An Application of Geographic Information System to Select Areas for Sanitary Landfill in Bang Nok- Khwaek Municipality

The study of Sanitary landfill in Bang Nok-khwaek municipality consists of two procedures. First, to survey and create the spatial database by using physical factor, environmental factor, economical factor and social factor to follow the method of Geographic information system: GIS, second, to analyze the proper spatial for allocating the sanitary landfill in Bang Nok-khwaek municipality by using Overlay techniques to calculate the weighting linear total in Arc GIS program. The study found that there are 2.49 sq.km. proper spatial for the sanitary landfill in Bang Nok-khwaek municipals city which is 66.76% of the whole area. The highest proper spatial is 0.02 sq.km. which is 0.54%, The high proper spatial is 0.3 sq.km. which is 8.04%, the moderate spatial is 1.62 sq.km. which is 43.43% and the low proper spatial is 0.55 sq.km. which is 14.75%. These results will be used as the guideline to select the sanitary landfill area in accordance with sanitation standard for Subdistrict Administrative Organization and Subbdistrict Municipality in Samut Songkhram provice.

Spatial Pattern and GIS-Based Model for Risk Assessment – A Case Study of Dusit District, Bangkok

The objectives of the research are to study patterns of fire location distribution and develop techniques of Geographic Information System application in fire risk assessment for fire planning and management. Fire risk assessment was based on two factors: the vulnerability factor such as building material types, building height, building density and capacity for mitigation factor such as accessibility by road, distance to fire station, distance to hydrants and it was obtained from four groups of stakeholders including firemen, city planners, local government officers and local residents. Factors obtained from all stakeholders were converted into Raster data of GIS and then were superimposed on the data in order to prepare fire risk map of the area showing level of fire risk ranging from high to low. The level of fire risk was obtained from weighted mean of each factor based on the stakeholders. Weighted mean for each factor was obtained by Analytical Hierarchy Analysis.