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21.
在传统空间辐射计方法基础上,将对流层中水汽垂直分层效应集成到校正模型中,提出一种改进的InSAR大气延迟相位校正方法。为验证改进方法的可行性,利用MERIS近红外水汽产品去除北京地区地面沉降InSAR监测中的大气延迟相位。以陆态网络GNSS站点监测结果为基准,验证改进的大气校正方法的监测精度。改进的大气校正方法、空间辐射计校正法和未校正的InSAR监测结果与陆态网络GNSS站点监测结果对比显示,均方根误差分别为0.388 cm、0.603 cm、0.685 cm,表明改进的方法相比于未校正和传统方法具有更高的精度,能有效削弱干涉图中的大气延迟相位误差。 相似文献
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叶绿素a荧光遥感研究进展 总被引：11，自引：0，他引：11
继叶绿素a反演的“蓝绿比值法”后,叶绿素a荧光遥感成为海水叶绿素a浓度反演的重要方法,对提高二类水体和赤潮水体的叶绿素a浓度的反演精度效果明显。本文回顾了人们对水体叶绿素a荧光的认识、测量和研究的历史过程,介绍了荧光产生的生物学机理以及它随叶绿素a浓度的正相关和“红移现象”等主要光谱特征。本文还总结了荧光量子产量、不同藻种生理状态、水体其他物质及大气的吸收等多种因素对叶绿素a荧光遥感的影响。基于对叶绿素a荧光光谱特征和影响因素的认识,人们相继建立了两种荧光遥感方法———基线荧光高度法和归一化荧光高度法。对于前景广阔的叶绿素荧光遥感领域,人们正进行着更深入的研究与探索,积累更多的现场数据和卫星同步数据,逐步完善和改进反演模型。 相似文献
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Soft-classification-based methods for estimating chlorophyll-a concentration (Cchla) by satellite remote sensing have shown great potential in turbid coastal and inland waters. However, one of the most important water color sensors, the MEdium Resolution Imaging Spectrometer (MERIS), has not been applied to the study of turbid or eutrophic lakes. In this study, we developed a new soft-classification-based Cchla estimation method using MERIS data for the highly turbid and eutrophic Taihu Lake. We first developed a decision tree to classify Taihu Lake into three optical water types (OWTs) using MERIS reflectance data, which were quasi-synchronous (±3 h) with in situ measured Cchla data from 91 sample stations. Secondly, we used MERIS reflectance and in situ measured Cchla data in each OWT to calibrate the optimal Cchla estimation model for each OWT. We then developed a soft-classification-based Cchla estimation method, which blends the Cchla estimation results in each OWT by a weighted average, where the weight for each MERIS spectra in each OWT is the reciprocal value of the spectral angle distance between the MERIS spectra and the centroid spectra of the OWT. Finally, the soft-classification based Cchla estimation algorithm was validated and compared with no-classification and hard-classification-based methods by the leave-one-out cross-validation (LOOCV) method. The soft-classification-based method exhibited the best performance, with a correlation coefficient (R2), average relative error (ARE), and root-mean-square error (RMSE) of 0.81, 33.8%, and 7.0 μg/L, respectively. Furthermore, the soft-classification-based method displayed smooth values at the edges of OWT boundaries, which resolved the main problem with the hard-classification-based method. The seasonal and annual variations of Cchla were computed in Taihu Lake from 2003 to 2011, and agreed with the results of previous studies, further indicating the stability of the algorithm. We therefore propose that the soft-classification-based method can be effectively used in Taihu Lake, and that it has the potential for use in other optically-similar turbid and eutrophic lakes, and using spectrally-similar satellite sensors. 相似文献
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基于MERIS数据的永久散射体处理中大气改正方法研究 总被引：1，自引：0，他引：1
分析了永久散射体PS(Permanent Scatlerers)处理中进行大气改正的必要性,介绍了大气改正的方法,指出现有方法存在的不足; 结合利用MERIS数据进行大气改正的优势,提出了基于MERIS数据的PS处理中大气改正的模型.采用青藏高原北麓河实验区ASAR数据对该模型进行验证的结果表明,该方法能够有效提高永久散射体处理中大气改正的可信性,从而使得利用相对较少的ASAR数据进行PS分析成为可能. 相似文献
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Comparative Analysis of Chlorophyll-a Distribution from SeaWiFS,MODIS-Aqua,MODIS-Terra and MERIS in the Arabian Sea 总被引：1，自引：0，他引：1
The variability of Chlorophyll-a (Chl-a) distribution derived from MODIS (on Aqua and Terra platforms) and MERIS sensors have been compared with SeaWiFS data in the Arabian Sea. MODIS Aqua has overestimated the SeaWiFS Chl-a within 25–32% in the coastal turbid (eutrophic) waters and underestimated in open ocean waters with error within 20%. However, there is no significant bias (?0.1 on log-scale) observed as the slope is well within 0.97-1.1 (log transformed). MODIS-Terra has underestimated the Chl-a concentration in open ocean waters by about 29–31%, which is higher than MODIS-Aqua. MODIS-Terra is observed to be more accurate than MODIS-Aqua in the coastal waters. MERIS is overestimating the SeaWiFS Chl-a with log RMS error of ～0.15 and log bias of ～0.13–0.2. The differences in the Chl-a estimates between each sensor are possibly due to differences in the sensor design, bio-optical algorithms and also due to the time differences between the satellites over passes. We have examined that the MERIS is performing similar to SeaWiFS and the MODIS-Aqua (Terra) data are reliable in open ocean (coastal) waters. However, Chl-a retrieval algorithms need to be improved especially for coastal turbid waters to continue with SeaWiFS data for long-term studies. 相似文献
26.
Sentinel-2 is planned for launch in 2014 by the European Space Agency and it is equipped with the Multi Spectral Instrument (MSI), which will provide images with high spatial, spectral and temporal resolution. It covers the VNIR/SWIR spectral region in 13 bands and incorporates two new spectral bands in the red-edge region, which can be used to derive vegetation indices using red-edge bands in their formulation. These are particularly suitable for estimating canopy chlorophyll and nitrogen (N) content. This band setting is important for vegetation studies and is very similar to the ones of the Ocean and Land Colour Instrument (OLCI) on the planned Sentinel-3 satellite and the Medium Resolution Imaging Spectrometer (MERIS) on Envisat, which operated from 2002 to early 2012. This paper focuses on the potential of Sentinel-2 and Sentinel-3 in estimating total crop and grass chlorophyll and N content by studying in situ crop variables and spectroradiometer measurements obtained for four different test sites. In particular, the red-edge chlorophyll index (CIred-edge), the green chlorophyll index (CIgreen) and the MERIS terrestrial chlorophyll index (MTCI) were found to be accurate and linear estimators of canopy chlorophyll and N content and the Sentinel-2 and -3 bands are well positioned for deriving these indices. Results confirm the importance of the red-edge bands on particularly Sentinel-2 for agricultural applications, because of the combination with its high spatial resolution of 20 m. 相似文献
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J. Dash 《International journal of geographical information science》2013,27(8):929-939
Large concentrations of herbicide were sprayed onto the forests of southern Vietnam in the 1960s and early 1970s. Over 30 years later, many of these contaminated forests have regained full canopy cover, albeit with reduced chlorophyll content. The European Space Agency produces an operational product for the estimation of terrestrial chlorophyll content over large areas of terrain. This product uses data recorded by the Medium Resolution Imaging Spectrometer (MERIS) on Envisat and is called the MERIS Terrestrial Chlorophyll Index (MERIS). The relationship between historical levels of herbicide contamination and contemporary MTCI was strong (R = 0.86) and negative, with high levels of herbicide contamination being associated (via low levels of chlorophyll concentration) with low levels of MTCI. This is the first published study to demonstrate a relationship between MTCI and a surrogate for chlorophyll content. The next stage of this research is to build on the strength of this relationship and use contemporary MTCI to estimate historical herbicide levels during the 1960s and 1970s across southern Vietnam. 相似文献
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利用光学遥感反演盐度,可以充分利用遥感数据的空间代表性,以及目前高分率遥感数据的高时空精度。本文利用MERIS(Medium Resolution Imaging Spectrometer)300 m数据,以干旱区的博斯腾湖(博湖)为例,探讨了光学遥感数据反演低盐湖泊水体盐度的可行性。结果显示:在开都河入流影响的博湖西南角,存在光学遥感反演盐度利用的黄色物质(CDOM)与盐度的反比关系,但相关性不高,而且在博湖区域不同时间、不同区域CDOM与盐度的关系都不同。博湖盐度低于3 g·L-1,而遥感数据计算盐度的精度约为1.1 psu,因而用光学遥感数据计算博湖盐度的误差太大。博湖本身CDOM与盐度关系的时空异质性以及相关性不高,目前光学遥感反演精度有限,因此,在博湖用光学遥感数据反演整个湖区的盐度有困难。用光学数据反演水体盐度要求盐度足够高,盐度和CDOM存在梯度,并满足CDOM扩散守恒,因此用光学遥感反演低盐湖泊水体盐度较为困难。 相似文献