Chlorophyll-a retrieval of coastal waters based on in situ hyperspectral data

2009 ◽  
Author(s):  
Wandong Ma ◽  
Ping Shi ◽  
Yuanzhi Zhang ◽  
Qianguo Xing ◽  
Jiakui Tang ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Coastal Waters ◽  
Hyperspectral Data

Estimation of chlorophyll‐a concentration in Lake Tai, China using in situ hyperspectral data

2006 ◽  
Vol 27 (19) ◽  
pp. 4267-4276 ◽  
Author(s):  
H. B. Jiao ◽  
Y. Zha ◽  
J. Gao ◽  
Y. M. Li ◽  
Y. C. Wei ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Hyperspectral Data ◽  
Chlorophyll A Concentration

Estimation of Chlorophyll-a Concentrations in the Pearl River Estuary Using In Situ Hyperspectral Data: A Case Study

2008 ◽  
Vol 42 (4) ◽  
pp. 22-27 ◽  
Author(s):  
Qianguo Xing ◽  
Chuqun Chen ◽  
Heyin Shi ◽  
Ping Shi ◽  
Yuanzhi Zhang
Keyword(s):  
Chlorophyll A ◽  
River Estuary ◽  
Pearl River Estuary ◽  
Second Order ◽  
Hyperspectral Data ◽  
Order Derivative ◽  
Pearl River ◽  
Strong Light ◽  
Turbid Waters

Taking Pearl River Estuary (PRE), China as an example, we explored the potential of in situ hyperspectral data in estimating chlorophyll-a concentrations of turbid waters. Two cruises were conducted on August 21, 2006 and May 18, 2004 to collect the data of water quality and remote sensing reflectance (Rrs). The field surveys showed that: chlorophyll-a concentration ranged from 2.97μg/L to 49.97μg/L, and turbidity 13.6-128.9 NTU. The Rrs spectra were binned to 10 nm resolution, and then processed to be first-order and second-order derivatives. A linear algorithm is developed to estimate chlorophyll-a concentrations based on second-order derivative at 670 nm; its mean relative error of estimation is less than 58%, and the root mean square error is 6.69 μg/L, which is better than other popular algorithms for turbid waters, i.e., the ratio of Rrs at 700 nm and 670 nm. The Case-I algorithm of blue-green band ratio is also proved to be a failed application in PRE, and so does the algorithm of fluorescence line height (FLH), which is questionable for its application in waters with strong light scattering and absorption. All the above work was done without classification of cloud conditions. This suggests that the second-order derivative at 670 nm could be effective for estimation of chlorophyll-a concentrations in turbid waters, especially in situ.

scholarly journals Local, Daily, and Total Bio-Optical Models of Coastal Waters of Manfredonia Gulf Applied to Simulated Data of CHRIS, Landsat TM, MIVIS, MODIS, and PRISMA Sensors for Evaluating the Error

2020 ◽  
Vol 12 (9) ◽  
pp. 1428 ◽  
Author(s):  
Rosa Maria Cavalli
Keyword(s):  
Chlorophyll A ◽  
Coastal Waters ◽  
Organic Material ◽  
Simulated Data ◽  
Local Models ◽  
Imaging Spectrometer ◽  
Mode 2 ◽  
Resolution Imaging ◽  
Remote Data

The spatial–temporal resolution of remote data covers coastal water variability, but this approach offers a lower accuracy than in situ observations. Two of the major error sources occur due to the parameterization of bio-optical models and spectral capability of the remote data. These errors were evaluated by exploiting data acquired in the coastal waters of Manfredonia Gulf. Chlorophyll-a concentrations, absorption of the colored dissolved organic material at 440 nm (aCDOM440nm), and tripton concentrations measured in situ varied between 0.09–1.76 mgm−3, 0.00–0.41 m−1, and 1.97–8.90 gm−3. In accordance with the position and time of in situ surveys, 36 local models, four daily models, and one total bio-optical model were parameterized and validated using in situ data before applying to Compact High-Resolution Imaging Spectrometer (CHRIS) mode 1, CHRIS mode 2, Landsat Thematic Mapper (TM), Multispectral Infrared and Visible Imaging Spectrometer (MIVIS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Precursore Iperspettrale della Missione Applicativa (PRISMA) simulated data. Concentrations retrieved from PRISMA data using local models highlighted the smallest errors. Because tripton abundance is great and tripton absorptions were better resolved than those of chlorophyll-a and colored dissolved organic material (CDOM), tripton concentrations were adequately retrieved from all data using total models, while only local models adequately retrieved chlorophyll-a concentrations and aCDOM440nm from CHRIS mode 1, CHRIS mode 2, MIVIS, and MODIS data. Therefore, the application of local models shows smaller errors than those of daily and total models; however, the capability to resolve the absorption of water constituents and analyze their concentration range can dictate the model choice. Consequently, the integration of more models allows us to overcome the limitations of the data and sensors.

scholarly journals Bio-Optical Characteristics of the Black Sea Coastal Waters near Sevastopol: Assessment of the MODIS and VIIRS Products Accuracy

2021 ◽  
Vol 37 (2) ◽  
Author(s):  
E. Yu. Skorokhod ◽  
T. Ya. Churilova ◽  
T. V. Efimova ◽  
N. A. Moiseeva ◽  
V. V. Suslin ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Black Sea ◽  
Coastal Waters ◽  
Light Absorption ◽  
Ecological Monitoring ◽  
Optically Active ◽  
The Black Sea ◽  
Active Components ◽  
Chlorophyll A Concentration

Purpose. The purpose of the work is to evaluate accuracy of the satellite products for the coastal waters near Sevastopol, reconstructed by the standard algorithms based on the MODIS and VIIRS (installed at the artificial Earth satellites Aqua and Terra, and at Suomi NPP, respectively) data. Methods and Results. In situ sampling was carried out at the station (44°37'26" N and 33°26'05" E) located at a distance of two miles from the Sevastopol Bay. The chlorophyll a concentration was measured by the spectrophotometric method. The spectral light absorption coefficients by optically active components were measured in accordance with the current NASA protocol. The spectroradiometers MODIS and VIIRS Level 2 data with spatial resolution 1 km in nadir around the in situ station (44°37'26"±0°00'32" N and 33°26'05"±0°00'54" E) were used. The satellite products were processed by the SeaDAS 7.5.3 software developed in NASA. The research showed that the standard NASA algorithms being applied to the MODIS and VIIRS data, yielded incorrect values of the optically active components’ content in the Black Sea coastal waters near Sevastopol as compared to the data of in situ measurements in the same region: the satellite-derived “chlorophyll a concentration” was on average 1.6 times lower in spring, and 1.4 times higher in summer; the contribution of phytoplankton pigments to total light absorption at 443 nm was underestimated in 8.7 times; the light absorption by colored detrital organic matter was overestimated in 2.2 times. Conclusions. The NASA standard algorithms are inapplicable to calculating bio-optical indices in the coastal waters of the Black Sea near Sevastopol since they provide incorrect values of the satellite products (Ca-s, aph-s(443) and aCDM-s(443)). Operative ecological monitoring based on satellite data requires development of a regional algorithm taking into account the seawater optical features in the region and in the coastal zone, in particular.

scholarly journals Mapping Chlorophyll-a Concentrations in the Kaštela Bay and Brač Channel Using Ridge Regression and Sentinel-2 Satellite Images

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 3004
Author(s):  
Antonia Ivanda ◽  
Ljiljana Šerić ◽  
Marin Bugarić ◽  
Maja Braović
Keyword(s):  
Remote Sensing ◽  
Chlorophyll A ◽  
Satellite Data ◽  
Coastal Waters ◽  
Optical Parameter ◽  
Data Set ◽  
Chl A ◽  
Sentinel 2

In this paper, we describe a method for the prediction of concentration of chlorophyll-a (Chl-a) from satellite data in the coastal waters of Kaštela Bay and the Brač Channel (our case study areas) in the Republic of Croatia. Chl-a is one of the parameters that indicates water quality and that can be measured by in situ measurements or approximated as an optical parameter with remote sensing. Remote sensing products for monitoring Chl-a are mostly based on the ocean and open sea monitoring and are not accurate for coastal waters. In this paper, we propose a method for remote sensing monitoring that is locally tailored to suit the focused area. This method is based on a data set constructed by merging Sentinel 2 Level-2A satellite data with in situ Chl-a measurements. We augmented the data set horizontally by transforming the original feature set, and vertically by adding synthesized zero measurements for locations without Chl-a. By transforming features, we were able to achieve a sophisticated model that predicts Chl-a from combinations of features representing transformed bands. Multiple Linear Regression equation was derived to calculate Chl-a concentration and evaluated quantitatively and qualitatively. Quantitative evaluation resulted in R2 scores 0.685 and 0.659 for train and test part of data set, respectively. A map of Chl-a of the case study area was generated with our model for the dates of the known incidents of algae blooms. The results that we obtained are discussed in this paper.

scholarly journals Hyper-spectral Remote Sensing of Water Quality Parameters in Lakes: A Case Study of Hyderabad City, Telangana State, India

2017 ◽  
Vol 8 (2) ◽  
pp. 5
Author(s):  
V. Hema Sailaja ◽  
P. Suman Babu ◽  
M. Anji Reddy
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Chlorophyll A ◽  
Secchi Depth ◽  
Quality Parameters ◽  
Water Quality Modeling ◽  
Hyperspectral Data ◽  
Water Quality Parameters ◽  
Model Versus

This paper is a research work intended to present a comprehensive water quality modeling for predicting three water quality parameters (Chlorophyll (a), Turbidity and Secchi Depth) in typical Inland lake environments (Hussain sagar and Umda sagar) using Hyperspectral Remote sensing technique. They are estimated through regression models by combining the field Spectro-radiometer reflectance values with concurrent in situ ground data (Analytical) collected in the study area and correlated and validated with the available Hyperspectral data (Hyperion).  A total of 180 in situ water sample and 900 spectral signatures were analysed during campaigns from 2010 to 2014 study period. The mean values of Chlorophyll-a varied between 6.983mgL<sup>-1</sup> and 24.858mgL<sup>-1</sup>, Turbidity varied between 16.583mgL<sup>-1</sup> and 48.867mgL<sup>-1</sup> and Secchi depth varied between 0.104mgL<sup>-1</sup> and 0.375mgL<sup>-1</sup> over the study period considering the two lakes during pre and post monsoon seasons. The band ratios of the reflected spectra at R670/R710, R710/R740 and R710/R550 are used for the development of the mathematical model of chlorophyll-a, Turbidity and Secchi depth respectively. The trained sets of the pixels extracted from the hyperspectral data for pure spectra are processed for preparing the water quality distribution maps. When subjected to multi-variant statistical tests of significance, the models have yielded satisfactory R<sup>2</sup> values. The model versus in situ analysis results demonstrated R<sup>2</sup>= 0.81% for Chlorophyll-a, R<sup>2</sup>= 0.81%  for Turbidity and R<sup>2</sup>= 0.78% for Secchi depth correlation and that of model versus satellite data exhibited R<sup>2</sup>= 0.60% for Chlorophyll-a, R<sup>2</sup>= 0.66% for Turbidity and R<sup>2</sup>= 0.65 %  for Secchi depth mean efficiency.

scholarly journals Bio-Optical Characteristics of the Black Sea Coastal Waters near Sevastopol: Assessment of the MODIS and VIIRS Products Accuracy

2021 ◽  
Vol 28 (2) ◽  
Author(s):  
E. Yu. Skorokhod ◽  
T. Ya. Churilova ◽  
T. V. Efimova ◽  
N. A. Moiseeva ◽  
V. V. Suslin ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Black Sea ◽  
Coastal Waters ◽  
Light Absorption ◽  
Ecological Monitoring ◽  
Optically Active ◽  
The Black Sea ◽  
Active Components ◽  
Chlorophyll A Concentration

Purpose. The purpose of the work is to evaluate accuracy of the satellite products for the coastal waters near Sevastopol, generated by the standard algorithms based on the MODIS and VIIRS (installed at the artificial Earth satellites Aqua and Terra, and at Suomi NPP, respectively) data. Methods and Results. In situ sampling was carried out at the station (44°37’26" N and 33°26’05" E) located at a distance of two miles from the Sevastopol Bay. The chlorophyll a concentration was measured by the spectrophotometric method. The spectral light absorption coefficients by optically active components were measured in accordance with the current NASA protocol. The spectroradiometers MODIS and VIIRS Level-2 data with spatial resolution 1 km in nadir around the in situ station (44°37’26"±0°00’32" N and 33°26’05"±0°00’54" E) were used. The satellite products were processed by the SeaDAS 7.5.3 software developed in NASA. The research showed that the standard NASA algorithms being applied to the MODIS and VIIRS data, yielded incorrect values of the optically active components’ content in the Black Sea coastal waters near Sevastopol as compared to the data of in situ measurements in the same region: the satellite-derived “chlorophyll a concentration” was on average 1.6 times lower in spring, and 1.4 times higher in summer; the contribution of phytoplankton to total light absorption at 443 nm was underestimated in 8.7 times; the light absorption by colored detrital matter was overestimated in 2.2 times. Conclusions. The NASA standard algorithms are inapplicable to calculating bio-optical indices in the coastal waters of the Black Sea near Sevastopol since they provide incorrect values of the satellite products (Ca-s, aph-s(443) and aCDM-s(443)). Operative ecological monitoring based on satellite data requires development of a regional algorithm taking into account the seawater optical features in the region and in the coastal zone, in particular.

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