BEPERS-88: Sea Ice Remote Sensing With Synthetic Aperture Radar in the Baltic Sea

Eos ◽  
1989 ◽  
Vol 70 (28) ◽  
pp. 698 ◽  
Author(s):  
M. Leppäranta ◽  
T. Thompson
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Baltic Sea ◽  
Synthetic Aperture ◽  
The Baltic Sea ◽  
The Baltic ◽  
Aperture Radar

Comparison of the main sea ice parameters received from satellite measurements and based on numerical simulation for the Baltic Sea region

2020 ◽  
Author(s):  
Jaromir Jakacki ◽  
Maciej Muzyka ◽  
Marta Konik ◽  
Anna Przyborska ◽  
Jan Andrzejewski
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Baltic Sea ◽  
Melting Time ◽  
Ice Thickness ◽  
Satellite Measurements ◽  
The Baltic Sea ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
The Baltic

<p>During the last decades remote sensing observations as well as modelling tools has been developed and become key elements of oceanographic research. One of the main advantages of both tools is a possibility of measuring large-scale areas.</p><p>The remote sensing measurements deliver only snapshots of the ice situation with no information about backgroundconditions. Moreover, providing picture of the whole area requires sometimes combining various datasets that increases uncertainties.  Modelling simulations provide full history of external conditions, but they also introduce errors that are the result of parameterizations. Also, an inaccuracy provided by forcing fields at the top and bottom boundaries are accumulated in the model.</p><p>In this work sea ice parameters such as sea ice concentration, thickness and volume obtained from both – satellite measurements and modelling has been compared. Numerical simulations were performed using standalone Community Ice Code (CICE) model (v. 6.0). It is a descendant of the basin scale dynamic-thermodynamic and thickness distribution sea ice model. The model is well known by scientific community and was widely used in a global as well as regional research, even operationally. The satellite derived ice thickness products were based on the C band HH-polarized SAR measurements originating from the satellites Sentinel-1 and RADARSAT-2. The sea ice concentration maps contain also visual and infrared information from MODIS and NOAA.</p><p>The ice extent, thickness and volume were compared in several regions within the Baltic Sea.  Seasonal changes were analyzed with a particular attention to ice formation and melting time. The sea ice extent datasets were compatible. Inconsistencies were observed for the sea ice thickness delivered by satellite measurements, especially during the ice melt. The work presents direction for ignoring satellite data with an error related to ice melting that allows for excluding erroneous satellite maps and obtain reliable intercalibration.</p><p> </p><p>This work was partly funded by Polish National Science Centre, project number 2017/25/B/ST10/00159</p>

scholarly journals BEPERS pilot study: an experiment with X-band synthetic aperture radar over Baltic Sea ice

1992 ◽  
Vol 38 (128) ◽  
pp. 23-35 ◽  
Author(s):  
Matti Leppäranta ◽  
Rlsto Kuittinen ◽  
Jan Askne
Keyword(s):  
Pilot Study ◽  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Baltic Sea ◽  
Open Water ◽  
Synthetic Aperture ◽  
Speckle Reduction ◽  
X Band ◽  
Sar Imagery ◽  
Aperture Radar

Abstract Remote-sensing methods are the primary ones used for ice mapping in the Baltic Sea. A major methodological improvement is now being introduced by satellite radars due to their weather independency and high resolution. To learn how to use ERS-1 synthetic aperture radar (SAR) data, an extensive field programme BEPERS (Bothnian Experiment in Preparation for ERS-1) with airborne SARs has been arranged. The BEPERS pilot study was undertaken in 1987 using the French VARAN-S X-band SAR. The SAR was flown on 1 day over four study areas of size approximately 10 km x 50 km, and intensive validation observations were made. The data were most useful for the education they provided on how to work with SAR in sea-ice mapping. They have been used for developing SAR image-analysis methods, back-scatter modelling investigations and geophysical validation of SAR imagery. Cleaning-up of images consisted of speckle reduction and segmentation. Back-scatter characteristics of undeformed ice and ridges were examined. Ice-type classification was based on the box-classification method. Eight ice types were defined but basically only two types, undeformed ice/open water and deformed ice, could be discriminated. Two basic problems of high practical importance remained: how to discriminate between (1) open water and undeformed ice, and (2) ridged ice and brash ice. The data further showed illustrative examples of SAR imagery over sea ice.

scholarly journals Estimation of degree of sea ice ridging in the Bay of Bothnia based on geolocated photon heights from ICESat-2

2021 ◽  
Vol 15 (6) ◽  
pp. 2511-2529
Author(s):  
Renée Mie Fredensborg Hansen ◽  
Eero Rinne ◽  
Sinéad Louise Farrell ◽  
Henriette Skourup
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Synthetic Aperture ◽  
The Baltic Sea ◽  
Ice Cloud ◽  
In Situ Observations ◽  
The Difference ◽  
The Baltic ◽  
Time Critical

Abstract. We present a comparison of Ice, Cloud and land Elevation Satellite-2 (ICESat-2) geolocated photon heights and operational ice charts from the Finnish Ice Service in the Bay of Bothnia in spring 2019. We show that ICESat-2 (IS2) retrievals from ice areas with different ridging characteristics, more precisely the degree of ice ridging (DIR), differ significantly. DIR is a particularly useful parameter for ice navigators, as it provides information on how difficult it is to navigate through an area based on e.g. sail heights and distribution of sea ice ridges. DIR estimates are included in ice charts of the Baltic Sea and are based primarily on in situ observations from an active icebreaker fleet. We show that DIR may potentially be estimated from IS2. We also present a comparison of IS2 measurements and Sentinel-1 synthetic aperture radar frames, discussing several individual cases of IS2 photon elevation behaviour over Baltic sea ice. We suggest that IS2 data can be of benefit to international ice services, especially if a time-critical photon height product were to be made available. Furthermore, we show that the difference between highest and mean photon elevations (elevation anomalies) of IS2 correspond to expected ridge sail heights in our study area. Our study is one of the first steps in creating sea ice applications beyond the traditional goal of freeboard and thickness retrieval for IS2.

scholarly journals BEPERS pilot study: an experiment with X-band synthetic aperture radar over Baltic Sea ice

1992 ◽  
Vol 38 (128) ◽  
pp. 23-35
Author(s):  
Matti Leppäranta ◽  
Rlsto Kuittinen ◽  
Jan Askne
Keyword(s):  
Pilot Study ◽  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Baltic Sea ◽  
Open Water ◽  
Synthetic Aperture ◽  
Speckle Reduction ◽  
X Band ◽  
Sar Imagery ◽  
Aperture Radar

AbstractRemote-sensing methods are the primary ones used for ice mapping in the Baltic Sea. A major methodological improvement is now being introduced by satellite radars due to their weather independency and high resolution. To learn how to use ERS-1 synthetic aperture radar (SAR) data, an extensive field programme BEPERS (Bothnian Experiment in Preparation for ERS-1) with airborne SARs has been arranged. The BEPERS pilot study was undertaken in 1987 using the French VARAN-S X-band SAR. The SAR was flown on 1 day over four study areas of size approximately 10 km x 50 km, and intensive validation observations were made. The data were most useful for the education they provided on how to work with SAR in sea-ice mapping. They have been used for developing SAR image-analysis methods, back-scatter modelling investigations and geophysical validation of SAR imagery. Cleaning-up of images consisted of speckle reduction and segmentation. Back-scatter characteristics of undeformed ice and ridges were examined. Ice-type classification was based on the box-classification method. Eight ice types were defined but basically only two types, undeformed ice/open water and deformed ice, could be discriminated. Two basic problems of high practical importance remained: how to discriminate between (1) open water and undeformed ice, and (2) ridged ice and brash ice. The data further showed illustrative examples of SAR imagery over sea ice.

scholarly journals Comparison of Target Detectors to Identify Icebergs in Quad-Polarimetric L-Band Synthetic Aperture Radar Data

2021 ◽  
Vol 13 (9) ◽  
pp. 1753
Author(s):  
Johnson Bailey ◽  
Armando Marino ◽  
Vahid Akbari
Keyword(s):  
Sea Ice ◽  
Synthetic Aperture Radar ◽  
Roc Curves ◽  
Radar Data ◽  
Open Ocean ◽  
Synthetic Aperture ◽  
False Alarms ◽  
Synthetic Aperture Radar Data ◽  
Whitening Filter ◽  
Aperture Radar

Icebergs represent hazards to ships and maritime activities and therefore their detection is essential. Synthetic Aperture Radar (SAR) satellites are very useful for this, due to their capability to acquire data under cloud cover and during day and night passes. In this work, we compared six state-of-the-art polarimetric target detectors to test their performance and ability to detect small-sized icebergs <120 m in four locations in Greenland. We used four single-look complex (SLC) ALOS-2 quad-polarimetric images from JAXA for quad-polarimetric detection and we compared with dual-polarimetric detectors using only the channels HH and HV. We also compared these detectors with single-polarimetric intensity channels and we tested using two scenarios: open ocean and sea ice. Our results show that the multi-look polarimetric whitening filter (MPWF) and the optimal polarimetric detector (OPD) provide the most optimal performance in quad- and dual-polarimetric mode detection. The analysis shows that, overall, quad-polarimetric detectors provide the best detection performance. When the false alarm rate (PF) is fixed to 10-5, the probabilities of detection (PD) are 0.99 in open ocean and 0.90 in sea ice. Dual-polarimetric or single-polarimetric detectors show an overall reduction in performance (the ROC curves show a decrease), but this degradation is not very large (<0.1) when the value of false alarms is relatively high (i.e., we are interested in bigger icebergs with a brighter backscattering >120 m, as they are easier to detect). However, the differences between quad- and dual- or single-polarimetric detectors became much more evident when the PF value was fixed to low detection probabilities 10-6 (i.e., smaller icebergs). In the single-polarimetric mode, the HV channel showed PD values of 0.62 for open ocean and 0.26 for sea ice, compared to values of 0.81 (open ocean) and 0.77 (sea ice) obtained with quad-polarimetric detectors.

scholarly journals Remote Sensing Supported Sea Surface pCO2 Estimation and Variable Analysis in the Baltic Sea

2021 ◽  
Vol 13 (2) ◽  
pp. 259
Author(s):  
Shuping Zhang ◽  
Anna Rutgersson ◽  
Petra Philipson ◽  
Marcus B. Wallin
Keyword(s):  
Remote Sensing ◽  
Baltic Sea ◽  
Mean Squared Error ◽  
Numerical Models ◽  
Mixed Layer Depth ◽  
Sea Surface ◽  
The Baltic Sea ◽  
Chl A ◽  
Marginal Seas ◽  
The Baltic

Marginal seas are a dynamic and still to large extent uncertain component of the global carbon cycle. The large temporal and spatial variations of sea-surface partial pressure of carbon dioxide (pCO2) in these areas are driven by multiple complex mechanisms. In this study, we analyzed the variable importance for the sea surface pCO2 estimation in the Baltic Sea and derived monthly pCO2 maps for the marginal sea during the period of July 2002–October 2011. We used variables obtained from remote sensing images and numerical models. The random forest algorithm was employed to construct regression models for pCO2 estimation and produce the importance of different input variables. The study found that photosynthetically available radiation (PAR) was the most important variable for the pCO2 estimation across the entire Baltic Sea, followed by sea surface temperature (SST), absorption of colored dissolved organic matter (aCDOM), and mixed layer depth (MLD). Interestingly, Chlorophyll-a concentration (Chl-a) and the diffuse attenuation coefficient for downwelling irradiance at 490 nm (Kd_490nm) showed relatively low importance for the pCO2 estimation. This was mainly attributed to the high correlation of Chl-a and Kd_490nm to other pCO2-relevant variables (e.g., aCDOM), particularly in the summer months. In addition, the variables’ importance for pCO2 estimation varied between seasons and sub-basins. For example, the importance of aCDOM were large in the Gulf of Finland but marginal in other sub-basins. The model for pCO2 estimate in the entire Baltic Sea explained 63% of the variation and had a root of mean squared error (RMSE) of 47.8 µatm. The pCO2 maps derived with this model displayed realistic seasonal variations and spatial features of sea surface pCO2 in the Baltic Sea. The spatially and seasonally varying variables’ importance for the pCO2 estimation shed light on the heterogeneities in the biogeochemical and physical processes driving the carbon cycling in the Baltic Sea and can serve as an important basis for future pCO2 estimation in marginal seas using remote sensing techniques. The pCO2 maps derived in this study provided a robust benchmark for understanding the spatiotemporal patterns of CO2 air-sea exchange in the Baltic Sea.

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