Spatial data analysis and remote sensing for observing tsunami-inundated areas

The occurrence of natural disasters is almost impossible to reduce, but its impact can be minimized by an initial assessment related to tsunami vulnerability mapping and the observation of tsunami inundation areas. The development of remote-sensing technology and its applications enable the use of satellite imagery for observing the areas affected areas by tsunami. This study aims to recognize areas potentially affected by tsunami and to develop a method for extracting the required information from medium-resolution satellite images (ALOS AVNIR-2) for tsunami-affected areas in the coastal area of Miyagi and Iwate Prefecture, Japan. The analysis focuses on land change due to tsunami events using parameters of vegetation, water, and soil calculated using the algorithms normalized difference vegetation index (NDVI), normalized difference water index (NDWI), normalized difference soil index (NDSI), and modified soil-adjusted vegetation index (MSAVI). Areas of inundation are created using spatial multi-criteria analysis with the use of several parameters. The analysis shows that tsunamis led to a decrease in both NDVI and MSAVI values and an increase in NDSI and NDWI. Index ranges were calculated for the tsunami-inundated areas using post-event images. It is considered that pixels having all of the indices in these ranges can be identified as tsunami inundation areas. Index ranges in the inundated areas are 0.00–0.075 for NDVI, 0.075–0.25 for NDWI, −0.237 to −0.137 for NDSI, and 0.012–0.037 for the MSAVI. The results of our analysis show the potential of the algorithms in delineating areas that could be affected by a tsunami disaster.