Downscaling MODIS-derived water maps with high-precision topographic data in a shallow lake. Issue 22 (17th November 2018)

• Record Type: Journal Article
• Authors: Xiao, Fei; Cheng, Weiming; Zhu, Lingling; Feng, Qi; Du, Yun
• Is Part Of: International journal of remote sensing. Volume 39:Issue 22(2018)
• Page Start: 7846
• Page End: 7860
• Publication Date: 2018-11-17
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2018.1474529
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: Remotely sensed imagery is the most efficient and widely used data source to monitor the water area changes. However, a trade-off always exists between temporal resolution and spatial resolution for satellite images. Taking the southern Dongting Lake as an example, this study was conducted to develop a method of downscaling the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived coarse spatial resolution water maps in shallow lakes with high-precision digital elevation model. The main principle of the method is to identify and adjust the horizontal location errors of the waterlines extracted from coarse-resolution data by analysing and modifying the elevation leaps using finer-scale topography information. Moving average filter was used to smooth the errors of waterlines caused by the geometric inaccuracies and classification uncertainties of the coarse data. The optimal local window size of the moving average filter was selected automatically using an exponential decay function model and a curvature algorithm for each pixel in the waterlines. In reference to Landsat Thematic Mapper data, the accuracy of the downscaling result is distinctly higher than that of the original MODIS normalized difference water index-derived water maps. The presented method is proved to be an effective tool for acquiring water maps of shallow lake with high spatio-temporal resolution using coarse- or moderate-resolution satellite imagery and high-precision topographic data.