Hiroyuki Miyazaki

The University of Tokyo | Todai · Center for Spatial Information Science

This study explores Human Activity Recognition (HAR) using smartphone sensors to address the challenges posed by position-dependent datasets. We propose a position-independent system that leverages data from accelerometers, gyroscopes, linear accelerometers, and gravity sensors collected from smartphones placed either on the chest or in the left/ri...

The world has incurred an immense impact from the novel coronavirus disease 2019 (COVID- 19). Various sectors such as health care system, socio-economic systems, governance system, public lifestyle, etc. has experienced a massive pressure by the COVID-19. It has been felt indispensable to device ways to monitor and interpret these kinds of crisis i...

Globally, rapid economic growth has contributed to an overall increase in the incidence of childhood obesity. Although the prevalence of obesity has been well recognized, the disparities related to a region’s socioeconomic environment in terms of the incidence of obesity are still less understood. Therefore, the purpose of this study was to examine...

As the concept of Society 5.0 evolved over the last 4–5 years, it is important to analyze the key policy perspectives of the concept and its relation to developing intelligent and resilient communities. While health care, agriculture, and education are strong pillars, disaster risk reduction and addressing key social issues are also integral parts...

Detailed demographics play an important role in the development of smart cities. However, especially in developing countries, the maintenance and management of this data is incomplete, which hinders the promotion of smart cities. The objective of this study is to develop a method to create detailed building distribution maps from satellite images,...

Plastic pollution is a critical global issue. Increases in plastic consumption have triggered increased production, which in turn has led to increased plastic disposal. In situ observation of plastic litter is tedious and cumbersome, especially in rural areas and around transboundary rivers. We therefore propose automatic mapping of plastic in rive...

Climate-related disasters severely threaten the livelihoods and food security of millions of Bangladesh is living in deltaic areas. The study looked at shifting patterns of land use, the state of food security, and adaption mechanisms in pre-and post-disaster contexts to anticipate the future situation and its influence on livelihood. The study use...

The primary aim of this textbook is to contribute towards the promotion of human security by educating nurses with a profound understanding of disaster nursing and to conduct innovative research and practices in cooperation. This textbook emphasizes on multi-professional connections; offers knowledge on how Japanese disaster nursing got evolved in...

This chapter is to understand the functionality of GIS focusing on disaster nursing operations, comprising (1) data acquisition, (2) data analysis, (3) data visualization, and (4) data management and sharing. The reader will understand the conceptual basics of GIS, which is useful for designing GIS-based information management systems and applicati...

This chapter introduces suitable applications for disaster risk reduction (DRR) using information technologies and geospatial information in primary health care. We assessed the practices in aspects of (1) problems addressed by the solution, (2) stakeholders of the problems, (3) user or beneficiary of the provided information and data, (4) outcomes...

To provide care that leaves no one behind during a disaster, it is important to address the diversity of people living in society, and inclusion are important. This chapter describes the phenomenon of disaster nursing and existing theories of community care. It proposes a meta-knowledge of disaster nursing called “care for DRR” regarding human prot...

This chapter provides basic methods of service design, which is a key technique for bringing benefits of ICT and GIS to end users. The methods comprise a series of user-oriented designs including defining and scoping problems, identifying and analyzing stakeholders, designing and defining specification requirements of information and data, and prot...

We have contributed to the mutual support of the community, not within the framework of medical care or disaster prevention to health and well-being directly contributed to SDG 3. Through the care of local nurses who can flexibly respond to any disaster, we have been visualizing the care and communication for disaster risk reduction while using new...

Prolonged health emergencies and disasters greatly affect health and well-being of individuals and communities. Past experiences on extreme emergencies and disasters have taught communities the value of preparedness. Information is key in responding to health crises especially in areas where health capacity is challenged. This chapter explains the...

Reducing the disparities in healthcare access is one of the important goals in healthcare services and is significant for national health. However, measuring the complexity of access in truly underserved areas is the critical step in designing and implementing healthcare policy to improve those services and to provide additional support. Even thoug...

While recent advancement of domain adaptation techniques is significant, most of methods only align a feature extractor and do not adapt a classifier to target domain, which would be a cause of performance degradation. We propose novel domain adaptation technique for object detection that aligns prediction output space. In addition to feature align...

Reducing congestion has been one of the critical targets of transportation policies, particularly in cities in developing countries suffering severe and chronic traffic congestions. Several traditional measures have been in place but seem not very successful. This paper applies the agent-based transportation model MATSim for a transportation analys...

Purpose The research aims to establish importance scheme of geospatial factors for land valuation activities that may serve as an eye-opener and aid the concerned government agencies in drafting land valuation policies and guidelines to achieve a sound land governance and administration. It specifically identifies and weighs geospatial valuation fa...

Estimation of economic loss due to flood often becomes necessary for flood damage assessment. Conventional practices to estimate damage by postflood survey are laborious and time-consuming. This study presents a framework of rapid estimation of flood damage using earth observation satellite data to minimize the time and efforts for damage assessmen...

Public transport service has been promoted to reduce the problems of traffic congestion and environmental impacts due to car dependency. Several public transportation modes are available in Bangkok Metropolitan Region (BMR) such as buses, heavy rails, vans, boats, taxis, and trains while in some areas have fewer modes of public transport available....

Current advances in deep learning is leading to human-level accuracy in computer vision tasks such as object classification, localization, semantic segmentation, and instance segmentation. In this paper, we describe a new deep convolutional neural network architecture called Vec2Instance for instance segmentation. Vec2Instance provides a framework...

Evacuation shelters are the most important means for safeguarding people in hazardous areas and situations, and thus minimizing losses, particularly those due to a disaster. Therefore, evacuation shelter assignment and evacuation planning are some of the critical factors for reducing vulnerability and increasing resilience in disaster risk reductio...

The authors wish to make the following corrections to this paper [...]

The name, EpiNurse, refers to local nurses who perform epidemiological surveillance and care to ensure human security in and communicate with health authorities on the health status of communities. They collect and report epidemiological information by using easy-to-use technology in communities in which access to health information of the populace...

Recently, object detectors based on deep learning have become widely used for vehicle detection and contributed to drastic improvement in performance measures. However, deep learning requires much training data, and detection performance notably degrades when the target area of vehicle detection (the target domain) is different from the training da...

The use of available place databases (like GeoNames and traditional maps) to obtain descriptive keywords of a user-defined place is not possible because such data sources mainly maintain location definitions of the well-known places only. Traditional sources may not be updated dynamically and may not ensure diverse information. Additionally, they d...

Easy, economical, and near-real-time identification of tourism areas of interest is useful for tourism planning and management. Numerous studies have been accomplished to analyze and evaluate the tourism conditions of a place using free and near-real-time data sources such as social media. This study demonstrates the potential of volunteered geogra...

Many cities across the world are exposed to more than one hazards. Focus on only the most prominent natural hazards, or the most recent event can be dangerous, as many potential threats to urban development are not assessed. Even when multiple hazards in a given area is assessed, there is a lot of confusion on how to utilize hazard information in m...

Land development in sub-urban areas is more frequent than in highly urbanized cities, causing land prices to increase abruptly and making it harder for valuers to update land values in timely manner. Apart from this, the non-availability of sufficient reliable market values forces valuers to use alternatives and subjective judgement. Land value is...

Flooding is one of the major disasters occurring in various parts of the world. Estimation of economic loss due to flood often becomes necessary for flood damage mitigation. This present practice to carry out post flood survey to estimate damage, which is a laborious and time-consuming task. This paper presents a framework of rapid estimation of fl...

Experienced opinions about products and services can guide a potential user for a better purchase decision. Fine-grained aspect level opinions embedded within reviews must be explored to discover experienced users' latent opinion about the aspects (i.e. features of products like cost, value for money, etc.) and their relative importance. In this pa...

Social media platforms contribute a huge part of the content available on the world wide web today. These platforms act as a rich source of real time data from live human sensors. These media disseminate spatiotemporal public opinion regarding a range of events, activities and human information behaviors. This paper explores the active user locatio...

[Ebook freely available at http://www.eria.org/publications/integrated-space-based-geospatial-system-strengthening-aseans-resilience-and-connectivity/] In recent decades, regional organisations have become increasingly active in connectivity disasters. This reflects a broader growing trend of intensifying regional cooperation for building resilient...

In this study, we present population distribution map and automated human settlement map for Maputo. To identify buildings from high-resolution remote sensing (HRRS) images of highly dense area, we used pixel-based classification frame with Ensemble Convolution Neural Network (ECNN) algorithm for building detection and used these identified buildin...

Taxis are considered one of the most convenient means of transportation, especially when people have to travel off-route, where public transportation is not a feasible option, and also when they need to reach a destination according to what is most convenient for them. However, many issues exist about taxi services, such as the problems of passenge...

This opinion paper highlights the state of public health assessment in evacuation centers following the 2015 Nepal earthquake. It also suggests an approach to reinforce risk assessment and surveillance of communicable diseases (CD) in remote Nepalese districts. A short surveillance research was conducted on outbreaks of infectious diseases in Nepal...

Recently, deep learning techniques have had a practical role in vehicle detection. While much effort has been spent on applying deep learning to vehicle detection, the effective use of training data has not been thoroughly studied, although it has great potential for improving training results, especially in cases where the training data are sparse...

Study/Objective This proposal is a practical, solution-oriented research which, in a way, challenges the conventional public health surveillance systems - which require real-time or near real-time, population-based, statistical alarms to alert to unusual activity - through innovative ongoing surveillance that will incorporate geospatial assessment...

Social media platforms are rich source of real time data from live human sensors. These media disseminate spatio-temporal public opinion regarding a range of events, activities and human information behaviors. This paper presents a use of social network sites (particularly twitter) as a rich source of data to be used in research activities. We deve...

Historical archives of satellite data for urgent issues of urban growth in global scale. We developed an on-demand service of human settlement mapping using Landsat archive. A machine learning algorithm, the Learning with Local and Global Consistency (LLGC), was applied for automation of the settlement detection, in which the algorithm enables to u...

Detail information of human settlements is crucial for development issues, such as public health, energy development, and disaster risk management. While the methodologies of settlement mapping in urban areas have been developed well, there are still few studies on settlement mapping in rural areas and villages, which are important for urban develo...

Methodology of automated human settlement mapping is highly needed for utilization of historical satellite data archives for urgent issues of urban growth in global scale, such as disaster risk management, public health, food security, and urban management. As development of global data with spatial resolution of 10-100 m was achieved by some initi...

Methodology of automated human settlement mapping is highly needed for utilization of historical satellite data archives for urgent issues of urban growth in global scale, such as disaster risk management, public health, food security, and urban management. As development of global data with spatial resolution of 10-100 m was achieved by some initi...

The International Society for Photogrammetry and Remote Sensing (ISPRS) Student Consortium (SC) is a network for young professionals studying or working within the fields of photogrammetry, remote sensing, Geographical Information Systems (GIS), and other related geo-spatial sciences. The main goal of the network is to provide means for information...

The International Society for Photogrammetry and Remote Sensing (ISPRS) Student Consortium (SC) is a network for young professionals studying or working within the fields of photogrammetry, remote sensing, Geographical Information Systems (GIS), and other related geo-spatial sciences. The main goal of the network is to provide means for information...

In this study, a method based on supervised machine learning is proposed to identify village buildings from open high-resolution remote sensing images. We select Google Earth (GE) RGB images to perform the classification in order to examine its suitability for village mapping, and investigate the feasibility of using machine learning methods to pro...

Due to the fact that geospatial information technology is considered necessary for disaster risk management (DRM), the need for more effective collaborations between providers and end users in data delivery is increasing. This paper reviews the following: (i) schemes of disaster risk management and collaborative data operation in DRM; (ii) geospati...

In this study, a novel unsupervised method for global urban area mapping is proposed. Different from traditional clustering-based unsupervised methods, in our approach a labeler is designed, which is able to automatically select training samples from satellite images by propagating common urban/non-urban knowledge through the unlabeled data. Two ki...

This paper presents a methodology of estimating population at 15-m resolution from ASTER-based urban extent map and existing population grid data. We proposed two methods of estimating population: dasymetric mapping and regression model. Experiment for Tsuchiura City, Japan, and Pasig City, Philippines, showed visually good distribution of the esti...

The ISPRS Student Consortium is an international organization for students and young professionals in the fields of photogrammetry, remote sensing, and the geospatial information sciences. Since its start ten years ago, the number of members of the Student Consortium has been steadily growing, now reaching close to 1000. Its increased popularity, e...

We present an automated classification method for global urban area mapping by integrating satellite images taken by Visible and Near-Infrared Radiometer of Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER/VNIR) and GIS data derived from existing urban area maps. The method consists of two steps. First, we extracted urban areas...

This paper presents methodology of estimating population at 15-m resolution from ASTER-based urban extent map and existing population grid data. We proposed two methods of estimating population: Proportional allocation and regression model. Experiment for Tsuchiura, Japan and Pasig, the Philippines showed visually good distribution of the estimated...

This reports a history and future prospects of the activities by the Student Forum of the Geoinformation Forum Japan. For growths of academic fields, active communications among students and young scientists are indispensable. Several academic communities in geoinformation fields are established by youths and play important roles of building networ...

This paper reports a history and future prospects of the activities by Asian students and young scientists on photogrammetry and remote sensing. For future growths of academic fields, active communications among students and young scientists are indispensable. In some countries and regions in Asia, local communities are already established by youth...

We developed an algorithm to determine a combination of satellite images according to observation extent and image quality. The algorithm was for testing necessity for completing coverage of the search extent. The tests excluded unnecessary images with low quality and preserve necessary images with good quality. The search conditions of the satelli...

We present development of automated algorithm for mapping global urban area in high resolution using ASTER satellite images and coarse-resolution urban area maps. The algorithm consists of two steps: classifying pixels of ASTER satellite images into urban or non-urban by Learning with Global and Local Consistency (LLGC) technique; and integration w...

We developed an algorithm to determine a combination of satellite images according to observation extent and image quality. The algorithm was for testing necessity for completing coverage of the search extent. The tests excluded unnecessary images with low quality and preserve necessary images with good quality. The search conditions of the satelli...

This paper reports a history and future prospects of the activities by Asian students and young scientists on photogrammetry and remote sensing. For future growths of academic fields, active communications among students and young scientists are indispensable. In some countries and regions in Asia, local communities are already established by youth...

We present an internet-based data development, called crowd sourcing, for global urban area mapping. Crowd sourcing is an approach in which non-expert people, called crowds, join a project of producing data with simple procedures. To introducing crowd sourcing for our global urban area mapping, we constructed a crowd sourcing platform with open sou...

We developed a ground truth database for urban areas from the Global Rural-Urban Mapping Project (GRUMP) Settlement Points gazetteer of populated place names by visually interpreting 3,734 urban points on satellite images, thus acquiring 2,144 urban and 1,388 non-urban data points. Our database contained many more urban data points than the existin...

We developed an automated method of image selection and urban area mapping for developing high-resolution global urban area maps. The method was successfully implemented and applied to 3372 cities of more than 0.1 million people of the world. As the result, the algorithm of image selection determined 11802 scenes of ASTER/VNIR satellite images and...

Currently, global urban extent map of high accuracy and high resolution have been constructed mainly using optical sensor including ASTER/VNIR. However, there are some regions where urban areas are not correctly detected due to cloud cover and similar reflectance among land cover classes. To solve the problems, we used microwave sensor images of AL...

We present a practical system for collecting ground truth data needed for global urban area mapping. To collect visually interpreted information effectively, we implemented crowd sourcing, with which the operators collect and send very accurate data generated by visual interpretation through the Internet. The system was constructed with Web Map Ser...

We present development of global urban area map using ASTER satellite images, which has much higher resolution than that of existing global urban area maps. To complete the map for world's cities, we developed automated algorithm for mapping urban area in high resolution. The algorithm consists of two steps: classifying pixels of ASTER satellite im...

Currently, global urban extent map of high accuracy and resolution have been constructed mainly using optical sensor including ASTER/VNIR. However, there are some regions where urban area is not detected because of cloud cover and similar reflectance among land cover classes. In the present work, by using ALOS/PALSAR, a microwave sensor, we propose...