MERIS遥感数据特性及应用

中等分辨率成像频谱仪(M ER IS)是搭载于由欧洲空间局(ESA)发射的迄今为止最大的综合性环境卫星ENV ISAT-1上的主要传感器,由法国和荷兰共同研制,是目前水色传感器中最有优势的传感器之一。文中主要介绍了M ER IS遥感数据的特点,与M OD IS、SeaW IFS传感器相比,M ER IS在波段设置与辐射灵敏度等方面都有较大的优势,更适合于海洋水色的应用。针对M ER IS的波段设置,重点介绍了M ER IS数据在海洋水色的应用范围与应用原理,并简要介绍其在大气与陆地上的应用。     

A 10-year wave energy resource assessment and trends of Indonesia based on satellite observations

Wave energy resource assessment and trends around Indonesian's ocean has been carried out by means of analyzing satellite observations. Wave energy flux or wave power can be approximated using parameterized sea states derived from satellite data. Unfortunately, only some surface parameters can be measured from remote sensing satellites, for example for ocean surface waves: significant wave height. Others, like peak wave period and energy period are not available, but can instead be estimated using empirical models. The results have been assessed by meteorological season. The assessment shows clearly where and when the wave power resource is promising around Indonesian's ocean. The most striking result was found from June to August, in which about 30–40 kW/m(the 90 th percentile: 40–60 kW/m, the 99th percentile: 50–70 kW/m) wave power energy on average has been found around south of the Java Island. The significant trends of wave energy at the 95% level have also been studied and it is found that the trends only occurred for the extreme cases, which is the 99th percentile(i.e.,highest 1%). Wave power energy could increase up to 150 W/m per year. The significant wave heights and wave power have been compared with the results obtained from global wave model hindcast carried out by wave model WAVEWATCH III. The comparisons indicated excellent agreements.     

基于主成分分析的ENVISAT ASAR数据在福建省漳州市香蕉园地提取中的应用(英文)

Banana is one of the main economic agrotypes in Zhangzhou, Fujian Province. The multi-temporal ENVISAT ASAR data with different polarization are used to classify the banana fields in this paper. Principal component analysis (PCA) was applied for six pairs of ASAR dual-polarization data. For its large leaves, banana has high backscatter. So the value of banana fields is high and shows very bright in the 1st component, which makes it much easier for banana fields extraction. Dual-polarization data provide more information, and the VV and VH backscatter of banana show different characters with other land covers. Based on the analysis of the radar signature of banana fields and other land covers and the 1st component, banana fields are classified using object-oriented classifier. Compared to the field survey data and ASTER data, the accuracy of banana fields in the study area is 83.5%. It shows that the principal component analysis provides the useful information in SAR images analysis and makes the extraction of banana fields easier. Supported by the Program for New Century Excellent Talents in University (NCET-05-0573), Fujian Science and Technology Project (No.2006I0018), the Science Project of the Education Department of Fujian Province(No. 2006F5022).     

Evaluation of ENVISAT ASAR data for sea surface wind retrieval in Hong Kong coastal waters of China

The C-band wind speed retrieval models, CMOD4, CMOD - IFR2, and CMOD5 were applied to retrieval of sea surface wind speeds from ENVISAT （European environmental satellite） ASAR （advanced synthetic aperture radar） data in the coastal waters near Hong Kong during a period from October 2005 to July 2007. The retrieved wind speeds are evaluated by comparing with buoy measurements and the QuikSCAT （quick scatterometer） wind products. The results show that the CMOD4 model gives the best performance at wind speeds lower than 15 m/s. The correlation coefficients with buoy and QuikSCAT winds are 0.781 and 0.896, respectively. The root mean square errors are the same 1.74 m/s. Namely, the CMOD4 model is the best one for sea surface wind speed retrieval from ASAR data in the coastal waters near Hong Kong.     

ENVISAT测高数据波形重跟踪分析研究

对卫星测高技术中的波形重跟踪技术及其算法进行了详细分析讨论．同时分析了波形重跟踪中最小二乘解初值及权的确定,根据ENVISAT的SGDR波形数据,利用波形重跟踪技术研究了开阔海域上的距离改正情况(一般距离改正为20～30cm)。结果表明,重跟踪改正后的精度,18Hz距离优于1Hz距离。     

基于高斯曲线拟合-FFT方法的南海风场反演

海面风场是海洋学的基本参量,获取海面风场对了解海洋的物理过程以及海洋与大气之间的相互作用至关重要。宽阔的海域面积及复杂的海面状况通常使南海海面上的风场信息很难被及时获取。ENVISAT ASAR是一种全天候全天时监测海面的微波雷达传感器,可实时获取海面风场数据。本文基于已有ASAR数据对南海海面风场进行反演实验,首先将结合高斯曲线拟合的FFT风向反演方法应用于南海风向反演,并参考Cross-Calibrated Multi-Platform （CCMP）风场数据去除180o方向模糊获得海面风向。然后,将高斯曲线拟合-FFT风向与传统的峰值-FFT风向进行对比,最后将准确率较高的高斯曲线拟合-FFT风向分别输入CMOD4模型和CMOD5模型获得海面风速大小。实验结果与CCMP参考数据的比较结果表明,在风条纹不明显的情况下,利用结合高斯曲线的FFT风向反演方法和CMOD4模型风速反演方法可有效地进行南海海面风场反演。该成果对利用SAR数据实时获取南海大面积海面风场信息,尤其是观测点缺乏海域的风场信息,具有重要的指导意义。     

基于 D-InSAR 技术的当雄地震形变场提取研究

随着D-InSAR技术在同震形变量测方面的优势日益突出,文中以2008年10月6日当雄Mw6.3级地震为对象,采用ENVISAT搭载的ASAR传感器c波段在图像模式下的5景level 0级影像,以90 m分辨率的SRTM DEM作为外部DEM,使用GAMMA软件采用二轨差分干涉测量的方法获取当雄地震同震形变场,并对其进行分析,确定震中位置为90.372°E,29.734°N,得到同震垂直形变约为33cm,形变量精度达到厘米级。     

ENVISAT-ASAR数据产品介绍与数据处理

因ASAR（Advanced Synthetic Aperture Radar）具有全天候、全天时、穿透性强、多种入射角、宽幅成像、多模式、多极化等优势,而成为遥感研究和应用的热点。它是当今最先进的合成孔径雷达数据。本文对ENVISAT的ASAR数据类型进行介绍,并利用欧空局开发的雷达处理工具NEST（Next ESA SAR Toolbox）软件包和ENVI软件对雷达数据进行辐射定标、影像校正和图像滤波处理,为ASAR数据处理方法提供了有益补充。     

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基于SAR数据的南极冰山分布监测

随着全球气候变暖,冰架崩解事件的发生愈益频繁.冰架崩解产生的冰山是南极冰盖-冰架-海洋系统中活跃的组成部分,冰山的运动特征和时空分布对南大洋洋流循环、海洋生态以及水文系统有着非常重要的影响.因此利用卫星遥感监测冰山运动与变化信息,探究冰山崩解和消融过程,研究南极冰山分布,以及冰山和周围海洋环境之间的相互作用机制,是理解南极冰山变化与全球气候变化之间关系的关键.本文利用覆盖全南极海岸线的ENVISAT ASAR影像,基于简译软件的面向对象的多尺度图像分割算法实现了全南极近岸海域冰山对象的提取.利用2006年8月63期ENVISAT ASAR影像提取了32 267座面积大于0.06 km²的冰山,统计了冰山空间分布特征,研究发现南极小型冰山在全南极淡水输入中扮演着重要的作用.