Spatial downscaling of MODIS Chlorophyll-a using Landsat 8 images for complex coastal water monitoring. (30th September 2018)

• Record Type: Journal Article
• Authors: Fu, Yanzhao; Xu, Shiguo; Zhang, Chengkun; Sun, Ya
• Is Part Of: Estuarine, coastal and shelf science. Volume 209(2018)
• Page Start: 149
• Page End: 159
• Publication Date: 2018-09-30
• Subjects: Remote sensing -- MODIS -- Landsat -- Chl-a -- Downscaling; Estuarine oceanography -- Periodicals; Coasts -- Periodicals; Estuarine biology -- Periodicals; Seashore biology -- Periodicals; Coasts; Estuarine biology; Estuarine oceanography; Seashore biology; Periodicals; 551.461805
• DOI: 10.1016/j.ecss.2018.05.031
• Languages: English
• ISSNs: 0272-7714

Abstract

Abstract: Chlorophyll-a (Chl-a) is an indicator for monitoring the trophic status of coastal water. However, its sampling and analysing in situ can be time consuming and spatially limited. With high temporal resolution and global coverage, Moderate Resolution Imaging Spectroradiometer (MODIS) Level 3 products are reliable and widely used for ocean ecosystem monitoring. The Landsat images can provide detailed spatial information for regional scale land cover and land change studies. The purpose of this study is to combine the 4 km resolution MODIS Chl-a data with 30 m resolution Landsat data to obtain high spatial resolution Chl-a maps for complex coastal water quality monitoring. A data fusion model of MODIS Chl-a and Landsat 8 OLI sensor data was built up for the east coast of the Laizhou Bay, China. The model is an optimal regression model of the band ratio OLI+2/OLI+5 and MODIS Chl-a. With residual correction, it managed to downscale the MODIS Chl-a data from resolution 4 km to 30 m. Validation were provided from in situ Chl-a measured in spring and autumn of 2013 and 2014. The model yields satisfactory results and the derived Chl-a map presents detailed information of coastal trophic status, which will be useful for regional water quality monitoring.