Pub Date : 2024-07-04DOI: 10.3389/frsen.2024.1359709
Gaia Gleratti, V. Martinez-Vicente, Elizabeth C. Atwood, Stefan G. H. Simis, Thomas Jackson
Estuarine and coastal transitional waters present a challenge for the interpretation of radiometric remote sensing. Neighbouring water masses have strongly contrasting optical properties at small spatial scales. Adjacency of land adds optical contaminations (adjacency effect) and further complicates satellite use in near-shore waters. In these areas, the lack of in situ observations has been the bottleneck for the characterisation of the uncertainty of satellite products. Radiometric underway measurements (e.g., ferries, ships of opportunity, autonomous vehicles) produce large volumes of in situ observations that can be used for radiometric validation. In this study, we evaluate the performance of the POLYMER atmospheric correction algorithm for the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3 (S3) for the retrieval of remote sensing reflectance Rrs(λ) in the transitional waters of Plymouth, United Kingdom using hyperspectral radiometric underway measurements. We explored the effect of the selection of time window, averaged areas around the in situ measurement and quality control flags into the matchup procedure. We selected matchups only within 1 pixel and ±30 min of the satellite overpass. Accuracy (RMSD) decreased spectrally from blue to red wavelengths (from 0.0015 to 0.00025 sr−1) and bias (Median Percentage Difference) was mostly positive (up to more than 100%) in relation to in situ observations. We segregated the dataset with respect to optical water types and distance to shore. Although no statistically significant difference was observed among those factors on the measures of performance for the reflectance retrieval, RMSD was the most sensitive metric. Our study highlights the potential to use OLCI full resolution imagery in nearshore areas and the need for more in situ data to be collected in the more turbid waters.
{"title":"Validation of full resolution remote sensing reflectance from Sentinel-3 OLCI across optical gradients in moderately turbid transitional waters","authors":"Gaia Gleratti, V. Martinez-Vicente, Elizabeth C. Atwood, Stefan G. H. Simis, Thomas Jackson","doi":"10.3389/frsen.2024.1359709","DOIUrl":"https://doi.org/10.3389/frsen.2024.1359709","url":null,"abstract":"Estuarine and coastal transitional waters present a challenge for the interpretation of radiometric remote sensing. Neighbouring water masses have strongly contrasting optical properties at small spatial scales. Adjacency of land adds optical contaminations (adjacency effect) and further complicates satellite use in near-shore waters. In these areas, the lack of in situ observations has been the bottleneck for the characterisation of the uncertainty of satellite products. Radiometric underway measurements (e.g., ferries, ships of opportunity, autonomous vehicles) produce large volumes of in situ observations that can be used for radiometric validation. In this study, we evaluate the performance of the POLYMER atmospheric correction algorithm for the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3 (S3) for the retrieval of remote sensing reflectance Rrs(λ) in the transitional waters of Plymouth, United Kingdom using hyperspectral radiometric underway measurements. We explored the effect of the selection of time window, averaged areas around the in situ measurement and quality control flags into the matchup procedure. We selected matchups only within 1 pixel and ±30 min of the satellite overpass. Accuracy (RMSD) decreased spectrally from blue to red wavelengths (from 0.0015 to 0.00025 sr−1) and bias (Median Percentage Difference) was mostly positive (up to more than 100%) in relation to in situ observations. We segregated the dataset with respect to optical water types and distance to shore. Although no statistically significant difference was observed among those factors on the measures of performance for the reflectance retrieval, RMSD was the most sensitive metric. Our study highlights the potential to use OLCI full resolution imagery in nearshore areas and the need for more in situ data to be collected in the more turbid waters.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":" 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141679035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-25DOI: 10.3389/frsen.2024.1390687
C. Parcerisas, Elena Schall, Kees te Velde, Dick Botteldooren, P. Devos, E. Debusschere
Studying marine soundscapes by detecting known sound events and quantifying their spatio-temporal patterns can provide ecologically relevant information. However, the exploration of underwater sound data to find and identify possible sound events of interest can be highly time-intensive for human analysts. To speed up this process, we propose a novel methodology that first detects all the potentially relevant acoustic events and then clusters them in an unsupervised way prior to manual revision. We demonstrate its applicability on a short deployment. To detect acoustic events, a deep learning object detection algorithm from computer vision (YOLOv8) is re-trained to detect any (short) acoustic event. This is done by converting the audio to spectrograms using sliding windows longer than the expected sound events of interest. The model detects any event present on that window and provides their time and frequency limits. With this approach, multiple events happening simultaneously can be detected. To further explore the possibilities to limit the human input needed to create the annotations to train the model, we propose an active learning approach to select the most informative audio files in an iterative manner for subsequent manual annotation. The obtained detection models are trained and tested on a dataset from the Belgian Part of the North Sea, and then further evaluated for robustness on a freshwater dataset from major European rivers. The proposed active learning approach outperforms the random selection of files, both in the marine and the freshwater datasets. Once the events are detected, they are converted to an embedded feature space using the BioLingual model, which is trained to classify different (biological) sounds. The obtained representations are then clustered in an unsupervised way, obtaining different sound classes. These classes are then manually revised. This method can be applied to unseen data as a tool to help bioacousticians identify recurrent sounds and save time when studying their spatio-temporal patterns. This reduces the time researchers need to go through long acoustic recordings and allows to conduct a more targeted analysis. It also provides a framework to monitor soundscapes regardless of whether the sound sources are known or not.
{"title":"Machine learning for efficient segregation and labeling of potential biological sounds in long-term underwater recordings","authors":"C. Parcerisas, Elena Schall, Kees te Velde, Dick Botteldooren, P. Devos, E. Debusschere","doi":"10.3389/frsen.2024.1390687","DOIUrl":"https://doi.org/10.3389/frsen.2024.1390687","url":null,"abstract":"Studying marine soundscapes by detecting known sound events and quantifying their spatio-temporal patterns can provide ecologically relevant information. However, the exploration of underwater sound data to find and identify possible sound events of interest can be highly time-intensive for human analysts. To speed up this process, we propose a novel methodology that first detects all the potentially relevant acoustic events and then clusters them in an unsupervised way prior to manual revision. We demonstrate its applicability on a short deployment. To detect acoustic events, a deep learning object detection algorithm from computer vision (YOLOv8) is re-trained to detect any (short) acoustic event. This is done by converting the audio to spectrograms using sliding windows longer than the expected sound events of interest. The model detects any event present on that window and provides their time and frequency limits. With this approach, multiple events happening simultaneously can be detected. To further explore the possibilities to limit the human input needed to create the annotations to train the model, we propose an active learning approach to select the most informative audio files in an iterative manner for subsequent manual annotation. The obtained detection models are trained and tested on a dataset from the Belgian Part of the North Sea, and then further evaluated for robustness on a freshwater dataset from major European rivers. The proposed active learning approach outperforms the random selection of files, both in the marine and the freshwater datasets. Once the events are detected, they are converted to an embedded feature space using the BioLingual model, which is trained to classify different (biological) sounds. The obtained representations are then clustered in an unsupervised way, obtaining different sound classes. These classes are then manually revised. This method can be applied to unseen data as a tool to help bioacousticians identify recurrent sounds and save time when studying their spatio-temporal patterns. This reduces the time researchers need to go through long acoustic recordings and allows to conduct a more targeted analysis. It also provides a framework to monitor soundscapes regardless of whether the sound sources are known or not.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"53 47","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140656478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-10DOI: 10.3389/frsen.2024.1372085
Kevin G. Ruddick, Agnieszka Bialek, V. E. Brando, Pieter De Vis, A. Dogliotti, D. Doxaran, Philippe Goryl, C. Goyens, Joel Kuusk, Daniel Spengler, K. Turpie, Q. Vanhellemont
Satellites are now routinely used for measuring water and land surface reflectance and hence environmentally relevant parameters such as aquatic chlorophyll a concentration and terrestrial vegetation indices. For each satellite mission, radiometric validation is needed at bottom of atmosphere for all spectral bands and covering all typical conditions where the satellite data will be used. Existing networks such as AERONET-OC for water and RadCalNet for land provide vital information for validation, but (AERONET-OC) do not cover all spectral bands or (RadCalNet) do not cover all surface types and viewing angles. In this Perspective Article we discuss recent advances in instrumentation, measurement methods and uncertainty estimation in the field of optical radiometry and put forward the viewpoint that a new network of automated hyperspectral radiometers is needed for multi-mission radiometric validation of water and land surface reflectance. The HYPERNETS federated network concept is described, providing a context for research papers on specific aspects of the network. This network is unique in its common approach to both land and water surfaces. The common aspects and the differences between land and water measurements are explained. Based on early enthusiasm for HYPERNETS data from validation-oriented workshops, it is our viewpoint that this new network of automated hyperspectral radiometers will be useful for multi-mission radiometric validation of water and multi-angle land surface reflectance. The HYPERNETS network has strong synergy with other measurement networks (AERONET, AERONET-OC, RadCalNet, FLUXNET, ICOS, skycam, etc.) and with optional supplementary measurements, e.g., water turbidity and fluorescence, land surface temperature and soil moisture, etc.
{"title":"HYPERNETS: a network of automated hyperspectral radiometers to validate water and land surface reflectance (380–1680 nm) from all satellite missions","authors":"Kevin G. Ruddick, Agnieszka Bialek, V. E. Brando, Pieter De Vis, A. Dogliotti, D. Doxaran, Philippe Goryl, C. Goyens, Joel Kuusk, Daniel Spengler, K. Turpie, Q. Vanhellemont","doi":"10.3389/frsen.2024.1372085","DOIUrl":"https://doi.org/10.3389/frsen.2024.1372085","url":null,"abstract":"Satellites are now routinely used for measuring water and land surface reflectance and hence environmentally relevant parameters such as aquatic chlorophyll a concentration and terrestrial vegetation indices. For each satellite mission, radiometric validation is needed at bottom of atmosphere for all spectral bands and covering all typical conditions where the satellite data will be used. Existing networks such as AERONET-OC for water and RadCalNet for land provide vital information for validation, but (AERONET-OC) do not cover all spectral bands or (RadCalNet) do not cover all surface types and viewing angles. In this Perspective Article we discuss recent advances in instrumentation, measurement methods and uncertainty estimation in the field of optical radiometry and put forward the viewpoint that a new network of automated hyperspectral radiometers is needed for multi-mission radiometric validation of water and land surface reflectance. The HYPERNETS federated network concept is described, providing a context for research papers on specific aspects of the network. This network is unique in its common approach to both land and water surfaces. The common aspects and the differences between land and water measurements are explained. Based on early enthusiasm for HYPERNETS data from validation-oriented workshops, it is our viewpoint that this new network of automated hyperspectral radiometers will be useful for multi-mission radiometric validation of water and multi-angle land surface reflectance. The HYPERNETS network has strong synergy with other measurement networks (AERONET, AERONET-OC, RadCalNet, FLUXNET, ICOS, skycam, etc.) and with optional supplementary measurements, e.g., water turbidity and fluorescence, land surface temperature and soil moisture, etc.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"340 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140719466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-10DOI: 10.3389/frsen.2024.1320454
Viktor Vabson, I. Ansko, Kim Duong, R. Vendt, Joel Kuusk, Kevin G. Ruddick, Agnieszka Bialek, G. Tilstone, J. I. Gossn, Ewa Kwiatkowska
Verifying and validating waterleaving radiance measurements from space for an accurate derivation of Ocean/Water Colour biogeophysical products is based on concurrent high-quality fiducial reference measurements (FRM) carried out on the ground or water body. The FRM principles established by the Committee on Earth Observation Satellites (CEOS) recommend that in situ Ocean Colour radiometers (OCR) have a documented history of SI traceable calibrations including uncertainty budgets. Furthermore, there can be significant differences between calibration and use of the instruments in the field due to differences in operating temperature, angular variation of the light field (especially for irradiance sensors), the intensity of the measured radiation, and spectral variation of the target, among others. Each of these factors may interact with individual properties of the instrument when deployed in the field, and estimation of such uncertainties requires instrument characterization in addition to the absolute radiometric calibration if expanded uncertainties within ±10% (k = 2) are the aim. The FRM4SOC Phase 2 project - funded by the European Commission in the frame of the Copernicus Programme and implemented by EUMETSAT - contributes to these efforts, aiming at developing an operational and sustained network of radiometric measurements of FRM quality. Within FRM4SOC-2, scientists from the Tartu Observatory (TO) of the University of Tartu performed an unprecedented batch of calibrations and characterizations on a set of 37 hyperspectral field radiometers representative of the most used OCR classes within the OC community. The calibrations and characterizations performed include the determination of radiometric responsivity, long-term stability, the accuracy of the spectral scale, non-linearity and accuracy of integration times, spectral stray light, angular response of irradiance sensors in air, dark signal, thermal sensitivity, polarization sensitivity, and signal-to-noise ratio of individual OCRs. Consistent correction of biases and extended uncertainty analysis procedures of in situ data obtained from different instruments and measurement models need to be clearly defined, which is the objective of this paper.
{"title":"Complete characterization of ocean color radiometers","authors":"Viktor Vabson, I. Ansko, Kim Duong, R. Vendt, Joel Kuusk, Kevin G. Ruddick, Agnieszka Bialek, G. Tilstone, J. I. Gossn, Ewa Kwiatkowska","doi":"10.3389/frsen.2024.1320454","DOIUrl":"https://doi.org/10.3389/frsen.2024.1320454","url":null,"abstract":"Verifying and validating waterleaving radiance measurements from space for an accurate derivation of Ocean/Water Colour biogeophysical products is based on concurrent high-quality fiducial reference measurements (FRM) carried out on the ground or water body. The FRM principles established by the Committee on Earth Observation Satellites (CEOS) recommend that in situ Ocean Colour radiometers (OCR) have a documented history of SI traceable calibrations including uncertainty budgets. Furthermore, there can be significant differences between calibration and use of the instruments in the field due to differences in operating temperature, angular variation of the light field (especially for irradiance sensors), the intensity of the measured radiation, and spectral variation of the target, among others. Each of these factors may interact with individual properties of the instrument when deployed in the field, and estimation of such uncertainties requires instrument characterization in addition to the absolute radiometric calibration if expanded uncertainties within ±10% (k = 2) are the aim. The FRM4SOC Phase 2 project - funded by the European Commission in the frame of the Copernicus Programme and implemented by EUMETSAT - contributes to these efforts, aiming at developing an operational and sustained network of radiometric measurements of FRM quality. Within FRM4SOC-2, scientists from the Tartu Observatory (TO) of the University of Tartu performed an unprecedented batch of calibrations and characterizations on a set of 37 hyperspectral field radiometers representative of the most used OCR classes within the OC community. The calibrations and characterizations performed include the determination of radiometric responsivity, long-term stability, the accuracy of the spectral scale, non-linearity and accuracy of integration times, spectral stray light, angular response of irradiance sensors in air, dark signal, thermal sensitivity, polarization sensitivity, and signal-to-noise ratio of individual OCRs. Consistent correction of biases and extended uncertainty analysis procedures of in situ data obtained from different instruments and measurement models need to be clearly defined, which is the objective of this paper.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"217 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140719745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-04DOI: 10.3389/frsen.2024.1305991
C. Legleiter, Lee R. Harrison
Introduction: Information on spatial patterns of water depth in river channels is valuable for numerous applications, but such data can be difficult to obtain via traditional field methods. Ongoing developments in remote sensing technology have enabled various image-based approaches for mapping river bathymetry; this study evaluated the potential to retrieve depth from multispectral images acquired by an uncrewed aircraft system (UAS).Methods: More specifically, we produced depth maps for a 4 km reach of a clear-flowing, relatively shallow river using an established spectrally based algorithm, Optimal Band Ratio Analysis. To assess accuracy, we compared image-derived estimates to direct measurements of water depth. The field data were collected by wading and from a boat equipped with an echo sounder and used to survey cross sections and a longitudinal profile. We partitioned our study area along the Sacramento River, California, USA, into three distinct sub-reaches and acquired a separate image for each one. In addition to the typical, self-contained, per-image depth retrieval workflow, we also explored the possibility of exporting a relationship between depth and reflectance calibrated using data from one site to the other two sub-reaches. Moreover, we evaluated whether sampling configurations progressively more sparse than our full field survey could still provide sufficient calibration data for developing robust depth retrieval models.Results: Our results indicate that under favorable environmental conditions like those observed on the Sacramento River during low flow, accurate, precise depth maps can be derived from images acquired by UAS, not only within a sub-reach but also across multiple, adjacent sub-reaches of the same river.Discussion: Moreover, our findings imply that the level of effort invested in obtaining field data for calibration could be significantly reduced. In aggregate, this investigation suggests that UAS-based remote sensing could facilitate highly efficient, cost-effective, operational mapping of river bathymetry at the reach scale in clear-flowing streams.
{"title":"Evaluating the potential for efficient, UAS-based reach-scale mapping of river channel bathymetry from multispectral images","authors":"C. Legleiter, Lee R. Harrison","doi":"10.3389/frsen.2024.1305991","DOIUrl":"https://doi.org/10.3389/frsen.2024.1305991","url":null,"abstract":"Introduction: Information on spatial patterns of water depth in river channels is valuable for numerous applications, but such data can be difficult to obtain via traditional field methods. Ongoing developments in remote sensing technology have enabled various image-based approaches for mapping river bathymetry; this study evaluated the potential to retrieve depth from multispectral images acquired by an uncrewed aircraft system (UAS).Methods: More specifically, we produced depth maps for a 4 km reach of a clear-flowing, relatively shallow river using an established spectrally based algorithm, Optimal Band Ratio Analysis. To assess accuracy, we compared image-derived estimates to direct measurements of water depth. The field data were collected by wading and from a boat equipped with an echo sounder and used to survey cross sections and a longitudinal profile. We partitioned our study area along the Sacramento River, California, USA, into three distinct sub-reaches and acquired a separate image for each one. In addition to the typical, self-contained, per-image depth retrieval workflow, we also explored the possibility of exporting a relationship between depth and reflectance calibrated using data from one site to the other two sub-reaches. Moreover, we evaluated whether sampling configurations progressively more sparse than our full field survey could still provide sufficient calibration data for developing robust depth retrieval models.Results: Our results indicate that under favorable environmental conditions like those observed on the Sacramento River during low flow, accurate, precise depth maps can be derived from images acquired by UAS, not only within a sub-reach but also across multiple, adjacent sub-reaches of the same river.Discussion: Moreover, our findings imply that the level of effort invested in obtaining field data for calibration could be significantly reduced. In aggregate, this investigation suggests that UAS-based remote sensing could facilitate highly efficient, cost-effective, operational mapping of river bathymetry at the reach scale in clear-flowing streams.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"6 6‐7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140741281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.3389/frsen.2024.1305787
Maximiliano Arena, Paula Pratolongo, H. Loisel, Manh Duy Tran, D. Jorge, Ana Laura Delgado
The site AERONET-OC Bahía Blanca (BB-AERONET-OC) is located at the mouth of the Bahía Blanca Estuary, Argentina (Southwestern Atlantic Ocean), a coastal system defined by its high suspended loads and relatively low colored dissolved organic matter. The typically high turbidity of these waters makes the BB-AERONET-OC distinctive within the AERONET-OC network stations, providing exceptional opportunities not only for the validation of atmospheric correction algorithms but also for the development of regional algorithms for coastal complex waters. A SeaWiFS Photometer Revision for Incident Surface Measurements (SeaPRISM) instrument was deployed in January 2020 in the upper rail of a Mareograph Tower, a 15 m tall structure, located 10 miles away from the coast in optically deep waters. In this work we used the remote sensing reflectance (Rrs) derived from the BB-AERONET-OC measurements along with in situ hyperspectral radiometric data to classify optical water types (OWTs). We assigned each Rrs(λ) spectra to one of the five OWTs defined by Tran et al., and OWTs were further characterized with the concentrations of optically significant components (chlorophyll-a and suspended particulate matter) and inherent optical properties (absorptions of phytoplankton, non-algal particles, and dissolved organic matter), retrieved from water samples obtained simultaneously with radiometric spectra. Based on a match-up exercise with in situ data, different schemes of atmospheric correction methods were applied to Sentinel-3 Ocean and Land Colour Instrument (OLCI) images. The operational product OLCI Level 2 European Space Agency (ESA) standard (hereafter referred to as “Standard Neural Network (NN)”) proves to be the most suitable atmospheric correction algorithm, which was then used to describe spatial patterns and temporal variability of the different OWTs in the region. The BB-AERONET-OC site is located in a sharp transition between estuarine and coastal waters that present contrasting optical conditions: OWT 4 dominates over time (73.72% of the observations), followed by OWT 3 (24.74%) and OWT 5 (1.53%). OWTs 4 and 5 are associated with turbid waters of the Bahía Blanca Estuary, especially OWT 5, which typifies the very turbid waters from the inner estuary, with the particulate load dominated by mineral sediments and detritus. OWT 3, in turn, depicts the eutrophic coastal waters of the inner shelf. The variability of OWTs and the relative contribution of organic and inorganic compounds to the suspended material would be mostly related with the prevalence of northwest winds in the area, which would drive the export of estuarine sediments to the shelf.
{"title":"Optical water characterization and atmospheric correction assessment of estuarine and coastal waters around the AERONET-OC Bahia Blanca","authors":"Maximiliano Arena, Paula Pratolongo, H. Loisel, Manh Duy Tran, D. Jorge, Ana Laura Delgado","doi":"10.3389/frsen.2024.1305787","DOIUrl":"https://doi.org/10.3389/frsen.2024.1305787","url":null,"abstract":"The site AERONET-OC Bahía Blanca (BB-AERONET-OC) is located at the mouth of the Bahía Blanca Estuary, Argentina (Southwestern Atlantic Ocean), a coastal system defined by its high suspended loads and relatively low colored dissolved organic matter. The typically high turbidity of these waters makes the BB-AERONET-OC distinctive within the AERONET-OC network stations, providing exceptional opportunities not only for the validation of atmospheric correction algorithms but also for the development of regional algorithms for coastal complex waters. A SeaWiFS Photometer Revision for Incident Surface Measurements (SeaPRISM) instrument was deployed in January 2020 in the upper rail of a Mareograph Tower, a 15 m tall structure, located 10 miles away from the coast in optically deep waters. In this work we used the remote sensing reflectance (Rrs) derived from the BB-AERONET-OC measurements along with in situ hyperspectral radiometric data to classify optical water types (OWTs). We assigned each Rrs(λ) spectra to one of the five OWTs defined by Tran et al., and OWTs were further characterized with the concentrations of optically significant components (chlorophyll-a and suspended particulate matter) and inherent optical properties (absorptions of phytoplankton, non-algal particles, and dissolved organic matter), retrieved from water samples obtained simultaneously with radiometric spectra. Based on a match-up exercise with in situ data, different schemes of atmospheric correction methods were applied to Sentinel-3 Ocean and Land Colour Instrument (OLCI) images. The operational product OLCI Level 2 European Space Agency (ESA) standard (hereafter referred to as “Standard Neural Network (NN)”) proves to be the most suitable atmospheric correction algorithm, which was then used to describe spatial patterns and temporal variability of the different OWTs in the region. The BB-AERONET-OC site is located in a sharp transition between estuarine and coastal waters that present contrasting optical conditions: OWT 4 dominates over time (73.72% of the observations), followed by OWT 3 (24.74%) and OWT 5 (1.53%). OWTs 4 and 5 are associated with turbid waters of the Bahía Blanca Estuary, especially OWT 5, which typifies the very turbid waters from the inner estuary, with the particulate load dominated by mineral sediments and detritus. OWT 3, in turn, depicts the eutrophic coastal waters of the inner shelf. The variability of OWTs and the relative contribution of organic and inorganic compounds to the suspended material would be mostly related with the prevalence of northwest winds in the area, which would drive the export of estuarine sediments to the shelf.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"72 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139842388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.3389/frsen.2024.1305787
Maximiliano Arena, Paula Pratolongo, H. Loisel, Manh Duy Tran, D. Jorge, Ana Laura Delgado
The site AERONET-OC Bahía Blanca (BB-AERONET-OC) is located at the mouth of the Bahía Blanca Estuary, Argentina (Southwestern Atlantic Ocean), a coastal system defined by its high suspended loads and relatively low colored dissolved organic matter. The typically high turbidity of these waters makes the BB-AERONET-OC distinctive within the AERONET-OC network stations, providing exceptional opportunities not only for the validation of atmospheric correction algorithms but also for the development of regional algorithms for coastal complex waters. A SeaWiFS Photometer Revision for Incident Surface Measurements (SeaPRISM) instrument was deployed in January 2020 in the upper rail of a Mareograph Tower, a 15 m tall structure, located 10 miles away from the coast in optically deep waters. In this work we used the remote sensing reflectance (Rrs) derived from the BB-AERONET-OC measurements along with in situ hyperspectral radiometric data to classify optical water types (OWTs). We assigned each Rrs(λ) spectra to one of the five OWTs defined by Tran et al., and OWTs were further characterized with the concentrations of optically significant components (chlorophyll-a and suspended particulate matter) and inherent optical properties (absorptions of phytoplankton, non-algal particles, and dissolved organic matter), retrieved from water samples obtained simultaneously with radiometric spectra. Based on a match-up exercise with in situ data, different schemes of atmospheric correction methods were applied to Sentinel-3 Ocean and Land Colour Instrument (OLCI) images. The operational product OLCI Level 2 European Space Agency (ESA) standard (hereafter referred to as “Standard Neural Network (NN)”) proves to be the most suitable atmospheric correction algorithm, which was then used to describe spatial patterns and temporal variability of the different OWTs in the region. The BB-AERONET-OC site is located in a sharp transition between estuarine and coastal waters that present contrasting optical conditions: OWT 4 dominates over time (73.72% of the observations), followed by OWT 3 (24.74%) and OWT 5 (1.53%). OWTs 4 and 5 are associated with turbid waters of the Bahía Blanca Estuary, especially OWT 5, which typifies the very turbid waters from the inner estuary, with the particulate load dominated by mineral sediments and detritus. OWT 3, in turn, depicts the eutrophic coastal waters of the inner shelf. The variability of OWTs and the relative contribution of organic and inorganic compounds to the suspended material would be mostly related with the prevalence of northwest winds in the area, which would drive the export of estuarine sediments to the shelf.
{"title":"Optical water characterization and atmospheric correction assessment of estuarine and coastal waters around the AERONET-OC Bahia Blanca","authors":"Maximiliano Arena, Paula Pratolongo, H. Loisel, Manh Duy Tran, D. Jorge, Ana Laura Delgado","doi":"10.3389/frsen.2024.1305787","DOIUrl":"https://doi.org/10.3389/frsen.2024.1305787","url":null,"abstract":"The site AERONET-OC Bahía Blanca (BB-AERONET-OC) is located at the mouth of the Bahía Blanca Estuary, Argentina (Southwestern Atlantic Ocean), a coastal system defined by its high suspended loads and relatively low colored dissolved organic matter. The typically high turbidity of these waters makes the BB-AERONET-OC distinctive within the AERONET-OC network stations, providing exceptional opportunities not only for the validation of atmospheric correction algorithms but also for the development of regional algorithms for coastal complex waters. A SeaWiFS Photometer Revision for Incident Surface Measurements (SeaPRISM) instrument was deployed in January 2020 in the upper rail of a Mareograph Tower, a 15 m tall structure, located 10 miles away from the coast in optically deep waters. In this work we used the remote sensing reflectance (Rrs) derived from the BB-AERONET-OC measurements along with in situ hyperspectral radiometric data to classify optical water types (OWTs). We assigned each Rrs(λ) spectra to one of the five OWTs defined by Tran et al., and OWTs were further characterized with the concentrations of optically significant components (chlorophyll-a and suspended particulate matter) and inherent optical properties (absorptions of phytoplankton, non-algal particles, and dissolved organic matter), retrieved from water samples obtained simultaneously with radiometric spectra. Based on a match-up exercise with in situ data, different schemes of atmospheric correction methods were applied to Sentinel-3 Ocean and Land Colour Instrument (OLCI) images. The operational product OLCI Level 2 European Space Agency (ESA) standard (hereafter referred to as “Standard Neural Network (NN)”) proves to be the most suitable atmospheric correction algorithm, which was then used to describe spatial patterns and temporal variability of the different OWTs in the region. The BB-AERONET-OC site is located in a sharp transition between estuarine and coastal waters that present contrasting optical conditions: OWT 4 dominates over time (73.72% of the observations), followed by OWT 3 (24.74%) and OWT 5 (1.53%). OWTs 4 and 5 are associated with turbid waters of the Bahía Blanca Estuary, especially OWT 5, which typifies the very turbid waters from the inner estuary, with the particulate load dominated by mineral sediments and detritus. OWT 3, in turn, depicts the eutrophic coastal waters of the inner shelf. The variability of OWTs and the relative contribution of organic and inorganic compounds to the suspended material would be mostly related with the prevalence of northwest winds in the area, which would drive the export of estuarine sediments to the shelf.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"33 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139782606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-08DOI: 10.3389/frsen.2023.1290110
D. Doxaran, Boubaker ElKilani, Alexandre Corizzi, C. Goyens
Since 2021, two autonomous HYPERNETS (A new hyperspectral radiometer integrated in automated networks of water and land bidirectional reflectance measurements for satellite validation) stations are operated in contrasted French coastal waters: one in the center of an optically complex coastal lagoon and one at the mouth of a highly turbid estuary. These stations perform predefined sequences of above-water hyperspectral radiometric measurements following a strict viewing geometry. The data recorded by the ®HYPSTAR radiometer is automatically transmitted to servers for quality-controls then computation of the water-leaving reflectance signal. Numerous matchups were identified with high (Sentinel2-MSI and Landsat8/9-OLI) and medium (Sentinel3-OLCI and Aqua-MODIS) spatial resolution satellite data and are analyzed to assess the performance of different atmospheric correction algorithms (Sen2Cor, ACOLITE, POLYMER, iCOR, C2RCC, GRS, BPAC, NIR-SWIR). Considering the specifications of each site (i.e., spatial and temporal variations of water optical properties), optimized matchup protocols are first established to guaranty high quality comparisons between satellite products and field measurements. The matchup results highlight the failure and limits of several atmospheric correction algorithms in complex/turbid coastal waters. The importance of accurate sun glint corrections in low to moderately-turbid waters (with the good performances of POLYMER, C2RCC and GRS processors, e.g., errors (MAPE) lower than 25% in the green spectral region) is also shown while the use of dark targets and spectral fitting to estimate the aerosol contributions is proved to be the most accurate method in the case of turbid waters (with Sen2Cor and ACOLITE errors (MAPE) lower than 20% in the visible and near-infrared spectral regions).
{"title":"Validation of satellite-derived water-leaving reflectance in contrasted French coastal waters based on HYPERNETS field measurements","authors":"D. Doxaran, Boubaker ElKilani, Alexandre Corizzi, C. Goyens","doi":"10.3389/frsen.2023.1290110","DOIUrl":"https://doi.org/10.3389/frsen.2023.1290110","url":null,"abstract":"Since 2021, two autonomous HYPERNETS (A new hyperspectral radiometer integrated in automated networks of water and land bidirectional reflectance measurements for satellite validation) stations are operated in contrasted French coastal waters: one in the center of an optically complex coastal lagoon and one at the mouth of a highly turbid estuary. These stations perform predefined sequences of above-water hyperspectral radiometric measurements following a strict viewing geometry. The data recorded by the ®HYPSTAR radiometer is automatically transmitted to servers for quality-controls then computation of the water-leaving reflectance signal. Numerous matchups were identified with high (Sentinel2-MSI and Landsat8/9-OLI) and medium (Sentinel3-OLCI and Aqua-MODIS) spatial resolution satellite data and are analyzed to assess the performance of different atmospheric correction algorithms (Sen2Cor, ACOLITE, POLYMER, iCOR, C2RCC, GRS, BPAC, NIR-SWIR). Considering the specifications of each site (i.e., spatial and temporal variations of water optical properties), optimized matchup protocols are first established to guaranty high quality comparisons between satellite products and field measurements. The matchup results highlight the failure and limits of several atmospheric correction algorithms in complex/turbid coastal waters. The importance of accurate sun glint corrections in low to moderately-turbid waters (with the good performances of POLYMER, C2RCC and GRS processors, e.g., errors (MAPE) lower than 25% in the green spectral region) is also shown while the use of dark targets and spectral fitting to estimate the aerosol contributions is proved to be the most accurate method in the case of turbid waters (with Sen2Cor and ACOLITE errors (MAPE) lower than 20% in the visible and near-infrared spectral regions).","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"166 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139852542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-08DOI: 10.3389/frsen.2023.1290110
D. Doxaran, Boubaker ElKilani, Alexandre Corizzi, C. Goyens
Since 2021, two autonomous HYPERNETS (A new hyperspectral radiometer integrated in automated networks of water and land bidirectional reflectance measurements for satellite validation) stations are operated in contrasted French coastal waters: one in the center of an optically complex coastal lagoon and one at the mouth of a highly turbid estuary. These stations perform predefined sequences of above-water hyperspectral radiometric measurements following a strict viewing geometry. The data recorded by the ®HYPSTAR radiometer is automatically transmitted to servers for quality-controls then computation of the water-leaving reflectance signal. Numerous matchups were identified with high (Sentinel2-MSI and Landsat8/9-OLI) and medium (Sentinel3-OLCI and Aqua-MODIS) spatial resolution satellite data and are analyzed to assess the performance of different atmospheric correction algorithms (Sen2Cor, ACOLITE, POLYMER, iCOR, C2RCC, GRS, BPAC, NIR-SWIR). Considering the specifications of each site (i.e., spatial and temporal variations of water optical properties), optimized matchup protocols are first established to guaranty high quality comparisons between satellite products and field measurements. The matchup results highlight the failure and limits of several atmospheric correction algorithms in complex/turbid coastal waters. The importance of accurate sun glint corrections in low to moderately-turbid waters (with the good performances of POLYMER, C2RCC and GRS processors, e.g., errors (MAPE) lower than 25% in the green spectral region) is also shown while the use of dark targets and spectral fitting to estimate the aerosol contributions is proved to be the most accurate method in the case of turbid waters (with Sen2Cor and ACOLITE errors (MAPE) lower than 20% in the visible and near-infrared spectral regions).
{"title":"Validation of satellite-derived water-leaving reflectance in contrasted French coastal waters based on HYPERNETS field measurements","authors":"D. Doxaran, Boubaker ElKilani, Alexandre Corizzi, C. Goyens","doi":"10.3389/frsen.2023.1290110","DOIUrl":"https://doi.org/10.3389/frsen.2023.1290110","url":null,"abstract":"Since 2021, two autonomous HYPERNETS (A new hyperspectral radiometer integrated in automated networks of water and land bidirectional reflectance measurements for satellite validation) stations are operated in contrasted French coastal waters: one in the center of an optically complex coastal lagoon and one at the mouth of a highly turbid estuary. These stations perform predefined sequences of above-water hyperspectral radiometric measurements following a strict viewing geometry. The data recorded by the ®HYPSTAR radiometer is automatically transmitted to servers for quality-controls then computation of the water-leaving reflectance signal. Numerous matchups were identified with high (Sentinel2-MSI and Landsat8/9-OLI) and medium (Sentinel3-OLCI and Aqua-MODIS) spatial resolution satellite data and are analyzed to assess the performance of different atmospheric correction algorithms (Sen2Cor, ACOLITE, POLYMER, iCOR, C2RCC, GRS, BPAC, NIR-SWIR). Considering the specifications of each site (i.e., spatial and temporal variations of water optical properties), optimized matchup protocols are first established to guaranty high quality comparisons between satellite products and field measurements. The matchup results highlight the failure and limits of several atmospheric correction algorithms in complex/turbid coastal waters. The importance of accurate sun glint corrections in low to moderately-turbid waters (with the good performances of POLYMER, C2RCC and GRS processors, e.g., errors (MAPE) lower than 25% in the green spectral region) is also shown while the use of dark targets and spectral fitting to estimate the aerosol contributions is proved to be the most accurate method in the case of turbid waters (with Sen2Cor and ACOLITE errors (MAPE) lower than 20% in the visible and near-infrared spectral regions).","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":" 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139792731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-05DOI: 10.3389/frsen.2023.1321621
E. Zubko, M. Zheltobryukhov, E. Chornaya, Konstantin A. Shmirko, Vladimir V. Lisitsa, Andrey N. Pavlov, A. Kochergin, Gennady Kornienko, G. Videen
Unpolarized sunlight is scattered by aerosols acquiring partial linear polarization. By aiming a ground-based detector vertically upward, it can record the polarimetric response of aerosols that are illuminated by the Sun. As the Sun sets, a portion of the sky is shadowed and the polarimetric response of the aerosols in the unshadowed region can be measured. This provides a means of scanning different portions of the atmospheric column with time. By comparing the measured polarimetric response with that of model agglomerated debris particles we can place constraints on the sizes and chemical composition of the aerosols in different portions of this column. We conducted a survey over 24 different epochs from April 2021 to December 2022, consisting of approximately 600 measurements of polarization of the atmosphere in twilight at the Ussuriysk Astrophysical Observatory. We found that most of the measurements correspond with water-ice particles or dust. However, on some occasions organic carbon dominated the measurements. These epochs correspond with increased fire seats in the region.
{"title":"Characterizing atmospheric aerosols using polarimetry and shadow hiding","authors":"E. Zubko, M. Zheltobryukhov, E. Chornaya, Konstantin A. Shmirko, Vladimir V. Lisitsa, Andrey N. Pavlov, A. Kochergin, Gennady Kornienko, G. Videen","doi":"10.3389/frsen.2023.1321621","DOIUrl":"https://doi.org/10.3389/frsen.2023.1321621","url":null,"abstract":"Unpolarized sunlight is scattered by aerosols acquiring partial linear polarization. By aiming a ground-based detector vertically upward, it can record the polarimetric response of aerosols that are illuminated by the Sun. As the Sun sets, a portion of the sky is shadowed and the polarimetric response of the aerosols in the unshadowed region can be measured. This provides a means of scanning different portions of the atmospheric column with time. By comparing the measured polarimetric response with that of model agglomerated debris particles we can place constraints on the sizes and chemical composition of the aerosols in different portions of this column. We conducted a survey over 24 different epochs from April 2021 to December 2022, consisting of approximately 600 measurements of polarization of the atmosphere in twilight at the Ussuriysk Astrophysical Observatory. We found that most of the measurements correspond with water-ice particles or dust. However, on some occasions organic carbon dominated the measurements. These epochs correspond with increased fire seats in the region.","PeriodicalId":198378,"journal":{"name":"Frontiers in Remote Sensing","volume":"11 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139381963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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