Soil erosion and its response to the changes of precipitation and vegetation cover on the Loess Plateau

Soil erosion is a major threat to our terrestrial ecosystems and an important global environmental problem. The Loess Plateau in China is one of the regions that suffered more severe soil erosion and undergoing climate warming and drying in the past decades. The vegetation restoration named Grain-to-Green Program has now been operating for more than 10 years. It is necessary to assess the variation of soil erosion and the response of precipita- tion and vegetation restoration to soil erosion on the Loess Plateau. In the study, the Revised Universal Soil Loss Equation （RUSLE） was applied to evaluate annual soil loss caused by water erosion. The results showed as follows. The soil erosion on the Loess Plateau between 2000 and 2010 averaged for 15.2 t hm-2 a 1 and was characterized as light for the value less than 25 t hm-2 a-1. The severe soil erosion higher than 25 t hm-2 a-~ was mainly distributed in the gully and hilly regions in the central, southwestern, and some scattered areas of earth-rocky mountainous areas on the Loess Plateau. The soil erosion on the Loess Plateau showed a deceasing trend in recent decade and reduced more at rates more than 1 t hm 2 a 1 in the areas suffering severe soil loss. Benefited from the improved vegetation cover and ecological construction, the soil erosion on the Loess Plateau was significantly declined, es- pecially in the east of Yulin, most parts of Yah＇an prefectures in Shaanxi Province, and the west of Luliang and Linfen prefectures in Shanxi Province in the hilly and gully regions. The variation of vegetation cover responding to soil erosion in these areas showed the relatively higher contribution than the precipitation. However, most areas in Qingyang and Dingxi pre- fectures in Gansu Province and Guyuan in Ningxia Hui Autonomous Region were predomi- nantly related to precipitation.     

Methods for detecting apparent differences between spatial tessellations at different time points

This paper proposes methods for detecting apparent differences between spatial tessellations at two different points in time, with the objective of conflation of spatial tessellations at multiple time points. The methods comprise three steps. First, we eliminate systematic differences between tessellations using the affine transformation. Second, we match subregions between tessellations at two points in time and match boundaries based on matching relationships between the subregions. Third, we propose a distance metric for measuring differences between the matched boundaries and a method for determining whether the measured differences are apparent or not. We apply the proposed methods to a part of the US Census data for 1990 and 2000 and empirically demonstrate the effectiveness of these methods.     

Possibilities and limits of prospective GIS land cover modelling—a compared case study: Garrotxes (France) and Alta Alpujarra Granadina (Spain)

This study focuses on the possibilities and the limits of a prospective GIS land cover modelling applied to two case studies (France and Spain). The methodology, based on available GIS tools, consists of using earlier land cover maps and relevant environmental factors (calibration data) to model actual, known land cover to validate the model. The model aggregates Markov chain analysis for time prediction and multi‐critera evaluation, multi‐objective evaluation and cellular automata to perform spatial contiguity of modelled land cover scores. The first results give an accurate, pixel by pixel prediction rate of approximately 75%. An important issue of this study consists of analysing prediction residues to improve the model.     

Statistics-based outlier detection for wireless sensor networks

Wireless sensor network (WSN) applications require efficient, accurate and timely data analysis in order to facilitate (near) real-time critical decision-making and situation awareness. Accurate analysis and decision-making relies on the quality of WSN data as well as on the additional information and context. Raw observations collected from sensor nodes, however, may have low data quality and reliability due to limited WSN resources and harsh deployment environments. This article addresses the quality of WSN data focusing on outlier detection. These are defined as observations that do not conform to the expected behaviour of the data. The developed methodology is based on time-series analysis and geostatistics. Experiments with a real data set from the Swiss Alps showed that the developed methodology accurately detected outliers in WSN data taking advantage of their spatial and temporal correlations. It is concluded that the incorporation of tools for outlier detection in WSNs can be based on current statistical methodology. This provides a usable and important tool in a novel scientific field.     

Incorporating spectral data into logistic regression model to classify land cover: a case study in Mt. Qomolangma (Everest) National Nature Preserve

Only few models for land-cover classification incorporated spectral data into ordinary logistic regression (OL model) in the Mt. Qomolangma (Everest) National Nature Preserve (QNNP) in China. In this study, spectral variables were incorporated into OL model and autologistic regression (AL) model to classify six main land covers. Twelve environmental variables and seven spectral variables of 10,000 stratified random sites in the QNNP were quantified and analyzed; OL model, AL model, OL model with spectral data (OLM model), and AL model with spectral data (ALM model) were estimated. The OLM and ALM models produced better estimates of regression coefficients and significantly improved model performance and overall accuracy for the grassland, sparsely vegetated land, and bare land compared with OL and AL models.     

多尺度地图面/面目标匹配模式及变化探测方法研究

多尺度地图数据更新的一个重要途径就是通过目标匹配技术获得已更新与待更新的不同比例尺地图之间表达同一地物的候选空间目标,并对候选匹配目标对进行比较,以便获得匹配目标间的差异以及发现未匹配的目标;进而,分析判断差异是否由该目标所表达的地理要素的实际变化所导致。该文以面目标匹配为例,对多尺度地图面目标匹配对的差异驱动因素和变化类型进行分析,针对不同模式的目标匹配对提出了利用长度差异、面积差异和重叠度指标进行差异驱动因素判别、变化探测和变化类型判定的方法,并验证了该方法的有效性和实用性。     

一种基于激光点云数据的房屋轮廓线提取方法

提出了一种基于激光点云数据提取房屋轮廓线的方法.首先在屋顶激光点云数据中搜索平面距离最远的两个激光点,选择其一为起始点,根据相邻边缘点连线的一侧不存在激光点的原则,检测屋顶所有的边缘点;然后对边缘点分组,利用最小二乘直线拟合方法分别拟合各条轮廓线并进行规则化;最后,选择轮廓线最外侧的激光点,对各条轮廓线进行平移外扩,并通过相邻轮廓线相交确定屋顶角点的坐标.实验结果表明,与通常采用的对屋顶激光点云构建不规则三角网(TIN)获取边缘点的方法相比,该算法运行效率明显提高,检测到的屋顶边缘点数量更多,获取的屋顶轮廓线精度更高.     

南京地区下垫面变化对城市热岛效应影响的数值模拟

利用新一代中尺度研究和预报模式(Weather Research and Forecasting Model,简称WRF)分别耦合多冠层、单冠层和平板模式三种情况进行南京地区2007年8月1日的天气过程模拟,分析不同城市冠层方案对南京气象场的模拟效果。在此基础上,结合模拟效果最好的城市冠层方案,研究南京城市下垫面的变化对其热岛的影响。结果表明:多冠层方案对近地面气温、10 m风场的模拟效果最好;城区的扩张使南京地区近地面气温升高,主要表现为城市区域夜间升温显著,并且导致热岛强度明显增强;城市扩张后,城区白天风速大范围地减小,同时热岛环流更加显著,且具有明显的城市热岛的"下游效应"。     

Statistical moment-based structural damage detection method in time domain

A novel structural damage detection method with a new damage index,i.e.,the statistical moment-based damage detection(SMBDD) method in the frequency domain,has been recently proposed.The aim of this study is to extend the SMBDD method in the frequency domain to the time domain for building structures subjected to non-Gaussian and non-stationary excitations.The applicability and effectiveness of the SMBDD method in the time domainis verified both numerically and experimentally.Shear buildings with various damage scenarios are first numerically investigated in the time domain taking into account the effect of measurement noise.The applicability of the proposed method in the time domain to building structures subjected to non-Gaussian and non-stationary excitations is then experimentally investigated through a series of shaking table tests,in which two three-story shear building models with four damage scenarios aretested.The identified damage locations and severities are then compared with the preset values.The comparative results are found to be satisfactory,and the SMBDD method is shown to be feasible and effective for building structures subjected to non-Gaussian and non-stationary excitations.     

A frequency response function change method for damage localization and quantification in a shear building under ground excitation

A frequency response function change (FRFC) method to detect damage location and extent based on the change in the frequency response functions of a shear building under the effects of ground excitation was proposed in this paper. The damage identification equation was derived from the motion equations of the system before and after the occurrence of the damage. Efforts to make the FRFC method less model‐dependent were made. Intact system matrices, which could be estimated using the measured data without the need for an analytical model, and the frequency response functions were required for the FRFC method. The effects of measurement noise and model parameter error in the FRFC method were studied numerically. The proposed FRFC method was validated by experimental studies of a six‐story steel building structure with single and multiple damage cases. Copyright © 2012 John Wiley & Sons, Ltd.