基于数字高程模型辅助制作手绘山体地貌的研究

为了更直接、美观地展现南粤古驿道重点线路及其示范段的位置、旅游资源、自然历史文化资源与自然文化历史价值,更好地反映广东省复杂多样的地貌,本次研究通过运用软件ArcGIS并利用数字高程模型(DEM)进行辅助参考,制作具有独特风格,可读性高,科学性与艺术性兼备的手绘山体地貌,展现了一种山体地貌晕渲的 新形式,新风格。

山体表面重构数值反演的同伦算法

本文主要研究山体表面重构过程.山体表面重构主要包括地球内部热流变化和地球表面运动规律两个过程,是三维对流扩散方程和二维山体表面运动方程的耦合,求解十分困难.为了模拟山体表面重构过程,还要对耦合方程进行反演研究,是一个大尺度非线性优化问题.为了克服对于初值的强烈依赖和非线性优化中存在的多极值难点,我们将同伦反演算法应用到山体表面重构模型,通过数值算例可以看出,本算法具有大范围收敛和较好的稳定特性.

重庆丰盛场区域山体变形对隧道开挖响应特性研究

采矿时隧道开挖会对地下环境造成危害,同时其引起过大的地表沉降也会对地表造成危害。本文以重庆永荣矿业有限公司丰盛一矿开采工程为背景,运用有限元数值模拟软件MIDAS/GTS建立隧道断面开挖的数值模型,计算隧道开挖引起的地表沉降量。结果表明,随着埋深的增大,围岩破坏程度渐进扩大趋势,同时地表沉降量先减小后增大。在岩性较差的地层进行隧道的开挖,容易引起周围岩体的扰动,在强度相差较大的地层交界处其影响达到最大,进而出现大的变形或破坏;但如果交界的两个地层岩性相同或相近,则影响较小。

重构山体表面的非线性多重网格有限元反演算法

山体重构模型是由两个过程构成:一个是山体内部的热对流扩散过程,另一个是山体表面运动过程.前者是描述三位空间中岩石温度变化规律,后者则是描述二维空间中山体表面演变规律.山体表面重构过程归结为求解该耦合方程的反演问题.从数值计算的角度来讲,求解该问题会遇到一些困难,例如:优化非凸罚函数和大计算量的问题.为了避免这些问题,本文建议利用非线性多重网格有限元反演算法重构山体表面.数值算例表明该算法具有很好的稳定性和收敛性.

自制实体教具促进初中地理课堂有效教学

地理教学中有不少难点和抽象内容，空间思维能力欠缺的初中学生学习起来比较困难，教师教学事倍功半，如果能及时指导学生做一些简单的相关教具，可变抽象为形象、变枯燥为生动，提升课堂教学有效性。

OTO模式风险规避混沌现象探析

OTO模式是一种将线下商务与线上互联网平台融合的电子商务商业模式,这种模式在中国蓬勃发展,前景大好。但正如所有商业模式一样,OTO模式存在风险现象。本文利用混沌理论相关知识,对OTO模式系统内部出现微小偏差并经过逐级放大最后导致结果与理想值大相径庭现象,通过"牛鞭效应"分析,发现并提出产生风险的原因及解决对策;通过建立改进的"涡旋吸引子"模型,分析风险变化的规律及利用"吸引子"有效控制风险的思路;最后通过"山体"模型,进一步阐述了规避风险的策略。

Rapid Susceptibility Mapping of Co-seismic Landslides Triggered by the 2013 Lushan Earthquake Using the Regression Model Developed for the 2008 Wenchuan Earthquake

The primary objective of landslide susceptibility mapping is the prediction of potential landslides in landslide-prone areas. The predictive power of a landslide susceptibility mapping model could be tested in an adjacent area of similar geo- environmental conditions to find out the reliability. Both the 2oo8 Wenchuan Earthquake and the 2o13 Lushan Earthquake occurred in the Longmen Mountain seismic zone, with similar topographical and geological conditions. The two earthquakes are both featured by thrust fault and similar seismic mechanism This paper adopted the susceptibility mapping model of co-seismic landslides triggered by Wenchuan earthquake to predict the spatial distribution of landslides induced by Lushan earthquake. Six influencing parameters were taken into consideration： distance from the seismic fault, slope gradient, lithology, distance from drainage, elevation and Peak Ground Acceleration （PGA）. The preliminary results suggested that the zones with high susceptibility of co- seismic landslides were mainly distributed in the mountainous areas of Lushan, Baoxing and Tianquan counties. The co-seismic landslide susceptibility map was completed in two days after the quake and sent to the field investigators to provide guidance for rescue and relief work. The predictive power of the susceptibility map was validated by ROC curve analysis method using 2o37 co-seismic landslides in the epicenter area. The AUC value of o.71o indicated that the susceptibility model derived from Wenchuan Earthquake landslides showed good accuracy inpredicting the landslides triggered by Lushan earthquake.

Mechanism and Geo-mechanics Models of Landslides Triggered by 5.12 Wenchuan Earthquake

Due to the extremely high magnitude, long duration, and the complicated geo-environment in the disaster area, the great 5.12 Wenchuan Earthquake not only produced a huge number of landslides and rockfalls, but also involved complicated dynamic processes. These processes are quite different from the characteristics of landslides and rockfalls under general gravitational force, and presently human knowledge is very poor in this field. In order to describe the special dynamic processes, some terms such as shattering-cracking, shattering-sliding, shattering-falls and ejection are defined in this paper. Combined with slope structures, a mechanism classification system of strong earthquake-triggered landslide and rockfall is suggested, which is divided into 5 categories and 14 types. This paper also analyzes the basic characteristics, dynamic processes and geo-mechanics conceptual models of some typologies, especial the type of shattering-sliding for most large-scales landsides. This paper initially reveals the formation mechanism, geo-mechanics models and dynamic features of landslides and rockfalls triggered by the great Wenchuan Earthquake.

Probability Prediction Model for Landslide Occurrences in Xi'an, Shaanxi Province, China

Landslides are increasing since the 1980s in Xi'an, Shaanxi Province, China. This is due to the increase of the frequency and intensity of precipitation caused by complex geological structures, the presence of steep landforms, seasonal heavy rainfall, and the intensifcation of human activities. In this study, we propose a landslide prediction model based on the analysis of intraday rainfall(IR) and antecedent effective rainfall(AER). Primarily, the number of days and degressive index of the antecedent effective rainfall which affected landslide occurrences in the areas around Qin Mountains, Li Mountains and Loess Tableland was established. Secondly, the antecedent effective rainfall and intraday rainfall were calculated from weather data which were used to construct critical thresholds for the 10%, 50% and 90% probabilities for future landslide occurrences in Qin Mountain, Li Mountain and Loess Tableland. Finally, the regions corresponding to different warning levels were identified based on the relationship between precipitation and the threshold, that is; "A" region is safe, "B" region is on watch alert, "C" region is on warning alert and "D" region is on severe warning alert. Using this model, a warning program is proposed which can predict rainfall-induced landslides by means of real-time rain gauge data and real-time geo-hazard alert and disaster response programs. Sixteen rain gauges were installed in the Xi'an region by keeping in accordance with the regional geology and landslide risks. Based on the data from gauges, this model accurately achieves the objectives of conducting real-time monitoring as well as providing early warnings of landslides in the Xi'an region.

Predicting the Rainfall-Triggered Landslides in a Forested Mountain Region Using TRIGRS Model

Landslides are natural disasters which can pose a serious threat to human and property in many areas around the world. The Transient Rainfall Infiltration and Grid-based Regional Slope-stability (TRIGRS) model was used to investigate the rainfall-induced shallow landslides in a forested mountain region, Korea. Various input data for TRIGRS model include time-varying rainfall, topographic characteristics, soil depth, material strength, and hydraulic properties. A series of calculations were conducted in determining the slope stability over the Jangheung region in Korea during the storm occurred on August 6, 1998. The results show that TRIGRS model captured about 64.1% of landslides that were extracted from the IKONOS2 imageries. The model demonstrated how the factor of safety changed with time during a storm considering both the transient and spatial responses of pore water pressure in its slope stability calculation.

The Influence of Gender and Other Characteristics on Rural Laborers' Employment Patterns in the Mountainous and Upland Areas of Sichuan,China

This study examines gender differences in rural laborers‘ employment patterns in the mountainous and upland areas of Sichuan, China. The analysis employs both representative survey data of 400 households and geographical data. Multinomial logistic regression models are used to analyze the influences of gender, among other factors, on employment decisions of rural males and females, where the factors considered include personal, household, community natural environmental characteristics. Dividing laborers into four categories, we find that the proportions of males who participating in on-farm, pluriactive, and off-farm work, and unemployment were 24.41%, 28.64%, 46.27%, and 0.68% respectively, while that of females who participating in on-farm, pluriactive, and offfarm work, and unemployment were 43.20%, 13.95%, 30.95%, and 11.90% respectively. As to individual characteristics, age(AGE) and physical condition(PHY) effects appeared to be more pronounced for men, while education(EDU) and marital status(MAR)effects appeared to be more pronounced for women. Regarding household and community characteristics, the effects of the presence in the household of children aged 6-(CHI), number of persons in the household(POP), and labor force(LAB), per capitaincome in village(INCV), and the development status of village enterprises(ENT) on women were greater than that on men. In addition, the presence in the household of elderly individuals aged 65+(OLD) and time to reach the nearest township(TIME) are shown to have opposite impacts on men and women. While the presence in the household of pupils(PUP) and per capital gross value of industrial output(GVIO) was found to be irresponsive to men and women taking pluriavtivity and off-farm job. With respect to natural environments characteristics, the effects on men were opposite of those on women. Unemployment of women was found to be particularly responsive to household characteristics. A multinomial regression approach is undertaken to analyze rural males‘ and females‘ decisions of the four employment patterns considered, an approach that reveals considerable heterogeneity that is concealed by the dichotomous approach employed in most previous studies. The study thus contributes to our understanding of rural employment patterns and gender difference in mountainous and upland areas.

GIS-based Earthquake-Triggered Landslide Hazard Zoning Using Contributing Weight Model

Earthquake-triggered landslides have aroused widespread attention because of their tremendous ability to harm people's lives and properties.The best way to avoid and mitigate their damage is to develop landslide hazard maps and make them available to the public in advance of an earthquake.Future construction can then be built according to the level of hazard and existing structures can be retrofit as necessary.During recent years various approaches have been made to develop landslide hazard maps using statistical analysis or physical models.However,these methods have limitations.This study introduces a new GIS-based approach,using the contributing weight model,to evaluate the hazard of seismically-induced landslides.In this study,the city and surrounding area of Dujiangyan was selected as the research area because of its moderate-high seismic activity.The parameters incorporated into the model that related to the probability of landslide occurrence were:slope gradient,slope aspect,geomorphology,lithology,base level,surface roughness,earthquake intensity,fault proximity,drainage proximity,and road proximity.The parameters were converted into raster data format with a resolution of 25×25m2 pixels.Analysis of the GIS correlations shows that the highest earthquake-induced landslide hazard areas are mainly in the hills and in some of the moderately steep mountainous areas of central Dujiangyan.The highest hazard zone covers an area of 11.1% of the study area,and the density distribution of seismically-induced landslides was 3.025/km2 from the 2008 Wenchuan earthquake.The moderately hazardous areas are mainly distributed within the moderately steep mountainous regions of the northern and southeastern parts of the study area and the hills of the northeastern part;covering 32.0% of the study area and with a density distribution of 2.123/km2 resulting from the Wenchuan earthquake.The lowest hazard areas are mainly distributed in the topographically flat plain in the northeastern part and some of the relatively gently slopes in the moderately steep mountainous areas of the northern part of Dujiangyan and the surrounding area.The lowest hazard areas cover 56.9% of the study area and exhibited landslide densities of 0.941/km2 and less from the Wenchuan earthquake.The quality of the hazard map was validated using a comparison with the distribution of landslides that were cataloged as occurring from the Wenchuan earthquake.43.1% of the study area consists of high and moderate hazardous zones,and these regions include 83.5% of landslides caused by the Wenchuan earthquake.The successful analysis shows that the contributing weight model can be effective for earthquake-triggered landslide hazard appraisal.The model's results can provide the basis for risk management and regional planning is.

GIS based Landslide Susceptibility Mapping of Tevankarai Ar Sub-watershed,Kodaikkanal,India using Binary Logistic Regression Analysis

Landslide susceptibility mapping is the first step in regional hazard management as it helps to understand the spatial distribution of the probability of slope failure in an area.An attempt is made to map the landslide susceptibility in Tevankarai Ar subwatershed,Kodaikkanal,India using binary logistic regression analysis.Geographic Information System is used to prepare the database of the predictor variables and landslide inventory map,which is used to build the spatial model of landslide susceptibility.The model describes the relationship between the dependent variable(presence and absence of landslide) and the independent variables selected for study(predictor variables) by the best fitting function.A forward stepwise logistic regression model using maximum likelihood estimation is used in the regression analysis.An inventory of 84 landslides and cells within a buffer distance of 10m around the landslide is used as the dependent variable.Relief,slope,aspect,plan curvature,profile curvature,land use,soil,topographic wetness index,proximity to roads and proximity to lineaments are taken as independent variables.The constant and the coefficient of the predictor variable retained by the regression model are used to calculate the probability of slope failure and analyze the effect of each predictor variable on landslide occurrence in thestudy area.The model shows that the most significant parameter contributing to landslides is slope.The other significant parameters are profile curvature,soil,road,wetness index and relief.The predictive logistic regression model is validated using temporal validation data-set of known landslide locations and shows an accuracy of 85.29 %.

Landslide susceptibility mapping using an integrated model of information value method and logistic regression in the Bailongjiang watershed,Gansu Province,China

Bailongjiang watershed in southern Gansu province, China, is one of the most landslide-prone regions in China, characterized by very high frequency of landslide occurrence. In order to predict the landslide occurrence, a comprehensive map of landslide susceptibility is required which may be significantly helpful in reducing loss of property and human life. In this study, an integrated model of information value method and logistic regression is proposed by using their merits at maximum and overcoming their weaknesses, which may enhance precision and accuracy of landslide susceptibility assessment. A detailed and reliable landslide inventory with 1587 landslides was prepared and randomly divided into two groups,(i) training dataset and(ii) testing dataset. Eight distinct landslide conditioning factors including lithology, slope gradient, aspect, elevation, distance to drainages,distance to faults, distance to roads and vegetation coverage were selected for landslide susceptibility mapping. The produced landslide susceptibility maps were validated by the success rate and prediction rate curves. The validation results show that the success rate and the prediction rate of the integrated model are 81.7 % and 84.6 %, respectively, which indicate that the proposed integrated method is reliable to produce an accurate landslide susceptibility map and the results may be used for landslides management and mitigation.

A Comparison of Conventional and Shear-Rate Dependent Mohr-Coulomb Models for Simulating Landslides

Landslides may cause many fatalities and heavy economic losses,so it is vital to understand their mechanics so as to take appropriate measures to mitigate their risk.Phenomenally,the loose soil behaves like frictional material in most circumstances,so Mohr-Coulomb type equations are often used to describe their movement.However,these models generally do not consider the influence of the shearrate on the Mohr-Coulomb friction angle,so the shear-rate dependence effect on the soil flow and landslide runout is not well understood.This paper reports on an application of the incompressible Smoothed Particle Hydrodynamics(SPH) method to the dynamics of dry granular assemblies.The traditional model with a constant friction angle is compared with the modified Mohr-Coulomb model with a variable friction angle related to the shear-rate.It is found that the shear-rate dependence effect is negligible for shallow granular flows along mild slopes.With steeper slopes of the ground and larger aspect ratios of the initial soil column,the rate-dependence effect becomes more important.

GIS-based Frequency Ratio and Logistic Regression Modelling for Landslide Susceptibility Mapping of Debre Sina Area in Central Ethiopia

Ethiopia has a mountainous landscape which can be divided into the Northwestern and Southeastern plateaus by the Main Ethiopian Rift and Afar Depression. Debre Sina area is located in Central Ethiopia along the escarpment where landslide problem is frequent due to steep slope, complex geology, rift tectonics, heavy rainfall and seismicity. In order to tackle this problem, preparing a landslide susceptibility map is very important. For this, GISbased frequency ratio(FR) and logistic regression(LR) models have been applied using landslide inventory and the nine landslide factors(i.e. lithology, land use, distance from river & fault, slope, aspect, elevation, curvature and annual rainfall). Database construction, weighting each factor classes or factors, preparing susceptibility map and validation were the major steps to be undertaken. Both models require a rasterized landslide inventory and landslide factor maps. The former was classified into training and validation landslides. Using FR model, weights for each factor classes were calculated and assigned so that all the weighted factor maps can be added to produce a landslide susceptibility map. In the case of LR model, the entire study area is firstly divided into landslide and non-landslide areas using the training landslides. Then, these areas are changed into landslide and non-landslide points so as to extract the FR maps of the nine landslide factors. Then a linear relationship is established between training landslides and landslide factors in SPSS. Based on this relationship, the final landslide susceptibility map is prepared using LR equation. The success-rate and prediction-rate of FR model were 74.8% and 73.5%, while in case of LR model these were 75.7% and 74.5% respectively. A close similarity in the prediction and validation rates showed that the model is acceptable. Accuracy of LR model is slightly better in predicting the landslide susceptibility of the area compared to FR model.

Numerical simulation of an algal bloom in Dianshan Lake

A hydrodynamic model and an aquatic ecology model of Dianshan Lake,Shanghai,were built using a hydrodynamic simulation module and the water quality simulation module of Delft3D,which is an integrated modelling suite offered by Deltares. The simulated water elevation,current velocity,and direction were validated with observed data to ensure the reliability of hydrodynamic model. The seasonal growth of different algae was analyzed with consideration of observed and historical data,as well as simulated results. In 2008,the dominant algae in Dianshan Lake was Bacillariophyta from February to March,while it was Chlorophyta from April to May,and Cyanophyta from July to August. In summer,the biomass of Cyanophyta grew quickly,reaching levels much higher than the peaks of Bacillariophyta and Chlorophyta. Algae blooms primarily occurred in the stagnation regions. This phenomenon indicates that water residence time can influence algal growth significantly. A longer water residence time was associated with higher algal growth. Two conclusions were drawn from several simulations: reducing the nutrients inflow had little effect on algal blooms in Dianshan Lake; however,increasing the discharge into Dianshan Lake could change the flow field characteristic and narrow the range of stagnation regions,resulting in inhibition of algal aggregation and propagation and a subsequent reduction in areas of high concentration algae.

THE APPLICATION OF ACOUSTIC LOGGING METHOD IN THE MODEL AND PARAMETERS IDENTIFICATION OF ROCK MASS

This paper describes the new method that is introduced into prediction of subsidence using system engineering method with acoustic logging and density logging. According to the result of acoustic logging, the real and complex rock beds are divided into a set of different bed groups and the equivalent mechanical model is to be built. Based on the modern control theory,according to the input data (convergence or settlement of the roof) and the output data (surface movement and deformation) of the system, the static parameters of equivalent rock beds can be derived from back calculation using the optimum method. Then the reqression relationship between the dynamic and static parameters can be built. So the prediction of rock and ground movements for other areas in the same district can be done, when using this relationship with the acoustic logging data and density logging data in situ.

Size and spatial distribution of landslides induced by the2015 Gorkha earthquake in the Bhote Koshi river watershed

The Mw 7.8 Gorkha earthquake in Nepal on April 25, 2015, produced thousands of landslides in the Himalayan mountain range. After the earthquake, two field investigations along Araniko Highway were conducted. Then, using remote sensing technology and geographic information system(GIS)technology, 1481 landslides were identified along the Bhote Koshi river. Correlations between the spatial distribution of landslides with slope gradient and lithology were analyzed. The power-law relationship of the size distribution of earthquake-induced landslides was examined in both the Higher Himalaya and Lesser Himalaya. Possible reasons for the variability of the power exponent were explored by examining differences in the geological situations of these areas. Multi-threshold cellular automata were introduced to model the complexity of system components. Most of the landslides occurred at slope gradients of 30°–40°, and the landslide density was positively correlated with slope gradient. Landslides in hard rock areas were more common than in soft rock areas. The cumulative number-area distribution of landslides induced by the Gorkha earthquake exhibited a negative power-law relationship, but the power exponents were different: 1.13 in the Higher Himalaya, 1.36 and Lesser Himalaya. Furthermore,the geological conditions were more complex and varied in the Lesser Himalaya than in the Higher Himalaya, and the cellular automata simulation results indicated that, as the complexity of system components increased, the power exponent increased.Therefore, the variability of the power exponent of landslide size distribution should ascribe to the complexity of geological situations in the Bhote Koshi river watershed.

三维地图动画生成中的粗粒度分布式并行计算

根据粗粒度并行计算的原理 ,对形成地形貌动画中计算量较大过程采用人为分割 ,把分割后的各部分数据交给配置基本相同的各台PC机进行计算 ,采用以空间换取时间的方法 ,提高系统的实时性 .