The contribution of ASTER, CBERS, R99/SIPAM e OrbiSAR-1 data to improve the oceanic monitoring

Bentz, Cristina Maria; Politano, Alexandre Tadeu; Genovez, Patrícia Carneiro; Lorenzzetti, João A.; Kampel, Milton

doi:10.1109/igarss.2007.4422967

Cited by 1 publication

(2 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Concurrent with the mesoscale eddy there was an uncommon sea floor oil seep event [17], which surface signature won't be discussed in detail here.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic

Kampel

Lorenzzetti

Bentz

et al. 2009

Sensors

Self Cite

View full text Add to dashboard Cite

Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL) and ocean color remote sensing estimates were conducted during an oceanographic cruise on the Brazilian Southeastern continental shelf and slope, Southwestern South Atlantic. In situ values were based on fluorometry, above-water radiometry and lidar fluorosensor. Three empirical algorithms were used to estimate CHL from radiometric measurements: Ocean Chlorophyll 3 bands (OC3MRAD), Ocean Chlorophyll 4 bands (OC4v4RAD), and Ocean Chlorophyll 2 bands (OC2v4RAD). The satellite estimates of CHL were derived from data collected by the MODerate-resolution Imaging Spectroradiometer (MODIS) with a nominal 1.1 km resolution at nadir. Three algorithms were used to estimate chlorophyll concentrations from MODIS data: one empirical - OC3MSAT, and two semi-analytical - Garver, Siegel, Maritorena version 01 (GSM01SAT), and CarderSAT. In the present work, MODIS, lidar and in situ above-water radiometry and fluorometry are briefly described and the estimated values of chlorophyll retrieved by these techniques are compared. The chlorophyll concentration in the study area was in the range 0.01 to 0.2 mg/m3. In general, the empirical algorithms applied to the in situ radiometric and satellite data showed a tendency to overestimate CHL with a mean difference between estimated and measured values of as much as 0.17 mg/m3 (OC2v4RAD). The semi-analytical GSM01 algorithm applied to MODIS data performed better (rmse 0.28, rmse-L 0.08, mean diff. -0.01 mg/m3) than the Carder and the empirical OC3M algorithms (rmse 1.14 and 0.36, rmse-L 0.34 and 0.11, mean diff. 0.17 and 0.02 mg/m3, respectively). We find that rmsd values between MODIS relative to the in situ radiometric measurements are < 26%, i.e., there is a trend towards overestimation of RRS by MODIS for the stations considered in this work. Other authors have already reported over and under estimation of MODIS remotely sensed reflectance due to several errors in the bio-optical algorithm performance, in the satellite sensor calibration, and in the atmospheric-correction algorithm.

show abstract

“…Concurrent with the mesoscale eddy there was an uncommon sea floor oil seep event [17], which surface signature won't be discussed in detail here.…”

Section: Resultsmentioning

confidence: 99%

“…Based on the MODIS chlorophyll fields, in situ data and numerical modeling was possible to observe an anticyclonic Brazil Current frontal eddy in the study area during the cruise [ 16 ]. Concurrent with the mesoscale eddy there was an uncommon sea floor oil seep event [ 17 ], which surface signature won't be discussed in detail here.…”

Section: Resultsmentioning

confidence: 99%