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Open AccessArticle

Long-Term Change of the Secchi Disk Depth in Lake Maninjau, Indonesia Shown by Landsat TM and ETM+ Data

1
Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8572, Japan
2
Research Center for Limnology, Indonesian Institute of Sciences (LIPI), Cibinong Science Center, Bogor 16911, Indonesia
3
Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8572, Japan
4
Kasumigaura Environmental Science Center, 1853 Okijuku-machi, Tsuchiura, Ibaraki 300-0023, Japan
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(23), 2875; https://doi.org/10.3390/rs11232875
Received: 31 October 2019 / Revised: 27 November 2019 / Accepted: 1 December 2019 / Published: 3 December 2019
(This article belongs to the Section Environmental Remote Sensing)
Most of the lakes in Indonesia are facing environmental problems such as eutrophication, sedimentation, and depletion of dissolved oxygen. The water quality data for supporting lake management in Indonesia are very limited due to financial constraints. To address this issue, satellite data are often used to retrieve water quality data. Here, we developed an empirical model for estimating the Secchi disk depth (SD) from Landsat TM/ETM+ data by using data collected from nine Indonesian lakes/reservoirs (SD values 0.5–18.6 m). We made two efforts to improve the robustness of the developed model. First, we carried out an image preprocessing series of steps (i.e., removing contaminated water pixels, filtering images, and mitigating atmospheric effects) before the Landsat data were used. Second, we selected two band ratios (blue/green and red/green) as SD predictors; these differ from previous studies’ recommendation. The validation results demonstrated that the developed model can retrieve SD values with an R2 of 0.60 and the root mean square error of 1.01 m in Lake Maninjau, Indonesia (SD values ranged from 0.5 to 5.8 m, n = 74). We then applied the developed model to 230 scenes of preprocessed Landsat TM/ETM+ images to generate a long-term SD database for Lake Maninjau during 1987–2018. The visual comparison of the in situ-measured and satellite estimated SD values, as well as several events (e.g., algal bloom, water gate open, and fish culture), showed that the Landsat-based SD estimations well captured the change tendency of water transparency in Lake Maninjau, and these estimations will thus provide useful data for lake managers and policy-makers. View Full-Text
Keywords: water transparency; historical Landsat data; empirical model; Indonesian lake; atmospheric correction water transparency; historical Landsat data; empirical model; Indonesian lake; atmospheric correction
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Setiawan, F.; Matsushita, B.; Hamzah, R.; Jiang, D.; Fukushima, T. Long-Term Change of the Secchi Disk Depth in Lake Maninjau, Indonesia Shown by Landsat TM and ETM+ Data. Remote Sens. 2019, 11, 2875.

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