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| Presentation | 2022-12-16 10:45 Machine learning for global detection of photovoltaic panel installation using Landsat-8 Imagery Ryo Ito, Ryu Sugimoto, Chiaki Tsutsumi, Ryosuke Nakamura (AIST)  SANE2022-77 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Nowadays, free-and-open medium-resolution satellite imagery can be utilized for sustainable monitoring of global changes. In this study, we investigate a method to detect and identify solar panels installed during two periods from Landsat8 imagery. In recent years, AI such as deep learning has been considered one of the monitoring methods. However, medium-resolution satellite imagery has some unique characteristics that become advantages and disadvantages compared to aerial imagery when applying AI. In the case of Landsat-8 imagery, it has multiple bands outside the visible range, but the 30m spatial resolution sometimes can obscure the shapes of features. In this study, we introduce several approaches based on these characteristics. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | image identification / sateｌlite image / Deep Learning / CNN / Landsat8 / solar panel / global changes / land cover change | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 312, SANE2022-77, pp. 74-76, Dec. 2022. | |
| Paper # | SANE2022-77 | |
| Date of Issue | 2022-12-08 (SANE) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | SANE2022-77 |
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| Conference Information | |
| Committee | SANE |
| Conference Date | 2022-12-15 - 2022-12-16 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Nagasaki Public Hall |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | ICSANE |
| Paper Information | |
| Registration To | SANE |
| Conference Code | 2022-12-SANE |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Machine learning for global detection of photovoltaic panel installation using Landsat-8 Imagery |
| Sub Title (in English) | |
| Keyword(1) | image identification |
| Keyword(2) | sateｌlite image |
| Keyword(3) | Deep Learning |
| Keyword(4) | CNN |
| Keyword(5) | Landsat8 |
| Keyword(6) | solar panel |
| Keyword(7) | global changes |
| Keyword(8) | land cover change |
| 1st Author's Name | Ryo Ito |
| 1st Author's Affiliation | National Institute of Advanced Industrial Science and Technology (AIST) |
| 2nd Author's Name | Ryu Sugimoto |
| 2nd Author's Affiliation | National Institute of Advanced Industrial Science and Technology (AIST) |
| 3rd Author's Name | Chiaki Tsutsumi |
| 3rd Author's Affiliation | National Institute of Advanced Industrial Science and Technology (AIST) |
| 4th Author's Name | Ryosuke Nakamura |
| 4th Author's Affiliation | National Institute of Advanced Industrial Science and Technology (AIST) |
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| Speaker | Author-1 |
| Date Time | 2022-12-16 10:45:00 |
| Presentation Time | 20 minutes |
| Registration for | SANE |
| Paper # | SANE2022-77 |
| Volume (vol) | vol.122 |
| Number (no) | no.312 |
| Page | pp.74-76 |
| #Pages | 3 |
| Date of Issue | 2022-12-08 (SANE) |
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