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杨志华 《沙漠与绿洲气象(新疆气象)》2014,8(5):48-52
新疆是我国沙尘天气多发区,但是地面测站稀少,使用卫星遥感监测沙尘天气有非常大的优势。利用国家卫星气象中心开发并向各省推广的SMART业务系统,以FY-3B/VIRR为数据源,采用以人机交互方式分析区域沙尘遥感监测方法。以2012年数据为例,对沙尘天气进行了遥感监测,结果表明FY-3B/VIRR数据可有效提取沙尘天气信息,具有较好的沙尘监测评估业务应用前景。 相似文献
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A Modified Becker''s Split-Window Approach for Retrieving Land Surface Temperature from AVHRR and VIRR 总被引：1，自引：0，他引：1 
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下载免费PDF全文 QUAN Weijun CHEN Hongbin HAN Xiuzhen LIU Yonghong YE Caihua 《Acta Meteorologica Sinica》2012,26(2):229-240
In order to provide a long time-series, high spatial resolution, and high accuracy dataset of land surface
temperature (LST) for climatic change research, a modified Becker and Li's split-window approach is pro-
posed in this paper to retrieve LST from the measurements of Advanced Very High Resolution Radiometer
(AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA)-7 to -18 and the Visible and
InfraRed Radiometer (VIRR) onboard FY-3A. For this purpose, the Moderate Resolution Transmittance
Model (MODTRAN) 4.1 was first employed to compute the spectral radiance at the top of atmosphere
(TOA) under a variety of surface and atmosphere conditions. Then, a temperature dataset consists of
boundary temperature Ts (which is one of the input parameters to MODTRAN), and channels 4 and 5
brightness temperatures (T4 and T5) were constructed. Note that channels 4 and 5 brightness tempera-
tures were simulated from the MODTRAN output spectral radiance by convolving them with the spectral
response functions (SRFs) of channels 4 and 5 of AVHRRs and VIRR. The coefficients of modified Becker
and Li's split-window approach for various AVHRRs and VIRR were subsequently regressed based on this
temperature dataset using the least square method. As an example of validation, one AVHRR satellite image
over Beijing acquired at 0312 UTC 27 April 2008 by AVHRR onboard NOAA-17 was selected to retrieve
the LST image using the modified Becker and Li's approach. The comparison between this LST image and
that from the MODIS level-2 LST product provided by the University of Tokyo in Japan indicates that
the correlation coefficient is 0.88, the bias is 0.6 K, and the root mean square deviation (RMSD) is 2.1 K.
Furthermore, about 70% and 37% pixels in the LST difference image, which is the result of retrieved LST
image from AVHRR minus the corresponding MODIS LST image, have the values within ±2 and ±1 K,
respectively. 相似文献
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采用FY-3A/VIRR数据,利用Becker局地分裂窗改进算法反演得到逐日陆表温度 (LST), 对2009年一次高温天气过程进行动态监测, 并分析不同下垫面的热环境变化。结果显示:此过程中可见光红外扫描辐射计 (VIRR) 陆表温度产品在敦煌辐射校正场地两次验证的误差为-0.17 K和1.77 K,与同时间过境的MODIS产品均方根误差为2.64 K,直方图对比陆表温度的频数分布基本一致;对高温天气过程监测发现,此次出现以华北的石家庄、郑州、北京等地和西北地区东部的西安等地为中心的两个陆表温度高值区, 部分地区达到了320.2 K以上;城市剖面资料证实城市热岛现象存在,并发现工矿用地的热岛效应不容忽视,主要是大面积的工矿用地周围植被破坏严重,地表增温更为显著。 相似文献
15.
Satellite retrieval of atmospheric water vapor is intended to further understand the role played by the energy and water cycle to determine the Earth's weather and climate. The algorithm for operational retrieval of total precipitable water (TPW) from the visible and infrared radiometer (VIRR) onboard Fengyun 3A (FY-3A) employs a split window technique for clear sky radiances over land and oceans during both day and night. The retrieved TPW is compared with that from the moderate resolution imaging spectroradiometer (MODIS) onboard the Terra satellite and data from radiosonde observations (RAOB). During the study period, comparisons show that the FY-3A TPW is in general agreement with the gradients and distributions from the Terra TPW. Their zonal mean difference over East Asia is smaller in the daytime than at night, and the main difference occurs in the complex terrain at mid latitude near 30°N. Compared with RAOB, the zonal FY-3A and the Terra TPW have a moist bias at low latitudes and a dry-bias at mid and high latitudes; in addition, the FY-3A TPW performs slightly better in zonal mean biases and the diurnal cycle. The temporal variation of the FY-3A and the Terra TPW generally fits the RAOB TPW with the FY-3A TPW. The FY-3A TPW is more accurate at night, while the Terra TPW is more accurate during the daytime. Comparisons of correlations, root mean square differences and standard deviations indicate that the FY-3A TPW series is more consistent with the RAOB TPW at selected stations. As a result, the FY-3A TPW has some advantages over East Asia in both spatial and temporal dimensions. 相似文献
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以FY-3可见光与红外辐射计（VIRR）为主要数据,利用FY3\VIRR 1、6、10通道数据,以指数法和光谱阈值相结合的多光谱积雪监测算法对2013年阿勒泰地区卫星数据进行积雪监测处理。处理结果与MODIS积雪监测业务产品对比分析得出：利用FY3\VIRR可以实现对研究区的积雪遥感监测,监测结果与现有MODIS积雪监测业务产品较一致,具有可比性。 相似文献
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In this paper,a thin cloud removal method was put forward based on the linear relationships between the thin cloud reflectance in the channels from 0.4 μm to 1.0 μm and 1.38 μm.Channels of 0.66 μm,0.86 μm and 1.38 μm were chosen to extract the water body information under the thin cloud.Two study cases were selected to validate the thin cloud removal method.One case was applied with the Earth Observation System Moderate Resolution Imaging Spectroradiometer(EOS/MODIS) data,and the other with the Medium Resolution Spectral Imager(MERSI) and Visible and Infrared Radiometer(VIRR) data from Fengyun-3A(FY-3A).The test results showed that thin cloud removal method did not change the reflectivity of the ground surface under the clear sky.To the area contaminated by the thin cloud,the reflectance decreased to be closer to the reference reflectance under the clear sky after the thin cloud removal.The spatial distribution of the water body area could not be extracted before the thin cloud removal,while water information could be easily identified by using proper near infrared channel threshold after removing the thin cloud.The thin cloud removal method could improve the image quality and water body extraction precision effectively. 相似文献
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基于RS和GIS的黑龙江省积雪时空变化研究 总被引：1，自引：0，他引：1
以黑龙江省为研究区域,以风云三号气象卫星遥感数据资料为基础,通过对FY－3 A和FY－3 B的VIRR波段特性的深入分析,对2013～2015年多期FY－3A和FY－3B的VIRR遥感影像提取出黑龙江省多期积雪数据,进行黑龙江省积雪时空变化监测研究,结合RS和GIS技术对其进行了分析并得出结论,对了解其时空分布特征及变化规律,对于促进该区的工农业生产和生态环境保护都具有十分重要的意义。 相似文献
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A modified Becker’s split-window approach for retrieving land surface temperature from AVHRR and VIRR 下载免费PDF全文
下载免费PDF全文 In order to provide a long time-series,high spatial resolution,and high accuracy dataset of land surface temperature(LST) for climatic change research,a modified Becker and Li’s split-window approach is proposed in this paper to retrieve LST from the measurements of Advanced Very High Resolution Radiometer(AVHRR) onboard National Oceanic and Atmospheric Administration(NOAA)-7 to-18 and the Visible and InfraRed Radiometer(VIRR) onboard FY-3A.For this purpose,the Moderate Resolution Transmittance Model(MODTRAN) 4.1 was first employed to compute the spectral radiance at the top of atmosphere(TOA) under a variety of surface and atmosphere conditions.Then,a temperature dataset consists of boundary temperature T s(which is one of the input parameters to MODTRAN),and channels 4 and 5 brightness temperatures(T 4 and T 5) were constructed.Note that channels 4 and 5 brightness temperatures were simulated from the MODTRAN output spectral radiance by convolving them with the spectral response functions(SRFs) of channels 4 and 5 of AVHRRs and VIRR.The coefficients of modified Becker and Li’s split-window approach for various AVHRRs and VIRR were subsequently regressed based on this temperature dataset using the least square method.As an example of validation,one AVHRR satellite image over Beijing acquired at 0312 UTC 27 April 2008 by AVHRR onboard NOAA-17 was selected to retrieve the LST image using the modified Becker and Li’s approach.The comparison between this LST image and that from the MODIS level-2 LST product provided by the University of Tokyo in Japan indicates that the correlation coefficient is 0.88,the bias is 0.6 K,and the root mean square deviation(RMSD) is 2.1 K.Furthermore,about 70% and 37% pixels in the LST difference image,which is the result of retrieved LST image from AVHRR minus the corresponding MODIS LST image,have the values within ± 2 and ± 1 K,respectively. 相似文献
20.
该文介绍了卫星观测海表温度 (SST) 算法的发展历程,给出了所用SST算法的回归模型,并在FY-3B/VIRR业务SST算法的基础上进行了改进。基于NOAA-19/AVHRR匹配数据集,进行多算法建模分析及精度评估,白天最优算法为非线性SST (NL) 算法,夜间最优算法为三通道SST (TC) 算法,最优算法的确定与NESDIS/STAR一致。建立2012年8月—2013年3月FY-3B/VIRR匹配数据集,并在此基础上进行多算法回归建模及精度评估,白天和夜间的最优均为NL算法,分析发现夜间TC算法采用匹配数据集版本2(MDB_V2) 时,3.7 μm通道存在类似百叶窗的条带现象。以2012年10—12月FY-3B/VIRR匹配数据集计算回归系数,以2013年1—3月独立样本进行精度评估,与浮标SST相比,NL算法白天和夜间的均方根误差分别为0.41℃和0.43℃。与日平均最优插值海温 (OISST) 相比,NL算法白天和夜间的均方根误差分别为1.45℃和1.5℃; 选择与OISST偏差在2℃以内的样本,NL算法白天和夜间均方根误差分别为0.82℃和0.84℃。 相似文献