Flooding has been increasing since 2004 in Japan due to localized heavy rainfall and geographical conditions. Determining areas vulnerable to flooding as one element of flood hazard maps related to disaster management for urban development is necessary. This research integrated Remote Sensing data, the Geography Information System (GIS) method and Analytical Hierarchy Process (AHP) calculation to determine the physical flood-vulnerable area in Okazaki City. We developed this research by applying data from the Geospatial Information Authority of Japan (GSI) to generate the slope map and drainage density; AMEDAS (Automated Meteorological Data Acquisition System) from the Japan Meteorological Agency (JMA) to generate the rainfall data; Soil map from the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) data; and Sentinel-2 imagery to generate the land cover map. We applied the AHP calculation for weighting pairwise the parameters by comparing five iterations of the normalized matrix. We utilized the spatial analysis tool in ArcGIS to run the pairwise comparison to adjudicate the distribution of flooding according to the AHP procedure. The percentage of relative weight was slope (43%), drainage density (20%), rainfall intensity (17%), then both infiltration rate and land cover (10%). The consistency value was reasonable: consistency index (CI—0.007) and consistency ratio (CR—0.6%). We generated high accuracy for flood vulnerability prediction; 0.88 for Probability of Detection (POD), 0.28 for Probability of False Detection (POFD), 0.44 for Critical Success Index (CSI), 1.9 for Bias, and 95 of Area under Curve (AUC). The flood vulnerability was matched to the flood inundation survey of Okazaki City in August 2008 and indicated an excellent Relative Operating Characteristic (ROC).

Understanding the impact of Indian Ocean Dipole (IOD) on fishery around Indonesia is important as the fishery resources are small compared to the demand. In this study, we analyzed the effect of positive and negative phases of IOD on chlorophyll-a concentration and the catch of Sardinella lemuru in the Bali Strait. Data are based on field surveys in the Bali Strait during the positive and negative phase of IOD and Sea Surface Temperature (SST) and Sea Surface Chlorophyll (SSC) obtained from the analysis of satellite images. The results suggest that SSC concentration in the strait significantly correlates with the positive and negative phase of IOD, possibly through a change of upwelling and downwelling there. It is suggested that the change of phytoplankton biomass due to positive IOD would result in an increase of Sardinella lemuru in the Bali Strait. This research has direct implications as important information for the government in planning lemuru fisheries management in the Bali Strait based on oceanographic studies and climate phenomena.

Purpose: – The purpose of this paper is to assess the vulnerability of the Kesennuma area in Japan to a tsunami disaster and to map the area of inundation. Design/methodology/approach: – Digital elevation model (DEM) data and ALOS image were used to create maps of the parameters of this study area: elevation, slope, coastal proximity, river, and land use. An analytical hierarchy process was used to assign weights to each parameter and a spatial multi-criteria analysis was applied through cell-based modelling for vulnerability mapping. Findings: – The vulnerability map shows that 17.679 km2 of the area could be inundated by a tsunami. High vulnerability areas were mostly found in coastal areas with a sloping coast and a cape area. A low elevation and the presence of rivers or water channels are factors that increase the impact of tsunamis. Inundation areas were predicted to spread in areas identified as having either high vulnerability or slightly high vulnerability. Research limitations/implications: – Because of the limited geospatial data, the authors encourage further studies using DEM data with a high spatial resolution. Practical implications: – The results of this research can be used as basic information for disaster mitigation and urban planning in coastal areas. Originality/value: – This research creates a new approach for assessing which areas could be inundated by tsunamis, based on the vulnerability map generated through remote sensing and spatial multi-criteria analysis. Moreover, the parameters used are very close to those of actual inundation maps.

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.