Automated Processing for Flood Area Detection Using ALOS-2 and Hydrodynamic Simulation Data

Rapid and frequent mapping of flood areas are essential for monitoring and mitigating flood disasters. The Advanced Land Observing Satellite-2 (ALOS-2) carries an L-band synthetic aperture radar (SAR) capable of rapid and frequent disaster observations. In this study, we developed a fully automatic, fast computation, and robust method for detecting flood areas using ALOS-2 and hydrodynamic flood simulation data. This study is the first attempt to combine flood simulation data from the Today’s Earth system (TE) with SAR-based disaster mapping. We used Bayesian inference to combine the amplitude/coherence data by ALOS-2 and the flood fraction data by TE. Our experimental results used 12 flood observation sets of data from Japan and had high accuracy and robustness for use under various ALOS-2 observation conditions. Flood simulation contributed to improving the accuracy of flood detection and reducing computation time. Based on these findings, we also assessed the operability of our method and found that the combination of ALOS-2 and TE data with our analysis method was capable of daily flood monitoring.

Analysis Disaster Vulnerability Capacity in Mempawah Hilir Subdistricts

Data in the West Kalimantan Figures (BPS) in 2010, there were 34 sub-districts in the West Kalimantan coastal area with a total area of 20,066 Km2 and a population of 1,100,000 people or 25% of the projected total of 4.4 million residents of West Kalimantan. Means that people who live in coastal areas including small islands have become the majority concentration on the distribution of the population of West Kalimantan, while having a close relationship with access to potential marine and coastal resources and environmental use. In the Strategic Plan of the West Kalimantan Regional Disaster Management Agency 2013-3018 (2) states that the inhibiting and driving factors are in disaster management in West Kalimantan due to the absence of hazard-prone mapping and safe disaster mapping, especially in coastal areas. The purpose of this research is to find out and analyze the level of disaster vulnerability in the District of Mempawah Hilir. The data collection method used is to determine aspects and indicators of capacity assessment of disasters in the District of Mempawah Hilir. From the results of the assessment of factors A to factor E, it can be concluded that the level of capacity of each village in Mempawah District is still very low. This low capacity value is dominated in villages in Sungai Kunyit and Siantan Districts. Villages that have moderate capacity value are Kuala Secapah Village, Pasir Village, Sengkubang Village and Jungkat Village. Overall villages in Mempawah sub-district are still low on the early warning factor and disaster risk assessment and preparedness development factors on all lines.

Pre-disaster mapping with drones: an urban case study in Victoria, British Columbia, Canada

We report a case study using drone-based imagery to develop a pre-disaster 3-D map of downtown Victoria, British Columbia, Canada. This represents the first drone mapping mission over an urban area approved by Canada's aviation authority. The goal was to assess the quality of the pre-disaster 3-D data in the context of geospatial accuracy and building representation. The images were acquired with a senseFly eBee Plus fixed-wing drone with real-time kinematic/post-processed kinematic functionality. Results indicate that the spatial accuracies achieved with this drone would allow for sub-meter building collapse detection, but the non-gimbaled camera was insufficient for capturing building facades.

Improving Community Capacity in Rapid Disaster Mapping: An Evaluation of Summer School

Experiences with natural disasters have intensified recent efforts to enhance cooperation mechanisms among official disaster management institutions to community participation. These experiences reveal a need to enhance rapid mapping technical assistance to be developed and shared among young scientists through a summer school. However, the question arose of how effective this summer school to be used as a tool to increase scientists’ understanding and capacity. This study sought to evaluate the extent to which human resource capacity building can be effectively implemented. The methods used for this evaluation is through observations, questionnaires and a weighted scoring based on knowledge, skills and attitudes’ criteria. The results indicate a significant improvement in knowledge (94.56%), skills (82%) and attitudes (85.20%) among the participants. Even though there are still gaps in participants’ skills, the summer school was found to be an effective way to train the young scientists for rapid mapping.