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Atmospheric water vapour content (WVC) is a vital parameter in the study of climate change. Various methods have been developed to derive atmospheric WVC from remotely sensed data. In this study, we compared three methods for retrieving atmospheric WVC from thermal infrared data in the Meteosat Second Generation-SEVIRI channels 9 (10.8 μm) and 10 (12.0 ?m). The three methods are (1) the split-window covariance-variance ratio method using a spatial moving window (method 1); (2) the split-window covariance-variance ratio method using a temporal moving window (method 2); and (3) the varying surface temperature method using split-window channel data (method 3). The derived WVC using these three methods was compared to two WVC data sets from European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data and the MODIS WVC product. Compared with these two data sets, the derived WVC using method 1 performed proved optimal. The valid pixels using methods 1 and 2 are greater than those using method 3. Furthermore, method 2 can be used to retrieve WVC over pixels where method 1 is invalid. 相似文献
993.
Yong Lin Xiaoping Xin Hongbin Zhang Xu Wang 《International journal of remote sensing》2015,36(19-20):5031-5044
Ecological time series data are widely used in ecological research thanks to the development of remote-sensing technologies and fixed ecological research stations. However, the serial correlation issue with time series, which violates the fundamental assumption of independence for traditional statistical models or analysis, is rarely considered by ecologists in vegetation–climate relationship research. In addition, the issue of time lags between climate change and vegetation response is also often ignored. Inadequate consideration of these issues produces misleading results in some cases. In this article, we propose an approach based on the Autoregressive Integrated Moving Average (ARIMA) model and the nonparametric test to address serial correlation issue and distribution requirements for the valid statistical analysis of time series data. With Hulunber meadow steppe as a case, we applied this approach to analyse the role of climate factors in vegetation dynamics based on leaf area index (LAI) data and climatic data. The results showed that the LAI dynamics of Hulunber meadow steppe were mainly related to temperature with the time lag of zero, whereas the impact of precipitation on LAI dynamics was not statistically obvious. The comparison of regression models that deal with serial correlation and residual normality to different extents showed that ignoring the serial correlation issue with time series data likely produces misleading results, highlighting the importance of serial correlation removal. The combination of nonparametric correlation tests with ARIMA-based cross-correlation analysis also proved quite useful in reducing the chance of spurious correlation and time lags resulting from outlier values in ARIMA-based cross-correlation. 相似文献
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Hadar Averbuch‐Elor Yunhai Wang Yiming Qian Minglun Gong Johannes Kopf Hao Zhang Daniel Cohen‐Or 《Computer Graphics Forum》2015,34(2):131-142
We present a distillation algorithm which operates on a large, unstructured, and noisy collection of internet images returned from an online object query. We introduce the notion of a distilled set, which is a clean, coherent, and structured subset of inlier images. In addition, the object of interest is properly segmented out throughout the distilled set. Our approach is unsupervised, built on a novel clustering scheme, and solves the distillation and object segmentation problems simultaneously. In essence, instead of distilling the collection of images, we distill a collection of loosely cutout foreground “shapes”, which may or may not contain the queried object. Our key observation, which motivated our clustering scheme, is that outlier shapes are expected to be random in nature, whereas, inlier shapes, which do tightly enclose the object of interest, tend to be well supported by similar shapes captured in similar views. We analyze the commonalities among candidate foreground segments, without aiming to analyze their semantics, but simply by clustering similar shapes and considering only the most significant clusters representing non‐trivial shapes. We show that when tuned conservatively, our distillation algorithm is able to extract a near perfect subset of true inliers. Furthermore, we show that our technique scales well in the sense that the precision rate remains high, as the collection grows. We demonstrate the utility of our distillation results with a number of interesting graphics applications. 相似文献
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基于ZigBee的矿用应力监测系统的研究 总被引:1,自引:0,他引:1
提出了一种新的煤矿巷道监测方法 ,即采用测力锚杆对巷道顶部深处的应力变化进行定时监测。系统主要分为三部分:传感器节点、通信主站和上位机。传感器节点负责采集和上传数据,数据主站负责管理各传感器节点并存储和上传数据,上位机负责汇总各传感器数据并对其进行分析处理。 相似文献
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基于云计算的混合并行遗传算法求解最短路径 总被引:2,自引:0,他引:2
为提高最短路径求解问题的效率,提出一种基于云计算的细粒度混合并行遗传算法求解最短路径的方法。方法采用云计算中H adoop的Map Reduce并行编程模型,提高编码效率,同时将细粒度并行遗传算法和禁忌搜索算法结合,提高了寻优算法的计算速度和局部寻优能力,进而提高最短路径的求解效率。仿真结果表明,该方法在计算速度和性能上优于经典遗传算法和并行遗传算法,是一种有效的最短路径求解方法。 相似文献
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