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The objective of this study was to utilize the space-time permutation scan statistic and GIS for investigating and visualizing the spatial diffusion of diarrhea outbreaks in Chiang Mai province, Thailand. A space-time retrospective analysis was conducted to detect the outbreak signals of diarrhea from 1 November 2003 to 31 October 2006, in order to include all confirmed diarrhea cases of patient less than five years of age. A total of 37,536 diarrhea cases were reported in Chiang Mai from November 1, 2003 to October 31, 2006. In the study, period had more village outbreak and the diarrhea incidence was so high. The strongest signals of outbreak (13 villages) was on 17 January 2006 (cool season) and occurred to the conurbations of Mac Chaem district (Chang Khoeng and Tha Pha sub-districts), which is located about 100 km to the south-west of Chiang Mai City. This signal had 44 cases observed over 8 days when 2.98 were expected (relative risk = 14.79). The weaker signal was on 29 June 2005 (begin of rainy season) that were located in southern Chiang Mai (Chore Thong district), there had 16 cases observed over 11 days when 1.21 were expected theoretically (relative risk = 13.24). The daily spatial spread or diffusion of diarrhea outbreak from the first day to the end day of incidence (17-24 January 2006) in the study site of Mac Chaem district was follow a pattern of contagious diffusion. They spread outward from a village of origin (Ban Rai), with high incidence to nearby villages, which related to the area of high population densities, within the urban and agricultural areas along the main course of Mae Chaem River. [ABSTRACT FROM AUTHOR]

Geographic Information System (GIS) techniques are used to develop the risk zone map of Dengue Fever (DF)/Dengue Haemorrhagic Fever (DHF) in Chachoengsao province, Thailand. The risk zonation index is derived using the Analytical Hierarchy Process (AHP). The medical database considered for the study was referenced to the geographical and meteorological data layers. Based on this analysis, potential areas were categorized as very high, high, moderately high, moderately low, low, and very low risk categories. The model used in this study provided valuable information to prepare DF/DHF risk zones for decision support to mitigate the epidemic. Factor weights used in AHP were evaluated and found to be acceptable as the consistency ratio (CR) was 0.031, which was < 0.1. Spatial modelling included a huge database about physical-environment, climatic, and demographic factors. Approximately, 74.96% people lived in very high, high, and moderately high risk zones. The most at risk zone was shown to be Mueang Chachoengsao district with a population of 142,485 or 22.34% of total population. The results from AHP based DF/DHF risk zonation gave useful information on different levels of disease risk areas. The methodology is general and can he applied in other application fields, such as disease outbreak during natural disaster. [ABSTRACT FROM AUTHOR]

The Chi River always faces floods and water shortage problems in the rainy season and subsequent dry season, respectively. The Royal Thai Government emphasizes on construction of floodwater retention reservoirs to store more water along the Chi River. This water is to be used mainly for agriculture in the subsequent dry season. A methodology was developed to identify potential floodwater retention zones using the Analytical Hierarchical Process and GIS-based data. They were surface water, drainage density, landform, land use, soil drainage, salt crust, geological formation, lineament density, vegetation index, and groundwater yield. The result was the potential water retention zones map, which was categorized as excellent, good, moderate, poor and very poor classes. The map was validated with a field survey of floodwater retention site. The results agreed with the field check. The hydrodynamic model (MIKE11) was employed to simulate diversion of discharges from the Chi River into retention reservoirs. The results of simulation revealed that the proposed reservoir (Kud Dok) could retain floodwater at the maximum storage capacity of 8.13 million m³ for return periods of 3, 5, 8 and 25 years. [ABSTRACT FROM AUTHOR]

This paper presents a new approach using an Artificial Neural Network technique to improve rainfall forecast performance. A real world case study was set up in Bangkok; 4 years of hourly data from 75 rain gauge stations in the area were used to develop the ANN model. The developed ANN model is being applied for real time rainfall forecasting and flood management in Bangkok, Thailand. Aimed at providing forecasts in a near real time schedule, different network types were tested with different kinds of input information. Preliminary tests showed that a generalized feedforward ANN model using hyperbolic tangent transfer function achieved the best generalization of rainfall. Especially, the use of a combination of meteorological parameters (relative humidity, air pressure, wet bulb temperature and cloudiness), the rainfall at the point of forecasting and rainfall at the surrounding stations, as an input data, advanced ANN model to apply with continuous data containing rainy and non-rainy period, allowed model to issue forecast at any moment. Additionally, forecasts by ANN model were compared to the convenient approach namely simple persistent method. Results show that ANN forecasts have superiority over the ones obtained by the persistent model. Rainfall forecasts for Bangkok from 1 to 3 h ahead were highly satisfactory. Sensitivity analysis indicated that the most important input parameter besides rainfall itself is the wet bulb temperature in forecasting rainfall. [ABSTRACT FROM AUTHOR]

The classification of irrigated crops by remote sensing requires the use of time series data, since the timing. cropping intensity and duration of cropping is quite variable over the course of a year. Rice is the dominant irrigated crop in tropical and sub-tropical Asia, where rainfall is high, but is seasonal and often uni-modal. Existing crop classification methods for rice are not able to distinguish between rainfed and irrigated crops, leading to errors in classification and estimated irrigated area. This paper describes a technique, a 'peak detector algorithm', to successfully discriminate between rainfed and irrigated rice crops in Suphanburi province, Thailand. The methodology uses a three-year time series of Satellite pour l'Observation de Ia Terre (SPOT) VEGETATION S10 Normalized Difference Vegetation Index (NDVI) data (10 day composites) to identify cropping intensity (number, timing and peak values). Peak NDVI is then lag-correlated with long term average rainfall data. There is a high correlation at a 40-50 day lag, between a peak rainfall and a 'single' peak NDVI of rainfed rice. In irrigated areas, there are multiple peaks, and multiple correlations with low values for at least 90 days after peak rainfall. The methodology currently uses a mask to remove un-cropped and non-rice areas, which is derived from existing Geographical Information Systems (GIS). The method achieves a classification accuracy of 89% or better against independent groundtruth data. The procedure is designed as a second level of analysis to refine classifications using other techniques of mapping irrigated area at global and regional scales. [ABSTRACT FROM AUTHOR]

Land use/land cover of the Earth is changing dramatically because of human activities and natural disasters. Information about changes is useful for updating land use/land cover maps for planning and management of natural resources, Several methods for land use/land cover change detection using time series Landsat imagery data were employed and discussed. Landsat 5 TM colour composites of 1990, 1993, 1996 and 1999 were employed for locating training samples for supervised classification in the coastal areas of Ban Don Bay, Surat Thani, Thailand. This study illustrated an increasing trend of shrimp farms. forest/mangrove and urban areas with a decreasing trend of agricultural and wasteland areas. Land use changes from one category to others have been clearly represented by the NDVI composite images, which were found suitable for delineating the development of shrimp farms and land use changes in Ban Don Bay. [ABSTRACT FROM AUTHOR]

Abstract: Air pollution is a serious problem in thickly populated and industrialized areas in Thailand, especially in Bangkok. The air pollution in Bangkok is abundant, especially in areas where pollution sources and the human population are concentrated. Economic growth and industrialization are proceeding at a rapid pace, accompanied by increasing emissions of air polluting sources. Furthermore, though the variety and quantities of polluting sources have increased dramatically, the development of a suitable method for monitoring the pollution causing sources has not followed at the same pace. Environmental impacts of air pollutants have impact on public health, vegetation, material deterioration etc. To prevent or minimize the damage caused by atmospheric pollution, suitable monitoring systems are urgently needed that can rapidly and reliably detect and quantify polluting sources for monitoring by regulating authorities in order to prevent further deterioration of the current pollution levels. Consequently, it is important that the current real-time air quality monitoring system, controlled by the Pollution Control Department (PCD), should be adapted or extended to aid in alleviating this problem. Nanotechnology has been applied to several industrial and domestic fields, for example, applications for gas monitoring systems, gas leak detectors in factories, fire and toxic gas detectors, ventilation control, breath alcohol detectors, and the like. Here we report an application example of studying air quality monitoring based on nanotechnology ‘solid state gas sensors’. So as to carry out air pollution monitoring over an extensive area, a combination of ground measurements through inexpensive sensors and wireless GIS will be used for this purpose. This portable device, comprising solid state gas sensors integrated to a Personal Digital Assistant (PDA) linked through Bluetooth communication tools and Global Positioning System (GPS), will allow rapid dissemination of information on pollution levels at multiple sites simultaneously. The AQ report generated can be then published using Internet GIS to provide a real-time information service for the PCD, for increased public awareness and enhanced public participation. The local deterministic and geostatistical interpolation methods have been used for spatial prediction, and to find out the most suitable method for studying air pollution, based on observations at each monitoring site. [Copyright &y& Elsevier]

The widely available laboratory spectrometers detect targets at spectral regions restricted to visible and near-infrared (VNIR). The spectral response of soils in this region is predominantly featureless and obstructs the exploitation of absorption features as diagnostic criterion. In this study, polynomial based modelling was developed as an alternative method of estimating soil organic matter (OM) from VNIR spectral region. Forty-one core samples, collected from Lop Buri, Thailand, were subjected to chemical and radiometric analysis. Computations were made across four categories of synthesized bandwidths. The selection procedure identified bands at 960, 1100 and 520 nm as OM sensitive. The widening interval of bandwidth has corresponded with diminishing predictive power, termed 'bandwidth decay effect'. The use of polynomial models and their validations showed a higher performance than the analysis made with multiple regressions analysis. The polynomial based approach offers a fresh opportunity for modelling other non-photoactive soil nutrient parameters. Furthermore, it may form the basis for integration of spectrometers and satellite sensors, aimed at mapping of non-vegetated soils. [ABSTRACT FROM AUTHOR]

Student attendance during classroom hours is important, because it impacts the academic performance of students. Consequently, several universities impose a minimum attendance percentage criterion for students to be allowed to attend examinations; therefore, recording student attendance is a vital task. Conventional methods for recording student attendance in the classroom, such as roll-call and sign-in, are an inefficient use of instruction time and only increase teachers' workloads. In this study, we propose a Bluetooth Low Energy-based student positioning framework for automatically recording student attendance in classrooms. The proposed architecture consists of two components, an indoor positioning framework within the classroom and student attendance registration. Experimental studies using our method show that the Received Signal Strength Indicator fingerprinting technique that is used in indoor scenarios can achieve satisfactory positioning accuracy, even in a classroom environment with typically high signal interference. We intentionally focused on designing a basic system with simple indoor devices based on ubiquitous Bluetooth technology and integrating an attendance system with computational techniques in order to minimize operational costs and complications. The proposed system is tested and demonstrated to be usable in a real classroom environment at Rangsit University, Thailand. [ABSTRACT FROM AUTHOR]

A Geographic Information System based Decision Support System (GIS based DSS) was developed for evaluating the optimal erosion management (which includes soil and water conservation: SWC and crop management system: CMS) alternatives watershed based upon the multi-objectives such as greatest physical effectiveness, cost-benefit return and social benefit acceptance. The system has been developed by integrating the decision element models: erosion model (Universal Soil Loss Equation: USLE, Modified USLE: MUSLE, Potential Nutrient Loss Model), economic model (Cost-Benefit Analysis: CBA), and social benefit model (Net Benefit Index: NBI), with a SWC knowledge based system (SWC-KBS) and multi-objectives optimization approach, into one system, using Arc-View GIS and Visual Basic programming. The application was tested in the Huai Talupkup small watershed, Thailand, an area of 1,550 ha. The selected optimal erosion management for 10 land class units (LCUs), which were based upon the similarity of land management regime which include a variety of terrace practices and suitable crop management systems. The selected optimal erosion management from the system, using a discount rate of 8 % and a project lifetime of 10 years, was found to have a net present value (NPV) of about 9.52 million Thai baht, erosion (soil loss) could be reduced about 78 % while the social net benefit index increased by 47 %from current conditions. The system proposed in this research enables quick review of results for different erosion management alternatives using preference criteria settings, which might not be possible with a dispersed analytical systems computation. It is suggested that this system can be applied to other watersheds for evaluating and enhancing the accuracy in effective decision-making in the optimal erosion management at the small watershed level. [ABSTRACT FROM AUTHOR]