In 2018, A large-scale earthquake occurred directly underneath Iburi area in Hokkaido. Furthermore, several volcanos erupted in Japan with volcanic terrain changed. In this report, we introduce disaster response in 2018 by Geospatial Information Authority of Japan (GSI) using satellite SAR data for detecting crustal movements and airborne SAR data for observing volcanic terrain changes. GSI released these results of analysis via website. Also GSI provided them to various institutes and local governments for their disaster response and recovery operations.

The heavy rain disaster caused by the Baiu front and the Typhoon No. 7 that stagnated near Japan in July, 2018 occurred widely around West Japan. The Geospatial Information Authority of Japan collected and provided information on disasters as a designated administrative agency based on the Basic Law on Disaster Countermeasures. In this report, we will introduce examples of taking aerial photographs and using them.

JAXA has been engaging in disaster management support using the Advanced Land Observing Satellite (ALOS) series since 2006. This paper shows the outline and examples of the results of disaster response support within Japan in 2018 using ALOS-2. It can be said that volcano observations by ALOS-2, accounting for half of responses, are in actual operation (sustained use in a decision-making context).

In the case of the Heavy Rain Event of July 2018, Aero Asahi Corporation took aerial photographs based on the disaster agreement with the Geographical Survey Institute. Some of the aerial photographs taken were influenced by the clouds, but it was able to read valuable information by referring to the GIS data published on the web.

Changes in terrain are one of the indicators of the scale of volcanic eruption. But, flying over a crater immediately after the eruption is dangerous. In such a case, surveying by SfM/MVS method using multiple oblique images is effective, and 3D models, ortho images, DSM from photos of safe places could be created. Here, we introduced examples of the Kusatsushirane eruption in January 2018 and the Shinmoedake eruption in March, 2018. Both of them were able to be grasped the scale of eruption safely and timely.

Today's high-definition topographic data analysis and SfM 3D-Modeling technology is effective for measurement of ground displacement and estimation of landslide area. In this study, Digital Geomorphic Image Matching analysis using differential LiDAR DEMs was applied to measure wide-area ground displacements of landslide. As a result, over 6 m displacement for 2 months was quantitatively and spatially measured. In additional case study, SfM 3D-Modeling was conducted just after the large landslide occurred in mountainous region. High-definition topographic data quickly made from aerial oblique photographs was effective for emergency planning for countermeasure work.

The 2018 Hokkaido Eastern Iburi Earthquake brought about great numbers of landslides in the broad area of the eastern Iburi region, Hokkaido, especially Atsuma town. As emergency disaster response to the earthquake, PASCO Corporation carried out 1) taking oblique aerial photographs, 2) automatic extraction of landslides using SPOT6 images, 3) detection of surface deformation with DInSAR analysis and 4) field surveys based on DInSAR analysis. We detected landslides from the broad area quickly by using optical satellite images and evaluated topographic changes before and after the earthquake.

A survey was quickly carried out under the harsh condition of intense heat in the area damaged by the record heavy rain that the Japan Meteorological Agency named “Heavy Rain in July 2018”. Our company is a local company in Hiroshima Prefecture that suffered damages, and have been engaged in the restoration and reconstruction immediately after the disaster. This manuscript introduces our company's efforts before the disaster and after the disaster.

We propose a fire radiative power (FRP) estimation algorithm which is adaptable to the Second-generation GLobal Imager (SGLI) sensor on board the GCOM-C satellite. This algorithm is based on the Stefan-Boltzmann's law to calculate FRP. In the Stefan-Boltzmann's law based FRP calculation, sub-pixel fire information is required ; fire temperature and its fractional area coverage in the observed fire pixel. In this study, a bi-spectral method is employed to retrieve sub-pixel fire information. Furthermore, “a stepwise estimation approach” is applied to estimate the sub-pixel fire information for a good FRP estimation. This approach estimates the fire area coverage at first using a regression formula which is expressed by the logistic function, and then estimates the fire temperature. The FRP calculated by our algorithm is evaluated by comparing with the MODIS fire product FRP. The correlation between our algorithm derived FRP and the MODIS FRP shows relatively high (0.70) with low bias error (0.42 [MW]).

A 3D measurement, such as a terrestrial laser scanning, is applied for an advanced infrastructure management and Building Information Modeling (BIM). Although a terrestrial laser scanning can acquire massive point cloud data for the BIM, 3D measurement using high precision LiDAR is affected by slab-vending with active loading, such as vehicle movements on a bridge. Thus, stripy noises occur in acquired point clouds. Therefore, we proposed three methodologies, such as multiple data subtraction, plane estimation with Least Median of Squares (LMeds), and noise pattern estimation, to remove the stripy noises for precise 3D bridge modeling. Our three methodologies were verified using terrestrial LiDAR data taken under a road bridge. Through our experiments, we confirmed that our algorithms can automatically cancel the vending affect of bridge in laser scanning works.