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Targeted Deletion of Fibrinogen Like Protein 1 Reveals a Novel Role in Energy Substrate Utilization
Fibrinogen like protein 1(Fgl1) is a secreted protein with mitogenic activity on primary hepatocytes. Fgl1 is expressed in the liver and its expression is enhanced following acute liver injury. In animals with acute liver failure, administration of recombinant Fgl1 results in decreased mortality supporting the notion that Fgl1 stimulates hepatocyte proliferation and/or protects hepatocytes from injury. However, because Fgl1 is secreted and detected in the plasma, it is possible that the role of Fgl1 extends far beyond its effect on hepatocytes. In this study, we show that Fgl1 is additionally expressed in brown adipose tissue. We find that signals elaborated following liver injury also enhance the expression of Fgl1 in brown adipose tissue suggesting that there is a cross talk between the injured liver and adipose tissues. To identify extra hepatic effects, we generated Fgl1 deficient mice. These mice exhibit a phenotype suggestive of a global metabolic defect: Fgl1 null mice are heavier than wild type mates, have abnormal plasma lipid profiles, fasting hyperglycemia with enhanced gluconeogenesis and exhibit differences in white and brown adipose tissue morphology when compared to wild types. Because Fgl1 shares structural similarity to Angiopoietin like factors 2, 3, 4 and 6 which regulate lipid metabolism and energy utilization, we postulate that Fgl1 is a member of an emerging group of proteins with key roles in metabolism and liver regeneration
ΠΠΎΡΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΈΠ΅ ΠΏΠΎΠ»Π΅ΠΉ Π΄ΡΠ΅ΠΉΡΠ° ΠΌΠΎΡΡΠΊΠΎΠ³ΠΎ Π»ΡΠ΄Π° ΠΏΠΎ ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»ΡΠ½ΡΠΌ ΡΠΏΡΡΠ½ΠΈΠΊΠΎΠ²ΡΠΌ ΡΠ°Π΄ΠΈΠΎΠ»ΠΎΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΠΌ ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΡΠΌ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΏΡΠΎΡΠ»Π΅ΠΆΠΈΠ²Π°Π½ΠΈΡ ΠΎΡΠΎΠ±ΡΡ ΡΠΎΡΠ΅ΠΊ
The state of the art methods for sea ice drift retrieval from sequential SAR images are described. An original algorithm based on scale-spaced image representation that efο¬ cient both to noise suppression and signal preserving is proposed. The validation of the algorithm against the manual-derived reference data presented. Its advantages demonstrated in comparison with previously developed algorithms using Sentinel-1a data.ΠΠΏΠΈΡΡΠ²Π°ΡΡΡΡ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Ρ ΠΊ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΌΡ ΡΠ°ΡΡΠ΅ΡΡ Π΄ΡΠ΅ΠΉΡΠ° ΠΌΠΎΡΡΠΊΠΎΠ³ΠΎ Π»ΡΠ΄Π° ΠΏΠΎ ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»ΡΠ½ΡΠΌ ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΡΠΌ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π΄Π°Π½Π½ΡΡ
Π°ΠΊΡΠΈΠ²Π½ΠΎΠΉ ΡΠ°Π΄ΠΈΠΎΠ»ΠΎΠΊΠ°ΡΠΈΠΈ Π Π‘Π-SAR (ΡΠ°Π΄ΠΈΠΎΠ»ΠΎΠΊΠ°ΡΠΎΡΡ Ρ ΡΠΈΠ½ΡΠ΅Π·ΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ Π°ΠΏΠ΅ΡΡΡΡΠΎΠΉ). ΠΡΠ΅Π΄Π»Π°Π³Π°Π΅ΡΡΡ ΠΎΡΠΈΠ³ΠΈΠ½Π°Π»ΡΠ½ΡΠΉ Π°Π»Π³ΠΎΡΠΈΡΠΌ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΌΠ½ΠΎΠ³ΠΎΠΌΠ°ΡΡΡΠ°Π±Π½ΠΎΠ³ΠΎ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π°Π΄Π°ΠΏΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Π°Π²Π»Π΅Π½ΠΈΡ ΡΡΠΌΠΎΠ². ΠΡΠΈΠ²ΠΎΠ΄ΡΡΡΡ ΠΎΡΠ΅Π½ΠΊΠΈ ΠΊΠ°ΡΠ΅ΡΡΠ²Π° ΡΠ°ΡΡΠ΅ΡΠΎΠ² Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π΄Π°Π½Π½ΡΡ
ΡΠΏΡΡΠ½ΠΈΠΊΠ° Sentinel-1Π, Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΡΡΡΡΡ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΠΎΠ³ΠΎ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΡΠΎΠΏΠΎΡΡΠ°Π²Π»Π΅Π½ΠΈΡ Ρ ΡΡΡΠ΅ΡΡΠ²ΡΡΡΠΈΠΌΠΈ ΠΌΠΈΡΠΎΠ²ΡΠΌΠΈ Π°Π½Π°Π»ΠΎΠ³Π°ΠΌΠΈ
ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π»Π΅Π΄ΠΎΠ²ΠΎΠΉ ΠΎΠ±ΡΡΠ°Π½ΠΎΠ²ΠΊΠΈ ΠΠ±ΡΠΊΠΎΠΉ Π³ΡΠ±Ρ ΠΏΠΎ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠΌ ΡΠΏΡΡΠ½ΠΈΠΊΠΎΠ²ΡΠΌ Π΄Π°Π½Π½ΡΠΌ Π² 2007β2017 Π³Π³.
The Obskay guba Bay is a region of rapidly developing oil and gas exploration. Knowing the current sea ice conditions including dangerous phenomena e. g. ridges and stamukhas is important for the safety of coastal and underwater construction as well as for ecological risk assessment. With this study, we aim to obtain new data on sea ice seasonal cycle in the southern and central part of the Obskay guba Bay for 10 years (from 2007 to 2017) and to demonstrate the capacity of satellite data in obtaining varying sea ice characteristics in the region. Analyzing daily visual MODIS and available Sentinel-1 SAR imagery, we derived dates of sea ice and fast ice formation, fast ice breakup and melt onset and the onset of ice-free period. For this purpose the satellite data were analyzed manually by sea ice expert. In addition, of sea ice ridges were derived and the sea ice drift data wea automatically processed in order to locate motionless sea ice features β stamukhas. The distribution of sea ice floes and field size in the region was derived from MODIS data. The analysis showed that there is a tendency towards a shorter ice covered period based on the data from 2007 to 2017. Overall, the formation of sea ice starts 9 days later and fast ice breakup occurs 16 days earlier compared to the long-term mean (1947β2010). The majority of ridges were located in the central part of the region and directed along the coast. The analysis confirmed absence of large stamuhas visible to be applied method (with a horizontal size of 100 m). The predominant sea ice field size range lies 500β1500 m. The study shows that a combination of images obtained in the optical range of the survey with radar data makes it possible to supplement the classical visual assessments with the results of automatic methods for detecting fast ice, detecting stamukha, as well as ice drift and deformation.ΠΠ±ΡΠΊΠ°Ρ Π³ΡΠ±Π° β ΡΠ°ΠΉΠΎΠ½ Π±ΡΡΠ½ΠΎ ΡΠ°Π·Π²ΠΈΠ²Π°ΡΡΠ΅ΠΉΡΡ Π΄ΠΎΠ±ΡΡΠΈ Π½Π΅ΡΡΠΈ ΠΈ Π³Π°Π·Π°. ΠΠ½Π°Π½ΠΈΠ΅ ΡΠ΅ΠΊΡΡΠΈΡ
Π»Π΅Π΄ΠΎΠ²ΡΡ
ΡΡΠ»ΠΎΠ²ΠΈΠΉ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ Π΄Π»Ρ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΠΈ Π±Π΅ΡΠ΅Π³ΠΎΠ²ΠΎΠΉ ΠΈ ΠΏΠΎΠ΄Π²ΠΎΠ΄Π½ΠΎΠΉ ΠΈΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΡ. Π¦Π΅Π»ΡΡ Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΡΠ΅Π½ΠΊΠ° ΡΡΠΎΠΊΠΎΠ² Π»Π΅Π΄ΠΎΠ²ΡΡ
ΡΠ²Π»Π΅Π½ΠΈΠΉ ΠΈ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ (ΡΠΊΠΎΡΠΎΡΡΡ Π΄ΡΠ΅ΠΉΡΠ°, Π»ΠΎΠΊΠ°Π»ΠΈΠ·Π°ΡΠΈΡ ΡΡΠ°ΠΌΡΡ
ΠΈ ΡΠΎΡΠΎΡΠΎΠ²) Π² ΡΠΆΠ½ΠΎΠΉ ΠΈ ΡΠ΅Π½ΡΡΠ°Π»ΡΠ½ΠΎΠΉ ΡΠ°ΡΡΠΈ ΠΠ±ΡΠΊΠΎΠΉ Π³ΡΠ±Ρ Ρ 2007 ΠΏΠΎ 2017 Π³. ΠΠ½Π°Π»ΠΈΠ·ΠΈΡΡΡ Π΅ΠΆΠ΅Π΄Π½Π΅Π²Π½ΡΠ΅ Π²ΠΈΠ·ΡΠ°Π»ΡΠ½ΡΠ΅ Π΄Π°Π½Π½ΡΠ΅ MODIS ΠΈ ΠΈΠΌΠ΅ΡΡΠΈΠ΅ΡΡ ΡΠ½ΠΈΠΌΠΊΠΈ Sentinel-1 SAR, ΠΌΡ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΠ»ΠΈ Π΄Π°ΡΡ Π½Π°ΡΠ°Π»Π° ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΠ³ΠΎ Π»Π΅Π΄ΠΎΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ, Π½Π°ΡΠ°Π»ΠΎ ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ Π²Π·Π»ΠΎΠΌΠ° ΠΏΡΠΈΠΏΠ°Ρ, Π½Π°ΡΡΡΠΏΠ»Π΅Π½ΠΈΠ΅ Π±Π΅Π·Π»Π΅Π΄Π½ΠΎΠ³ΠΎ ΠΏΠ΅ΡΠΈΠΎΠ΄Π°. Π ΡΠ΅Π»ΠΎΠΌ ΠΏΠΎ Π΄Π°Π½Π½ΡΠΌ Ρ 2007 ΠΏΠΎ 2017 Π³. Π½Π°Π±Π»ΡΠ΄Π°Π΅ΡΡΡ ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΡ ΡΠΌΠ΅Π½ΡΡΠ΅Π½ΠΈΡ ΡΡΡΠ΅ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΡ Π»Π΅Π΄ΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠΊΡΠΎΠ²Π°. ΠΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΌΠΎΡΡΠΊΠΎΠ³ΠΎ Π»ΡΠ΄Π° Π½Π°ΡΠΈΠ½Π°Π΅ΡΡΡ ΠΏΠΎΠ·ΠΆΠ΅, Π° Π²Π·Π»ΠΎΠΌ ΠΏΡΠΈΠΏΠ°Ρ β ΡΠ°Π½ΡΡΠ΅ ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ ΡΠΎ ΡΡΠ΅Π΄Π½ΠΈΠΌΠΈ ΠΌΠ½ΠΎΠ³ΠΎΠ»Π΅ΡΠ½ΠΈΠΌΠΈ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡΠΌΠΈ (1947β2010 Π³Π³.). Π’Π°ΠΊΠΆΠ΅ Π±ΡΠ»ΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Ρ ΡΠΊΠΎΡΠΎΡΡΡ Π΄ΡΠ΅ΠΉΡΠ° ΠΌΠΎΡΡΠΊΠΎΠ³ΠΎ Π»ΡΠ΄Π° ΠΈ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΠ΅ ΡΠΎΡΠΎΡΠΎΠ². ΠΡΡΡΡΡΡΠ²ΠΈΠ΅ Π² ΡΠ°ΠΉΠΎΠ½Π΅ ΠΊΡΡΠΏΠ½ΡΡ
ΡΡΠ°ΠΌΡΡ
Π±ΡΠ»ΠΎ ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠΆΠ΄Π΅Π½ΠΎ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ°ΠΌΠΈ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° Π°Π²ΡΠΎΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ Π Π‘Π-ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ
Π‘Π²ΡΠ·Ρ ΠΊΡΡΠΏΠ½ΠΎΠΌΠ°ΡΡΡΠ°Π±Π½ΠΎΠΉ ΠΈΠ·ΠΌΠ΅Π½ΡΠΈΠ²ΠΎΡΡΠΈ ΠΏΠΎΠ»Ρ Π΄ΡΠ΅ΠΉΡΠ° Π»ΡΠ΄Π° Π² Π‘Π΅Π²Π΅ΡΠ½ΠΎΠΌ ΠΠ΅Π΄ΠΎΠ²ΠΈΡΠΎΠΌ ΠΎΠΊΠ΅Π°Π½Π΅ Ρ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡΠΌΠΈ ΠΎΠ±ΡΠ΅ΠΉ Π»Π΅Π΄ΠΎΠ²ΠΈΡΠΎΡΡΠΈ, ΠΏΡΠΎΠΈΡΡ ΠΎΠ΄ΡΡΠΈΠΌΠΈ Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ ΠΏΠΎΡΠ»Π΅Π΄Π½ΠΈΡ Π΄Π΅ΡΡΡΠΈΠ»Π΅ΡΠΈΠΉ
Discusses the relationship of a large-scale field variability of drift ice in the Arctic Ocean with a climate change total sea ice extent, occurring in recent decades, based on a unique data set of daily drift fields derived from remote sensing data analysis. Analysis of vector fields of the sea ice drift is done using vector-algebraic method that allows to significantly compress the initial information and describe the vector fields by a limited set of scalar parameters. The joint analysis of the variability of drift field and changes in atmospheric circulation types was carried out within the framework of the classification of large-scale atmospheric processes in theArcticby Vangengeim-Girs-Dydina. It was shown that the predominant circulating type now (B type) contributes to the creation of conditions for ice buildup.Π Π°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ ΡΠ²ΡΠ·Ρ ΠΊΡΡΠΏΠ½ΠΎΠΌΠ°ΡΡΡΠ°Π±Π½ΠΎΠΉ ΠΈΠ·ΠΌΠ΅Π½ΡΠΈΠ²ΠΎΡΡΠΈ ΠΏΠΎΠ»Ρ Π΄ΡΠ΅ΠΉΡΠ° Π»ΡΠ΄Π° Π² Π‘Π΅Π²Π΅ΡΠ½ΠΎΠΌ ΠΠ΅Π΄ΠΎΠ²ΠΈΡΠΎΠΌ ΠΎΠΊΠ΅Π°Π½Π΅ Ρ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡΠΌΠΈ ΠΎΠ±ΡΠ΅ΠΉ Π»Π΅Π΄ΠΎΠ²ΠΈΡΠΎΡΡΠΈ, ΠΏΡΠΎΠΈΡΡ
ΠΎΠ΄ΡΡΠΈΠΌΠΈ Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ ΠΏΠΎΡΠ»Π΅Π΄Π½ΠΈΡ
Π΄Π΅ΡΡΡΠΈΠ»Π΅ΡΠΈΠΉ, Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΠ½ΠΈΠΊΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΌΠ°ΡΡΠΈΠ²Π° Π΄Π°Π½Π½ΡΡ
Π΅ΠΆΠ΅Π΄Π½Π΅Π²Π½ΡΡ
ΠΏΠΎΠ»Π΅ΠΉ Π΄ΡΠ΅ΠΉΡΠ°, ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΡ
Π² ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ Π°Π½Π°Π»ΠΈΠ·Π° Π΄Π°Π½Π½ΡΡ
Π΄ΠΈΡΡΠ°Π½ΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ Π·ΠΎΠ½Π΄ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΠ΅ΠΌΠ»ΠΈ. ΠΠ½Π°Π»ΠΈΠ· Π²Π΅ΠΊΡΠΎΡΠ½ΡΡ
ΠΏΠΎΠ»Π΅ΠΉ Π΄ΡΠ΅ΠΉΡΠ° ΠΌΠΎΡΡΠΊΠΎΠ³ΠΎ Π»ΡΠ΄Π° Π²ΡΠΏΠΎΠ»Π½ΡΠ΅ΡΡΡ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π²Π΅ΠΊΡΠΎΡΠ½ΠΎΠ°Π»Π³Π΅Π±ΡΠ°ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π°, ΠΊΠΎΡΠΎΡΡΠΉ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎ ΡΠΆΠΈΠΌΠ°ΡΡ ΠΈΡΡ
ΠΎΠ΄Π½ΡΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΈ ΠΎΠΏΠΈΡΡΠ²Π°ΡΡ Π²Π΅ΠΊΡΠΎΡΠ½ΡΠ΅ ΠΏΠΎΠ»Ρ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΡΠΌ Π½Π°Π±ΠΎΡΠΎΠΌ ΡΠΊΠ°Π»ΡΡΠ½ΡΡ
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ². Π‘ΠΎΠ²ΠΌΠ΅ΡΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΈΠ·ΠΌΠ΅Π½ΡΠΈΠ²ΠΎΡΡΠΈ ΠΏΠΎΠ»Π΅ΠΉ Π΄ΡΠ΅ΠΉΡΠ° ΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΡΠΈΠΏΠ° Π°ΡΠΌΠΎΡΡΠ΅ΡΠ½ΠΎΠΉ ΡΠΈΡΠΊΡΠ»ΡΡΠΈΠΈ Π²ΡΠΏΠΎΠ»Π½ΡΠ»ΡΡ Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΠΊΡΡΠΏΠ½ΠΎΠΌΠ°ΡΡΡΠ°Π±Π½ΡΡ
Π°ΡΠΌΠΎΡΡΠ΅ΡΠ½ΡΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π² ΠΡΠΊΡΠΈΠΊΠ΅ ΠΠ°Π½Π³Π΅Π½Π³Π΅ΠΉΠΌΠ°βΠΠΈΡΡΠ°β ΠΡΠ΄ΠΈΠ½ΠΎΠΉ. ΠΠΎΠΊΠ°Π·Π°Π½ΠΎ, ΡΡΠΎ ΠΏΡΠ΅ΠΎΠ±Π»Π°Π΄Π°ΡΡΠΈΠΉ Π² Π½Π°ΡΡΠΎΡΡΠ΅Π΅ Π²ΡΠ΅ΠΌΡ ΡΠΈΠΏ ΡΠΈΡΠΊΡΠ»ΡΡΠΈΠΈ (Π) ΡΠΏΠΎΡΠΎΠ±ΡΡΠ²ΡΠ΅Ρ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΡΡΠ»ΠΎΠ²ΠΈΠΉ Π΄Π»Ρ Π½Π°ΡΠ°ΡΡΠ°Π½ΠΈΡ Π»ΡΠ΄Π°
Improving Sea Ice Drift Retrieval from SAR Images Using Phase- and Cross-Correlation Techniques
A new combination of phase- and cross-correlation techniques for sea ice tracking from sequential synthetic aperture radar images investigated. An operational Python-based sea ice drift algorithm based on this combination from Sentinel-1 images is proposed