利用卫星遥感资料反演感热和潜热通量的研究综述

区域平均感热和潜热通量是气象、水文、生态模式中的关键物理因子，卫星遥感反演为观测区域平均感热和潜热通量提供了可能。对利用卫星遥感资料反演地气通量的方法进行了总结和评述。首先描述了现在常用的反演方法，分析了方法中的各种假定对反演结果的影响，并对不同的模式反演结果进行了比较。还指出了评价卫星反演通量的精度时需要注意的问题。最后对该领域内现存的问题与发展方向进行探讨。     

利用卫星遥感资料反演感热和潜热通量的研究综述

区域平均感热和潜热通量是气象、水文、生态模式中的关键物理因子,卫星遥感反演为观测区域平均感热和潜热通量提供了可能。对利用卫星遥感资料反演地气通量的方法进行了总结和评述。首先描述了现在常用的反演方法,分析了方法中的各种假定对反演结果的影响,并对不同的模式反演结果进行了比较。还指出了评价卫星反演通量的精度时需要注意的问题。最后对该领域内现存的问题与发展方向进行探讨。     

2008年T213与德国降水数值预报产品对比检验

为了解各种数值预报的误差特点,更好地在预报过程中选择数值预报产品作为参考依据,将中国国家气象中心的T213降水预报与德国降水预报分别进行晴雨预报检验,对2008年5—8月东北地区降水资料进行对比分析。结果表明：两种模式24-120h预报正确率为60％-70％,随着预报时效的增加,正确率呈下降趋势,德国降水预报的正确率高于T213,两种预报漏报率均明显小于空报率,T213漏报率较低,为5％左右,德国降水预报空报率较低,为20％左右。对2008年4-6月出现东北冷涡过程的两种模式降水预报进行对比分析,发现德国降水预报正确率明显高于T213预报,对冷涡降水预报有一定的指示意义。     

Accuracy assessment of digital elevation models by means of robust statistical methods

Measures for the accuracy assessment of Digital Elevation Models (DEMs) are discussed and characteristics of DEMs derived from laser scanning and automated photogrammetry are presented. Such DEMs are very dense and relatively accurate in open terrain. Built-up and wooded areas, however, need automated filtering and classification in order to generate terrain (bare earth) data when Digital Terrain Models (DTMs) have to be produced. Automated processing of the raw data is not always successful. Systematic errors and many outliers at both methods (laser scanning and digital photogrammetry) may therefore be present in the data sets. We discuss requirements for the reference data with respect to accuracy and propose robust statistical methods as accuracy measures. Their use is illustrated by application at four practical examples. It is concluded that measures such as median, normalized median absolute deviation, and sample quantiles should be used in the accuracy assessment of such DEMs. Furthermore, the question is discussed how large a sample size is needed in order to obtain sufficiently precise estimates of the new accuracy measures and relevant formulae are presented.     

Quick Bird遥感影像的几何校正

以高分辨率的Quick Bird卫星数据为对象,经影像信息融合,使处理后的图像分辨率提高且接近真彩色,具有良好的判识效果;选择若干个GPS地面控制点作为参考点,以遥感图像处理软件ER Mapper6.2为平台,对图像进行二次多项式几何精校正,纠正后的图像点位误差在lm左右,说明纠正后的图像具有较高的几何精度.     

单基站CORS系统在中小区域测绘中的应用探讨

本文对单基站CORS系统的建设和应用进行了探讨,通过单基站CORS系统在成都市龙泉驿区的建设使用情况和数据检验分析,表明单基站CORS系统完全可以胜任中小区域中的一般测量工作。其作业的有效范围广,在保证测量精度的前提下,提高了作业效率,降低了劳动强度和生产成本。     

Detection of coffee berry necrosis by digital image processing of landsat 8 oli satellite imagery

Coffee berry necrosis is a fungal disease that, at a high level, significantly affects coffee productivity. With the advent of surface mapping satellites, it was possible to obtain information about the spectral signature of the crop on a time scale pertinent to the monitoring and detection of plant phenological changes. The objective of this paper was to define the best machine learning algorithm that is able to classify the incidence CBN as a function of Landsat 8 OLI images in different atmospheric correction methods. Landsat 8 OLI images were acquired at the dates closest to sampling anthracnose field data at three times corresponding to grain filling period and were submitted to atmospheric corrections by DOS, ATCOR, and 6SV methods. The images classified by the algorithms of machine learning, Random Forest, Multilayer Perceptron and Naive Bayes were tested 30 times in random sampling. Given the overall accuracy of each test, the algorithms were evaluated using the Friedman and Nemenyi tests to identify the statistical difference in the treatments. The obtained results indicated that the overall accuracy and the balanced accuracy index were on an average around 0.55 and 0.45, respectively, for the Naive Bayes and Multilayer Perceptron algorithms in the ATCOR atmospheric correction. According to the Friedman and Nemenyi tests, both algorithms were defined as the best classifiers. These results demonstrate that Landsat 8 OLI images were able to identify an incidence of the coffee berry necrosis by means of machine learning techniques, a fact that cannot be observed by the Pearson correlation.     

Mapping spiny aster infestations with QuickBird imagery

QuickBird satellite imagery acquired in June 2003 and September 2004 was evaluated for detecting the noxious weed spiny aster [Leucosyris spinosa (Benth.) Greene] on a south Texas, USA rangeland area. A subset of each of the satellite images representing a diversity of cover types was extracted and used as a study site. The satellite imagery had a spatial resolution of 2.8 m and contained 11-bit data. Unsupervised and supervised classification techniques were used to classify false colour composite (green, red, and near-infrared bands) images of the study site. Imagery acquired in June was superior to that obtained in September for distinguishing spiny aster infestations. This was attributed to differences in spiny aster phenology between the two dates. An unsupervised classification of the June image showed that spiny aster had producer's and user's accuracies of 90% and 93.1%, respectively, whereas a supervised classification of the June image had producer's and user's accuracies of 90% and 81.8%, respectively. These results indicate that high resolution satellite imagery coupled with image analysis techniques can be used successfully for detecting spiny aster infestations on rangelands.     

Error analysis of satellite attitude determination using a vision-based approach

Improvements in communication and processing technologies have opened the doors to exploit on-board cameras to compute objects’ spatial attitude using only the visual information from sequences of remote sensed images. The strategies and the algorithmic approach used to extract such information affect the estimation accuracy of the three-axis orientation of the object.This work presents a method for analyzing the most relevant error sources, including numerical ones, possible drift effects and their influence on the overall accuracy, referring to vision-based approaches. The method in particular focuses on the analysis of the image registration algorithm, carried out through on-purpose simulations. The overall accuracy has been assessed on a challenging case study, for which accuracy represents the fundamental requirement. In particular, attitude determination has been analyzed for small satellites, by comparing theoretical findings to metric results from simulations on realistic ground-truth data. Significant laboratory experiments, using a numerical control unit, have further confirmed the outcome.We believe that our analysis approach, as well as our findings in terms of error characterization, can be useful at proof-of-concept design and planning levels, since they emphasize the main sources of error for visual based approaches employed for satellite attitude estimation. Nevertheless, the approach we present is also of general interest for all the affine applicative domains which require an accurate estimation of three-dimensional orientation parameters (i.e., robotics, airborne stabilization).     

无棱镜技术在电厂施工土方量测量中的应用

随着全站仪在测量中的广泛应用,测量的精度有了很大的提高.特别是无棱镜技术的发展,改变了以往的测量手段和方法,提高了工作的效率.土方量测量是施工过程中不可避免的,为此本文介绍无棱镜测量技术在洛河电厂施工过程中测量土方量的应用情况,通过对比实验,我们对无棱镜测量技术工作效率和成果精度以及适用条件进行分析.