Wind resource assessment from C-band SAR

Using accurate inputs of wind speed is crucial in wind resource assessment, as predicted power is proportional to the wind speed cubed. First, wind speeds retrieved from a series of 91 ERS-2 SAR and Envisat ASAR images, at moderate wind speeds (2-15 m s^− 1), were validated against in situ measurements from an offshore mast in the North Sea. The wind direction input, necessary for SAR wind speed retrievals, was obtained from the meteorological mast and from a local gradient analysis of wind streaks in the SAR images. A wind speed standard deviation of ∼ 1.1 m s^− 1 was found when in situ wind directions were used. The use of local gradient wind directions yielded a standard deviation of ∼ 1.3 m s^− 1. Wind speeds retrieved from three geophysical model functions (CMOD-IFR2, CMOD4, and CMOD5) were compared. The best approximation to the in situ measurements of wind speed was found for CMOD-IFR2, despite a bias on the order of − 0.3 m s^− 1. CMOD4 retrievals also underestimated the wind speed, whereas the bias on CMOD5 retrievals was negligible. Then, wind resource assessments were made from the SAR-based wind observations to show how errors in wind speed from the different SAR wind retrievals were reflected in the wind statistics. The mean wind speed, obtained for all of the 91 SAR scenes, was linked closely to the bias of SAR wind retrievals. Agreement to ± 15% of the in situ measurements was found for all the wind retrieval methods tested. The accuracy of power density estimates for the entire data set was evaluated by the standard deviation of SAR wind retrievals relative to the in situ measurements. SAR wind fields retrieved with CMOD-IFR2, using in situ wind direction inputs, exactly yielded the power density predicted from in situ measurements alone. The SAR-based wind resource assessment also corresponded well to predictions from longer time series of in situ measurements. This indicates that a reliable wind resource assessment may be achieved from a series of randomly selected SAR images. The findings presented here could be useful in future wind resource assessment based on SAR images.     

Envisat ASAR数据共享平台的设计与实现

随着经济和社会的迅速发展,科学数据共享是一个大趋势,也是目前研究的热点之一,而卫星数据共享是科学数据共享的非常重要的组成部分。中国遥感卫星地面站是我国重要的民用对地观测遥感卫星数据接收、处理、存档和分发单位,目前已经存储的各类遥感卫星数据近百万余景,数据存储量高达100TB。为了适应我国经济建设和科学研究的需要,中国遥感卫星地面站提出了“建立国家级卫星数据共享基础平台”的目标,承担了科技部“Envisat-1ASAR雷达卫星数据共享项目”。本文介绍了地面站的Envisat-1ASAR雷达卫星数据共享系统的设计依据和实现思路,阐述了系统的若干关键技术和创新点,最后展望了系统将来的发展方向。     

基于联合PWF2pCFAR算法的Envisat/ASAR双极化数据舰船检测方法研究

利用极化白化滤波PWF算法融合Envisat/ASAR双极化复数据图像,同时抑制相干斑,然后利用双参数恒虚警率2pCFAR算法进行舰船目标检测。在不同检测门限和检测模板条件下,利用实测VV/HV极化组合数据进行的仿真实验结果表明,联合PWF 2pCFAR算法不仅能够有效地检测出舰船目标,较好地降低了虚警率,也能够保留舰船目标的结构信息;同时得到了一组相对最优的检测门限与检测模板,具有一定的实际参考意义。     

Envisat卫星寿命延长方案对SAR数据应用的影响

卫星的工作寿命主要取决于卫星的燃料量,一旦燃料耗尽,卫星就会失去控制而报废。根据对Envisat卫星剩余燃料的估算,欧空局将于2010年10月22日对Envisat卫星采取新措施,减少燃料消耗,以延长卫星寿命。本文主要介绍了Envisat卫星寿命延长方案对SAR数据应用所产生的影响。     

Envisat AP图像P-CFAR舰船检测方法研究

Envisat的AP数据可以在一次成像过程中得到同一场景的两幅不同极化模式的数据,使用这种数据进行船只检测可以有效的提高检测概率并降低虚警率。为利用AP数据中包含的关于目标和场景的有效信息,引入了基于向量矢量的P-CFAR检测器对交替极化数据进行检测。首先使用GIS数据对陆地区域进行了掩膜处理,剔除了陆地区域的影响。然后使用P-CFAR检测器对目标进行检测。通过检测器窗口的滑动,我们对中心像素的信息量进行计算,并将其与检测阈值进行比较,从而检测得到目标。最后,为剔除虚警,使用了一个复合目标辨识算法对检测得到的候选目标进行了辨识。为了评价该算法的检测性能,利用Envisat ASAR的交替极化数据进行了实验,实验结果表明该方法能够充分利用目标和场景的有效信息,在环境干扰较大的情况下也可以对舰船进行有效的检测。     

基于联合PWF-2pCFAR算法的Envisat/ASAR双极化数据舰船检测方法研究

利用极化白化滤波(PWF)算法融合Envisat/ASAR双极化复数据图像,同时抑制相干斑,然后利用双参数恒虚警率(2pCFAR)算法进行舰船目标检测。在不同检测门限和检测模板条件下,利用实测VV/HV极化组合数据进行的仿真实验结果表明,联合PWF-2pCFAR算法不仅能够有效地检测出舰船目标,较好地降低了虚警率,也能够保留舰船目标的结构信息;同时得到了一组相对最优的检测门限与检测模板,具有一定的实际参考意义。     

Envisat ASAR在特大洪涝灾害监测中的应用

我国是个洪涝灾害多发的国家,灾害的监测对于防洪减灾具有重要的意义。通过依托中欧“龙计划”项目,结合广西梧州市6·23特大洪涝灾害监测工作,探讨了Envisat雷达数据在洪涝灾害监测工作中的应用,结果表明Envisat ASAR多极化数据在洪水监测中可以起到重要作用,提出了应用中存在的一些问题。     

Inter-comparison study of water level estimates derived from hydrodynamic-hydrologic model and satellite altimetry for a complex deltaic environment

Riverine deltas are hydrologically one of the most active terrestrial bodies supporting an intricate network of rivers, a highly unsteady flow regime, high agricultural productivity and large population centers. Understanding the complex hydrology of riverine deltas is challenging due to the paucity of conventional ground-based measurements on river water levels and flows that result in large spatial and temporal sampling gaps. One way to bridge this sampling issue is to employ hydrodynamic models in combination with remotely-sensed water level elevation data from satellite altimetry in a data assimilation framework. However, a good understanding of the performance of models and altimetry is required beforehand. Using Bangladesh as an example of a complex delta, an inter-comparison study was therefore performed for water level estimates derived from the two methods: 1) satellite altimetry and 2) hydrodynamic-hydrologic modeling framework. The Envisat mission was selected for satellite altimetry-based water level data. For the modeling framework, a calibrated 1-D hydrodynamic model, HEC-RAS, was set up for the major rivers of Bangladesh using in-situ river bathymetry, gaged stream flow and water level data. Envisat water level estimates were generally found to be exceeded by the model-based values by 0.20 m and 1.90 m for Monsoon and dry seasons, respectively. In general, the average RMSE between Envisat and modeled estimates is more than 2.0 m. The closest agreement with altimetry was observed during the high flow Monsoon season over the Brahmaputra river. Envisat estimates are found to disagree most with model-based estimates for small to medium-sized river basins that are mountainous and flashy. This inter-comparison study provides preliminary guidance on the relative weights to assign for each type of estimate when designing a data assimilation scheme for optimal water level prediction in ungaged basins.     

Persistent iceberg groundings in the western Weddell Sea, Antarctica

We use the time-average of a series of satellite synthetic aperture radar (SAR) images from 2005 to 2007 to identify grounded icebergs in the western Weddell Sea. Satellite laser altimetry along repeated ground tracks confirms that regions of high mean backscatter are associated with stationary, tabular icebergs. The altimeter data also provide iceberg freeboard, from which we infer maximum ice draft assuming the lightly-grounded limit and a two-layer density model consistent with a source at Filchner-Ronne Ice Shelf. The maximum iceberg draft agrees very well with the ocean depth at a point where the bathymetry is well constrained by ship soundings. However, for an extensive region near 71°S, south of Larsen C Ice Shelf, the maximum grounding depth for several icebergs reveals the ocean to be locally more than 200 m shallower than in bathymetry products. This previously uncharted bank is expected to have a profound effect on the northward flow of the western Weddell Gyre and the cross-slope transport of offshore warm deep water towards the eastern Antarctic Peninsula ice shelves. Passive microwave data also show that sea-ice concentration is reduced in the vicinity of this group of grounded icebergs, indicating an iceberg influence on ocean/atmosphere heat and freshwater exchanges.     

Envisat-ASAR数据的特点及其在多云多雨地区的应用前景

Envisat是由欧空局发射的一颗先进的极轨对地观测卫星,载有10种传感器,其中有先进的合成孔径雷达ASAR(Advanced Synthetic Aperture Radar)。ASAR工作在C波段,具有主动相控天线系统,5种成像模式,7种成像条带及交替极化成像功能。以获得的广东肇庆地区的ASAR交替极化模式精确分辨率图像为实例,介绍了ASAR数据的特点,分析ASAR图像中建筑物、河流、农田、船舶、林地等几种典型地物的后向散射系数值。结果表明ASAR数据可以广泛应用于多云多雨地区的土地覆盖分类,农作物估产,船只探测和海洋等领域。