Real-time Landslide Early Warning System Based on Fuzzy Ad Hoc Data Covering Methods Using Empirically-based Model
In this research, we take a different approach to build a new landslide warning system by using the fuzzy rule-based system (FRBS) model rather than either satellite remote sensing or dynamical approach that was employed in most landslides warning studies. This fuzzy model was developed based on ad hoc data covering methods and empirically-based model. In this case, fuzzy rules were set by learning from numerical data. We found the model satisfactorily simulated the occurrence of landslide with values of area under the Fuzzy Receiver Operating Characteristic (ROC) curve at 0.825 (range: 0 to 1, perfect score: 1) resulting in a good agreement with the occurrence of landslide data obtained from the Indonesian National Agency for Disaster Management (BNPB). For the domain research, this warning system is developed at Banjarnegara, Central Java, Indonesia, which chosen as an example of a populated highland that is highly vulnerable to landslides. In this system, Soil Moisture Index (SMI) was calculated based on a regolith-moisture model to represent the soil moisture conditions. Besides, the empirical intensity-duration (ID) threshold and cumulative rainfall threshold (CT) have been calculated as an empirically-based model. They were derived on a numerical basis, starting from a database of 141 shallow landslides from 2011 to 2017. Fuzzy ROC analysis was employed to validate an FRBS based on continuous time series of newest rainfall and evapotranspiration data and landslide database from 2018 to 2019. Ultimately, the Fuzzy model could simulate the gold standard of the landslide alert system with small error measures.
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