scholarly journals EVALUATING ACOMP, FLAASH AND QUAC ON WORLDVIEW-3 FOR SATELLITE DERIVED BATHYMETRY (SDB) IN SHALLOW WATER

2020 ◽  
Vol 46 (3) ◽  
pp. 151-158
Author(s):  
Abdul Basith ◽  
Ratna Prastyani
Keyword(s):  
Shallow Water ◽  
Marine Ecosystem ◽  
Atmospheric Correction ◽  
Atmospheric Effects ◽  
Green Band ◽  
Yellow Band ◽  
Band Ratio ◽  
Bathymetric Survey ◽  
Significant Challenge ◽  
Band Combinations

Bathymetry map is instrumental for monitoring marine ecosystem and supporting marine transportation. Optical satellite imagery has been widely utilised as an alternative method to derive bathymetry map in shallow water. Nonetheless, interactions between electromagnetic energy and Earth’s atmosphere causing the atmosphere effects pose a significant challenge in satellite-derived bathymetry (SDB) application. In this study, Worldview-3 imagery was used to obtain bathymetry map in shallow water. Three atmospheric correction models (ACOMP, FLAASH and QUAC) were employed to eliminate atmospheric effects on Worldview-3 imagery. Three simple band ratios involving coastal blue, blue, green and yellow band were used to test the performance of atmospheric correction models. ACOMP combined with blue and green band ratio efficaciously provided the best performance where it explained 77% of model values. Bathymetry map obtained from Worldview-3 was also validated using bathymetry data acquired from bathymetric survey over the study area. The estimated depths shared aggregable results with measured depths (depth < 20 m) with accuracy of 2.07 m. This study shows that robust atmospheric correction combined with suitable simple band combinations offered bathymetry map retrieval with relatively high accuracy.

scholarly journals Accuracy Assessment of Satellite Derived Bathymetry Model for Depth Extraction in Sorong Shallow Water Area

2021 ◽  
Vol 925 (1) ◽  
pp. 012053
Author(s):  
Ratna Sari Dewi ◽  
Aldino Rizaldy
Keyword(s):  
Shallow Water ◽  
Measurement Data ◽  
Water Area ◽  
Green Band ◽  
Blue Band ◽  
Band Ratio ◽  
Marine Research ◽  
Single Beam ◽  
Sea Bed ◽  
Shallow Water Area

Abstract Marine research has continuously improved the methods in obtaining the related bathymetric data; not only relying on the conventional methods for i.e. echosounder-based methods, but also by incorporating satellite technology for i.e. passive remote sensing technology, in this case, satellite derived bathymetry (SDB). Regarding the SDB method, as we know, variation of sea bed cover can influence the relation between the spectral reflection of shallow water area and the depth of the sea. In this situation, normalization of the sea bed variation is needed. Previous studies have mentioned that the band ratio can help to normalize the variation of sea bed cover. This research is intended to compare the accuracy of satellite derived bathymetry by using single band and band ratio. Four bands of Sentinel 2A (blue, green, red, and NIR bands) are used along with a single beam echosounder (SBES) measurement data published in 2015 used as training and testing data for the SDB model. Furthermore, the influence of sun glint correction to the results was evaluated and the accuracy of the model was estimated. In total there are four single bands and six combinations of band ratio that are used for this research. The results show that green band outperformed band ratio in term of RMSE value. However, visually, only band ratio of blue/green band that provided a much more representative depth spatial distribution especially for shallow water area below 3 m. In this case, band ratio is effective in normalizing the variation of sea bed cover. Furthermore, the use of sun glint correction in the process is also increase accuracies of the SDB model. The highest accuracy was obtained when using green band after sun glint correction with RMSE value 2.999 m while when using band ratio of the blue band to the green band (blue/green), the accuracy was 3.624 m. In conclusion, SDB model to extend methods in obtaining bathymetry data is promising as more images become available free of charge and in various resolutions.

scholarly journals New Approaches to Processing Ground-based SAR (GBSAR) Data for Deformation Monitoring

2018 ◽  
Vol 10 (12) ◽  
pp. 1936 ◽  
Author(s):  
Sichun Long ◽  
Aixia Tong ◽  
Ying Yuan ◽  
Zhenhong Li ◽  
Wenhao Wu ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Atmospheric Correction ◽  
Deformation Monitoring ◽  
Atmospheric Effects ◽  
Threshold Optimization ◽  
Before And After ◽  
Multiple Threshold ◽  
The Stability ◽  
Average Coherence

In this paper, aiming at the limitation of persistence scatterers (PS) points selection, a new method for selecting PS points has been introduced based on the average coherence coefficient, amplitude dispersion index, estimated signal-to-noise ratio and displacement standard deviation of multiple threshold optimization. The stability and quality of this method are better than that of a single model. In addition, an atmospheric correction model has also been proposed to estimate the atmospheric effects on Ground-based synthetic aperture radar (GBSAR) observations. After comparing the monitoring results before and after correction, we clearly found that the results are in good agreement with the actual observations after applying the proposed atmospheric correction approach.

scholarly journals Evaluation of Atmospheric Correction Algorithms over Spanish Inland Waters for Sentinel-2 Multi Spectral Imagery Data

2019 ◽  
Vol 11 (12) ◽  
pp. 1469 ◽  
Author(s):  
Marcela Pereira-Sandoval ◽  
Ana Ruescas ◽  
Patricia Urrego ◽  
Antonio Ruiz-Verdú ◽  
Jesús Delegido ◽  
...  
Keyword(s):  
Near Infrared ◽  
Atmospheric Correction ◽  
Inland Waters ◽  
Atmospheric Effects ◽  
Image Correction ◽  
Lakes And Reservoirs ◽  
Dark Pixel ◽  
Organic Particles ◽  
Sentinel 2

The atmospheric contribution constitutes about 90 percent of the signal measured by satellite sensors over oceanic and inland waters. Over open ocean waters, the atmospheric contribution is relatively easy to correct as it can be assumed that water-leaving radiance in the near-infrared (NIR) is equal to zero and it can be performed by applying a relatively simple dark-pixel-correction-based type of algorithm. Over inland and coastal waters, this assumption cannot be made since the water-leaving radiance in the NIR is greater than zero due to the presence of water components like sediments and dissolved organic particles. The aim of this study is to determine the most appropriate atmospheric correction processor to be applied on Sentinel-2 MultiSpectral Imagery over several types of inland waters. Retrievals obtained from different atmospheric correction processors (i.e., Atmospheric correction for OLI ‘lite’ (ACOLITE), Case 2 Regional Coast Colour (here called C2RCC), Case 2 Regional Coast Colour for Complex waters (here called C2RCCCX), Image correction for atmospheric effects (iCOR), Polynomial-based algorithm applied to MERIS (Polymer) and Sen2Cor or Sentinel 2 Correction) are compared against in situ reflectance measured in lakes and reservoirs in the Valencia region (Spain). Polymer and C2RCC are the processors that give back the best statistics, with coefficients of determination higher than 0.83 and mean average errors less than 0.01. An evaluation of the performance based on water types and single bands–classification based on ranges of in situ chlorophyll-a concentration and Secchi disk depth values- showed that performance of these set of processors is better for relatively complex waters. ACOLITE, iCOR and Sen2Cor had a better performance when applied to meso- and hyper-eutrophic waters, compare with oligotrophic. However, other considerations should also be taken into account, like the elevation of the lakes above sea level, their distance from the sea and their morphology.

scholarly journals Using Landsat-8 Images for Quantifying Suspended Sediment Concentration in Red River (Northern Vietnam)

2018 ◽  
Vol 10 (11) ◽  
pp. 1841 ◽  
Author(s):  
Quang Pham ◽  
Nguyen Ha ◽  
Nima Pahlevan ◽  
La Oanh ◽  
Thanh Nguyen ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Suspended Sediment Concentration ◽  
Atmospheric Correction ◽  
Sediment Concentration ◽  
Suspended Load ◽  
Red River ◽  
Landsat 8 ◽  
Band Ratio ◽  
Radiometric Data

Analyzing the trends in the spatial distribution of suspended sediment concentration (SSC) in riverine surface water enables better understanding of the hydromorphological properties of its watersheds and the associated processes. Thus, it is critical to identify an appropriate method to quantify spatio-temporal variability in SSC. This study aims to estimate SSC in a highly turbid river, i.e., the Red River in Northern Vietnam, using Landsat 8 (L8) images. To do so, in situ radiometric data together with SSC at 60 sites along the river were measured on two different dates during the dry and wet seasons. Analyses of the in situ data indicated strong correlations between SSC and the band-ratio of green and red channels, i.e., r-squared = 0.75 and a root mean square error of ~0.3 mg/L. Using a subsample of in situ radiometric data (n = 30) collected near-concurrently with one L8 image, four different atmospheric correction methods were evaluated. Although none of the methods provided reasonable water-leaving reflectance spectra (ρw), it was found that the band-ratio of the green-red ratio is less sensitive to uncertainties in the atmospheric correction for mapping SSC compared to individual bands. Therefore, due to its ease of access, standard L8 land surface reflectance products available via U.S. Geological Survey web portals were utilized. With the empirical relationship derived, we produced Landsat-derived SSC distribution maps for a few images collected in wet and dry seasons within the 2013–2017 period. Analyses of image products suggest that (a) the Thao River is the most significant source amongst the three major tributaries (Lo, Da and Thao rivers) providing suspended load to the Red River, and (b) the suspended load in the rainy season is nearly twice larger than that in the dry season, and it correlates highly with the runoff (correlation coefficient = 0.85). Although it is demonstrated that the atmospheric correction in tropical areas over these sediment-rich waters present major challenges in the retrievals of water-leaving reflectance spectra, the study signifies the utility of band-ratio techniques for quantifying SSC in highly turbid river waters. With Sentinel-2A/B data products combined with those of Landsat-8, it would be possible to capture temporal variability in major river systems in the near future.

scholarly journals Atmospheric correction of APEX hyperspectral data

2016 ◽  
Vol 20 (1) ◽  
pp. 16-20 ◽  
Author(s):  
Sindy Sterckx ◽  
Kristin Vreys ◽  
Jan Biesemans ◽  
Marian-Daniel Iordache ◽  
Luc Bertels ◽  
...  
Keyword(s):  
Atmospheric Correction ◽  
Hyperspectral Data ◽  
Atmospheric Effects ◽  
Atmospheric Transmission ◽  
Specific Effects ◽  
Correction Process ◽  
Moderate Resolution ◽  
Data Processing Center ◽  
Processing Steps ◽  
Central Data

Abstract Atmospheric correction plays a crucial role among the processing steps applied to remotely sensed hyperspectral data. Atmospheric correction comprises a group of procedures needed to remove atmospheric effects from observed spectra, i.e. the transformation from at-sensor radiances to at-surface radiances or reflectances. In this paper we present the different steps in the atmospheric correction process for APEX hyperspectral data as applied by the Central Data Processing Center (CDPC) at the Flemish Institute for Technological Research (VITO, Mol, Belgium). The MODerate resolution atmospheric TRANsmission program (MODTRAN) is used to determine the source of radiation and for applying the actual atmospheric correction. As part of the overall correction process, supporting algorithms are provided in order to derive MODTRAN configuration parameters and to account for specific effects, e.g. correction for adjacency effects, haze and shadow correction, and topographic BRDF correction. The methods and theory underlying these corrections and an example of an application are presented.

scholarly journals Improved MODIS-Aqua Chlorophyll-a Retrievals in the Turbid Semi-Enclosed Ariake Bay, Japan

2018 ◽  
Vol 10 (9) ◽  
pp. 1335 ◽  
Author(s):  
Meng Meng Yang ◽  
Joji Ishizaka ◽  
Joaquim I. Goes ◽  
Helga do R. Gomes ◽  
Elígio de Raús Maúre ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Red Tide ◽  
Atmospheric Correction ◽  
Ariake Bay ◽  
Band Ratio ◽  
Simple Method ◽  
Chl A ◽  
Switching Algorithm ◽  
Economic Significance

The accurate retrieval of chlorophyll-a concentration (Chl-a) from ocean color satellite data is extremely challenging in turbid, optically complex coastal waters. Ariake Bay in Japan is a turbid semi-enclosed bay of great socio-economic significance, but it suffers from serious water quality problems, particularly due to red tide events. Chl-a derived from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor on satellite Aqua in Ariake Bay was investigated, and it was determined that the causes of the errors were from inaccurate atmospheric correction and inappropriate in-water algorithms. To improve the accuracy of MODIS remote sensing reflectance (Rrs) in the blue and green bands, a simple method was adopted using in situ Rrs data. This method assumes that the error in MODIS Rrs(547) is small, and MODIS Rrs(412) can be estimated from MODIS Rrs(547) using a linear relation between in situ Rrs(412) and Rrs(547). We also showed that the standard MODIS Chl-a algorithm, OC3M, underestimated Chl-a, which was mostly due to water column turbidity. A new empirical switching algorithm was generated based on the relationship between in situ Chl-a and the blue-to-green band ratio, max(Rrs(443), Rrs(448)/Rrs(547), which was the same as the OC3M algorithm. The criterion of Rrs(667) of 0.005 sr−1 was used to evaluate the extent of turbidity for the switching algorithm. The results showed that the switching algorithm performed better than OC3M, and the root mean square error (RMSE) of estimated Chl-a decreased from 0.414 to 0.326. The RMSE for MODIS Chl-a using the recalculated Rrs and the switching algorithm was 0.287, which was a significant improvement from the RMSE of 0.610, which was obtained using standard MODIS Chl-a. Finally, the accuracy of our method was tested with an independent dataset collected by the local Fisheries Research Institute, and the results revealed that the switching algorithm with the recalculated Rrs reduced the RMSE of MODIS Chl-a from 0.412 of the standard to 0.335.

scholarly journals Validation of ASTER Emissivity Retrieval Using the Mako Airborne TIR Imaging Spectrometer at the Algodones Dune Field in Southern California, USA

2020 ◽  
Vol 12 (5) ◽  
pp. 815 ◽  
Author(s):  
Amit Mushkin ◽  
Alan R. Gillespie ◽  
Elsa A. Abbott ◽  
Jigjidsurengiin Batbaatar ◽  
Glynn Hulley ◽  
...  
Keyword(s):  
Southern California ◽  
Thermal Emission ◽  
Atmospheric Correction ◽  
Atmospheric Effects ◽  
Spectral Measurements ◽  
Spectral Variability ◽  
Pixel Resolution ◽  
Imaging Spectrometer ◽  
Dune Field ◽  
Cavity Radiation

Validation of emissivity (ε) retrievals from spaceborne thermal infrared (TIR) sensors typically requires spatial extrapolations over several orders of magnitude for a comparison between centimeter-scale laboratory ε measurements and the common decameter and lower resolution of spaceborne TIR data. In the case of NASA’s Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) temperature and ε separation algorithm (TES), this extrapolation becomes especially challenging because TES was originally designed for the geologic surface of Earth, which is typically heterogeneous even at centimeter and decameter scales. Here, we used the airborne TIR hyperspectral Mako sensor with its 2.2 m/pixel resolution, to bridge this scaling issue and robustly link between ASTER TES 90 m/pixel emissivity retrievals and laboratory ε measurements from the Algodones dune field in southern California, USA. The experimental setup included: (i) Laboratory XRD, grain size, and TIR spectral measurements; (ii) radiosonde launches at the time of the two Mako overpasses for atmospheric corrections; (iii) ground-based thermal measurements for calibration, and (iv) analyses of ASTER day and night ε retrievals from 21 different acquisitions. We show that while cavity radiation leads to a 2% to 4% decrease in the effective emissivity contrast of fully resolved scene elements (e.g., slipface slopes and interdune flats), spectral variability of the site when imaged at 90 m/pixel is below 1%, because at this scale the dune field becomes an effectively homogeneous mixture of the different dune elements. We also found that adsorption of atmospheric moisture to grain surfaces during the predawn hours increased the effective ε of the dune surface by up to 0.04. The accuracy of ASTER’s daytime emissivity retrievals using each of the three available atmospheric correction protocols was better than 0.01 and within the target performance of ASTER’s standard emissivity product. Nighttime emissivity retrievals had lower precision (<0.03) likely due to residual atmospheric effects. The water vapor scaling (WVS) atmospheric correction protocol was required to obtain accurate (<0.01) nighttime ASTER emissivity retrievals.

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