Japan Geoscience Union Meeting 2018

Presentation information

[EE] Poster

M (Multidisciplinary and Interdisciplinary) » M-TT Technology & Techniques

[M-TT36] Environmental Remote Sensing

Mon. May 21, 2018 1:45 PM - 3:15 PM Poster Hall (International Exhibition Hall7, Makuhari Messe)

convener:Wei Yang(Chiba University), Yuji Sakuno(Institute of Engineering, Hiroshima University), Akihiko Kondoh(千葉大学環境リモートセンシング研究センター)

[MTT36-P03] Long-term Satellite Monitoring of Water Quality Parameters in Lake Kasumigaura, Japan

*Wei Yang1, Bunkei Matsushita2, Akihiko Kondoh1 (1.Chiba Univ., 2.Univ. of Tsukuba)

Keywords:inland lake, satellite remote sensing, water quality

Routine monitoring of water quality parameters is necessary for sustainable management of freshwater ecosystems. However, the spatial and temporal heterogeneity of water areas often results in inadequate monitoring and analysis of water quality using conventional in-situ sampling methods. Satellite remote sensing is a feasible technique for monitoring inland lakes in terms of being able to cover large spatial areas at very frequent intervals. In this study, ENVISAT/MERIS satellite images were applied to estimate the water quality parameters (e.g., Chlorophyll-a, Secchi disk depth) in Lake Kasumigaura, Japan between 2003 and 2012. The MERIS Level 1B radiance data were first processed through an atmospheric correction algorithm developed specifically for turbid inland waters. Then the water quality parameters were retrieved from the atmospherically corrected reflectance using a series of our algorithms developed in previous studies. Finally, the satellite-derived parameters were compared with the field database of Lake Kasumigaura. The results showed that the MERIS data in tandem with the atmospheric correction and water quality retrieval algorithms yielded acceptable accuracies with a normalized mean absolute error (NMAE) lower than 34%, and a coefficient of determination (R2) higher than 0.73. Moreover, the MERIS-derived parameters also showed seasonal and yearly variations similar to those of the field measured data. These findings demonstrate the potential of our proposed algorithms to routinely monitor water quality in Lake Kasumigaura using satellite observations in an operational manner.