Importance Of Geographical Information Systems Research Articles

Spatial analysis of the locations of public schools in the holy city of Najaf, using geographic information systems (GIS).

The importance of Geographic Information Systems (GIS) has become necessary for scientists, researchers, and users of urban planning and spatial and geographical analysis in general, not only for preparing maps or providing information, but for distributing data on maps, matching information, analyzing, organizing, and classifying it, especially after the great technological development that it is witnessing. The world and the need of planners and geographers to keep pace with the development of other disciplines in terms of speed in analyzing huge and diverse numbers of data and statistics and finding the most appropriate solutions and making the best decisions, which made resorting to the use of geographic information systems indispensable in many applied studies that deal with various fields

GIS and Types of GIS Education Programs

Recent developments in mapping technologies that forms data for planning and decision mechanism, makes it necessary to use these technologies by forming “clever maps” through geographical information systems (GIS). Up to now, the concept of GIS couldn’t be understood both in educational institutions and at private sector. The importance of geographical information systems and its fields of use should be emphasized. GIS education in secondary education and universities must be a government policy. Different certificate programs for staff training both in private sector and governmental organizations should be encouraged to increase productivity and quick decision making. Universities in North Cyprus has realized the importance of GIS and started GIS education in different departments recently.

Ingestion risks of metals in groundwater based on TIN model and dose-response assessment — A case study in the Xiangjiang watershed, central-south China

Groundwater samples were collected in the Xiangjiang watershed in China from 2002 to 2008 to analyze concentrations of arsenic, cadmium, chromium, copper, iron, lead, mercury, manganese, and zinc. Spatial and seasonal trends of metal concentrations were then discussed. Combined with geostatistics, an ingestion risk assessment of metals in groundwater was performed using the dose-response assessment method and the triangulated irregular network (TIN) model. Arsenic concentration in groundwater had a larger variation from year to year, while the variations of other metal concentrations were minor. Meanwhile, As concentrations in groundwater over the period of 2002–2004 were significantly higher than that over the period of 2005–2007, indicating the improvement of groundwater quality within the later year. The hazard index (HI) in 2002 was also significantly higher than that in 2005, 2006, 2007 and 2008. Moreover, more than 80% of the study area recorded an HI of more than 1.0 for children, suggesting that some people will experience deleterious health effects from drinking groundwater in the Xiangjiang watershed. Arsenic and manganese were the largest contributors to human health risks (HHRs). This study highlights the value of long-term health risk evaluation and the importance of geographic information system (GIS) technologies in the assessment of watershed-scale human health risk.

Modeling spatial and temporal transmission of foot-and-mouth disease in France: identification of high-risk areas

Foot-and-mouth disease is one of the most contagious diseases of animal livestock. We used statistical tools to explore the dynamics of epidemics and to evaluate the consequences of virus reintroduction in France. We developed a stochastic farm-based model adapted to the French farm structure from previous modeling works following the 2001 epidemic in the United Kingdom. This model depends upon the distance between the 280,000 French farms and on species type (e.g. cows and sheep) and it tracks each animal's farm status at any given day. Since data were only available at the town scale, the farm location and the number of animals in each farm were simulated over the surface area of each French town, as well as the number of mixed farms. Based on 200 simulations of the model, our results allowed for the study of local disease transmission, since it begins simulations once limitation of movement is put into place. On average, the same 50 randomly chosen initially infected farms would lead to 1,110 infected farms (610; 1,590) when two control strategies (culling within 0.5 km from an infected farm and vaccination within 3 km) are put into place. Regions with high densities of cows and sheep (e.g. Pays-de-la-Loire) are high-risk zones, confirming that the epidemic process depends upon the location and the type of initially infected farms (size, species type). The results of this model highlight the importance of Geographical Information Systems (GIS) to obtain more precise data concerning herds.

The use of Geographical Information Systems for analysing and visualising biodiversity data

Technology plays a key role in innovative research and it is important that environmental scientists are aware of technologies that are having an impact on their discipline. This paper demonstrates the importance of Geographical Information Systems (GIS) for biodiversity management and research using three powerful analysis functions and a species presence/absence database. The three analysis functions are: data integration, terrain analysis and data visualisation. Data integration functions enable the environmental characteristics of a species location to be known and therefore provide information on species habitat. An important environmental determinant of species habitat is terrain and the identification of three terrain indices (micro, meso and macro) is demonstrated. GIS visualisation techniques make tabular data easier to understand, highlight general trends and can be a stimulus for research. This research highlights a need for coordination and leadership in biodiversity information management so that researchers can easily access this data.

Factors affecting the performance of family planning workers: importance of geographical information systems in empirical analysis

An intensive family planning intervention based on community health workers (CHWs) has been in place in the Matlab area of rural Bangladesh for over a decade. Despite the programme's relative success, considerable variations in the performances of CHWs remain a concern. The purpose of this paper is to explore the determinants of CHWs performances by introducing geographical factors in addition to the conventional socioeconomic and other related variables. The attribute data on the study area were obtained from a longitudinal surveillance system, and the spatial data came from a geographical information system (GIS) database. The catchment areas for all 80 CHWs were defined by using GIS technology and spatially referenced data. A cross-sectional time-series regression model was employed on the longitudinal data of 16 years for the 80 CHWs. One significant finding of the empirical analysis is that the size of catchment area influences the performance of CHWs significantly. Geographical barriers to movement in the catchment area also affect performance of the CHW. The exercise implies that the performance of the CHWs can be improved significantly by defining their catchment areas using GIS techniques. Copyright © 1999 John Wiley & Sons, Ltd.

Factors affecting the performance of family planning workers: importance of geographical information systems in empirical analysis.

Substantial variation in contraceptive prevalence rates (CPRs) and fertility rates (FRs) between community health workers (CHWs) has been documented since the inception of the Matlab family planning program in rural Bangladesh. The coefficients of variation of these indicators for Matlab CHWs were 7% and 26%, respectively, in 1995. To identify the reasons for these performance variations, geographical information system (GIS) approaches were applied to longitudinal and cross-sectional data on 80 CHWs for the period 1980-95. Each observation in the data-set included catchment area-specific characteristics, measures of CHW efficiency in service delivery, and CHW-specific characteristics for one specific year. A one-unit increase in the average age of target women in the catchment area increases the CPR by 9.2%. The CPR increases by 0.2% for each 1% increase in women's literacy and decreases by 0.1% for each 1% increase in the number of Muslim households in the catchment area. An increase of 1 sq. km in the size of the catchment area reduces the CPR by 3%. CHW performance increases with age up to 45 years and then decreases. Similarly, a 1-year increase in the average age of target women reduces the FR by 2%. A 10% increase in the size of the catchment area reduces program performance by increasing the FR by 1.4%. A single geographic barrier to movement increases the FR by 1%. This analysis indicates that CHW performance can be improved significantly by defining catchment areas through use of GIS techniques. Without knowledge of the spatial distribution of population and the physical barriers to movement, allocating a fixed number of clients per CHW may not be the most efficient approach.