Asim Abdullah Ainullotfi


“I give my thanks to Allah for providing me the opportunity to further my studies under INSTeG.
It has a good developing environment where the supervisors, senior officers of INSTeG
encourage every student to always improve themselves in many aspect. It has also
the environment of sharing ideas among students from different background of research so
that our thoughts and minds are always open to alternative aspects of geospatial and remote
sensing techniques. I learned a lot staying in INSTeG and I hope that this environment is maintained.”

 Name .. : ..  ‘Asim ‘Abdullah Ainullotfi
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 Research Interest .. : ..  Local Knowledge and Remote Sensing
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 Contact No (Office) .. : ..  + (60) 13 – 702 8556
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 E-mail .. : ..
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 Present Position .. : ..  Candidate of MSc Student (Full time)
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 Supervisor : ..  Prof. Madya Dr. Ab. Latif bin Ibrahim
 Education  . : ..  B. Sc. (Remote Sensing), Universiti Teknologi Malaysia
 Research Projects : ..  – ..
 Description  ……………  : .. The integration between local knowledge and remote sensing provides a more efficient approach in flood forecasting which
………….. .. could enable the authorities and local communities to make an early preparation for flood disaster. Remote sensing in flood forecasting is a method using satellite data to identify the risk areas and the range areas that might be affected by flood inundation.  This modern technique depends mostly on the ability of technology to give digital prediction of what might happen. While local knowledge from the local communities are the knowledge of observation, experience and wisdom of facing flood incidents, surviving the flood and learn from their past actions to always be prepared for flood when the common signs come in every pre-flood events. Integrating the information from the local knowledge and the remote sensing technique could provide a more efficient flood forecasting method for the people thus reducing casualties and damages. Types of local knowledge are identified based on areas affected by the flood from previous information about flood events. The remote sensing technique will classify areas that are prone and most probable to be flooded while the local knowledge will lend information of how the local folks predict that flood will occur. With the combine information from local knowledge and remote sensing, it can provide a good flood forecasting method. A few approaches of integration are expected to produce from this research. A map of correlation between local knowledge flood prediction and the affected area of flood or a map of attribute data for areas with flood prediction local knowledge. With the combination information of local knowledge and techniques of remote sensing for flood forecasting, it could help the authorities and the local communities to establish an evacuation plan for the community if flood occurs in their area. With this, it could decrease the number of casualties and damage.
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