Quantifying the protective function of a forest against rockfall for past,present and future scenarios using two modelling approaches

Following a major rockfall event in 1987, two types of protection measures were taken in the village Saint Martin le Vinoux (French Alps). Firstly, technical measures using civil engineering were installed, and secondly, a forest management intervention to increase its protection was carried out. This study aims to assess whether this intervention was successful in the sense that it improved the protective function of the forest. We evaluated the rockfall risk for the situation of 1987 (before the intervention), today and the future, using model simulations with past, present and future vegetation cover scenarios. To increase the meaningfulness of our results, we used two different models, called Rockfor^.NET, which is a rapid one-dimensional rockfall forest evaluation tool, using simple slope and forest characteristics and RockyFor, a process based on three-dimensional rockfall simulation model that takes the barrier effect of individual trees explicitly into account. Both models correctly predicted that the forest was not capable of stopping rocks from the 1987 rockfall event. Further, both models indicate an increase of the number of rocks reaching the base of the slope from 1987 onwards. RockyFor shows an increase from 11% in 1987 to 19% in 2086. Rockfor^.NET shows an increase from 26% in 1987 to 56% in 2086. We conclude that a second attempt to increase the protective function of the forest should aim at restoring a dense coppice stand.     

Spatial variability assessment of soil nutrients in an intense agricultural area,a case study of Rugao County in Yangtze River Delta Region,China

Topsoil samples (0–20 cm) (n = 237) were collected from Rugao County, China. Geostatistical variogram analysis, sequential Gaussian simulation (SGS), and principal component (PC) analysis were applied to assess spatial variability of soil nutrients, identify the possible areas of nutrient deficiency, and explore spatial scale of variability of soil nutrients in the county. High variability of soil nutrient such as soil organic matter (SOM), total nitrogen (TN), available P, K, Fe, Mn, Cu, Zn, and B concentrations were observed. Soil nutrient properties displayed significant differences in their spatial structures, with available Cu having strong spatial dependence, SOM and available P having weak spatial dependence, and other nutrient properties having moderate spatial dependence. The soil nutrient deficiency, defined here as measured nutrient concentrations which do not meet the advisory threshold values specific to the county for dominant crops, namely rice, wheat, and rape seeds, was observed in available K and Zn, and the deficient areas covered 38 and 11%, respectively. The first three PCs of the nine soil nutrient properties explained 62.40% of the total variance. TN and SOM with higher loadings on PC1 are closely related to soil texture derived from different parent materials. The PC2 combined intermediate response variables such as available Zn and P that are likely to be controlled by land use and soil pH. Available B has the highest loading on PC3 and its variability of concentrations may be primarily ascribed to localized anthropogenic influence. The amelioration of soil physical properties (i.e. soil texture) and soil pH may improve the availability of soil nutrients and the sustainability of the agricultural system of Rugao County.     

金沙江流域生态保护与建设决策支持系统

利用地理信息系统对生态保护与建设相关的地理信息进行采集、管理、分析,对政府部门的决策是一种有效的技术支撑。本文主要介绍“金沙江流域(云南部分)生态保护与建设决策支持系统”的体系结构设计和系统实现。     

广西都安喀斯特石漠化的分布特征及其与岩性的空间相关性

在以广西都安瑶族自治县为研究对象 ,以RS与GIS一体化为分析手段 ,首先采用TM影像为背景资料 ,辅以地形图、土地利用图、土壤图、地质图以及GPS实测数据库等相关资料综合分析的基础上 ,建立石漠化分级的遥感影像解译指标体系 ,生成都安县石漠化分级分布图和数字化岩性图 ,然后从空间相关性的角度阐明了不同级别石漠化与碳酸盐岩岩性之间的内存联系     

A probabilistic approach to exposure risk assessment

The introduction of hazardous substances into the environment has long been recognized as being a cause of several diseases in humans, wildlife, and plants. The damaging character of suspected contaminants is usually assessed via a “reject/retain” design with no explicit link between levels of exposure and intensities of the potential adverse health effects even though this connection may be important for the development of public health regulations that limit exposure to hazardous substances. Here, we propose a probabilistic approach to exposure risk assessment as a way around this typical flaw. We develop a Bayesian model using proximity to the source of an alleged contaminant as a surrogate for exposure. Subsequently, we carry out an experimental study based on simulated data to illustrate the model implementation with real world data. We also discuss a possible way of extending the model to accommodate potential heterogeneity in the spatial distribution of the focal disease.     

Long-period ground motions from the 2003 Tokachi-oki earthquake

We study characteristics of long-period ground motions from the 2003 Tokachi-oki earthquake (Mj 8.0), a large interplate earthquake, based on spatial distribution maps and attenuation relationships for four kinds of peak ground velocity (PGV) value. The first kind (PGV(WB)) is obtained from a maximal value of vector sum of the three-component, wide-band velocity seismograms, and the other three kinds (PGV(BP10), PGV(BP20), and PGV(BP30)) are obtained from a maximal value of vector sum of the three-component, narrow band-pass filtered velocity seismograms (the central periods are 10, 20, and 30 s). The spatial distribution maps for all kinds of PGV value show azimuth dependence; the PGV values in Hokkaido, northern side of the epicenter are larger than those in Tohoku, southwestern side of the epicenter, when compared at a comparable distance. We find that the features result from the radiation pattern of long-period surface waves, that is, the source effect. The attenuation relationships show the following trends: The PGV(WB) values are larger than the sum of the PGV(BP10), PGV(BP20), and PGV(BP30) at distances (D) less than 200 km, while the PGV(WB) values are comparable to the sum of the PGV(BP20) and PGV(BP30) at D > 200 km. This indicates that the PGV(WB) values at D < 200 km are affected by ground motions with periods less than 10 s, while long-period surface waves mainly contribute to the PGV(WB) values at D > 200 km. The basin site effects generate a patchy pattern in the spatial distribution maps and a large scattering in the attenuation relationships for the PGV(WB) and PGV(BP10) values. Finally, we conclude that the PGV(WB) values from the 2003 Tokachi-oki earthquake are controlled by the radiation pattern of long-period S and surface waves and various basin site effects.     

Recognizing spatial distribution patterns of grassland insects: neural network approaches

The main objective of this study was to fit and recognize spatial distribution patterns of grassland insects using various neural networks, and to analyze the feasibility of neural networks for detecting spatial distribution patterns of grassland insects. BP neural network, Learning vector quantization (LVQ) neural network, linear neural network and Fisher’s linear discriminant analysis were used to fit and recognize spatial distribution patterns at different ecological scales. Various comparisons and analysis were conducted. The results showed that BP, LVQ and linear neural networks were better algorithms for recognizing spatial distribution patterns of grassland insects. BP neural network was the best algorithm to fit spatial distribution patterns. BP network may be used to recognize the spatial details of distribution patterns, and the recognition performance of BP network became better as the increase of the number of hidden layers and neurons. Performance of linear neural network for pattern recognition was similar to linear discrimination method. Linear neural network would yield better performance in finding the general trends of distribution patterns. Recognition performance of LVQ network was just between BP network and linear network. It was found that recognition performance of neural networks depended upon not only the ecological scale but also the criterion for classification. Under the uniform criterion, recognition efficiency of linear methods tended to be weak as ecological scale became to be coarser. A joint use of neural networks was suggested in order to achieve both overall and detailed understanding on spatial distribution patterns.     

An application of Spartan spatial random fields in environmental mapping: focus on automatic mapping capabilities

This paper investigates the potential of Spartan spatial random fields (SSRFs) in real-time mapping applications. The data set that we study focuses on the distribution of daily gamma dose rates over part of Germany. Our goal is to determine a Spartan spatial model from the data, and then use it to generate “predictive” maps of the radioactivity. In the SSRF framework, the spatial dependence is determined from sample functions that focus on short-range correlations. A recently formulated SSRF predictor is used to derive isolevel contour maps of the dose rates. The SSRF predictor is explicit. Moreover, the adjustments that it requires by the user are reduced compared to classical geostatistical methods. These features present clear advantages for an automatic mapping system. The performance of the SSRF predictor is evaluated by means of various cross-validation measures. The values of the performance measures are similar to those obtained by classical geostatistical methods. Application of the SSRF method to data that simulate a radioactivity release scenario is also discussed. Hot spots are detected and removed using a heuristic method. The extreme values that appear in the path of the simulated plume are not captured by the currently used Spartan spatial model. Modeling of the processes leading to extreme values can enhance the predictive capabilities of the spatial model, by incorporating physical information.     

用空间光滑方法评估弱地震活动区的地震活动性参数

本文以长江中游地震带为研究区域,该区地震活动比较弱,发震构造不清晰,但人口、经济分布集中,中小地震往往会造成强烈的社会影响。自有记载以来,共记录到122次Ms≥4．7级的地震,最大的地震为1631年常德63/4级地震,在这样的区域进行地震危险性分析,依据构造特征和地震活动进行潜源划分的方法会带来较大的不确定性,为了更合理地评价其危险性,本文试图先在研究区内划分活动水平相当的等b值区域,然后利用空间光滑法计算各区的地震年平均发生率分布。结果显示,各分区内年平均发生率存在较大差异,年发生率分布图与现代和历史地震震中分布格局基本一致,为潜源区划分提供了一种量化的空间参考数据。