Comparison of different satellite sensors in detecting cyanobacterial bloom events in the Baltic Sea

Reinart, Anu; Kutser, Tiit

doi:10.1016/j.rse.2006.02.013

Cited by 158 publications

(97 citation statements)

References 20 publications

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“…MODIS band-1 has been shown to be sensitive to changes in concentrations of cyanobacteria grown in cultures and has therefore been suggested for the qualitative mapping of cyanobacterial blooms [48], while MODIS band-2 has been successfully used to quantify algal blooms in the Baltic Sea [49]. Kahru et al [26] suggested using MODIS band 1, 3, and 4 as true-color images to detect the presence of blooms, and as a quantitative quantification, they proposed using the difference between band-2 and band-1 as a water surface turbidity index.…”

Section: Kahru's Modelmentioning

confidence: 99%

Comparative Analysis of Four Models to Estimate Chlorophyll-a Concentration in Case-2 Waters Using MODerate Resolution Imaging Spectroradiometer (MODIS) Imagery

et al. 2012

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Abstract:The occurrence and extent of intense harmful algal blooms (HABs) have increased in inland waters during recent decades. Standard monitor networks, based on infrequent sampling from a few fixed observation stations, are not providing enough information on the extent and intensity of the blooms. Remote sensing has great potential to provide the spatial and temporal coverage needed. Several sensors have been designed to study water properties (AVHRR, SeaBAM, and SeaWIFS), but most lack adequate spatial resolution for monitoring algal blooms in small and medium-sized lakes. Over the last decade, satellite data with 250-m spatial resolution have become available with MODIS. In the present study, three models inspired by published approaches (Kahru, Gitelson, and Floating Algae Index (FAI)) and a new approach named APPEL (APProach by ELimination) were adapted to the specific conditions of southern Quebec and used to estimate chlorophyll-a concentration (Chl-a) using MODIS data. Calibration and validation were provided from in situ Chl-a measured in four lakes over 9 years (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008) and concurrent MODIS imagery. MODIS bands 3 to 7, originally at 500-m spatial resolution, were downscaled to 250 m. The APPEL, FAI, and Kahru models yielded satisfactory results and enabled estimation of Chl-a for heavy blooming conditions (Chl-a > 50 mg•m −3 ), with coefficients of determination reaching 0.95, 0.94, and 0.93, respectively. The model inspired from Gitelson did not provide good estimations compared to the others (R 2 = 0.77).However, the performance of all models decreased when Chl-a was below 50 mg•m −3 . OPEN ACCESSRemote Sens. 2012, 4 2374

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Section: Kahru's Modelmentioning

confidence: 99%

Comparative Analysis of Four Models to Estimate Chlorophyll-a Concentration in Case-2 Waters Using MODerate Resolution Imaging Spectroradiometer (MODIS) Imagery

et al. 2012

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“…When determining the trophic state of an aquatic system, one of the main indicators is the chlorophyll-a (chl-a) concentration [2]. Chl-a is also the primary component of almost all phytoplankton species, one of the main indicators of the presence of cyanobacteria in inland waters [3] and the primary optically active component in the study of water color [4]. All of these characteristics enhance the importance of monitoring chl-a concentration in aquatic systems, not only because of its consequences to environmental and public health, but also for its role as a bio-indicator of algal blooms.…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo- to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil

et al. 2014

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Monitoring chlorophyll-a (chl-a) concentrations is important for the management of water quality, because it is a good indicator of the eutrophication level in an aquatic system. Thus, our main purpose was to develop an alternative technique to monitor chl-a in time and space through remote sensing techniques. However, one of the limitations of remote sensing is the resolution. To achieve a high temporal resolution and medium space resolution, we used the Moderate Resolution Imaging Spectroradiometer (MODIS) 500-m reflectance product, MOD09GA, and limnological parameters from the Itumbiara Reservoir. With these data, an empirical (O14a) and semi-empirical (O14b) algorithm were developed. Algorithms were cross-calibrated and validated using three datasets: one for each campaign and a third consisting of a combination of the two individual campaigns. OPEN ACCESSRemote Sens. 2014, 6 1635 Algorithm O14a produced the best validation with a root mean square error (RMSE) of 30.4%, whereas O14b produced an RMSE of 32.41% using the mixed dataset calibration. O14a was applied to MOD09GA to build a time series for the reservoir for the year of 2009. The time-series analysis revealed that there were occurrences of algal blooms in the summer that were likely related to the additional input of nutrients caused by rainfall runoff. During the winter, however, the few observed algal blooms events were related to periods of atmospheric meteorological variations that represented an enhanced external influence on the processes of mixing and stratification of the water column. Finally, the use of remote sensing techniques can be an important tool for policy makers, environmental managers and the scientific community with which to monitor water quality.

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“…Landsat data have been used to monitor algal blooms [Chang et al, 2004;Vincent et al, 2004], and Moderate Resolution Imaging Spectroradiometer ( MODIS) 250-meter and Medium Resolution Imaging Spectrometer ( MERIS) fullresolution (300-meter) bands have been utilized to detect cyanobacterial blooms [Reinart and Kutser, 2006] as well as to monitor water quality [Koponen et al, 2004].…”

Section: Eos Volume 90 Number 5 3 February 2009mentioning

confidence: 99%

Eos, Transactions, American Geophysical Union Volume 90, Number 5, 3 February 2009

2009

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Comparison of different satellite sensors in detecting cyanobacterial bloom events in the Baltic Sea

Cited by 158 publications

References 20 publications

Comparative Analysis of Four Models to Estimate Chlorophyll-a Concentration in Case-2 Waters Using MODerate Resolution Imaging Spectroradiometer (MODIS) Imagery

Comparative Analysis of Four Models to Estimate Chlorophyll-a Concentration in Case-2 Waters Using MODerate Resolution Imaging Spectroradiometer (MODIS) Imagery

Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo- to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil

Eos, Transactions, American Geophysical Union Volume 90, Number 5, 3 February 2009

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