# Machine Learning-Powered Rainfall-Based Landslide Predictions in Hong Kong--An Exploratory Study
## 3 The Pilot Study--ML-Powered Natural Terrain Landslide Susceptibility Analysis
### Background
\begin{table}
\begin{tabular}{l l l l l l l l l l l} \hline \hline  & & **[PERSON] \& [PERSON] (1998)**[**9**]** & **[PERSON] \& [PERSON] (2002)**[**10**]** & **[PERSON] \& [PERSON] (2016)**[**2**]** & **[PERSON] \& et al. (2021)**[**11**]** & **[PERSON] et al. (2021a)**[**13**]** & **The Current Pilot Study** \\ \hline \multirow{4}{*}{Modelling Approach} & \(\bullet\) & Conventional & \multirow{4}{*}{Machine} & \(\bullet\) & Conventional & \multirow{4}{*}{Machine} & \(\bullet\) & Machine & \multirow{4}{*}{Machine} \\  & Statistical & & learning-based & Statistical & learning-based & learning-based & & & learning-based \\  & Approach & & Regional & & Approach & & & & & \\ \cline{1-1}  & Territory-wide & \(\bullet\) & Territory-wide & \(\bullet\) & Territory-wide & \(\bullet\) & Year-based & \(\bullet\) & Regional \\  & \(\bullet\) & Year-based & \(\bullet\) & Year-based & \(\bullet\) & Year-based & \(\bullet\) & Object-based & \(\bullet\) & Year-based \\  & \(\bullet\) & Terrain uni-based & \(\bullet\) & Grid-based & \(\bullet\) & Grid-based & & Grid-based & (30 m \(\times\) 30 m object & \(\bullet\) & Grid-based \\  & (247 terrain units) & & (20 m \(\times\) 20 m) & (5 m \(\times\) 5 m) & & (5 m \(\times\) 5 m) & & formed by 2 m \(\times\) & (5 m \(\times\) 5 m) \\ \hline Resampling Ratio & Not Applicable & 1:1 & Not Applicable & 1:1 & 1:1 & 1:2 & \multicolumn{2}{c}{Not Applicable} \\ \hline \hline \multirow{4}{*}{Features} & \(\bullet\) & & & & & \(\bullet\) & Elevation & \(\bullet\) & Elevation & \\  & & & & & & & & \(\bullet\) & Slope Gradient & \\  & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\  & & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of Landsible Susceptibility Studies in Hong Kong. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**[PERSON] \& [PERSON] (1998)** [9]} & **[PERSON] \& [PERSON] (2002)** [10] & **[PERSON] \& [PERSON] (2016)** [2] & [PERSON] et al. (2021)** [11] & **[PERSON] et al. (2021a)** [13] & **The Current Pilot Study** \\ \hline  & & & & & & \(\bullet\) & Logistic Regression & \\  & & & & & & \(\bullet\) & Random Forest & \\  & & & & & & LogitBoost & \\  & & & & \(\bullet\) & Logistic Regression & \(\bullet\) & Convolutional & \\  & & & & \(\bullet\) & Random Forest & Neural Network & & \\  & & & & \(\bullet\) & Adaboost Tree & (CNN) & \(\bullet\) & Decision Tree \\ Machine Learning & & & & \(\bullet\) & Support Vector & Bidirectional long & \(\bullet\) & Random Forest \\ Algorithm & & & & & Machine & & & \\  & & & & & Multilayer & architecture of & \\  & & & & & Perceptron & Recurrent Neural & \\  & & & & & Network & & \\  & & & & & (BiLSTM-RNN) & & \\  & & & & & & CNN-LSTM & \\ \hline  & \multicolumn{2}{c}{ \begin{tabular}{c} \\ \end{tabular}  } & \multicolumn{2}{c}{ \begin{tabular}{c} By landslide \\ \(\sim\) \\ In five \\ susceptibility \\ classes \\ \end{tabular}  } & \multicolumn{2}{c}{ \begin{tabular}{c} By landslide \\ \(\sim\) \\ In four \\ susceptibility \\ classes \\ \end{tabular}  } & \multicolumn{2}{c}{ \begin{tabular}{c} By landslide \\ density (i.e., no. of \\ landside/km\({}^{2}\)), \\ \end{tabular}  } & \multicolumn{2}{c}{ \begin{tabular}{c} By predicted \\ probability of \\ landslide \\ classes \\ \end{tabular}  } & \multicolumn{2}{c}{ \begin{tabular}{c} By predicted \\ probability of \\ landslide \\ \end{tabular}  } \\  & \multicolumn{2}{c}{ \begin{tabular}{c} By predicted \\ probability of \\ landslide \\ \end{tabular}  } & \multicolumn{2}{c}{ \begin{tabular}{c} By predicted \\ probability of \\ landslide \\ \end{tabular}