• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.2
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• pp.93-108
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• 2014

The inventory list of wildlife species inhabiting or distributing in Gyeonggi Province was made by compiling species data from precedent surveys, 10 national level nature surveys, 1 survey that Gyeonggi-do conducted, and 46 local surveys presented in scientific journals. Total 2,913 wildlife species including 2,041 vascular plants, 39 mammals, 304 birds, 34 herptiles, 145 fish, and 350 benthic macro-invertebrates were listed in the inventory. It explains 47% of nationwide total species in vascular plants, 31.5% in mammals, 58.2% in birds, 65.4% in herptiles, 12.2% in fish. The total number of important species including endangered species, national monuments, national red lists, etc. was 628 species, accounting for 21.6% of all listed species in Gyeonggi Province. More than 90% of endangered bird species, almost half of endangered fish and herptile species were found in Gyeonggi Province. In particular, abundant bird diversity and inhabitation of many endangered bird species were identified in Gyeonggi Province. Species diversity was greater in the northern area adjacent to the Demilitarized Zone and the eastern forest area. The distribution of the important species such as national endangered species was more distinct in these areas, especially in Gapyeong and Yeoncheon Counties. The inventory list compiled in this study implicates the level of management for biological resources and can provide information for policy decisions regarding new survey sites, protection management of specific species and areas, management practices by spatial characteristics. It should be more compiled and updated with survey data to be utilized as basic indices for local biodiversity strategies and management of biological resources.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.69-85
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• 2014

Carbon stocks of NFI plots can be accurately estimated using field survey information. However, an accurate estimation of carbon stocks in other unsurveyed sites is very difficult. In order to fill this gap, various spatial information can be used as an ancillary data. In South Korea, there is the 1:5,000 forest type map that was produced by digital air-photo interpretation and field survey. Because this map contains very detailed forest information, it can be used as the high-quality spatial data for estimating carbon stocks. In this study, we compared three upscaling methods based on the 1:5,000 forest type map and 5th national forest inventory data. Map algebra(method 1), RK(Regression Kriging)(method 2), and GWR(Geographically Weighted Regression)(method 3) were applied to estimate forest carbon stock in Chungcheong-nam Do and Daejeon metropolitan city. The range of carbon stocks from method 2(1.39~138.80 tonC/ha) and method 3(1.28~149.98 tonC/ha) were more similar to that of previous method(1.56~156.40 tonC/ha) than that of method 1(0.00~93.37 tonC/ha). This result shows that RK and GWR considering spatial autocorrelation can show spatial heterogeneity of carbon stocks. We carried out paired t-test for carbon stock data using 186 sample points to assess estimation accuracy. As a result, the average carbon stocks of method 2 and field survey method were not significantly different at p=0.05 using paired t-test. And the result of method 2 showed the lowest RMSE. Therefore regression kriging method is useful to consider spatial variations of carbon stocks distribution in rugged terrain and complex forest stand.

• Journal of Korean Society of Forest Science
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• v.97 no.4
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• pp.445-451
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• 2008

This study was carried out to develop Tablet PC based customizing system for fine mapping of forest cover type. The major contents and characteristics of FIS developed in this study were as follows. Field Investigation System (FIS) has a merit of accessibility to display exact location in various spatial data with position information received from the GPS. FIS can be used to record and manage many field information on which field investigation is done, with the help of the memo tool, field-sheet tool, calculating distance and area with measuring tool as well as editing forest type. It is possible to do field investigation effectively using FIS developed in this study. Accordingly, investigation and time costs can be reduced and field-work productivity will be improved.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.6
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• pp.65-78
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• 2023

In recent times, the frequency and intensity of natural disasters, such as heavy rains and typhoons, have been increasing due to the impacts of climate change. This has led to a rise in social and economic damages. Rural areas, in particular, possess limited disaster response capabilities due to their underdeveloped infrastructure and are highly vulnerable to flooding. Therefore, it is crucial to establish preventative and responsive measures. In this study, an Inventory-Based Flood Loss Estimation (IB-FLE) method utilizing high-resolution spatial information was developed for estimating flood-related losses in rural areas. Additionally, the developed approach was applied to a study area and compared with the Multidimensional Flood Damage Analysis (MD-FDA) method. Compared to the MD-FDA, the IB-FLE enables faster and more accurate estimation of flood damages and allows for the assessment of individual building and agricultural land losses using up-to-date information. The findings of this study are expected to contribute to the rational allocation of budgets for rural flood damage prevention and recovery, as well as enhancing disaster response capabilities.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.2
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• pp.44-55
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• 2018

The importance of establishing a greenhouse gas inventory is emerging for policymaking and its implementation to cope with climate change. Thus, it is needed to establish Approach 3 level Land Use, Land-Use Change and Forestry (LULUCF) matrix that is spatially explicit regarding land use classifications and changes. In this study, four types of spatial information suitable for establishing the LULUCF matrix were analyzed - Cadastral Map, Land Cover Map, Forest Map, and Biotope Map. This research analyzed the classification properties of each type of spatial information and compared the quantitative and qualitative characteristics of the maps in Boryeong city. Drawn from the conclusions of the quantitative comparison, the forest area showed the maximum difference of 50.42% ($303.79km^2$) in the forest map and 46.09%($276.65km^2$) in the cadastral map. The qualitative comparison drew five qualitative characteristics: data construction scope difference, data construction purpose difference, classification standard difference, and classification item difference. As a result of the study, it was evident that the biotope map was the most appropriate spatial information for the establishment of the LULUCF matrix. In addition, if the LULUCF matrix is made by integrating the biotope, the forest map, and the land cover map, the limitations of each spatial information would be improved. The accuracy of the LULUCF matrix is expected to be improved when the map of the level-3 land cover map and the biotope map of 1:5,000 covering the whole country are completed.

• Journal of Korean Society of Forest Science
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• v.88 no.3
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• pp.389-399
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• 1999

This study was conducted to develop an application software, SIDAS3D(Stand Inventory Data Analysis System for 3 Dimensional Representation), of which the purpose of development is to make it easier to analyze and display the 3D spatial structure of a forest stand, based on the data such as tree position, species, DBH, height, clear length of individual trees, and crown width. This program has a statistical analysis function for stand attributes per hectare and displays simple graphs of stand statistics such as the distribution of diameters, heights, and volumes. It also has two additional functions, of which one is to display the 3D image of stand structure and the other is to display the image of crown projection. In addition, this program provides an imaginary treatment simulation function, which can visually confirm the suitability of silvicultural treatments on computers. To test the precision and reliability of SIDAS3D, data obtained by the precision forest inventory method were used. Statistical analysis ability of SIDAS3D was compared with that of SAS. And its representational ability was compared with that of TreeDraw. According to the verification, SIDAS3D was superior to SAS and TreeDraw in both the data processing time and the interpretative ability of results. It was concluded that SIDAS3D could be used to help users efficiently make decisions for appropriate silvicultural treatments and rational management plans because it has analysis functions providing various valuable information.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1731-1745
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• 2023

Within the framework of the post-2020 climate regime, the Paris Agreement's emphasis on Nationally Determined Contributions and Biennial Transparency Reporting is paramount in addressing its long-term temperature goal. A salient issue is the treatment of wetland ecosystems within the context of Land Use, Land-Use Change, and Forestry, as defined by the Intergovernmental Panel on Climate Change. In the 2019 National Inventory Report, wetlands were recategorized as emission sources due to their designation as inundated areas. This study employs C-band radar imagery to discriminate between inundated and non-inundated regions of wetlands, enabling the quantification of their spatial dynamics. The research capitalizes on 24-period Sentinel-1 satellite data to cover both the inundation and desiccation phases while centering its attention on Ungok Wetland, a Ramsar-designated inland wetland conservation area in Korea. The inundated area is quantitatively assessed through the integration of multi-temporal Sentinel-1 Single-Look Complex (SLC) data, aerial orthophotography, and inland wetland spatial information. Furthermore, the study scrutinizes fluctuations in the maximum and minimum inundated areas, with substantial changes corroborated via drone aerial reconnaissance. The outcomes of this investigation hold the potential to make substantive contributions to the refinement of national greenhouse gas absorption and emission factors, thereby informing the development of comprehensive greenhouse gas inventories. These efforts align directly with the overarching objectives of the Paris Agreement.

• Journal of Korean Society of Forest Science
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• v.99 no.5
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• pp.770-776
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• 2010

This study was conducted to assess the existing flora and fauna, and to develop a spatial map of Alapang communal forest located in the province of Benguet, Philippines. A total of 52 species belonging to 27 families were identified during the inventory in this communal forest using the quadrat method while a total of 30 species belonging to 18 families were recorded using line intercept technique for the assessment of grasses, herbs, vines and other low-lying vegetation. The diversity index of the species in Alapang communal forests using the quadrat method was 2.6649 while for the line intercept technique it was 2.5446. The most dominant species in this area was found to be Pinus kesiya Royle ex Gordon (Benguet pine) under Family Pinaceae with an importance value of 106.74%. In the faunal assessment, four species of birds and a small mammal particularly a rodent were identified during the study. Aside from the high species diversity of this communal forest, the presence of endemic and indicator species in the area denotes that this forest was still in good condition hence must be protected. Spatial maps and database system were generated based from data gathered in the field using Geographic Information System (GIS).

• Journal of Environmental Health Sciences
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• v.30 no.3
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• pp.293-299
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• 2004

Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence, numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristics of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends is towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a model of vehicle emission calculation by using real-time traffic data was studied. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It is possible that characteristics of hourly air pollutants emission rates is obtained from hourly traffic volume and speed. An emission rates model is allocated with a high resolution space by using geographic information system (GIS). Vehicle emission model was developed with a high resolution spatial, gridded and hourly emission rates.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.597-607
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• 2016

The goal of this study was to analyze landslide susceptibility using two different models and compare the results. For this purpose, a landslide inventory map was produced from a field survey, and the inventory was divided into two groups for training and validation, respectively. Sixteen landslide conditioning factors were considered. The relationships between landslide occurrence and landslide conditioning factors were analyzed using the FR (Frequency Ratio) and EBF (Evidential Belief Function) models. The LSI (Landslide Susceptibility Index) maps that were produced were validated using the ROC (Relative Operating Characteristics) curve and the SCAI (Seed Cell Area Index). The AUC (Area under the ROC Curve) values of the FR and EBF LSI maps were 80.6% and 79.5%, with prediction accuracies of 72.7% and 71.8%, respectively. Additionally, in the low and very low susceptibility zones, the FR LSI map had higher SCAI values compared to the EBF LSI map, as high as 0.47%p. These results indicate that both models were reasonably accurate, however that the FR LSI map had a slightly higher accuracy for landslide susceptibility mapping in the study area.