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“Since joining INSTeG, I have discovered a lot about INSTeG and the wide range |
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| Â Name | .. | : | .. | Â Nurulhani Roslan |
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| Â Research Interest | .. | : | .. | Â Cloud classification for rainfall estimation |
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| Â Contact No (Office) | .. | : | .. | Â +6013 4920493 |
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| Â E-mail | .. | : | .. | Â nhaniroslan@gmail.com |
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| Â Present Position | .. | : | .. | Â Candidate of PhD Student (Full time) |
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| Â Supervisor | .. | : | .. | Â Dr Mohd Nadzri Bin Md Reba and Dr Muhamad Askari |
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| Â Education | : | .. | Â B. Sc. (Remote Sensing), Universiti Teknologi Malaysia | .. | ||
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| Â Research Projects | . | : | .. | .. | – | |
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|  Description | ………….. |  : | .. | Flood forecasting is one of the alternatives in structural flood control. This forecasting could be one of the most effective non- |
| ………….. | .. | structural procedures in managing floods. Many scientist are beginning to look into this approach by characterize the cloud and hence predict the rainfall amount using remote sensing data. This method is designed because it not required high cost operation. In general, cloud characterizations are carried out using passive and active remote sensing by a number of researchers. A part of these attempts was integrating radar data for rainfall estimation with meteorological satellites. The cloud pixels are extracted from the satellite imagery and classification is carried out based on their physical properties. From the classification of cloud, rainfall estimation can be carried out. This study will give good approaches to flood forecasting and hence give benefit in flood early warning system. |