• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.97-106
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• 2006

Site index is an essential tool to estimate forest productivity. Generally, a site index equation is developed and used from the relationship between stand age and dominant tree heights. However, there is a limit to the use of the site index equation in the application of variable ages, environmental influence, and estimation of site index for the unstocked forest. Therefore, it has been attempted to develop a new site index equation based on various environmental factors including site, climate, and topographical variables. This study was conducted to develop a site index equation based on the relationship between site index and environmental factors for the species of Pinus koraiensis in Yangpyung-Gun, Gyunggi Province. The influence of climatic factors (temperature and solar irradiation ratio), topographical factors (elevation, slope, ratio of slope to valley and aspect) and soil profiles (soil depth by layer and soil consistency) on site index were evaluated by multiple regression analysis. Five environmental factors were selected in the final site index equation for Pinus koraiensis. The site index equation developed in this study was also verified by three evaluation statistics: model's estimation bias, model's precision, and mean square error of measurement. Based on the site index equation, the number of productive areas for Pinus koraiensis were estimated by applying GIS technique to digitized forest maps. In addition, the distribution of productive areas was compared with the areas of current distribution of Pinus koraiensis. It is expected that the results obtained in this study could provide valuable information about the amount and distribution of productive areas for Pinus koraiensis reforestation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.327-335
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• 2014

Current volume tables might underestimate or overestimate the volumes of individual trees in a specific region because the tables were made using the data from broad regions within South Korea. Therefore, to solve this problem, this study was conducted to develop local stem volume tables reflecting the local growth pattern and properties using stem taper equations in the regions of Hongcheon and Yeongju. We developed the local stem volume table for Pinus densiflora, which is the widely planted species in South Korea. To derive the most suitable taper equation for estimating the stem volume of region, three models of Max & Burkhart, Kozak and Parresol et al. were applied and their fitness were statistically analyzed by using the Fitness Index, Bias, and Standard Error of Bias. The result showed that there is a significant difference among the three models, and the Fitness Index of the Kozak model was highest compared to the other models. Therefore, the Kozak model was chosen for generating stem taper equation and stem volume tables for P. densiflora. The result from the developed stem volume tables of each region was compared to the current stem volume tables with driven by the data of tree growth obtained throughout the nation. The result showed that there is a significant difference (0.000< ${\alpha}=0.05$) in two regions, Hongcheon and Yeongju, and also there is a significant difference (0.000< ${\alpha}=0.05$) between the two regions.

• Journal of Wetlands Research
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• v.13 no.3
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• pp.499-514
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• 2011

An underlying assumption of traditional hydrologic frequency analysis is that climate, and hence the frequency of hydrologic events, is stationary, or unchanging over time. Under stationary conditions, the distribution of the variable of interest is invariant to temporal translation. Water resources infrastructure planning and design, such as dams, levees, canals, bridges, and culverts, relies on an understanding of past conditions and projection of future conditions. But, Water managers have always known our world is inherently non-stationary, and they routinely deal with this in management and planning. The aim of this paper is to give a brief introduction to non-stationary extreme value analysis methods. In this paper, a non-stationary hydrologic frequency analysis approach is introduced in order to determine probability rainfall consider changing climate. The non-stationary statistical approach is based on the conditional Generalized Extreme Value(GEV) distribution and Maximum Likelihood parameter estimation. This method are applied to the annual maximum 24 hours-rainfall. The results show that the non-stationary GEV approach is suitable for determining probability rainfall for changing climate, sucha sa trend, Moreover, Non-stationary frequency analyzed using SOI(Southern Oscillation Index) of ENSO(El Nino Southern Oscillation).

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.58-69
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• 2007

The vegetation area that occupies 76% in land surface of the earth can give a considerable impact on water resources, environment and ecological system by future climate change. The purpose of this study is to predict future vegetation cover information from NDVI (Normalized Difference Vegetation Index) extracted from satellite images. Current vegetation information was prepared from monthly NDVI (March to November) extracted from NOAA AVHRR (1994 - 2004) and Terra MODIS (2000 - 2004) satellite images. The NDVI values of MODIS for 5 years were 20% higher than those of NOAA. The interrelation between NDVIs and monthly averaged climate factors (daily mean, maximum and minimum temperature, rainfall, sunshine hour, wind velocity, and relative humidity) for 5 river basins of South Korea showed that the monthly NDVIs had high relationship with monthly averaged temperature. By linear regression, the future NDVIs were estimated using the future mean temperature of CCCma CGCM2 A2 and B2 climate change scenario. The future vegetation information by NOAA NDVI showed little difference in peak value of NDVI, but the peak time was shifted from July to August and maintained high NDVIs to October while the present NDVI decrease from September. The future MODIS NDVIs showed about 5% increase comparing with the present NDVIs from July to August.

• Journal of Korean Society of Disaster and Security
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• v.13 no.2
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• pp.1-9
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• 2020

Vietnamese cities have a high risk of flooding under climate change due to their geographical characteristics. In this situation, the urban area is expanding with rapid growth of urban population. However, the risk of flooding is increasing due to the increase in impermeable areas and insufficient infrastructure. This study analyzed the urban expansion trend at the national level in Vietnam for the past 10 years (2007-2017) by using the Urban Expansion Intensity Index. Also, this study selected Hue City as a region with a large impact of climate change and a rapid expansion and found the possibility of flooding in the urban expansion area. The result showed that cities have been expanded around major cities in the Red River Delta, Mekong Delta, and coastal areas. In the case of Hue City, the area with fast expansion rate has a higher expected flood area. It implies that the risk of flood disasters may increase if the urabn expansion is carried out without disaster prevention measures. It is expected that Korean urban disaster prevention policies such as urban climate change disaster vulnerability analysis system will be helpful in establishing urban plans considering climate change in the fast growing regions such as Vietnam.

• Atmosphere
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• v.30 no.4
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• pp.377-390
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• 2020

Not only emissions, but also atmospheric circulation is a key factor that affects local particulate matters (PM) concentrations in Korea through ventilation effects and transboundary transports. As part of the atmospheric circulation, air stagnation especially adversely affects local air quality due to weak ventilation. This study investigates the large-scale circulation related to air stagnation over Korea during winter and projects the climate change impacts on atmospheric patterns, using observed PM data, reanalysis and regional climate projections from HadGEM3-RA with Modified Korea Particulate matter Index. Results show that the stagnation affects the PM concentration, accompanied by pressure ridge at upper troposphere and weaken zonal pressure gradient at lower troposphere. Downscaling using HadGEM3-RA is found to yield Added-Value in the simulated low tropospheric winds. For projection of future stagnation, SSP5-8.5 and SSP1-2.6 (high and low emission) scenarios are used here. It has been found that the stagnation condition occurs more frequently by 11% under SSP5-8.5 and by 5% under SSP1-2.6 than in present-day climate and is most affected by changes in surface wind speed. The increase in the stagnation conditions is related to anticyclonic circulation anomaly at upper troposphere and weaken meridional pressure gradient at lower troposphere. Considering that the present East Asian winter monsoon is mainly affected by change in zonal pressure gradient, it is worth paying attention to this change in the meridional gradient. Our results suggest that future warming condition increase the frequency of air stagnation over Korea during winter with response of atmospheric circulation and its nonlinearity.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1219-1230
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• 2022

Multi-spectral drones in agricultural observation require quantitative and reliable data based on physical quantities such as radiance or reflectance in crop yield analysis. In the case of remote sensing data for crop monitoring, images taken in the same area over time-series are required. In particular, biophysical data such as leaf area index or chlorophyll are analyzed through time-series data under the same reference, it can be directly analyzed. So, comparable reflectance data are required. Orthoimagery using drone images, the entire image pixel values are distorted or there is a difference in pixel values at the junction boundary, which limits accurate physical quantity estimation. In this study, reflectance and vegetation index based on drone images were calculated according to the correction method of drone images for time-series crop monitoring. comparing the drone reflectance and ground measured data for spectral characteristics analysis.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.713-723
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• 2023

Climate change is significantly affecting coastal areas, and its impacts are expected to intensify. Recent studies on climate change adaptation and risk assessment in coastal regions increasingly integrate the concepts of recovery resilience and vulnerability. The aim of this study is to develop a measurement model for coastal hazard recovery resilience in the context of climate change adaptation. Before constructing the measurement model, a comprehensive literature review was conducted on coastal hazard recovery resilience, establishing a conceptual framework that included operational definitions for vulnerability and recovery resilience, along with several feedback mechanisms. The measurement model for coastal hazard recovery resilience comprised four metrics (MRV, LRV, RTSPV, and ND) and a Coastal Resilience Index (CRI). The developed indices were applied to domestic coastal erosion cases, and regional analyses were performed based on the index grades. The results revealed that the four recovery resilience metrics provided insights into the diverse characteristics of coastal erosion recovery resilience at each location. Mapping the composite indices of coastal resilience indicated that the areas along the East Sea exhibited relatively lower coastal erosion recovery resilience than the West and South Sea regions. The developed recovery resilience measurement model can serve as a tool for discussions on post-adaptation strategies and is applicable for determining policy priorities among different vulnerable regional groups.

• Journal of Korean Society of Rural Planning
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• v.17 no.3
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• pp.1-13
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• 2011

This study aims to analyse the landscape ecological characteristics of 39 rural villages in Korea and classify them according to their characteristics. After producing a land-use map of rural villages, this study quantified the landscape ecological characteristics of the subject sites as 18 landscape indexes using Fragstats. By applying the landscape index as a variable, selecting 4 factor through principal component analysis and conducting a cluster analysis, it classified them into 3 groups. Rural villages of Korea have their unique types of land-use due to the influence of physical environment such as geography, climate and ecology as well as the social and cultural influence, and the characteristics of land-use can be analysed and classified using the landscape index, the quantified landscape ecological characteristics.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.5-6
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• 2015

Recently, freezing index of frost penetration depth estimation used in Korea is applied according to the standard, published by MOLIT in 2003. However, it is difficult to consider can not be determined to standard reflects weather conditions in accordance with the current climate warming or abnormally high temperature. Also the temperature should be considered local variables because heavy local gap. Therefore, this study is through the freezing index presented in MOLIT's code by calculating the frost penetration depth determining whether the adequacy and conducted a study to apply in the field. As a result, when the Elevation 100m to standard in Incheon frost penetration depth is found to be 50.8cm.