Ocean Wave Parameters Retrieval from TerraSAR-X Images Validated against Buoy Measurements and Model Results
نویسندگان
چکیده
An ocean surface wave retrieval algorithm, Parameterized First-guess Spectrum Method (PFSM), which was initially developed for C-band Synthetic Aperture Radar (SAR), is modified to extract wave parameters from X-band TerraSAR-X (TS-X) images. Wave parameters, including significant wave height (SWH) and mean wave period (MWP) were extracted from nine TS-X HH-polarization images and were compared to in situ buoy measurements. The range of these wave retrievals is from 1 to 5 m of SWH and from 2 to 10 s of MWP. The retrieval accuracy could reach 80%. After that, a total of 16 collected TS-X HH-polarization images were used to invert wave parameters and then the retrieval results were compared to the operational WAVEWATCH-III wave model results. The SAR and in situ buoy wave comparison shows a 0.26 m Root-Mean-Square Error (RMSE) of SWH and a 19.8% of Scatter Index (SI). The SAR and WAVEWATCH-III model comparison yields slightly worse results with an RMSE of 0.43 m of SWH and a 32.8% of SI. For MWP, the SAR and buoy comparison shows the RMSE is 0.45 s with an SI of 26%, which is better than the results from the SAR and WAVEWATCH-III model comparison. Our results show that the PFSM algorithm is suitable to estimate wave parameters from X-band TS-X data. OPEN ACCESS Remote Sens. 2015, 7 12816
منابع مشابه
Validation of Coastal Wind and Wave Fields by High Resolution Satellite Data
methods to derive wind speed and the sea state from Synthetic Aperture Radar (SAR) satellite data are presented and applied for use in high resolution numerical modeling for coastal application. The new radar satellite TerraSAR-X (TS-X) images the sea surface with a high resolution up to 1m. So not only the wind field and integrated sea state parameters but also individual ocean waves with wave...
متن کاملSea State Measurements from Ts-x Sar Data
An empirical algorithm XWAVE to derive significant wave height from high resolution TerraSAR-X (TS-X) and Tandem-X (TD-X) has been developed. The algorithm is created especially for spaceborne X-band SAR data without needing a priori information. TS-X scenes were acquired in the over buoys located at the coast of United States of America and Canada and including Hawaii islands. Integral wave pa...
متن کاملPreliminary Assessment of Wind and Wave Retrieval from Chinese Gaofen-3 SAR Imagery
The Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) launched by the China Academy of Space Technology (CAST) has operated at C-band since September 2016. To date, we have collected 16/42 images in vertical-vertical (VV)/horizontal-horizontal (HH) polarization, covering the National Data Buoy Center (NDBC) buoy measurements of the National Oceanic and Atmospheric Administration (NOAA) aro...
متن کاملValidation of significant wave height product from Envisat ASAR using triple collocation
Nowadays, spaceborne Synthetic Aperture Radar (SAR) has become a powerful tool for providing significant wave height. Traditionally, validation of SAR derived ocean wave height has been carried out against buoy measurements or model outputs, which only yield a inter-comparison, but not an ‘absolute’ validation. In this study, the triple collocation error model has been introduced in the validat...
متن کاملError Analysis on ESA's Envisat ASAR Wave Mode Significant Wave Height Retrievals Using Triple Collocation Model
Nowadays, spaceborne Synthetic Aperture Radar (SAR) has become a powerful tool for providing significant wave height (SWH). Traditionally, validation of SAR derived SWH has been carried out against buoy measurements or model outputs, which only yield an inter-comparison, but not an “absolute” validation. In this study, the triple collocation error model has been introduced in the validation of ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Remote Sensing
دوره 7 شماره
صفحات -
تاریخ انتشار 2015