Retrieval of Chlorophyll a, suspended solids, and colored dissolved organic matter in Tokyo Bay using ASTER data

Kishino, Motoaki; Tanaka, Akihiko; Ishizaka, Joji

doi:10.1016/j.rse.2005.05.016

Cited by 69 publications

(33 citation statements)

References 23 publications

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“…Besides, Landsat 8 OLI has been innovated with 12 bits of radiance resolution compared to 8 bits for the older ones, Landsat 5 TM and Landsat 7 ETM+. Numerous studies on ocean color remote sensing for water quality parameter retrieval have been done, most of which follow three main methods: (i) using semi-analytic models based on the correlation between the inherent optical properties (IOPs) and the water quality parameters [7,[11][12][13][14][15]; (ii) using empirical models between IOPs and these parameters [1,16,17,]; and (iii) using empirical models between remote sensing reflectance and the same parameters [18][19][20][21]. The third approach has been applied in this study, which is based on the correlation between remote sensing reflectance values extracted from Landsat 8 OLI and field measurements.…”

Section: Study Sitementioning

confidence: 99%

Spatiotemporal Variation of Turbidity Based on Landsat 8 OLI in Cam Ranh Bay and Thuy Trieu Lagoon, Vietnam

Quang

Sasaki

Higa

et al. 2017

Water

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Abstract:In recent years, seagrass beds in Cam Ranh Bay and Thuy Trieu Lagoon have declined from 800 to 550 hectares, resulting insignificantly reducing the number of fish catch. This phenomenon is due to the effect of the degradation of water environment. Turbidity is one of the most important water quality parameters directly related to underwater light penetration which affects the primary productivity. This study aims to investigate spatiotemporal variation of turbidity in the waters with major factors affecting its patterns using remote sensing data. An algorithm for turbidity retrieval was developed based on the correlation between in situ measurements and a red band of Landsat 8 OLI with R 2 = 0.84 (p < 0.05). Simulating WAves Nearshore (SWAN) model was used to compute bed shear stress, a major factor affecting turbidity in shallow waters. In addition, the relationships between turbidity and rainfall, and bed shear stress induced by wind were analyzed. It was found that: (1) In the dry season, turbidity was low at the middle of the bay while it was high in shallow waters nearby coastlines. Resuspension of bed sediment was a major factor controlling turbidity during time with no rainfall. (2) In the rainy season or for a short time after rainfall in the dry season, turbidity was high due to a large amount of runoff entering into the study area.

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Section: Study Sitementioning

confidence: 99%

Spatiotemporal Variation of Turbidity Based on Landsat 8 OLI in Cam Ranh Bay and Thuy Trieu Lagoon, Vietnam

Quang

Sasaki

Higa

et al. 2017

Water

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“…To explore the relationship between the spectral signature of a water body and the water's biophysical parameters, both linear and non-linear models have been developed (Zhang et al, 2002;Darecki et al, 2003;Kishino et al, 2005). For midoceanic (case I) waters, regression models are even processed operationally (Esaias et al, 1998;Carder et al, 2004).…”

Section: Mapping Sediment Concentrations and Light Climatementioning

confidence: 99%

Satellite-based monitoring of tropical seagrass vegetation: current techniques and future developments

Ferwerda¹,

Leeuw

Atzberger³

et al. 2007

Hydrobiologia

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Decline of seagrasses has been documented in many parts of the world. Reduction in water clarity, through increased turbidity and increased nutrient concentrations, is considered to be the primary cause of seagrass loss. Recent studies have indicated the need for new methods that will enable early detection of decline in seagrass extent and productivity, over large areas. In this review of current literature on coastal remote sensing, we examine the ability of remote sensing to serve as an information provider for seagrass monitoring. Remote sensing offers the potential to map the extent of seagrass cover and monitor changes in these with high accuracy for shallow waters. The accuracy of mapping seagrasses in deeper waters is unclear. Recent advances in sensor technology and radiometric transfer modelling have resulted in the ability to map suspended sediment, sea surface temperature and below-surface irradiance. It is therefore potentially possible to monitor the factors that cause the decline in seagrass status. When the latest products in remote sensing are linked to seagrass production models, it may serve as an early-warning system for seagrass decline and ultimately allow a better management of these susceptible ecosystems.

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“…Agricultural runoff and addition of organic wastes from various industries such as food processing plants, tanneries, textile factories and dairies result in the loading of nitrates and phosphorus into water bodies which leads to eutrophication resulting in high growth of algae (Fried et al,2003;Gunatilaka and Wijeyaratne, 2009). The Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) imageries from the NASA's Terra satellite have been widely used for the estimation of Chl-a in aquatic systems (Sakuno and Matsunaga, 2002;Kishino et al, 2005;Nas et al, 2009). This is mainly because ASTER has a spatial resolution 15 m and swath width of 60 km in the visible and near-infrared (VNIR) spectral region (Yamaguchi et al, 1998), which is sufficiently high to target smaller water bodies, such as lakes, lagoons and estuaries.…”

Section: Introductionmentioning

confidence: 99%

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Dahanayaka¹,

Perera²,

Wijeyaratne³

et al. 2016

Turk. J. Fish. Aquat. Sci.

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This study was aimed to determine the present level and past trends of eutrophication of the Bolgoda North lake, Sri Lanka using in situ Chlorophyll-a (Chl-a) measurements and remote sensing data obtained from Advanced Space-borne Thermal Emission and Reflectance Radiometer (ASTER) satellite data. From March to October 2013, Chl-a, nitrate and phosphate contents of the lake were measured once a month on the days of ASTER overpass and using standard laboratory methods. Cloud-free ASTER images of the lake for the 2000-2013 period were atmospherically corrected using Fast Line-ofsight Atmospheric Analysis of Hypercubes (FLAASH) and in-situ Chl-a data were regressed with atmospherically corrected three ASTER Visible and Near Infrared band ratios of the same date. The green/red band ratio, which had the highest coefficient of determination, was used to develop algorithm for generation of 15-m resolution Chl-a distribution maps. Results indicated that eutrophication of this lake has increased from 2008 to 2011. Heavy eutrophic conditions were noted in several regions of the lake in 2013, especially in water stagnant areas and adjacent to freshwater inlets. Unplanned urbanization and inadequate facilities for waste management have resulted in heavy eutrophication of the water body. If the present trends of waste disposal and unplanned urbanization continue, enormous environmental problems would be resulted in future.

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Retrieval of Chlorophyll a, suspended solids, and colored dissolved organic matter in Tokyo Bay using ASTER data

Cited by 69 publications

References 23 publications

Spatiotemporal Variation of Turbidity Based on Landsat 8 OLI in Cam Ranh Bay and Thuy Trieu Lagoon, Vietnam

Spatiotemporal Variation of Turbidity Based on Landsat 8 OLI in Cam Ranh Bay and Thuy Trieu Lagoon, Vietnam

Satellite-based monitoring of tropical seagrass vegetation: current techniques and future developments

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