Landslide Susceptibility Mapping in Brazil: A Review

Abstract

Landslide susceptibility studies are a common type of landslide assessment. Landslides are one of the most frequent hazards in Brazil, resulting in significant economic and social losses (e.g., deaths, injuries, and property destruction). This paper presents a literature review of susceptibility mapping studies in Brazil and analyzes the methods and input data commonly used. The publications used in this analysis were extracted from the Web of Science platform. We considered the following aspects: location of study areas, year and where the study was published, methods, thematic variables, source of the landslide inventory, and validation methods. The susceptibility studies are concentrated in Brazil’s south and southeast region, with the number of publications increasing since 2015. The methods commonly used are slope stability and statistical models. Validation was performed based on receiver operating characteristic (ROC) curves and area under the curve (AUC). Even though landslide inventories constitute the most critical input data for susceptibility mapping, the criteria used for the creation of landslide inventories are not evident in most cases. The included studies apply various validation techniques, but evaluations with potential users and information on the practical applicability of the results are largely missing.

Landslide susceptibility mapping using O-CURE and PAM clustering algorithms

“…Although the results indicated the high-performance capability of the proposed model, the limitation of this study is: the study considered only 7 landslide conditioning factors, there are other several factors (Dias et al, 2021;Lima et al, 2022;Tehrani et al, 2022) that are known to have an association with landslide occurrences. Moreover, further comprehensive studies will be conducted to compare the proposed model with other commonly applied models, increase the number of conditioning factors, and apply it in other study areas with a different dataset to evaluate its performance in LSM modeling.…”

Relict landslide detection in rainforest areas using a combination of k-means clustering algorithm and Deep-Learning semantic segmentation models

“…The focus is the detection of relict landslides partially covered by vegetation using semantic segmentation on CBERS-4A WPM images. Detecting relict landslides may help update the inventory map of the region that is dated from the 1970s and did not suffer great reviews (Dias et al, 2021).…”

“…An inventory map is available for a major event that occurred in 1967, when almost 600 landslides of various sizes were identified, which caused destruction and human losses (Fúlfaro et al, 1976). Despite the high landslide occurrence rate in the region, there is a lack of landslide documentation, with few studies updating the previously inventory map and monitoring the landslides (Correa et al, 2017;Dias et al, 2021).…”

Geographical Information System (GIS)-Based Landslide Susceptibility Mapping in Malaysia: A Review of Past, Current and Future Trends

“…Therefore, most of the studies mentioned landslide inventory mapping as a first step of their research about landslides. These inventories could be generated using a variety of approaches (manual, semiautomated, and automatic) for a variety of objectives, including regional or local event recordkeeping and as the initial stage in susceptibility, vulnerability, and risk assessments (Dias et al, 2021). Moreover, the aim of the inventory and objectives of the study determine the technique, even though there are many techniques to create an inventory map.…”