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International tourists' destination choice differences according to Plog's personality types: analyzing the case of Mongolia based on the recreation opportunity spectrum

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INTERNATIONAL JOURNAL OF URBAN SCIENCES 2020年第4期24卷 485-515页

作者： Bayarsaikhan, Tsolmon Kim, Sang-Tae Gim, Tae-Hyoung Tommy Seoul Natl Univ Grad Sch Environm Studies Seoul South Korea Korea Culture & Tourism Inst Stat & Evaluat Ctr Seoul South Korea Seoul Natl Univ Grad Sch Environm Studies Gwanak Ro 1Bldg 82Room 222 Seoul 08826 South Korea Seoul Natl Univ Interdisciplinary Program Landscape Architecture Gwanak Ro 1Bldg 82Room 222 Seoul 08826 South Korea

In the international tourism market, the number of arrivals in Asian regions is increasing every year, and that of foreign tourists in Mongolia, a new tourism market, is also rapidly rising. This study tests differences in the destination choice among international tourists visiting Mongolia using the Plog's personality model. It classifies Mongolia into several regions using the recreation opportunity spectrum and then tests whether Plog's personality types significantly affect the destination choice. Analytical results based on the data of an on-site survey of 406 U.S., South Korean, and Russian tourists recruited at eleven representative destinations present that while the tourists are categorized into psychocentric, midcentric, and allocentric types, allocentric tourists are the largest in number. Also, Plog's personality types are found to differentiate tourist destination choices when socio-demographic and travel-related confounding variables are controlled for. Allocentric tourists are likely to visit primitive areas, whereas psychocentrics tend to visit urban tourist attractions. Accordingly, this study confirms the validity of the recreation opportunity spectrum and Plog's personality types, using the case of Mongolia with unique natural, urban, and tourism settings. Also, tourism service providers and marketers may benefit from the segmentation technique and analytical results suggested in this study in order to assess the needs of their visitors.

关键词： Plog's personality model recreation opportunity spectrum international tourism destination choice Mongolia

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The effect of built environments on the walking and shopping behaviors of pedestrians;A study with GPS experiment in Sinchon retail district in Seoul, South Korea

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CITIES 2019年 89卷 1-13页

作者： Hahm, Yeankyoung Yoon, Heeyeun Choi, Yunwon Seoul Natl Univ Coll Agr & Life Sci Dept Landscape Architecture & Rural Syst Engn 1 Gwanak Ro Seoul 08826 South Korea Seoul Natl Univ Res Inst Agr & Life Sci 1 Gwanak Ro Seoul 08826 South Korea Seoul Natl Univ Interdisciplinary Program Landscape Architecture 1 Gwanak Ro Seoul 08826 South Korea

With this research, we aim to identify built environmental components of retail districts that affect pedestrian behaviors and influence their shopping behavior. We conducted GPS experiments to observe visitors' choice of walking route-pedestrian volume and visit duration-and the questionnaire survey to obtain their records of shopping on where and how much they spent in the Sinchon retail district of Seoul, South Korea. We then employed a path analysis to assess the causal relationship between the built environment, walking behavior, and shopping behavior. We found that pedestrians prefer streets with safety from vehicles, high design quality;higher hierarchy, centrality, and provision of resting places or other street amenities;and that all of these variables also increase pedestrian's visit duration and induce spending at stores on the street. This study would provide design guidelines to municipalities or private retailers looking to revitalize retail districts through environmental improvements.

关键词： Built environment Retail district Walking behavior Shopping behavior Path analysis Global Positioning System (GPS)

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Is Water Pricing Policy Adequate to Reduce Water Demand for Drought Mitigation in Korea?

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WATER 2019年第6期11卷 1256页

作者： Park, Haekyung Lee, Dong Kun 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

Korea experienced an unexpected drought in the southern Seoul metropolitan area from 2015 to 2017. After that, the Korean government has been drafting various policies to mitigate the effects of drought. However, these are primarily long-term drought policies, such as reservoir expansion. A comprehensive water demand reduction policy, which considers both short-term and long-term droughts, is also required. To confirm the effectiveness of the water pricing policy in Korea, we estimated the water demand reduction volume during droughts by assuming the drought and water pricing policy. We used two models for simulation: the severe drought area prediction (SDAP) model and the SD (system dynamics) model. The results showed the water demand reduction by price would not be significantly effective in Korea. We indicated that the effectiveness of policies could differ in each situation so that appropriate policies are needed for each country. This discussion could provide policy implications for other countries being at risk of droughts as well as the Korean government. Furthermore, we discussed non-price water policies that could be implemented in combination with the pricing policy in cases where the water pricing policy does not effectively reduce water demand.

关键词： water pricing water demand reduction machine learning system dynamics simulation drought mitigation

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Persistent global greening over the last four decades using novel long-term vegetation index data with enhanced temporal consistency

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REMOTE SENSING OF ENVIRONMENT 2024年 311卷

作者： Jeong, Sungchan Ryu, Youngryel Gentine, Pierre Lian, Xu Fang, Jianing Li, Xing Dechant, Benjamin Kong, Juwon Choi, Wonseok Jiang, Chongya Keenan, Trevor F. Harrison, Sandy P. Prentice, Iain Colin Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul South Korea Seoul Natl Univ Integrated Major Smart City Global Convergence Seoul South Korea Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Seoul South Korea Columbia Univ Dept Earth & Environm Engn New York NY USA Columbia Univ Ctr Learning Earth Artificial intelligence & Phys New York NY USA Seoul Natl Univ Res Inst Agr & Life Sci Seoul South Korea German Ctr Integrat Biodivers Res iDiv Leipzig Germany Univ Leipzig Leipzig Germany Yale Univ Yale Sch Environm New Haven CT 06511 USA Univ Illinois Inst Sustainabil Energy & Environm Agroecosyst Sustainabil Ctr Urbana IL USA Univ Illinois Coll Agr Consumer & Environm Sci Dept Nat Resources & Environm Sci Urbana IL USA Lawrence Berkeley Natl Lab Climate & Ecosyst Sci Div Berkeley CA USA Univ Calif Berkeley Dept Environm Sci Policy & Management Berkeley CA USA Univ Reading Geog & Environm Sci Reading RG6 6AH England Imperial Coll London Georgina Mace Ctr Living Planet Dept Life Sci Silwood Pk CampusBuckhurst Rd Ascot SL5 7PY England Tsinghua Univ Minist Educ Key Lab Earth Syst Modelling Dept Earth Syst Sci Beijing 100084 Peoples R China

Advanced Very High-Resolution Radiometer (AVHRR) satellite observations have provided the longest global daily records from 1980s, but the remaining temporal inconsistency in vegetation index datasets has hindered reliable assessment of vegetation greenness trends. To tackle this, we generated novel global long-term Normalized Difference Vegetation Index (NDVI) and Near-Infrared Reflectance of vegetation (NIRv) datasets derived from AVHRR and Moderate Resolution Imaging Spectroradiometer (MODIS). We addressed residual temporal inconsistency through three-step post processing including cross-sensor calibration among AVHRR sensors, orbital drifting correction for AVHRR sensors, and machine learning-based harmonization between AVHRR and MODIS. After applying each processing step, we confirmed the enhanced temporal consistency in terms of detrended anomaly, trend and interannual variability of NDVI and NIRv at calibration sites. Our refined NDVI and NIRv datasets showed a persistent global greening trend over the last four decades (NDVI: 0.0008 yr(-1);NIRv: 0.0003 yr(-1)), contrasting with those without the three processing steps that showed rapid greening trends before 2000 (NDVI: 0.0017 yr(-1);NIRv: 0.0008 yr(-1)) and weakened greening trends after 2000 (NDVI: 0.0004 yr(-1);NIRv: 0.0001 yr(-1)). These findings highlight the importance of minimizing temporal inconsistency in long-term vegetation index datasets, which can support more reliable trend analysis in global vegetation response to climate changes.

关键词： AVHRR MODIS NDVI NIRv Greening trend Orbital drift

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How has COVID-19 impacted the economic resilience of retail clusters?: Examining the difference between neighborhood-level and district-level retail clusters

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CITIES 2023年 140卷 104457页

作者： Che, Jihyun Lee, Jae Seung Kim, Saehoon Seoul Natl Univ Interdisciplinary Program Landscape Architecture 1 Gwanak Ro Seoul 08826 South Korea Seoul Natl Univ Grad Sch Environm Studies Dept Environm Design Urban Design Concentrat 1 Gwanak Ro Seoul 08826 South Korea Seoul Natl Univ Environm Planning Inst 1 Gwanak Ro Seoul 08826 South Korea Seoul Natl Univ Integrated Major Smart City Global Convergence 1 Gwanak Ro Seoul 08826 South Korea Seoul Natl Univ Grad Sch Environm Studies 1 Gwanak Ro Seoul 08826 South Korea

The spread of COVID-19 greatly restricted physical and economic activities in global cities due to growing fears of infection and lockdown policies. Accordingly, the transfer of shopping activities from traditional markets to e-commerce has accelerated. Urban retail has substantially declined by competing with these disrupting factors, but resilience capabilities are known to vary by scale and regional characteristics. This study identifies which types of retail clusters were more resilient to the economic shock caused by the pandemic. This research focuses on the changes in online and in-store sales and how retailers recovered differently at the neighborhood and district levels in 2019 and 2020. This research compares the resilience of two types of retail clusters by calcu-lating the loss of resilience and online adaptivity. The findings suggest that neighborhood-level retail areas were more resilient and bounced back in sales at a faster rate than district-level retail areas during the pandemic. These findings suggest that retail clusters are more resilient if they have steady populations and low-rent loads and can accommodate online shopping. The study contributes theoretical insights into how sales have changed and how e-commerce has increased the resilience of retail clusters throughout the pandemic by examining in -store and online sales.

关键词： COVID-19 Retail clusters Retail resilience Credit card sales data In-store and online sales

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Gap-filling approaches for eddy covariance methane fluxes: A comparison of three machine learning algorithms and a traditional method with principal component analysis

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GLOBAL CHANGE BIOLOGY 2020年第3期26卷 1499-1518页

作者： Kim, Yeonuk Johnson, Mark S. Knox, Sara H. Black, T. Andrew Dalmagro, Higo J. Kang, Minseok Kim, Joon Baldocchi, Dennis Univ British Columbia Inst Resources Environm & Sustainabil Vancouver BC Canada Univ British Columbia Dept Earth Ocean & Atmospher Sci Vancouver BC Canada Univ British Columbia Dept Geog Vancouver BC Canada Univ British Columbia Fac Land & Food Syst Vancouver BC Canada Univ Cuiaba Environm Sci Grad Program Cuiaba Brazil Natl Ctr AgroMeteorol Seoul South Korea Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Seoul South Korea Seoul Natl Univ Interdisciplinary Program Agr & Forest Meteorol Seoul South Korea Univ Calif Berkeley Dept Environm Sci Policy & Management Berkeley CA 94720 USA

Methane flux (FCH4) measurements using the eddy covariance technique have increased over the past decade. FCH4 measurements commonly include data gaps, as is the case with CO2 and energy fluxes. However, gap-filling FCH4 data are more challenging than other fluxes due to its unique characteristics including multidriver dependency, variabilities across multiple timescales, nonstationarity, spatial heterogeneity of flux footprints, and lagged influence of biophysical drivers. Some researchers have applied a marginal distribution sampling (MDS) algorithm, a standard gap-filling method for other fluxes, to FCH4 datasets, and others have applied artificial neural networks (ANN) to resolve the challenging characteristics of FCH4. However, there is still no consensus regarding FCH4 gap-filling methods due to limited comparative research. We are not aware of the applications of machine learning (ML) algorithms beyond ANN to FCH4 datasets. Here, we compare the performance of MDS and three ML algorithms (ANN, random forest [RF], and support vector machine [SVM]) using multiple combinations of ancillary variables. In addition, we applied principal component analysis (PCA) as an input to the algorithms to address multidriver dependency of FCH4 and reduce the internal complexity of the algorithmic structures. We applied this approach to five benchmark FCH4 datasets from both natural and managed systems located in temperate and tropical wetlands and rice paddies. Results indicate that PCA improved the performance of MDS compared to traditional inputs. ML algorithms performed better when using all available biophysical variables compared to using PCA-derived inputs. Overall, RF was found to outperform other techniques for all sites. We found gap-filling uncertainty is much larger than measurement uncertainty in accumulated CH4 budget. Therefore, the approach used for FCH4 gap filling can have important implications for characterizing annual ecosystem-scale methane budgets, the acc

关键词： artificial neural network comparison of gap-filling techniques eddy covariance machine learning marginal distribution sampling methane flux random forest support vector machine

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Correction to: Simultaneous detection of four lily‑infecting viruses by a multiplex RT‑PCR assay

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Journal of General Plant Pathology 2021年第4期87卷 225-225页

作者： Lim, Mi Sang Min, Dong Joo Hong, Jin Sung Choi, Sun Hee Department of Horticulture Biotechnology and Landscape Architecture Seoul Women’s University Seoul Korea Interdisciplinary Program in Smart Agriculture Kangwon National University Chuncheon Korea

A correction to this paper has been published: https://***/10.1007/s10327-021-01008-7

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Evaluation of four image fusion NDVI products against in-situ spectral-measurements over a heterogeneous rice paddy landscape

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AGRICULTURAL AND FOREST METEOROLOGY 2021年 297卷 108255-108255页

作者： Kong, Juwon Ryu, Youngryel Huang, Yan Dechant, Benjamin Houborg, Rasmus Guan, Kaiyu Zhu, Xiaolin Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul South Korea Seoul Natl Univ Dept Landscape Architecture & Rural Syst Engn Seoul South Korea Seoul Natl Univ Res Inst Agr & Life Sci Seoul South Korea Planet Labs San Francisco CA USA Univ Illinois Dept Nat Resources & Environm Sci Urbana IL USA Univ Illinois Natl Ctr Supercomp Applicat Urbana IL USA Aspiring Universe Corp Champaign IL USA Hong Kong Polytech Univ Dept Land Surveying & Geoinformat Hong Kong Peoples R China Seoul Natl Univ Integrated Major Smart City Global Convergence Seoul South Korea

Satellite image fusion methods that improve spatial and temporal resolution have significant potential to advance understanding of ecosystem dynamics in space and time. However, systematic evaluations of image fusion methods against in situ spectral data are lacking. Here, we used a suite of in situ spectral data collected at 60 elementary sampling units (10 x 10 m) covering 15 Landsat pixel (30 x 30 m) plots and one Moderate Resolution Imaging Spectroradiometer (MODIS) pixel (250 x 250 m) throughout the entire growing season in a heterogeneous rice paddy landscape to evaluate four state-of-the-art image fusion NDVI products. They include the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), Flexible Spatiotemporal DAta Fusion (FSDAF), SaTellite dAta IntegRation (STAIR), and the CubeSat Enabled Spatio-Temporal Enhancement Method (CESTEM);the former three blended Landsat and MODIS data, whereas the latter combined CubeSats, Landsat, and MODIS observations. All fusion products showed strong linear relationships against in situ data when combining all spatial and temporal observations (R-2: 0.73 to 0.93) although there were partly negative biases (-1% to -9%). These biases resulted from forcing data to image fusion algorithms, such as Landsat (-4%) and MODIS (-7%). Performance difference between fusion methods were considerably larger for spatial than for temporal variation. Furthermore, Landsat NDVI explained only 17-22% of spatial variation against in situ spectral data, which can be translated into weak performance of image fusion products to predict spatial variability in NDVI. Image fusion products that relied on spatial interpolation showed large biases (-15% to -30%) for a vegetation plot surrounded by mixed land cover plots. Our results highlight key sources of uncertainty and will be instrumental in improving satellite image fusion methods to monitor land surface phenology in space and time.

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Who lives in and owns cold homes? A case study of fuel poverty in Seoul, South Korea

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ENERGY RESEARCH & SOCIAL SCIENCE 2019年 47卷 202-214页

作者： You, Youngsoo Kim, Saehoon Seoul Natl Univ Interdisciplinary Program Landscape Architecture Grad Sch Environm Studies 1 Gwanak Ro Seoul 08826 South Korea Seoul Natl Univ Dept Landscape Architecture Urban Design Concentrat Grad Sch Environm Studies 1 Gwanak Ro Seoul 08826 South Korea Seoul Natl Univ Environm Planning Inst Grad Sch Environm Studies 1 Gwanak Ro Seoul 08826 South Korea

The study aims to identify residence groups that are highly vulnerable to fuel poverty in the urban area of a South Korean city. Thereby, the paper emphasizes that fuel poverty problems occur in different ways according to the social and spatial contexts and thus need a more contextualized policy approach beyond the simplistic criteria of household income and heating cost. To fully capture the meaning of cold homes, an empirical dataset of thermal efficiency of individual dwellings and actual heating in a residential area in Seoul, South Korea is examined along with the tenure type and the ownership attributes. The analyses reveal that the amount of actual heating energy consumption did not show any clear relation with the thermal efficiency of housing or the tenure type. Additionally, considerably inefficient dwellings like old, detached houses are occupied by elderly owners who often lack both the financial capability and intention to properly maintain their properties. The result indicates that people who are living in cold homes are not always confined to poor residents living in rented homes. The study proposes some new types of potential fuel poverty based on the analyses of thermal efficiency and heating patterns by dwellings.

关键词： Fuel poverty Thermal efficiency Actual heating consumption Tenure type Ownership Seoul

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Urban Forest Growth and Gap Dynamics Detected by Yearly Repeated Airborne Light Detection and Ranging (LiDAR): A Case Study of Cheonan, South Korea

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REMOTE SENSING 2019年第13期11卷 1551-1551页

作者： Choi, Heejoon Song, Youngkeun Jang, Youngwoon Seoul Natl Univ Interdisciplinary Program Landscape Architecture Seoul 08826 South Korea Seoul Natl Univ Grad Sch Environm Studies Dept Landscape Architecture Seoul 08826 South Korea Samah Aerial Survey CO Dept Contents Goyang 10442 South Korea

Understanding forest dynamics is important for assessing the health of urban forests, which experience various disturbances, both natural (e.g., treefall events) and artificial (e.g., making space for agricultural fields). Therefore, quantifying three-dimensional changes in canopies is a helpful way to manage and understand urban forests better. Multitemporal airborne light detection and ranging (LiDAR) datasets enable us to quantify the vertical and lateral growth of trees across a landscape scale. The goal of this study is to assess the annual changes in the 3-D structures of canopies and forest gaps in an urban forest using annual airborne LiDAR datasets for 2012-2015. The canopies were classified as high canopies and low canopies by a 5 m height threshold. Then, we generated pixel- and plot-level canopy height models and conducted change detection annually. The vertical growth rates and leaf area index showed consistent values year by year in both canopies, while the spatial distributions of the canopy and leaf area profile (e.g., leaf area density) showed inconsistent changes each year in both canopies. In total, high canopies expanded their foliage from 12 m height, while forest gap edge canopies (including low canopies) expanded their canopies from 5 m height. Annual change detection with LiDAR datasets might inform about both steady growth rates and different characteristics in the changes of vertical canopy structures for both high and low canopies in urban forests.

关键词： airborne LiDAR annual repeated LiDAR canopy growth forest disturbance canopy structure change detection

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