• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.449-459
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• 2015

The conventional National Forest Inventory(NFI)-based forest carbon stock estimation method is suitable for national-scale estimation, but is not for regional-scale estimation due to the lack of NFI plots. In this study, for the purpose of regional-scale carbon stock estimation, we created grid-based forest carbon stock maps using spatial ancillary data and two types of up-scaling methods. Chungnam province was chosen to represent the study area and for which the $5^{th}$ NFI (2006~2009) data was collected. The first method (method 1) selects forest type map as ancillary data and uses regression model for forest carbon stock estimation, whereas the second method (method 2) uses satellite imagery and k-Nearest Neighbor(k-NN) algorithm. Additionally, in order to consider uncertainty effects, the final AGB carbon stock maps were generated by performing 200 iterative processes with Monte Carlo simulation. As a result, compared to the NFI-based estimation(21,136,911 tonC), the total carbon stock was over-estimated by method 1(22,948,151 tonC), but was under-estimated by method 2(19,750,315 tonC). In the paired T-test with 186 independent data, the average carbon stock estimation by the NFI-based method was statistically different from method2(p<0.01), but was not different from method1(p>0.01). In particular, by means of Monte Carlo simulation, it was found that the smoothing effect of k-NN algorithm and mis-registration error between NFI plots and satellite image can lead to large uncertainty in carbon stock estimation. Although method 1 was found suitable for carbon stock estimation of forest stands that feature heterogeneous trees in Korea, satellite-based method is still in demand to provide periodic estimates of un-investigated, large forest area. In these respects, future work will focus on spatial and temporal extent of study area and robust carbon stock estimation with various satellite images and estimation methods.

• 한국해양학회지
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• v.24 no.3
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• pp.157-164
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• 1989

Quantitative species distribution and primary productivity of phytoplankton were studied monthly from August, 1987 to July, 1988 along with the quantitative distribution of total heterotrophic bacterioplankton and three groups of physiologically chracteristic bacterioplankton in the intertidal and subtidal waters off Kum River Estuary, Yellow Sea. A total of 121 phytoplankton taxa including 102 diatoms occurred, and cell concentration ranged from 15 to 5451 (cells/ml). The great spatio-temporal variations of the number of phytoplankton species and cell concentration well reflected the environmental differences between the intertidal and subtidal waters. Primary productivity (in Piopt, mgC/$m^3$/hr) ranged from 0.6 to 27.3. Just after the phytoplankton bloom (March) Piopt was very low in April at station 1, where amylolytic bacterioplankton also showed quite low population density. The peaks of primary productivity were not always coincided with those of phytoplankton standing crop. The ratio of Piopt's between samples well indicated the environmental differences between the intertidal and subtidal waters. Little characteristic trend was found in the scatter diagrams of phytoplankton standing crop along the population densities of total heterotrophic bacterioplankton and the three groups of physiologically characteristic bacterioplankton. In summer the phytoplankton standing crop was minimum in contrast with the high population density of bacterioplankton, which implies the influx of much allochthonous orgainc matter from Kum River. The scatter diagrams of Piopt along bacterioplankton population density revealed some phenomena there. Piopt had highly positive correlation with the population density of amylolytie bacterioplankton($R^2$=0.84) and that of lipolytic bacterioplankton($R^2$=0.70) while total heterotrophic bacterioplankton and proteolytic bacterioplankton had lesser correlations with Piopt. From the regression lines the increase of unit Piopt (mgC/$m^3$/hr) in the study area was calculated to mean the increase of $9.0{\times}10$ cells/ml and $8.0{\times}10$ cells/ml of amylolytic bacterioplankton and lipolytic bacterioplankton, respectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.215-231
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• 2020

Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R²) and root mean square error (RMSE). The final model performed very well, with 0. 98 R² and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.

• Korean Journal of Ecology and Environment
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• v.50 no.1
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• pp.96-115
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• 2017

Understanding effects of thermal pollution and acidification has long been a concern of aquatic ecologists, but it remains largely unknown in Korea. This study was performed to elucidate the effects of thermal wastewater effluent (TWE) and acid rain on water quality and attached algae in a small mountain stream, the Buso Stream, a tributary located in the Hantan River basin. A total of five study sites were selected in the upstream area including the inflowing point of hot-spring wastewater (HSW), one upstream site (BSU), and three sites below thermal effluent merged into the stream (1 m, 10 m and 300 m for BSD1, BSD2, and BSD3, respectively). Field surveys and laboratory analyses were carried out every month from December 2015 to September 2016. Water temperature ranged $1.7{\sim}28.8^{\circ}C$ with a mean of $15.0^{\circ}C$ among all sites. Due to the effect of thermal effluent, water temperature at HSW site was sustained at high level during the study period from $17.5^{\circ}C$ (January) to $28.8^{\circ}C$ (September) with a mean of $24.2{\pm}3.7^{\circ}C$, which was significantly higher than other sites. Thermal wastewater effluent also brought in high concentration of nutrients(N, P). The effect of TWE was particularly apparent during dry season and low temperature period (December~March). Temperature effect of TWE did not last toward downstream, while nutrient effect seemed to maintain in longer distance. pH ranged 5.1~8.4 with a mean of 6.9 among all sites during the study period. The pH decrease was attributed to seasonal acid rain and snow fall, and their effects was identified by acidophilic diatoms dominated mainly by Eunotia pectinalis and Tabellaria flocculosa during March and August. These findings indicated that water quality and periphyton assemblages in the upstream region of Buso Stream were affected by thermal pollution, eutrophication, and acidification, and their confounding effects were seasonally variable.

• Korean Journal of Ecology and Environment
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• v.50 no.1
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• pp.1-15
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• 2017

Daecheong Reservoir was made by the construction of a large dam (>15 m in height) on the middle to downstream of the Geum River and the discharge systems have the watergate-spillway (WS), a hydropower penstock (HPP), and two intake towers. The purpose of this study was to investigate the limnological anomalies of turbid water reduction, green algae phenomenon, and oligotrophic state in the lower part of reservoir dam site, and compared with hydro-meteorological factors. Field surveys were conducted in two stations of near dam and the outlet of HPP with one week intervals from January to December 2000. Rainfall was closely related to the fluctuations of inflow, outflow and water level. The rainfall pattern was depended on the storm of monsoon and typhoon, and the increase of discharge and turbidity responded more strongly to the intensity than the frequency. Water temperature and DO fluctuations within the reservoir water layer were influenced by meteorological and hydrological events, and these were mainly caused by water level fluctuation based on temperature stratification, density current and discharge types. The discharges of WS and HPP induced to the flow of water bodies and the outflows of turbid water and nutrients such as nitrogen and phosphorus, respectively. Especially, when hypoxic or low-oxygen condition was present in the bottom water, the discharge through HPP has contributed significantly to the outflow of phosphorus released from the sediment into the downstream of dam. In addition, HPP effluent which be continuously operated throughout the year, was the main factor that could change to a low trophic level in the downreservoir (lacustrine zone). And water-bloom (green-tide) occurring in the lower part of reservoir was the result that the water body of upreservoir being transported and diffused toward the downreseroir, when discharging through the WS. Finally, the hydropower effluent was included the importance and dynamics that could have a temporal and spatial impacts on the physical, chemical and biological factors of the reservoir ecosystem.

• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.895-910
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• 2013

Multi-screen service is a service that consumes more than one media in a number of terminals simultaneously or discriminately. This multi-screen service has become useful due to distribute of smart TV and terminals. Also, in case of hybrid broadcasting environment that is convergence of broadcasting and communication environment, it is able to provide various user experience through contents consumed by multiple screens. In hybrid broadcasting environment, scene composition technology can be used as an element technology for multi-screen service. Using scene composition technology, multiple media can be consumed complexly through the specified presentation time and space. Thus, multi-screen service based on the scene composition technology can provide spatial and temporal control and consumption of multiple media by linkage between the terminals. However, existing scene composition technologies are not able to use easily in hybrid broadcasting because of applicable environmental constraints, the difficulty in applying the various terminal and complexity. For this problems, HTML5 can be considered. HTML5 is expected to be applied in various smart terminals commonly, and provides consumption of diverse media. So, in this paper, it proposes the scene composition and multi-screen service technology based on HTML5 that is expected be used in various smart terminals providing hybrid broadcasting environment. For this, it includes the introduction in terms of HTML5 and multi-screen service, the method of providing information related with scene composition and multi-screen service through the extention of elements and attributes in HTML5, media signaling between terminals and the method of synchronization. In addition, the proposed scene composition and multi-screen service technology based on HTML5 was verified through the implementation and experiment.

• Journal of Environmental Impact Assessment
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• v.29 no.1
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• pp.26-36
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• 2020

This study aimed at investigating present research and knowledge-base on climate change adaptation in ecosystem sector and analyzed the current status of basic information on ecosystem that functions as evidence-base of climate change adaptation to deduce the suggestions for the future development for knowledge and information in biodiversity. In this perspective, a questionary survey titled as "the ecological knowledge-base and information needs for climate change adaptation" with the researchers who were engaged with adaptation studies for biodiversity in the ecosystem related-research institutes including national and 17 regional local governments-affiliated agencies in Korea. The results are as follows; current status of utilizing ecological information which supports climate change adaptation strategy, future needs for adaptation knowledge and ecological information, and activation of utilizing ecological information. The majority of respondents (90.7%) replied that the ecological information has high relevance when conducting research on climate change adaptation. However, only half of all respondents (53.2%) agreed with the real viability of current information to the adaptation research. Particularly, urgent priority for researchers was deduced as intensifying knowledge-base and constructing related information on 'ecosystem change from climate change (productivity, community structure, food chain, phenology, range distribution, and number of individuals) with the overall improvement of information contents and its quality. The respondents emphasized with the necessity of conducting field surveys of local ecosystem and constructing ecosystem inventories, advancing monitoring designs for climate change in ecosystem, and case studies for regional ecosystem changes with the guidance or guidelines for monitoring ecosystem change to enhance the quality of adaptation research and produce related information. In terms of activation for ecological information usage, national and local adaptation network should be working based on the integrated ecological platform necessary to support exchanges of knowledge and information and to expand ecosystem types in time and spatial dimension.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.77-83
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• 2015

Frequent pattern mining, which is one of the major areas actively studied in data mining, is a method for extracting useful pattern information hidden from large data sets or databases. Moreover, frequent pattern mining approaches have been actively employed in a variety of application fields because the results obtained from them can allow us to analyze various, important characteristics within databases more easily and automatically. However, traditional frequent pattern mining methods, which simply extract all of the possible frequent patterns such that each of their support values is not smaller than a user-given minimum support threshold, have the following problems. First, traditional approaches have to generate a numerous number of patterns according to the features of a given database and the degree of threshold settings, and the number can also increase in geometrical progression. In addition, such works also cause waste of runtime and memory resources. Furthermore, the pattern results excessively generated from the methods also lead to troubles of pattern analysis for the mining results. In order to solve such issues of previous traditional frequent pattern mining approaches, the concept of representative pattern mining and its various related works have been proposed. In contrast to the traditional ones that find all the possible frequent patterns from databases, representative pattern mining approaches selectively extract a smaller number of patterns that represent general frequent patterns. In this paper, we describe details and characteristics of pattern condensing techniques that consider the maximality or closure property of generated frequent patterns, and conduct comparison and analysis for the techniques. Given a frequent pattern, satisfying the maximality for the pattern signifies that all of the possible super sets of the pattern must have smaller support values than a user-specific minimum support threshold; meanwhile, satisfying the closure property for the pattern means that there is no superset of which the support is equal to that of the pattern with respect to all the possible super sets. By mining maximal frequent patterns or closed frequent ones, we can achieve effective pattern compression and also perform mining operations with much smaller time and space resources. In addition, compressed patterns can be converted into the original frequent pattern forms again if necessary; especially, the closed frequent pattern notation has the ability to convert representative patterns into the original ones again without any information loss. That is, we can obtain a complete set of original frequent patterns from closed frequent ones. Although the maximal frequent pattern notation does not guarantee a complete recovery rate in the process of pattern conversion, it has an advantage that can extract a smaller number of representative patterns more quickly compared to the closed frequent pattern notation. In this paper, we show the performance results and characteristics of the aforementioned techniques in terms of pattern generation, runtime, and memory usage by conducting performance evaluation with respect to various real data sets collected from the real world. For more exact comparison, we also employ the algorithms implementing these techniques on the same platform and Implementation level.

• Journal of the Korean Geographical Society
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• v.41 no.2 s.113
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• pp.168-187
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• 2006

Windy meteorological conditions and dried fire fuels due to higher atmospheric instability and dryness in the lower troposphere can exacerbate fire controls and result in more losses of forest resources and residential properties due to enhanced large wildland fires. Long-term (1979-2005) climatology of the Haines Index reconstructed in this study reveals that spatial patterns and intra-annual variability of the atmospheric instability and dryness in the lower troposphere affect the frequency of wildland fire incidences over the Korean Peninsula. Exponential regression models verify that daily high Haines Index and its monthly frequency has statistically significant correlations with the frequency of the wildland fire occurrences during the fire season (December-April) in South Korea. According to the climatic maps of the Haines Index created by the Geographic Information System (GIS) using the Digital Elevation Model (DEM), the lowlands below 500m from the mean sea level in the northwestern regions of the Korean Peninsula demonstrates the high frequency of the Haines Index equal to or greater than five in April and May. The annual frequency of the high Haines Index represents an increasing trend across the Korean Peninsula since the mid-1990s, particularly in Gyeongsangbuk-do and along the eastern coastal areas. The composite of synoptic weather maps at 500hPa for extreme events, in which the high Haines Index lasted for several days consecutively, illustrates that the cold low pressure system developed around the Sea of Okhotsk in the extreme event period enhances the pressure gradient and westerly wind speed over the Korean Peninsula. These results demonstrate the need for further consideration of the spatial-temporal characteristics of vertical atmospheric components, such as atmospheric instability and dryness, in the current Korean fire prediction system.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.1 s.15
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• pp.51-63
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• 2000

Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.