First Results of Monitoring Nature Conservation Sites in Alpine Region by Using Very High Resolution (VHR) X-Band SAR Data

2013 ◽  
Vol 6 (5) ◽  
pp. 2265-2274 ◽  
Author(s):  
Iftikhar Ali ◽  
Christian Schuster ◽  
Marc Zebisch ◽  
Michael Forster ◽  
Birgit Kleinschmit ◽  
...  
Keyword(s):  
Nature Conservation ◽  
High Resolution ◽  
Alpine Region ◽  
X Band ◽  
First Results ◽  
Sar Data ◽  
Very High

Sub-urban landscape characterization by very high-resolution X-band COSMO-Skymed SAR images: first results

2010 ◽  
Author(s):  
Fabio Del Frate ◽  
Domenico Loschiavo ◽  
Chiara Pratola ◽  
Giovanni Schiavon ◽  
Domenico Solimini
Keyword(s):  
High Resolution ◽  
Urban Landscape ◽  
Sar Images ◽  
Landscape Characterization ◽  
X Band ◽  
First Results ◽  
Very High

scholarly journals Studying the Applicability of X-Band SAR Data to the Network-Scale Mapping of Pavement Roughness on US Roads

2020 ◽  
Vol 12 (9) ◽  
pp. 1507 ◽  
Author(s):  
Franz J. Meyer ◽  
Olaniyi A. Ajadi ◽  
Edward J. Hoppe
Keyword(s):  
High Resolution ◽  
Remote Sensing Data ◽  
Ride Quality ◽  
International Roughness Index ◽  
Pavement Roughness ◽  
X Band ◽  
The Us ◽  
Network Scale ◽  
Sar Data ◽  
Satellite Radar

The traveling public judges the quality of a road mostly by its roughness and/or ride quality. Hence, mapping, monitoring, and maintaining adequate pavement smoothness is of high importance to State Departments of Transportation in the US. Current methods rely mostly on in situ measurements and are, therefore, time consuming and costly when applied at the network scale. This paper studies the applicability of satellite radar remote sensing data, specifically, high-resolution Synthetic Aperture Radar (SAR) data acquired at X-band, to the network-wide mapping of pavement roughness of roads in the US. Based on a comparison of high-resolution X-band Cosmo-SkyMed images with road roughness data in the form of International Roughness Index (IRI) measurements, we found that X-band radar brightness generally increases when pavement roughness worsens. Based on these findings, we developed and inverted a model to distinguish well maintained road segments from segments in need of repair. Over test sites in Augusta County, VA, we found that our classification scheme reaches an overall accuracy of 92.6%. This study illustrates the capacity of X-band SAR for pavement roughness mapping and suggests that incorporating SAR into DOT operations could be beneficial.

scholarly journals Brief Communication: Rapid mapping of landslide events: the 3 December 2013 Montescaglioso landslide, Italy

2014 ◽  
Vol 14 (7) ◽  
pp. 1835-1841 ◽  
Author(s):  
A. Manconi ◽  
F. Casu ◽  
F. Ardizzone ◽  
M. Bonano ◽  
M. Cardinali ◽  
...  
Keyword(s):  
High Resolution ◽  
Synthetic Aperture Radar ◽  
Southern Italy ◽  
Surface Deformation ◽  
Synthetic Aperture ◽  
Sar Images ◽  
Main Road ◽  
Rapid Mapping ◽  
X Band ◽  
Sar Data

Abstract. We present an approach to measure 3-D surface deformations caused by large, rapid-moving landslides using the amplitude information of high-resolution, X-band synthetic aperture radar (SAR) images. We exploit SAR data captured by the COSMO-SkyMed satellites to measure the deformation produced by the 3 December 2013 Montescaglioso landslide, southern Italy. The deformation produced by the deep-seated landslide exceeded 10 m and caused the disruption of a main road, a few homes and commercial buildings. The results open up the possibility of obtaining 3-D surface deformation maps shortly after the occurrence of large, rapid-moving landslides using high-resolution SAR data.

scholarly journals Improved estimation of flood parameters by combining space based SAR data with very high resolution digital elevation data

2009 ◽  
Vol 13 (5) ◽  
pp. 567-576 ◽  
Author(s):  
H. Zwenzner ◽  
S. Voigt
Keyword(s):  
High Resolution ◽  
Flood Mapping ◽  
Scaling Effects ◽  
Data Set ◽  
Digital Elevation ◽  
Geometric Precision ◽  
Elevation Data ◽  
Lidar Dem ◽  
Sar Data ◽  
Very High

Abstract. Severe flood events turned out to be the most devastating catastrophes for Europe's population, economy and environment during the past decades. The total loss caused by the August 2002 flood is estimated to be 10 billion Euros for Germany alone. Due to their capability to present a synoptic view of the spatial extent of floods, remote sensing technology, and especially synthetic aperture radar (SAR) systems, have been successfully applied for flood mapping and monitoring applications. However, the quality and accuracy of the flood masks and derived flood parameters always depends on the scale and the geometric precision of the original data as well as on the classification accuracy of the derived data products. The incorporation of auxiliary information such as elevation data can help to improve the plausibility and reliability of the derived flood masks as well as higher level products. This paper presents methods to improve the matching of flood masks with very high resolution digital elevation models as derived from LiDAR measurements for example. In the following, a cross section approach is presented that allows the dynamic fitting of the position of flood mask profiles according to the underlying terrain information from the DEM. This approach is tested in two study areas, using different input data sets. The first test area is part of the Elbe River (Germany) where flood masks derived from Radarsat-1 and IKONOS during the 2002 flood are used in combination with a LiDAR DEM of 1 m spatial resolution. The other test data set is located on the River Severn (UK) and flood masks derived from the TerraSAR-X satellite and aerial photos acquired during the 2007 flood are used in combination with a LiDAR DEM of 2 m pixel spacing. By means of these two examples the performance of the matching technique and the scaling effects are analysed and discussed. Furthermore, the systematic flood mapping capability of the different imaging systems are examined. It could be shown that the combination of high resolution SAR data and LiDAR DEM allows the derivation of higher level flood parameters such as flood depth estimates, as presented for the Severn area. Finally, the potential and the constraints of the approach are evaluated and discussed.

scholarly journals Intermittent SBAS (ISBAS) InSAR with COSMO-SkyMed X-band high resolution SAR data for landslide inventory mapping in Piana degli Albanesi (Italy)

2014 ◽  
Author(s):  
Francesca Cigna ◽  
Alessandro Novellino ◽  
Colm J. Jordan ◽  
Andrew Sowter ◽  
Massimo Ramondini ◽  
...  
Keyword(s):  
High Resolution ◽  
Landslide Inventory ◽  
X Band ◽  
Sar Data

NIHAO-UHD: High-resolution Simulations of MW mass galaxies

2017 ◽  
Vol 13 (S334) ◽  
pp. 209-212
Author(s):  
Tobias Buck ◽  
Andrea Macciò ◽  
Melissa Ness ◽  
Aura Obreja ◽  
Aaron Dutton
Keyword(s):  
High Resolution ◽  
Milky Way ◽  
Satellite System ◽  
The Galaxy ◽  
First Results ◽  
History Of ◽  
Galaxy Center ◽  
Hydrodynamical Simulations ◽  
Very High ◽  
Disc Galaxies

AbstractHigh resolution cosmological and hydrodynamical simulations have reached a resolution able to resolve in a self consistent way the disc of our galaxy, the galaxy center and the satellites orbiting around it. We present first results from the NIHAO-UHD project, a set of very high-resolution baryonic zoom-in simulations of Milky Way mass disc galaxies. These simulations model the full cosmological assembly history of the galaxies and their satellite system using the same, well tested physics as the NIHAO project. We show that these simulations can self-consistently reproduce the observed kinematical and morphological features of the X-shaped bulge observed in our own Milky Way.

Multi-temporal DInSAR analysis with X-band high resolution SAR data: examples and potential

2010 ◽  
Author(s):  
Fabio Bovenga ◽  
Davide Oscar Nitti ◽  
Alberto Refice ◽  
Raffaele Nutricato ◽  
Maria Teresa Chiaradia
Keyword(s):  
High Resolution ◽  
X Band ◽  
Multi Temporal ◽  
Sar Data
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