摘要
Based on the principle of “pre-disaster prevention outweighs rescue during disasters”, this study targets areas threatened by natural disasters, and develops an automatic algorithm based on the Prim algorithm to serve as an automatic identification system. In the face of natural disasters that disable key facilities in the region and prevent settlements from contacting the outside world or outsiders from sending rescuers to the settlements, the proposed system helps to identify whether these regions will become isolated areas and conduct disaster mitigation and relief resource allocation before any natural disaster in order to reduce potential disaster losses. An automatic identification system, based on the threshold of channel blocking due to broken roads and bridges, determines through the decision tree model and relevant patterns whether such regions will become isolated areas by identifying areas based on the results of model analysis. The proposed system’s identification results are verified by actual case histories and comparisons;the results can be used to correctly identify isolated areas. Finally, Microsoft Visual Studio C # and Google Map are employed to apply the results and to produce an information mode for the determination and decision support of isolated areas affected by natural disasters.
Based on the principle of “pre-disaster prevention outweighs rescue during disasters”, this study targets areas threatened by natural disasters, and develops an automatic algorithm based on the Prim algorithm to serve as an automatic identification system. In the face of natural disasters that disable key facilities in the region and prevent settlements from contacting the outside world or outsiders from sending rescuers to the settlements, the proposed system helps to identify whether these regions will become isolated areas and conduct disaster mitigation and relief resource allocation before any natural disaster in order to reduce potential disaster losses. An automatic identification system, based on the threshold of channel blocking due to broken roads and bridges, determines through the decision tree model and relevant patterns whether such regions will become isolated areas by identifying areas based on the results of model analysis. The proposed system’s identification results are verified by actual case histories and comparisons;the results can be used to correctly identify isolated areas. Finally, Microsoft Visual Studio C # and Google Map are employed to apply the results and to produce an information mode for the determination and decision support of isolated areas affected by natural disasters.
