Combining AHP with GIS in synthetic evaluation of environmental suitability for living in China's 35 major cities

There are nearly 700 cities in China, each with their own particular characteristics of natural environment quality and rates of economic development. When people are able to choose a city to live in, they will take into account these characteristics in order to improve their lifestyles. Based on geographic information system technology and the analytic hierarchy process method, a model of the living environment suitability index (LESI) for the larger cities of China was designed. The LESI was constructed by using the factors of economic condition, convenience and livable degree, natural environment and natural resources. The LESI model was then applied to compare the living conditions in 35 major cities in China in 2007, including 30 provincial capitals and 5 sub-provincial cities. LESI values were higher for cities in southeast China than for cities in the northwest. The highest LESI values were mainly distributed along the Chinese southeast coast and the Yangtze River Delta. Cities with the lowest LESI values were found in the centre and north of China. Of the 35 cities, 4 had highly suitable living environments and 7 had unsuitable living environments.     

河南省泥石流危险度分区

在分析历史资料和防治现状的基础上引入城市重要性作为判别准则之一,以18个地级市为研究对象利用层次分析法对河南省泥石流危险度分区。依据泥石流危险度权重的不同将河南省分为5个区间,其中危险度大的城市1个,危险度中等的城市3个,危险度小的城市6个,危险度极小城市2个,无危险度城市6个。以期为河南省泥石流灾害的防治提供有益的参考。     

Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer

As threats of landslide hazards have become gradually more severe in recent decades,studies on landslide prevention and mitigation have attracted widespread attention in relevant domains.A hot research topic has been the ability to predict landslide susceptibility,which can be used to design schemes of land exploitation and urban development in mountainous areas.In this study,the teaching-learning-based optimization(TLBO)and satin bowerbird optimizer(SBO)algorithms were applied to optimize the adaptive neuro-fuzzy inference system(ANFIS)model for landslide susceptibility mapping.In the study area,152 landslides were identified and randomly divided into two groups as training(70%)and validation(30%)dataset.Additionally,a total of fifteen landslide influencing factors were selected.The relative importance and weights of various influencing factors were determined using the step-wise weight assessment ratio analysis(SWARA)method.Finally,the comprehensive performance of the two models was validated and compared using various indexes,such as the root mean square error(RMSE),processing time,convergence,and area under receiver operating characteristic curves(AUROC).The results demonstrated that the AUROC values of the ANFIS,ANFIS-TLBO and ANFIS-SBO models with the training data were 0.808,0.785 and 0.755,respectively.In terms of the validation dataset,the ANFISSBO model exhibited a higher AUROC value of 0.781,while the AUROC value of the ANFIS-TLBO and ANFIS models were 0.749 and 0.681,respectively.Moreover,the ANFIS-SBO model showed lower RMSE values for the validation dataset,indicating that the SBO algorithm had a better optimization capability.Meanwhile,the processing time and convergence of the ANFIS-SBO model were far superior to those of the ANFIS-TLBO model.Therefore,both the ensemble models proposed in this paper can generate adequate results,and the ANFIS-SBO model is recommended as the more suitable model for landslide susceptibility assessment in the study area considered due to its excellent accuracy and efficiency.     

矿石体重回归分析在新疆乌宗布拉克矿区的应用研究

在资源储量估算的过程中,矿石小体重的准确与否将直接影响到资源储量估算的客观程度。对矿石小体重的准确预测将需要通过大量的统计分析工作,传统的方法是利用矿石小体重的算术平均值进行估算矿床资源储量,并没有考虑到多矿种对矿石小体重的影响程度。本文利用Excel软件"数据分析"的"回归"功能模块,对实验室所测定的矿石小体重值与其对应品位进行二元线性回归分析,快速、准确地构建矿石体重与其品位的数学模型,从而为资源储量估算提供了更客观、更科学的矿石体重模型。     

易发程度指数法在宣州区地质灾害易发区划分中的应用研究

在分析地质灾害成因的基础上,选取了地形地貌、地质背景、气候、地质灾害点密度、人类工程活动等5个主要影响因素对宣州区地质灾害的易发性进行分区评价,并对区内的地质灾害易发区进行划分。根据分析评价结果,将宣州区划分为4个地质灾害易发区。分区结果较符合宣州区地质灾害发育实际情况,为宣州区的防灾减灾工作提供科学依据。     

不同空间权重定义下中国人口分布空间自相关特征分析

人口分布的研究对实现人口、环境、资源可持续管理具有深刻意义。相对于洛伦斯曲线、基尼系数等传统度量指标,运用空间自相关分析可以较好地表达人口分布的集聚现象,揭示人口格局的空间结构和空间相互作用。空间自相关测度的关键因素之一为空间权重矩阵。当前人口空间自相关特征测度多采用单一邻近关系定义空间权重矩阵,忽视了不同空间邻近关系对自相关特征分析结果的影响。本文根据距离阈值和邻接关系定义了八种空间权重,包括新定义的高铁两小时可达性空间权重。基于2010年《中国人口年鉴》统计资料,结合GeoDa软件测度了中国人口空间分布自相关特征并分析空间权重定义对自相关特征分析结果的影响。发现:(1)在不同空间邻近关系下,中国省域人口密度分布在全局自相关上均呈现空间正自相关,但其显著性水平有差异;(2)局部自相关分析结果Moran's I表现出明显的区域差异。     

APPLICATION OF GEOGRAPHICAL PARAMETER DATABASE TO ESTABLISHMENT OF UNIT POPULATION DATABASE

Now GIS is turning into a good tool in handling geographical, economical, and population data, so we can obtain more and more information from these data. On the other hand, in some cases, for a calamity, such as hurricane, earthquake, flood, drought etc., or a decision-making, such as setting up a broadcasting transmitter, building a chemical plant etc., we have to evaluate the total population in the region influenced by a calamity or a project. In this paper, a method is put forward to evaluate the population in such special region. Through exploring the correlation of geographical parameters and the distribution of people in the same region by means of quantitative analysis and qualitative analysis, unit population database (1km× 1km) is established. In this way, estimating the number of people in a special region is capable by adding up the population in every grid involved in this region boundary. The geographical parameters are obtained from topographic database and DEM database on the scale of     

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迭代逼近科学方法在速度估算中的作用

以地球物理中的速度为题 ,在详细描述了速度参数重要作用、各类速度基本概念及其应用范围、影响速度估算的各种因素的基础上 ,以模型和处理流程的叠加速度分析为例 ,在两个层面上展现了迭代逼近方法。又以剩余层速度分析为例 ,说明了具有反馈控制思想的迭代逼近算法 ,从而指出该方法在速度估算中的重要作用     

最小二乘定权方法对流动重力计算结果的影响

在处理流动重力观测数据时,采用最小二乘方法解算由权系数和观测值组成的超定方程组,得到最优权值,并利用最优权计算重力值。结果表明,等权方法计算得到的结果点值精度不高,但包含了较全的重力异常地震分析预报信息;不等权方法计算得到的结果点值精度较高,但削弱了有用的重力异常地震分析预报信息;最小二乘方法计算得到的结果不但有较高的点值精度,对M_S4.0及以上地震的分析预报效果也最优。