Journal of the Korean Institute of Landscape Architecture
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v.37
no.3
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pp.54-60
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2009
The purpose of this study is to analyze the impacts of three-dimensional land cover on changing urban air temperatures and to explore some strategies of urban landscaping towards mitigation of heat build-up. This study located study spaces within a diameter of 300m around 24 Automatic Weather Stations(AWS) in Seoul, and collected data of diverse variables which could affect summer energy budgets and air temperatures. The study also selected reflecting study objectives 6 smaller-scale spaces with a diameter of 30m in Chuncheon, and measured summer air temperatures and three-dimensional land cover to compare their relationships with results from Seoul's AWS. Linear regression models derived from data of Seoul's AWS revealed that vegetation volume, greenspace area, building volume, building area, population density, and pavement area contributed to a statistically significant change in summer air temperatures. Of these variables, vegetation and building volume indicated the highest accountability for total variability of changes in the air temperatures. Multiple regression models derived from combinations of the significant variables also showed that both vegetation and building volume generated a model with the best fitness. Based on this multiple regression model, a 10% increase of vegetation volume decreased the air temperatures by approximately 0.14%, while a 10% increase of building volume raised them by 0.26%. Relationships between Chuncheon's summer air temperatures and land cover distribution for the smaller-scale spaces also disclosed that the air temperatures were negatively correlated to vegetation volume and greenspace area, while they were positively correlated to hardscape area. Similarly to the case of Seoul's AWS, the air temperatures for the smaller-scale spaces decreased by 0.32% ($0.08^{\circ}C$) as vegetation volume increased by 10%, based on the most appropriate linear model. Thus, urban landscaping for the reduction of summer air temperatures requires strategies to improve vegetation volume and simultaneously to decrease building volume. For Seoul's AWS, the impact of building volume on changing the air temperatures was about 2 times greater than that of vegetation volume. Wall and rooftop greening for shading and evapotranspiration is suggested to control atmospheric heating by three-dimensional building surfaces, enlarging vegetation volume through multilayered plantings on soil surfaces.
The implementation of the sunset provision of unexecuted urban parks in Seoul has been postponed; however, the mentioned parks still remain vulnerable since they can be subject to development under certain circumstances. Local governments may purchase the parks to prevent their loss but are constrained due to limited resources. The purpose of this study is to prioritize the purchase of unexecuted urban parks in Seoul based on landscape connectivity, which represents the important role of allowing the movement of wildlife and providing biodiversity in urban environments. In this study, we used four potential scenarios (PB100, PB1, PA100, PA1), which reflects the degree of land cover change resulting from the implementation of the sunset provision, and the role of Han River as a conduit or barrier for wildlife movement. Landscape connectivity was evaluated by calculating current flow betweenness centrality (CFBC). This was used to rank the importance of the unexecuted urban parks in Seoul. The results demonstrated that the implementation of the sunset provision will greatly decrease the connectivity of all parks in Seoul and particularly more so for parks in the southern part of the city. In addition, the results suggested that the low connectivity of Han river will diminish the connectivity around Bukhansan Mountain in the northern part of Seoul. Our study can be used for the prioritization of purchase, since it has the ability to evaluate the anticipated vulnerability of each park's connectivity after the sunset provision.
The impact on streamflow and groundwater recharge considering future potential climate and land use change was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for a $260.4km^2$ which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.8 to 0.7 and 0.7 to 0.5, respectively. The CCCma CGCM2 data by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) of the IPCC (Intergovemmental Panel on Climate Change) were adopted and the future weather data was downscaled by Delta Change Method using 30 years (1977 - 2006, baseline period) weather data. The future land uses were predicted by CA (Cellular Automata)-Markov technique using the time series land use data of Landsat images. The future land uses showed that the forest and paddy area decreased 10.8 % and 6.2 % respectively while the urban area increased 14.2 %. For the future vegetation cover information, a linear regression between monthly NDVI (Normalized Difference Vegetation Index) from NOAA/AVHRR images and monthly mean temperature using five years (1998 - 2002) data was derived for each land use class. The future highest NDVI value was 0.61 while the current highest NDVI value was 0.52. The model results showed that the future predicted runoff ratio ranged from 46 % to 48 % while the present runoff ratio was 59 %. On the other hand, the impact on runoff ratio by land use change showed about 3 % increase comparing with the present land use condition. The streamflow and groundwater recharge was big decrease in the future.
Silver nanoparticles (AgNPs) have potential applications in medicine, photocatalysis, agriculture, and cosmetic fields due to their unique physicochemical properties and strong antimicrobial activity. Here, AgNPs were synthesized using actinobacterial SL19 strain, isolated from acidic forest soil in Poland, and confirmed by UV-vis and FTIR spectroscopy, TEM, and zeta potential analysis. The AgNPs were polydispersed, stable, spherical, and small, with an average size of 23 nm. The FTIR study revealed the presence of bonds characteristic of proteins that cover nanoparticles. These proteins were then studied by using liquid chromatography with tandem mass spectrometry (LC-MS/MS) and identified with the highest similarity to hypothetical protein and porin with molecular masses equal to 41 and 38 kDa, respectively. Our AgNPs exhibited remarkable antibacterial activity against Escherichia coli and Pseudomonas aeruginosa. The combined, synergistic action of these synthesized AgNPs with commercial antibiotics (ampicillin, kanamycin, streptomycin, and tetracycline) enabled dose reductions in both components and increased their antimicrobial efficacy, especially in the case of streptomycin and tetracycline. Furthermore, the in vitro activity of the AgNPs on human cancer cell lines (MCF-7, A375, A549, and HepG2) showed cancer-specific sensitivity, while the genotoxic activity was evaluated by Ames assay, which revealed a lack of mutagenicity on the part of nanoparticles in Salmonella Typhimurium TA98 strain. We also studied the impact of the AgNPs on the catalytic and photocatalytic degradation of methyl orange (MO). The decomposition of MO was observed by a decrease in intensity of absorbance within time. The results of our study proved the easy, fast, and efficient synthesis of AgNPs using acidophilic actinomycete SL19 strain and demonstrated the remarkable potential of these AgNPs as anticancer and antibacterial agents. However, the properties and activity of such particles can vary by biosynthesized batch.
Microclimatic data were measured, and the human thermal sensation was analyzed at 10 local climate zones based on the major land cover classification to investigate the thermal environment of urban areas during summer nighttime. From the results, the green infrastructure areas (GNIAs) showed an average air temperature of 1.6℃ and up to 2.4℃ lower air temperature than the gray infrastructure areas (GYIAs), and the GNIAs showed an average relative humidity of 9.0% and up to 15.0% higher relative humidity. The wind speed of the GNIAs and GYIAs had minimal difference and showed no significance at all locations, except for the forest location, which had the lowest wind speed owing to the influence of trees. The local winds and the surface roughness, which was determined based on the heights of buildings and trees, appeared to be the main factors that influenced wind speed. At the mean radiant temperature, the forest location showed the maximum value, owing to the influence of trees. Except at the forest location, the GNIAs showed an average decrease of 5.5℃ compared to GYIAs. The main factor that influenced the mean radiant temperature was the sky view factor. In the analysis of the human thermal sensation, the GNIAs showed a "neutral" thermal perception level that was neither hot nor cold, and the GYIAs showed a "slightly warm" level, which was a level higher than those of the GNIAs. The GNIAs showed a 3.2℃ decrease compared to the GYIAs, except at the highest forest location, which indicated a half-level improvement in the human thermal environment.
Journal of the Korean Institute of Landscape Architecture
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v.37
no.3
/
pp.46-53
/
2009
Urbanization brings several changes to the natural environment. Its consequences can have a direct effect on climatic features, as in the Urban Heat Island Effect. One factor that directly affects the urban climate is the green area. In urban areas, vegetation is suppressed in order to accommodate manmade buildings and streets. In this paper we analyze the effect of green areas on the urban temperature in Seoul. The period selected for analysis was July 30th, 2007. The ground temperature was measured using Landsat TM satellite imagery. Land cover was calculated in terms of city area, water, bare soil, wet lands, grass lands, forest, and farmland. We extracted the surface temperature using the Linear Regression Model. Then, we did a regression analysis between air temperature at the Automatic Weather Station and surface temperature. Finally, we calculated the temperature decrease area and the population benefits from the green areas. Consequently, we determined that a green area with a radius of 500m will have a temperature reduction area of $67.33km^2$, in terms of urban area. This is 11.12% of Seoul's metropolitan area and 18.09% of the Seoul urban area. We can assume that about 1,892,000 people would be affected by this green area's temperature reduction. Also, we randomly chose 50 places to analysis a cross section of temperature reduction area. Temperature differences between the boundaries of green and urban areas are an average of $0.78^{\circ}C$. The highest temperature difference is $1.7^{\circ}C$, and the lowest temperature difference is $0.3^{\circ}C$. This study has demonstrated that we can understand how green areas truly affect air temperature.
Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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2014.10a
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pp.1-24
/
2014
This study uses geo-spatial crop modeling to quantify the biophysical impact of weather extremes. More specifically, the study analyzes the weather extreme which affected maize production in the USA in 2012; it also estimates the effect of a similar weather extreme in 2050, using future climate scenarios. The secondary impact of the weather extreme on food security in the developing world is also assessed using trend analysis. Many studies have reported on the significant reduction in maize production in the USA due to the extreme weather event (combined heat wave and drought) that occurred in 2012. However, most of these studies focused on yield and did not assess the potential effect of weather extremes on food prices and security. The overall goal of this study was to use geo-spatial crop modeling and trend analysis to quantify the impact of weather extremes on both yield and, followed food security in the developing world. We used historical weather data for severe extreme events that have occurred in the USA. The data were obtained from the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA). In addition we used five climate scenarios: the baseline climate which is typical of the late 20th century (2000s) and four future climate scenarios which involve a combination of two emission scenarios (A1B and B1) and two global circulation models (CSIRO-Mk3.0 and MIROC 3.2). DSSAT 4.5 was combined with GRASS GIS for geo-spatial crop modeling. Simulated maize grain yield across all affected regions in the USA indicates that average grain yield across the USA Corn Belt would decrease by 29% when the weather extremes occur using the baseline climate. If the weather extreme were to occur under the A1B emission scenario in the 2050s, average grain yields would decrease by 38% and 57%, under the CSIRO-Mk3.0 and MIROC 3.2 global climate models, respectively. The weather extremes that occurred in the USA in 2012 resulted in a sharp increase in the world maize price. In addition, it likely played a role in the reduction in world maize consumption and trade in 2012/13, compared to 2011/12. The most vulnerable countries to the weather extremes are poor countries with high maize import dependency ratios including those countries in the Caribbean, northern Africa and western Asia. Other vulnerable countries include low-income countries with low import dependency ratios but which cannot afford highly-priced maize. The study also highlighted the pathways through which a weather extreme would affect food security, were it to occur in 2050 under climate change. Some of the policies which could help vulnerable countries counter the negative effects of weather extremes consist of social protection and safety net programs. Medium- to long-term adaptation strategies include increasing world food reserves to a level where they can be used to cover the production losses brought by weather extremes.
It is important to determine optimum soil covering depths for tree survival and growth because soil covering depths for establishing tree planting bases in coastal reclaimed lands are related to the costs for soil collection, transportation and land reclamation. The objectives of this study were carried out to determine optimum soil covering depths for the normal growth of planted trees in a coastal reclaimed land. The study sites were located in Asan National Industrial Complex in Pyeongtaek City, Gyeonggi-do. Four tree species (Pinus thunbergii, Chamaecyparis pisifera, Zelkova serrata, Quercus acutissima) with one hundred eighty trees of each species were planted in various depths of soil covering (no soil covering, 0.5 m, 1.5 m, 2.0 m soil covering treatments) on April 1998, and the tree growth patterns were measured on September 2000. The change of soil properties, tree mortality rate, root collar diameter and height growth were measured from each soil covering depth treatment on September 2000. Soil pH, EC, exchangeable cations ($K^+$, $Na^+$, $Ca^{2+}$, $Mg^{2+}$), anion $Cl^-$, and base saturation increased with decreased soil covering depths. The mortality rates of tree species showed decreased with increased soil covering depths. The height growth of tree species increased with increased soil covering depths. Height growth of Pinus thunbergii was significantly different between the soil covering depth below 0.5m and other three covering depths, while the growth of other species (C. pisifera, Z. serrata, Q. acutissima) was significantly higher in soil covering depths below 1.5 m than in other soil covering depth treatments. The root collar diameter growth of all tree species showed increasing trends with increased soil covering depths. It is recommended to cover the soil depths above 1.5 m to decrease mortality and to stimulate the tree growth of C. pisifera, Z. serrata and Q. acutissima, while P. thunbergii which is a salt tolerate species could be planted in the 1.0 m soil covering depth.
Countries around the world, including the Republic of Korea, are participating in efforts to preserve biodiversity. Concerning species, in particular, studies that aim to find potential habitats and establish conservation plans by conducting habitat suitability analysis for specific species are actively ongoing. However, few studies on mid- to long-term changes in suitable habitat areas are based on accumulated information. Therefore, this study aimed to analyze the time-series changes in the habitat suitable area and examine the otters' changing pattern (Lutra lutra) designated as Level 1 endangered wildlife in Gangwon-do. The time-series change analysis used the data on otter species' presence points from the 2nd, 3rd, and 4th national natural environment surveys conducted for about 20 years. Moreover, it utilized the land cover map consistent with the survey period to create environmental variables to reflect each survey period's habitat environment. The suitable habitat area analysis used the MaxEnt model that can run based only on the species presence information, and it has been proven to be reliable by previous studies. The study derived the habitat suitability map for otters in each survey period, and it showed a tendency that habitats were distributed around rivers. Comparing the response curves of the environmental variables derived from the modeling identified the characteristics of the habitat favored by otters. The examination of habitats' change by survey period showed that the habitats based on the 2nd National Natural Environment Survey had the widest distribution. The habitats of the 3rd and 4th surveys showed a tendency of decrease in area. Moreover, the study aggregated the analysis results of the three survey periods and analyzed and categorized the habitat's changing pattern. The type of change proposed different conservation plans, such as field surveys, monitoring, protected area establishment, and restoration plan. This study is significant because it produced a comprehensive analysis map that showed the time-series changes of the location and area of the otter habitat and proposed a conservation plan that is necessary according to the type of habitat change by region. We believe that the method proposed in this study and its results can be used as reference data for establishing a habitat conservation and management plan in the future.
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