The use of ALOS data in studying environmental changes in Malaysia

• 資料種別: 文書・図像類
• タイトル: The use of ALOS data in studying environmental changes in Malaysia
• 著者・編者: Lim, Hwee San; Jafri, Mohd. Zubir Mat; Abdullah, Khiruddin; Saleh, Nasirun Mohd.; Tahrin, Norhaslinda Mohamed
• 著者標目: Lim, Hwee San; Jafri, Mohd. Zubir Mat; Abdullah, Khiruddin; Saleh, Nasirun Mohd.; Tahrin, Norhaslinda Mohamed
• 出版事項: 宇宙航空研究開発機構地球観測研究センター (JAXA)(EORC)
• 出版年月日等: 2011
• 出版年（W3CDTF）: 2011
• タイトル（掲載誌）: 宇宙航空研究開発機構特別資料 = JAXA Special Publication: Final Reports of the ALOS Research Announcement Programs 1&2, 2011
• 巻号年月日等（掲載誌）: JAXA-SP-11-007E
• 掲載巻: JAXA-SP-11-007E
• 掲載ページ: PI404-1-PI404-20
• ISSN（掲載誌）: ISSN : 1349-113X
• 本文の言語コード: eng
• 件名標目: Water Quality; TSS; Land Cover
• 対象利用者: 一般
• 一般注記: Remote sensing data have been widely used in environmental studies like land cover change, flood observation, environmental pollution monitoring. This study is dealing with obtaining land cover, flood observation and environmental pollution using ALOS data. With the availability of remotely sensed and in situ data sets the derivable geophysical parameters are water depth, sea surface temperature (SST) and sediment (suspended matter) concentration. Understanding of the optical properties of water and the atmospheric contribution serves as a basic for the derivation of algorithms for specific applications using data in the visible and the near infrared regions. For the thermal region atmospheric absorption and the surface thermal properties are considered for the development of the SST algorithm. Analyses of time series of remote sensing images with regard to the variation of the water quality parameters of interest are required. In situ water samples coincident with the remote sensing data will be collected. Measurements of the in situ water quality parameters are performed at selected locations within the studied area, i.e. water areas surrounding Penang Island. Surface and vertical profile of sediment concentrations will be measured. This will be done at various locations along the coastal and during diurnal various times of the year. The time scheme for the data collection will be covering different seasons of the year. Satellite scenes that coincide simultaneously with the in situ data will be employed.; Several processing steps will be performed to the remote sensing data for water quality maps generation: 1. Geometric correction - images will be rectified to the corresponding maps or coordinate system of the area.; 2. Atmospheric correction - the darkest pixel method will be applied to reduce atmospheric contamination on the scenes. Other methods will also be investigated. Cloud masking will be; performed to the thermal data.; 3. Algorithm calibration, regression analysis - regression analysis will be performed to determine the optimum algorithm for each application.; 4. Generation of water quality maps - the calibrated algorithm will be applied to the remote sensing data sets for establishing water quality maps.; 5. Interpretation and modeling - from the retrieved information, detailed interpretation can be made.; Human-induced changes in land cover are as ancient as humankind itself. Society's demand for physical resources, and the expansion of its technological, managerial, and institutional capacity to produce, move, and consume such resources, have long altered land vegetation and other surface features. The characteristics of land cover have important impacts on climate, global biogeochemistry, and the abundance and composition of terrestrial species. The land cover will be mainly derived from visual interpretation of recent high resolution satellite images digitally enhanced. In this study, we propose to use high resolution satellite imagery to map areas of forest clearing and general land cover types for the entire Peninsular Malaysia region. In this study, the supervised and unsupervised classifications techniques will be used to generate thematic land cover maps. And then their accuracy will be determined by the Kappa Coefficient and overall accuracy. The thematic interpretation of ALOS data and the validation of the land cover map will be supported by available Landsat TM images, SPOT images and IRS data, and vegetation maps and field data collected in the region. The resulting land cover map will be integrated in a socio-economic study to assess the trends and patterns of deforestation by including demographic and social and environmental policies. Finally, we also will study the land cover changes over the study areas. There were two steps involved in identifying land cover changes using the ALOS imagery: 1) identify the land cover types on both of the ALOS images, and 2) compare the land cover types on the ALOS images to determine which areas represented land cover changes. In this study, we also will investigate the coincident distribution, and detailed patterns in space and time of land cover, land-cover attributes, and land-cover change. Several processing steps will be performed to the remote sensing data: 2. Atmospheric correction - the darkest pixel method will be applied to reduce atmospheric contamination on the scenes. Other methods will also be investigated. Cloud masking will be performed to the thermal data.; 3. Classification analysis - two classification techniques analysis will be performed to determine the land cover types.; 4. Accuracy assessments - Kappa Coefficient will be performed to determine the accuracy of the classified maps.; 5. Generation of land covers maps - the best produced accuracy classifier will be used to generate land cover maps.; 6. Land cover changes interpretation - from the generated land cover maps, detailed land cover changes can be made.; 7. Interpretation and modeling - from the retrieved information, detailed interpretation can be made.; 形態: カラー図版あり; 形態: DVD-ROM1枚; Physical characteristics: Original contains color illustrations; Note: One DVD-ROM; 資料番号: AA0065135067; レポート番号: JAXA-SP-11-007E
• 一次資料へのリンクURL: https://jaxa.repo.nii.ac.jp/?action=repository_action_common_download&item_id=4537&item_no=1&attribute_id=31&file_no=1
• オンライン閲覧公開範囲: 限定公開
• 連携機関・データベース: 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）; https://irdb.nii.ac.jp
• 提供元機関・データベース: 宇宙航空研究開発機構 : 宇宙航空研究開発機構リポジトリ