An Atmospheric Correction Algorithm for Remote Sensing of Bright Coastal Waters Using MODIS Land and Ocean Channels in the Solar Spectral Region

2007 ◽  
Vol 45 (6) ◽  
pp. 1835-1843 ◽  
Author(s):  
Bo-Cai Gao ◽  
Marcos J. Montes ◽  
Rong-Rong Li ◽  
Heidi Melita Dierssen ◽  
Curtiss O. Davis
Keyword(s):  
Remote Sensing ◽  
Coastal Waters ◽  
Spectral Region ◽  
Atmospheric Correction ◽  
Correction Algorithm

scholarly journals Assessment of Polymer Atmospheric Correction Algorithm for Hyperspectral Remote Sensing Imagery over Coastal Waters

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4125
Author(s):  
Mariana A. Soppa ◽  
Brenner Silva ◽  
François Steinmetz ◽  
Darryl Keith ◽  
Daniel Scheffler ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Coastal Waters ◽  
Spectral Region ◽  
Atmospheric Correction ◽  
Hyperspectral Remote Sensing ◽  
Water Colour ◽  
Percentage Difference ◽  
Green Spectral Region

Spaceborne imaging spectroscopy, also called hyperspectral remote sensing, has shown huge potential to improve current water colour retrievals and, thereby, the monitoring of inland and coastal water ecosystems. However, the quality of water colour retrievals strongly depends on successful removal of the atmospheric/surface contributions to the radiance measured by satellite sensors. Atmospheric correction (AC) algorithms are specially designed to handle these effects, but are challenged by the hundreds of narrow spectral bands obtained by hyperspectral sensors. In this paper, we investigate the performance of Polymer AC for hyperspectral remote sensing over coastal waters. Polymer is, in nature, a hyperspectral algorithm that has been mostly applied to multispectral satellite data to date. Polymer was applied to data from the Hyperspectral Imager for the Coastal Ocean (HICO), validated against in situ multispectral (AERONET-OC) and hyperspectral radiometric measurements, and its performance was compared against that of the hyperspectral version of NASA’s standard AC algorithm, L2gen. The match-up analysis demonstrated very good performance of Polymer in the green spectral region. The mean absolute percentage difference across all the visible bands varied between 16% (green spectral region) and 66% (red spectral region). Compared with L2gen, Polymer remote sensing reflectances presented lower uncertainties, greater data coverage, and higher spectral similarity to in situ measurements. These results demonstrate the potential of Polymer to perform AC on hyperspectral satellite data over coastal waters, thus supporting its application in current and future hyperspectral satellite missions.

scholarly journals Assessing an Atmospheric Correction Algorithm for Time Series of Satellite-Based Water-Leaving Reflectance Using Match-Up Sites in Australian Coastal Waters

2021 ◽  
Vol 13 (10) ◽  
pp. 1927
Author(s):  
Fuqin Li ◽  
David Jupp ◽  
Thomas Schroeder ◽  
Stephen Sagar ◽  
Joshua Sixsmith ◽  
...  
Keyword(s):  
Coastal Waters ◽  
Atmospheric Correction ◽  
Correction Method ◽  
In Situ Measurements ◽  
Landsat 8 ◽  
Correction Algorithm ◽  
Simple Method ◽  
North East ◽  
The Impact

An atmospheric correction algorithm for medium-resolution satellite data over general water surfaces (open/coastal, estuarine and inland waters) has been assessed in Australian coastal waters. In situ measurements at four match-up sites were used with 21 Landsat 8 images acquired between 2014 and 2017. Three aerosol sources (AERONET, MODIS ocean aerosol and climatology) were used to test the impact of the selection of aerosol optical depth (AOD) and Ångström coefficient on the retrieved accuracy. The initial results showed that the satellite-derived water-leaving reflectance can have good agreement with the in situ measurements, provided that the sun glint is handled effectively. Although the AERONET aerosol data performed best, the contemporary satellite-derived aerosol information from MODIS or an aerosol climatology could also be as effective, and should be assessed with further in situ measurements. Two sun glint correction strategies were assessed for their ability to remove the glint bias. The most successful one used the average of two shortwave infrared (SWIR) bands to represent sun glint and subtracted it from each band. Using this sun glint correction method, the mean all-band error of the retrieved water-leaving reflectance at the Lucinda Jetty Coastal Observatory (LJCO) in north east Australia was close to 4% and unbiased over 14 acquisitions. A persistent bias in the other strategy was likely due to the sky radiance being non-uniform for the selected images. In regard to future options for an operational sun glint correction, the simple method may be sufficient for clear skies until a physically based method has been established.

scholarly journals Using Optical Water Types to Monitor Changes in Optically Complex Inland and Coastal Waters

2019 ◽  
Vol 11 (19) ◽  
pp. 2297 ◽  
Author(s):  
Kristi Uudeberg ◽  
Ilmar Ansko ◽  
Getter Põru ◽  
Ave Ansper ◽  
Anu Reinart
Keyword(s):  
Remote Sensing ◽  
Coastal Waters ◽  
Atmospheric Correction ◽  
Suspended Sediments ◽  
Reflectance Spectra ◽  
Water Type ◽  
Colored Dissolved Organic Matter ◽  
Water Color ◽  
Sentinel 2

The European Space Agency’s Copernicus satellites Sentinel-2 and Sentinel-3 provide observations with high spectral, spatial, and temporal resolution which can be used to monitor inland and coastal waters. Such waters are optically complex, and the water color may vary from completely clear to dark brown. The main factors influencing water color are colored dissolved organic matter, phytoplankton, and suspended sediments. Recently, there has been a growing interest in the use of the optical water type (OWT) classification in the remote sensing of ocean color. Such classification helps to clarify relationships between different properties inside a certain class and quantify variation between classes. In this study, we present a new OWT classification based on the in situ measurements of reflectance spectra for boreal region lakes and coastal areas without extreme optical conditions. This classification divides waters into five OWT (Clear, Moderate, Turbid, Very Turbid, and Brown) and shows that different OWTs have different remote sensing reflectance spectra and that each OWT is associated with a specific bio-optical condition. Developed OWTs are distinguishable by both the MultiSpectral Instrument (MSI) and the Ocean and Land Color Instrument (OLCI) sensors, and the accuracy of the OWT assignment was 95% for both the MSI and OLCI bands. To determine OWT from MSI images, we tested different atmospheric correction (AC) processors, namely ACOLITE, C2RCC, POLYMER, and Sen2Cor and for OLCI images, we tested AC processors ALTNNA, C2RCC, and L2. The C2RCC AC processor was the most accurate and reliable for use with MSI and OLCI images to estimate OWTs.

An Antisubmarine Detection Method Using IR Spectrometer in Ocean Remote Sensing

2012 ◽  
Vol 490-495 ◽  
pp. 1337-1341
Author(s):  
Zhi Wu Ke ◽  
Rui Yu ◽  
Rui Xiang ◽  
Ke Long Zhang ◽  
Yong Ma
Keyword(s):  
Remote Sensing ◽  
Ir Spectrum ◽  
Detection Method ◽  
Sea Water ◽  
Atmospheric Correction ◽  
Correction Algorithm ◽  
Ir Imaging ◽  
Detection Approach ◽  
Infrared Spectrometer ◽  
Ocean Remote Sensing

According to the reduction of submarine noise level, Non-acoustics antisubmarine detection method becomes more important for the ocean remote sensing, especially infrared (IR) imaging remote sensing detection method. Conventional IR imaging remote sensing antisubmarine detection is more difficult because modern advanced submarine IR thermal radiance is not obvious. In this paper, our main purpose is to develop the advanced IR imaging remote sensing antisubmarine detection approach by using infrared spectrometer. The IR spectrum information derived from IR spectrometer in sea water and then retrieves the water-leaving spectra by the standard atmospheric correction algorithm. The submarine is detected by analyzing the water-leaving spectrum information. Results of comparisons with conventional IR imaging remote sensing antisubmarine detection, the modified approach is available to estimate the spectrum properties and effective to antisubmarine detection in sea water

scholarly journals Atmospheric Correction of Airborne Hyperspectral CASI Data Using Polymer, 6S and FLAASH

2021 ◽  
Vol 13 (24) ◽  
pp. 5062
Author(s):  
Mengmeng Yang ◽  
Yong Hu ◽  
Hongzhen Tian ◽  
Faisal Ahmed Khan ◽  
Qingping Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Coastal Waters ◽  
Atmospheric Correction ◽  
Hyperspectral Data ◽  
Spectral Shape ◽  
Time Difference ◽  
The Other ◽  
Atmospheric Effects ◽  
Aerosol Scattering ◽  
Correction Technique

Airborne hyperspectral data play an important role in remote sensing of coastal waters. However, before their application, atmospheric correction is required to remove or reduce the atmospheric effects caused by molecular and aerosol scattering and absorption. In this study, we first processed airborne hyperspectral CASI-1500 data acquired on 4 May 2019 over the Uljin coast of Korea with Polymer and then compared the performance with the other two widely used atmospheric correction approaches, i.e., 6S and FLAASH, to determine the most appropriate correction technique for CASI-1500 data in coastal waters. Our results show the superiority of Polymer over 6S and FLAASH in deriving the Rrs spectral shape and magnitude. The performance of Polymer was further evaluated by comparing CASI-1500 Rrs data with those obtained from the MODIS-Aqua sensor on 3 May 2019 and processed using Polymer. The spectral shapes of the derived Rrs from CASI-1500 and MODIS-Aqua matched well, but the magnitude of CASI-1500 Rrs was approximately 0.8 times lower than MODIS Rrs. The possible reasons for this difference were time difference (1 day) between CASI-1500 and MODIS data, higher land adjacency effect for MODIS-Aqua than for CASI-1500, and possible errors in MODIS Rrs from Polymer.

scholarly journals Evolution of Ocean Color Atmospheric Correction: 1970–2005

2021 ◽  
Vol 13 (24) ◽  
pp. 5051
Author(s):  
Howard R. Gordon
Keyword(s):  
Coastal Waters ◽  
Spectral Region ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Visible Region ◽  
Coastal Areas ◽  
Open Ocean ◽  
Water Properties ◽  
Blue Spectral Region ◽  
Global Data

Retrieval of water properties from satellite-borne imagers viewing oceans and coastal areas in the visible region of the spectrum requires removing the effect of the atmosphere, which contributes approximately 80–90% of the measured radiance over the open ocean in the blue spectral region. The Gordon and Wang algorithm originally developed for SeaWiFS (and used with other NASA sensors, e.g., MODIS) forms the basis for many atmospheric removal (correction) procedures. It was developed for application to imagery obtained over the open ocean (Case 1 waters), where the aerosol is usually non-absorbing, and is used operationally to process global data from SeaWiFS, MODIS and VIIRS. Here, I trace the evolution of this algorithm from early NASA aircraft experiments through the CZCS, OCTS, SeaWiFs, MERIS, and finally the MODIS sensors. Strategies to extend the algorithm to situations where the aerosol is strongly absorbing are examined. Its application to sensors with additional and unique capabilities is sketched. Problems associated with atmospheric correction in coastal waters are described.

Sign in / Sign up

Export Citation Format

Share Document