丹巴滑坡的位移特征   总被引：1，自引：0，他引：1  

樊晓一  乔建平  田宏岭 《山地学报》2007,25(2):202-206

滑坡位移资料可为分析滑坡运动规律、发展趋势和预测预报提供依据。通过对丹巴滑坡治理过程中滑坡前部、中部和后部的位移监测资料分析,滑坡位移速度可划分为两个阶段:位移速度增加阶段和减少阶段。分析了各部位的各个阶段运动特征及其影响因素。对各部位位移速度在增加阶段和减小阶段的速度与时间关系的曲线拟合,表明滑坡在位移速度增加阶段具有相似的运动特征,拟合方程都较好地符合指数方程,而在速度减小阶段受治理工程的影响差别较大,拟合方程分别为对数、线性和指数方程。以监测数据的初始值和累计最大值,利用Lo-gistic模型对各部位的累计位移进行预测,预测值与实测值的拟合程度较高,表明丹巴滑坡在治理过程中的整个累计位移较好地遵循Logistic增长过程。从位移监测资料可以看出,滑坡治理工程有效地控制了滑坡的活动。  相似文献   

GIS-based landslide susceptibility for Arsin-Yomra (Trabzon,North Turkey) region   总被引：14，自引：3，他引：14  

Aykut Akgün  Fikri Bulut 《Environmental Geology》2007,51(8):1377-1387

The purpose of this study is to assess the susceptibility of landslides around Yomra and Arsin towns near Trabzon, in northeast of Turkey, using a geographical information system (GIS). Landslide inventory of the area was made by detailed field surveys and the analyses of the topographical map. The landslide triggering factors are considered to be slope angle, slope aspect, distance from drainage, distance from roads and the weathered lithological units, which were called as “geotechnical units” in the study. Idrisi and ArcGIS packages manipulated all the collected data. Logistic regression (LR) and weighted linear combination (WLC) statistical methods were used to create a landslide susceptibility map for the study area. The results were assessed within the scope of two different points: (a) effectiveness of the methods used and (b) effectiveness of the environmental casual parameters influencing the landslides. The results showed that the WLC model is more suitable than the LR model. Regarding the casual parameters, geotechnical units and slopes were found to be the most important variables for estimating the landslide susceptibility in the study area.  相似文献   

不同品性冬小麦籽粒灌浆特性研究   总被引：3，自引：0，他引：3  

信志红  郭建平  谭凯炎  张利华  刘凯文  杨荣光  张颖  孙义 《气象与环境科学》2019,42(1):18-25

为揭示冬小麦干物质积累过程的动态变化,利用不同品种冬小麦分期播种的灌浆速率资料,建立了Logistic模型,定量分析了不同播期条件下不同品性冬小麦的灌浆特性,并探讨了冬小麦灌浆特性对气象因子的响应情况。结果表明,籽粒灌浆质量与开花后天数的关系符合Logistic生长曲线方程。基于Logistic模型求算的各次级参数能够较好地表征冬小麦籽粒灌浆特性,半冬性品种较春性品种灌浆高峰期出现时间早;春性品种的粒重渐增期和粒重快增期持续时间一般长于半冬性品种的;半冬性品种的平均活跃灌浆期较春性品种的短;早播和正常播种条件下,春性品种最大和平均灌浆速率均高于半冬性品种的,而迟播条件下春性品种最大和平均灌浆速率均低于半冬性品种的,适期晚播更利于春性品种灌浆和千粒重增加。灌浆特性的变异系数分布总体呈春性品种大于半冬性品种的,表明播期对春性品种的影响更大。不同籽粒灌浆特性对气象因子的响应不同,其中孕穗—成熟期内的平均气温、孕穗—乳熟期内的降水量、播种—乳熟期内的日照时数与冬小麦灌浆特性相关密切,基于灌浆特性与气象因子建立的逐步回归方程决定系数为0.507～0.875,均通过了0.01的显著性检验。  相似文献   

Quantifying determinants of cash crop expansion and their relative effects using logistic regression modeling and variance partitioning     

《International Journal of Applied Earth Observation and Geoinformation》2015

Cash crop expansion has been a major land use change in tropical and subtropical regions worldwide. Quantifying the determinants of cash crop expansion should provide deeper spatial insights into the dynamics and ecological consequences of cash crop expansion. This paper investigated the process of cash crop expansion in Hangzhou region (China) from 1985 to 2009 using remotely sensed data. The corresponding determinants (neighborhood, physical, and proximity) and their relative effects during three periods (1985–1994, 1994–2003, and 2003–2009) were quantified by logistic regression modeling and variance partitioning. Results showed that the total area of cash crops increased from 58,874.1 ha in 1985 to 90,375.1 ha in 2009, with a net growth of 53.5%. Cash crops were more likely to grow in loam soils. Steep areas with higher elevation would experience less likelihood of cash crop expansion. A consistently higher probability of cash crop expansion was found on places with abundant farmland and forest cover in the three periods. Besides, distance to river and lake, distance to county center, and distance to provincial road were decisive determinants for farmers’ choice of cash crop plantation. Different categories of determinants and their combinations exerted different influences on cash crop expansion. The joint effects of neighborhood and proximity determinants were the strongest, and the unique effect of physical determinants decreased with time. Our study contributed to understanding of the proximate drivers of cash crop expansion in subtropical regions.  相似文献   

The use of logistic model tree (LMT) for pixel- and object-based classifications using high-resolution WorldView-2 imagery     

Ismail Colkesen 《国际地球制图》2017,32(1):71-86

Logistic model tree (LMT), a new method integrating standard decision tree (DT) induction and linear logistic regression algorithm in a single tree, have been recently proposed as an alternative to DT-based learning algorithms. In this study, the LMT was applied in the context of pixel- and object-based classifications using high-resolution WorldView-2 imagery, and its performance was compared with C4.5, random forest and Adaboost. Results of the study showed that the LMT generally produced more accurate classification results than the other methods for both pixel- and object-based classifications. The improvement in classification accuracy reached to 3% in pixel-based and 5% in object-based classifications. It was also estimated that the LMT algorithm produced the most accurate results considering the allocation and overall disagreement errors. Based on the Wilcoxon’s Signed-Ranks tests, the performance differences between the LMT and the other methods were statistically significant for both pixel- and object-based image classifications.  相似文献   

外来蓝领农民工城市定居意愿影响因素——以广东省东莞市为例     

席文凯  张虹鸥  黄耿志  王洋  金利霞 《地域研究与开发》2017,36(1)

以外来蓝领(即工厂、企业中的外来产业工人)高度集聚的广东省东莞市为例,基于814份有效调查问卷数据,采用Logistic模型和描述性统计分析,结合预假设及反馈验证,揭示了外来蓝领工人城市定居意愿的影响因素。回归结果显示:工资收入、产权住房、工作时间、是否已婚、生活满意度等经济、环境、家庭和心理因素均对外来民工的定居意愿产生显著的影响;而年龄、性别、户口性质、受教育水平等因素未通过显著性检验,既反映现有文献中存在的争议,也反馈了当地的真实情况。相关统计分析发现,拥有资格证书、本地户口及其赋予的福利权利、良好的居住环境也有助于提高外来蓝领农民工的定居意愿。最后,讨论了提高外来蓝领工人城市定居意愿的政策启示。  相似文献   

The rate,extent and spatial predictors of forest loss (2000–2012) in the terrestrial protected areas of the Philippines     

《Applied geography (Sevenoaks, England)》2017

While studies on deforestation of protected areas (PAs) have been conducted in many parts of the world, no comparative study has been done over an entire country in the tropics. Thus, we conducted a country-wide assessment of forest cover loss in all terrestrial protected areas of the Philippines, covering 198 PAs with a total area of 4.68 million ha. This study utilised Hansen's Landsat-derived global maps of forest cover change from 2000 to 2012, with tree canopy cover data for 2000 as the base year. Correlation and logistic regression analyses were employed to determine the significance and magnitude of the relationships between forest cover and 11 predictor variables. The assessment of forest loss reveals that the terrestrial protected areas are generally effective in reducing forest loss. Over the 12-year period, the average rate (2.59%) of forest clearing in protected areas is marginally lower by 0.1% than the entire country (2.69%). Within the same duration, the average forest loss rate within the 2-km buffer zones of selected protected areas is 1.4 times of those inside PAs. However, there was a significant number of PAs with phenomenal forest cover loss in terms of extent (48,583 ha over 12 years) and rate (up to 21%). We found that spatial predictor variables included in this study have weak or no relationships with forest cover, and hence they are not reliable inputs for predictive modelling. Comprehensive assessments of deforestation are needed at the micro-scale (e.g. single PA level) level and relatively shorter historical timeframe (e.g. less than a decade), to generate useful information for policy formulation, planning, and management.  相似文献   

异地海域年极值风暴增水同现规律的探讨   总被引：1，自引：1，他引：1  

董胜  梁永超  郝小丽 《中国海洋大学学报(自然科学版)》2004,34(3):468-474

以塘沽和龙口海洋观测站20年极值增水值为样本，基于二维冈贝尔逻辑分布模式，探讨了不同海域风暴潮增水极值的联合分布规律。通过对二维分布的联合概率密度、条件概率密度和同现概率的计算，给出了相应的工程设计参数，供有关部门在防潮规划时参考。  相似文献   

An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps   总被引：12，自引：0，他引：12  

H.A. Nefeslioglu  C. Gokceoglu  H. Sonmez 《Engineering Geology》2008,97(3-4):171-191

The main purpose of this study is to highlight the conceptual differences of produced susceptibility models by applying different sampling strategies: from all landslide area with depletion and accumulation zones and from a zone which almost represents pre-failure conditions. Variations on accuracy and precision values of the models constructed considering different algorithms were also investigated. For this purpose, two most popular techniques, logistic regression analysis and back-propagation artificial neural networks were taken into account. The town Ispir and its close vicinity (Northeastern part of Turkey), suffered from landsliding for many years was selected as the application site of this study. As a result, it is revealed that the back-propagation artificial neural network algorithms overreact to the samplings in which the presence (1) data were taken from the landslide masses. When the generalization capacities of the models are taken into consideration, these reactions cause imprecise results, even though the area under curve (AUC) values are very high (0.915 < AUC < 0.949). On the other hand, the susceptibility maps, based on the samplings in which the presence (1) data were taken from a zone which almost represents pre-failure conditions constitute more realistic susceptibility evaluations. However, considering the spatial texture of the final susceptibility values, the maps produced using the outputs of the back-propagation artificial neural networks could be interpreted as highly optimistic, while of those generated using the resultant probabilities of the logistic regression equations might be evaluated as pessimistic. Consequently, it is evident that, there are still some needs for further investigations with more realistic validations and data to find out the appropriate accuracy and precision levels in such kind of landslide susceptibility studies.  相似文献   

Is correlation dimension a reliable proxy for the number of dominant influencing variables for modeling risk of arsenic contamination in groundwater?     

Jason Hill  Faisal Hossain  Bellie Sivakumar 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(1):47-55

The correlation dimension (CD) of a time series provides information on the number of dominant variables present in the evolution of the underlying system dynamics. In this study, we explore, using logistic regression (LR), possible physical connections between the CD and the mathematical modeling of risk of arsenic contamination in groundwater. Our database comprises a large-scale arsenic survey conducted in Bangladesh. Following the recommendation by Hossain and Sivakumar (Stoch Environ Res Risk Assess 20(1–2):66–76, 2006), who reported CD values ranging from 8 to 11 for this database, 11 variables are considered herein as indicators of the aquifer’s geochemical regime with potential influence on the arsenic concentration in groundwater. A total of 2,048 possible combinations of influencing variables are considered as candidate LR risk models to delineate the impact of the number of variables on the prediction accuracy of the model. We find that the uncertainty associated with prediction of wells as safe and unsafe by LR risk model declines systematically as the total number of influencing variables increases from 7 to 11. The sensitivity of the mean predictive performance also increases noticeably for this range. The consistent reduction in predictive uncertainty coupled with the increased sensitivity of the mean predictive behavior within the universal sample space exemplify the ability of CD to function as a proxy for the number of dominant influencing variables. Such a rapid proxy, based on non-linear dynamic concepts, appears to have considerable merit for application in current management strategies on arsenic contamination in developing countries, where both time and resources are very limited.  相似文献