Numerous rockfall incidents involving infrastructure damage and loss of life have been reported along roads in mountainous terrain. Previous studies have used quantitative risk assessment approaches to identify the level of rockfall risk. However, appropriate quantitative indicators that are able to describe time-varying risk have not yet been developed. This study aims to develop a rockfall risk mitigation method based on reliability concepts, to classify rockfall data, to model the probability of rockfall occurrence, and to estimate the magnitude of risk reduction through mitigation measures. A synthetic measure of rockfall risk is proposed, which allows to compare directly and quantitatively the rockfall risk for different cut slopes under unmitigated and mitigated conditions. The proposed methodology can estimate the risk reduction obtained using mitigation measures, such as introducing protections barriers, their periodic maintenance, and horizontal coverage ratio. This methodology was applied to 20 years of rockfall data collected by the Korea Expressway Corporation from 1215 artificial cut slopes along the highway network in South Korea. The rockfall frequency was analyzed based on the inventory data, and a rockfall hazard mitigation strategy was demonstrated using the suggested methodology for the case study. It was shown that appropriate mitigation strategies, based on number of protection barriers, interval of periodic maintenance, and horizontal coverage ratio, can be devised to reduce the risk of different artificial slopes below a target failure probability. The approach shown in this study can provide insights into ways of improving overall risk management to prevent losses by rockfall.

The shape and size of planning units (PUs) at the initial stage of regional systematic conservation planning (SCP) can strongly affect the final portfolio. In previous studies, the influence of PU shape and size has typically been considered for single study sites that include mainly natural land cover types. The impacts of PU shape and size in areas dominated by different land cover types have not been compared. We identified and compared the influence of three types of land uses, and shape and size of PUs in the efficiency of final portfolios in SCP. We show that PU shape is not significant for portfolio efficiency in all areas dominated by different land cover types, while smaller size of PUs would be more useful in the heterogeneous landscapes like agricultural and urban areas than the homogeneous landscapes like forest. We also show that the magnitude of the influences of PU shape and size differs depending on the dominant land cover type. Areas dominated by agricultural land cover were the most sensitive to the influence of PU shape and size, whereas areas dominated by forest were the least sensitive. Therefore, we recommend to planners to understand the different impacts of PU shape and size by the dominant land cover type and consider a similar approach with this study.

Context: Although many studies have considered urban structure when investigating urban ecological networks, few have considered the three-dimensional (3D) structure of buildings as well as urban green spaces. Airborne LiDAR datasets provide an opportunity to quantify 3D structure and evaluate 3D metrics in connectivity mapping. Objectives: We examined an urban ecological network using the 3D structure of both green spaces and buildings. Methods: Using breeding-season bird species observations and airborne LiDAR data collected, we assessed the influence of 3D structural variables on species diversity. We used correlation analyses to determine if vertical distribution, volume, area, and height of both buildings and vegetation were related to bird species diversity. Then we conducted circuit theory-based current flow betweenness centrality (CFBC) analysis using the LiDAR-derived structural variables. Results: We found that the volumes of buildings and 8–10 m vegetation heights were both highly correlated with species richness per unit area. There were significant differences between 2D and 3D connectivity analysis using LiDAR-derived variables among urban forest patches, boulevards, and apartment complexes. Within urban forest patches and parks, 3D CFBC represented canopy structural characteristics well, by showing high variance in spatial distributions. Conclusions: The 3D CFBC results indicated that adjacent high-rise buildings, dense apartment complexes, and densely urbanized areas were isolated, as characterized by low centrality values, but that vegetation planted in open spaces between buildings could improve connectivity by linking isolated areas to core areas. Our research highlights the importance of considering 3D structure in planning and managing urban ecological connectivity.

As human populations move into cities they are increasingly isolated from the natural world, with associated negative impacts on health and well-being. However, as cities renew themselves through urban redevelopment and climate-adaptation, opportunities arise to improve people's access to urban green areas that can be informed by modeling the network of urban open spaces. Recent research identified the need for multi-criteria indices of access to urban green spaces. Including open spaces such as empty lots, ground- A nd air-spaces surrounding buildings, and spaces associated with roads and other linear features can improve planning for urban greenspaces by identifying areas of opportunity for additional greening. Further, the gradient of interconnections among open spaces can be used to prioritize urban greening locations to build green networks. We modelled all open-space connections across 605 km2 in Seoul, population 10.3 million, using Omniscape, a landscape connectivity model. We combined the resulting open-space connectivity map with distance-based indices for existing urban parks and street trees. Combining these criteria permits rank-prioritization of locations where new green spaces would most improve residents' access. We found 2910 of 3375 (86.2%) locations where urban green spaces already exist within 300 m for city residents. Of the remaining 465 locations, 276 are in areas with the lowest-open space connections. For urban street trees, 44.3% of the 2588 km of the city's major roads are already planted with street trees. Of the remainder, 210 km (8.1%) are located in the areas with the least connections to green spaces. Nine new urban parks would provide relief for the most highly-impacted areas, where the flow of open space is lowest and where no green spaces are available within 300 m. The integration of a spatial model typically used for conservation assessments with city planning provides useful additional context for building urban health.

Increasing heat in urban areas raises heat-related health risks. Green infrastructure and managing surface albedo can reduce the radiation exposure of pedestrians. However, selecting options among various radiant fluxes mitigation strategies is challenging, particularly due to potential interactions among options such as planting vegetation or changing surface albedos. We used a multi-strategies model for determining optimal design combinations for reducing mean radiant temperature (MRT) in urban environments across a range of costs and benefits. The solutions are developed by a non-dominated sorting genetic algorithm II (NSGA II) with a MRT simulator. We selected four MRT reduction strategies: tree planting, grass planting, albedo reduction of building walls, and albedo reduction of sidewalks. Model test results for a simulated street canyon show a wide range of optimal alternative plans considering the combination effects of the four strategies. While previous studies have focused on single options to reduce heat load, we found benefits were higher by using a combination of these strategies, which can provide synergistic benefits. These results provide useful information for decision makers confronting real world problems such as heat related mortality. Thermal-friendly design methods and green infrastructure will help the urban environment become sustainable and improve human health and well-being.

Mapping the elderly population exposure to heat hazard in urban areas is important to inform adaptation strategies for increasingly-deadly urban heat under climate change. However, fine-scale mapping is lacking, because global climate change projections have not previously been integrated with urban heat island effects especially with urban three-dimensional characteristics for within-city heat risk analyses. This study compared the spatial patterns of deadly heat exposure for elderly populations in two East Asian megacities, Seoul and Tokyo, using current climate (2006–2015) and two future periods (2040s and 2090s). We integrated global warming projections (the Shared Socioeconomic Pathway 5 based on Representative Concentration Pathway 8.5) with local urban characteristics and demographics. We found that, for the historical period, the overall hotspots of elderly population exposure to urban heat was larger in Tokyo because of relatively higher maximum air temperatures and lack of green spaces, whereas in the future periods, Seoul will have larger hotspots because the elderly population density will have increased. About 20% of the area in Seoul and 0.3–1% of Tokyo will be hotpots in the 2040s, and the size of these hotspots increases to 25–26% and 2–3%, respectively, in the 2090s. The spatial patterns of hotspots identify different types of priority areas and suggest that alternative adaptation strategies for two cities are appropriate. The approach introduced here will be useful for identifying sustainable thermal environments in other cities with high density elderly population and severe heat hazard.

Because trees can positively influence local environments in urban ecosystems, it is important to measure their morphological characteristics, such as height and diameter at breast height (DBH). However, measuring these data for each individual tree is a time-consuming process that requires a great deal of manpower. In this study, we investigated the feasibility of using mobile LiDAR to estimate tree height and DBH along urban streets and in urban parks. We compared measurements from a mobile LiDAR unit with field measurements of tree height and DBH in urban parks and streets. The height-above-ground and Pratt circle fit methods were applied to calculate tree height and DBH, respectively. The LiDAR-estimated tree heights were highly accurate albeit slightly underestimated, with a root mean square error of 0.359 m for the street trees and 0.462 m for the park trees. On the other hand, the estimated DBHs were moderately accurate and overestimated, with a root mean square error of 3.77 cm for the street trees and 8.95 cm for the park trees. Densely planted trees in the park and obstacles in urban areas result in “shadows” (areas with no data), reducing accuracy. Irregular trunk shapes and scanned data that did not include full data point coverage of every trunk were the reasons for the errors. Despite these errors, this study highlights the potential of tree measurements obtained with mobile terrestrial LiDAR platforms to be scaled up from point-based locations to neighborhood-scale and city-scale inventories.

As climate change is ongoing, many studies have recently focused on adaptation to climate change from a spatial perspective. However little is known about how changing the spatial composition of landuse could improve climate change resilience. Consideration of climate change impacts when spatially allocating landuse could be a useful and fundamental long term adaptation strategy, particularly for regional planning. Here, we identify climate adaptation scenarios based on existing extents of three landuse classes using multi-objective genetic algorithms for a 9982 km 2 region with 3.5 million inhabitants in South Korea. We selected five objectives for adaptation based on predicted climate change impacts and regional economic conditions: minimization of disaster damage and existing landuse conversion, maximization of rice yield, protection of high species richness areas, and economic value. We generated 17 Pareto landuse scenarios by six weighted combinations of the adaptation objectives. Most scenarios, although varying in magnitude, showed better performance than the current spatial landuse composition for all adaptation objectives, suggesting that some alteration of current landuse patterns could increase overall climate resilience. Given the flexible structure of the optimization model, we expect that regional stakeholders could efficiently generate other scenarios by adjusting model parameters (weighting combinations) or replacing input data (impact maps), and selecting a scenario depending on preference or a number of problem-related factors.

The movement of wildlife can be constrained by river development projects owing to the presence of artificial structures. This study analyzes the spatial riparian crossing patterns of two mammal species, the leopard cat (Felis bengalensis euptilura) and water deer (Hydropotes inermis). We examine their ability to traverse from habitat on one side of the river to the other, through riparian vegetation, embankments, and the river,. We used 34 months of monitoring on 104 stream segments with varying levels of human modification on the Seom river, South Korea, to analyze their riparian crossing preferences across the river between suitable habitats on either side of the steam. Environmental variables were used for two scales of analysis: a watershed scale and a stream segment scale that examined both riparian habitat suitability and riparian crossings. At the watershed scale, habitat suitability was determined using species distribution modeling. The resulting maps were inputted with other predictor variables to logistic regression models to predict areas of high probability for the species’ occurences. For the river segment analyses, we determined species’ presences and potential crossings from snow tracking, heat sensor cameras, and scat. We compared the predicted crossing locations from the watershed scale model to observed crossings. The watershed models indicate that leopard cats prefer upland forest, while water deer prefer the forest edge and riparian corridor. For both target species, the best riparian habitats were characterized by the presence of vegetation cover on the embankment and by at least one side of an embankment being adjacent to farmland or forest cover. The two species showed different riparian crossing preferences. Water deer crossed through large culverts or under bridges, whereas leopard cats utilized drainage pipes and smaller culvert boxes. Stream reaches located close to a river tributary had the highest connectivity values, and areas modeled as good habitats were linked near riparian and watershed areas with high density for both species as well as culvert boxes with a high openness ratio. Artifacts such as steep banks, concrete embankments, and adjacent roads were found to degrade the riparian connectivity of wildlife. These outcomes can be used to identify suitable riparian wildlife habitats of mammals, to evaluate lateral connectivity of riparian corridors for mammals, and to develop criteria for river conservation and restoration in urbanizing areas and developing countries.