Publications

Heege, Thomas; Kiselev, Viacheslav; Wettle, Magnus; Nguyen Nghia Hung (2014). Operational multi-sensor monitoring of turbidity for the entire Mekong Delta. INTERNATIONAL JOURNAL OF REMOTE SENSING, 35(8), 2910-2926.

Abstract
An operational satellite-based approach was implemented to monitor turbidity and organic absorption in the Mekong river system. Using physics-based algorithms linked together in a fully automated processing chain, more than 300 Landsat Enhanced Thematic Mapper (ETM) scenes and 1000 MODIS scenes, representing five years of data, were used to produce standardized, quantitative time series of turbidity and organic absorption across Vietnam, Thailand, Cambodia, Laos, and China. To set up this system, the specific inherent optical properties (SIOPs) of the Mekong river system were determined through three separate field campaigns, laboratory analysis, and subsequent optical closure calculations. Following this, a range of satellite data types was tested using the derived Mekong-specific inherent optical properties, including Moderate Resolution Imaging Spectroradiometer (MODIS) 500m data, Landsat ETM, Medium Resolution Imaging Spectrometer (MERIS), Satellite Pour l'Observation de la Terre (SPOT) 5, RapidEye, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and QuickBird. The satellite-based turbidity estimates were coincident with available field data, and comparisons showed them to be in good agreement. Overall, the derived SIOPs were suitable for water-quality monitoring of the Mekong, and the MODIS, MERIS, Landsat, and RapidEye sensors were found to be the most radiometrically stable and thereby suitable for ongoing operational processing. The implemented system delivers consistent results across the different satellite sensors and over time, but is limited to where the spatial resolution of the sensor is still able to resolve the river width. The system is currently applicable for the entire Mekong river system, both for near-real-time monitoring and for analysis of historical data archive.

DOI:
10.1080/01431161.2014.890300

ISSN:
0143-1161; 1366-5901