Pub Date : 2019-01-01DOI: 10.4018/978-1-5225-0937-0.CH012
H. Alouaoui, S. Turki, S. Faiz
Our study focuses on the task of land use evolution in urban environment which is fundamental in revealing the territorial planning. It refers crucially to the use of spatial data mining tools due to their high potential in handling with spatial data characteristics. The results of our knowledge discovery process are spatial and spatiotemporal association rules referring to the land use and its evolution. Three proposals based on different knowledge extraction techniques are detailed. The first approach aims to extract spatiotemporal association rules by introducing time into the attributes. The second approach forecasts the extracted rules at different dates. The third approach is devoted to the mining of spatiotemporal association rules. This proposal looks for rules that relate properties of reference objects with properties of other spatial relevant objects. The extracted patterns are relationships involving the spatial objects during time periods. To prove the applicability of each approach, experimentations are conducted on real world data. The obtained results are promising.
{"title":"Knowledge Extraction from Geographical Databases for Land Use Data Production","authors":"H. Alouaoui, S. Turki, S. Faiz","doi":"10.4018/978-1-5225-0937-0.CH012","DOIUrl":"https://doi.org/10.4018/978-1-5225-0937-0.CH012","url":null,"abstract":"Our study focuses on the task of land use evolution in urban environment which is fundamental in revealing the territorial planning. It refers crucially to the use of spatial data mining tools due to their high potential in handling with spatial data characteristics. The results of our knowledge discovery process are spatial and spatiotemporal association rules referring to the land use and its evolution. Three proposals based on different knowledge extraction techniques are detailed. The first approach aims to extract spatiotemporal association rules by introducing time into the attributes. The second approach forecasts the extracted rules at different dates. The third approach is devoted to the mining of spatiotemporal association rules. This proposal looks for rules that relate properties of reference objects with properties of other spatial relevant objects. The extracted patterns are relationships involving the spatial objects during time periods. To prove the applicability of each approach, experimentations are conducted on real world data. The obtained results are promising.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76090319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.4018/978-1-5225-7033-2.ch058
K. Rouzbehani, Ghazaleh Sajjadi, Mohamad Rahim Hatami
Breast cancer is a major health issue in all countries affecting thousands of women. Its causes are unknown and the national and international strategies to reduce its morbidity and mortality levels are based on early detection of cancer through screening and treatment according to clinical guidelines. Thus, knowledge of which women are at risk and why they are at risk is therefore essential component of disease prevention and screening. In 2015, an estimated 231,840 new cases of invasive breast cancer are expected to be diagnosed in women in the United States, along with 60,290 new cases of non-invasive (in situ) breast cancer. The purpose of this study is to provide a more detailed analysis of the breast cancer distribution in the United States by comparing the spatial distribution of breast cancer cases against physical environmental factors using Geographic Information System (GIS). Further, it gives background information to the GIS and its applications in health-related research.
{"title":"GIS, Spatial Analysis, and Modeling","authors":"K. Rouzbehani, Ghazaleh Sajjadi, Mohamad Rahim Hatami","doi":"10.4018/978-1-5225-7033-2.ch058","DOIUrl":"https://doi.org/10.4018/978-1-5225-7033-2.ch058","url":null,"abstract":"Breast cancer is a major health issue in all countries affecting thousands of women. Its causes are unknown and the national and international strategies to reduce its morbidity and mortality levels are based on early detection of cancer through screening and treatment according to clinical guidelines. Thus, knowledge of which women are at risk and why they are at risk is therefore essential component of disease prevention and screening. In 2015, an estimated 231,840 new cases of invasive breast cancer are expected to be diagnosed in women in the United States, along with 60,290 new cases of non-invasive (in situ) breast cancer. The purpose of this study is to provide a more detailed analysis of the breast cancer distribution in the United States by comparing the spatial distribution of breast cancer cases against physical environmental factors using Geographic Information System (GIS). Further, it gives background information to the GIS and its applications in health-related research.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73860486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.4018/978-1-5225-7033-2.ch063
C. Tissot, E. Neethling, Mathias Rouan, G. Barbeau, H. Quénol, Céline Le Coq
This paper focuses on simulating environmental impacts on grapevine behavioral dynamics and vineyard management strategies. The methodology presented uses technology from geomatics object oriented databases and spatio-temporal data models. Our approach has two principle objectives, first, to simulate grapevine phenology and grape ripening under spatial and temporal environmental conditions and constraints and secondly, to simulate viticultural practices and adaptation strategies under various constraints (environmental, economical, socio-technical). The approach is based on a responsive agent-based structure where environmental conditions and constraints are considered as a set of forcing data (biophysical, socio-economic and regulatory data) that influences the modelled activities. The experiment was conducted in the regulated wine producing appellation Grand Cru “Quarts de Chaume”, situated in the middle Loire Valley, France. All of the methodology, from the implementation of the knowledge database to the analysis of the first simulation, is presented in this paper.
本文的重点是模拟环境对葡萄树行为动力学的影响和葡萄园管理策略。该方法采用了面向对象的地理信息数据库和时空数据模型技术。我们的方法有两个主要目标，首先，模拟时空环境条件和约束下的葡萄物候和葡萄成熟，其次，模拟各种约束(环境、经济、社会技术)下的葡萄栽培实践和适应策略。该方法基于一种基于反应性主体的结构，将环境条件和制约因素视为一套影响模拟活动的强迫数据(生物物理、社会经济和监管数据)。实验是在位于法国卢瓦尔河谷中部的“Quarts de Chaume”特级酒庄进行的。本文介绍了从知识库的实现到第一次仿真分析的所有方法。
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Pub Date : 2019-01-01DOI: 10.4018/IJEPR.2018010104
J. Ran, Z. Nedović-Budić
The policy integration of spatial planning and flood risk management is a promising approach to mitigate flooding. Scholars indicate that the absence of appropriate information base and technological capacity is among the factors impeding this integration. This study found that what needs to be improved is the access to geographic information and geographic technologies by individual policy makers, rather than the ownership of such resources by one organisation as a whole. Based on this finding, we designed the goals and functions for a Spatially Integrated Policy Infrastructure (SIPI) which shares not only geographic information but also models and analysis tools. A prototype of SIPI was also developed as an illustration of the selected functions of this SIPI. The design of SIPI is consistent with other frontier studies and projects in the field of GIS and planning. The development process also provides experience for future studies and development of infrastructures that aim at supporting policy integration.
{"title":"Designing an Information Infrastructure for Policy Integration of Spatial Planning and Flood Risk Management","authors":"J. Ran, Z. Nedović-Budić","doi":"10.4018/IJEPR.2018010104","DOIUrl":"https://doi.org/10.4018/IJEPR.2018010104","url":null,"abstract":"The policy integration of spatial planning and flood risk management is a promising approach to mitigate flooding. Scholars indicate that the absence of appropriate information base and technological capacity is among the factors impeding this integration. This study found that what needs to be improved is the access to geographic information and geographic technologies by individual policy makers, rather than the ownership of such resources by one organisation as a whole. Based on this finding, we designed the goals and functions for a Spatially Integrated Policy Infrastructure (SIPI) which shares not only geographic information but also models and analysis tools. A prototype of SIPI was also developed as an illustration of the selected functions of this SIPI. The design of SIPI is consistent with other frontier studies and projects in the field of GIS and planning. The development process also provides experience for future studies and development of infrastructures that aim at supporting policy integration.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83564847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.4018/978-1-5225-7033-2.ch006
T. M. Ng’ang’a, P. Wachira, T. J. Wango, J. M. Ndung'u, Margaret N. Ndungo
This Chapter introduces the need for general Digital Rights Management (DRM) requirements. Further, it intertwines DRM with its spatial counterpart, Geospatial DRM (GeoDRM). However, unlike DRM, GeoDRM is far much complicated due to issues such as the development of Web Mapping technology among other issues. The Chapter discusses the ability of GeoDRM to mitigate transgression of Intellectual Property Rights (IPR). Highlighting economical and environmental wellbeing and other benefits of Spatial Data Infrastructure (SDI) geared towards global sustainable developments, the Chapter focuses on challenges of National Spatial Data Infrastructures (NSDIs) and Regional SDIs and the need to harmonize their standards for the upward mobility of global SDI (GSDI). Emphasizing the undisputed need for Local, Regional and Global Spatial Data Infrastructures (SDIs), in the presence of various Geo-communities and different GeoDRM models, the Chapter concludes that capacity building need to be urgently but carefully harnessed across all levels in order to develop cohesive GeoDRM policies.
{"title":"Geospatial Digital Rights Management","authors":"T. M. Ng’ang’a, P. Wachira, T. J. Wango, J. M. Ndung'u, Margaret N. Ndungo","doi":"10.4018/978-1-5225-7033-2.ch006","DOIUrl":"https://doi.org/10.4018/978-1-5225-7033-2.ch006","url":null,"abstract":"This Chapter introduces the need for general Digital Rights Management (DRM) requirements. Further, it intertwines DRM with its spatial counterpart, Geospatial DRM (GeoDRM). However, unlike DRM, GeoDRM is far much complicated due to issues such as the development of Web Mapping technology among other issues. The Chapter discusses the ability of GeoDRM to mitigate transgression of Intellectual Property Rights (IPR). Highlighting economical and environmental wellbeing and other benefits of Spatial Data Infrastructure (SDI) geared towards global sustainable developments, the Chapter focuses on challenges of National Spatial Data Infrastructures (NSDIs) and Regional SDIs and the need to harmonize their standards for the upward mobility of global SDI (GSDI). Emphasizing the undisputed need for Local, Regional and Global Spatial Data Infrastructures (SDIs), in the presence of various Geo-communities and different GeoDRM models, the Chapter concludes that capacity building need to be urgently but carefully harnessed across all levels in order to develop cohesive GeoDRM policies.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86503145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.4018/ijaeis.2018070103
F. Conte, A. Ahmadi
Mermaid is a new decision support tool for managing shellfish growing areas. It is written in Visual Basic for Application (VBA) language and uses Microsoft Excel for input, calculation, and output modules. The program automatically imports the regulatory agency's data and generates scattergrams that can be used as decision support tools to help decide which shellfish growing areas should be closed and which ones should be open for harvest. The Mermaid program uses the equations developed by the Pearl model that provide more sensitive and accurate measures of sanitation safety for consumption of shellfish, and are more accurate than the U.S. National Standards.
美人鱼是管理贝类养殖区的一种新的决策支持工具。它是用VBA (Visual Basic for Application)语言编写的，使用Microsoft Excel作为输入、计算和输出模块。该程序自动导入监管机构的数据并生成散点图，这些散点图可以作为决策支持工具，帮助决定哪些贝类养殖区应该关闭，哪些应该开放捕捞。“美人鱼”项目使用由“珍珠”模型开发的方程式，为食用贝类提供了更灵敏、更准确的卫生安全措施，比美国国家标准更准确。
{"title":"Mermaid","authors":"F. Conte, A. Ahmadi","doi":"10.4018/ijaeis.2018070103","DOIUrl":"https://doi.org/10.4018/ijaeis.2018070103","url":null,"abstract":"Mermaid is a new decision support tool for managing shellfish growing areas. It is written in Visual Basic for Application (VBA) language and uses Microsoft Excel for input, calculation, and output modules. The program automatically imports the regulatory agency's data and generates scattergrams that can be used as decision support tools to help decide which shellfish growing areas should be closed and which ones should be open for harvest. The Mermaid program uses the equations developed by the Pearl model that provide more sensitive and accurate measures of sanitation safety for consumption of shellfish, and are more accurate than the U.S. National Standards.","PeriodicalId":54004,"journal":{"name":"International Journal of Agricultural and Environmental Information Systems","volume":null,"pages":null},"PeriodicalIF":1.4,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88801434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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