Research on Spatial Downscale Temperature Prediction by using Machine Learning and its Application in Urban Heat Island

• Material Type: 博士論文
• Title: Research on Spatial Downscale Temperature Prediction by using Machine Learning and its Application in Urban Heat Island
• Author/Editor: オウ, ルイ
• Author Heading: オウ, ルイ
• Publication Date: 2021-09-24
• Publication Date (W3CDTF): 2021-09-24
• Alternative Title: 機械学習を用いた空間ダウンスケールの気温予測法及び都市ヒートアイランドへの応用に関する研究
• Degree grantor/type: 北九州市立大学
• Date Granted: 2021-09-24
• Date Granted (W3CDTF): 2021-09-24
• Dissertation Number: 甲第168号
• Degree Type: 博士(工学)
• Conferring No. (Dissertation): 甲第168号
• Text Language Code: eng
• Subject Heading: Air Temperature; Urban Heat Island; Downscaling; Machine Learning; Metropolitan Area
• Target Audience: 一般
• Note (General): This study introduced a temperature spatial downscaling method based on machine learning algorithm to downscale air temperature from 1 km to 250 m for high-resolution atmosphere urban heat island (UHI) analysis. The core of this downscaling method is to establish the regression model between urban structure and temperature, and then we used the unchanged characteristics of regression models at different scale to predict high-resolution temperature data with high-resolution resolution urban structure, thereby analyzed atmosphere urban heat island. Finally, we compared the similarity and differentiation between atmosphere UHI and surface UHI. The results indicated the following: (1) The machine learning method was proved to be suitable for the air temperature spatial downscaling predication; (2) The UHI characteristics of metropolitan areas in different climatic regions of Japan are different; (3) There are great differences in intensity and spatial distribution between atmosphere UHI and surface UHI is great.
• Persistent ID (NDL): info:ndljp/pid/11976718; https://dl.ndl.go.jp/pid/11976718
• Collection: 障害者向け資料
• Collection (Materials For Handicapped People:1): テキストデータ
• Collection (particular): 国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文; https://dl.ndl.go.jp/collections/A00014
• Acquisition Basis: 博士論文（自動収集）
• Date Accepted (W3CDTF): 2022-01-10T16:22:37+09:00
• Date Created (W3CDTF): 2021-12-25
• Format (IMT): application/pdf
• Access Restrictions: 国立国会図書館内限定公開
• Service for the Digitized Contents Transmission Service: 図書館・個人送信対象外
• Availability of remote photoduplication service: 可
• Periodical Title (URI): https://kitakyu.repo.nii.ac.jp/records/928
• Data Provider (Database): 国立国会図書館 : 国立国会図書館デジタルコレクション; https://dl.ndl.go.jp

Table of Contents

2023-09-07 再収集