A complete interferometric Synthetic Aperture Radar (SAR) simulator has been developed. It achieves precise results by using geodetic models to represent the Earth’s shape, and considering SAR effects such as range migration, Doppler shifts, or perturbations of movement in the airborne case, which are included via the inverse Extended Chirp Scaling Algorithm (ECSA).

Microwave imaging techniques, in particular synthetic aperture radar (SAR), are able to obtain useful images even in adverse weather or darkness, which makes them suitable for target position or feature estimation. However, typical SAR imagery is not informative for the operator, because it is synthesized using complex radio signals with greater than 1.0 m wavelength. To deal with the target id...

This study concerned with fusion of synthetic aperture radar and optical satellite imagery. Due to the difference in the underlying sensor technology, data from synthetic aperture radar (SAR) and optical sensors refer to different properties of the observed scene and it is believed that when they are fused together, they complement each other to improve the performance of a particular applicati...

Based on Canadian Satellite (RADARSAT) synthetic aperture radar (SAR) images and simulations from a radar-backscattering model, we determined that conventional wet snow-mapping algorithms should perform optimally for a snowpack with a liquid-water content 3%, at low incidence angle ( = 20–30 ) and for a rather smooth surface (rms height ≤ 2.1 mm).

In this paper, radar target classification based on Synthetic Aperture Radar (SAR) images is investigated. Different criteria for extracting features from MSTAR data are presented, and classification rates shown, emphasizing where the useful information in terms of recognition resides. The combination of different features is also examined, linking the classification accuracy of the system to t...

Most paddy rice in the world grows in warm, humid and rainy environment where it is hard to acquire optical remote sensing data. Synthetic Aperture Radar (SAR) can acquire remote sensing information due to its all weather imaging and frequent revisit capability in the areas. A semi-empirical backscattering model was used to estimate leaf area index (LAI) from ENVISAT ASAR (Advanced Synthetic Ap...

RAMSEY, E. III; WERLE, D.; SUZUOKI, Y.; RANGOONWALA, A., and LU, Z., 2012. Limitations and potential of satellite imagery to monitor environmental response to coastal flooding. Journal of Coastal Research, 28(2), 457–476. West Palm Beach (Florida), ISSN 0749-0208. Storm-surge flooding and marsh response throughout the coastal wetlands of Louisiana were mapped using several types of remote sensi...

-Remote Sensing technologies provide the spatial data/maps and offer great advantages for a land consolidation project. But sometimes in some regions, optics and infrared remote sensing can not work well. SAR (Synthetic aperture radar), an active microwave remote sensing imaging radar, has the unique capabilities of obtaining abundant electromagnetic information from ground objects all day/all ...

For merging Synthetic Aperture Radar (SAR) with georeferenced data, one usually uses processing software to orthorectify the SAR images in order to add them in a GIS. Nevertheless, this projection involves an important alteration of the information of SAR images and are often specific to some particular SAR sources. Moreover, the transformation of radarcoding data from a GIS into the radar geom...

Synthetic aperture radar (SAR) remote sensing, with its advantages of all-weather coverage, all day/night acquisitions, cloud penetration, and signal independence of the solar illumination angle, can be applied to land cover classification and land consolidation, especially in some regions where optics and infrared remote sensing do not work well. A limitation of its using for land consolidatio...