Intelligent Geographic Information Systems Research Articles

FULL-STACK розробка інтелектуальної системи розвитку міграції населення

A generalised model of population migration is proposed. On the basis of the model of population migration, the article develops models of: a set of directions of population flows, which are formed on internal and external flows of the State; duration of migration, which is determined by its nature in time, including permanent or irreversible duration of migration, movement for a relatively short time, annual movement of people and pendulum duration of migration; type and form of migration. A model of indicators of actual migration (resettlement) that can characterise the overall level of mobility of the population of the territories, the scale, structure, directions and effectiveness of migration flows for a given period is developed and their groups are divided. It is proposed that the results of population migration should be presented in the form of a number of absolute and relative indicators for the purpose of further regression analysis of data, namely, those who arrived for permanent residence from other settlements; those who left for permanent residence to other settlements; migration balance or mechanical growth. Inter-rayon relations are characterised by the strength of migration flows. To obtain the results of migration, we take into account the strength of migration flows, which depend on the population of the territories between which the exchange takes place and on their location. The result of this exchange is expressed in the migration balance or by means of efficiency coefficients of migration ties. The intensity of migration exchange, independent of the population size of both the areas of origin and the places of settlement, is determined by the intensity coefficients of migration ties. The types of migration intensity coefficients are formed depending on the properties, namely the intensity coefficients of arrival (immigration), departure (emigration), reverse migration, and net migration. The intelligent geographic information system implements the lightgbm algorithm for population migration forecasting, which is a decision tree with gradient reinforcement. For data analysis, the migration forecasting system includes regression analysis and neural networks and is capable of predicting international migration or migration between different countries.

Formation of a data network in a geo-information system for forest inventory

This article considers the application of intelligent geographic information system in forestry. A distinctive feature of the proposed system is the use of data processing module included in the GIS. Ways of increasing the efficiency of network resources are also considered. Recommendations have been formulated, which will enhance the quality of service, transmission speed, efficiency and scalability of routing protocols, cost and signal quality in GIS.

A Heuristic Approach for GPS-Based Routing

Vehicle routing (such as for package delivery) presents challenges for operations planning and operations control. Planning ensures that vehicles are assigned to “good” routes, and control enables routes to be changed in real time in response to changes in destination requirements. Both planning and control can be accomplished using web-based, intelligent geographic information system tools to rapidly generate a heuristic solution using an embedded algorithm, rather than the established approach of using explicit customized optimization models. The authors contrast the established approach of using customized integer optimization models to a heuristic that integrates human judgment with Google Maps travel time data to solve vehicle routing problems. This paper discusses the data requirements, simplifying assumptions, and practical performance of both approaches. The advantage of the heuristic approach is that genuine, useful access to much of the power of highly sophisticated OR network models can be provided to large numbers of analytically unsophisticated managers, along with enhanced operational control.

Spatial-temporal dynamic simulation of anti-noise urban expansion based on fuzzy intelligent control system and GIS

On the basis of FHWA model of the Federal Highway Administration and the combination with the geographic information system (GIS) and Fuzzy intelligent control system, the group independently researches and develops a simulation and evaluation system for the traffic noise in the urban road. This system is able to simulate the influence of traffic source, point source, and arbitrary shape area source on the urban sound field environment. It is combined with the noise radiation and the communication model, and the occlusion and attenuation by the buildings and forest belts on the traffic noise have been considered. It can calculate the traffic noise in urban areas and directly render the predicted results on the GIS map, and form a traffic noise map, which visually and clearly displays the pollution degree and distribution map of the traffic noise in urban areas. The noise maps of Guangzhou inner ring roads and Zhujiang New Town are drawn to provide scientific decision-making basis for the control of urban traffic noise pollution.

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The main features of an efficiency evaluation of positional (stationary and autonomous) sonar systems at the design stage and deciding on the coordinates of the antenna installation site based on modeling and visualization of the expected surveillance zones using intelligent geographic information systems are considered in the paper. The issues of intellectual decision support for the rational spatial distribution of receiving antennas are considered. The influence of the information support quality of geographic information systems on the calculations accuracy of expected surveillance zones of the sonar systems under the various hydrological and acoustic conditions is assessed. A new performance indicator in the form of spatial volume of the expected surveillance zone is proposed. A method for solving the optimization problem of finding the maximum volume of the illuminated space as a coordinates function of the antenna placement within a given observation area, with fixed technical characteristics of the monitoring system and given noise conditions, acoustic characteristics of the detection object and the observation time has been developed. The proposed approach to selecting the rational variant of the receiving antennas location of positional hydroacoustic facilities and systems in the interests of dispatching geospatial processes using as a mean of intelligent support the modern hardware and software complex realizing the specified selection by such efficiency indicator as volume of illuminated space, in the conditions of a two-dimensionally inhomogeneous model of medium, close to real hydrological-acoustic conditions, allows to increase the accuracy of assessing the illumination efficiency of underwater environment of positional hydroacoustic means and systems and significantly reduce the design and development time as compared with the traditional approach, requiring expensive field observation over a long period of time.

SUPPORT FOR DECISION-MAKING ON THE RATIONAL PLACEMENT OF ANTENNAS OF UNDERWATER COMMUNICATION SYSTEMS IN THE INTERESTS OF DISPATCHING OF GEO-SPACE PROCESSES

The paper considers the main features of evaluating the efficiency of positional and mobile underwater communication systems with immersed correspondent objects at the stage of their design and deciding on the coordinates of the installation site of the transmitter-receiver antennas based on modeling and visualization of the expected underwater communication zones using intelligent geographic information systems. The influence of the quality of information support of geographic information systems on the accuracy of the calculation results of the expected zones of underwater communication in various hydrological and acoustic conditions is assessed. Research subject. The article is devoted to the issues of evaluating the efficiency of underwater communication and intellectual decision-making support for rational spatial distribution of receiving and transmitting antennas of underwater communication systems with immersed correspondent objects. Method. A method for optimizing (choosing a rational option) the spatial distribution of receiving and transmitting antennas of positional underwater communications or the depth of setting of lowered and towed antennas of marine underwater communications using specialized software and information tools and geographic information systems is considered. Core results. A new performance indicator is proposed in the form of the spatial volume of the underwater communication zone and a method has been developed to optimize the spatial distribution of the receiving and transmitting antennas according to the criterion of the maximum volume of the expected underwater communication zone for given hydrological and acoustic conditions in the area. Practical relevance. The introduction of the developed method into the systems of sonar calculations and automated decision support for advanced underwater communication systems will significantly reduce the decision-making time for the placement of antennas (when designing or planning applications) and increase the efficiency (stability and range) of underwater communication means with immersed objects - correspondents.

Understanding the New Human Dynamics in Smart Spaces and Places: Toward a Splatial Framework

The smart technologies led by advances in artificial intelligence, machine learning, and the emerging data science in recent years are transforming many facets of society in profound ways. One of these affected areas is the experience of human dynamics in general and human mobility in particular with the growing maturity of smart technologies. The goal of this article is to critically examine the concepts of space and place in geography in general and in geographic information science (GIScience) in particular so that intelligent geographic information systems incorporating concepts of smart space and smart place can be developed to support human dynamics research. We argue that the current discussions on smart technologies are conceptually constrained due to their confinement to absolute space and physical place. By engaging research on smart technologies with geography and GIScience, we seek to move beyond the crude, and often simplistic, conceptualizations of space and place by synthesizing the multiple dimensions of both space and place. By doing so, we can better understand human dynamics through a synergistic perspective of both space and place. The space–place (splatial) framework proposed in this article will enable us to creatively study the human dynamics in the age of smart technologies. Our approach will not only allow us to better understand human dynamics but also advance and enrich our theoretical and methodological frameworks for studying smart technologies and the profound social impacts from a geographic perspective. Challenges for the implementation of the proposed framework are discussed and directions for future research are highlighted. Key Words: GIScience, human dynamics, place, space, splatial framework.

Interpreting the Fuzzy Semantics of Natural-Language Spatial Relation Terms with the Fuzzy Random Forest Algorithm

Naïve Geography, intelligent geographical information systems (GIS), and spatial data mining especially from social media all rely on natural-language spatial relations (NLSR) terms to incorporate commonsense spatial knowledge into conventional GIS and to enhance the semantic interoperability of spatial information in social media data. Yet, the inherent fuzziness of NLSR terms makes them challenging to interpret. This study proposes to interpret the fuzzy semantics of NLSR terms using the fuzzy random forest (FRF) algorithm. Based on a large number of fuzzy samples acquired by transforming a set of crisp samples with the random forest algorithm, two FRF models with different membership assembling strategies are trained to obtain the fuzzy interpretation of three line-region geometric representations using 69 NLSR terms. Experimental results demonstrate that the two FRF models achieve good accuracy in interpreting line-region geometric representations using fuzzy NLSR terms. In addition, fuzzy classification of FRF can interpret the fuzzy semantics of NLSR terms more fully than their crisp counterparts.

Dealing with Resilience Conceptualisation. Formal Ontologies as a Tool for Implementation of Intelligent Geographic Information Systems

The paper addresses the issue of the representation of the concept of resilience (urban, environmental and landscape resilience) in the context of geographic information systems. In the current technical and scientific debate, resilience is configured as an intrinsic property of a system to switch from one equilibrium state to another without losing its basic internal structure, also definable in terms of identity. The paths to success or stable growth as well as those of continuing and recursive crisis, although already explained in macroeconomic terms through the mechanisms of accumulation and multiplication (cumulative advantage), are also interpreted in terms of resilience. So, in the field of studies on spatial planning, the concept of resilience became particularly significant in an era characterized by great instability of social systems, deep economic and environmental crisis. In the process of urban and regional planning, conceive the development of an urban region in terms of resilience means using the logic of complex systems and then adapt in this way their methods of knowledge representation. The concept of resilience is multi-dimensional and vague, so its conceptualization is complex. The formal ontologies can be a useful tool to orient geographic information systems towards more complex forms of knowledge representation and to adapt them to the requirements of logic and formal complex systems, such as today's urban regions.

Locating Soil Tests with Intelligent Compaction Data and Geographic Information System Technology

Intelligent compaction is gaining popularity as a tool for evaluating soil compaction. Unfortunately, intelligent compaction equipment collects an overwhelming amount of data, especially for an inspector who is making decisions in the field. The goal of this approach is to identify optimal places to perform field compaction tests on the basis of relative compaction values. This paper presents a geographic information system application that analyzes and views intelligent compaction data to support in-field decision making. To facilitate the analysis, intelligent compaction data were converted from geographic coordinates into a regularized station and offset coordinate system. A grid of points at 1-ft intervals was placed over the intelligent compaction data, and spatial analysis tools were used to average the compaction values within various distances of the grid points. On the assumption that 95% of a soil lift must be compacted correctly, statistical analyses were performed to identify points that fell between the 4th and 6th percentiles of the compaction value. A positive outcome from field compaction tests at these locations would indicate that at least 95% of the lift was properly compacted; a negative outcome would indicate that less than 95% of the lift was compacted adequately and that additional compaction work was required.

Hierarchy of knowledge in GIS

An intelligent geographic information system (GIS) has to handle various types and huge volumes of geoscience-related knowledge as well as enormous amounts of data and information. More recent attention concentrates on collection, representation, management, and usage of knowledge. This article presents a three-tier hierarchy for geoscience knowledge in a GIS. The first tier is for knowledge of data. It includes knowledge of feature objects definition, data structure, data model, and relations among data as well as rules, restrictions, and regulations about data. The second tier is for knowledge of processing. It describes analysis models, data processing procedures, workflows, and conditions. The third tier contains knowledge of a GIS for the public sector. This tier provides knowledge to people on how to access this GIS and what the GIS can do. The three-tier hierarchy of knowledge in a GIS provides an understandable and practical category frame to handle geoscience knowledge. One of the advantages of this hierarchy is that it separates system resource consumption into different stages so it can avoid exhausting the system at peak times when the GIS handles a complex, large task.

Computing and managing cardinal direction relations

Qualitative spatial reasoning forms an important part of the commonsense reasoning required for building intelligent geographical information systems (GIS). Previous research has come up with models to capture cardinal direction relations for typical GIS data. In this paper, we target the problem of efficiently computing the cardinal direction relations between regions that are composed of sets of polygons and present two algorithms for this task. The first of the proposed algorithms is purely qualitative and computes, in linear time, the cardinal direction relations between the input regions. The second has a quantitative aspect and computes, also in linear time, the cardinal direction relations with percentages between the input regions. Our experimental evaluation indicates that the proposed algorithms outperform existing methodologies. The algorithms have been implemented and embedded in an actual system, CARDIRECT, that allows the user to 1) specify and annotate regions of interest in an image or a map, 2) compute cardinal direction relations between them, and 3) pose queries in order to retrieve combinations of interesting regions.

Individual and multipersonal fuzzy spatial relations acquired using human–machine interaction

A major challenge in constructing intelligent geographic information systems (GIS) has been the specification of the meaning of spatial relations so they can be incorporated as linguistic terms in geographic query languages or as fuzzy relations in the geographic object model. This study used an intelligent program that chose questions to ask of users so the fuzziness of the spatial relation concept would be reduced. The users were required to provide only yes/no answers. From this question and answer session the program constructs a fuzzy base relation. Results obtained from human subjects are presented. Two geographic databases were used, each providing a different spatial context. For each database there were eight sessions: one session for each of the spatial relation terms, four terms for nearness and four terms for farness terms, Multiperson concept construction was explored using the agreement, global evidence, combined agreement and global evidence, and Zimmermann's method. Results suggest that even with a relatively small, simple spatial database, significant semantic variation does exist. This result has significant implications for maintaining semantic integrity within and between geographic databases as well as managing semantic variation.

Development of hypermap database for ITS and GIS

The purpose of this paper is to develop a methodology that combines video images and digital maps for intelligent transportation systems (ITS) and geographic information systems (GIS). In this study, (1) the database structure of a digital map for integrating video images; (2) the georeferencing method of moving images by the time-tag; and (3) the hypermap database using Differential Global Positioning System (DGPS), were developed. The database was designed to replay a video image corresponding to a point on a two-dimensional digital map. Furthermore, the linkage of various objects existing both in video image and digital map was accomplished in this methodology. The practical use of hypermap research was examined by applying it to the proposed moving image georeferencing method. Furthermore, the level of accuracy was evaluated by utilizing the exact location of street lamps as control points, with the result that 92.8% of control points were included within two consequent frames.

From Biodiversity to Ecodiversity: A Landscape‐Ecology Approach to Conservation and Restoration

AbstractAn environmental revolution is urgently needed that will lead to a post‐industrial symbiosis between man and nature. This can be realized only if the present unrestrained biological impoverishment and neotechnological landscape degradation are replaced by the creation of healthy and attractive landscapes. Restorationists can fulfill a vital role in this process. They must broaden their scales from biodiversity restoration in small, protected nature islands to the large‐scale restoration of natural and cultural landscapes. To achieve this they must restore not only the patterns of vegetation but also the processes that create these patterns, including human land uses. Their goal should be to restore the total biological, ecological, and cultural landscape diversity, or “ecodiversity,” and its intrinsic and instrumental values of highly valuable, endangered seminatural, agricultural and rural landscapes. For this purpose it is essential to maintain and restore the dynamic flow equilibrium between biodiversity, ecological, and cultural landscape heterogeneity, as influenced by human land uses, which occur at different spatial and temporal scales and intensities. Recent advances in landscape ecology should be utilized for broader assessment of ecodiversity, including proposed indices of ecodiversity, new techniques such as Intelligent Geographical Information Systems (IGIS), and Green Books for the holistic conservation and restoration of valuable endangered landscapes. Restoration ecology can make an important contribution to an urgently needed environmental revolution. This revolution should lead to a new symbiosis between man and nature by broadening the goal of vegetation restoration to ecological and cultural landscape restoration, and thereby to total landscape ecodiversity.

From conventional to knowledge-based geographic information systems

Artificial intelligence (AI) has received an explosion of interest during the last 5 years in various fields. There is no longer any question that expert systems and neural networks will be of central importance for developing the next generation of more intelligent geographic information systems. Such knowledge-based geographic information systems will play an especially key role in spatial decision and policy analysis related to issues such as environmental monitoring and management, land use planning, motor vehicle navigation, and distribution logistics. This paper sketches briefly the major characteristics of conventional geographic information systems, and then looks at some of the potentials of AI principles and techniques in a GIS environment where emphasis is laid on expert systems and artificial neural networks technologies and techniques.

Development of intelligent geographical information systems

Abstract The analysis of geographical information is compared with other production processes in which a user can only accept an end-product if it meets certain quality requirements. Whereas users are responsible for defining the levels of quality they need to use the results of the analyses of geographical information systems in their work, database managers, experts and modellers could greatly assist users to achieve the quality of results they seek by formalizing information on: (1) data collection, level of resolution and quality; (2) the use of the basic analytical functions of the geographical information system; and (3) the data requirements, sensitivity and error propagation in models. These meta-data could be incorporated in a knowledge base alongside the geographical information system where, together with procedures for on-line error propagation, a user could be advised on the best way to achieve a desired aim. If the analysis showed that the original constellation of data, methods and models could not achieve the aim with the desired quality, the intelligent geographical information system would present a range of alternative strategies—better methods, more data, different data, better models, better model calibration, or better spatial resolution—and their costs by which the user's aims could reasonably be achieved.

Interactive machine acquisition of a fuzzy spatial relation

The modeling of spatial relations is fundamental to the development of intelligent geographical information systems for applications in the geosciences. However, some spatial relations have an inherent fuzziness about them that is difficult to formalize. This paper presents a method and program for machine acquisition of fuzzy base relation near. Techniques from artificial intelligence such as adaptive parameter adjustment, generate and test, and heuristic search are used in a program to interrogate a user and construct a fuzzy base relation. Base spatial relations acquired through this program can be used subsequently to populate the knowledge base of a fuzzy knowledge-based system and provide more realistic answers to geographical queries.

Knowledge-based geographic information systems (KBGIS): New analytic and data management tools

In its simplest form, a geographic information system (GIS) may be viewed as a data base management system in which most of the data are spatially indexed, and upon which sets of procedures operate to answer queries about spatial entities represented in the data base. Utilization of artificial intelligence (AI) techniques can enhance greatly the capabilities of a GIS, particularly in handling very large, diverse data bases involved in the earth sciences. A KBGIS has been developed by the U.S. Geological Survey which incorporates AI techniques such as learning, expert systems, new data representation, and more. The system, which will be developed further and applied, is a prototype of the next generation of GIS's, an intelligent GIS, as well as an example of a general-purpose intelligent data handling system. The paper provides a description of KBGIS and its application, as well as the AI techniques involved.

Artificial Intelligence and Natural Resource Management

The use of artificial intelligence (AI) in natural resource management began with the development of expert systems for problem-solving and decision-making. The use of expert systems in turn led to the development of other AI procedures pertinent to natural resource management. Of particular significance are (i) integrated expert systems, which link management models with natural resource models; (ii) intelligent geographic information systems, which permit interpretation of relations within and among landscape data themes; and (iii) AI modeling of animal behavior and interaction with the environment. These procedures provide new ways to view classic problems in systems analysis.