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X-band COSMO-SkyMed SAR data for sea wave simulations and coastal vulnerability assessment  [PDF]
G. Benassai,A. Montuori,M. Migliaccio,F. Nunziata
Ocean Science Discussions (OSD) , 2012, DOI: 10.5194/osd-9-3281-2012
Abstract: In this paper, X-band COSMO-SkyMed Synthetic Aperture Radar (SAR) data are first experimented as wind field forcing of coastal wind-wave oceanographic modeling for both sea-wave numerical simulation and coastal vulnerability assessment purposes. The SAR data set consists of 60 X-band VV-polarized Level 1B Detected Ground Multi-look (DGM) ScanSAR Huge Region COSMO-SkyMed SAR measurements, collected in the test area of the Southern Tyrrhenian Coastal basin during the winter season of 2010. On one hand, the wind-wave oceanographic modeling is based on the third-generation Simulating WAves Nearshore (SWAN) model, which is used for sea wave state estimation in coastal and island regions. On the other hand, the coastal vulnerability assessment model is based on the use of a key parameter known as impact index, which consistently provides the coastal risk evaluation due to the inundation of the inshore land. Experiments consist of numerical wave simulations of the SWAN model accomplished with respect to some relevant wave storms recorded in the test area during the winter season of 2010. The wind forcing is provided by X-band COSMO-SkyMed SAR-based wind field estimations which are properly blended with both buoys wave data and ECMWF model winds to retrieve meaningful wave parameters (e.g. significant wave height, wave directions and periods) as physical descriptors of tidal events. The output of numerical wave simulations are used to perform the coastal vulnerability assessment in the considered test area along the coastal plain of river Sele. The assessment is accomplished in terms of wave run-up height, storm beach retreat and both short- and long-term erosion shoreline evolution. Experimental results accomplished with X-band COSMO-SkyMed SAR-based wind field forcing are successfully compared with the ones gathered by using both buoys wave field data and ECMWF model winds, only. They demonstrate that both wind-wave interaction modeling and coastal vulnerability assessment can take full benefits of blended wind field products composed by X-band COSMO-SkyMed SAR wind field estimations and model data.
基于结构特征分析的cosmo-skymed图像商用船舶分类算法  [PDF]
蒋少峰,王超,吴樊,张波,汤益先,张红
遥感技术与研究 , 2014,
Abstract: 船舶分类与识别对于海洋交通运输监测与管理具有重要意义,同时也是sar海洋应用的重要组成部分。cosmo\|skymed高分辨率合成孔径雷达(sar)图像下,商用船舶的结构轮廓明显,散货船、集装箱船和油船的特征清晰可辨,为船舶识别分类提供有效支持。提出了一种基于结构特征分析的商用船舶分类算法,通过提取核密度估计值、船舶积分主轴位置及左中右3部分积分量比例等特征,可实现船舶类型的区分。通过在东海试验区的同步实验,证明cosmo\|skymed图像商用船舶分类算法的平均分类精度达到89.94%。
高分辨率雷达卫星cosmo-skymed干涉测量生成dem的实验研究  [PDF]
蒋厚军,廖明生,张路,王腾
武汉大学学报(信息科学版) , 2011,
Abstract: ?介绍了cosmo-skymed对地观测系统,分析了高分辨率sar传感器和tandem观测星座与相干性之间的关系,并利用间隔1d的cosmo-skymedtandem数据生成了祁连山区的dem。提出通过对无地形变化的差分干涉相位进行滤波来提取大气和轨道误差引起的测量偏差,探讨了实验干涉数据去相干的因素,并将生成的dem与astergdem进行了对比。
X-band COSMO-SkyMed wind field retrieval, with application to coastal circulation modeling  [PDF]
A. Montuori,P. de Ruggiero,M. Migliaccio,S. Pierini
Ocean Science Discussions (OSD) , 2012, DOI: 10.5194/osd-9-3251-2012
Abstract: In this paper, X-band COSMO-SkyMed SAR wind field retrieval is investigated to force coastal circulation modeling. The SAR data set consists of 60 X-band Level 1B Multi-Look Ground Detected ScanSAR Huge Region COSMO-SkyMed SAR data, gathered in the Southern Tyrrhenian Sea during the Summer and Winter seasons of 2010. The SAR-based wind vector field estimation is accomplished by resolving both the SAR-based wind speed and wind direction retrieval problems independently. The sea surface wind speed is retrieved by means of a SAR wind speed algorithm based on the Azimuth cut-off procedure, while the sea surface wind direction is provided by means of a SAR wind direction algorithm based on the Discrete Wavelet Transform Multi-Resolution Analysis. The obtained wind fields are compared with ground truth data provided by both ASCAT scatterometer and ECMWF model wind fields. SAR-derived wind vector fields and ECMWF model wind data are used to construct a blended wind product regularly sampled in both space and time, which is then used to force a coastal circulation model of a Southern Tyrrhenian coastal area to simulate wind-driven circulation processes. The modeling results clearly show that X-band COSMO-SkyMed SAR data can be valuable in providing effective wind fields for coastal circulation modeling.
X-band COSMO-SkyMed wind field retrieval, with application to coastal circulation modeling  [PDF]
A. Montuori,P. de Ruggiero,M. Migliaccio,S. Pierini
Ocean Science (OS) & Discussions (OSD) , 2013, DOI: 10.5194/os-9-121-2013
Abstract: In this paper, X-band COSMO-SkyMed synthetic aperture radar (SAR) wind field retrieval is investigated, and the obtained data are used to force a coastal ocean circulation model. The SAR data set consists of 60 X-band Level 1B Multi-Look Ground Detected ScanSAR Huge Region COSMO-SkyMed SAR data, gathered in the southern Tyrrhenian Sea during the summer and winter seasons of 2010. The SAR-based wind vector field estimation is accomplished by resolving both the SAR-based wind speed and wind direction retrieval problems independently. The sea surface wind speed is retrieved by means of a SAR wind speed algorithm based on the azimuth cut-off procedure, while the sea surface wind direction is provided by means of a SAR wind direction algorithm based on the discrete wavelet transform multi-resolution analysis. The obtained wind fields are compared with ground truth data provided by both ASCAT scatterometer and ECMWF model wind fields. SAR-derived wind vector fields and ECMWF model wind data are used to construct a blended wind product regularly sampled in both space and time, which is then used to force a coastal circulation model of a southern Tyrrhenian coastal area to simulate wind-driven circulation processes. The modeling results show that X-band COSMO-SkyMed SAR data can be valuable in providing effective wind fields for coastal circulation modeling.
Rice mapping using ALOS PALSAR dual polarization data
ALOS PALSAR双极化数据水稻制图

LING Feilong,LI Zengyuan,BAI Lin,TIAN Xin,CHEN Erxue,YANG Yongtian,
凌飞龙
,李增元,白黎娜,田昕,陈尔学,杨永恬

遥感学报 , 2011,
Abstract: Fine beam dual polarization data onboard Advanced Land Observing Satellite-Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) for Hai'an, Jiangsu, China acquired in 2008 were used to analyze rice backscatter features at L-band SAR for the development of rice mapping method. Similar temporal change trend of backscatter was observed at L-band SAR to that of C-band. With the dependence of HH backscatter on the spatial distribution structure of the rice canopy, Bragg resonance scattering has been observed in some mechanically planted fi elds due to extremely enhanced backscatter, making it diffi cult to map rice using L-band SAR. However, the HV polarization is not subject to Bragg resonance. Considering the Bragg resonance effect in HH polarization, a rice mapping method was proposed based on the temporal change characteristics of backscattering coeffi cient by the synergistic use of HH and HV polarization images of ALOS PALSAR. A mapping accuracy of about 88.4% was achieved.
Investigating the Relationship between X-Band SAR Data from COSMO-SkyMed Satellite and NDVI for LAI Detection  [PDF]
Fulvio Capodici,Guido D'Urso,Antonino Maltese
Remote Sensing , 2013, DOI: 10.3390/rs5031389
Abstract: Monitoring spatial and temporal variability of vegetation is important to manage land and water resources, with significant impact on the sustainability of modern agriculture. Cloud cover noticeably reduces the temporal resolution of retrievals based on optical data. COSMO-SkyMed (the new Italian Synthetic Aperture RADAR-SAR) opened new opportunities to develop agro-hydrological applications. Indeed, it represents a valuable source of data for operational use, due to the high spatial and temporal resolutions. Although X-band is not the most suitable to model agricultural and hydrological processes, an assessment of vegetation development can be achieved combing optical vegetation indices (VIs) and SAR backscattering data. In this paper, a correlation analysis has been performed between the crossed horizontal-vertical (HV) backscattering ( s°HV) and optical VIs ( VIopt) on several plots. The correlation analysis was based on incidence angle, spatial resolution and polarization mode. Results have shown that temporal changes of s°HV ( Δs°HV) acquired with high angles (off nadir angle; θ > 40°) best correlates with variations of VIopt ( ΔVI). The correlation between ΔVI and Δ s°HV has been shown to be temporally robust. Based on this experimental evidence, a model to infer a VI from s° ( VISAR) at the time, ti + 1, once known, the VIopt at a reference time, ti, and Δ s°HV between times, ti + 1 and ti, was implemented and verified. This approach has led to the development and validation of an algorithm for coupling a VIopt derived from DEIMOS-1 images and s°HV. The study was carried out over the Sele plain (Campania, Italy), which is mainly characterized by herbaceous crops. In situ measurements included leaf area index (LAI), which were collected weekly between August and September 2011 in 25 sites, simultaneously to COSMO-SkyMed (CSK) and DEIMOS-1 imaging. Results confirm that VISAR obtained using the combined model is able to increase the feasibility of operational satellite-based products for supporting agricultural practices. This study is carried out in the framework of the COSMOLAND project (Use of COSMO-SkyMed SAR data for LAND cover classification and surface parameters retrieval over agricultural sites) funded by the Italian Space Agency (ASI).
Robust Techniques for Coherent Change Detection Using Cosmo-Skymed SAR Images
Azzedine Bouaraba;Arezki Younsi;Aichouche Belhadj Aissa;Marc Acheroy;Nada Milisavljevic;Damien Closson
PIER M , 2012, DOI: 10.2528/PIERM11110707
Abstract: The satellite-borne SAR (Synthetic Aperture Radar) is a quite promising tool for high-resolution geo-surface measurement. Recently, there has been a great interest in Coherent Change Detection (CCD), where the coherence between two SAR images is evaluated and analyzed to detect surface changes. The sample coherence threshold may be used to distinguish between the changed and unchanged regions in the scene. Using COSMO-SkyMed (CSK) images, we show that for changed areas, the coherence is low but not completely lost. This situation, which is caused by the presence of bias in the coherence estimate, considerably degrades the performance of the sample threshold method. To overcome this problem, robust detection in inhomogeneous data must be considered. In this work, we propose the application and improvement of three techniques: Mean Level Detector (MLD), Ordered Statistic (OS) and Censored Mean Level Detector (CMLD), all applied to coherence in order to detect surface changes. The probabilities of detection and false alarm are estimated experimentally using high-resolution CSK images. We show that the proposed method, CMLD with incorporation of guard cells (GC) in the range direction, is robust and allows for nearly 4% higher detection probability in case of low false alarm probability.
Potential of X-Band TerraSAR-X and COSMO-SkyMed SAR Data for the Assessment of Physical Soil Parameters  [PDF]
Azza Gorrab,Mehrez Zribi,Nicolas Baghdadi,Bernard Mougenot,Zohra Lili Chabaane
Remote Sensing , 2015, DOI: 10.3390/rs70100747
Abstract: The aim of this paper is to analyze the potential of X-band SAR measurements (COSMO-SkyMed and TerraSAR-X) made over bare soils for the estimation of soil moisture and surface geometry parameters at a semi-arid site in Tunisia (North Africa). Radar signals acquired with different configurations ( HH and VV polarizations, incidence angles of 26° and 36°) are statistically compared with ground measurements (soil moisture and roughness parameters). The radar measurements are found to be highly sensitive to the various soil parameters of interest. A linear relationship is determined for the radar signals as a function of volumetric soil moisture, and a logarithmic correlation is observed between the radar signals and three surface roughness parameters: the root mean square height (Hrms), the parameter Zs = Hrms2/l (where l is the correlation length) and the parameter Zg?= Hrms × (Hrms/l)α (where α is the power of the surface height correlation function). The highest dynamic sensitivity is observed for Zg at high incidence angles. Finally, the performance of different physical and semi-empirical backscattering models (IEM, Baghdadi-calibrated IEM and Dubois models) is compared with SAR measurements. The results provide an indication of the limits of validity of the IEM and Dubois models, for various radar configurations and roughness conditions. Considerable improvements in the IEM model performance are observed using the Baghdadi-calibrated version of this model.
Mapping Tropical Rainforest Canopy Disturbances in 3D by COSMO-SkyMed Spotlight InSAR-Stereo Data to Detect Areas of Forest Degradation  [PDF]
Janik Deutscher,Roland Perko,Karlheinz Gutjahr,Manuela Hirschmugl,Mathias Schardt
Remote Sensing , 2013, DOI: 10.3390/rs5020648
Abstract: Assessment of forest degradation has been emphasized as an important issue for emission calculations, but remote sensing based detecting of forest degradation is still in an early phase of development. The use of optical imagery for degradation assessment in the tropics is limited due to frequent cloud cover. Recent studies based on radar data often focus on classification approaches of 2D backscatter. In this study, we describe a method to detect areas affected by forest degradation from digital surface models derived from COSMO-SkyMed X-band Spotlight InSAR-Stereo Data. Two test sites with recent logging activities were chosen in Cameroon and in the Republic of Congo. Using the full resolution COSMO-SkyMed digital surface model and a 90-m resolution Shuttle Radar Topography Mission model or a mean filtered digital surface model we calculate difference models to detect canopy disturbances. The extracted disturbance gaps are aggregated to potential degradation areas and then evaluated with respect to reference areas extracted from RapidEye and Quickbird optical imagery. Results show overall accuracies above 75% for assessing degradation areas with the presented methods.
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