Geospatial Information Authority Of Japan Research Articles

Submeter-level land cover mapping of Japan

Deep learning has shown promising performance in submeter-level mapping tasks; however, its annotation cost remains a challenge, especially when applied on a large scale. In this paper, we introduce the first submeter-level land cover mapping of Japan, employing eight classes. We present a human-in-the-loop framework that achieves national-scale mapping with a small amount of additional labeled data together with OpenEarthMap, a recently introduced benchmark dataset for global submeter-level land cover mapping. Using aerial imagery provided by the Geospatial Information Authority of Japan, we create land cover classification maps for the entire country of Japan and evaluate their accuracy. By adding a small amount of labeled data to areas where a U-Net model trained on OpenEarthMap clearly failed and retraining the model, an overall accuracy of 80% was achieved, which is a nearly 16 percentage point improvement after retraining. Our framework, with its low-cost and high-accuracy mapping results, demonstrates the potential to contribute to the automatic updating of land cover maps using submeter-level optical remote sensing data. The mapping results will be made publicly available.

Impacts of Proximity to Primary Source Areas on Concentrations of POPs at Global Sampling Stations Estimated from Land Cover Information.

Given the considerable financial and logistical resources supporting long-term monitoring for air pollutants, and the use of these data for performance evaluation of mitigation measures, it is important to account for contributions from primary versus secondary sources. We demonstrate a simple approach for using open source Global land cover raster data from the National Mapping Organization from the Geospatial Information Authority of Japan to assess local source inputs for air measurements of legacy persistent organic pollutants (POPs)-polychlorinated biphenyls (PCBs) and organochlorine pesticides-reported under the Global atmospheric passive sampling (GAPS) Network at 119 locations for the time period 2005-2014. The land cover composition within a 10 km radius around the GAPS sites was identified to create source impact indicator (SII) vectors to quantify and rank the remoteness of the sites from human infrastructure. Using principal component analysis, three SII vectors were established to rank sites by impact of (i) general infrastructure/remoteness, (ii) urban infrastructure, and (iii) agricultural infrastructure. General infrastructure describes the combined effects of settlements and agricultural infrastructure. We found significant correlations (p < 0.05) between POP concentrations in air and specific SIIs. PCB levels in air had a statistically significant correlation to the SII ranking urban impacts around the sampling sites, while Endosulfan I, Endosulfan II, and Endosulfan sulfate had a statistically significant correlation with SII ranking agricultural impacts. The complete GAPS data set from 2004-2014 (1040 samples at 119 locations) was standardized based on the SII rankings to assess the global temporal trends of legacy POPs. SIIs were incorporated in the multiple regression analysis to determine global halving times. This includes short-term monitoring data from 79 locations that were previously excluded. Furthermore, the SII approach allows the integration of global monitoring data from different studies for broader global temporal trend analysis. This ability to link the results of independent and small-scale studies can enhance temporal trend analysis in support of the larger scale initiatives, such as inter alia, the Global Monitoring Plan and Effectiveness Evaluation of the Stockholm Convention in the case of POPs. This simple approach using open source data has a broad potential for application for other classes of air pollutants.

Rapid and quantitative uncertainty estimation of coseismic slip distribution for large interplate earthquakes using real-time GNSS data and its application to tsunami inundation prediction

This study proposes a new method for the uncertainty estimation of coseismic slip distribution on the plate interface deduced from real-time global navigation satellite system (GNSS) data and explores its application for tsunami inundation prediction. Jointly developed by the Geospatial Information Authority of Japan and Tohoku University, REGARD (REal-time GEONET Analysis system for Rapid Deformation monitoring) estimates coseismic fault models (a single rectangular fault model and slip distribution model) in real time to support tsunami prediction. The estimated results are adopted as part of the Disaster Information System, which is used by the Cabinet Office of the Government of Japan to assess tsunami inundation and damage. However, the REGARD system currently struggles to estimate the quantitative uncertainty of the estimated result, although the obtained result should contain both observation and modeling errors caused by the model settings. Understanding such quantitative uncertainties based on the input data is essential for utilizing this resource for disaster response. We developed an algorithm that estimates the coseismic slip distribution and its uncertainties using Markov chain Monte Carlo methods. We focused on the Nankai Trough of southwest Japan, where megathrust earthquakes have repeatedly occurred, and used simulation data to assume a Hoei-type earthquake. We divided the 2951 rectangular subfaults on the plate interface and designed a multistage sampling flow with stepwise perturbation groups. As a result, we successfully estimated the slip distribution and its uncertainty at the 95% confidence interval of the posterior probability density function. Furthermore, we developed a new visualization procedure that shows the risk of tsunami inundation and the probability on a map. Under the algorithm, we regarded the Markov chain Monte Carlo samples as individual fault models and clustered them using the k-means approach to obtain different tsunami source scenarios. We then calculated the parallel tsunami inundations and integrated the results on the map. This map, which expresses the uncertainties of tsunami inundation caused by uncertainties in the coseismic fault estimation, offers quantitative and real time insights into possible worst-case scenarios.Graphical

Japanese stone monuments and disaster memory – perspectives for DRR

PurposeThe paper focuses on an aspect of disaster often overlooked by experts: that of disaster memory both as a prevention tool and one potentially contributing to the resilience of vulnerable communities in Japan. The objective is, more specifically, to explore one specific source of disaster memory in Japan, namely the disaster-related stone monuments scattered throughout the archipelago.Design/methodology/approachTo achieve the goals, the authors have studied several types of materials. First, the authors have used the “Natural Disaster Monument” online database compiled by the Geospatial Information Authority of Japan (GIS), data upon which the authors based the field research study, focused on water-related disaster in Otsu city (Shiga Prefecture). Simultaneously, the authors have systematically searched Japanese newspapers since the middle of the 19th century as well as the archives of Shiga prefecture in order to collect additional information on the statistical reality of these monuments, the context of their creation and in order to better estimate the severity of our case studies.FindingsFirst, the findings show that stone monuments are indeed structuring elements of disaster memory in Japan. Not only are they present throughout the archipelago, but in addition, they are still for the most part visited by local communities. Second, the findings show how this material culture of disaster, as a vector of disaster memory, could be used as a tool to better understand and bring awareness to the occurrence of specific hazards, especially to future generations.Originality/valueThe authors promote an interdisciplinary approach by associating anthropology and history. The study offers a new and original character about an object of study relating to both the cultural and historical fields but still often neglected as a tool and object of research in DDR. The authors provide a method and suggest ways to integrate these stone monuments into DDR policies. Finally, the authors propose to better integrate these monuments into the overall reflection on disaster awareness and disaster mitigation.

Meteotsunamis in Japan Associated with the Tonga Eruption in January 2022

Large-amplitude meteotsunamis were observed in many areas in Japan, following the arrival of barometric Lamb waves emitted by an underwater volcanic eruption of Hunga Tonga-Hunga Ha‘apai in January 2022. We modeled the power spectra of the tidal level data obtained from 12 tide stations of the Geospatial Information Authority of Japan, based on a method of transfer function which converts the barometric pressure pulse spectra into the meteotsunami spectra. The obtained transfer functions are similar at 12 stations. The pressure pulse spectra are obtained from the ensemble average of ∼1500 Soratena weather sensors of Weathernews Inc. distributed over Japan. The observed meteotsunami spectra can be characterized by the enhanced seiche eigenmodes at each station excited by the mesoscale pressure pulse within the amplitude error of 50%, which contributes for accumulating the necessary knowledge to understand the potential dangers in various different areas over Japan.

Methodology of estimating the number of inhabitants to assess the population exposure to environmental noise in Japan

Population exposure has been used in the risk assessment process for environmental noise. The number of inhabitants is essential data for the evaluation of population exposure. However, such data is not opened to the public to prevent privacy violation. There are several existing methods for the estimation of the number of habitants, but only with limited accuracy. The purpose of this study is to propose a more accurate method for estimating the number of inhabitants using web scraping techniques and numerical maps issued by the Geospatial Information Authority of Japan. The number of inhabitants is estimated from the number of households and the census. The number of households is calculated based on the total number of housing that is extracted from using web scraping techniques. The proposed method is found to present a better accuracy of the number of inhabitants for the detached houses while the estimation for apartment houses should be still improved.

Real-time automatic uncertainty estimation of coseismic single rectangular fault model using GNSS data

Rapid estimation of the coseismic fault model for medium-to-large-sized earthquakes is key for disaster response. To estimate the coseismic fault model for large earthquakes, the Geospatial Information Authority of Japan and Tohoku University have jointly developed a real-time GEONET analysis system for rapid deformation monitoring (REGARD). REGARD can estimate the single rectangular fault model and slip distribution along the assumed plate interface. The single rectangular fault model is useful as a first-order approximation of a medium-to-large earthquake. However, in its estimation, it is difficult to obtain accurate results for model parameters due to the strong effect of initial values. To solve this problem, this study proposes a new method to estimate the coseismic fault model and model uncertainties in real time based on the Bayesian inversion approach using the Markov Chain Monte Carlo (MCMC) method. The MCMC approach is computationally expensive and hyperparameters should be defined in advance via trial and error. The sampling efficiency was improved using a parallel tempering method, and an automatic definition method for hyperparameters was developed for real-time use. The calculation time was within 30 s for 1 × 106 samples using a typical single LINUX server, which can implement real-time analysis, similar to REGARD. The reliability of the developed method was evaluated using data from recent earthquakes (2016 Kumamoto and 2019 Yamagata-Oki earthquakes). Simulations of the earthquakes in the Sea of Japan were also conducted exhaustively. The results showed an advantage over the maximum likelihood approach with a priori information, which has initial value dependence in nonlinear problems. In terms of application to data with a small signal-to-noise ratio, the results suggest the possibility of using several conjugate fault models. There is a tradeoff between the fault area and slip amount, especially for offshore earthquakes, which means that quantification of the uncertainty enables us to evaluate the reliability of the fault model estimation results in real time.

Responses of GSI to the Kanto-Tohoku Heavy Rainfall Disaster in September 2015－Aerial Photographs and Presumed Inundation-Area Maps of Joso district－

In case of a large scale natural disaster, Geospatial Information Authority of Japan (GSI) provides necessary geospatial information to contribute to lifesaving rescue activities and disaster recovery measures operated by relevant disaster management organizations (DMOs). When the Kanto-Tohoku Heavy Rainfall Disaster in September 2015 occurred, GSI took aerial photographs and unmanned aerial vehicle movies, and produced presumed inundation-area maps of Joso district to supply DMOs with such geospatial information.

平成30年７月豪雨における浸水推定図の作成 －SNSとDEMを活用した災害時の浸水範囲と浸水深の推定－

A heavy rain accompanied by a front hit western Japan in July 2018, flooded the Takahashi River system and the Hijikawa River, and brought an inundation disaster nearby. Geospatial Information Authority of Japan (GSI) created and released provisional inundation depth maps by deciphering and analyzing the inundation area and depth using social media, aerial photographs, and DEM.

Laser measurement and calculation of elevation changes in the debris-flow source area in Atami City before and after the disaster

A debris flow occurred due to heavy rain in Izusan, Atami City, Shizuoka Prefecture on July 3, 2021. In order to understand the situation of the debris flow, Geospatial Information Authority of Japan (GSI) measured the elevation using a laser scanner mounted on an unmanned aerial vehicle (UAV) three days after the disaster. In this area, airborne laser measurements were conducted as public survey in 2009 and 2019. These past data enabled GSI to calculate the elevation changes by comparing the results of laser measurements between three periods, including before and after the disaster. As a result, detailed and quantitative information including volume of residual soil is obtained. The results were released through GSI website on the same day as the UAV measurement. In this paper, its calculation process and results are reported.

Application of the WRF model to the coastal area at Ise Bay, Japan: evaluation of model output sensitivity to input data

ABSTRACT WRF simulations were conducted for Ise Bay, Japan for January and July 2016 to evaluate sensitivity of model input and output above sea surface to the replacement of three default input datasets with region-specific input datasets. For atmospheric input data, a final analysis created by the National Centers for Environmental Prediction (NCEP-FNL) was replaced with a mesoscale analysis created by the Japan Meteorological Agency (JMA). Topography and land use dataset released by the US Geological Survey were replaced with dataset released by the GeoSpatial Information authority of Japan. For sea surface temperature (SST) data, NCEP-FNL was replaced with an analysis created by JMA. Of the three region-specific datasets, replacement of atmospheric data results in the largest improvements in the accuracy of simulated wind speeds in January and July and of temperature in July 2016. Improvements in model output accuracy over sea surface can be seen near the coastline by replacing topography and land use data. Replacement of SST data results in the largest improvements in simulated temperature accuracy in January 2016. Replacing all three default input datasets results in the largest improvement, and expands on results from previous studies that focused on the effects of replacing only one input data.

Flood Inundation Mapping of the Hitachi Region in the Kuji River Basin, Japan, During the October 11–13, 2019 Extreme Rain Event

The frequency of severe flood events has been increasing recently in Japan. One of the latest events occurred in October 2019 and caused extensive damage in several river basins, especially in the central and northern regions of the country. In this study, we selected the Hitachi region (Hitachi-Omiya and Hitachi-Ota) within the Kuji River Basin which underwent considerable flooding due to the failure of embankments at two locations in the region. Maximum-possible flood inundation maps were generated using survey-based data and hydrological modeling for the Hitachi region. These maps incorporated the flood scenarios (embankment failures). All the generated products were compared with the reference flood mapping, i.e., Sentinel-1 data and Geospatial Information Authority of Japan (GSI) data for that region. It was observed that generated flood inundation mapping product based on the survey-data yielded results similar to those obtained with GSI data for the Hitachi region. Although each flood mapping product has advantages and disadvantages, they can be a good reference for the proper management and mitigation of flood disaster in the future. The rapid development of flood inundation mapping products that consider varying flood scenarios is an important part of flood mitigation strategies.

Refinement of a gravimetric geoid model for Japan using GOCE and an updated regional gravity field model

We developed a refined gravimetric geoid model for Japan on a 1 × 1.5 arc-minute (2 km) grid from a GOCE-based satellite-only global geopotential model and a regional gravity field model updated in this study. First, we have constructed a regional gravity field model for Japan using updated gravity datasets together with a residual terrain model: 323,431 land gravity data, 77,389 shipborne marine gravity data, and Sandwell’s v28.1 altimetry-derived global marine gravity model. Then, the geoid was determined with the gravity field model. The methodology for gravimetric geoid determination was based on the remove–compute–restore technique with Helmert’s second method of condensation of topography (Stokes–Helmert scheme). Here, the hybrid Meissl–Molodensky modified spheroidal Stokes kernel was employed to minimize the truncation error under an appropriate combination of different kinds of gravity data. In addition, a high-resolution GSI-DEM on a 0.4 × 0.4 arc-second (10 m) grid, together with the SRTM-DEM on a 7.5 × 11.25 arc-second (250 m) grid, was utilized for precisely applying terrain correction to the regional gravity field model. Consequently, we created a gravimetric geoid model for Japan, consistent with 971 GNSS/leveling geoid heights distributed over the four main islands of Japan with a standard deviation of 5.7 cm, showing a considerable improvement by 2.3 cm over the previous model (JGEOID2008). However, there remain some areas with large discrepancies between the computed and GNSS/leveling geoid heights in northern Japan (Hokkaido), mountainous areas in central Japan, and some coastal regions. Since terrestrial gravity data are especially sparse in these areas, we speculated that the largeness of the geoid discrepancies there could be partly attributed to the insufficient coverage and accuracy of gravity data. The Geospatial Information Authority of Japan has started airborne gravity surveys to be covered over the Japanese Islands, and in future, we plan to develop a geoid model for Japan further accurately by incorporating airborne gravity data to come.

Disaster Response Activities of Geospatial Information Authority of Japan to the Heavy Rain Event in August 2019

A heavy rain accompanied by a front hit Saga prefecture in Kyushu, Japan in August 2019, flooded the Rokkaku river and others, and brought an inundation disaster nearby. Geospatial Information Authority of Japan (GSI), which is one of the designated government oraganizations enacted by the Disaster Countermeasures Basic Act, took aerial photographs and produced inundation-depth estimation maps to support activities of relevant disaster management organizations. These products were also published on GSI's website for general use. This article shows major GSI's activities, especially for providing the geospatial products that are helpful for flood disaster management. In addition, outreach activities to government and public organizations that conduct disaster response activities are also reported.

Disaster Response Activities of Geospatial Information Authority of Japan to Typhoon Hagibis in 2019

Disaster Response Activities of Geospatial Information Authority of Japan to Typhoon Hagibis in 2019

Web-Based Sea Level Change Simulation System Using PNG Elevation Tiles and Smart Tile Architecture

We have developed a web-based processing system that can simulate positive and negative sea level changes globally by selecting the best Digital Elevation Model (DEM) for a target region from multiple DEMs. A PNG elevation tile format is used as the DEM format, which reduces the DEM data size. The PNG tile format implements client-based processing, and the DEM data are provided from different websites. In addition, the smart tile architecture is adopted, which enables on-demand simulation by adding a tile conversion process (i.e., a DEM selection process) during image drawing by using JavaScript. To demonstrate the system, we have employed three DEMs, i.e., the Geospatial Information Authority of Japan (GSI) map (~10-m resolution), the ASTER Global Digital Elevation Models (ASTER GDEM version 3) as global land area (~30-m resolution), and the General Bathymetric Chart of the Oceans as bathymetric data (~1000-m resolution). The ASTER Global Water Bodies Database is also used in the data selection process. The GSI provides their DEM in a PNG elevation tile format, and the other data are provided by the Geological Survey of Japan in PNG elevation tile format. We assume the current DEM sea level as 0 m, and the sea level can be changed to an arbitrary integer value (−10,000 to 10,000 m). Combining ASTER GDEM for land and GEBCO for sea makes it possible to target DEM of the whole earth. Moreover, it was shown that if a higher resolution DEM is available, it is possible to combine the higher resolution DEM in that area. The combining the PNG elevation tile format with the smart tile architecture demonstrates the possibilities of a client-based web processing service like that of the server-based OGC Web Processing Service.

Distribution and Characteristics of Slope Movements in the Southern Part of Hiroshima Prefecture Caused by the Heavy Rain in Western Japan in July 2018

Record-breaking heavy rainfall in July 2018 caused an extremely large number of slope movements over a broad area of western Japan. We mapped the distribution of slope movements in the southern part of Hiroshima Prefecture through an interpretation of aerial photographs that were acquired after the rainfall by the Geospatial Information Authority of Japan, and counted a total of 8,497 slope-movement starting points. The widespread distribution of slope movements – from Etajima City of Hiroshima Prefecture to Kasaoka City of Okayama Prefecture – suggests that the heavy rain affected a very large area. The starting points of debris flow during this disaster were commonly close to the crest of mountain ranges. We compared the distribution of slope movements to the 24-hr rainfall accumulation during the heaviest rainfall event to clarify the factors that caused regional difference in slope-movement distribution. We found the area of highest density of the slope movements was consistent with the area receiving a cumulative rainfall of &gt;250 mm. This observation indicated that the position of slope-movement starting points was not related to differences in geology.

A Report on “Old Map Collection” by Geospatial Information Authority of Japan

Abstract. Historical maps are valuable resources to understand the topography, land use, and land cover of the country in the past. Recently they have been used as basic data in fields such as education, disaster prevention or research on local history. Geospatial Information Authority of Japan (GSI) has been working on collecting and archiving historical maps which were drawn before than Meiji period. However, public use of these maps is often confined because they are almost non-existent or have the possibility of being damaged. Therefore, in order for everyone to use these maps, GSI created a website “Old Map Collection” (Figure 1), which provides various digitized historical maps. In this presentation, we introduce the summary of “Old Map Collection” and some of its new contents.In 2005 GSI created a website “Old Map Collection” to provide historical maps for public use as historical, cultural, and academic documents. Users can browse about 1,500 map sheets including various related information, e.g., name, size, date-of-creation, author, and pictorial image. Also all maps are categorized into 15 fields such as maps made in Meiji period, maps of Japan, world maps, and Ino’s maps, based on their age of publication, range of area, and purpose of use, which enables users to find maps more easily.2018 marked the 150th anniversary since the beginning of Meiji period, when the modernization of Japan started. In order to bequeath the history of Meiji to future generations, Japanese government has promoted the policy named “MEIJI 150th”. One of the projects GSI conducted related to “MEIJI 150th” was the additional release of 1:20,000 scale original rapid survey map, e.g., Figure 2, on “Old Map Collection”. This map was created from 1880 to 1886 (the 13th -19th years of Meiji period) in advance of the national survey by General Staff Office of the Imperial Japanese Army, and is now owned only by GSI. It contains 921 colored map sheets which cover the area of capital Tokyo and its surrounding regions.

Geospatial Information Authority of Japan’s (GSI’s) support for geography education

Abstract. In Japan, the National Courses of Study was revised in 2016 and 2017. One of the most extensive discussions is on enhancing geography education in primary and secondary levels in this era of globalization. Further, it is argued how the Geospatial Information Authority of Japan (GSI), the national organization within the Japanese government for the production and coordination of basic geospatial information, should play a more important role in this process to support the promotion of geography education. In addition to these actions, GSI had started discussion with specialists for geography education and high-school teachers about supports for geography education expected to GSI. This presentation discusses the role of GSI in the promotion of geography education.

1/30 scale of Japan topography model realized with Minecraft

Abstract. The purpose of this research is to provide an environment for children to learn about Japan's topography. In recent years, games have been attracting attention as tools for active learning, which has been a departure from conventional knowledge acquisition bias education. I focused on 3D sandbox game called Minecraft (Mojang/Microsoft) which is popular among children. In Minecraft, players can freely move in the 3D world and create buildings. Minecraft can reproduce 3D topography and simulate it, so it has high potential as a geography and geology education.I have created 1/30 scale of Japanese terrain model for Minecraft Java 1.12.2. The created data can be downloaded and used freely. The usage method is simple, it only copies it to the prescribed directory of the environment where Minecraft was installed.For the elevation data necessary for model creation, I use the elevation tile released by the Geospatial Information Authority of Japan as open Data. This elevation tile covers the whole of Japan with 10m mesh accuracy. This elevation tile is an application of the tiled map image often used in Web maps to data representation. I call such a data set “Data Tile Map”. Each pixel holds the elevation as a signed integer in cm units, using 24-bit RGB values.The creation program is written in JavaScript and can be executed in an environment with a web browser. With the creation program you can change the output resolution (zoom level) and vertical direction exaggeration ratio. In the future, I plan to add functions to correspond to the terrain of the world and create data by specifying the area.