Geospatial susceptibility mapping of earthquake-induced landslides in Nuweiba area, Gulf of Aqaba, Egypt

Earthquake induced landslides are one of the most severe geo-environmental hazards that cause enormous damage to infrastructure, property, and loss of life in Nuweiba area. This study developed a model for mapping the earthquake-induced landslide susceptibility in Nuweiba area in Egypt with considerations of geological, geomorphological, topographical, and seismological factors. An integrated approach of remote sensing and GIS technologies were applied for that target. Several data sources including Terra SAR-X and SPOT 5 satellite imagery, topographic maps, field data, and other geospatial resources were used to model landslide susceptibility. These data were used specifically to produce important thematic layers contributing to landslide occurrences in the region. A rating scheme was developed to assign ranks for the thematic layers and weights for their classes based on their contribution in landslide susceptibility. The ranks and weights were defined based on the knowledge from field survey and authors experiences related to the study area. The landslide susceptibility map delineates the hazard zones to three relative classes of susceptibility: high, moderate, and low. Therefore, the current approach provides a way to assess landslide hazards and serves for geo-hazard planning and prediction in Nuweiba area.

Developing a Spatial Tool for Assessing Coastal Community and Identifying Infrastructure at Risk

A recent trend of sea level shows constant rising. Sea level rise has caused a significant risk to seaside areas. This study examines the potential effect of climate change and rising sea levels on coastal regions and evaluates the susceptibility of coastal areas in Inverloch, Melbourne Australia. A model of Hypothetically Flooded Zones, based on LiDAR data was built, processed and manipulated in ArcGIS. Through applying this model, the effect of rising sea level on the infrastructures such as buildings, dwellings, roads, land use and the population was assessed. Elevation data sets of varying resolution and accuracy have been processed to show the improved quality of LiDAR data contributes to a more precise delineation of flood-prone coastal lands. After the susceptible areas to sea level rise were delineated, the worst-case scenario was calculated (based on the increase in sea level projected for 2100) and it would impacts about 0.86% of roads, 221 of different building infrastructures. This method can be used in other areas to protect the coasts due to rapid changes caused by climate change.

ArcGIS-based evaluation of geo-hazards at Yaozhou County,Shaanxi,China

In conventional susceptibility evaluation of geo-hazards,there are some limits,such as unreasonable division of evaluated region,difficulty in quantifying evaluation indicators,time-consuming calculation.To address these problems,we try to employ the software ArcGIS to evaluate geo-hazards susceptibility.The study area of Yaozhou County is automatically divided into 3562 units.Based on the spatial overlay analysis function of ArcGIS,quantitative evaluation of geo-hazards susceptibility is implemented in the study area,and the geo-hazards susceptibility zoning is mapped.It is observed that the evaluation results match well with field investigations.