WEKO3
アイテム
オープンソースのリモートセンシングデータと機械学習アプローチを活用したラオス人民民主共和国ナム・グム川流域（NNRB）における洪水危険度マッピング
https://doi.org/10.18997/0002001045
https://doi.org/10.18997/0002001045e9a61226-0a83-4f0d-bd36-a2fdaed9dc77
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
kou_k_594.pdf (12.4 MB)
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| アイテムタイプ | 学位論文 = Thesis or Dissertation(1) | |||||||
|---|---|---|---|---|---|---|---|---|
| 公開日 | 2024-11-19 | |||||||
| 資源タイプ | ||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_db06 | |||||||
| 資源タイプ | doctoral thesis | |||||||
| タイトル | ||||||||
| タイトル | Leveraging open-source remote-sensing data and machine learning approaches for flood prediction and susceptibility mapping in Nam Ngum River Basin (NNRB), Lao PDR | |||||||
| 言語 | en | |||||||
| タイトル | ||||||||
| タイトル | オープンソースのリモートセンシングデータと機械学習アプローチを活用したラオス人民民主共和国ナム・グム川流域（NNRB）における洪水危険度マッピング | |||||||
| 言語 | ja | |||||||
| 言語 | ||||||||
| 言語 | jpn | |||||||
| 著者 |
Mangkhaseum, Sackdavong
× Mangkhaseum, Sackdavong
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| 抄録 | ||||||||
| 内容記述タイプ | Abstract | |||||||
| 内容記述 | Frequent floods caused by monsoons and rainstorms have significantly affected the resilience of human and natural ecosystems in the Nam Ngum River Basin, Lao PDR. A cost-efficient framework integrating advanced remote sensing and machine learning techniques is proposed to address this issue by enhancing flood susceptibility understanding and informed decision-making. This study utilizes remote sensing geo-datasets and machine learning algorithms (Random Forest, Support Vector Machine, Artificial Neural Networks, and Long Short-Term Memory) to generate comprehensive flood susceptibility maps. The results highlight Random Forest’s superior performance, achieving the highest train and test Area Under the Curve of Receiver Operating Characteristic (AUROC) (1.00 and 0.993), accuracy (0.957), F1-score (0.962), and kappa value (0.91), with the lowest mean squared error (0.207) and Root Mean Squared Error (0.043). Vulnerability is particularly pronounced in low-elevation and low-slope southern downstream areas (Central part of Lao PDR). The results reveal that 36– 53% of the basin’s total area is highly susceptible to flooding, emphasizing the dire need for coordinated floodplain management strategies. This research uses freely accessible remote sensing data, addresses data scarcity in flood studies, and provides valuable insights for disaster risk management and sustainable planning in Lao PDR In addition, the generated flood susceptibility map is used to analyze the possible effect on the different land use/land cover classes, populations and critical facilities. ANN and DNN outperform LSTM, achieving higher accuracy based on Receiver Operating Characteristics. The resulting flood susceptibility maps identify critical zones within the Nam Ngum River Basin at high risk of flooding, revealing that 36-53% of the basin area is highly susceptible, especially in low-elevation and low-slope regions. Additionally, 85-93% of the population is highly vulnerable to flooding within 261 to 296 km² of built-up area. Almost all of the critical facilities for health and education lie within the area, which is highly susceptible to flooding. |
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| 目次 | ||||||||
| 内容記述タイプ | TableOfContents | |||||||
| 内容記述 | 1 INTRODUCTION| 2 LITERATURE REVIEW| 3 STUDY AREA| 4 RESULTS AND DISCUSSION| 5 FLOOD RISK ASSESSMENT ON LAND COVER, POPULATION, AND CRITICAL FACILITIES IN NAM NGUM RIVER BASIN, LAO PDR| 6 CONCLUSION AND RECOMMENDATION | |||||||
| 備考 | ||||||||
| 内容記述タイプ | Other | |||||||
| 内容記述 | 九州工業大学博士学位論文 学位記番号:工博甲第594号 学位授与年月日:令和6年9月25日 | |||||||
| 学位授与番号 | ||||||||
| 学位授与番号 | 甲第594号 | |||||||
| 学位名 | ||||||||
| 学位名 | 博士（工学） | |||||||
| 学位授与年月日 | ||||||||
| 学位授与年月日 | 2024-09-25 | |||||||
| 学位授与機関 | ||||||||
| 学位授与機関識別子Scheme | kakenhi | |||||||
| 学位授与機関識別子 | 17104 | |||||||
| 学位授与機関名 | 九州工業大学 | |||||||
| 言語 | ja | |||||||
| 学位授与年度 | ||||||||
| 内容記述タイプ | Other | |||||||
| 内容記述 | 令和6年度 | |||||||
| 出版タイプ | ||||||||
| 出版タイプ | VoR | |||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||
| アクセス権 | ||||||||
| アクセス権 | open access | |||||||
| アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||||
| ID登録 | ||||||||
| ID登録 | 10.18997/0002001045 | |||||||
| ID登録タイプ | JaLC | |||||||
