Disaster debris estimation using high-resolution polarimetric stereo-SAR

AbstractThis paper addresses the problem of debris estimation which is one of the most important initial challenges in the wake of a disaster like the Great East Japan Earthquake and Tsunami. Reasonable estimates of the debris have to be made available to decision makers as quickly as possible. Current approaches to obtain this information are far from being optimal as they usually rely on manual interpretation of optical imagery. We have developed a novel approach for the estimation of tsunami debris pile heights and volumes for improved emergency response. The method is based on a stereo-synthetic aperture radar (stereo-SAR) approach for very high-resolution polarimetric SAR. An advanced gradient-based optical-flow estimation technique is applied for optimal image coregistration of the low-coherence non-interferometric data resulting from the illumination from opposite directions and in different polarizations. By applying model based decomposition of the coherency matrix, only the odd bounce scattering contributions are used to optimize echo time computation. The method exclusively considers the relative height differences from the top of the piles to their base to achieve a very fine resolution in height estimation. To define the base, a reference point on non-debris-covered ground surface is located adjacent to the debris pile targets by exploiting the polarimetric scattering information. The proposed technique is validated using in situ data of real tsunami debris taken on a temporary debris management site in the tsunami affected area near Sendai city, Japan. The estimated height error is smaller than 0.6m RMSE. The good quality of derived pile heights allows for a voxel-based estimation of debris volumes with a RMSE of 1099m3. Advantages of the proposed method are fast computation time, and robust height and volume estimation of debris piles without the need for pre-event data or auxiliary information like DEM, topographic maps or GCPs

High-temperature Fluidized Receiver for Concentrated Solar Radiation by a Beam-down Reflector System

AbstractThis study proposes a novel fluidized receiver for absorbing concentrated solar light at high temperatures. Previously, a tubular receiver and a volumetric receiver were developed to make high-temperature air for a solar gas turbine system. The aim was to combine these elements with a tower reflector; however, it was challenging to install these heavy receivers on the top of the tower. Currently, a fluidized receiver prototype is tested by a 3 kWh solar simulator in preparation for a field test at the Miyazaki beam-down reflector system. The fluid dynamics of the prototype receiver is numerically investigated. The currently treated receiver is an inner-circulating fluidized bed spouted by concentric gas streams with high and low velocities in the center and outer annulus, respectively. The draft tube is submerged in the particles to organize particle circulation. Concentrated light irradiates the particles through a quartz window at the top of the receiver container. Such a fluidized bed was first adopted by Kodama et al. for thermochemical reactions; however, it is currently pursued for its potential as a high-temperature receiver aimed at concentrated solar power generation. Experiments of the prototype receiver (inner diameter = 45mm) demonstrated that the inner particles are heated to a temperature greater than 900°C and that an increase of the central gas velocity removes the excess temperature near the particle bed surface. A numerical computation suggests that the large-scale circulation of particles leads to the activation of thermal mixing. The currently proposed receiver is thus expected to attenuate re-radiation losses likely to occur in a conventional volumetric porous receiver. The scale-up of the receiver is being considered by the numerical computation for a field test in the Miyazaki 100 kWh beam-down reflector system

ES2010-90114 MOLTEN-SALT TUBULAR ABSORBER/REFORMER (MoSTAR) PROJECT: REFORMING PERFORMANCE OF REACTOR TUBES DURING INTERMITTENT HEATING

ABSTRACT Reforming performances for the double-walled reactor tubes with Na

Detecting Urban Floods with Small and Large Scale Analysis of ALOS-2/PALSAR-2 Data

When a large-scale flood disaster occurs, it is important to identify the flood areas in a short time in order to effectively support the affected areas afterwards. Synthetic Aperture Radar (SAR) is promising for flood detection. A number of change detection methods have been proposed to detect flooded areas with pre- and post-event SAR data. However, it remains difficult to detect flooded areas in built-up areas due to the complicated scattering of microwaves. To solve this issue, in this paper we propose the idea of analyzing the local changes in pre- and post-event SAR data as well as the larger-scale changes, which may improve accuracy for detecting floods in built-up areas. Therefore, we aimed at evaluating the effectiveness of multi-scale SAR analysis for flood detection in built-up areas using ALOS-2/PALSAR-2 data. First, several features were determined by calculating standard deviation images, difference images, and correlation coefficient images with several sizes of kernels. Then, segmentation on both small and large scales was applied to the correlation coefficient image and calculated explanatory variables with the features at each segment. Finally, machine learning models were tested for their flood detection performance in built-up areas by comparing a small-scale approach and multi-scale approach. Ten-fold cross-validation was used to validate the model, showing that highest accuracy was offered by the AdaBoost model, which improved the F1 Score from 0.89 in the small-scale analysis to 0.98 in the multi-scale analysis. The main contribution of this manuscript is that, from our results, it can be inferred that multi-scale analysis shows better performance in the quantitative detection of floods in built-up areas