors and Materials
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 37, Number 6(4) (2025)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 2589-2605
S&M4076 Research Paper of Special Issue https://doi.org/10.18494/SAM5539 Published: June 30, 2025 Applicability of the Geospatial Segment Anything Model for Reservoir Extraction Using KOMPSAT-3/3A Satellite Imagery [PDF] Namhoon Kim, Suhong Yoo, Hanna Lee, Sumin Park, and Gihong Kim (Received January 10, 2025; Accepted April 23, 2025) Keywords: remote sensing, deep learning, Segment Anything Model, image segmentation, water body extraction, reservoir monitoring, KOMPSAT-3/3A
Accurate reservoir area data are essential for effective water resource management, yet traditional field surveys often face labor and logistical challenges. In this study, we evaluated the Geospatial Segment Anything Model (GeoSAM) in conjunction with high-resolution KOMPSAT-3/3A satellite imagery for reservoir delineation in the Korean Peninsula. Our experiments demonstrate that GeoSAM consistently achieves high accuracies (85.95–97.10%), surpassing the conventional normalized difference water index-based extraction method, which averaged 93.74%. Moreover, GeoSAM maintains robust performance under challenging conditions—such as frozen reservoirs, shadowed areas, and cloudy environments—by incorporating additional point prompts. These findings underscore the potential of GeoSAM to advance remote sensing applications in water resource management, particularly for small- and medium-sized urban areas.
Corresponding author: Gihong Kim  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Namhoon Kim, Suhong Yoo, Hanna Lee, Sumin Park, and Gihong Kim, Applicability of the Geospatial Segment Anything Model for Reservoir Extraction Using KOMPSAT-3/3A Satellite Imagery, Sens. Mater., Vol. 37, No. 6, 2025, p. 2589-2605. |
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