scholarly journals Geographic information system based spatio-temporal dengue fever cluster analysis and mapping

2019 ◽  
Vol 22 (3) ◽  
pp. 297-304 ◽  
Author(s):  
Shuchi Mala ◽  
Mahesh Kumar Jat
SAINTEKBU ◽  
2018 ◽  
Vol 10 (1) ◽  
pp. 83-91
Author(s):  
Novi Dwesti Bahtiar ◽  
Agus Sifaunajah

One of the most common cases of disease in Indonesia is dengue hemorrhagic fever. Jombang region is one of the areas whose people are infected with dengue fever because every year there must be cases and cases that occur is also high. Various efforts have been made to prevent the spread of the disease. Among the 3M program (Drain, Closing, and Bury), fumigation (fogging) in each area that is endemic DHF. But still there are victims, even increasing from the years. From these problems is also required system capable of providing relief. With this problem then built a Web-Based Geographic Information System that can help people to know the actual spread of dengue fever. Geographic Information System is a collection of computer systems that store, process, manipulate, analyze geography data into quality information related to geographic objects. Within the Geographic Information System itself there are two important elements of Geographic Data used as a reference for attribute data, and the attribute data itself used to support spatial or geographical information. The design of the map to be displayed in this application using Google Maps API, while the methodology in the development of this system using waterfall method that includes system analysis, system design, system implementation and testing. In making this Web-based Geographic Information System uses MySQL as database to store the required data and use PHP as the programming language. The purpose of making Geographic Information System is to help Jombang District Health Office in providing information to the community about the spread of dengue fever so that it can reduce the number of patients each year. Keywords: Google Maps, GIS, Healthy, Dengue Fever.


1998 ◽  
Vol 2 (2) ◽  
pp. 19
Author(s):  
Carlos Terán ◽  
Carlos Jimenez ◽  
Carlos González ◽  
Edgar Villaneda

<p>El estudio desarrolló una metodología objetiva de zonificación agroclimática mediante el uso del sistema de información geográfica (SIG) ARC/Info<sup>®</sup>. Se consideró la variación espacio-temporal de los elementos climáticos y espaciales del suelo y la vegetación pre­valecientes en la región de La Mojana (Colombia), para lo cual se empleó la información de 30 estaciones pluviométricas, una estación pluviográfica y 13 estaciones climáticas; para el procesa miento de los datos se combinaron técnicas de agrupamiento estadístico-matemáticas (análisis de Cluster y de Componentes Principales). Toda la información se desplegó en el sistema de información geográfica ARC/Info<sup>®</sup>, con celdas de 250 x 250 m<sup>2</sup> (6.25 ha), y se interpoló mediante el algoritmo denominado "distancia inversa ponderada" propuesto por Watson y Philip en 1985. La zonificación se efectuó teniendo en cuenta los excesos de precipitación derivados del balance hídrico y que se producen durante el período de lluvias; estos excesos se presentaron en las décadas 12 a 33. Con base en dos mapas, se creó una matriz geográfica en donde cada mapa representa la variación espacial de los excesos de precipitación en una década. A esta matriz se aplicó la técnica de Análisis de Componentes Principales (ACP), escogiéndose aquellos que presentaron la mayor variabilidad. Después, se aplicó el Análisis de Cluster usando el método de isocluster, para producir la zonificación final.</p><p> </p><p><strong>Methodology for agroclimatic classification at La Mojana Region in Colombia with the Geographic Information System ARC/Info</strong></p><p>A methodology for agroclimatic classification was developed in La Mojana region of Colombia using the Geographic lnformation System ARC/lnfo. Data considering the temporal variation of dimate at different locations, as well as temporal changes in soils and cover vegetation of La Mojana were used for this purpose. Processing of data was performed using both, Cluster Analysis and the principal component analysis (PCA). The information collected was incorporated into the ARC/Info program, by means of the algorithm named "inverse system weighted interpolation". Based on two leading maps which describe 87.2% of the variation in precipitation during two decades, a geographic matrix was developed applying the PCA technique, and selecting those components which exhibited the greatest variability. The final classification for the most representative regions of La Mojana was performed using Cluster Analysis.</p><p> </p>


2019 ◽  
Vol 15 (1) ◽  
pp. 65-82
Author(s):  
Szilárd Madaras

Abstract This paper contains the analysis of employment in the settlements of Harghita County, using the GIS (Geographic Information System) analysis, Spearman’s correlation, principal component analysis, and the cluster analysis methods. Based on the database of a set of indicators which describe the demographic, employment, and enterprise dimensions, remarkable spatial differences were observed between the settlements. The principal objectives of the county development plan regarding the employment were analysed, and a discussion took place on the possibilities of employment development in Harghita County.


Author(s):  
Juan Eugenio Hernández-Ávila ◽  
Mario-Henry Rodríguez ◽  
René Santos-Luna ◽  
Veronica Sánchez-Castañeda ◽  
Susana Román-Pérez ◽  
...  

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