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981.
Theory for Reconstruction of an Unknown Number of Contaminant Sources using Probabilistic Inference 总被引:1,自引:0,他引:1
Eugene Yee 《Boundary-Layer Meteorology》2008,127(3):359-394
We address the inverse problem of source reconstruction for the difficult case of multiple sources when the number of sources
is unknown a priori. The problem is solved using a Bayesian probabilistic inferential framework in which Bayesian probability
theory is used to derive the posterior probability density function for the number of sources and for the parameters (e.g.,
location, emission rate, release time and duration) that characterize each source. A mapping (source–receptor relationship)
that relates a multiple source distribution to the concentration measurements made by an array of detectors is formulated
based on a forward-time Lagrangian stochastic model. A computationally efficient methodology for determination of the likelihood
function for the problem, based on an adjoint representation of the source–receptor relationship and realized in terms of
a backward-time Lagrangian stochastic model, is described. An efficient computational algorithm based on a parallel tempered
Metropolis-coupled reversible-jump Markov chain Monte Carlo (MCMC) method is formulated and implemented to draw samples from
the posterior probability density function of the source parameters. This methodology allows the MCMC method to initiate jumps
between the hypothesis spaces corresponding to different numbers of sources in the source distribution and, thereby, allows
a sample from the full joint posterior distribution of the number of sources and the parameters for each source to be obtained.
The proposed methodology for source reconstruction is tested using synthetic concentration data generated for cases involving
two and three unknown sources. 相似文献
982.
为了提高人工增雨作业的作业水平和增雨效率,利用2010—2012年徐州市人工增雨作业中的多种观测资料,在分析徐州地区地形特征、增雨作业习惯的基础上,研究出适合本地区使用的人工增雨效果检验方法,建立人工增雨潜势分析模型,对未来12h的人工增雨潜势和临近增雨潜势进行逐步分级判断,将增雨潜势区分为两级:级别Ⅰ增雨潜势较小和级别Ⅱ增雨潜势较大,并指导人工增雨作业。2013年徐州人工增雨作业实践表明,人工增雨12h潜势预报模型和临近预报模型具有较高的准确率。以增雨潜势预报模型为基础,修改徐州地区人工增雨作业流程,提高指挥人员的工作效率,并提高人工增雨作业的效率。 相似文献
983.
动态系统的抗差Kaliman滤波 总被引:9,自引:0,他引:9
离散历元的动态观测量及其相应的动态模型可能存在异常,若数据处理模型不考虑对这些异常的特别处理,则动态模型参数估值及其所提供的动态信息将极不可靠。基于贝叶斯统计和抗差估计原理,我们构造了一种抗差滤波算法。该算法考虑观测分布和参数验前分布均为污染分布。并利用一个实测网验算该算法和模型的可靠性。 相似文献
984.
Yixuan Tu Shunlin Liang Xiangqin Wei Yunjun Yao Xiaotong Zhang 《International Journal of Digital Earth》2020,13(4):487-503
ABSTRACTA fractional vegetation cover (FVC) estimation method incorporating a vegetation growth model and a radiative transfer model was previously developed, which was suitable for FVC estimation in homogeneous areas because the finer-resolution pixels corresponding to one coarse-resolution FVC pixel were all assumed to have the same vegetation growth model. However, this assumption does not hold over heterogeneous areas, meaning that the method cannot be applied to large regions. Therefore, this study proposes a finer spatial resolution FVC estimation method applicable to heterogeneous areas using Landsat 8 Operational Land Imager reflectance data and Global LAnd Surface Satellite (GLASS) FVC product. The FVC product was first decomposed according to the normalized difference vegetation index from the Landsat 8 OLI data. Then, independent dynamic vegetation models were built for each finer-resolution pixel. Finally, the dynamic vegetation model and a radiative transfer model were combined to estimate FVC at the Landsat 8 scale. Validation results indicated that the proposed method (R2?=?0.7757, RMSE?=?0.0881) performed better than either the previous method (R2?=?0.7038, RMSE?=?0.1125) or a commonly used method involving look-up table inversions of the PROSAIL model (R2?=?0.7457, RMSE?=?0.1249). 相似文献
985.
高分辨率地表冻融监测对研究根河地区碳氮循环、水土流失和土壤冻融侵蚀非常重要。本文采用Kou等(2017)提出的被动微波亮温降尺度方法和1 km空间分辨率的温度数据,将0.25°空间分辨率的被动微波亮温降尺度至0.01°空间分辨率。利用通过模型模拟与实验数据发展得到的冻融判别式算法DFA_Zhao(Discriminant Function Algorithm)和改进的冻融判别式算法DFA_Kou(Improved Discriminant Function Algorithm),基于降尺度前后的被动微波亮温监测根河地区的地表冻融。以根河地区2013年7月—2015年12月的地下0—5 cm深度的实测土壤温度检验这两种冻融判识算法的分类精度。结果显示,降尺度前后两种冻融判识算法整体判对率差异在6.72%内;DFA_Zhao算法融化判对率的均值比DFA_Kou算法高10%,DFA_Kou算法冻结判对率均值比DFA_Zhao算法高1%。两种冻融判别式算法的冻结判对率均在90%以上,升轨期的融化判对率均在80%以上,但两算法降轨期的融化判对率较低,在40%—82%之间。同时,还进一步讨论并分析了两种冻融判别式算法和被动微波亮温降尺度方法可能存在的问题,指出了可能的改进方向。 相似文献
986.
987.
988.
Semi-arid parkland agrosystems are strongly sensitive to climate change and anthropic pressure. In the context of sustainability research, trees are considered critical for various ecosystem services covering environment quality as well as food security and health. But their actual ecological impact on both cropland and natural vegetation is not well understood yet, and collecting spatial and structural information around agroforestry systems is becoming an important issue. Tree mapping in semi-arid parklands could be one of these prerequisites. While for obtaining an exhaustive inventory of individual trees and for analysing their spatial distribution, remote sensing is the ideal tool. However, it has been noted that depending on the spatial resolution and sensor spectral characteristics, tree species cannot be distinguished clearly, even in the sparsely vegetated semi-arid ecosystems of West Africa. Thus, this work focuses on assessing the capabilities of Worldview-3 imagery, acquired in 8 spectral bands, to detect, delineate, and identify certain key tree species in the Faidherbia albida parkland in Bambey, Senegal, based on a ground-truth database corresponding to 5000 trees. The tree crowns are delineated through NDVI thresholding and consecutive filtering to provide object-based radiometric signatures, radiometric indices, and textural information. A factorial discriminant analysis is then performed, which indicates that only four out of the seven most abundant species in the study area can be discriminated: “Faidherbia albida”,” Azadirachta indica”, “Balanites aegyptiaca” and “Tamarindus indica”. Next, random forest and support vector machine classifiers are employed to identify the optimal combination of classifier parameters to discriminate these classes with a high accuracy, robustness, and stability. The linear support vector machine with cost=1 and gamma=0.01 provides the optimal results with a global accuracy of 88 % and kappa of 0.71. This classifier is applied to the whole study area to map all the trees with crowns larger than 2 m, sorted in four identified species and a fifth common group of unidentified species. This map thus enables analysing the variability in tree density and the spatial distribution of different species. Such information can afterwards be correlated to the ecological functioning of the parkland and local practices, and offers promising opportunities to help future sustainability initiatives in different socio-ecological contexts. 相似文献
989.
基于相关向量机的高光谱影像分类研究 总被引:2,自引:0,他引:2
虽然支持向量机在高光谱影像分类得到成功应用,但是它自身固有许多不足之处。相关向量机是在贝叶斯框架下提出的更加稀疏的学习机器,它没有规则化系数,其核函数不需要满足Mercer条件,不仅具备良好的泛化能力,而且还能够得到具有统计意义的预测结果。本文从分析支持向量机用于高光谱影像分类存在的不足出发,提出了一种基于相关向量机的高光谱影像分类方法,介绍了稀疏贝叶斯分类模型,将相关向量机学习转化为最大化边缘似然函数估计问题,并采用了快速序列稀疏贝叶斯学习算法。通过PHI和OMIS影像分类实验分析表明了基于相关向量机的高光谱影像分类方法的优越性。 相似文献
990.