• Journal of Environmental Science International
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• v.13 no.12
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• pp.1033-1039
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• 2004

The methodology developed by Soil Conservation Service for determination of runoff value from precipitation is applied to estimate the precipitation recharge in the Pyungchang river basin. Two small areas of the basin are selected for this study. The CN values are determined by considering the type of soil, soil cover and land use with the digital map of 1:25,000. Forest covers more than $94{\%}$ of the study area.. The CN values for the study area vary between 47 in the forest area and 94 in the bare soil under AMC 2 condition. The precipitation recharge rate is calculated for the year when the precipitation data is available since 1990. To obtain the infiltration rate, the index of CN and five day antecedent moisture conditions are applied to each precipitation event during the study period. As a result of estimation, the value of precipitation recharge ratio in the study area vary between $15.2{\%}\;and\;35.7{\%}$ for the total precipitation of the year. The average annual precipitation recharge rate is $26.4{\%}\;and\;26.8{\%}$, meaning 377.9mm/year and 397.5mm/year in each basin.

• Journal of Ecology and Environment
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• v.45 no.4
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• pp.255-263
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• 2021

Background: Ecosystem service mapping is an important tool for decision-making in landscape planning and natural resource management. Today, pollination service mapping is based on the Lonsdorf model (InVEST software) that determines the availability of nesting and floral resources for each land cover and estimates pollination according to the foraging range of the desired species. However, it is argued that the Lonsdorf model has significant limitations in estimating pollination in a landscape that can affect the results of this model. Results: This paper presents a free software, named PollMap, that does not have the limitations of the Lonsdorf model. PollMap estimates the pollination service according to a modified version of the Lonsdorf model and assumes that only cells within the flight range of bees are important in the pollination mapping. This software is produced for estimating and mapping crop pollination in agricultural landscapes. The main assumption of this software is that in the agricultural landscapes, which are dominated by forest and agriculture ecosystems, forest patches serve only as a nesting habitat for wild bees and the surrounding fields provide floral resources. Conclusion: The present study provided new software for mapping crop pollination in agricultural landscapes that does not have the limitations of the Lonsdorf model. We showed that the use of the Lonsdorf model for pollination mapping requires attention to the limitations of this model, and by removing these limitations, we will need new software to obtain a reliable mapping of pollination in agricultural landscapes.

• Journal of Environmental Impact Assessment
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• v.27 no.2
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• pp.124-138
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• 2018

This research was conducted to examine the availability of spatial data for assessing absorption rates of $CO_2$ in the forest of Ansan-si and evaluate the validity of methods that analyze $CO_2$ absorption. To statistically assess the $CO_2$ absorption rates per year, the 1:5,000 Digital Forest-Map (Lim5000) and Standard Carbon Removal of Major Forest Species (SCRMF) methods were employed. Furthermore, Land Cover Map (LCM) was also used to verify $CO_2$ absorption rate availability per year. Great variations in $CO_2$ absorption rates occurred before and after the year 2010. This was due to improvement in precision and accuracy of the Forest Basic Statistics (FBS) in 2010, which resulted in rapid increase in growing stock. Thus, calibration of data prior to 2010 is necessary, based on recent FBS standards. Previous studies that employed Lim5000 and FBS (2015, 2010) did not take into account the $CO_2$ absorption rates of different tree species, and the combination of SCRMF and Lim5000 resulted in $CO_2$ absorption of 42,369 ton. In contrast to the combination of SCRMF and Lim5000, LCM and SCRMF resulted in $CO_2$ absorption of 40,696 ton. Homoscedasticity tests for Lim5000 and LCM resulted in p-value <0.01, with a difference in $CO_2$ absorption of 1,673 ton. Given that $CO_2$ absorption in forests is an important factor that reduces greenhouse gas emissions, the findings of this study should provide fundamental information for supporting a wide range of decision-making processes for land use and management.

• Journal of the Korean Geographical Society
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• v.38 no.5
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• pp.667-685
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• 2003

To address the requirements of gap analysis for species protection, as well as the needs of state and federal agencies for detailed digital land cover, a 43-class map at the vegetation alliance level was created for the state of Kansas using multi-temporal Thematic Mapper imagery. The mapping approach included the use of three-date multi-seasonal imagery, a two-stage classification approach that first masked out cropland areas using unsupervised classification and then mapped natural vegetation with supervised classification, visualization techniques utilizing a map of small multiples and field experts, and extensive use of ancillary data in post-hoc processing. Accuracy assessment was conducted at three levels of generalization (Anderson Level I, vegetation formation, and vegetation alliance) and three cross-tabulation approaches. Overall accuracy ranged from 51.7% to 89.4%, depending on level of generalization, while accuracy figures for individual alliance classes varied by area covered and level of sampling.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.29-36
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• 2011

Evapotranspiration (ET) from the various surfaces needs to be understood because it is a crucial hydrological factor to grasp interaction between the land surface and the atmosphere. A traditional way of estimating it, which is calculating it empirically using lysimeter and pan evaporation observations, has a limitation that the measurements represent only point values. However, these measurements cannot describe ET because it is easily affected by outer circumstances. Thus, remote sensing technology was applied to estimate spatial distribution of ET. In this study, we estimated major components of energy balance method (i.e. net radiation flux, soil heat flux, sensible heat flux, and latent heat flux) and ET as a map using Mapping Evapo-Transpiration with Internalized Calibration (METRIC) satellite-based image processing model. This model was run using Landsat imagery of Gyeongan watershed in Korea on Feb 1, 2003 and Sep 13, 2006. Basic statistical analyses were also conducted. The estimated mean daily ETs had respectively 22% and 11% of errors with pan evaporation data acquired from the Suwon Weather Station. This result represented similar distribution compared with previous studies and confirmed that the METRIC algorithm had high reliability in the watershed. In addition, ET distribution of each land use type was separately examined. As a result, it was identified that vegetation density had dominant impacts on distribution of ET. Seasonally, ET in a growing season represented significantly higher than in a dormant season due to more active transpiration. The ET maps will be useful to analyze how ET behaves along with the circumstantial conditions; land cover classification, vegetation density, elevation, topography.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.2 s.20
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• pp.39-47
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• 2002

For the purpose of data construction for the systematic management and sight-seeing guidance of the natural park, the Kumoh Mt. Province Park was selected as a pilot area. Digital topographic maps, thematic maps and satellite imagery covering the object area were processed and then landform analysis for elevation, slope, aspect and so on was conducted through DEM generation, and the landcover map and NDVI maP were extracted from Landsat TM data. The database was then constructed with these spatial data for GSIS. The image map was generated from IKONOS satellite data, which cover the pilot area data, with one meter resolution and also 3D visualization which was overlaid with main paths up a mountain were conducted. And the moving image files were produced along main paths up including main natural spectacular sights, cultural assets and management facilities. It is expected that the research result can be utilized as the fundamental data for re-assessing suitable land use and constructing Web-based guidance system.

• Korean Journal of Ecology and Environment
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• v.47 no.3
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• pp.146-159
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• 2014

In this study, we evaluated the temporal changes of water quality in the 90 reservoirs in Korea and the relationships between water quality and their environmental factors in the reservoirs for effective management of reservoirs. The majority of study reservoirs were categorized as the eutrophic state based on Carlson's trophic index. Among 90 reservoirs, more than 55.0% were nutrient-rich based on $TSI_{TP}$ in each month, where more than 50.0% were nutrient-rich based on $TSI_{Chl-a}$ from June to November. Seasonal Mann-Kendall test was used to analyze temporal variation of water quality in the selected 60 reservoirs using monthly data from 2004 to 2008. The results showed that 27 (45.0%) reservoirs showed the improvement of water quality based on TP and Chl-a concentrations, while 14 (23.3%) and 11 (18.3%) reservoirs displayed the degradation of water quality based on TP and Chl-a concentrations, respectively. Meanwhile, a self-organizing map classified the study reservoirs into five groups based on differences of hydrogeomorphology (altitude, catchment area, bank height, lake age, etc.). Physicochemical factors and land use/cover types showed clear differences among groups. Finally, hydrogeomorphology of reservoirs were related to water quality, indicating that the hydrogeomorphological characters strongly affect water quality of reservoirs.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.13-22
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• 2009

Urban expansion has caused environmental problems, traffic jam and real estate. Trend analysis of Urban expansion is needed for analysis and prediction of the existing problem-solving, urban planning and land use. In this study, We constructed database based on MOE(Minister of environment)'s landcover(1980's, 2000's), 1: 25,000 digital topographical map using of DEM and data of the National Statistical Office for urban and build up expand analysis of South Korea. As a result, The rate of increase in population of Gyeonggi-do, Incheon and Ulsan are high but Jeollanam-do is low. Area of development zone was 2.15 fold increase in comparison with before it. Slope aspect is south or east and urban expansion was increase in district such as Chungcheongnam-do, Gyeonggi-do, Jeollanam-do. Existing road of accessibility was high than development zone. Metropolitan city developre it. In conclusion, we found that South Korea urban expansion was developed from metropolitan city. In natural topographical conditions, the development was progress advantageous zone to disadvantageous zone. Also, we found that population was rapidly increase with new development as the center zone in urban expansion zone.

• Journal of Environmental Science International
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• v.27 no.8
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• pp.665-675
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• 2018

The purpose of this study was to identify the characteristics of the home range and habitat use of Rhinolophus ferrumequinum individuals that inhabit urban areas. The bats were tracked using GPS tags. For analysis of the home rage, Minimum Convex Polygon (MCP) and Kernel Home Range (KHR) methods were used. The landscape types of all positional information were analyzed using ArcGIS 9.3.1 (ESRI Inc.). The average home range of 16 R. ferrumequinum individuals was $68.63{\pm}25.23ha$, and the size of the overall home range for the females ($85.49{\pm}25.40ha$) was larger than that for the males ($51.76{\pm}8.30ha$). The highest average home range for the males was found in August ($61.21{\pm}0.01ha$), whereas that for the females was found in September ($112.27{\pm}5.94ha$). The size of 50% KHR ranged from a minimum of 13.26 ha to a maximum of 31.00 for the males and a minimum of 8.02 ha to a maxinum of 42.16 ha for the females, showing no significant differences between the two sexes. In addition, males and females showed no differences in the size of 50% KHR in the monthly comparisons. However, the females showed differences in the size of their core area between periods before and after giving birth. The comparisons between 100% MCP and 50% KHR showed that the types of habitats used by R. ferrumequinum were mostly forest areas, including some farmlands. In addition, comparisons with a land cover map showed that the proportion of broad-leaved forests was the highest, followed by that of mixed forests.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1277-1290
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• 2020

Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.