Analysis Of Geospatial Information Research Articles

Model and method of making management decisions based on the analysis of geospatial information

The article proposes a model and method of making managerial decisions based on the analysis of geospatial information. The goal of the article is to improve the model and method of making managerial decisions based on the analysis of geospatial information. The results: the algorithm of process of acceptance of the administrative decision which consists of a situational and conceptual part is offered; the algorithm of actions of the head of the organization on the basis of the developed model of acceptance of the administrative decision is offered; the situation when the quality of the decision depends on external factors on which the decision-making body does not influence is considered; the general scheme of a method of acceptance of administrative decisions on the basis of the analysis of the geospatial information is resulted. The methods used are: methods of systems analysis, decision theory, information processing, optimal solutions, probability theory. Conclusions. The model of managerial decision-making has been improved, which, unlike the known ones, is dynamic and is based on the selection of decisions that are optimal by the combined criterion, using predictive values of probabilities of environmental conditions, which ensures the validity of management decisions. The method of managerial decision-making based on geospatial information analysis, which is based on data forecasting and management decision-making models and uses the method of semantic segmentation of species images to assess the a priori probabilities of environmental conditions, further enables decision-making in conditions of risk and uncertainty. The direction of further research is the development of information technology for management decisions based on the analysis of geospatial information.

A lightweight ensemble spatiotemporal interpolation model for geospatial data

ABSTRACT Missing data is a common problem in the analysis of geospatial information. Existing methods introduce spatiotemporal dependencies to reduce imputing errors yet ignore ease of use in practice. Classical interpolation models are easy to build and apply; however, their imputation accuracy is limited due to their inability to capture spatiotemporal characteristics of geospatial data. Consequently, a lightweight ensemble model was constructed by modelling the spatiotemporal dependencies in a classical interpolation model. Temporally, the average correlation coefficients were introduced into a simple exponential smoothing model to automatically select the time window which ensured that the sample data had the strongest correlation to missing data. Spatially, the Gaussian equivalent and correlation distances were introduced in an inverse distance-weighting model, to assign weights to each spatial neighbor and sufficiently reflect changes in the spatiotemporal pattern. Finally, estimations of the missing values from temporal and spatial were aggregated into the final results with an extreme learning machine. Compared to existing models, the proposed model achieves higher imputation accuracy by lowering the mean absolute error by 10.93 to 52.48% in the road network dataset and by 23.35 to 72.18% in the air quality station dataset and exhibits robust performance in spatiotemporal mutations.

3D Visualization Process and Efficiency Analysis of Geographic Information Based on WebGL

Abstract. With the rapid development of geographic information technology, the web-based 3D visualization technology is constantly updated with the development of computers. However, the traditional 3D geographic data visualization software based on the rich-client model it has significant limitations in the display and analysis of geospatial information and it is difficult to install and use, result in that difficult to meet the application of Geo-dynamic simulation, visual analysis, and collaborative decision-making of the geographic process. In order to show the realism of spatial data more directly, this paper introduces a 3D visualization process design method of geographic information and analyses the 3D data modelling building and visualization efficiency. The process combines multiple data sources are loaded automatically, cross platform, 2D & 3D integration, and make a wider range of customers easily access to the visualization effect of 3D spatial data.

Analysis of Geospatial Information about Submergence Area using UAV

A growing number of people are using laser scanner for gathering data in relation to interior space. Laser scanner is able to reduce the required amount of time and labor while generating high-density point cloud. Hence, it is increasingly used in various applications, including construction of indoor three-dimensional model, measurement of inner structure deformation and maintenance and management of deformation of buildings. In this study, point cloud data about cave was generated by making use of the mobile hand scanner created based on SLAM technology. Moreover, this study aimed to produce a cross-section of the cave with this mobile hand scanner in order to prove its applicability. As a result, the geospatial information about 2km long cave could be constructed effectively with 30-minute data acquisition. Moreover, the cross-section of the cave was generated for proving the effectiveness of this mobile scanner. It would be possible to monitor the changes inside the cave with a periodic data acquisition. Also, the data acquired through mobile scanning would be of great help in constructing geospatial information.

무인항공시스템에 의한 수몰지역 공간정보 구축 및 분석

무인항공시스템에 의한 수몰지역 공간정보 구축 및 분석

Relationship between tsunami hazard and land condition by geospatial information analysis

Relationship between tsunami hazard and land condition by geospatial information analysis

Geospatial information analysis of land use impacts in southern Alabama

Geospatial information analysis of land use impacts in southern Alabama

Spatial Analysis for Flood Control by Using Environmental Modeling

To create the final spatial information and analysis, flood hazard maps and land development priority maps and information, data for the flood events to 2009 in north of Iran were incorporated with using Geo-spatial Information System data of physiographic divisions, geologic divisions, land cover classification, elevation, drainage network, administrative districts and population density and environmental parameters modeling. Special analysis also attention was paid to population density for the construction of the land development priority map and using satellite image analysis to determine land use changes and analysis of geo-spatial information, because highly dense populated areas represent the highly important urban and industrial areas. While geo-information technology offers an opportunity to support flood management adequate geo-spatial information is a prerequisite for sustainable development, but many parts of the world lack adequate information on environmental resources. Such information providing, which serves as an important tool for decision-making in land use planning, can help provide effective information to natural disaster management. This paper develops a framework for flood control and begins with some general comments on the importance of land use planning and outlines some current environmental issues and then presenting environmental models to use in disaster management plan by using GIS and remote sensing results. Flood control is a complex problem that requires cooperation of many scientists in different fields. The article also discusses the role that geo-information and environmental planning and GIS and remote sensing technology play in disaster management control to reduce negative impacts of flood and present proper alternatives for developing of Gorganrood in the north of Iran. Advanced high-resolution sensor technology has provided immense scope to the decision makers for analysis of flood and damages details using GIS and remote sensing.