|
|
|
|
|
Rubio, Anna; Mader, Julien; Corgnati, Lorenzo; Mantovani, Carlo; Griffa, Annalisa; Novellino, Antonio; Quentin, Céline; Wyatt, Lucy; Schulz-stellenfleth, Johannes; Horstmann, Jochen; Lorente, Pablo; Zambianchi, Enrico; Hartnett, Michael; Fernandes, Carlos; Zervakis, Vassilis; Gorringe, Patrick; Melet, Angélique; Puillat, Ingrid. |
High Frequency Radar (HFR) is a land-based remote sensing instrument offering a unique insight to coastal ocean variability, by providing synoptic, high frequency and high resolution data at the ocean atmosphere interface. HFRs have become invaluable tools in the field of operational oceanography for measuring surface currents, waves and winds, with direct applications in different sectors and an unprecedented potential for the integrated management of the coastal zone. In Europe, the number of HFR networks has been showing a significant growth over the past 10 years, with over 50 HFRs currently deployed and a number in the planning stage. There is also a growing literature concerning the use of this technology in research and operational oceanography. A... |
Tipo: Text |
Palavras-chave: High frequency radar; Operational oceanography; Coastal observing systems; Radar remote sensing; Surface currents; Surface waves; Model assessment; Data assimilation. |
Ano: 2017 |
URL: https://archimer.ifremer.fr/doc/00368/47879/47895.pdf |
| |
|
|
Sano,E. E.; Huete,A. R.; Moran,M. S.. |
In this study, we investigated the feasibility of using the C-band European Remote Sensing Satellite (ERS-1) synthetic aperture radar (SAR) data to estimate surface soil roughness in a semiarid rangeland. Radar backscattering coefficients were extracted from a dry and a wet season SAR image and were compared with 47 in situ soil roughness measurements obtained in the rocky soils of the Walnut Gulch Experimental Watershed, southeastern Arizona, USA. Both the dry and the wet season SAR data showed exponential relationships with root mean square (RMS) height measurements. The dry C-band ERS-1 SAR data were strongly correlated (R² = 0.80), while the wet season SAR data have somewhat higher secondary variation (R² = 0.59). This lower correlation was probably... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Surface roughness; Radar remote sensing; Microwave. |
Ano: 1999 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06831999000400017 |
| |
|
|
|