GIS-Based Decision Support System for Village Level

2018 ◽  
pp. 275-295
Author(s):  
Subbu Lakshmi Esakki Pandian ◽  
Kiran Yarrakula ◽  
Probal Chaudhury
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Spatial Data ◽  
Rural Areas ◽  
Vital Role ◽  
Population Total ◽  
Rural Sector ◽  
Male And Female ◽  
Village Level

Decision support system (DSS) plays a vital role especially in rural areas to develop rural sector for sustainable development and socio-economic uplifting of the country. To make appropriate decisions and to develop village economy, decision support system is useful for the mandal revenue officer, collector, Surpanch, and different administrators. It deals both spatial and non-spatial data at village level and comprises various ancillary information including mandal maps and village-wise information of Anantapur and Kadapa districts of Andhra Pradesh such as number of houses, male and female, SC/ST/OBC/general (or) OC population, literate and illiterate population, total working and non-working population. Datasets are collected from district collector office, mandal revenue officer (MRO) and inserted in GIS database. This chapter makes an attempt to build features of various decisions at Anantapur and Kadapa districts by integrating various layers of information at village level.

GIS-Based Decision Support System for Village Level

2019 ◽  
pp. 1384-1402
Author(s):  
Subbu Lakshmi Esakki Pandian ◽  
Kiran Yarrakula ◽  
Probal Chaudhury
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Spatial Data ◽  
Rural Areas ◽  
Vital Role ◽  
Population Total ◽  
Rural Sector ◽  
Male And Female ◽  
Village Level

Decision support system (DSS) plays a vital role especially in rural areas to develop rural sector for sustainable development and socio-economic uplifting of the country. To make appropriate decisions and to develop village economy, decision support system is useful for the mandal revenue officer, collector, Surpanch, and different administrators. It deals both spatial and non-spatial data at village level and comprises various ancillary information including mandal maps and village-wise information of Anantapur and Kadapa districts of Andhra Pradesh such as number of houses, male and female, SC/ST/OBC/general (or) OC population, literate and illiterate population, total working and non-working population. Datasets are collected from district collector office, mandal revenue officer (MRO) and inserted in GIS database. This chapter makes an attempt to build features of various decisions at Anantapur and Kadapa districts by integrating various layers of information at village level.

scholarly journals Development of a decision support system for tsunami evacuation: application to the Jiyang District of Sanya city in China

2017 ◽  
Vol 17 (3) ◽  
pp. 335-343 ◽  
Author(s):  
Jingming Hou ◽  
Ye Yuan ◽  
Peitao Wang ◽  
Zhiyuan Ren ◽  
Xiaojuan Li
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
High Risk ◽  
Decision Support System ◽  
Travel Time ◽  
Support System ◽  
Spatial Data ◽  
Population Distribution ◽  
Numerical Models ◽  
Tsunami Inundation

Abstract. Major tsunami disasters often cause great damage in the first few hours following an earthquake. The possible severity of such events requires preparations to prevent tsunami disasters or mitigate them. This paper is an attempt to develop a decision support system for rapid tsunami evacuation for local decision makers. Based on the numerical results database of tsunami disasters, this system can quickly obtain the tsunami inundation and travel time. Because numerical models are calculated in advance, this system can reduce decision-making time. Population distribution, as a vulnerability factor, was analyzed to identify areas of high risk for tsunami disasters. Combined with spatial data, this system can comprehensively analyze the dynamic and static evacuation process and identify problems that negatively impact evacuation, thus supporting the decision-making for tsunami evacuation in high-risk areas. When an earthquake and tsunami occur, this system can rapidly obtain the tsunami inundation and travel time and provide information to assist with tsunami evacuation operations.

Application of Multi-Dimensional Analysis Technology in Telecom Industry

2011 ◽  
Vol 219-220 ◽  
pp. 643-647
Author(s):  
Li Yong Chen ◽  
Xiu Ye Yin
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Dimensional Analysis ◽  
Support System ◽  
Rapid Development ◽  
Vital Role ◽  
The World ◽  
Telecom Industry ◽  
The Right ◽  
Leading Enterprises

With the rapid development of China's telecom industry, the management of domestic enterprises are constantly changing. Operate method was closed to internationalization constantly. In this process, the technology of OLAP plays a very vital role for the development of enterprises. China's telecom industry should depend on the technology of OLAP to get an efficient decision support system to make an accurate in time efficient decision if they want to survive in the world keen competition, and then leading enterprises moving in the right direction. This paper introduced Multi-dimensional analysis technology, Illustrates the application of drilling and rotation Combined with concrete examples. Hope to provide some help for the development of enterprises, promote the rapid development of China's telecom industry through this paper.

Spatial OLAP and Multicriteria Integrated Approach for Decision Support System

2021 ◽  
pp. 1114-1142
Author(s):  
Charef Abdallah Bensalloua ◽  
Djamila Hamdadou
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Spatial Data ◽  
Unified Modeling Language ◽  
Integrated Approach ◽  
Multidimensional Analysis ◽  
Modeling Language ◽  
Spatial Decision Support System ◽  
Conflict Situations

This article describes how Spatial On-Line Analytical Processing, such a decisional technology, offers the possibilities of spatial and multidimensional analysis of data stored in multidimensional structure namely spatial data warehouse. However, this technology is limited in the quality aspect of the decision related to the multicriteria consideration. In the current article, the objective is to propose a Spatial Decision Support System namely “Silvicultura” for facilitating decision making in complex situations. This approach is based on integrating multicriteria analysis with SOLAP in order to enrich the spatial and multidimensional analysis with the contribution of MCA tools for mitigating conflict situations. The authors have based their proposal modeling on Unified Modeling language, since it is a well-known standard modeling language and can be easily extended for multidimensional modeling. Finally, in order to validate their proposal, the authors present a case study to show how to use it in the agroforestry management.

Web MCA-based Decision Support System for Incident Situations in Maritime Traffic: Case Study of Adriatic Sea

2017 ◽  
Vol 70 (6) ◽  
pp. 1312-1334 ◽  
Author(s):  
Nenad Mladineo ◽  
Marko Mladineo ◽  
Snjezana Knezic
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Spatial Data ◽  
Adriatic Sea ◽  
Weather Forecasting ◽  
Preference Ranking ◽  
Maritime Traffic

This paper describes a Multi-Criteria-Analysis (MCA)-based Decision Support System (DSS) developed for the management of incidents in maritime traffic. The developed DSS helps to organise a large quantity of information related to emergency management, spatial data and “live” data (radar data, weather forecasting data), to make it available to decision makers in a comprehensible and user-friendly way. Special care has been taken to model human Decision-Making (DM) processes during incident situations. Since the DM process is always multi-criterial, a Multi-Criteria Decision-Making (MCDM) method called Preference Ranking Organisation Method for Enrichment Evaluations (PROMETHEE) is used. However, a simplified variation of PROMETHEE II has been utilised to make results more understandable to non-expert users. The aim of this research is to incorporate effective DSS in human DM processes, thus reducing the possibility of making poor decisions. The concept of Web MCA-based DSS is presented as a case study: Web DSS developed for the east coast of the Adriatic Sea.

scholarly journals A Customized Decision Support System for Renewable Energy Application by Housing Association

2019 ◽  
Vol 11 (16) ◽  
pp. 4377 ◽  
Author(s):  
Aleksandra Besser ◽  
Jan K. Kazak ◽  
Małgorzata Świąder ◽  
Szymon Szewrański
Keyword(s):  
Renewable Energy ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Spatial Data ◽  
Housing Association ◽  
Local Scale ◽  
Environmental Data ◽  
Housing Associations ◽  
Entire Area

One of the major problems in socio-environmental systems is the growing depletion of non-renewable resources and environmental degradation, resulting from inadequate environmental management and planning. Deepening environmental problems have forced countries to create management instruments that will help repair damage and support environmental protection efforts. The aim of this research is to develop a customized decision support system for the management of renewable energy based on the existing Geographic Information Systems (GIS). The proposed tool enables assessing the potential of solar energy production at the local scale, analyzing each rooftop. Due to the scale of the analyzed area and the details of the assessment, the tool is customized to the needs of housing associations. The system combines an existing GIS tool for calculating the solar radiation potential of rooftops (SOLIS) together with Tableau software that was used to aggregate and analyze data. In order to present the applicability of the developed tool, visualizations were prepared based on housing buildings managed by the “Biskupin” Housing Association in Wrocław (Poland) which is responsible for the management of 3415 residential premises. The created system based on spatial and environmental data will help to decide how to manage the available resources and the environment at the local scale while reducing the pressure on the environment. The tool allows for the aggregation, filtering and presentation of spatial data for the entire area of a housing association, as well as for a single building.

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