GALILEO局域增强完备性监测网布设研究

完备性是飞机飞行安全的重要指标之一。我国在各种网的布设中一般只注重精度,而忽略了完备性。本文利用GALILEO模拟数据,在飞行轨迹固定的情况下,通过增减监测站的数量以及变换监测网的形状,计算飞机的精度和垂直保护水平(VPL),并分析飞机在不同监测网中精度和垂直保护水平的的变化规律,可以知道飞机在正方形网形的整体精度好于在其他网形中的精度,飞机在在正方形网形中的VPL虽大于在五边网形中的VPL,但两者相差很少。综合考虑,正方形网形是局域完备性监测网的最优布设网形。     

全站仪交汇法在高速公路路面沉降监测中的应用

文章介绍了全站仪交会法沉降监测,方便简洁地解决了测量人员不能进入的高速公路等特殊位置的测量问题,并通过对该方法的精度分析,论证了其可行性和有效性,对以后类似的测量工作提供经验和依据。     

单中继星单低轨卫星的联合定轨精度分析

针对由单中继星和单低轨卫星组成的联合定轨系统,给出了系统内不同轨道卫星摄动项的选取方案和卫星间的可见性判别模型。在模拟出含有白噪声的四程测距观测数据文件的基础上,研究了测距精度和采样弧段对联合定轨中高、低轨卫星定轨精度的影响。得出如下结论:联合定轨更有利于对低轨卫星的轨道改进;同样的采样时间条件下,测距噪声越小定轨精度越高,并且采样时间越短它的影响越明显;同样的测距噪声条件下,所用资料的采样时间越长精度越高,但当测距精度很高时,TDRS达到最好定轨精度所需的采样时间相应有所缩短。并在定出轨道后进行了轨道预报,分析了轨道预报的趋势及精度。     

CPⅢ测量数据处理系统开发若干关键技术研究

本文首先介绍了无砟轨道的相关内容,指出CPⅢ测量数据处理是整个建设中的关键,提出系统开发的总体目标与要求且设计了系统总体结构,详细阐述了系统开发中涉及的关键技术与基本理论,文中最后结合具体工程实例验证系统开发成果。     

基于MAPGIS的县级土地利用数据库建设及探讨——以大同市新荣区为例

本文体现了3S技术在县级土地更新调查中的重要性。重点介绍了在MAPGIS土地利用数据库系统中通过专题数据建立土地利用现状数据库,从内业判读,到外业调查,然后进行数据入库前的检查,分析数据的精度,入库后的相关处理和检查,最后建立新荣区1:1万土地利用数据库。通过建立的数据库,进行统计和汇总,输出各种专题图表,供土地部门进行合理规划和决策。     

基于精密星历的计算卫星位置的方法

分析了拉格朗日多项式插值算法,提出了将Neville算法实现于精密星历的插值,数值试验表明,其克服了函数插值的龙格现象,有很好的逼近效果.     

基于GPS的短基线定向测量及精度分析

介绍了利用GPS载波相位测量技术进行短基线定向的基本方法,推导了估计GPS短基线定向的精度公式,得到了对于边长400～700 m的基线可以达到±(1"～2")的方位精度.     

静态精密单点定位精度分析

阐述了精密单点定位技术的应用价值,分析了观测数据和精密钟差采样间隔对静态精密单点定位的影响,提供了工程实际使用有益的参考.     

Applications of AnnAGNPS model for soil loss estimation and nutrient loading for Malaysian conditions

The study evaluated the performance and suitability of AnnAGNPS model in assessing runoff, sediment loading and nutrient loading under Malaysian conditions. The watershed of River Kuala Tasik in Malaysia, a combination of two sub-watersheds, was selected as the area of study. The data for the year 2004 was used to calibrate the model and the data for the year 2005 was used for validation purposes. Several input parameters were computed using methods suggested by other researchers and studies carried out in Malaysia. The study shows that runoff was predicted well with an overall R² value of 0.90 and E value of 0.70. Sediment loading was able to produce a moderate result of R² = 0.66 and E = 0.49, nitrogen loading predictions were slightly better with R² = 0.68 and E = 0.53, and phosphorus loading performance was slightly poor with an R² = 0.63 and E = 0.33. The erosion map developed was in agreement with the erosion risk map produced by the Department of Agriculture, Malaysia. Rubber estates and urban areas were found to be the main contributors to soil erosion. The simulation results showed that AnnAGNPS has the potential to be used as a valuable tool for planning and management of watersheds under Malaysian conditions.     

Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China

The significance of crop yield estimation is well known in agricultural management and policy development at regional and national levels. The primary objective of this study was to test the suitability of the method, depending on predicted crop production, to estimate crop yield with a MODIS-NDVI-based model on a regional scale. In this paper, MODIS-NDVI data, with a 250 m resolution, was used to estimate the winter wheat (Triticum aestivum L.) yield in one of the main winter-wheat-growing regions. Our study region is located in Jining, Shandong Province. In order to improve the quality of remote sensing data and the accuracy of yield prediction, especially to eliminate the cloud-contaminated data and abnormal data in the MODIS-NDVI series, the Savitzky–Golay filter was applied to smooth the 10-day NDVI data. The spatial accumulation of NDVI at the county level was used to test its relationship with winter wheat production in the study area. A linear regressive relationship between the spatial accumulation of NDVI and the production of winter wheat was established using a stepwise regression method. The average yield was derived from predicted production divided by the growing acreage of winter wheat on a county level. Finally, the results were validated by the ground survey data, and the errors were compared with the errors of agro-climate models. The results showed that the relative errors of the predicted yield using MODIS-NDVI are between −4.62% and 5.40% and that whole RMSE was 214.16 kg ha⁻¹ lower than the RMSE (233.35 kg ha⁻¹) of agro-climate models in this study region. A good predicted yield data of winter wheat could be got about 40 days ahead of harvest time, i.e. at the booting-heading stage of winter wheat. The method suggested in this paper was good for predicting regional winter wheat production and yield estimation.