Incidence angle dependencies for C-band backscatter from sea ice during both the winter and melt season

نویسندگان

چکیده

Incidence angle normalization is used to reduce the radiometric ambiguity within or between synthetic aperture radar (SAR) images. For sea ice, incidence typically constrained winter months because of difficulty capturing rapidly changing backscatter values during melt season. Here, we make use high-temporal-resolution RADASAT Constellation Mission (RCM) SAR images quantify dependencies (slopes) for first-year ice (FYI), second-year (SYI), and multi-year (MYI) several stages melt. We apply a new successive image differencing method mitigate rapid changes in Slopes SYI are shown, first time, winter, most season periods. Time series slopes also at intervals as short thirty minutes. early period (FYI -0.230, -0.191, MYI -0.175 dB/1°) similar those -0.235, -0.208, -0.167 dB/1°). During snow period, remain FYI (-0.235 dB/1°), but become steeper (-0.241 (-0.240 All types reach their maximum slope steepness ponding -0.308, -0.283, -0.289 then shallower again drainage -0.198, -0.207, -0.240 show that melt-season-specific provide important improvements visual interpretation imagery consistency automated classification algorithms.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

C-band Backscatter Measurements of Winter Sea Ice in the Weddell Sea, Antarctica

During the 1992 Winter Weddell Gyre Study, a C-band scatterometer was used from the German ice-breaker R/V Polarstern to obtain detailed shipborne measurement scans of Antarctic sea ice. The frequency-modulated continuous-wave (FM-CW) radar operated at 4.3 GHz and acquired like(VV) and cross-polarization (HV) data at a variety of incidence angles (10-75). Calibrated backscatter data were record...

متن کامل

Large-scale inverse Ku-band backscatter modeling of sea ice

Polar sea ice characteristics provide important inputs to models of several geophysical processes. Microwave scatterometers are ideal for monitoring these regions due to their sensitivity to ice properties and insensitivity to atmospheric distortions. Many forward electromagnetic scattering models have been proposed to predict the normalized radar cross section ( ) from sea ice characteristics....

متن کامل

A C-band Backscatter Model for Lake Ice in Alaska

ERS-1 SAR imagery of lake ice growing on shallow lundra lakes in northern Alaska shows interesting radar backscatter variations. Based on the analysis of ice cores from these lakes, a multi-layer backscatter model comprised of the following elements has been developed: I) specular air-ice, ice-water and ice-frown soil boundaries; 2) an ice layer of variable thickness; 3) ice sub-layers with air...

متن کامل

Improving Sea Ice Characterization in Dry Ice Winter Conditions Using Polarimetric Parameters from C- and L-Band SAR Data

Sea ice monitoring and classification is one of the main applications of Synthetic Aperture Radar (SAR) remote sensing. C-band SAR imagery is regarded as an optimal choice for sea ice applications; however, other SAR frequencies has not been extensively assessed. In this study, we evaluate the potential of fully polarimetric L-band SAR imagery for monitoring and classifying sea ice during dry w...

متن کامل

Ku-, X- and C-Band Microwave Backscatter Indices from Saline Snow Covers on Arctic First-Year Sea Ice

In this study, we inter-compared observed Ku-, Xand C-band microwave backscatter from saline 14 cm, 8 cm, and 4 cm snow covers on smooth first-year sea ice. A Ku-, Xand C-band surface-borne polarimetric microwave scatterometer system was used to measure fully-polarimetric backscatter from the three snow covers, near-coincident with corresponding in situ snow thermophysical measurements. The stu...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IEEE Transactions on Geoscience and Remote Sensing

سال: 2023

ISSN: ['0196-2892', '1558-0644']

DOI: https://doi.org/10.1109/tgrs.2023.3315056