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.

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-

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.

Western Siberia contains the world's most extensive wetlands. Despite its recognition as a significant global carbon reservoir, the spatial structure and composition of micro-topographical elements in patterned wetlands have never been analyzed in detail. To address this uncertainty, we applied a multi-scale approach to make a general and realistic estimation of land cover in Western Siberia. Our approach was based on using a regional wetland typology map (1:2500 000 scale), further refined by satellite image classifications (LANDSAT TM, ETM+ in 1:200 000 scale) on test areas designated in the boreal region of Western Siberia. In addition, QuickBird imagery was used for evaluation the fraction of area occupied by micro-topographical elements within patterned wetlands. Finally, we estimated the areal fractions of these micro-landscapes composing the vegetation mosaic of 20 classes on the wetland typology map for each climatic region of the study area. The total area of peatlands was calculated at 68.5 × 10⁶ ha, which is higher than earlier estimates. We found almost equal areal extents of ridge–hollow and ridge–hollow–pool patterned wetlands in almost all climatic regions of Western Siberia; in the northern boreal region, however, the ridge–hollow–pool wetland type became dominant and exceeded the areal extent of ridge–hollow wetlands in a proportion of 80–20%. Also, the open water fraction increased dramatically in the northern boreal region. The results of this survey can be used in models of ecosystem carbon dynamics and inventory of trace gas fluxes in wetlands.

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.