A comparison of alternative criteria for defining fuzzy boundaries on fuzzy categorical maps

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模糊类别制图的空间统计学方法

类别地图是地理信息系统（ＧＩＳ）应用中所利用的重要数据类别。这类数据可以从摄影测量和遥感技术得到。用摄影测量方法（影像判读）制作的类别地图常以点、线和多边形的离散目标形式描述,而遥感图像分类方法输出的类别地图以连通光栅块形式表达。不论哪一种情况,在每一个多边形或者光栅块（即制图单元）中仅允许单一类别,边界内部非均匀性和模糊形已经被“过滤”了。这样的类别地图沿用了古曲脆集合论,因为每个制图单元只允许     

融入空间关系的二型模糊模型高分辨率遥感影像分割

为解决高分辨率遥感影像分割中,由光谱测度的空间复杂性、相同类型地物目标异质性增大带来的类属不确定性以及分割决策不确定性等引起的分割精度下降问题,提出一种融入空间关系的区间二型模糊模型高分辨率遥感影像监督分割方法。(1)建立高斯函数模型作为一型模糊模型,用来刻画像素类属的不确定性;(2)模糊化一型模糊模型中的均值或标准差,建立区间二型模糊模型,以强化类属的不确定表达和增加分割决策信息;(3)综合一型模糊模型及区间二型模糊模型的上、下隶属函数建模模糊决策模型;(4)融入邻域像素关系,使用待分像素及其邻域像素在模糊决策模型中的隶属度共同决定像素的类属。采用本文算法分别对真实高分辨遥感影像及合成影像进行分割,并对测试结果进行定性和定量分析。结果表明,本文算法可以得到更高的分割精度。     

Lightning flash mensuration using video from the space shuttle Columbia (STS‐32)

Abstract

Environmental data are often utilized to guide interpretation of spectral information based on context, however, these are also important in deriving vegetation maps themselves, especially where ecological information can be mapped spatially. A vegetation classification procedure is presented which combines a classification of spectral data from Landsat‐5 Thematic Mapper (TM) and environmental data based on topography and fire history. These data were combined utilizing fuzzy logic where assignment of each pixel to a single vegetation category was derived comparing the partial membership of each vegetation category within spectral and environmental classes. Partial membership was assigned from canopy cover for forest types measured from field sampling. Initial classification of spectral and ecological data produced map accuracies of less than 50% due to overlap between spectrally similar vegetation and limited spatial precision for predicting local vegetation types solely from the ecological information. Combination of environmental data through fuzzy logic increased overall mapping accuracy (70%) in coniferous forest communities of northwestern Montana, USA.     

Classification of remote sensing images from urban areas using a fuzzy possibilistic model

The classification of very high-resolution remotely sensed images from urban areas is addressed. Previous studies have shown the interest of exploiting the local geometrical information of each pixel to improve the classification. This is performed using the derivative morphological profile (DMP) obtained with a granulometric approach, using opening and closing operators. For each pixel, this DMP constitutes the feature vector on which the classification is based. In this letter, we present an interpretation of the DMP in terms of a fuzzy measurement of the characteristic size and contrast of each structure. This fuzzy measure can be compared to predefined possibility distributions to derive a membership degree for a set of given classes. The decision is taken by selecting the class with the highest membership degree. This model is illustrated and validated in a classification problem using IKONOS images.     

Application of fuzzy combination operators to flood vulnerability assessments in Seoul,Korea

The goal of this study was to apply, verify and compare fuzzy models with various fuzzy combination operators to analyze the vulnerability to flooding in Seoul, Korea, and to create flood vulnerability maps. We employed the IPCC concept of vulnerability, which comprises exposure to climate, sensitivity and the adaptive capacity, to identify factors that influence flooding. Eleven factors were compiled in a spatial database using geographical information system. The relative weight of each factor was converted into a fuzzy membership value, which was integrated to obtain a flood vulnerability index using five fuzzy combination operators (fuzzy AND, fuzzy OR, fuzzy algebraic sum, fuzzy algebraic product and fuzzy gamma). Overall, the fuzzy models were quite effective tools for flood vulnerability assessment. Of the five fuzzy combination operators, the fuzzy AND operator obtained the highest prediction accuracy of 88.68%. This study achieved better flood vulnerability assessments by employing and comparing fuzzy combination operators.     

改进的区间二型模糊聚类遥感影像变化检测

遥感影像的复杂模糊性问题会干扰影像变化检测的结果,可引入区间二型模糊C均值聚类算法解决此问题,但算法参数的随机性导致检测结果不稳定。本文首先利用局部最优解优化萤火虫算法中的候选解,引入可变步长因子,以此自适应寻优区间二型模糊C均值聚类算法的模糊因子;然后结合寻优得到的模糊因子进行区间二型模糊C均值聚类,迭代更新隶属区间提取变化信息;最后通过基于复合梯形法则的加权Karnik-mendel算法降型和解模糊优化聚类中心,依据最大隶属度原则判断变化类型。通过试验验证,本文方法得到更优模糊因子和更精确的聚类中心,具有更好的稳健性,变化检测精度得到提高,检测得到的变化区域更加精细。     

Using the Relative Operating Characteristic to Quantify Certainty in Prediction of Location of Land Cover Change in India

This paper describes a methodology by which modelers, ecologists and planners can quantify the certainty in predicting the location of change for a given quantity of change. The specification of the quantity of a land cover category and the specification of the location of a land cover category are two distinct fundamental concepts in geographical analysis. It is crucial that scientists have appropriate quantitative tools to analyze each of these two concepts independently of one another. This paper gives methods whereby a scientist can convert a map of relative propensity for disturbance to a map of probability of future disturbance, based on a quantifiable validation of a map's predictive ability. The required inputs are: (1) maps that show a Boolean categorical variable at times 0, 1 and 2, (2) a technique to create a map that shows the relative propensity for membership in the Boolean category, and (3) a predicted proportion of the category at time 3.     

一种新的高分辨率遥感影像模糊监督分类方法

针对高分辨率遥感影像分类中由于细节特征突出、同质区域光谱测度变异性增大所带来的像素类属的不确定性及模型的不确定性等造成的误分结果,提出一种基于模糊隶属函数的监督分类方法。对同质区域定义高斯隶属函数模型用来表征像素类属不确定性;模糊化该隶属函数参数建立影像模糊隶属函数,以建模同质区域光谱测度的不确定性;用训练样本在所有类别中的模糊隶属函数及原隶属函数（高斯隶属函数）中的隶属度为输入,建立模糊线性神经网络模型作为目标函数,实现分类决策。该算法和经典算法对World View-2全色合成影像及真实影像进行定性和定量分类实验,分类结果验证了文中方法具有更高的分类精度。     

地图质量评判的数学模型

应用数学分析方法建立一个地图质量模糊评判的数学模型，并用上述模型对１２幅地形图编绘质量进行评判，所得结果令人满意。     

Fuzzy topological relations between fuzzy spatial objects

Fuzziness is an internal property of spatial objects.How to model fuzziness of a spatial object is a main task of next generation GIS.This paper proposes basic fuzzy spatial object types based on fuzzy topology.These object types are the natural extension of current nonfuzzy spatial object types.A fuzzy cell complex structure is defined for modeling fuzzy regions,lines and points.Furthermore,fuzzy topological relations between these fuzzy spatial objects are formalized based on the 9intersection approach.This model can be implemented for GIS applications due to its scientific theory basis.     

Change detection assessment using fuzzy sets and remotely sensed data: an application of topographic map revision

This paper explores a methodology for computing the amount of changes that have occurred within an area by using remotely sensed technologies and fuzzy modelling. The discussion concentrates on the formulation of a standard procedure that, using the concept of fuzzy sets and fuzzy logic, can define the likelihood of changes detected from remotely sensed data. Furthermore, an example of how fuzzy visualisation of areas undergoing changes can be incorporated into a decision support system for prioritisation of areas requiring topographic map revision and updating is presented. By adapting the membership function of the fuzzy model to fit the shape of the histogram characterising the change image (derived from any of the common pre-classification methods of change detection), areas can be identified according to their likelihood of having undergone change during the period of observation.     

模糊评价中最大隶属度原则有效性检验

模糊综合评价过程中,针对评语集B的处理通常采用最大隶属度原则,引入最大隶属度原则有效度指标,判断评价结果的有效性。实验结果表明,最大隶属度原则并不是普遍适用,存在失效问题,针对可能存在的失效问题,通过对隶属度的定量化描述,能得到更为合理的评判结果,弥补最大隶属度原则的不足。     

基于模糊推理的最大似然分类算法研究

本文将模糊集理论与最大似然分类原理相结合,用模糊均值和模糊协方差代替传统最大似然分类的均值和协方差矩阵,依据极大隶属度原则,对最大似然分类算法进行改进。并尝试采用一种基于相异像素空间分布算法的分类精度评定方法,得到相异像素空间分布图,依据该空间分布图对不同的分类方法进行精度评定。实验结果表明,改进后的最大似然分类法的正确率、Kappa系数均优于传统的最大似然分类方法,所采用的精度评定方法也较传统方法在有效性、效率等方面有所改善。     

自适应距离和模糊拓扑优化的模糊聚类SAR影像变化检测

针对模糊聚类算法的不足,结合差分影像的特点,提出一种基于自适应距离（adaptive distance）和模糊拓扑（fuzzy topology）理论的SAR影像变化检测技术框架（FATCD）。FATCD首先基于自适应距离公式提出一种自适应的样本到聚类中心的距离计算方法,优化了聚类过程中像元隶属度的计算公式,提高了模糊隶属度函数的准确程度;而后利用模糊拓扑理论改进传统去模糊化方式最大隶属度原则,从而增强了去模糊化过程。借助这两点,FATCD提高了模糊聚类变化检测的性能。两组真实SAR影像数据的试验结果表明本文方法可行、有效。     

Landslide susceptibility mapping of a catchment area using frequency ratio,fuzzy logic and multivariate logistic regression approaches

Geospatial database creation for landslide susceptibility mapping is often an almost inhibitive activity. This has been the reason that for quite some time landslide susceptibility analysis was modelled on the basis of spatially related factors. This paper presents the use of frequency ratio, fuzzy logic and multivariate regression models for landslide susceptibility mapping on Cameron catchment area, Malaysia, using a Geographic Information System (GIS) and remote sensing data. Landslide locations were identified in the study area from the interpretation of aerial photographs, high resolution satellite images, inventory reports and field surveys. Topographical, geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing tools. There were nine factors considered for landslide susceptibility mapping and the frequency ratio coefficient for each factor was computed. The factors chosen that influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature and distance from drainage, all from the topographic database; lithology and distance from lineament, taken from the geologic database; land cover from TM satellite image; the vegetation index value from Landsat satellite images; and precipitation distribution from meteorological data. Using these factors the fuzzy membership values were calculated. Then fuzzy operators were applied to the fuzzy membership values for landslide susceptibility mapping. Further, multivariate logistic regression model was applied for the landslide susceptibility. Finally, the results of the analyses were verified using the landslide location data and compared with the frequency ratio, fuzzy logic and multivariate logistic regression models. The validation results showed that the frequency ratio model (accuracy is 89%) is better in prediction than fuzzy logic (accuracy is 84%) and logistic regression (accuracy is 85%) models. Results show that, among the fuzzy operators, in the case with “gamma” operator (λ = 0.9) showed the best accuracy (84%) while the case with “or” operator showed the worst accuracy (69%).     

Fuzzy Logic System for Road Identification Using Ikonos Images

Research into both extraction of man-made objects and automatic change detection from aerial and satellite images has made significant progress in recent years. This paper presents an approach, based on a fuzzy logic system, for the identification of suburban roads in Ikonos images. The linguistic variables are the mean and standard deviation (SD) of different objects with Gaussian membership function. After the roads have been identified provisionally and their skeleton extracted, the skeleton can be vectorised and then used as direct input to a GIS for further analysis. The method was tested on an Ikonos "Geo" image covering Bilesavar in north-western Iran. For the suburban area of Bilesavar, the results showed that grey scale values ranged from 20 to 190 for non-roads and 226 to 228 for roads, the optimum width of the Gaussian kernel function was 3 and the SD was 0.4. It was also found that about 91% of main roads with a width of 6 to 12 pixels could be extracted from high resolution satellite imagery by the algorithm. The computer program for this study has been developed in visual C++ based on Windows 98     

A Microsoft VBA Application for Generating Heat Maps

A choropleth map is a form of thematic map used to portray the structural characteristics of some particular geographical distribution not apparent in data presented in tabular form. Preparation of a choropleth map starts with the assignment of map features to classes based on the value of a specific feature attribute followed by the association of classes of features with appropriate map colors or symbols. Map features are often geographical regions with naturally or artificially defined boundaries, but choropleth maps can also be prepared by segmenting the area to be mapped into a regular grid of regions. Maps prepared with each grid shaded in an intuitive manner such as blue for grids with the lowest attribute values to red for the highest values can be termed “heat maps”. This technical note describes the HeatMap Microsoft Excel application which converts information contained in a worksheet into a heat map, and then converts the heat map into a file suitable for display using mapping systems such as Google Earth. An example illustrates how the application can be used to visualize the seventeenth century frontier between the Polish/Lithuanian Commonwealth and the Ottoman Empire.     

一种基于Choquet模糊积分小波系数选择的遥感图像融合方法

为较好地保留多光谱、高分辨率遥感影像融合时的光谱信息和高分辨率信息,在小波变换基础上提出了一种基于模糊积分的融合算法,其基本思想是在IHS空间,对强度分量Ⅰ及高分辨率图像进行小波分解后,保留Ⅰ分量的低频系数,对于高频细节特征,将局部窗口内的方差、平均梯度和能量当作单因素指标,应用Choquet模糊积分综合各单因素指标得到一个综合指标,并据此来选取小波系数.实验结果表明,该算法在光谱质量改善方面明显优于IHS以及一些经典的小波变换遥感图像融合算法,是一种有效的遥感图像融合算法.