A fine fuzzy spatial partitioning model for line objects based on computing with words and application in natural language spatial query

For the performance of geographic information systems, it has been widely recognized that efficient data structures and algorithms supporting proximity based access to spatial data are a crucial ingredient. Because of that, in the last years, a lot of data structures for storage of multidimensional non-point objects have been proposed in the literature (for an overview see our tutorial introduction in this volume). Almost all of these approaches are made to support queries based on spatial neighborhood of objects, so-called proximity queries. Common examples of such proximity queries are range queries, returning all objects intersecting a given (rectangular) region, or nearest neighbor queries, determining the object nearest to a given point. But a geographic or cartographic information system should also support queries that do not exclusively refer to the spatial neighborhood of objects. For example, different versions of spatial data must be organized such that proximity queries to any version of the data can be answered efficiently. Or, given a set of object classes, a spatial query that involves an arbitrary combination of these classes should also be supported. Because of the growing size of data sets to be handled in geographic information systems, an appropriate data organisation to support such and several other application-specific queries becomes more and more important. In this paper, we will present two approaches for access structures supporting the two types of queries mentioned above. Handling of versioned, spatial data is the topic of Section 2, while Section 3 discusses queries on some classes selected from the set of object classes stored in a geographic information system.

The concept of an intelligent geographic information system (IGIS) is not new. However, the term represents a complex set of ideas and methods that cannot be combined into one method, theory, or concept. This chapter attempts to describe this new domain in geographic information system science and technology. Here, we present selected results of theoretical investigations and technological developments to share the vision of IGIS.

С.А. Глушенко - кандидат экономических наук, старший преподаватель кафедры информационных систем и прикладной информатики, Ростовский государственный экономический университет (РИНХ)Адрес: 344002, г. Ростов-на-Дону, ул. Большая Садовая, д. 69E-mail: gs-gears@yandex.ru В статье обосновывается важность применения оценки рисков при реализации системы обеспечения информационной безопасности. Рассматриваются наиболее распространенные методики оценки риска и предлагается использовать для этих целей теорию нечеткой логики. Описывается предложенная нечеткая продукционная модель (НПМ), в которой определены семь входных лингвистических переменных, характеризующих факторы риска, четыре выходных лингвистических переменных, характеризующих риски различных областей информационной безопасности, а также четыре базы правил. Отмечается, что НПМ является первым приближением для рассматриваемой предметной области и требует оптимизации с целью минимизации ошибки выходов модели. Рассматриваются наиболее распространенные методы оптимизации параметров нечетких моделей и обосновываются преимущества применения методов, основанных на использовании нейро-нечетких сетей (ННС). Описывается процесс преобразования элементов нечеткой модели, таких как блок фаззификации, блок базы правил и блок дефаззификации во фрагменты нейронной сети. Результатом данного процесса является нейро-нечеткая сеть, соответствующая нечеткой модели. Построение разработанной ННС осуществляется на основе системы нейро-нечеткого вывода (adaptive neuro-fuzzy inference system, ANFIS) посредством применения специализированного пакета Neuro-Fuzzy Designer программного средства MATLAB. Обучение модели было выполнено гибридным методом, который представляет собой комбинацию методов наименьших квадратов и обратного распространения ошибки. Результатом данного процесса является оптимизация (настройка) параметров функций принадлежности входных лингвистических переменных. Использованный подход нейро-нечеткого моделирования позволил получить более адекватную нечеткую продукционную модель, которая позволяет проводить лингвистический анализ рисков информационной безопасности организации. Полученные с ее помощью сведения позволяют ИТ-менеджерам определять приоритеты рисков и разрабатывать эффективные планы мероприятий по снижению влияния наиболее опасных угроз. [1] Исследование выполнено при финансовой поддержке РФФИ, в рамках научного проекта № 16-31-00285 «Методы и модели нечеткой логики в системах принятия решений управления рисками»

To make sure that regional reconstruction goes smoothly, it is important to know how rural construction areas in a river basin change over time and space and what factors affect those changes. This study focuses on the rural construction areas in the Nanxi River Basin. Through geographic information systems’ spatial analysis methods, the construction area morphology, center of gravity migration, and agglomeration degree are analyzed to reveal its spatiotemporal evolution from 1990 to 2020. The geographical detector is used to explore the interaction of multidimensional driving factors such as natural geography, socio-economic development, and cultural heritage protection. The research results show that (1) the rural construction area in the Nanxi River Basin shows an evolution trend of “agglomeration expansion and northward shift of the center of gravity.” (2) Cultural, economic, and natural factors all play a part in how rural construction areas change over time. Cultural factors, like the distance between farms and the layout of educational resources, have the most significant impact, followed by economic and natural factors. (3) The study also suggests a “cultural gene-natural base-economic potential” model that can help us understand how to protect cultural heritage and boost the economy at the same time. This result has direct guiding significance for the implementation of China’s rural revitalization strategy. It can give natural resource planning departments a scientific way to figure out the best way to use land and give cultural heritage management agencies a way to come up with safe development plans. It also provides a reference for the sustainable development path of resource-rich villages around the world.

Geographic information systems (GIS) can assist researchers and practitioners engaged in community-specific analyses that focus on older populations and their resource environments. Although some gerontologists may be using GIS for data visualization (i.e., to present data in map form), GIS spatial analytical functions appear to be underused in studies of older populations. This article examines the capacity and potential of GIS in gerontological research and practice by (a) briefly defining GIS; (b) describing the utility of some basic GIS visualization and spatial analytical methods using an illustrative, community-based gerontological study; and (c) discussing challenges and opportunities in the application of this information technology.

Creation of a consistent 3D model of a city requires accurate data. Usually, accuracy assurance problems of data are solved by time consuming and expensive process of collecting and aligning with ground control points (GCP). Therefore, alternative methods become important. Using existing Geographic Information Systems (GIS) databases may decrease the time and cost of creating a reference dataset by reducing the number of GCPs required for producing high quality 3D data or GIS databases can serve as reference data. For this purpose, new spatial data analysis methods are needed to assure that GIS databases are of high-quality. In this paper, we propose a novel methodology and its sample development for comparative spatial analysis of digitized point cloud and the corresponding GIS database in order to statistically assess opportunities to align Mobile Mapping Systems (MMS) data with existing GIS databases or to improve involved datasets. The method is evaluated using LiDAR data provided by Estonian company Reach-U Ltd. and GIS database layers from different Estonian open and closed databases.

Fuzzy‐logic‐based methods and fuzzy logic formalism have been demonstrated as appropriate to address the uncertainty and subjectivity in complex environmental problems. This study investigates the use of three fuzzy logic methods in fisheries analysis, aiming towards the grouping and ranking of fishing subareas, according to their fisheries yield. Initially, a simple fuzzyc‐means clustering model was applied to the fishing subareas examined. A rule‐based Mamdani‐type fuzzy inference system was then developed to allow the direct fishing subarea classification. Finally, a species‐economic value weighted global fuzzy membership model was introduced, serving as an indirect classification and ranking scheme. Global memberships were plotted on simple ternary diagrams, producing representations that serve as tools in fisheries management. All methods examined the performance of the Greek fishing subareas, based on the annual landings series of the 10 most abundant fish species in terms of landed biomass, during the period 1985–1999.

Spatial aspects are often crucial for agriculture-related companies. This paper presents how methods of spatial analysis can help to elaborate regional network planning strategy for a large agricultural bank. Corporate reporting microdata, a novel source for the research of Russian business, were processed and visualized with geographical information system (GIS). The overlay of agribusiness clusters and bank accessibility zones revealed uneven patterns of its current branch network. This approach was applicable as a first step for the location choice strategy. The results allowed us to propose a new office location in order to cover territories for the further development of the bank.

An increasing number of emerging web database applications deal with large georeferenced data sets. However, exploring these large data sets through spatial queries can be very time and resource intensive. The need for interactive spatial queries has arisen in many applications such as Geographic Information Systems (GIS) for efficient decision-support. In this paper, we propose a new interactive spatial query processing technique for GIS. We present a family of the Incremental Refining Spatial Join (IRSJ) algorithms that can be used to report incrementally refined running estimates for aggregate queries while simultaneously displaying the actual query result tuples of the data sets sampled so far. Our goal is to minimize the time until an acceptably accurate estimate of the query result is available (to users) measured by a confidence interval. Our approach enables more interactive data exploration and analysis. While similar work has been done in relational databases, to the best of our knowledge, this is the first work using this approach in GIS. We investigate and evaluate different sampling methodologies through extensive experimental performance comparisons. Experiments on both real and synthetic data show an order of magnitude response time improvement relative to the final answer obtained when using a full R-tree join. We also show the impact of different index structures on the performance of our algorithms using three known sampling methods.

The sediments of the Dongting Lake come from four channels (one of them was closed in 1959), connected with the Yangtze River, four tributaries (Lishui, Yuanjiang, Zishui and Xiangjiang) and local area, and some of them are transported into the Yangtze River in Chenglingji, which is located at the exit of the Dongting Lake, some of them deposit into drainage system in the lake region and the rest deposit into the lake. The annual mean sediment is 166,555xl04t, of which 80% come from the four channels, 18% from the four tributaries and 2% from local area, whereas 26% of the total sediments are transported into the Yangtze River and 74% deposited into the lake and the lake drainage system. Based on topographic maps of 1974, 1988 and 1998, and the spatial analysis method with geographic information system (GIS), changes in sediment deposition and erosion are studied in this paper. By overlay analysis of 1974 and 1988, 1988 and 1998, erosion and sediments deposition areas are defined. The main conclusions are: (1) sediment rate in the lake is larger than erosion rate from 1974 to 1998. The mean deposition in the lake is 0.43 m; (2) annual sediment deposition is the same between 1974–1988 and 1988–1998, but the annual volume of deposition and erosion of 1988–1998 is bigger than that in 1974–1988; (3) before the completion of the Three Gorges Reservoir, there will be 7.82xl08m3of sediments deposited in the lake, which would make the lake silted up by 0.33 m; (4) in the lake, the deposition area is found in the north of the east Dongting Lake, the south-west of the south Dongting Lake, and the east of the west Dongting Lake; while the eroded area is in the south of the east Dongting Lake, the middle of the south Dongting Lake, the west of the west Dongting Lake, as well as Xiangjiang and Lishui river flood channels.

The output function of standard affine Takagi-Sugeno systems presents shape failures and does not have continuous derivatives in the corresponding output function. These characteristics give an undesirable behaviour in many practical applications such us fuzzy control or fuzzy modelling. In order to avoid these problems, this paper presents a new method for deriving a shape-preserving affine Takagi-Sugeno model, using a standard trapezoidal fuzzy partition specification. Each univariate trapezoidal fuzzy partition is primarily transformed into an equivalent triangular one. An adaptive first-order symmetrical B-spline filter is later applied on each triangular partition in order to derive a mixed linear-rational spline fuzzy partition. The obtained model retains monotony, convexity and positivity of the corresponding control points defined on the cores of the original fuzzy partition. These properties are due to the characteristics of the linear-rational spline partitions obtained. Finally, a simple example is given to practically show the usefulness of the approach.

Spatial Data Grid allows for solving larger problems and executing applications that traditional Web GIS (Geographic Information System) can not handle efficiently. In Spatial Data Grid, all functions of GIS are encapsulated as stateful Web Services. The purpose of this paper is to design and implement a new mechanism to organize miscellaneous Vector Map Services, built on GT4 (Globus Toolkit 4), and based on WSRF (Web Services Resource Framework). In this paper, we demonstrate the general procedure to build a Grid Vector Map Service (spatial query, buffer analysis, overlay analysis, etc) based on GT4. We design and implement two kinds of Vector Map Services: Domain Service and Node Service, which can be chosen by users after they log in the Grid Portal correctly. Finally, we present some experimental results and draw some conclusions. The new mechanism allows more flexible usage of available resources in the Grid and is expected to decrease the efforts needed to configure and maintain nodes in the Grid, and it buffers some frequently accessed information in resources, in this way, access times of GIS Server will be sharply decreased and query time will be reduced.

As the development of the theory and technology of geographical information, Geographical Information System (GIS) has been widely applied in variety of industries. It usually refers to the analytical problem of multi-factor in GIS thematic application. In this field, the determination of factors' weight is a common and important problem. It actually deals the data when processing the spatial analysis applying GIS, for example, according to the importance of some factor, assign some value to it then process spatial overlay operation using the values and finally conclude some evaluation or result. In reality, there are many factors that affect the some kind of evaluation. Usually, we choose several more important factors as the evaluation criterion in order to make convenient for research. Then we assign some weight values to these factors and process spatial analysis then conclude some decision or evaluation to make support for decision-making. We can choose the factors that can make more impaction on the evaluation or decision-making using the method of Analytical Hierarchy Process (AHP). However, it has strong subjectivity of the factors' weight values assigned by this method. Rough set theory, which can effectively remove the impaction made by artificial factors, can make up the deficiency. It can make the spatial analysis more objective and more effective combining the two methods in GIS spatial analysis.

This paper proposed a max-min-entropy-based fuzzy partition method for fuzzy model based estimation of human operator functional state (OFS). The optimal number of fuzzy partitions for each I/O variable of fuzzy model is determined by using the entropy criterion. The fuzzy models were constructed by using Wang-Mendel method. The OFS estimation results showed the practical usefulness of the proposed fuzzy modeling approach.

The authors consider the application of geoinformation mapping in the analysis of hazardous processes using space images, digital terrain models, as well as comparative analysis of the landscape map and the map of hazardous exogenous processes. As a result, a large-scale map of hazardous processes within the Mondy depression was created. At the first stage, space images, physical and geographical conditions were analyzed, as well as the morphometric indicators of the territory. On the basis of that analysis classes of hazardous exogenous processes that affected the landscapes of the depression were identified. Further the classes of hazardous exogenous processes were compared with landscape facies, within the contours of which hazardous processes of different intensity are common. Calculation of hazardous exogenous processes using the data of morphometric indicators was made, the information on the long-term change in the main elements of the climate of the study area obtained. The method of spatial analysis in geographic information systems on a vector basis marked the main hazardous exogenous processes that have developed in the territory of the Mondy depression. The gravitational-slope class, represented by collapses and screes, is most widespread in the investigated area. Fluvial class of the dangerous exogenous processes is mostly indicated by mudflows in the valleys of small and temporary watercourses. Cryogenic class of these processes is least developed.