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Do blue-green roofs yield optimal thermal performance? Synergy analysis of the combination of green roofs and water retention layer

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JOURNAL OF BUILDING ENGINEERING 2024年 95卷

作者： Yun, Seok Hwan Kim, Eun Sub Lee, Dong Kun Piao, Zheng Gang Kim, Sang Hyuck Kim, Nayoun Hwang, Hyemee Park, Seunghwan Bae, Chaeyoung Kim, Ji Yeon Piao, Yong Nam, Ye Kyung Heo, Sujung Lee, Jaehong Kang, Hyewon Jeon, Yoonho Nam, Sangwook Natl Inst Environm Studies Ctr Climate Change Adaptat Tsukuba Japan Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul South Korea Seoul Natl Univ Integrated Major Smart City Global Convergence Pro Seoul South Korea Seoul Natl Univ Specialized Grad Sch Intelligent Ecosci Seoul South Korea Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Seoul South Korea Korea Inst Civil Engn & Bldg Technol Dept Bldg Energy Res Goyang Si Gyeonggi Do South Korea Suwon Res Inst Dept Urban Planning & Design Res Suwon South Korea SK Forest Smart Green Solut Team Seoul South Korea Cheongju Univ Sch Business Adm Cheongju Chungcheongbuk South Korea

Blue-green roofs can potentially enhance the outdoor thermal environment in urban areas and reduce indoor energy consumption. By integrating a water retention layer with green roofs, bluegreen roofs maximize environmental benefits through rainwater storage and increased evapotranspiration. This study evaluates the thermal performance of blue-green roofs during summer and examines their potential for microclimate improvement and energy savings. The study investigates the individual and interactive effects of the blue-green roof components by measuring the upper and lower surface temperatures with incremental application of soil, blue, and green layers and analyzing their synergistic benefits. The results indicate that blue-green roofs exhibited a cooling effect of up to 7.5 degrees C on the upper surface temperature and up to 17.4 degrees C on the lower surface temperature, showing the greatest potential for improving indoor and outdoor thermal comfort. The synergistic effect of the blue-green roof was -0.80 degrees C on the upper surface and +1.59 degrees C on the lower surface. This research provides an in-depth investigation into the thermal performance of blue-green roofs in both indoor and outdoor spaces, highlighting their synergistic effects through incremental application. This contributes to climate-responsive architectural design and practices aimed at enhancing energy efficiency in building retrofitting for hot climates.

关键词： Thermal performance Blue green roof Water retention layer Building energy saving Cooling

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Comparison between point cloud and mesh models using images from an unmanned aerial vehicle

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MEASUREMENT 2019年 138卷 461-466页

作者： Park, Haekyung Lee, Dongkun Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul 08826 South Korea Seoul Natl Univ Res Inst Agr & Life Sci Dept Landscape Architecture & Rural Syst Engn Seoul 08826 South Korea

Structure from motion (SfM) is a well-known algorithm used for the generating of three-dimensional (3D) spatial information using images. The objective of this study is to compare the measurements of objects ascertained from point cloud and mesh models derived from the SfM algorithm. In particular, we analyze a single tree to determine the correlation between the number of acquired images from the UAVs and the object measurement for each model. The results indicate that the number of images does not have a critical impact on surveys and the point cloud is approximately 2% more accurate than mesh models for individual tree measurement. Our results will be useful in terms of selecting the data acquisition method as well as the data itself for measuring objects based on SfM 3D data. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： SfM 3D spatial data Tree measurement Point cloud Mesh Unmanned aerial vehicles

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Forest landscape connectivity to prioritize afforestation in urban ecosystems: Seoul as a case study

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URBAN FORESTRY & URBAN GREENING 2023年 90卷

作者： Jin, Lin Song, Youngkeun Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul 08826 South Korea Seoul Natl Univ Integrated Major Smart City Global Convergence Seoul 08826 South Korea Seoul Natl Univ Grad Sch Environm Studies Dept Environm Design Seoul 08826 South Korea Seoul Natl Univ 1 Gwanak Ro Seoul 08826 South Korea

Forest landscape connectivity is a key indicator that reflects the quality and function of the ecological environment. In urban ecosystems, analysis frameworks are needed to prioritize and optimize afforestation projects that maintain and increase forest landscape connectivity to help mitigate the increasing fragmentation of urban habitats, coordinate the relationship between urban development and urban ecosystem services, and guide decision making processes. The objective of this study is to identify forest patches that are most worth conserving and small patches that make the most significant contribution to landscape connectivity after their transformation into forest patches in a high-density city. We conducted a case study in Seoul, South Korea, where we initially quantified the landscape connectivity changes from 2001 to 2018 using the probability of connectivity (PC) and integral index of connectivity indices. Subsequently, we calculated the importance of each forest patch for four different years and ranked the potential contribution of each patch based on data from 2018 using the delta values for PC index (dPC). Our results showed that forest landscape connectivity in Seoul increased significantly from 2001 to 2018. In all four years, the ten forest patches with the highest dPC values remained nearly unchanged and were large in size;however, the individual area of each patch was not strictly related to its importance for connectivity. Based on these findings, we further examined the potential effect that the afforestation of habitat patches smaller than 20 ha would have on the overall forest landscape connectivity in Seoul. We also identified the 50 most important patches for afforestation using six land use and land cover types to provide a guide for effective afforestation efforts in Seoul. We expect that this study could enhance the effectiveness of habitat connectivity intervention while providing a realistic strategy for ecological afforestation planni

关键词： Afforestation Ecological connectivity Ecological network Urban forest Graph theory

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Evaluating Earthwork Volume Index (Evi) for Effective Eia with Correlation to Landslide Risk

SSRN

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SSRN 2023年

作者： Heo, Sujung Lee, Dong Kun Park, Sangjin Kim, Eunsub Kim, Ho Gul Lee, Jongook Fedorov, Nikolai Park, Hansu Interdisciplinary Program and Life Science Seoul National University Seoul Korea Republic of Korea Institute of Public Administration Korea Republic of Department of Landscape Architecture and Urban Planning Cheongju University Cheongju Korea Republic of Sustainable Development Team Schneider Electric Korea Republic of School of Earth and Environmental Science Seoul National University Seoul Korea Republic of

The Earthwork Volume Index (EVI) serves as a metric for measuring and representing terrain changes in specific areas, and its importance in environmental impact assessments (EIAs) is growing. Utilizing this index requires understanding the range of appropriate standards to take necessary actions during development projects. Excessive human development leads to an increase in the EVI, and this EVI can serve as a metric for disaster assessment resulting from human development. This study aims to assess the impact of urban landslides, which can cause substantial human casualties, by identifying correlations with EVI and determining its threshold values. Initially, EIA documents for urban development were reviewed to investigate the EVI of various projects from the 2007 to 2022, and areas with significant landform changes were selected as the study sites, Busan city in Rep. of Korea. Subsequently, landslide inventory data obtained from interviews with Busan municipal authorities and literature reviews were analyzed using the Random Forest (RF) algorithm, alongside selected disaster impact variables. The model's high accuracy was confirmed through the validation of the AUC value (0.906), and the importance of each environmental impact variable was determined. The EVI values were classified into five levels using the Natural Jenkin method in ArcGIS 10.8.6. It was observed that the risk of landslides increases dramatically in areas with the highest level of EVI, specifically those with an EVI of 12 or above. Overall, the research's innovation lies in its pioneering efforts to establish EVI as a crucial factor in EIA processes, providing a new perspective on the correlation between urban development, terrain changes, and landslide occurrences, and offering practical insights for effective disaster prevention strategies in urban areas. © 2023, The Authors. All rights reserved.

关键词： Landslides

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BESSv2.0: A satellite-based and coupled-process model for quantifying long-term global land-atmosphere fluxes

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REMOTE SENSING OF ENVIRONMENT 2023年第1期295卷

作者： Li, Bolun Ryu, Youngryel Jiang, Chongya Dechant, Benjamin Liu, Jiangong Yan, Yulin Li, Xing Seoul Natl Univ Res Inst Agr & Life Sci Seoul South Korea Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Seoul South Korea Univ Illinois Coll Agr Consumer & Environm Sci Urbana IL USA German Ctr Integrat Biodivers Res iDiv Leipzig Germany Univ Leipzig Leipzig Germany Seoul Natl Univ Interdisciplinary Program Agr & Forest Meteorol Seoul South Korea

Recent remote-sensing-based global carbon, water and energy budgets over land still include considerable uncertainties. Most existing flux products of terrestrial carbon, water and energy components were developed individually, despite the inherently coupled processes among them. In this study, we present a new set of global daily surface downwelling shortwave radiation (SW), net radiation (Rnet), evapotranspiration (ET), gross primary productivity (GPP), terrestrial ecosystem respiration (TER) and net ecosystem exchange (NEE) datasets at 0.05 degrees resolutions from 1982 to 2019, by improving a satellite-based and coupled-process model-the Breathing Earth System Simulator (BESS). The new version of BESS (v2.0) integrated a newly developed ecosystem respiration module, an optimality-based maximum carboxylation rate (Vcmax) model, and extended the temporal coverage of flux datasets from 1982 to 2019. We evaluated BESS products against the FLUXNET2015 dataset at the site scale, and against several remote sensing and/or machine learning products on a global scale. At the site scale, BESS products agreed well with FLUXNET measurements, capturing 84%, 53%, 65%, 51% and 31% of daily variation in Rnet, ET, GPP, TER and NEE, respectively. Interannual variation in BESS NEE showed relatively low consistency with the FLUXNET measurements, while the rest fluxes explained approximately half of the interannual variation. On a global scale, we found marked discrepancies in spatio-temporal patterns between BESS and several benchmark products. Over the period 1982-2019, BESSv2.0 estimated the mean annual global Rnet, ET, GPP, TER and NEE to be 340.97 & PLUSMN;5.22 ZJ yr- 1 (mean & PLUSMN;1 SD), 67.67 & PLUSMN;0.71 103 km3 yr- 1, 125.74 & PLUSMN;5.95 Pg C yr- 1 (P < 0.01) by-0.05 103 km3 yr-2 for ET, by 0.52 Pg C yr-2 for GPP, by 0.28 Pg C yr-2 for TER, and by-0.25 Pg C yr-2 for NEE. We further evaluated various coupled processes derived by BESS in terms of functional properties (i.

关键词： Carboxylation

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Analysis of Land Use and Land Cover Change Using Time-Series Data and Random Forest in North Korea

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REMOTE SENSING 2021年第17期13卷 3501页

作者： Piao, Yong Jeong, Seunggyu Park, Sangjin Lee, Dongkun Seoul Natl Univ Res Inst Agr Life Sci Seoul 08826 South Korea Natl Inst Biol Resources Anim Resources Div Incheon 22689 South Korea Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul 08826 South Korea Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Seoul 08826 South Korea

North Korea being one of the most degraded forests globally has recently been emphasizing in forest restoration. Monitoring the trend of forest restoration in North Korea has important reference significance for regional environmental management and ecological security. Thus, this study constructed and analyzed a time-series land use land cover (LULC) map to identify the LULC changes (LULCCs) over extensive periods across North Korea and understand the forest change trends. The analysis of LULC used Landsat multi-temporal image and Random Forest algorithm on Google Earth Engine(GEE) from 2001 to 2018 in North Korea. Through the LULCC detection technique and consideration of the cropland change relation with elevation, the forest change in North Korea for 2001-2018 was evaluated. We extended the existing sampling methodology and obtained a higher overall accuracy (98.2% +/- 1.6%), with corresponding kappa coefficients (0.959 +/- 0.037), and improved the classification accuracy in cropland and forest cover. Through the change detection and spatial analysis, our research shows that the forests in the southern and central regions of North Korea are undergoing restoration. The sampling method we extended in this study can effectively and reliably monitoring the change trend of North Korea forests. It also provides an important reference for the regional environmental management and ecological security in North Korea.

关键词： forest change trend terrace field North Korea random forest (RF) Google Earth Engine (GEE)

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Integrating restorative perception into urban street planning: A framework using street view images, deep learning, and space syntax

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CITIES 2024年 147卷

作者： Wu, Yunfei Liu, Qiqi Hang, Tian Yang, Yihong Wang, Yijun Cao, Lei Nanjing Forestry Univ Dept Art & Design Nanjing Peoples R China Nanjing Forestry Univ Dept Landscape Architecture Nanjing Peoples R China Seoul Natl Univ Grad Sch Environm Studies Dept Environm Design Seoul South Korea Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul South Korea Seoul Natl Univ Integrated Major Smart City Global Convergence Seoul South Korea Sanjiang Univ Dept Arts Nanjing Peoples R China 159 Longpan Rd Nanjing 210037 Peoples R China

Existing urban street planning often neglects human perception despite being designed for human utility. Therefore, exploring the relationship between urban street planning and human perception, especially restorative perception, is crucial for sustainable urban planning. In this study, we analyzed restorative perception of urban streets among different population groups and accessibility of urban streets using Baidu Street View Images, deep learning, and space syntax. Furthermore, we clarified the impacts of various street elements on restorative perception using correlation and ridge regression analyses. Based on restorative perception and accessibility coupling assessment, streets were classified into four types, identifying "inefficient segments" and "prioritized segments". The results showed that: 1) the level of restorative perception of streets in Nanjing was relatively limited and exhibited variation across different population groups;2) the impacts of different street elements on restorative perception varied, with trees having the highest positive impact (beta = 0.378), while walls had the greatest negative impact (beta = - 0.182);and 3) "prioritized segments" and "inefficient segments" represented 33.92 % and 17.96 %, respectively, indicating the urgent demand for streets planning and renewal. These findings can offer targeted recommendations for enhancing restorative environment of urban streets and identifying priority areas for urban street planning.

关键词： Restorative perception Urban street planning Street view image Deep learning Space syntax

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The magnitude and causes of edge effects on soil organic carbon stocks within and across urban to rural forest patches

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landscape AND URBAN PLANNING 2021年 215卷 104223-104223页

作者： Bae, Jeehwan Ryu, Youngryel Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul South Korea Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Coll Agr & Life Sci Seoul 151921 South Korea Seoul Natl Univ Integrated Major Smart City Global Convergence Seoul South Korea

landscape fragmentation has created large areas of forest edge. Understanding how soil organic carbon (SOC) stocks within forest edges respond to fragmentation is essential to assess carbon budgets;however, the causes and magnitude of edge effects on SOC stocks have been poorly characterized. Here, we quantify the edge effects on SOC stocks within and across urban to rural forest patches from three fragmented urban forests to a large patch of rural forest. The SOC stocks within 20 m of the rural forest edge (1.86 kgC m(-2)) is on average 80% lower than the interiors of rural forest (10.47 kgC m(-2)). We found that biotic factors, including annual litterfall mass (R-2 > 0.94), peak leaf area index (R-2 > 0.92), and fine-root mass density (R-2 > 0.77), explained the spatial variation in SOC stocks within the rural forest. In urban forests, human activities at forest edges led to contrasting edge effects on SOC stocks, for instance, the SOC stocks at the east edges (4.74 kgC m(-2)) were 56% greater than at the west edges (3.03 kgC m(-2)) explained by the adjacent land uses (e.g., paved roads vs. non-paved soils) and in-situ litterfall management. We also found significant differences in summer soil temperature (Delta T-S > 2.8 degrees C) and soil moisture (Delta VWC > 0.05 m(3) m(-3)) between the east and west forest edges. Our results reveal that the factors responsible for the edge effects on SOC stocks in rural forests are biotic factors, while heterogeneous human activities at the local scale lead to complex edge effects on urban forest SOC stocks.

关键词： Forest fragmentation Edge effect Forest edge Soil organic carbon Urban soil Urban forest

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Quantifying the Effects of Green-Gray Infrastructure at the Urban Catchment Scale Under Various Rainfall Patterns

SSRN

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SSRN 2022年

作者： Bae, Chaeyoung Lee, Dongkun Sohn, Wonmin Interdisciplinary Program in Landscape Architecture & Integrated Major in Smart City Global Convergence Seoul National University Korea Republic of College of Agriculture and Life Science Seoul National University Korea Republic of School of Planning Design and Construction Michigan State University United States

This study evaluated several green-gray infrastructure strategies under various rainfall patterns to support decision-making on flood management in urbanized catchments. The evaluation framework based on a simulation was applied to the target study area under 20 design storms with different return periods, durations, and time distributions. Time-dependent resilience assessment was simulated by real flood events. The main conclusions were: 1) Among green infrastructure (GI) practices, the performance of green roofs (GRs) was better than that of permeable pavements (PPs);2) all three hydrological performance indexes decreased as the return period of a storm increased, but the reduction patterns differed depending on the quantile and duration;3) the implementation of GI practices should be combined with the improvement of gray infrastructure to achieve optimal flood mitigation under extreme rainfall events. The results highlight the importance and necessity of detailed comparisons of various options that can aid the decision-making process governing green-gray infrastructure planning. © 2022, The Authors. All rights reserved.

关键词： Floods

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Reconstruction of a Long-term spatially Contiguous Solar-Induced Fluorescence (LCSIF) over 1982-2022

arXiv

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arXiv 2023年

作者： Fang, Jianing Lian, Xu Ryu, Youngryel Jeong, Sungchan Jiang, Chongya Gentine, Pierre Department of Earth and Environmental Engineering Columbia University New YorkNY10027 United States Interdisciplinary Program in Landscape Agriculture Seoul National University Seoul Korea Republic of Integrated Major in Smart City Global Convergence Seoul National University Seoul Korea Republic of Department of Landscape Architecture and Rural Systems Engineering Seoul National University Seoul Korea Republic of Department of Natural Resources and Environmental Sciences University of Illinois at Urbana-Champaign United States

Satellite-observed solar-induced chlorophyll fluorescence (SIF) is a powerful proxy for diagnosing the photosynthetic characteristics of terrestrial ecosystems. Despite the increasing spatial and temporal resolutions of these satellite retrievals, records of SIF are primarily limited to the recent decade, impeding their application in detecting long-term dynamics of ecosystem function and structure. In this study, we leverage the two surface reflectance bands (red and near-infrared) available both from Advanced Very High-Resolution Radiometer (AVHRR, 1982-2022) and MODerate-resolution Imaging Spectroradiometer (MODIS, 2001-2022). Importantly, we calibrate and orbit-correct the AVHRR bands against their MODIS counterparts during their overlapping period. Using the long-term bias-corrected reflectance data, a neural network is then built to reproduce the Orbiting Carbon Observatory-2 SIF using AVHRR and MODIS, and used to map SIF globally over the entire 1982-2022 period. Compared with the previous MODIS-based CSIF product relying on four reflectance bands, our two-band-based product has similar skill but can be advantageously extended to the bias-corrected AVHRR period. Further comparison with three widely used vegetation indices (NDVI, kNDVI, NIRv;all based empirically on red and near-infrared bands) shows a higher or comparable correlation of LCSIF with satellite SIF and site-level GPP estimates across vegetation types, ensuring a greater capacity of LCSIF for representing terrestrial photosynthesis. Globally, LCSIF-AVHRR shows an accelerating upward trend since 1982, with an average rate of 0.0025 mW m-2 nm-1 sr-1 per decade during 1982-2000 and 0.0038 mW m-2 nm-1 sr-1 per decade during 2001-2022. Previous greening hotspots of India and China since 2000 are also identified as hotspots for enhanced photosynthesis. Our LCSIF data provide opportunities to better understand the long-term dynamics of ecosystem photosynthesis and their underlying driving processes. © 20

关键词： Photosynthesis

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