This page has only limited features, please log in for full access.

Prof. Yoshiki Yamagata
National Institute for Environmental Studies, Tsukuba, Japan

Basic Info


Research Keywords & Expertise

0 Climate Change
0 Data Analysis
0 Land Use
0 System Design
0 environment

Fingerprints

Land Use
Climate Change
environment
urban systems
Data Analysis

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Article
Published: 28 July 2021 in Nature Communications
Reads 0
Downloads 0

This study aims to develop and validate prediction models for the number of all heatstroke cases, and heatstrokes of hospital admission and death cases per city per 12 h, using multiple weather information and a population-based database for heatstroke patients in 16 Japanese cities (corresponding to around a 10,000,000 population size). In the testing dataset, mean absolute percentage error of generalized linear models with wet bulb globe temperature as the only predictor and the optimal models, respectively, are 43.0% and 14.8% for spikes in the number of all heatstroke cases, and 37.7% and 10.6% for spikes in the number of heatstrokes of hospital admission and death cases. The optimal models predict the spikes in the number of heatstrokes well by machine learning methods including non-linear multivariable predictors and/or under-sampling and bagging. Here, we develop prediction models whose predictive performances are high enough to be implemented in public health settings.

ACS Style

Soshiro Ogata; Misa Takegami; Taira Ozaki; Takahiro Nakashima; Daisuke Onozuka; Shunsuke Murata; Yuriko Nakaoku; Koyu Suzuki; Akihito Hagihara; Teruo Noguchi; Koji Iihara; Keiichi Kitazume; Tohru Morioka; Shin Yamazaki; Takahiro Yoshida; Yoshiki Yamagata; Kunihiro Nishimura. Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts. Nature Communications 2021, 12, 1 -11.

AMA Style

Soshiro Ogata, Misa Takegami, Taira Ozaki, Takahiro Nakashima, Daisuke Onozuka, Shunsuke Murata, Yuriko Nakaoku, Koyu Suzuki, Akihito Hagihara, Teruo Noguchi, Koji Iihara, Keiichi Kitazume, Tohru Morioka, Shin Yamazaki, Takahiro Yoshida, Yoshiki Yamagata, Kunihiro Nishimura. Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts. Nature Communications. 2021; 12 (1):1-11.

Chicago/Turabian Style

Soshiro Ogata; Misa Takegami; Taira Ozaki; Takahiro Nakashima; Daisuke Onozuka; Shunsuke Murata; Yuriko Nakaoku; Koyu Suzuki; Akihito Hagihara; Teruo Noguchi; Koji Iihara; Keiichi Kitazume; Tohru Morioka; Shin Yamazaki; Takahiro Yoshida; Yoshiki Yamagata; Kunihiro Nishimura. 2021. "Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts." Nature Communications 12, no. 1: 1-11.

Journal article
Published: 13 May 2021 in Remote Sensing
Reads 0
Downloads 0

Local climate zone (LCZ) maps have been used widely to study urban structures and urban heat islands. Because remote sensing data enable automated LCZ mapping on a large scale, there is a need to evaluate how well remote sensing resources can produce fine LCZ maps to assess urban thermal environments. In this study, we combined Sentinel-2 multispectral imagery and dual-polarized (HH + HV) PALSAR-2 data to generate LCZ maps of Nanchang, China using a random forest classifier and a grid-cell-based method. We then used the classifier to evaluate the importance scores of different input features (Sentinel-2 bands, PALSAR-2 channels, and textural features) for the classification model and their contribution to each LCZ class. Finally, we investigated the relationship between LCZs and land surface temperatures (LSTs) derived from summer nighttime ASTER thermal imagery by spatial statistical analysis. The highest classification accuracy was 89.96% when all features were used, which highlighted the potential of Sentinel-2 and dual-polarized PALSAR-2 data. The most important input feature was the short-wave infrared-2 band of Sentinel-2. The spectral reflectance was more important than polarimetric and textural features in LCZ classification. PALSAR-2 data were beneficial for several land cover LCZ types when Sentinel-2 and PALSAR-2 were combined. Summer nighttime LSTs in most LCZs differed significantly from each other. Results also demonstrated that grid-cell processing provided more homogeneous LCZ maps than the usual resampling methods. This study provided a promising reference to further improve LCZ classification and quantitative analysis of local climate.

ACS Style

Chaomin Chen; Hasi Bagan; Xuan Xie; Yune La; Yoshiki Yamagata. Combination of Sentinel-2 and PALSAR-2 for Local Climate Zone Classification: A Case Study of Nanchang, China. Remote Sensing 2021, 13, 1902 .

AMA Style

Chaomin Chen, Hasi Bagan, Xuan Xie, Yune La, Yoshiki Yamagata. Combination of Sentinel-2 and PALSAR-2 for Local Climate Zone Classification: A Case Study of Nanchang, China. Remote Sensing. 2021; 13 (10):1902.

Chicago/Turabian Style

Chaomin Chen; Hasi Bagan; Xuan Xie; Yune La; Yoshiki Yamagata. 2021. "Combination of Sentinel-2 and PALSAR-2 for Local Climate Zone Classification: A Case Study of Nanchang, China." Remote Sensing 13, no. 10: 1902.

Journal article
Published: 29 May 2020 in Journal of Building Engineering
Reads 0
Downloads 0

In the last decade, retrofitting strategies have been reviewed to improve energy efficiency and reduce the environmental impact of existing buildings. One retrofitting strategy consists of innovating building envelopes with the adoption of high-performance materials or systems. Despite the potential performance enhancement, opportunities for new envelopes have been constrained because various envelope options are difficult to be evaluated synthetically. Also, the decisions should consider the optimization of multiple objectives as well as uncertainties. In this respect, this paper aims to support the decision of selecting building envelopes to meet multiple objectives under uncertainties while considering possible envelope options. A multi-objective optimization model is developed considering the existing built form, uncertainties in performance predictions, and incorporating newly developed façade systems. The optimal selection includes emerging materials and technologies that are provided with building envelope renovation options to satisfy indoor thermal comfort, energy balance, environmental emissions, and economic aspects. The decision-support framework is also devised to add any envelope options. This adaptable framework enables decision makers to accommodate new system materials and proactively evaluate their feasibility. The optimization model and framework proposed in this research will contribute to providing a roadmap for transforming existing buildings into smart and sustainable built systems.

ACS Style

Soowon Chang; Daniel Castro-Lacouture; Yoshiki Yamagata. Decision support for retrofitting building envelopes using multi-objective optimization under uncertainties. Journal of Building Engineering 2020, 32, 101413 .

AMA Style

Soowon Chang, Daniel Castro-Lacouture, Yoshiki Yamagata. Decision support for retrofitting building envelopes using multi-objective optimization under uncertainties. Journal of Building Engineering. 2020; 32 ():101413.

Chicago/Turabian Style

Soowon Chang; Daniel Castro-Lacouture; Yoshiki Yamagata. 2020. "Decision support for retrofitting building envelopes using multi-objective optimization under uncertainties." Journal of Building Engineering 32, no. : 101413.

Journal article
Published: 19 November 2019 in Smart Cities
Reads 0
Downloads 0

Urban systems design arises from disparate current planning approaches (urban design, Planning Support Systems, and community engagement), compounded by the reemergence of rational planning methods from new technology (Internet of Things (IoT), metric based analysis, and big data). The proposed methods join social considerations (Human Well-Being), environmental needs (Sustainability), climate change and disaster mitigation (Resilience), and prosperity (Economics) as the four foundational pillars. Urban systems design integrates planning methodologies to systematically tackle urban challenges, using IoT and rational methods, while human beings form the core of all analysis and objectives. Our approach utilizes an iterative three-phase development loop to contextualize, evaluate, plan and design scenarios for the specific needs of communities. An equal emphasis is placed on feedback loops through analysis and design, to achieve the end goal of building smart communities.

ACS Style

Michael B. Tobey; Robert B. Binder; Soowon Chang; Takahiro Yoshida; Yoshiki Yamagata; Perry P. J. Yang; Yang. Urban Systems Design: A Conceptual Framework for Planning Smart Communities. Smart Cities 2019, 2, 522 -537.

AMA Style

Michael B. Tobey, Robert B. Binder, Soowon Chang, Takahiro Yoshida, Yoshiki Yamagata, Perry P. J. Yang, Yang. Urban Systems Design: A Conceptual Framework for Planning Smart Communities. Smart Cities. 2019; 2 (4):522-537.

Chicago/Turabian Style

Michael B. Tobey; Robert B. Binder; Soowon Chang; Takahiro Yoshida; Yoshiki Yamagata; Perry P. J. Yang; Yang. 2019. "Urban Systems Design: A Conceptual Framework for Planning Smart Communities." Smart Cities 2, no. 4: 522-537.

Journal article
Published: 11 October 2019 in Smart Cities
Reads 0
Downloads 0

Meeting the needs of increasing environmental and systematic pressures in urban settlements requires the use of integrated and wholistic approaches. The Urban Systems Design (USD) Conceptual Framework joins the metric-based modeling of rationalized methods with human-driven goals to form a combined iterative design and analysis loop. The framework processes information for the fundamental element of cities—humans—to large-scale modeling and decision-making occurring in district- and ward-level planning. There is a need in the planning and design profession to better integrate these efforts at a greater scale to create smart communities that are inclusive and comprehensive in aspects from data management to energy and transportation networks. The purpose of this study is to examine the applicability of this method as it pertains to a model and design integrated approach. Northern Sumida Ward, located in Tokyo, exemplifies the contextualized needs of Tokyo, and Japan, while forming a coherent internal community. Focusing on methodology, our process explores the creation of typologies, metric-based analysis, and design-based approaches that are integrated into modeling. The results of the analyses provide initial evidence regarding the validity of the USD approach in modeling changes to complex systems at differing design scales, connecting various qualities of the built environment, building and urban forms, and diagnostic comparisons between baseline and change conditions. Because of some inconsistencies and the need for further evidence gathering, the methods and processes show that there is much work to be done to strengthen the model and to continue building a more productive field of USD. However, in this framework’s continuing evolution, there is increasing evidence that combining the planning and design of urban systems creates a more resilient, economically viable, sustainable, and comfortable city.

ACS Style

Michael B. Tobey; Robert B. Binder; Takahiro Yoshida; Yoshiki Yamagata. Urban Systems Design Case Study: Tokyo's Sumida Ward. Smart Cities 2019, 2, 453 -470.

AMA Style

Michael B. Tobey, Robert B. Binder, Takahiro Yoshida, Yoshiki Yamagata. Urban Systems Design Case Study: Tokyo's Sumida Ward. Smart Cities. 2019; 2 (4):453-470.

Chicago/Turabian Style

Michael B. Tobey; Robert B. Binder; Takahiro Yoshida; Yoshiki Yamagata. 2019. "Urban Systems Design Case Study: Tokyo's Sumida Ward." Smart Cities 2, no. 4: 453-470.

Journal article
Published: 09 April 2019 in Sustainability
Reads 0
Downloads 0

This study downscales the population and gross domestic product (GDP) scenarios given under Shared Socioeconomic Pathways (SSPs) into 0.5-degree grids. Our downscale approach has the following features. (i) It explicitly considers spatial and socioeconomic interactions among cities, (ii) it utilizes auxiliary variables, including road network and land cover, (iii) it endogenously estimates the influence from each factor by a model ensemble approach, and (iv) it allows us to control urban shrinkage/dispersion depending on SSPs. It is confirmed that our downscaling results are consistent with scenario assumptions (e.g., concentration in SSP1 and dispersion in SSP3). Besides, while existing grid-level scenarios tend to have overly-smoothed population distributions in nonurban areas, ours does not suffer from the problem, and captures the difference in urban and nonurban areas in a more reasonable manner. Our gridded dataset, including population counts and gross productivities by 0.5 degree grids by 10 years, are available from http://www.cger.nies.go.jp/gcp/population-and-gdp.html.

ACS Style

Daisuke Murakami; Yoshiki Yamagata. Estimation of Gridded Population and GDP Scenarios with Spatially Explicit Statistical Downscaling. Sustainability 2019, 11, 2106 .

AMA Style

Daisuke Murakami, Yoshiki Yamagata. Estimation of Gridded Population and GDP Scenarios with Spatially Explicit Statistical Downscaling. Sustainability. 2019; 11 (7):2106.

Chicago/Turabian Style

Daisuke Murakami; Yoshiki Yamagata. 2019. "Estimation of Gridded Population and GDP Scenarios with Spatially Explicit Statistical Downscaling." Sustainability 11, no. 7: 2106.

Journal article
Published: 01 February 2019 in Energy Procedia
Reads 0
Downloads 0

To achieve low carbon cities or green smart city, it is very important to foresee how we can reduce the number of cars in the residential communities without losing convenience and comfort of people. For that purpose, walkability is one of the key performance indicators expressing the environmental quality of a district. As the first step for creating a low-carbon smart community, this study attempts to evaluate the influence of walkability on traffic behavior of people by using mobile GPS data. Specifically, we statistically analyze the relationship between various walkability indices (centrality, betweenness, angularity, etc.) evaluated by road network data, and pedestrian movement estimated by mobile GPS data in the six main wards in Tokyo, Japan. The result suggests the usefulness of our approach for low-carbon smart community design rousing people’s walking activity. The walkability results and data are then compared to the results of a macrosimulation traffic model for the Sumida Ward of Tokyo to understand the impact that walkability may have on emissions if built environment conditions are improved in favor of a lesser automobile mode share.

ACS Style

Yoshiki Yamagata; Daisuke Murakami; Yihan Wu; Perry Pei-Ju Yang; Takahiro Yoshida; Robert Binder. Big-data analysis for carbon emission reduction from cars: Towards walkable green smart community. Energy Procedia 2019, 158, 4292 -4297.

AMA Style

Yoshiki Yamagata, Daisuke Murakami, Yihan Wu, Perry Pei-Ju Yang, Takahiro Yoshida, Robert Binder. Big-data analysis for carbon emission reduction from cars: Towards walkable green smart community. Energy Procedia. 2019; 158 ():4292-4297.

Chicago/Turabian Style

Yoshiki Yamagata; Daisuke Murakami; Yihan Wu; Perry Pei-Ju Yang; Takahiro Yoshida; Robert Binder. 2019. "Big-data analysis for carbon emission reduction from cars: Towards walkable green smart community." Energy Procedia 158, no. : 4292-4297.

Book chapter
Published: 01 January 2019 in Encyclopedia of Ecology
Reads 0
Downloads 0

Earth's atmospheric CO2 level has increased beyond 400 ppm and still continuing to rise. In fact, this is the highest level in the last 2 million years. It appears we are heading towards an overshoot of CO2 concentration before stabilizing green house gases (GHGs) to keep global warming below dangerous level. In Paris on December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) agreed to strengthen the global response to the threat of climate change by keeping a global temperature rise this century well below 2° celsius above preindustrial levels and to pursue efforts to limit the temperature increase even further to 1.5° celsius. Can this level of CO2 stabilization still be achieved? One core strategies in the mitigation mix are negative emissions technologies (NETs) which are also explicitly described as important options in many IPCC (AR5) CO2 emission scenarios. Among others, BioEnergy with Carbon Capture and Storage (BECCS) are shown their potential for CO2 removable from the atmosphere. BECCS as the NETs are most widely selected by integrated assessment models (IAMs) to meet the requirements of temperature limits of 2° and below. It is based on assumed carbon-neutral bioenergy combined with capture of CO2 produced by combustion and its subsequent storage in geological or ocean repositories. BECCS is a net transfer of CO2 from the atmosphere into geological layers. However, its credibility as a climate change mitigation option and their impacts to global and regional ecosystems are still unknown. To explore the ecosystem impacts of the large-scale deployment of negative emission land use scenarios, we review some papers that are analyzing global impacts of the land use scenarios on various factors of ecosystem services to look at the sustainability limits to their global large scale deployments. Ecological services implications of the NETs especially land demanding BECCS land use scenarios need to be addressed before implementing such projects not only for achieving global low carbon target but also achieving more comprehensive ecological sustainabilities to meet the sustainable development goals (SDGs).

ACS Style

Yoshiki Yamagata. Global Negative Emission Land Use Scenarios and Their Ecological Implications. Encyclopedia of Ecology 2019, 96 -107.

AMA Style

Yoshiki Yamagata. Global Negative Emission Land Use Scenarios and Their Ecological Implications. Encyclopedia of Ecology. 2019; ():96-107.

Chicago/Turabian Style

Yoshiki Yamagata. 2019. "Global Negative Emission Land Use Scenarios and Their Ecological Implications." Encyclopedia of Ecology , no. : 96-107.

Journal article
Published: 28 November 2018 in Sustainability
Reads 0
Downloads 0

The objective of this study is to map direct and indirect seasonal urban carbon emissions using spatial micro Big Data, regarding building and transportation energy-use activities in Sumida, Tokyo. Building emissions were estimated by considering the number of stories, composition of use (e.g., residence and retail), and other factors associated with individual buildings. Transportation emissions were estimated through dynamic transportation behaviour modelling, which was obtained using person-trip surveys. Spatial seasonal emissions were evaluated and visualized using three-dimensional (3D) mapping. The results suggest the usefulness of spatial micro Big Data for seasonal urban carbon emission mapping; a process which combines both the building and transportation sectors for the first time with 3D mapping, to detect emission hot spots and to support community-level carbon management in the future.

ACS Style

Yoshiki Yamagata; Takahiro Yoshida; Daisuke Murakami; Tomoko Matsui; Yuki Akiyama. Seasonal Urban Carbon Emission Estimation Using Spatial Micro Big Data. Sustainability 2018, 10, 4472 .

AMA Style

Yoshiki Yamagata, Takahiro Yoshida, Daisuke Murakami, Tomoko Matsui, Yuki Akiyama. Seasonal Urban Carbon Emission Estimation Using Spatial Micro Big Data. Sustainability. 2018; 10 (12):4472.

Chicago/Turabian Style

Yoshiki Yamagata; Takahiro Yoshida; Daisuke Murakami; Tomoko Matsui; Yuki Akiyama. 2018. "Seasonal Urban Carbon Emission Estimation Using Spatial Micro Big Data." Sustainability 10, no. 12: 4472.

Chapter
Published: 21 February 2018 in The Interrelationship Between Financial and Energy Markets
Reads 0
Downloads 0

Climate resiliency is a key topic for cities across the world especially after the Paris Agreement. By combing socio-economic situations, carbon emission reduction, disaster risk management, and other factors determine sustainability of cities, we need to understand trade-offs among these factors. In other words, wise urban systems design are required in cities in the world. Especially in the developed countries like Japan which are expected to experience unprecedented pollution decrease, we need to achieve “wise shrink” of cities that are desirable from multiple viewpoints. With such a background, we introduce our spatially-explicit urban land-use model (SULM) as a tool to analyze the trade-offs among climate resilient sustainability. The SULM is applied to an analysis in the Tokyo metropolitan area to analyze the implications of Business-As-usual (BAU), Compact city, and Wise shrink land use scenarios. SULM could be a useful tool for assessing urban resiliency against climate extreme events for eco-urbanism oriented land forms.

ACS Style

Yoshiki Yamagata; Daisuke Murakami. Spatially Explicit Land-Use Modelling for Assessing Climate-Resilient Sustainable Urban Forms. The Interrelationship Between Financial and Energy Markets 2018, 213 -228.

AMA Style

Yoshiki Yamagata, Daisuke Murakami. Spatially Explicit Land-Use Modelling for Assessing Climate-Resilient Sustainable Urban Forms. The Interrelationship Between Financial and Energy Markets. 2018; ():213-228.

Chicago/Turabian Style

Yoshiki Yamagata; Daisuke Murakami. 2018. "Spatially Explicit Land-Use Modelling for Assessing Climate-Resilient Sustainable Urban Forms." The Interrelationship Between Financial and Energy Markets , no. : 213-228.

Journal article
Published: 16 January 2018 in Environment and Planning B: Urban Analytics and City Science
Reads 0
Downloads 0

Nighttime data from the Defense Meteorological Satellite Program Operational Linescan System have been widely used to map urban/built-up areas (hereafter referred to as “built-up area”), but to date there has not been a geographically comprehensive evaluation of the effectiveness of using nighttime lights data to map urban areas. We created accurate, convenient, and scalable grid cells based on Defense Meteorological Satellite Program/Operational Linescan System nighttime light pixels. We then calculated the density of Landsat-derived built-up areas within each grid cell. We explored the relationship between Defense Meteorological Satellite Program/Operational Linescan System nighttime lights data and the density of built-up areas to assess the utility of nighttime lights for mapping urban areas in 50 cities across the globe. We found that the brightness of nighttime lights was only in moderate agreement with the density of built-up areas; moreover, correlations between nighttime lights and Landsat-derived built-up areas were weak. Even in relatively sparsely populated urban regions (where the density of the built-up area is less than 20%), the highest correlation coefficient ( R2) was only 0.4. Furthermore, nighttime lights showed lighted areas that extended beyond the area of large cities, and nighttime lights reduced the area of small cities. The results suggest that it is difficult to use the regression model to calibrate the Defense Meteorological Satellite Program/Operational Linescan System nighttime lights to fit urban built up areas.

ACS Style

Hasi Bagan; Habura Borjigin; Yoshiki Yamagata. Assessing nighttime lights for mapping the urban areas of 50 cities across the globe. Environment and Planning B: Urban Analytics and City Science 2018, 46, 1097 -1114.

AMA Style

Hasi Bagan, Habura Borjigin, Yoshiki Yamagata. Assessing nighttime lights for mapping the urban areas of 50 cities across the globe. Environment and Planning B: Urban Analytics and City Science. 2018; 46 (6):1097-1114.

Chicago/Turabian Style

Hasi Bagan; Habura Borjigin; Yoshiki Yamagata. 2018. "Assessing nighttime lights for mapping the urban areas of 50 cities across the globe." Environment and Planning B: Urban Analytics and City Science 46, no. 6: 1097-1114.

Journal article
Published: 08 January 2018 in Sustainability Science
Reads 0
Downloads 0

Negative emission technologies such as bioenergy with carbon capture and storage (BECCS) are regarded as an option to achieve the climatic target of the Paris Agreement. However, our understanding of the realistic sustainable feasibility of the global lands for BECCS remains uncertain. In this study, we assess the impact of BECCS deployment scenarios on the land systems including land use, water resources, and ecosystem services. Specifically, we assess three land-use scenarios to achieve the total amount of 3.3 GtC year−1 (annual negative emission level required for IPCC-RCP 2.6) emission reduction by growing bioenergy crops which requires huge use of global agricultural and forest lands and water. Our study shows that (1) vast conversion of food cropland into rainfed bio-crop cultivation yields a considerable loss of food production that may not be tolerable considering the population increase in the future. (2) When irrigation is applied to bio-crop production, the bioenergy crop productivity is enhanced. This suppresses the necessary area for bio-crop production to half, and saves the land for agricultural productions. However, water consumption is doubled and this may exacerbate global water stress. (3) If conversion of forest land for bioenergy crop cultivation is allowed without protecting the natural forests, large areas of tropical forest could be used for bioenergy crop production. Forest biomass and soil carbon stocks are reduced, implying degradation of the climate regulation and other ecosystem services. These results suggest that without a careful consideration of the land use for bioenergy crop production, a large-scale implementation of BECCS could negatively impact food, water and ecosystem services that are supporting fundamental human sustainability.

ACS Style

Yoshiki Yamagata; Naota Hanasaki; Akihiko Ito; Tsuguki Kinoshita; Daisuke Murakami; Qian Zhou. Estimating water–food–ecosystem trade-offs for the global negative emission scenario (IPCC-RCP2.6). Sustainability Science 2018, 13, 301 -313.

AMA Style

Yoshiki Yamagata, Naota Hanasaki, Akihiko Ito, Tsuguki Kinoshita, Daisuke Murakami, Qian Zhou. Estimating water–food–ecosystem trade-offs for the global negative emission scenario (IPCC-RCP2.6). Sustainability Science. 2018; 13 (2):301-313.

Chicago/Turabian Style

Yoshiki Yamagata; Naota Hanasaki; Akihiko Ito; Tsuguki Kinoshita; Daisuke Murakami; Qian Zhou. 2018. "Estimating water–food–ecosystem trade-offs for the global negative emission scenario (IPCC-RCP2.6)." Sustainability Science 13, no. 2: 301-313.

Journal article
Published: 04 January 2018 in The Egyptian Journal of Remote Sensing and Space Science
Reads 0
Downloads 0

The quality of a supervised classification map depends on the quality of the ground reference data and the classification method used. However, training samples for agriculture landscapes are often mixed with noise. Therefore, the classification of agriculture regions using remotely sensed data requires the use of classification methods with good generalization capabilities. In this study, the performance of the subspace method in land cover classification of a complex cropping mix area is explored. Landsat-5 thematic mapper (TM) data were used to classify 12 different land cover classes in the study area, located between Tianjin and Tangshan cities in northern China. We compared the classification maps obtained using the subspace method with those obtained using the self-organizing map neural network (SOM) and maximum likelihood classification (MLC) methods. The results of this comparative study confirm that the subspace method performed better than both the SOM and MLC methods. Furthermore, a comparison of the sensitivity of these methods to the reduction in the training sample size shows that the subspace method has a lower sensitivity to variations in the number of training pixels used than the other two methods. Our results demonstrate the ability of the subspace method to distinguish between different crop types over a large area. Moreover, the subspace method is less sensitive to small training sample sizes than the other two methods.

ACS Style

Hasi Bagan; Huilong Li; Yonghui Yang; Wataru Takeuchi; Yoshiki Yamagata. Sensitivity of the subspace method for land cover classification. The Egyptian Journal of Remote Sensing and Space Science 2018, 21, 383 -389.

AMA Style

Hasi Bagan, Huilong Li, Yonghui Yang, Wataru Takeuchi, Yoshiki Yamagata. Sensitivity of the subspace method for land cover classification. The Egyptian Journal of Remote Sensing and Space Science. 2018; 21 (3):383-389.

Chicago/Turabian Style

Hasi Bagan; Huilong Li; Yonghui Yang; Wataru Takeuchi; Yoshiki Yamagata. 2018. "Sensitivity of the subspace method for land cover classification." The Egyptian Journal of Remote Sensing and Space Science 21, no. 3: 383-389.

Journal article
Published: 01 December 2017 in Energy Procedia
Reads 0
Downloads 0

The objective of this study is mapping carbons utilizing spatial BigData relating buildings and transportations. Regarding buildings, number of storeys, composition of use (e.g., residence and shops), and area of individual buildings are considered. Difference of hourly emission intensity from residence, commercial buildings, firms, and so on, also considered. Regarding transportations, vehicle location by one minutes are considered to capture dynamic fluctuation of transportation behavior. CO2 emissions from individual buildings and road links in Sumida, Tokyo, Japan, are estimated by 30 minutes by a bottom-up approach. The results are visualized in a 3D manner. The result suggests the usefulness of our carbon mapping approach to detect hot spots, abnormal emissions, and so on, that helps efficient carbon management.

ACS Style

Yoshiki Yamagata; Daisuke Murakami; Takahiro Yoshida. Urban carbon mapping with spatial BigData. Energy Procedia 2017, 142, 2461 -2466.

AMA Style

Yoshiki Yamagata, Daisuke Murakami, Takahiro Yoshida. Urban carbon mapping with spatial BigData. Energy Procedia. 2017; 142 ():2461-2466.

Chicago/Turabian Style

Yoshiki Yamagata; Daisuke Murakami; Takahiro Yoshida. 2017. "Urban carbon mapping with spatial BigData." Energy Procedia 142, no. : 2461-2466.

Model experiment description paper
Published: 30 November 2017 in Geoscientific Model Development
Reads 0
Downloads 0

In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a special report in 2018 on the impacts of global warming of 1.5 °C above pre-industrial levels and related global greenhouse gas emission pathways. In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5 °C, including a potential overshoot and long-term impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the low-emissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across different sectors (global and regional hydrology, lakes, global crops, global vegetation, regional forests, global and regional marine ecosystems and fisheries, global and regional coastal infrastructure, energy supply and demand, temperature-related mortality, and global terrestrial biodiversity).

ACS Style

Katja Frieler; Stefan Lange; Franziska Piontek; Christopher P. O. Reyer; Jacob Schewe; Lila Warszawski; Fang Zhao; Louise Chini; Sebastien Denvil; Kerry Emanuel; Tobias Geiger; Kate Halladay; George Hurtt; Matthias Mengel; Daisuke Murakami; Sebastian Ostberg; Alexander Popp; Riccardo Riva; Miodrag Stevanovic; Tatsuo Suzuki; Jan Volkholz; Eleanor Burke; Philippe Ciais; Kristie Ebi; Tyler D. Eddy; Joshua Elliott; Eric Galbraith; Simon N. Gosling; Fred Hattermann; Thomas Hickler; Jochen Hinkel; Christian Hof; Veronika Huber; Jonas Jägermeyr; Valentina Krysanova; Rafael Marcé; Hannes Müller Schmied; Ioanna Mouratiadou; Don Pierson; Derek P. Tittensor; Robert Vautard; Michelle van Vliet; Matthias F. Biber; Richard A. Betts; Benjamin Leon Bodirsky; Delphine Deryng; Steve Frolking; Chris D. Jones; Heike K. Lotze; Hermann Lotze-Campen; Ritvik Sahajpal; Kirsten Thonicke; Hanqin Tian; Yoshiki Yamagata. Assessing the impacts of 1.5 °C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b). Geoscientific Model Development 2017, 10, 4321 -4345.

AMA Style

Katja Frieler, Stefan Lange, Franziska Piontek, Christopher P. O. Reyer, Jacob Schewe, Lila Warszawski, Fang Zhao, Louise Chini, Sebastien Denvil, Kerry Emanuel, Tobias Geiger, Kate Halladay, George Hurtt, Matthias Mengel, Daisuke Murakami, Sebastian Ostberg, Alexander Popp, Riccardo Riva, Miodrag Stevanovic, Tatsuo Suzuki, Jan Volkholz, Eleanor Burke, Philippe Ciais, Kristie Ebi, Tyler D. Eddy, Joshua Elliott, Eric Galbraith, Simon N. Gosling, Fred Hattermann, Thomas Hickler, Jochen Hinkel, Christian Hof, Veronika Huber, Jonas Jägermeyr, Valentina Krysanova, Rafael Marcé, Hannes Müller Schmied, Ioanna Mouratiadou, Don Pierson, Derek P. Tittensor, Robert Vautard, Michelle van Vliet, Matthias F. Biber, Richard A. Betts, Benjamin Leon Bodirsky, Delphine Deryng, Steve Frolking, Chris D. Jones, Heike K. Lotze, Hermann Lotze-Campen, Ritvik Sahajpal, Kirsten Thonicke, Hanqin Tian, Yoshiki Yamagata. Assessing the impacts of 1.5 °C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b). Geoscientific Model Development. 2017; 10 (12):4321-4345.

Chicago/Turabian Style

Katja Frieler; Stefan Lange; Franziska Piontek; Christopher P. O. Reyer; Jacob Schewe; Lila Warszawski; Fang Zhao; Louise Chini; Sebastien Denvil; Kerry Emanuel; Tobias Geiger; Kate Halladay; George Hurtt; Matthias Mengel; Daisuke Murakami; Sebastian Ostberg; Alexander Popp; Riccardo Riva; Miodrag Stevanovic; Tatsuo Suzuki; Jan Volkholz; Eleanor Burke; Philippe Ciais; Kristie Ebi; Tyler D. Eddy; Joshua Elliott; Eric Galbraith; Simon N. Gosling; Fred Hattermann; Thomas Hickler; Jochen Hinkel; Christian Hof; Veronika Huber; Jonas Jägermeyr; Valentina Krysanova; Rafael Marcé; Hannes Müller Schmied; Ioanna Mouratiadou; Don Pierson; Derek P. Tittensor; Robert Vautard; Michelle van Vliet; Matthias F. Biber; Richard A. Betts; Benjamin Leon Bodirsky; Delphine Deryng; Steve Frolking; Chris D. Jones; Heike K. Lotze; Hermann Lotze-Campen; Ritvik Sahajpal; Kirsten Thonicke; Hanqin Tian; Yoshiki Yamagata. 2017. "Assessing the impacts of 1.5 °C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b)." Geoscientific Model Development 10, no. 12: 4321-4345.

Journal article
Published: 16 June 2017 in Sustainability
Reads 0
Downloads 0

Resilience is a multi-faceted concept frequently used across a wide range of disciplines, practices, and sectors. There is a growing recognition of the utility of resilience as a bridging concept that can facilitate inter-and transdisciplinary approaches to tackle complexities inherent in decision making under conditions of risk and uncertainty. Such conditions are common in urban planning, infrastructure planning, asset management, emergency planning, crisis management, and development processes where systemic interdependencies and interests at stake influence decisions and outcomes. A major challenge that can undermine the use of resilience for guiding planning activities is the value-laden and contested nature of the concept that can be interpreted in a variety of ways. Because resilience is context-specific and generally depends on local aspirations, this issue can be partially tackled by adopting participatory approaches for the conceptualization of resilience. This paper provides an example of how co-design methods can be employed for conceptualizing resilience. The Structured Interview Matrix was used as a technique to facilitate discussions among a diverse group of researchers and practitioners attending the International Workshop on Tools and Indicators for Assessing Urban Resilience. Participants deliberated on issues related to constituent elements of urban resilience, including its position vis-

ACS Style

Ayyoob Sharifi; Lorenzo Chelleri; Cate Fox-Lent; Stelios Grafakos; Minal Pathak; Marta Olazabal; Susie Moloney; Lily Yumagulova; Yoshiki Yamagata. Conceptualizing Dimensions and Characteristics of Urban Resilience: Insights from a Co-Design Process. Sustainability 2017, 9, 1032 .

AMA Style

Ayyoob Sharifi, Lorenzo Chelleri, Cate Fox-Lent, Stelios Grafakos, Minal Pathak, Marta Olazabal, Susie Moloney, Lily Yumagulova, Yoshiki Yamagata. Conceptualizing Dimensions and Characteristics of Urban Resilience: Insights from a Co-Design Process. Sustainability. 2017; 9 (6):1032.

Chicago/Turabian Style

Ayyoob Sharifi; Lorenzo Chelleri; Cate Fox-Lent; Stelios Grafakos; Minal Pathak; Marta Olazabal; Susie Moloney; Lily Yumagulova; Yoshiki Yamagata. 2017. "Conceptualizing Dimensions and Characteristics of Urban Resilience: Insights from a Co-Design Process." Sustainability 9, no. 6: 1032.

Journal article
Published: 01 May 2017 in Energy Procedia
Reads 0
Downloads 0
ACS Style

Yoshiki Yamagata; Daisuke Murakami. Spatially-explicit Resilience Modeling for PV Electricity Supply-demand Balance. Energy Procedia 2017, 105, 3269 -3274.

AMA Style

Yoshiki Yamagata, Daisuke Murakami. Spatially-explicit Resilience Modeling for PV Electricity Supply-demand Balance. Energy Procedia. 2017; 105 ():3269-3274.

Chicago/Turabian Style

Yoshiki Yamagata; Daisuke Murakami. 2017. "Spatially-explicit Resilience Modeling for PV Electricity Supply-demand Balance." Energy Procedia 105, no. : 3269-3274.

Journal article
Published: 18 December 2016 in Spatial Statistics
Reads 0
Downloads 0

This study develops a spatially varying coefficient model by extending the random effects eigenvector spatial filtering model. The developed model has the following properties: its spatially varying coefficients are defined by a linear combination of the eigenvectors describing the Moran coefficient; each of its coefficients can have a different degree of spatial smoothness; and it yields a variant of a Bayesian spatially varying coefficient model. Moreover, parameter estimation of the model can be executed with a relatively small computational burden. Results of a Monte Carlo simulation reveal that our model outperforms a conventional eigenvector spatial filtering (ESF) model and geographically weighted regression (GWR) models in terms of the accuracy of the coefficient estimates and computational time. We empirically apply our model to the hedonic land price analysis of flood hazards in Japan.

ACS Style

Daisuke Murakami; Takahiro Yoshida; Hajime Seya; Daniel A. Griffith; Yoshiki Yamagata. A Moran coefficient-based mixed effects approach to investigate spatially varying relationships. Spatial Statistics 2016, 19, 68 -89.

AMA Style

Daisuke Murakami, Takahiro Yoshida, Hajime Seya, Daniel A. Griffith, Yoshiki Yamagata. A Moran coefficient-based mixed effects approach to investigate spatially varying relationships. Spatial Statistics. 2016; 19 ():68-89.

Chicago/Turabian Style

Daisuke Murakami; Takahiro Yoshida; Hajime Seya; Daniel A. Griffith; Yoshiki Yamagata. 2016. "A Moran coefficient-based mixed effects approach to investigate spatially varying relationships." Spatial Statistics 19, no. : 68-89.

Preprint
Published: 28 October 2016
Reads 0
Downloads 0

This study downscales the population and gross domestic product (GDP) scenarios given under Shared Socioeconomic Pathways (SSPs) into 0.5-degree grids. Our downscale approach has the following features: (i) it explicitly considers spatial and socioeconomic interactions among cities; (ii) it utilizes auxiliary variables, including, road network and land cover; (iii) it endogenously estimates influence from each factor by a model ensemble approach; (iv) it allows us controlling urban shrinkage/dispersion depending on SSPs. It is confirmed that our downscaling results are consistent with scenario assumptions (e.g., concentration in SSP1 and dispersion in SSP3). Besides, while existing grid-level scenario tends to have overly-smoothed population distributions in non-urban areas, ours does not suffer from the problem, and captures difference in urban and non-urban areas in a more reasonable manner.

ACS Style

Daisuke Murakami; Yoshiki Yamagata. Estimation of gridded population and GDP scenarios with spatially explicit statistical downscaling. 2016, 1 .

AMA Style

Daisuke Murakami, Yoshiki Yamagata. Estimation of gridded population and GDP scenarios with spatially explicit statistical downscaling. . 2016; ():1.

Chicago/Turabian Style

Daisuke Murakami; Yoshiki Yamagata. 2016. "Estimation of gridded population and GDP scenarios with spatially explicit statistical downscaling." , no. : 1.

Book chapter
Published: 11 August 2016 in Physics of Automatic Target Recognition
Reads 0
Downloads 0

This chapter introduces our newly developed Spatially explicit Urban Land-use Model (SULM) as a tool for resilient urban planning. The SULM can create land-use and social economic scenarios at micro districts level based on an urban economic theory. In order to co-design transformative urban plans with local stake holders, it is important to visualize possible future land-use scenarios. This model makes it possible to endogenously project the residential choice of households, floor space and land area with considering location-specific disaster risk as well as economic and environmental factors. With this model, we can create scenarios for not only urban growth, but also urban shrinking, thus the method could be useful for both developing and developed countries’ situations. In this study, the model was developed and calibrated for the Tokyo Metropolitan Area (Greater Tokyo) at the micro-district level (around 1 km grid) and used to simulate possible land-use scenarios with different urban forms. We have specifically looked at the implications for climate change mitigation and adaptation capacities. This chapter explains mainly the tested three land-use scenarios; (1) Business as usual scenario, (2) Extreme urban compact city scenario, and (3) Combined mitigation and adaptation scenario. The scenarios were assessed with multiple criteria including disaster/energy resilience and environmental sustainability (CO2 emissions, urban climate) and economic benefits. The obtained results have shown that fairly large future economic costs could be saved by additionally considering adaptation (flood risk) in combination with mitigation (CO2 emissions) in the scenario that we call “Wise Shrinking”. Our research suggests that integration of resilience thinking into urban planning is important and promising.

ACS Style

Yoshiki Yamagata; Hajime Seya; Daisuke Murakami. Urban Economics Model for Land-Use Planning. Physics of Automatic Target Recognition 2016, 25 -43.

AMA Style

Yoshiki Yamagata, Hajime Seya, Daisuke Murakami. Urban Economics Model for Land-Use Planning. Physics of Automatic Target Recognition. 2016; ():25-43.

Chicago/Turabian Style

Yoshiki Yamagata; Hajime Seya; Daisuke Murakami. 2016. "Urban Economics Model for Land-Use Planning." Physics of Automatic Target Recognition , no. : 25-43.