The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Recently airborne SAR at very high frequencies, such as X- and Ku-bands, has been widely studied for many applications. In these studies, the backscatter properties at different frequencies have been well discussed. However, these properties of the urban objects and structures have not been sufficiently discussed yet. In this paper, we focus on evaluating the difference of Ku- and X-band SAR intensity...
Detection and characterization of avalanches are important for making avalanche inventories as well as for the management of emergency situations. In this paper we propose a scheme for automatic detection and mapping of avalanches in SAR images. The approach builds upon the hypothesis that compacted rough snow of an avalanche has very high backscatter intensity values compared to homogeneous snow...
Snow cover in cold and arid regions is a key factor controlling regional energy balances, the hydrological cycle, and water utilization. Optical remote sensing data offer an effective means of mapping snow cover, although their application is limited by solar illumination conditions, conversely, SAR technology offers the ability to measure snow wetness changes in all weather. In the present study,...
The paper presents a comparison of automatic temporal change detection techniques on the basis of SAR data acquired during the 2015 DALO-ARCTIC campaign in Greenland. The data, acquired by DLR's F-SAR sensor, includes fully polarimetric imagery at X-, C-, S- and L-band with temporal baselines ranging from very short (less than one hour) to long (more than three weeks). Results for both coherent (interferometric)...
In this paper, we propose an effective wet snow mapping method with focus on the incident angle of microwave. Surface scattering is dominant for both wet snow and bare ground. However, it is expected that the characteristic of the wet snow scattering is different from the bare ground one according to the variation of dielectric constant. At the same time, surface scattering characteristics, especially...
Snow plays an important role in subarctic environments and its spatial dispersion is notably linked to vegetation cover. The objective of this paper is to present an approach to estimate snow depth from SAR data using classification of vegetation types from the same SAR dataset. The polarimetric RADARSAT-2 data are used to produce a classification of the vegetation cover types and the effect of the...
In this work, X and C band images acquired by COSMO-SkyMed (CSK) and Sentinel-1 (S1), respectively, on alpine environment have been compared for investigating snow characteristics. The specific capabilities of each sensor, involving also optical sensors (i. e., Landsat and Sentinel-2 satellites), have been exploited. Dense Media Radiative Transfer theory, with quasi-crystalline approximation (DMRT-QCA)...
Snow depth is one of the most important parameters for hydrological applications. SAR (Synthetic Aperture Radar) has the ability to monitor the surface deformation effectively, with a certain penetration and interference measurement capability. The refraction of microwaves in dry snow is shown to have a significant effect on the interferometric phase. According to this, snow depth estimation with...
In recent years, unmanned aerial vehicles (UAVs) have been widely used for civilian remote sensing applications. One of them is to assess damages due to man-made or natural disasters and search for bodies in the debris. In this work, we propose to support avalanche search and rescue (SAR) operation with UAVs. The image acquired by the UAV is processed through a pre-trained convolutional neural network...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.