Geology

Geomorphology

Landslide

Computer science

Cartography

Random forest

Geography

Confusion matrix

Multilayer perceptron

Machine learning

Perceptron

Support vector machine

Benchmark (surveying)

Deep learning

Artificial intelligence

Artificial neural network

Decision tree

Convolutional neural network

Naive Bayes classifier

Scientific Reports

Landslides are considered as one of the most devastating natural hazards in Iran, causing extensive damage and loss of life. Landslide susceptibility maps for landslide prone areas can be used to plan for and mitigate the consequences of catastrophic landsliding events. Here, we developed a deep convolutional neural network (CNN-DNN) for mapping landslide susceptibility, and evaluated it on the Isfahan province, Iran, which has not previously been assessed on such a scale. The proposed model was trained and validated using training (80%) and testing (20%) datasets, each containing relevant data on historical landslides, field records and remote sensing images, and a range of geomorphological, geological, environmental and human activity factors as covariates. The CNN-DNN model prediction accuracy was tested using a wide range of statistics from the confusion matrix and error indices from the receiver operating characteristic (ROC) curve. The CNN-DNN model was evaluated comprehensively by comparing it to sever...

Deep learning-based landslide susceptibility mapping