• International Journal of Advanced Culture Technology
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• v.3 no.2
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• pp.144-148
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• 2015

The paper presents the estimation of power losses in distribution transformer of Provincial Electricity Authority (PEA) distribution system at Muang district of Suphanburi province in Thailand. Data of 416 power distribution transformers composed of transformer (kVA), load current, no load loss and full load loss which were used for calculating energy losses. It was found that the total energy loss of all transformers is approximately 1,756,380 kWh/year.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.3-6
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• 2005

In this paper, the real scenario of water situation (e.g. water management, water availability and flooding) in an irrigated rice cultivation area in Suphanburi Province, Central-West Thailand is discussed together with the NDVI time series data. The result shown is derived by our classifier named 'Peak Detector Algorithm (PDA)'. The method discriminated 5 classes in terms of irrigation activities and cropping intensities, namely, Non-irrigated, Poorly irrigated - 1 crop/year, Irrigated - 2 crops/year, Irrigated - 3 crops/year and Others (no cultivation happens in a year or other land covers). The overall accuracy of all classified results (1999-2001) is around $77\%$ against independent ground truth data (general activities or function of an area). In the classified results, spatial and temporal inconsistency appeared significantly in the Western and Southern areas of Suphanburi. The inconsistency resulted mainly by anomaly of rainfall pattern in 1999 and their temporal irrigation activity. The algorithm however, was proved that it could detect actual change of irrigation status in a year.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.952-954
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• 2003

In this paper, we present the different characteristics of NDVI fluctuation pattern between irrigated and non-irrigated area in Suphanburi province, in Central Thailand. For non-irrigated rice cultivation area, there is a strong correlation between NDVI fluctuation and peak rainfall, while there is a lower correlation with irrigated area. In this study, the 'peak detector' classifier was developed to identify the area of non-irrigated and irrigated cropping and its cropping intensity (number of crops per year). This classifier was created based on cropping characteristics such as number of crops, time or planting period of each crop and its relationship with the peak of rainfall. The classified result showed good accuracy in identification irrigated and nonirrigated rice cultivation areas.