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MODIS衛星データを用いたPM2.5大気汚染の検出(その1:黄砂検出との違い)
https://doi.org/10.57375/00001642
https://doi.org/10.57375/000016428d4dc2ec-1937-4bdb-9400-bff9be80ea0a
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
231-242.pdf (14.4 MB)
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| Item type | 紀要論文 / Departmental Bulletin Paper(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2015-08-06 | |||||
| タイトル | ||||||
| タイトル | MODIS衛星データを用いたPM2.5大気汚染の検出(その1:黄砂検出との違い) | |||||
| タイトル | ||||||
| タイトル | Detection of PM2.5 Air Pollutions by Using MODIS Data (Part 1: Differences between the Detection of PM2.5 Air Pollutions and the Detection of Dust and Sandstorms) | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | jpn | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | PM2.5 Air Pollution | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Dust and Sandstorms | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | MODIS | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | AVI | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | YDI | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Composite Color Image | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | departmental bulletin paper | |||||
| ID登録 | ||||||
| ID登録 | 10.57375/00001642 | |||||
| ID登録タイプ | JaLC | |||||
| 著者 |
加藤, 芳信
× 加藤, 芳信× Kato, Yoshinobu |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | In recent years, PM2.5 air pollution is a social and transboundary environmental issue with the rapid economic growth in many countries. As PM2.5 is small and includes various ingredients (e.g., sulfur oxide, nitrogen oxide, vitriol, nitrate salt, soot, etc.), the detection of PM2.5 air pollutions by using satellite data is difficult compared with the detection of dust and sandstorms (DSS). DSS can be detected by using AVI method and YDI method. AVI (Aerosol Vapor Index) is defined as AVI=T12-T11, where T12 and T11 are the brightness temperatures at 12μm and 11μm wave lengths, respectively. For MODIS data, T12 and T11 correspond to band32 and band31, respectively. YDI (Yellow Dust Index) is defined as YDI=(band4-band3)/(band4+band3). AVI and YDI methods detect PM2.5 air pollutions only a little. In this paper, we examine various RGB composite color images for detecting PM2.5 air pollutions by using MODIS data, i.e., {R, G, B = band4, band3, T11}, {R, G, B = band10, band9, T11}, {R, G, B = band9, band8, T11}, {R, G, B = AVI, band7-band1, T11}, {R, G, B = AVI, band10-band9, T11}, etc. A good method for the detection of PM2.5 air pollution is {R, G, B = band10, band9, T11}. In this composite color image, PM2.5 air pollutions are represented by light purple or pink color. This proposed method is applied to the detection of PM2.5 air pollutions in the wide area from China and India to Japan by using MODIS data on 12 January 2013, and AVI method is applied to DSS detection in the same area. By comparing the AVI image with the image by the proposed method, PM2.5 air pollutions can be distinguished from DSS. The proposed method is simpler than the method by Nagatani et al. (2013), and is useful to grasp the distribution of PM2.5 air pollutions in the wide area. | |||||
| 書誌情報 |
福井工業大学研究紀要 号 45, p. 231-242, 発行日 2015-08-06 |
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| 出版者 | ||||||
| 出版者 | 福井工業大学 | |||||
| 書誌レコードID | ||||||
| 識別子タイプ | NCID | |||||
| 関連識別子 | TF00010523 | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
