Time-series analysis of Landsat-MSS/TM/OLI images over Amazonian waters impacted by gold mining activities

Lobo, Felipe L.; Costa, Maycira; Novo, Evlyn Márcia Leão de Moraes

doi:10.1016/j.rse.2014.04.030

Cited by 127 publications

(145 citation statements)

References 53 publications

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“…Lobo et al used a time-series analysis of Landsat-MSS/TM/OLI images to assess the impacts of gold mining activities to Amazonian waters. This result indicated that water reflectance of red band of Landsat was the most appropriate for establishing a robust empirical model for TSS retrieval [43]. Vanhellemont and Ruddick used Landsat 8 OLI Band 4 to retrieve turbidity in the Southern North Sea where the water depth was less than 50 m. They also used MODIS red band, 645 nm, for testing turbidity retrieval algorithm.…”

Section: Turbidity Algorithmmentioning

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: Turbidity Algorithmmentioning

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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“…Sun glint and sky light caused by the Fresnel reflection on sea surface have strong impacts on the sea surface reflectance (Kutser, Vahtmäe, Paavel, & Kauer, 2013), especially for high resolution satellite images (Kay, Hedley, & Lavender, 2009;Lobo, Costa, & Novo, 2015) such as Landsat and HJ-1. Variations in sun glint might be one of major sources causing uncertainties in using the FAI, VB-FAH, NDVI and NIR-RED (the vertical height extracted by the NIR and red bands, or the band difference, Richardson & Everitt, 1992) indexes to classify macroalgae pixels.…”

Section: Sensitivity Of Vb-fah To Variations In Sea Surface Glint Andmentioning

confidence: 99%

Mapping macroalgal blooms in the Yellow Sea and East China Sea using HJ-1 and Landsat data: Application of a virtual baseline reflectance height technique

Xing

2016

Remote Sensing of Environment

139

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Several methods have been proposed in previous studies to map macroalgal blooms (MABs) in the Yellow Sea (YS) and East China Sea (ECS), yet some of the required spectral bands are not available on the new HJ-1 satellite sensors although they do provide optimal resolution and temporal coverage (30-m resolution with 2-day revisit frequency) for bloom mapping. In this study, an index of Virtual-Baseline Floating macroAlgae Height (VB-FAH) is proposed to use the green and red bands as the baseline to measure the height of the near-infrared (NIR) reflectance. Cross-sensor comparison with Landsat TM and ETM + data suggests that for several images evaluated here VB-FAH appears to be comparable to the previously proposed Floating Algae Index (FAI) even in the absence of a shortwave-infrared (SWIR) band. VB-FAH is applied to 30-m resolution TM and ETM + data for the YS during 1995-2006 and to HJ-1 data for the ECS during 2009-2014 to map MABs. Results show bloom history in the YS back to 1999 and early bloom occurrence in the ECS in winter and spring (e.g., February and March 2013). MABs are also found to extend to the ECS as far south as 26°N near Fujian Province and Taiwan, and as far east as the Kuroshio Current. These new findings provide important information for exploring the origins, causes, and consequences of MABs in the YS and ECS.

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“…L8 aims to provide data continuity to the global NASA Landsat Earth observation program that started in the 1970s. The OLI sensor has been evaluated to be suitable for the assessment of water quality and water constituents in many water bodies such as lakes, estuaries, rivers and coastal zones Vanhellemont & Ruddick, 2014;Brando et al, 2015;Franz et al, 2015;Lobo et al, 2015;Slonecker et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Mapping phytoplankton blooms in deep subalpine lakes from Sentinel-2A and Landsat-8

et al. 2018

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For effective lakes' management, highfrequent water quality data on a synoptic scale are essential. The aim of this study is to test the suitability of the latest generation of satellite sensors to provide information on lake water quality parameters for the five largest Italian subalpine lakes. In situ data of phytoplankton composition, chlorophyll-a (chl-a) concentration and water reflectance were used in synergy with satellite observations to map some algal blooms in 2016. Chl-a concentration maps were derived from satellite data by applying a bio-optical model to satellite data, previously corrected for atmospheric effects. Results were compared with in situ data, showing good agreement. The shape and magnitude of water reflectance from different satellite data were consistent. Output chl-a concentration maps, show the distribution within each lake during blooming events, suggesting a synoptic view is required for these events monitoring. Maps show the dynamic of bloom events with concentration increasing from 2 up to 7 mg m -3 and dropping again to initial value in less than 20 days. Latest generation sensors were shown to be valuable tools for lakes monitoring, thanks to frequent, free of charge data availability over long time periods.

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Time-series analysis of Landsat-MSS/TM/OLI images over Amazonian waters impacted by gold mining activities

Cited by 127 publications

References 53 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

Mapping macroalgal blooms in the Yellow Sea and East China Sea using HJ-1 and Landsat data: Application of a virtual baseline reflectance height technique

Mapping phytoplankton blooms in deep subalpine lakes from Sentinel-2A and Landsat-8

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