A GIS plug-in for Bayesian belief networks: Towards a transparent software framework to assess and visualise uncertainties in ecosystem service mapping

The complexity and spatial heterogeneity of ecosystem processes driving ecosystem service delivery require spatially explicit models that take into account the different parameters affecting those processes. Current attempts to model ecosystem service delivery on a broad, regional scale often depend on indicator-based approaches that are generally not able to fully capture the complexity of ecosystem processes. Moreover, they do not allow quantification of uncertainty on their predictions. In this paper, we discuss a QGIS plug-in which promotes the use of Bayesian belief networks for regional modelling and mapping of ecosystem service delivery and associated uncertainties. Different types of specific Bayesian belief network output maps, delivered by the plug-in, are discussed and their decision support capacities are evaluated. This plug-in, used in combination with firmly developed Bayesian belief networks, has the potential to add value to current spatial ecosystem service accounting methods. The plug-in can also be used in other research domains dealing with spatial data and uncertainty.     

User activities and the heterogeneity of urban space:The case of Dahiyat Al Hussein park

Urban researchers have maintained a constant interest in the complexity and continuity of urban space usage. Some have applied actor–network theory (ANT) to investigate the heterogeneity of spaces and present them through the networks of their users’ activities. However, these accounts are predominantly limited in examining the extent to which these spaces may be heterogeneous when exploring such networks. This paper draws on recent ANT scholarship, which employs an ethnographic research conducted in a main park in a housing project at Dahiyat Al Hussein in Amman, Jordan. The findings describe the complex and unpredictable negotiations that occur within spaces by documenting the varieties and interrelations among user activity networks within this common and shared urban space. This research reveals the extent to which spaces, parks in this case, may be heterogeneous by unpacking their usage. The conclusions and insights assert the necessity of paying attention to design detail and creating designs that are responsive to evolving user activities.     

The Spatial LASSO With Applications to Unmixing Hyperspectral Biomedical Images

Hyperspectral imaging (HSI) is a spectroscopic method that uses densely sampled measurements along the electromagnetic spectrum to identify the unique molecular composition of an object. Traditionally HSI has been associated with remote sensing-type applications, but recently has found increased use in biomedicine, from investigations at the cellular to the tissue level. One of the main challenges in the analysis of HSI is estimating the proportions, also called abundance fractions of each of the molecular signatures. While there is great promise for HSI in the area of biomedicine, large variability in the measurements and artifacts related to the instrumentation has slow adoption into more widespread practice. In this article, we propose a novel regularization and variable selection method called the spatial LASSO (SPLASSO). The SPLASSO incorporates spatial information via a graph Laplacian-based penalty to help improve the model estimation process for multivariate response data. We show the strong performance of this approach on a benchmark HSI dataset with considerable improvement in predictive accuracy over the standard LASSO. Supplementary materials for this article are available online.     

基于子波域空间相关的多分辨图像滤波方法

从静态子波变换入手,提出了一种有效的图像滤波算法。通过计算相邻尺度下细节信号的空间相关性来区分噪声和信号,如果子波系数的空间相关性大,则认为此位置的系数含有特征及边缘信息予以保留。实现这种理论的完整方法包括两部分:空间滤波和子波收缩。仿真结果表明这个算法有很好的降噪性能。     

空间数据立方体的物化视图选择方法研究

针对决策支持系统(DSS)中集成空间分析能力的应用趋势，研究基于空间数据仓库的一种决策分析工具——空间在线分析处理(Spatial OLAP)，拟解决影响空间OLAP在线响应的瓶颈难点——空间数据立方体的物化问题。首先系统地提出空间OLAP的模型，然后对现有空间度量物化视图选择方法进行改进，提出了双向空间Greedy算法。实验证明．该算法在降低选择时间和求解质量两方面具有更好的表现。     

Qualitative representation of spatial knowledge in two-dimensional space

Various relation-based systems, concerned with the qualitative representation and processing of spatial knowledge, have been developed in numerous application domains. In this article, we identify the common concepts underlying qualitative spatial knowledge representation, we compare the representational properties of the different systems, and we outline the computational tasks involved in relation-based spatial information processing. We also describesymbolic spatial indexes, relation-based structures that combine several ideas in spatial knowledge representation. A symbolic spatial index is an array that preserves only a set of spatial relations among distinct objects in an image, called the modeling space; the index array discards information, such as shape and size of objects, and irrelevant spatial relations. The construction of a symbolic spatial index from an input image can be thought of as a transformation that keeps only a set of representative points needed to define the relations of the modeling space. By keeping the relative arrangements of the representative points in symbolic spatial indexes and discarding all other points, we maintain enough information to answer queries regarding the spatial relations of the modeling space without the need to access the initial image or an object database. Symbolic spatial indexes can be used to solve problems involving route planning, composition of spatial relations, and update operations.     

无保护间隔的OFDM信道自适应均衡的一种新算法

近年来作为一种特殊的多载波调制方式——正交频分复用(OFDM)已得到越来越多的人的关注.对于传统的OFDM系统来说,如果循环前缀的长度大于信道的时延扩散值,则可以通过简单的频域均衡来解调OFDM信号.可是循环前缀的使用却降低了系统的传输效率,如果能压缩甚至去掉循环前缀,而保持系统性能不变,则是很有意义的,为此本文给出了一种新的均衡结构,利用循环迭代手段以减少甚至去掉循环前缀,最后通过计算机模拟,证实了这种结构的有效性.     

多码CDMA系统中联合并行干扰抵消与迭代信道估计方法

本文针对多码CDMA系统提出了一种联合并行干扰抵消与迭代信道估计方法。该方法首先通过导频符号对信道进行估计，然后使用RAKE接收机后的软信息对信道参数进行修正，最后通过并行干扰抵消(PIC)去除多码干扰(MCI)。仿真结果表明，经过多次迭代后，该方法可显著地降低多码CDMA系统的误比特率平台。本文同时还给出了信道估计质量、码道数和PIC次数对多码CDMA系统性能的影响。     

MC-CDMA系统迭代检测中的一种信道估计算法

在DS—CDMA系统中，联合译码的迭代多用户检测是克服多址干扰增加系统容量的有效方法。本文将多用户检测和译码相结合的迭代检测技术应用于MC—CDMA系统，其中，多用户检测器由串行干扰消除和其后的MMSE滤波器组成。文中提出一种时域信道估计作为迭代初始值的频域信道估计算法，比单纯的频域信道估计方法节约导频符号数量，并且由于信道估计性能的改善，加快了迭代检测的收敛速度。