• Korean Journal of Environment and Ecology
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• v.28 no.4
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• pp.393-403
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• 2014

The aim of this study was to use the information deduced from biotopemap in Boryeong, Chungnam province conducted in 2011 and to select the wildlife survey point. The information used for the study was deduced from the knowledge and experience of wildlife specialists and was realized by 6 environmental variables (Outside distance from food vegetation, Outside distance from farm land, Outside distance from forest, Human density, Outside distance from road, Outside distance from water). 6 environmental variables were modeled by map overlay method and the model could deduce the correlation of 94.72% as a result of comparing with occurrence information. The areas predicted to have many occurrences were rural landscapes, forests, and valleys, and they can be used to deduce the quality wildlife survey results in the limit of survey range (area, schedule, and budget). However, it had the limit points such as the inside of forests was excluded, all species did not prefer the same habitat. The following studies are needed for this part in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.236-256
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• 2011

Forest carbon stocks change due to land use change is an important data required by UNFCCC(United Nations framework convention on climate change). Spatially explicit estimation of forest carbon stocks based on IPCC GPG(intergovernmental panel on climate change good practice guidance) tier 3 gives high reliability. But a current estimation which was aggregated from NFI data doesn't have detail forest carbon stocks by polygon or cell. In order to improve an estimation remote sensing and GIS have been used especially in Europe and North America. We divided research trends in main countries into 4 categories such as remote sensing, GIS, geostatistics and environmental modeling considering spatial heterogeneity. The easiest way to apply is combination NFI data with forest type map based on GIS. Considering especially complicated forest structure of Korea, geostatistics is useful to estimate local variation of forest carbon. In addition, fine scale image is good for verification of forest carbon stocks and determination of CDM site. Related domestic researches are still on initial status and forest carbon stocks are mainly estimated using k-nearest neighbor(k-NN). In order to select suitable method for forest in Korea, an applicability of diverse spatial data and algorithm must be considered. Also the comparison between methods is required.

• Proceedings of the KSRS Conference
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• v.2
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• pp.570-573
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• 2006

College GIS and remote sensing education usually consists of commercial software packages implementations in the classroom. Computer programming is quite important when college graduates work in private or public sectors relevant with GIS and remote sensing implementations. The objective of this paper was to develop a valley management system which implements GIS and remote sensing as the key components for education. The Valley Authority is entitled with water resource protection for sustainable drinking water supply of the second largest city in Taiwan. The test area consists of three different government agencies, Forest Service, EPA, and Water Resource Agency. Materials were provided by the Valley Authority in ArcGIS file format. MapObjects have made the GIS development process much easier. Remote sensing with image manipulation functions were provided by computer programming with Visual Baisc.NET and Visual C#.NET. Attributes inquiry are performed by these two computer languages as well. ArcGIS and ArcPad are also used for simple GIS manipulations of the test area. Comparison between DIY and commercial GIS can be made by college students. Functions provided by the developed valley management system depending on how many map layers have been used and what types of MapObjects components have been used. Computer programming experience is not essential but can be helpful for a college student. The whole process is a step-by-step sequence which college students can modify to depict their capability in GIS and remote sensing. The development process has gone through one semester, three hours every week in 18 weeks. College students enrolled in this class entitled with GIS showed remarkable progresses both in GIS and remote sensing.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.2
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• pp.199-205
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• 2009

A simple and effective analysis method is presented for predicting the best infiltration area. Based on geospatial information, numerical estimation barometer for degree of infiltration risk has been derived. The dominant geospatial features influencing infiltration risk have been found to be area altitude, degree of surface gradient, relative direction of surface gradient to the surveillance line, degree of surface gradient repetition, regional forest information. Each feature has been numerically expressed corresponding to the degree of infiltration risk of that area. Four different detection probability maps of infiltration risk for the surveillance area are drawn on the actual map with respect to the numerically expressed five dominant factors of infiltration risks. By combining the four detection probability maps, the complete picture of thr best infiltration area has been drawn. By using the map and the analytic method the effectiveness of surveillance operation can be improved.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.27-42
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• 2016

Forest accounts for almost 64 percents of total land cover in South Korea. For inventorying, monitoring, and managing such large area of forest, application of remote sensing and geographic information system (RS/GIS) technology is essential. On the basis of spectral characteristics of satellite imagery, forest cover and tree species can be classified, and forest cover map can be prepared. Using three dimensional data of LiDAR(Light Detection and Ranging), tree location and tree height can be measured, and biomass and carbon stocks can be also estimated. In addition, many indices can be extracted using reflection characteristics of land cover. For example, the level of vegetation vitality and forest degradation can be analyzed with VI (vegetation Index) and TGSI (Top Grain Soil Index), respectively. Also, pine wilt disease and o ak w ilt d isease c an b e e arly detected and controled through understanding of change in vegetation indices. RS and GIS take an important role in assessing carbon storage in climate change related projects such as A/R CDM, REDD+ as well. In the field of climate change adaptation, impact and vulnerability can be spatio-temporally assessed for national and local level with the help of spatio-temporal data of GIS. Forest growth, tree mortality, land slide, forest fire can be spatio-temporally estimated using the models in which spatio-temporal data of GIS are added as influence variables.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.4
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• pp.81-90
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• 2005

Based on the landslide hazard scoring system of Korea Forest Research Institute, a GIS model for predicting landslide hazards was developed. The risk of landslide hazards was analyzed as the function of 7 environmental site factors for the terrain, vegetation, and geological characteristics of the corresponding forest stand sites. Among the environmental factors, slope distance, relative height and shapes of slopes were interpreted using the forestland slope interpretation module developed by Chung et al. (2002). The program consists of three modules for managing spatial data, analyzing landslide hazard and report-writing, A performance test of the model showed that 72% of the total landslides in Youngin-Ansung landslides area took place in the highly vulnerable zones of grade 1 or 2 of the landslide hazard scoring map.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.329-338
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• 2011

The time-series normalized difference vegetation index (NDVI) product has proven to be a powerful tool to investigate the phenological information because it can monitor the change of the forests with very high time-resolution, This study described the application of the DFT analysis over the 9 year MODIS data for the identification of the two types of vegetation cover, Pinus densiflora(Pd) and Querqus mongolica(Qm) which are dominant species of evergreen and broadleaved deciduous forest, respectively, The total number of samples was 5148 reference cycles which consist of 2160 Pd and 2988 Qm. They were extracted from the pixel-based MODIS scenes over the 9 years from 2000 to 2008 of South Korea. The DFT analysis was mainly focused on the 0th and $1^{st}$ harmonic components, each of which represents the mean value and the variation amplitude of the NDVI over the years, respectively. The $0^{th}$ harmonic values of the vegetation Pd and Qm averaged over the 9 years were 0.74 and 0.65, respectively. This implies that Pd has a higher NDVI than Qm. Similarly obtained $1^{st}$ harmonic values of Pd and Qm were 0.19 and 0.27, respectively. This can be intuitively understood considering that the seasonal variation of Qm is much larger than Pd. This distinctive difference of the $1^{st}$ harmonic value has been used to identify evergreen and deciduous forests. Overall agreement between the Fourier analysis-based map and the actal vegetation map has been estimated to be as high as 75%. This study found that the DFT analysis can be a concise and repeatable method to separate and trace the changes of evergreen and deciduous forest using the annual NDVI cycles.

• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.311-320
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• 2009

This study was carried out to estimate forest biomass and to produce forest biomass thematic map for Muju county by combining field data from the 5$^{th}$ National Forest Inventory (2006-2007) and satellite data. For estimating forest biomass, two methods were examined using a Landsat TM-5(taken on April 28th, 2005) and field data: multi-variant regression modeling and t-Nearest Neighbor (k-NN) technique. Estimates of forest biomass by the two methods were compared by a cross-validation technique. The results showed that the two methods provide comparatively accurate estimation with similar RMSE (63.75$\sim$67.26ton/ha) and mean bias ($\pm$1ton/ha). However, it is concluded that the k-NN method for estimating forest biomass is superior in terms of estimation efficiency to the regression model. The total forest biomass of the study site is estimated 8.4 million ton, or 149 ton/ha by the k-NN technique.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.305-309
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• 2006

SAR (Synthetic Aperture Radar) technology, which is not influenced by cloud cover because of using electromagnetic wave of long wavelength, has an advantage in mapping the earth. NASA, recognizing these strong points of SAR, launched SRTM (Shuttle Radar Topography klission), and acquired the topographic information of the earth. SRTM and NED (National Elevation Data) of USGS were used for the research and vegetation height map was produced through differentiating the two data. Correlation between SRTM-NED and planting year was analyzed to see the relationship. Strong correlation was detected and it shows the feasibility of estimating timber age and eventually creating timber age map from SRTM-NED. Additional analyses were conducted to check if the linearity is influenced by regional characteristics and forest uniformity. As results, the correlation between SRTM-NED and timber age is influenced by roughness of the terrain. Overall, this paper shows that timber age estimation using SRTM and NED can be sufficiently practical.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.86-96
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• 2006

Ecoclimap-1, a new complete surface parameter global database at a 1-km resolution, was previously presented. It is intended to be used to initialize the soil-vegetation- atmosphere transfer schemes in meteorological and climate models. Surface parameters in the Ecoclimap-1 database are provided in the form of a per-class value by an ecoclimatic base map from a simple merging of land cover and climate maps. The principal objective of this ecoclimatic map is to consider intra-class variability of life cycle that the usual land cover map cannot describe. Although the ecoclimatic map considering land cover and climate is used, the intra-class variability was still too high inside some classes. In this study, a new strategy is defined; the idea is to use the information contained in S10 NDVI SPOT/VEGETATION profiles to split a land cover into more homogeneous sub-classes. This utilizes an intra-class unsupervised sub-clustering methodology instead of simple merging. This study was performed to provide a new ecolimatic map over Northeast Asia in the framework of Ecoclimap-2 global database construction for surface parameters. We used the University of Maryland's 1km Global Land Cover Database (UMD) and a climate map to determine the initial number of clusters for intra-class sub-clustering. An unsupervised classification process using six years of NDVI profiles allows the discrimination of different behavior for each land cover class. We checked the spatial coherence of the classes and, if necessary, carried out an aggregation step of the clusters having a similar NDVI time series profile. From the mapping system, 29 ecosystems resulted for the study area. In terms of climate-related studies, this new ecosystem map may be useful as a base map to construct an Ecoclimap-2 database and to improve the surface climatology quality in the climate model.