共查询到20条相似文献，搜索用时 15 毫秒
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《Geoscience and Remote Sensing Letters, IEEE》2007,4(4):542-546
This letter uses a large ocean satellite data set to document relationships between Ku-band radar backscatter (sigmao) of the sea surface, near-surface wind speed (U), and ocean wave height (SWH). The observations come from satellite crossovers of the Tropical Rainfall Mapping Mission (TRMM) Precipitation Radar (PR) and two satellite altimeters, namely: 1) Jason-1 and 2) ENVISAT. At these nodes, we obtain TRMM clear-air normalized radar cross-section data along with coincident altimeter-derived significant wave height. Wind speed estimates come from the European Centre for Medium-Range Weather Forecast. TRMM PR is the first satellite to measure low incidence Ku-band ocean backscatter at a continuum of incidence angles from 0deg to 18deg. This letter utilizes these global ocean data to assess hypotheses developed in past theoretical and field studies. 相似文献
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由卫星测高数据观测到的印度洋海啸波高 总被引：5，自引：1，他引：4
本文介绍了利用卫星测高资料测定的印度洋地震引起的海啸波高的研究成果 ,以及卫星测高数据在对海啸灾害进行预测的应用价值。通过卫星雷达测高可观测到沿卫星星下点轨迹的相距几公里的点上的海面高 ,还提供了特别有价值的对海啸波的连续观测结果 相似文献
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Jianhua Wan Qinting Sun Shanwei Liu Yinlong Li 《Journal of the Indian Society of Remote Sensing》2018,46(12):1939-1947
The characteristics of sea-level change in the China Sea and its vicinity are studied by combining TOPEX/Poseidon (T/P), Jason-1, Jason-2, and Jason-3 altimeter data. First, the sea-surface height is computed by using monthly data via collinear adjustment, regional selection, and crossover adjustment. The sea-level anomaly (SLA) from October 1992 to July 2017 is calculated based on the difference that is obtained by the value derived from the inverse distance weighting method to interpolate the CNES_CLS15 model value at a normal point. By analyzing the satellite data at the same time in orbit, three mean bias groups over the China Sea and its vicinity are obtained: the difference between T/P and Jason-1 is ??11.76 cm, the difference between Jason-1 and Jason-2 is 9.6 cm, and the difference between Jason-2 and Jason-3 is 2.42 cm. To establish an SLA series for 25 years in the study area, the SLAs are corrected. Mean rate of sea-level rise of the Bohai Sea, Yellow Sea, East China Sea, and South China Sea of 4.87 mm/a, 2.68 mm/a, 2.88 mm/a, and 4.67 mm/a, respectively, is found by analyzing the series of SLAs. 相似文献
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S. Chander 《国际地球制图》2016,31(2):158-175
Satellite with ARgos and ALtika (SARAL) altimeter includes the ALTIKA payload, a 35.75 GHz Ka band radar altimeter. High pulse repetition frequency of SARAL (4 KHz) satellite provides better along-track information. Jason-1/2 data have been extensively utilized as a follow-up of TOPEX/Poseidon altimeter data for its accurate measurements of the sea surface heights, particularly for geodetic mission of Jason-1. In this study, we have compared SARAL and Jason-1/2 altimetry-derived classical and residual geoids over the Indian offshore using Rapp’s, EGM96 and EGM08 gravity model coefficients, which are of interest for better understanding of geological and structural evolution/interpretation. SARAL and Jason-1/2 data have also been used over the two prominent geological features over the Indian offshore, namely the Bombay High in the western offshore and the 85°E Ridge in the Bay of Bengal. The SARAL altimetry-derived geoids could delineate these major geological/structural features with distinct residual geoidal lows. 相似文献
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介绍了国际上InSAR观测值大气改正方法最新的研究进展，应用实例证明了由于大气（尤其是水汽）的影响，传统的InSAR形变量的监测精度往往只能限制在cm级；而利用GPS数据，通过基于地形的GPS扰动模型（GTTM），大幅度削弱了大气对干涉影像的影响，并成功地探测出了美国洛杉矾地区明显的季节性地表形变，形变量精度可提高到5mm左右。通过与GPS／MODIS集成大气改正模型的结果的比较表明，GTTM和GPS／MODIS两种大气改正模型在削弱InSAR观测值大气水汽影响方面具有很强的互补性。 相似文献
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Jean-François Crétaux Stephane Calmant Vladimir Romanovski Anton Shabunin Florent Lyard Muriel Bergé-Nguyen Anny Cazenave Fabrice Hernandez Felix Perosanz 《Journal of Geodesy》2009,83(8):723-735
Altimetry missions such as Topex/Poseidon, Jason-1, GFO and ENVISAT have been widely used in the continental domain over lakes,
rivers and wetland although they were mostly dedicated to oceanic studies. Knowledge of the instrumental biases is a key issue.
Numerous sites have been dedicated to calibration purposes, either in the oceanic domain (Harvest offshore platform in California,
Corsica, Bass Strait in Australia) or over lakes (Lake Erie in United States). A new site (Lake Issykkul in Kirghizstan) is
proposed for calibration in the continental domain. This lake is covered by past (T/P) and current radar altimetry satellites
(Jason-1, T/P, GFO, and ENVISAT). Several in situ water levels and local meteorological variables are available at the site.
Located in a mountainous area, it offers an opportunity for calibration far away from all other existing sites and very different
environment contexts. Two GPS campaigns have been conducted on the lake in 2004 and in 2005. They consisted of cruises with
stations installed onboard a boat following the satellite ground tracks, and onshore settings. This enabled estimating a bias
for each altimeter and each tracking algorithm available. Biases obtained for Envisat, GFO, T/P and Jason-1 using the default
ocean tracker (respectively, 48.1 ± 6.6, 7.5 ± 4.0, 0 ± 4.3 and 7.0 ± 5.5 cm) agree with biases published at the other calibration
sites. For Jason-1, there is a significant disagreement with results obtained in the ocean field (7 cm instead of 13 cm) but
is coherent with bias obtained on the Lake Erie site. Erroneous estimates of the sea state bias correction from non-oceanic-like
waveforms is discussed as a possible explanation. Errors in the ionospheric, wet and dry tropospheric corrections for the
continental domain are also highlighted and quantified. 相似文献
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P C S Devara P E Raj G Pandithurai R S Maheskumar K K Dani 《Journal of the Indian Society of Remote Sensing》1997,25(4):225-238
Lidar has evolved as one of the powerful and versatile techinqne for atmospheric monitoring and geophysical and hydrographic studies from different observational platforom. This paper discusses the recent advances that have taken place in the lidar technology for rnulti-dimensional atmospheric, hydragraphic and vegetation monitoring together with the results of some specific atmospheric studies carried our for the past ten years using the lider systems built at the Indian Institute of Tropical Meteorotogy (IITm) Pune. 相似文献
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使用测高卫星Jason-2传感器地球物理数据记录（sensor geophysical data record,SGDR）的近海海面高观测数据,基于最大似然估计4参数法,对波形数据进行重跟踪。考虑到星下点沿轨方向前后相邻海面高观测值中高频改正信号具有相关性的特征,提出了确定海面高的最优高斯低通滤波半径选择的技术方法,即对星下点沿轨方向观测值进行差分计算,形成差分数据序列,根据序列的相关系数性来确定滤波半径。对于SGDR数据,若对其进行低通滤波,建议滤波半径选为2 km,既可抑制沿轨海面高数据的高频误差,又可保证该数据没有被过度平滑。研究成果可为充分利用卫星测高数据建立高精度近海海面高模型提供参考,进而促进高精度陆海无缝垂直基准的技术体系建设。 相似文献
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Anoop Kumar Mishra Rakesh M. Gairola Vijay K. Agarwal 《Journal of the Indian Society of Remote Sensing》2012,40(1):65-74
In the present study an attempt has been made to improve the rainfall estimation technique developed recently by Mishra et
al. (2009a, 2009b) based on KALPANA and Tropical Rainfall Measuring Mission (TRMM)-Precipitation Radar (PR) data over the Indian land and oceanic
region. The algorithm for rainfall estimation was basically based on synergistically analyzing the thermal infra-red radiances
from Kalpana/INSAT data along with the high resolution, horizontal and vertical rainfall estimates from PR. Presently the
augmentation is based on the data base of precipitable water and relative humidity from National Centre for Environmental
Prediction-Global forecast System (NCEP-GFS) data as a background field to correct for the biases in earlier algorithm. The
algorithm is tested for many case studies of monsoon rainfall over India and adjoining oceanic regions. The rainfall from
the present scheme is compared with the standard TRMM-3B42 rain product. The validation with the Automatic Weather Station
(AWS) rain gauge and the Global Precipitation and Climatology Project (GPCP) version 2 rain products shows that the present
scheme is able to retrieve the rainfall with a very good accuracy. These studies are aimed at the rainfall retrievals in near
future from both INSAT-3D and Megha-Tropiques, IR and MW imagers respectively. 相似文献
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利用模拟数据对Autonomous Atmospheric Compensation(AAC)和In-scene Atmospheric Compensation(ISAC)这两种高光谱热红外数据大气校正方法进行了对比和分析。结果显示,在满足方法适用条件情况下,AAC方法大气校正精度较高,除湿热的热带大气外,大气透过率的反演误差小于0.02,大气上行辐射的误差小于0.004W.m-2.sr-1.cm;而ISAC方法精度较低,透过率误差在0.05至0.3之间,上行辐射误差在0.003W.m-2.sr-1.cm至0.035W.m-2.sr-1.cm之间变化,误差随大气水汽含量增加而增加。大气非均一性对大气校正精度影响分析表明,AAC方法大气校正精度受大气非均一性影响显著。因此,需从高光谱数据光谱信息出发,发展针对低空间分辨率高光谱热红外数据的大气校正方法,以克服现有方法大气水平均一假设的不足。 相似文献
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Aerosol and water vapour are very important element in the Earth’s climate system which has direct role in the Earth’s radiation budget. In this paper the seasonality, latitudinal distribution and the relationship of aerosol optical thickness (AOD) and water vapour (WV) using MODIS Level 3 monthly data from 2001 to 2008 are analysed. The analysis shows that AOD (0.55 μm) values reach maximum during southwest monsoon and remain minimum during northeast monsoon period. The Equatorial Indian Ocean shows minimum AOD (0.115 to 0.153) throughout the year compared to Arabian Sea (0.208 to 0.613) and Bay of Bengal (0.214 to 0.351). Arabian Sea shows high variation and maximum value of AOD compared to Bay of Bengal and Equatorial Indian Ocean. During southwest monsoon WV over Bay of Bengal was found higher in concentration compared to Arabian Sea and Equitorial Indian Ocean throughout the study period. Comparison between Arabian Sea (2.98 cm to 5.07 cm) and Bay of Bengal (3.49 cm to 5.94 cm) shows that WV concentration is less in Arabian Sea throughout the year. The analysis of correlation between WV and AOD was found to be inconsistent. However, AOD and WV shows a strong positive correlation for whole year (Mean R2 =0.90) in the Equitorial Indian Ocean region except in the months of January, February and March. In general, the correlation between WV and AOD is found to be strongly positive for oceanic aerosol (sea salt) in low water vapour condition. 相似文献
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对流层延迟差异影响合成孔径雷达干涉测量技术(InSAR)形变测量精度;水汽的变化影响天气变化.对流层延迟与水汽具有较好的对应,因此有必要开展全球导航卫星系统(GNSS)对流层延迟的插值研究.以京津冀地区为例,针对GNSS对流层延迟,开展对流层延迟的空间插值研究.首先开展了GNSS对流层延迟与水汽的比较分析,两者存在显著正相关特性,相关性超过91.7%,论证了对流层延迟取代水汽的可行性.然后利用反距离权重法对京津冀地区2016年9月至2017年8月的12组GNSS测站对流层延迟进行空间插值,通过提取插值点对流层延迟与GNSS站点对流层延迟比较验证空间插值精度.全年数据平均偏差最大为1.12cm,均方根误差最大为0.89cm;未发生降水过程平均偏差最大为1.25cm,均方根误差最大为0.82cm;发生降水过程平均偏差最大为1.08cm,均方根误差最大为1.38cm.京津冀平原区域的GNSS对流层延迟空间插值结果精度满足气象等应用要求,可为气象预报和InSAR大气校正提供参考. 相似文献
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利用Jason-3星载GPS观测数据,采用简化动力学方法和运动学方法对Jason-3卫星进行精密定轨研究. 通过载波相位残差、重叠轨道对比、参考轨道对比和卫星激光测距(SLR)轨道检核四种方式评定轨道精度. 计算相位残差均方根(RMS)值,简化动力学轨道的RMS值在0.7～0.8 cm,运动学轨道的RMS值在0.50～0.55 cm;简化动力学轨道重叠部分径向RMS值达到0.32 cm,运动学轨道重叠部分径向RMS值达到1.12 cm;与国际DORIS服务(IDS)官方提供的参考轨道对比,简化动力学轨道径向精度达到1.47 cm,运动学轨道径向精度达到4.36 cm;利用SLR观测数据进行核验,简化动力学轨道精度整体优于2.1 cm,运动学轨道精度整体优于3.3 cm. 通过实验证明:Jason-3卫星的简化动力学轨道和运动学轨道的精度均达到cm级. 相似文献
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The DORIS Doppler measurements collected by Jason-1 are abnormally perturbed by the influence of the South Atlantic Anomaly (SAA). The DORIS ultra-stable oscillators on-board Jason-1 are not as stable as they should be; their frequency is sensitive both to the irradiation rate and to the total irradiation encountered in orbit. The consequence is that not only are the DORIS measurement residuals higher than they ought to be, but also large systematic positioning errors are introduced for stations located in the vicinity of the SAA. In this paper, we present a method that has been devised to obtain a continuous observation of Jason-1 frequency offsets. This method relies on the precise determination of the station frequency and troposphere parameters via the use of other DORIS satellites. More than 3 years of these observations have then been used to construct a model of response of the oscillators of Jason-1 to the SAA. The sensitivity of the Jason-1 oscillators to the SAA perturbations has evolved over time, multiplied by a factor of four between launch and mid-2004. The corrective performances of the model are discussed in terms of DORIS measurement residuals, precise orbit determination and station positioning. The average DORIS measurement residuals are decreased by more than 7 % using this model. In terms of precise orbit determination, the 3D DORIS-only orbit error decreases from 5 to 4.2 cm, but the DORIS+SLR orbit error is almost unaffected, due to the already good quality of this type of orbit. In terms of station positioning, the model brings down the average 3D mono-satellite monthly network solution discrepancy with the International Terrestrial Reference Frame ITRF2000 from 11.3 to 6.1 cm, and also decreases the scatter about that average from 11.3 to 3.7 cm. The conclusion is that, with this model, it is possible to re-incorporate Jason-1 in the multi-satellite geodetic solutions for the DORIS station network. 相似文献
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Rahul Nigam Bimal Kumar Bhattacharya Keshav R. Gunjal N. Padmanabhan N. K. Patel 《Journal of the Indian Society of Remote Sensing》2012,40(1):1-9
To study impact of climate change on vegetation time series vegetation index has a vital role to know the behaviour of vegetation
dynamics over a time period. INSAT 3A CCD (Charged Couple Device) is the only geostationary sensor to acquire regular coverage
of Asia continent at 1 km × 1 km spatial resolution with high temporal frequency (half-an-hour). A formulation of surface
reflectances in red, near infrared (NIR), short wave infrared (SWIR) and NDVI from INSAT 3A CCD has been defined and integrated
in the operational chain. The atmospheric correction of at-sensor reflectances using SMAC (Simple Model for Atmospheric Correction)
model improved the NDVI by 5–40% and also increased its dynamic range. The temporal dynamics of 16-day NDVI composite at 0500
GMT for a growing year (June 2008–March 2009) showed matching profiles with reference to global products (MODIS TERRA) over
known land targets. The root mean square deviation (RMSD) between the two was 0.14 with correlation coefficient (r) 0.84 from
200 paired datasets. This inter-sensor cross-correlation would help in NDVI calibration to add continuity in long term NDVI
database for climate change studies. 相似文献
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在Brown-Hayne模型基础上,利用迭代最小二乘算法实现了回波波形参数的重跟踪,同时利用重心偏移算法(OCOG)、阈值算法对Jason-2 卫星的波形数据在中国渤海、黄海、东海、南海4个海域开展了波形重跟踪试验。试验表明,在4个海域,Brown-Hayne模型法获得的波形重跟踪结果相比较于阈值法、OCOG算法与法国空间局(CNES)公布结果最为一致,相互较差的标准差约2 cm左右。50%阈值算法获得的波形重跟踪结果相比较于其它阈值精度更优,与CNES比较其标准差在3~6 cm,但存在4~10 cm的系统偏差。OCOG算法获得的结果存在较大误差,但其结果可作为Brown-Hayne模型解算的初始值。当卫星地面轨迹靠近大陆时,波形重跟踪获得的海面高改正量会较宽阔海域增大,其中南海区域的海面高改正量最大,可达1 m,其原因可能是卫星地面轨迹经过了西沙群岛,雷达回波波形受到了一定的影响。 相似文献