An inter-comparison of soil moisture data products from satellite remote sensing and a land surface model

Significant advances have been achieved in generating soil moisture (SM) products from satellite remote sensing and/or land surface modeling with reasonably good accuracy in recent years. However, the discrepancies among the different SM data products can be considerably large, which hampers their usage in various applications. The bias of one SM product from another is well recognized in the literature. Bias estimation and spatial correction methods have been documented for assimilating satellite SM product into land surface and hydrologic models. Nevertheless, understanding the characteristics of each of these SM data products is required for many applications where the most accurate data products are desirable. This study inter-compares five SM data products from three different sources with each other, and evaluates them against in situ SM measurements over 14-year period from 2000 to 2013. Specifically, three microwave (MW) satellite based data sets provided by ESA's Climate Change Initiative (CCI) (CCI-merged, -active and -passive products), one thermal infrared (TIR) satellite based product (ALEXI), and the Noah land surface model (LSM) simulations. The in-situ SM measurements are collected from the North American Soil Moisture Database (NASMD), which involves more than 600 ground sites from a variety of networks. They are used to evaluate the accuracies of these five SM data products. In general, each of the five SM products is capable of capturing the dry/wet patterns over the study period. However, the absolute SM values among the five products vary significantly. SM simulations from Noah LSM are more stable relative to the satellite-based products. All TIR and MW satellite based products are relatively noisier than the Noah LSM simulations. Even though MW satellite based SM retrievals have been predominantly used in the past years, SM retrievals of the ALEXI model based on TIR satellite observations demonstrate skills equivalent to all the MW satellite retrievals and even slightly better over certain regions. Compared to the individual active and passive MW products, the merged CCI product exhibits higher anomaly correlation with both Noah LSM simulations and in-situ SM measurements.     

星载GPS观测数据预处理模型研究

星载GPS不同于地基GPS。为了进行基于星载GPS的低轨卫星精密定轨和地球重力场模型解算,本文研究了星载GPS观测数据的钟差改正、整周模糊度解算、周跳探测、卫星跟踪点改正、GPS天线相位中心偏移和改正等的模型,给出了对应的处理公式和处理过程。     

Calibration of satellite gradiometer data aided by ground gravity data

Parametric least squares collocation was used in order to study the detection of systematic errors of satellite gradiometer data. For this purpose, simulated data sets with a priori known systematic errors were produced using ground gravity data in the very smooth gravity field of the Canadian plains. Experiments carried out at different satellite altitudes showed that the recovery of bias parameters from the gradiometer “measurements” is possible with high accuracy, especially in the case of crossing tracks. The mean value of the differences (original minus estimated bias parameters) was relatively large compared to the standard deviation of the corresponding second-order derivative component at the corresponding height. This mean value almost vanished when gravity data at ground level were combined with the second-order derivative data set at satellite altitude. In the case of simultaneous estimation of bias and tilt parameters from ∂² T/∂z ²“measurements”, the recovery of both parameters agreed very well with the collocation error estimation. Received: 10 October 1996 / Accepted 25 May 1998     

重力卫星加速度数据的插值算法研究

阐述拉格朗日插值法和牛顿插值法的原理,详细地推导其一次,二次微分通用公式,并分别利用推导出来的微分公式对卫星星历模拟数据进行了相应的插值计算,得到对应的卫星加速度数据.通过比较不同公式的计算结果,验证一次、二次微分公式的正确性,并得到一些有益的结论.     

视频卫星数据的运动车辆提取

针对新兴的视频卫星数据在道路监控中应用研究较少的问题,该文提出了一种基于特征的视频卫星数据运动车辆提取优化算法。以SkySat-1卫星获取的Las Vegas地区的视频数据为实验数据,采用传统帧差法与阈值法进行运动车辆提取,验证了该方法对视频卫星数据处理的有效性,同时在此基础上根据空间特征信息界定出道路以内的感兴趣区域,进一步根据车辆的几何特征信息对感兴趣区域的疑似车辆目标进行筛选。实验结果表明:所提算法在提取精度和完整度上明显优于基于像素的帧差法与阈值法的提取结果。     

Wheat crop production estimation using satellite data

This paper reports acreage, yield and production forecasting of wheat crop using remote sensing and agrometeorological data for the 1998–99 rabi season. Wheat crop identification and discrimination using Indian Remote Sensing (IRS) ID LISS III satellite data was carried out by supervised maximum likelihood classification. Three types of wheat crop viz. wheat-1 (high vigour-normal sown), wheat-2 (moderate vigour-late sown) and wheat-3 (low vigour-very late sown) have been identified and discriminated from each other. Before final classification of satellite data spectral separability between classes were evaluated. For yield prediction of wheat crop spectral vegetation indices (RVI and NDVI), agrometeorological parameters (ET_max and TD) and historical crop yield (actual yield) trend analysis based linear and multiple linear regression models were developed. The estimated wheat crop area was 75928.0 ha. for the year 1998–99, which sowed ?2.59% underestimation with land record commissioners estimates. The yield prediction through vegetation index based and vegetation index with agrometeorological indices based models were 1753 kg/ha and 1754 kg/ha, respectively and have shown relative deviation of 0.17% and 0.22%, the production estimates from above models when compared with observed production show relative deviation of ?2.4% and ?2.3% underestimations, respectively.     

基于IGS超快星历的GPS钟差线性预报分析

本文在分析IGS超快星历卫星钟差的基础上,首先分析分别采用线性模型和二次多项式模型,利用实际观测值得到的预报值与IGS提供的超快预报值进行比较分析。在此基础上,利用实际观测的超快卫星钟差拟合得到线性模型分别预报后一天和后两天的钟差,分别利用第一天和第二天的实际钟差观测资料拟合得到的线性模型预报第三天的卫星钟差,并与IGS最终钟差产品进行比较分析。得出一些有益的结论与同行商榷。     

Method for evaluating real-time GNSS satellite clock offset products

Real-time satellite clock offset products are frequently utilized in navigation and positioning service fields. The precision of such products is a key issue for their application. The evaluation methods existed for satellite clock offset products are mostly based on post-processed satellite clock offset solutions, which will encounter problems in real-time product evaluation, especially for real-time satellite clock offset products estimated from data with regional stations only. We propose an improved evaluation method for global navigation satellite system (GNSS) satellite clock offset products. In the proposed method, we use all-satellite reference method instead of single-satellite reference method to eliminate the timescale in satellite clock offset products. Moreover, a preprocessing step is suggested to detect gross errors and initial clock bias before evaluating the precision of the satellite clock offsets. We conduct two examples to verify our method, and the experimental results show that the proposed method is more reasonable in assessing the GNSS satellite clock offset precision, and it also provides a reliable approach to analyzing the estimated satellite clock offset in both real-time and post-processed, or globally and regionally.     

星载GPS的多目标跟踪数据处理方法

针对测量船外测数据对多个目标进行定轨精度较低的问题,该文提出了星载GPS数据、测量船外测数据的融合处理方法。在多目标测控任务中,航天测量船船载设备获取的外测数据仅包含一个主跟踪目标的测角数据和多个跟踪目标的测距数据,且测角数据精度较低,该文采用由星载GPS数据获取的等效测角数据和由测量船外测设备获取的测距数据进行定轨,经过分析试算,该方法有效弥补了船载外测设备测角数据精度较低的问题,提高了初轨确定的能力以及卫星星间距离的解算精度。     

国产高分辨率卫星数据在黄河防凌监测中应用

自2002～2003年度首次启用遥感技术监测黄河凌情以来,到目前已连续进行了10个年度.10个年度的生产实践表明:国产高分辨率卫星遥感数据能够有效跟踪黄河凌情的发展过程,实现黄河凌情的日动态监测、重点时段的精细监测和突发凌汛灾害时的实时监测.黄河凌情尤其在封开河阶段,日变化非常显著,中巴资源卫星作为国产高分辨率可见光民用遥感卫星的代表,以其大视场、高空间、高时间分辨率的特点,动态监测凌情,基本做到每天实现一次全覆盖监测的能力,配合其他如中国遥感卫星等高分辨率可见光、雷达数据,初步实现了凌情发展预估、开河前的河道槽蓄水量计算、封开河期间冰凌险情监测以及发生凌汛灾害时灾情信息采集与评估,为黄河防凌     

基于卫星精密轨道数据的复图像对精确配准

图像精确配准是InSAR数据处理中关键步骤之一。在介绍复图像对配准过程后,利用Doris软件逐步实现复图像对粗配准、精配准;深入分析配准过程中相干系数的变化,总结干涉条纹图、相干图特点,证实基于精密卫星轨道数据可以实现图像对精确配准的可行性。     

Growing stock estimation through stratified sampling on satellite remote sensing data

Aerial photographs are being extensively used for forest surveys i.e. forest cover type mapping, assessment of growing stock, estimation of area, vegetation studies, etc. Satellite remote sensing technology offers new possibilities and scope for achieving some of the above applications with higher accuracy and reliability. The assessment of growing stock through subjective stratification has also become possible with increase in spatial and spectral resolution. In the present study, the LANDSAT TM FCC (1966) has been visually interpreted on the basis of tonal characteristics. Stratified random sampling method has then used for determination of number of sample units for collection of ground Inventory data. Using regression equations, the volume per hectare of individual forest cover types were calculated. Satellite remote sensing data has been used for initial stratification, distribution of sample plots and calculation of area under various forest cover types. Estimate has been made for available commecial and non-commercial growing stocks in the study area.     

Forecasting vegetation greenness with satellite and climate data

A new and unique vegetation greenness forecast (VGF) model was designed to predict future vegetation conditions to three months through the use of current and historical climate data and satellite imagery. The VGF model is implemented through a seasonality-adjusted autoregressive distributed-lag function, based on our finding that the normalized difference vegetation index is highly correlated with lagged precipitation and temperature. Accurate forecasts were obtained from the VGF model in Nebraska grassland and cropland. The regression R/sup 2/ values range from 0.97-0.80 for 2-12 week forecasts, with higher R/sup 2/ associated with a shorter prediction. An important application would be to produce real-time forecasts of greenness images.     

State-of-the-art of elevation extraction from satellite SAR data

Relative or absolute elevation extraction from satellite radar data has been an active research topic for more than 20 years. Various investigations have been made on different methods depending on the predominant “fashion” and data availability, leading each time to new developments to improve the capability and the applicability of each method. The paper presents an update of the state-of-the-art of elevation extraction from satellite SAR data. The performance and limitations of four different methods (clinometry, stereoscopy, interferometry and polarimetry) are reviewed, as well as their applicability to different satellite SAR sensors. Their advantages and disadvantages and how they are addressed during the data processing are also analysed. Finally, concluding remarks look at the complementarity aspects of each method to make the best use of the existing and future radar data for elevation extraction.     

District-level rice-yield estimation for Orissa using satellite data

Remotely-sensed data transformed into a vegetation index (radiance ratio of near infrared to red) has been related to district rice yields for Orissa using IRS-1A LISS-I data of kharif seasons 1988–89 and 1989–90. Using the empirical relation of the first year, estimation of rice yield has been done for the 1989–90 kharif season. Deviations in the districts of coastal tract and central tableland ranged from 1.9 to 11.1 percent whereas deviations were larger in Eastern Ghat and Northern plateau of Orissa.