层次分析法(AHP)在三江平原地质环境质量评价中的应用

应用层次分析法(AHP)对影响三江平原环境地质质量的岩石、土壤和水3个子系统分别进行评价，通过分析影响各子系统的主要因子，建立子系统层次结构模型和质量指数数学模型，得出各子系统的质量指数，从而评价出各个子系统的质量状况。在此基础上，建立地质环境系统质量评价的层次结构模型和数学模型，计算出地质环境质量指数，并对该地区的质量状况进行评价，得出三江地区总体环境地质状况是好的结论。     

土地质量地球化学评估方法研究与应用:以盘锦市为例

运用层次分析法和隶属度函数建立了土地质量地球化学评估模型,以土地利用现状图斑为评价单元,对盘锦地区耕地土地质量进行了地球化学评估。对肥力指标和环境指标综合评价结果显示,盘锦地区耕地环境综合质量状况良好,三级质量以上耕地面积达到了88.04%,是优质的水稻产区,为科学管理土地和发展特色农业提供了可靠的地球化学数据。     

GIS支持下的农业土地资源评价研究—以贵阳市区为例

本文基于土地质量评价的“压力－状态－响应”（PSR）模型，选取土壤重金属污染作为评价的一个压力为指标，应用GIS对贵阳市区农业土地资源进行了综合质量评价。定量评价的结果表明，区域农业土地资源中大部分土地资源重较好，但旱地和水田共有17．11km^2的重金属重度污染区，这部分耕地已不适宜种植农作物，同时，适合人类耕作的高质量耕地由于土壤重金属污染减少了近1／3，说明贵阳市区进行土壤重金属污染防治具有重要的意义。     

贵阳市区土地资源评价模型的建立

以贵阳市区为例，选取自然生态系统指标、社会经济系统指标和农田污染系统指标，建立了土地资源评价模型，研究结果表明，将层次分析法（AHP）运用于评价模型的建立，并与地理信息系统（GIS）技术结合，是进行土地资源评价的有效途径。     

山东省地质环境质量评价研究

选取综合指数法为主要研究方法,在充分分析和借鉴前人研究经验的基础上,建立了适合山东省地质环境状况的评价指标体系,并对山东省各地市目前的地质环境质量进行了总体评价。研究中选取区域地质条件、地质灾害、人类活动和资源4个指标,各指标下又划分了若干子指标,构成了山东省地质环境质量评价的三级指标体系;然后运用层次分析法确定各指标的权重,并对相关数据进行计算,得出山东省各地市的地质环境质量的综合指数;最后根据各地市的综合指数得分将山东省地质环境质量划分为3类：即地质环境条件相对较好的鲁西鲁北地区、地质环境质量居中的胶东半岛地区和地质环境质量较差的鲁中山区。     

层次分析法在土壤环境评价中的应用评价

利用土壤质地、全盐量、土壤水分、有机质、全氮、全磷、饱气带厚度、地下水PH值、土壤交换性盐基总量等九项因子作为作为影响湿地生态的土壤环境质量评价指标,建立了土壤环境质量评价综合指数数学模型.根据张掖城市湿地调查资料,确定了各因子参数评分值并应用层次分析法计算湿地土壤环境质量评价因子的权重.据此,对张掖城城市湿地土壤环境...     

浙江慈溪市土地生态质量调查和评估

土壤、大气、水和农产品质量共同构成土地生态质量的内涵。通过慈溪市基本农田质量调查试点项目,开展了高精度土壤地球化学调查和农产品、灌溉水、大气质量调查,建立了土地生态质量评估模型。以土壤地球化学质量评估为基础,进行了大气、水、农产品综合质量评估,以及慈溪市农用地土地生态质量评价。评价显示,慈溪市农用地土地生态质量绝大部分优良,只有局部如城市周边等地存在生态风险。试点成果为浙江省国土资源特别是基本农田的数量、质量和生态管护并重的精细化管理提供了示范和依据。     

土壤质量评价国外研究进展

土壤是人类赖以生存的根本资源。土壤质量涉及到动植物生产力,大气、水的质量和人类的健康,随着人们对自然资源和环境保护意识的增强,越来越多的国家和地区已将土壤质量评价工作作为实现可持续发展的一个重要方面。通过土壤质量评价,了解土壤管理和利用的现状,为土壤质量的改善及可持续利用提供理论依据和技术支撑。根据国外近10年的研究,总结了主要的评价指标体系和评价方法。评价指标主要包括土壤物理、化学和生物性质3个方面的指标。评价方法分为定性和定量评价,定量评价应用较广,包括土壤质量指数、土壤质量模型、多元线性回归、相对土壤质量法等。掌握和了解国外相关研究的动态,对于开展土地质量地球化学评估及土地的分等定级工作有着重要的意义。     

土地环境质量综合评价模型的建立--以山东半岛蓝色经济区为例

依据多目标区域地球化学调查资料,对土地环境质量综合评价方法进行探讨,建立评价模型。提出土地环境质量综合评价是土壤内部指标分等、外部指标定级,整合全部评价因素的新观点。采用相关系数、半方差函数进行指标筛选,层次分析法确定参评指标权重,通过隶属度函数模型将土壤不同含量单位的指标纳入同一评价体系形成内部因素,叠加区域地下水、农作物质量等外部因素,建立土地质量综合评价模型。根据模型对山东半岛蓝色经济区土地环境质量进行综合评价,结果表明：山东半岛土地可分为优质、优良、良好、中、差5等20级,其中可作绿色（111和121级）及无公害（211和221级）食品生产基地的土地占62．60％;需农业种植结构调整的512和522级土地面积267．54 km2,多位于矿区（金矿、石墨矿、铜铁矿）周边或紧邻城镇地带。土地环境质量综合评价方法及模型的建立对山东其他地区基本农田保护和土地质量等级划分具有一定借鉴意义。     

土地质量评估中评价单元的划分 ——以山西忻州盆地为例

多目标区域地球化学调查、区域生态地球化学评价和土地地球化学质量评估是一项系列工程,其中土地地球化学质量评估与人类的生产、生活息息相关。土地地球化学质量评估工作非常复杂,对工作区进行评估单元的划分是核心内容。评估单元是土地地球化学质量评估的最小空间单位。以山西忻州盆地为例,采用评估区的土地利用类型图和土壤类型图相叠加的方法．对其进行国家一省级评估,为国家、省市土地的宏观管理和规划提供地球化学依据,为实现土地可持续利用的战略目标服务。     

Assessing groundwater vulnerability and its inconsistency with groundwater quality,based on a modified DRASTIC model: a case study in Chaoyang District of Beijing City

Depth to water, net recharge, aquifer media, soil media, topography, impact of the vadose zone media, and hydraulic conductivity of the aquifer (DRASTIC) model based on a geographic information system (GIS) is the most widely adopted model for the evaluation of groundwater vulnerability. However, the model had its own disadvantages in various aspects. In this work, several methods and the technologies have been introduced to improve on the traditional model. The type of the aquifer was replaced by the thickness of the aquifer, and the index of topography was removed. The indexes of the exploitation of the groundwater and the type of land use that reflected the special vulnerability were added to the system. Furthermore, considering the wideness of the study area, the fixed weights in the DRASTIC model were not suitable. An analytic hierarchy process (AHP) method and an entropy weight (Ew) method were introduced to calculate the weights of parameters. Then, the Spearman Rho correlation coefficients between IVI and the Nemerow synthetical pollution index (NI) of the groundwater quality were significantly improved, after the four steps of modification. The level differences with little gaps between Nemerow comprehensive pollution indexes and groundwater vulnerability occupied the proportion of the area from 75.68 to 84.04%, and finally, a single-parameter sensitivity analysis for the two models was used to compute the effective weights of these parameters. By comparison, the DRMSICEL model seems to perform better than the DRASTIC model in the study area. And the results show discrepancies between the vulnerability indices and groundwater quality as indicated by existence of vulnerable areas with bad water quality and vice versa.     

PSR框架下的黑龙江省海伦市耕地质量评价

为科学评价现有耕地质量水平,利用环境卫星、Landsat8遥感影像以及地球化学调查等数据,提取了土壤肥力、水分、重金属污染等多种指标信息,采用与土壤水含量相关性更强的TVDI代替传统的DVI方法,建立了基于压力-状态-响应模型（PSR）的土壤质量评价方法.运用层次分析法（AHP）为各评价指标赋予权重,结合专家评分与线性内插法实现评价因子的定量评价,最终将各评价因子进行空间权重叠加获得地块评价单元.评价结果表明：海伦市一级耕地占28.75%,二级耕地占71.17%,三级及以下耕地占0.08%,耕地质量总体较高.通过对不同等级耕地空间分布的结果分析,提出了针对性的耕地改良建议.     

基于AHP和BP神经网络的深部地热水可持续开发能力评价

采用资料完整性、开采潜力、回灌量、平均水压下降速率、地面沉降速率、水温、水质、地热井布局8项指标构建天津地热可持续开发能力评价指标体系;运用层次分析法确定了各项指标的权重,建立起评价因素集和评语集,给出了归一化数值;建立了天津地热可持续开发能力的BP神经网络模型,以层次分析法得出的结果作为样本,对BP网络进行了训练和测试,实例评价结果表明了AHP和BP神经网络方法的可行性,为地热资源的可持续开发能力评价提供了一种新的评价方法。     

应用MapGIS空间分析模块进行土地质量地球化学评估的探讨

利用农业地质调查资料,探讨了如何应用MapGIS空间分析模块进行土地质量地球化学评估。以内江市沱江乡土地整理区为例,选取土壤养份指标、土壤环境指标、水、大气环境指标以及大宗农作物安全性指标为主要评价指标,通过MapGIS数字地面模型,绘制出单因素单指标分级图,并应用区对区的空间分析模块进行多指标、多因素的叠加分析,最终绘制成土地质量地球化学分等定级图。采用MapGIS空间分析模块进行土地质量地球化学评估,可以提高土地质量地球化学评估后期成图的效率,其方法简单实用,评估结果与工作区实际情况相符。     

层次分析法在山地地质灾害危险性评价中的应用——以辽宁凌源地区为例

凌源市是辽西地区山地地质灾害危害较为严重的区域。在GIS技术支持下,选取地形、岩性、构造、降雨、道路、土地利用等6个因素作为评价指标,根据已发生的68个山地地质灾害点计算了各指标因子的敏感性,分别采用层次分析法、信息量法和统计量法确定了各指标的权重,利用因子叠置法对危险性进行了综合评价。结果表明层次分析法在该区山地地质灾害危险性评价中效果良好。该研究对相似地区山地地质灾害危险性区划具有一定的借鉴意义。     

Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran

The main goal of this study is to produce landslide susceptibility maps of a landslide-prone area (Haraz) in Iran by using both fuzzy logic and analytical hierarchy process (AHP) models. At first, landslide locations were identified by aerial photographs and field surveys, and a total of 78 landslides were mapped from various sources. Then, the landslide inventory was randomly split into a training dataset 70?% (55 landslides) for training the models and the remaining 30?% (23 landslides) was used for validation purpose. Twelve data layers, as the landslide conditioning factors, are exploited to detect the most susceptible areas. These factors are slope degree, aspect, plan curvature, altitude, lithology, land use, distance from rivers, distance from roads, distance from faults, stream power index, slope length, and topographic wetness index. Subsequently, landslide susceptibility maps were produced using fuzzy logic and AHP models. For verification, receiver operating characteristics curve and area under the curve approaches were used. The verification results showed that the fuzzy logic model (89.7?%) performed better than AHP (81.1?%) model for the study area. The produced susceptibility maps can be used for general land use planning and hazard mitigation purpose.     

Quality assessment of the Italian Landslide Inventory using GIS processing

Landslides constitute one of the most important natural hazards in Italy as they are widespread and result in considerable damage and fatalities every year. The Italian Landslide Inventory (IFFI) Project was launched in 1999 with the aim of identifying and mapping landslides over the entire Italian territory. The inventory currently holds over 480,000 landslides and has been available by means of Web services since 2005. The aim of this study is to define quality indices for evaluation of the homogeneity and completeness of the IFFI database. In order to estimate the completeness of the landslide attribute information, a heuristic approach has been used to assign weighting values to significant parameters selected from the landslide data sheet. The completeness and homogeneity of the landslide mapping has been evaluated by means of three different methods: an area-frequency distribution analysis; the proximity of the landslides surveyed to urban areas; variation of the landslide index within the same lithology. The quality indices have allowed identification of areas with a high level of completeness and critical areas in which the data collected have been underestimated or are not very accurate. The quality assessment of collected and stored data is essential in order to use the IFFI database for definition and implementation of landslide susceptibility models and for land use planning and management.     

Risk assessment of water inrush in karst tunnels based on two-class fuzzy comprehensive evaluation method

A feasible and accurate method named two-class fuzzy comprehensive evaluation is put forward to assess the risk of water inrush in karst tunnels. In view of regarding tunnel face as the evaluation object, 12 influencing factors of water inrush are selected as the evaluation index system consisting of 4 first-class and 12 second-class indices. Based on fuzzy mathematics theory and expert evaluation method, all the indices are quantitatively graded according to five risk grades. The weights of indices affecting water inrush are rationally distributed by using analytic hierarchy process. Membership functions and weights of indices are utilized to stepwise compute the membership degree of indices corresponding to risk grade, and the principle of maximum membership degree is carried out to discern the risk grade of water inrush. The tunnel faces in seven segments of Qiyueshan tunnel are chosen as the case studies. Evaluation results are derived from the proposed method, and they are generally consistent with the actual results through comparisons. This method provides a cogent way for evaluating the risk of water inrush in karst tunnels.