Improved estimates of bio-optical parameters in optically complex water using hyperspectral remote sensing data. Issue 8 (18th April 2021)
- Record Type:
- Journal Article
- Title:
- Improved estimates of bio-optical parameters in optically complex water using hyperspectral remote sensing data. Issue 8 (18th April 2021)
- Main Title:
- Improved estimates of bio-optical parameters in optically complex water using hyperspectral remote sensing data
- Authors:
- Ali, Syed Moosa
Gupta, Anurag
Raman, Mini
Sahay, Arvind
Motwani, Gunjan
Muduli, Pradipta R.
Krishna, Aswathy Vijaya
Tirkey, Anima - Abstract:
- ABSTRACT: In this study, bio-optical parameters were derived from hyperspectral data of optically complex waters using spectrum matching technique (SMT). Models for inherent optical properties (IOPs) of the water column were tuned using in-situ dataset from the study area (i.e., Chilika lagoon). Constructed IOPs were used to simulate remote sensing reflectance ( R r s ) spectra at 60 wavelengths (equally spaced between 400 and 700 nm) using radiative transfer solution provided by Hydrolight-Ecolight software (HE53). Results of the simulation were stored as a R r s – IOP look up table (LUT). To check the accuracy, in-situ measured R r s were compared with those from the LUT. Retrieved values of two bio-optical parameters i.e., chlorophyll-a concentration (Chl- a ) and coloured dissolved organic matter (CDOM)+Detritus absorption coefficient at 440 nm ( a d g ( 440 ) ) were compared with corresponding in-situ measurements to get good statistical match. Coefficient of determination ( R 2 ) and root mean squared error (RMSE) were 0.80 and 2.66 mg m − 3 respectively for Chl- a, whereas 0.77 and 0.23 m − 1 respectively for a d g ( 440 ) . These parameters were also retrieved using two commonly used semi-analytical inversion algorithms (SAA)- (a) Linear matrix inversion (LMI) and (b) Garver-Siegal Maritorena (GSM). Both the SAA showed poor performance. R 2 for Chl- a from GSM and LMI were 0.13 and 0.41, respectively, with RMSE of 6.85 mg m − 3 and 4.82 mg m − 3 respectively.ABSTRACT: In this study, bio-optical parameters were derived from hyperspectral data of optically complex waters using spectrum matching technique (SMT). Models for inherent optical properties (IOPs) of the water column were tuned using in-situ dataset from the study area (i.e., Chilika lagoon). Constructed IOPs were used to simulate remote sensing reflectance ( R r s ) spectra at 60 wavelengths (equally spaced between 400 and 700 nm) using radiative transfer solution provided by Hydrolight-Ecolight software (HE53). Results of the simulation were stored as a R r s – IOP look up table (LUT). To check the accuracy, in-situ measured R r s were compared with those from the LUT. Retrieved values of two bio-optical parameters i.e., chlorophyll-a concentration (Chl- a ) and coloured dissolved organic matter (CDOM)+Detritus absorption coefficient at 440 nm ( a d g ( 440 ) ) were compared with corresponding in-situ measurements to get good statistical match. Coefficient of determination ( R 2 ) and root mean squared error (RMSE) were 0.80 and 2.66 mg m − 3 respectively for Chl- a, whereas 0.77 and 0.23 m − 1 respectively for a d g ( 440 ) . These parameters were also retrieved using two commonly used semi-analytical inversion algorithms (SAA)- (a) Linear matrix inversion (LMI) and (b) Garver-Siegal Maritorena (GSM). Both the SAA showed poor performance. R 2 for Chl- a from GSM and LMI were 0.13 and 0.41, respectively, with RMSE of 6.85 mg m − 3 and 4.82 mg m − 3 respectively. For a d g ( 440 ), the value of R 2 from GSM and LMI were 0.87 and 0.71, respectively, but with a high RMSE of 0.91 m − 1 and 0.81 m − 1 respectively. SMT was applied to airborne hyperspectral AVIRIS-NG (Airborne Visible/Infrared Imaging Spectrometer Next Generation) dataset of Chilika lake to derive pixel-wise chlorophyll-a concentration and the magnitude of CDOM+Detritus absorption coefficient at 440 nm ( a d g ( 440 ) ). Spatial variability of these parameters in its different domains (i.e. Northern-, Central- and Southern-region of the lake) have been addressed. … (more)
- Is Part Of:
- International journal of remote sensing. Volume 42:Issue 8(2021)
- Journal:
- International journal of remote sensing
- Issue:
- Volume 42:Issue 8(2021)
- Issue Display:
- Volume 42, Issue 8 (2021)
- Year:
- 2021
- Volume:
- 42
- Issue:
- 8
- Issue Sort Value:
- 2021-0042-0008-0000
- Page Start:
- 3056
- Page End:
- 3073
- Publication Date:
- 2021-04-18
- Subjects:
- Remote sensing -- Periodicals
Télédétection -- Périodiques
621.3678 - Journal URLs:
- http://www.tandfonline.com/toc/tres20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/01431161.2020.1865585 ↗
- Languages:
- English
- ISSNs:
- 0143-1161
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.528000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 22042.xml