研究課題/領域番号 |
22K18055
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研究種目 |
若手研究
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配分区分 | 基金 |
審査区分 |
小区分64040:自然共生システム関連
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研究機関 | 総合地球環境学研究所 |
研究代表者 |
NguyenTien Hoang 総合地球環境学研究所, 研究部, 特任助教 (20829379)
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研究期間 (年度) |
2022-04-01 – 2025-03-31
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研究課題ステータス |
交付 (2022年度)
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配分額 *注記 |
4,550千円 (直接経費: 3,500千円、間接経費: 1,050千円)
2024年度: 650千円 (直接経費: 500千円、間接経費: 150千円)
2023年度: 1,820千円 (直接経費: 1,400千円、間接経費: 420千円)
2022年度: 2,080千円 (直接経費: 1,600千円、間接経費: 480千円)
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キーワード | Machine learning / Remote sensing / Ecological modeling |
研究開始時の研究の概要 |
This research will develop a machine learning-based species distribution model based on multiple remotely sensed data sources. The results will enrich the understanding of habitat characteristics and contribute to conservation planning of critically endangered mammals.
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研究実績の概要 |
During the initial year, I analyzed satellite imagery to create a map of land use changes and deforestation patterns in the study area over the past decade. Furthermore, various machine learning techniques have been evaluated to predict the locations where local people typically harvest forest resources. These results, which were presented at the NERPS Conference and the General Meeting of the AJG, serve to pinpoint intact forests where rare species are likely to exist. Additionally, I conducted a survey to collect ground truth data to enhance forest mapping accuracy and assess the applicability of thermal sensing with drone technology for wildlife monitoring.
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現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
Despite some deviations from the initial plan, I believe the research is generally progressing smoothly.
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今後の研究の推進方策 |
I intend to move forward with the research as initially planned.
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