• Atmosphere
• /
• v.29 no.2
• /
• pp.131-147
• /
• 2019

On the urban scale, Micro-climate analysis models for urban scale have been developed to investigate the atmospheric characteristics in urban surface in detail and to predict the micro-climate change due to the changes in urban structure. BioCAS (Biometeorological Climate Impact Assessment System) is a system that combines such analysis models and has been implemented internally in the Korea Meteorological Administration. One of role in this system is the analysis of the health impact by heat waves in urban area. In this study, the vegetation cooling models A and B were developed and linked with BioCAS and evaluated by the temperature drop at the vegetation areas during ten selected heat-wave days. Smaller prediction errors were found as a result of applying the vegetation cooling models to the heat-wave days. In addition, it was found that the effects of the vegetation cooling models produced different results according to the distribution of vegetation area in land cover near each observation site - the improvement of the model performance on temperature analysis was different according to land use at each location. The model A was better fitted where the surrounding vegetation ratio was 50% or more, whereas the model B was better where the vegetation ratio was less than 50% (higher building and impervious areas). Through this study, it should be possible to select an appropriate vegetation cooling model according to its fraction coverage so that the temperature analysis around built-up areas would be improved.

• The Journal of the Korea Contents Association
• /
• v.10 no.11
• /
• pp.452-460
• /
• 2010

This study carried out stability evaluation for design flood stage of vegetation models with river sites using 1D HEC-RAS and 2D RMA-2 numerical models. The vegetation models established in this study were divided into which channel reaches consist of urban, rural and mountain rivers with the social and cultural significance of the sites. Examination results from the numerical models showed a similar aspect with the design flood stage of these rivers before vegetation modeling. Also, no embankment overflow was shown from the urban river with additional vegetation density of 25%, although there were approximately 0.20m rising in the flood stage. In case of ural and mountain rivers, vegetation models showed scarce rising in flood stage.

• International Journal of Contents
• /
• v.8 no.3
• /
• pp.34-41
• /
• 2012

The concept of vegetation freeboard equivalence (VFE) is presented from the comparison between the rise in stage with/without vegetation and the freeboard height under design discharge conditions. In South Korea, the freeboard height of large, medium and small rivers is defined as a function of river discharge. Two models are used for this analysis of flood stage with and without vegetation: the 1-D model HEC-RAS and the 2-D model RMA-2. Both models are applied to three river study sites of the Geum River in South Korea as representative sites for a large, a medium and a small river. The analysis shows that without vegetation, both models provide comparable results and the calculated results are in very good agreement with the design configuration. The vegetation effects on the medium river are less significant, and the freeboard is adequate to contain the rise in stage from the added floodplain vegetation in large rivers. The concept of vegetation freeboard equivalence is therefore useful for the analysis of flood river stages after the restoration of channels with increased floodplain vegetation.

• KIEAE Journal
• /
• v.13 no.5
• /
• pp.89-96
• /
• 2013

Green roofs can reduce surface water runoff, provide a habitat for wildlife moderate the urban heat island effect, improve building insulation and energy efficiency, improve the air quality, create aesthetic and amenity value, and preserve the roof's waterproofing. Green roofs are mainly divided into three types : intensive, simple-intensive, and extensive. Especially, extensive roof environment is a harsh one for plant growth; limited water availability, wide temperature fluctuations, high exposure to wind and solar radiation create highly stressed environment. This study, aimed at extensive green roof, was carried out on the rooftop of the library at Seoul Women's Univ. from October to November, 2012 and from March to August, 2013. To suggest the most effective vegetation model for biodiversity and heat island mitigation, surface temperatures were monitored by each vegetation model. We found that herbaceous plants of Aster sphathulifolius, Aceriphyllum rossii and Belamcanda chinensis, shrub of Syringa patula 'Miss Kim', Thymus quinquecostatus var. japonica, Sedum species can mixing each other. Among them, the vegetation models including Sedum takesimense, Aster sphathulifolius, Thymus quinquecostatus var. japonica was more effective on the surface temperature mitigation, because the species have the tolerance and high ratio of covering, and also in water. Especially, in the treatment of bark mulching, they helped to increase the temperature of vegetation models. In the case of summer, temperature mitigation of vegetation models were no significant difference among vegetation types. Compared to surface temperature of June, July and August were apparent impact of temperature mitigation, it shows that temperature mitigation are strongly influenced by substrate water content.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.12 no.6
• /
• pp.123-130
• /
• 2009

Fragmentation due to land developments causes disturbances and changes of composition in forest vegetation. The purpose of the study was to develop the impact assessment model for quantitative distance or degree of disturbance by land developments. This study conducted a survey about structure and composition of forest vegetation to determine degree of impact from land developments. The results of field survey, there was a difference in structure and composition of forest vegetation such as tree canopy, herbaceous cover, and number of vine and alien species the distances from edge to interior area such as 0m, 10m, 20m, 40m, and over 60m. To assess the disturbance of forest vegetation, the factors selected were the rate of vine's cover and appearance of alien species. The impact assessment model about vine species explained by a distance, forest patch size, type of forest fragmentation, and type of vegetation ($R^2$=0.44, p<0.001). The other model about alien species explained by a distance, type of forest fragmentation, type of vegetation, and width of road (85.9%, p<0.005). The models applied to Samsong housing development in Goyang-si, Gyunggi-do. The vines and alien species in the study area have had a substantial impact on forest vegetation from edge to 20 or 40m. The impact assessment models were high reliability for estimating impacts to land developments. The impact of forest vegetation by development activities could be minimized thorough the adoption of the models introduced at the stage of EIA.

• Korean Journal of Remote Sensing
• /
• v.35 no.6_3
• /
• pp.1209-1219
• /
• 2019

For consistent vegetation monitoring, it is necessary to generate time-series vegetation index datasets at fine temporal and spatial scales by fusing the complementary characteristics between temporal and spatial scales of multiple satellite data. In this study, we quantitatively and qualitatively analyzed the prediction accuracy of time-series change information extracted from spatio-temporal fusion models of multiple satellite data for vegetation monitoring. As for the spatio-temporal fusion models, we applied two models that have been widely employed to vegetation monitoring, including a Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and an Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM). To quantitatively evaluate the prediction accuracy, we first generated simulated data sets from MODIS data with fine temporal scales and then used them as inputs for the spatio-temporal fusion models. We observed from the comparative experiment that ESTARFM showed better prediction performance than STARFM, but the prediction performance for the two models became degraded as the difference between the prediction date and the simultaneous acquisition date of the input data increased. This result indicates that multiple data acquired close to the prediction date should be used to improve the prediction accuracy. When considering the limited availability of optical images, it is necessary to develop an advanced spatio-temporal model that can reflect the suggestions of this study for vegetation monitoring.

• Journal of Korea Water Resources Association
• /
• v.43 no.9
• /
• pp.823-833
• /
• 2010

Open-channel flows with submerged vegetation show two distinct flow structures in the vegetation and upper layers. That is, the flow in the vegetation layer is featured by relatively uniform mean velocity with suppressed turbulence from shear, while the flow in the upper layer is akin to that in the plain open-channel. Due to this dual characteristics, the flow has drawn many hydraulic engineers' attentions. This study compares layer-averaged models for flows with submerged vegetation. The models are, in general, classified into two-layer and three-layer models. The two-layer model divides the flow depth into vegetation and upper layers, while the three-layer model further divides the vegetation layer into inner and outer vegetation layers depending on the influence of the bottom roughness. This study compares the two-layer model and the three layer-model. It is found that the two-layer model predicts better the average value of the velocity and the prediction by the three-layer model is sensitive to Reynolds shear stress. In the three-layer model, the mean flow in the inner vegetation layer does not affect the flow seriously, which motivates the proposal of the modified two-layer model. The two-layer model, capable of predicting non-uniform mean velocity, is based on the Reynolds stress which is linear and of power form in the upper and vegetation layers, respectively. Application results reveal that the modified two-layer model predicts the mean velocity at an accuracy similar to the two- and three-layer models, but it predicts poorly in the case of very low vegetation density.

• Korean Journal of Remote Sensing
• /
• v.28 no.6
• /
• pp.597-609
• /
• 2012

Leaf area index (LAI) is important in explaining the ability of the crop to intercept solar energy for biomass production and in understanding the impact of crop management practices. This paper describes a procedure for estimating LAI as a function of image-derived vegetation indices from temporal series of IKONOS, Landsat TM, and MODIS satellite images using empirical models and demonstrates its use with data collected at Missouri field sites. LAI data were obtained several times during the 2002 growing season at monitoring sites established in two central Missouri experimental fields, one planted to soybean (Glycine max L.) and the other planted to corn (Zea mays L.). Satellite images at varying spatial and spectral resolutions were acquired and the data were extracted to calculate normalized difference vegetation index (NDVI) after geometric and atmospheric correction. Linear, exponential, and expolinear models were developed to relate temporal NDVI to measured LAI data. Models using IKONOS NDVI estimated LAI of both soybean and corn better than those using Landsat TM or MODIS NDVI. Expolinear models provided more accurate results than linear or exponential models.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.30 no.3
• /
• pp.73-85
• /
• 2002

The purpose of this study was to develop prediction models for plant species abundance by stream restoration. Generally the stream plant is affected by stream gemophology. So in this study, the relationship between the vegetation abundance and stream gemophology was developed by multiple regression analysis. The stream characteristics utilized in this study were longitudinal slope, transectional slope, micro-landforms through the longitudinal direction, riparian width and geometric mean diameter and biggest diameter of bed material, and cumulated coarse and fine sand weight portion. The Pyungchang River with mountainous watershed and the Kyungan stream and the Bokha stream in the agricultural region were selected and vegetation species abundance and stream characteristics were documented from the site at 2~3km intervals from the upper stream to the lower. The Models for predicting the vegetation abundance were developed by multiple regression analysis using SPSS statistics package. The linear relationship between the dependant(species abundance) and independant(stream characteristics) variables was tested by a graphical method. Longitudinal and transectional slope had a nonlinear relationship with species abundance. In the next step, the independance between the independant variables was tested and the correlation between independant and dependant variables was tested by the Pearson bivariate correlation test. The selected independant variables were transectional slope, riparian width, and cumulated fine sand weight portion. From the multiple regression analysis, the $R^2$for the Pyungchang river, Kyungan stream, Bokga stream were 0.651, 0.512 and 0.240 respectively. The natural stream configuration in the Pyungchang river had the best result and the lower $R^2$for Kyunan and Bokha stream were due to human impact which disturbed the natural ecosystem. The lowest $R^2$for the Bokha stream was due to the shifting sandy bed. If the stream bed is fugitive, the prediction model may not be valid. Using the multiple regression models, the vegetation abundance could be predicted with stream characteristics such as, transection slope, riaparian width, cumulated fine sand weigth portion, after stream restoration.

• Journal of Environmental Science International
• /
• v.27 no.2
• /
• pp.135-141
• /
• 2018

The specification of surface vegetation is essential for simulating actual evapotranspiration of water resources. The availability of land cover maps based on remotely collected data makes the specification of surface vegetation easier. The spatial resolution of hydrologic models rarely matches the spatial scales of the vegetation data needed, and remotely collected vegetation data often are upscaled up to conform to the hydrologic model scale. In this study, the effects of the grid scale of of surface vegetation on the results of actual evapotranspiration were examined. The results show that the coarser resolution causes larger error in relative terms and that a more realistic description of area-averaged vegetation nature and characteristics needs to be considered when calculating actual evapotranspiration.