• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.2
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• pp.109-123
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• 2014

Kaloula borealis is the species of Amphibia which belongs to Kaloula genus and it is the only species inhabiting in Korea. The population size and habitat of Kaloula borealis have been significantly decreased on a national scale due to the diversified developments and the uses of agricultural pesticides. Accordingly, the Ministry of Environment has designated and managed them as the class II of endangered species, in accordance with "Endangered Species Protection and Management Act"; however, a particular study focused on the ecological restoration of Kaloula borealis is desperately needed to prevent their extinction. This study was conducted to propose the HSI (Habit Suitability Index) of Kaloula borealis based on literature survey on ecology and habitats of Kaloula borealis, as well as their HSI. Factors to be investigated in HSI include: space, feed, cover, water(breeding) and threatening factors and the variables of each factor were also proposed. The distance from wetland, grassland, farm, stream and rice paddy, as well as the altitude of spawning pond were proposed as the variables of space, whereas the bed structure of forest and low-rise grassland were proposed as the variables of feeding. The variables of water (breeding) include the area of permanent and temporary wetlands, coverage of emerged pants (ratio of open water), water depth, water temperature, water quality, pH level, etc., whereas the presence of predator, distance from street and pollutants were proposed as the variables of threatening factor. The sub-standards by HSI factor of Kaloula borealis have been drawn from in-depth consultation with experts and based on this, the final HSI of Kaloula borealis was developed.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.287-305
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• 2016

Over the past half century, satellites have continuously expanded their roles in remote sensing applications. As the number of satellites to be launched are expected to continuously increase in coming years, the research on satellite payloads will be in high demands. Earth Observation (EO) satellites are nowadays widely utilized for various purposes. Especially, Agriculture and forestry applications are considered as their major application areas. Since about 85% of domestic land cover is classified as forest or cropland areas, it would be reasonable to suggest that the demand for these satellites should be of high priority. In this paper, a comprehensive analysis is performed on the technical specifications of satellite payloads that may be applicable to agricultural applications. We attempted to build a solid database on payload specifications by collecting relevant information available from various related institutes and academic research works. A number of experts involved in national agricultural research and satellite development programs have been invited to investigate required payload design. Based on the current technology development status and future plan, multiple options for future satellite payload designs have been suggested bearing in mind that the results may be applicable to the future agriculture and forestry satellite payload design. The proposed payload specifications are analyzed in depth through satellite operation simulations under the mission of observing the national agriculture areas. The proposed design scheme and simulation results may be used as technical references to satellite payload design for future space missions.

• Korean Journal of Remote Sensing
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• v.33 no.6_3
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• pp.1223-1232
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• 2017

This paper presents an approach to detect changes caused by urban development over a large area using KOMPSAT optical images. In order to minimize the radiometric dissimilarities between the images acquired at different times, we apply the grid-based rough radiometric correction as a preprocessing to detect changes in a large area. To improve the accuracy of the change detection results for urban development, we mask-out non-interest areas such as water and forest regions by the use of land-cover map provided by the Ministry of Environment. The Change Vector Analysis(CVA) technique is applied to detect changes caused by urban development. To confirm the effectiveness of the proposed approach, a total of three study sites from Sejong City is constructed by combining KOMPSAT-2 images acquired on May 2007 and May 2016 and a KOMPSAT-3 image acquired on March 2014. As a result of the change detection accuracy evaluation for the study site generated from the KOMPSAT-2 image acquired on May 2007 and the KOMPSAT-3 image acquired on March 2014, the overall accuracy of change detection was about 91.00%. It is demonstrated that the proposed method is able to effectively detect urban development changes in a large area.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.167-178
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• 2018

Urban green areas or forest regions play an important role in lowering the air temperature of the surrounding areas. This cooling effect does not only affect inside of the green areas, but also extends into neighboring streets and buildings. In this study, the Land Surface Temperature (LST) are retrieved from the Landsat 8 satellite data for 8 clear days in Seoul, Korea from 2013 to 2015, and used for analyzing the cooling effect at an urban green region, Seonjeongneung, located in the southern part of Seoul. The LST distribution from the boundary of the Seonjeongneung presents that the cooling effect of the green areas was found to extend in many directions into the urban areas. The LST estimations of residential and commercial areas around the Seonjeongneung are also analyzed to assess how the green areas affect the type of land cover and the surroundings in the urban areas. Relatively lower LST for the residential areas from the Seonjeongneung boundary ranges from 100 to 250 m, resulting in an average cooling effect of $2.3^{\circ}C$. On the other hand, the LST distribution in the commercial areas shows that the effective distance of green areas are relatively low in the range of 0 to 200 m, which means the average cooling effect is approximately $0.3^{\circ}C$. This result shows that the cooling effect of the Seonjeongneung is clearly noticeable, particularly, the residential areas show greater cooling effect than commercial areas.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.71-91
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• 2018

In recent years, application of UAV(Unmanned Aerial Vehicle) to seed sowing and pest control has been actively carried out in the field of agriculture. In this study, UAS(Unmanned Aerial System) is constructed by combining image sensor of various wavelength band and SfM((Structure from Motion) based image analysis technique in UAV. Utilization of UAS based vegetation survey was investigated and the applicability of precision farming was examined. For this purposes, a UAS consisting of a combination of a VIS_RGB(Visible Red, Green, and Blue) image sensor, a modified BG_NIR(Blue Green_Near Infrared Red) image sensor, and a TIR(Thermal Infrared Red) sensor with a wide bandwidth of $7.5{\mu}m$ to $13.5{\mu}m$ was constructed for a low cost UAV. In addition, a total of ten vegetation indices were selected to investigate the chlorophyll, nitrogen and water contents of plants with visible, near infrared, and infrared wavelength's image sensors. The images of each wavelength band for the test area were analyzed and the correlation between the distribution of vegetation index and the vegetation index were compared with status of the previously surveyed vegetation and ground cover. The ability to perform vegetation state detection using images obtained by mounting multiple image sensors on low cost UAV was investigated. As the utility of UAS equipped with VIS_RGB, BG_NIR and TIR image sensors on the low cost UAV has proven to be more economical and efficient than previous vegetation survey methods that depend on satellites and aerial images, is expected to be used in areas such as precision agriculture, water and forest research.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.4
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• pp.92-103
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• 2017

As a professional occupation, landscape education focuses on fostering professional human resources and is one of the major axes of the landscape industry. In this study, a survey of landscape students on their learning and pedagogics was conducted with the aim to present basic information for the improvement of teaching on landscape construction. A total of 348 people answered 14 questions in the category of the impression of landscape construction classes included in the questionnaire. The results showed that the students found landscape construction classes academically important and recognized the necessity for completing these classes, but they were not satisfied with the learning environments and pedagogics used in these classes. They found what they learned not readily applicable to actual practice and saw these classes as part of their preparations for the landscape engineer qualification test. Their demands in relation to the classes included field practice-oriented teaching and participation in various programs for field practice, which highlights the necessity for human resource management-oriented classes that cover planning, design, construction, and management. Challenges in relation to field practice included the provision of environment, for example offering a variety of opportunities and improving treatment in practice. This study has significance in that it analyzed the views of students and discussed directions for future improvement since there is a lack of studies and discussions about education in the field of landscape construction. This study also has a limitation that only four-year universities were included in the study. Comprehensive studies including investigating junior college and graduate school curricula and case studies of landscape construction curricula overseas are needed in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.61-72
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• 2008

Leaf area index (LAI) is a key biophysical variable influencing land surface processes such as photosynthesis, transpiration and energy balance, and is a required input to estimate evapotranspiration in various ecological and hydrological models. The development of more correct and useful LAIs estimation techniques is required by these importance, but LAIs had been assumed in most LAI research through simple relations with the normalized difference vegetation index (NDVI) because the field measurement is difficult on wide area. This paper is to evaluate the MODIS LAI Product's practical use by comparing with LAIs that is derived from NOAA AVHRR NDVIs and the 2 years (2003-2004) measured LAIs of Korea Forest Research Institute in Gyeongancheon watershed (561.12 $Km^2$). As a result, the MODIS LAIs of deciduous forests showed higher values about 14 % and 15~30 % than the measured LAIs and NOAA LAIs. In the year of 2003, the MODIS LAIs in coniferous forests were 5 % higher than the measured LAIs, and showed about 7 % differences comparing with the NOAA LAIs except April. These differences come from the insufficient field data measured in partial points of the target area, and the extracted reference data from MODIS LAIs include the limits of spatial resolution and the error of incorrect land cover classification. Thus, using the MODIS data by the proper correction with the measured data can be useful as an input data for ecological and hydrological models which offers the vegetation information and simulates the water balance of a given watershed.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.29-33
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• 2010

The purpose of LiDAR ground classification is to archive both goals which are acquiring confident ground points with high precision and describing ground shape in detail. In spite of many studies about developing optimized algorithms to kick out this, it is very difficult to classify ground points and describing ground shape by airborne LiDAR data. Especially it is more difficult in a dense forested area like Korea. Principle misclassification was mainly caused by complex forest canopy hierarchy in Korea and relatively coarse LiDAR points density for ground classification. Unfortunately, a lot of LiDAR surveying performed in summer in South Korea. And by that reason, schematic LiDAR points distribution is very different from those of Europe. So, this study propose enhanced ground classification method considering Korean land cover characteristics. Firstly, this study designate highly confident candidated LiDAR points as a first ground points which is acquired by using big roller classification algorithm. Secondly, this study applied weighted gradient kernel(WGK) algorithm to find and include highly expected ground points from the remained candidate points. This study methods is very useful for reconstruct deformed terrain due to misclassification results by detecting and include important terrain model key points for describing ground shape at site. Especially in the case of deformed bank side of river area, this study showed highly enhanced classification and reconstruction results by using WGK algorithm.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.11-18
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• 2012

Increasing concern about biodiversity has lead to a rise in demand on the spatial assessment of biological resources such as biodiversity assessment, protected area selection, habitat management and restoration in Korea. The purpose of this study is to create species richness map through data collection and modeling techniques for wildlife habitat assessment. The GAM (Generalized Additive Model) is easy to interpret and shows better relationship between environmental variables and a response variable than an existing overlap analysis and GLM (Generalized Linear Model). The study area delineated by a large watershed contains Jirisan national park, Mt. Baekun and Sumjin river with three kinds of protected areas (a national park, a landscape ecology protected area and an otter protected area). We collected the presence-absence data for wildlife (mammals and birds) using a stratified random sampling based on a land cover in the study area and implemented natural and socio-environmental data affecting wildlife habitats. After doing a habitat use analysis and specifying significant factors for each species, we built habitat suitability models using a presence-absence model and created habitat suitability maps for each species. Biodiversity maps were generated by taxa and all species using habitat suitability maps. Significant factors affecting each species habitat were different according to their habitat selection. Although some species like a water deer or a great tit were distributed at the low elevation, most potential habitats for mammals and birds were found at the edge of a national park boundary or near a forest around the medium elevation of a mountain range. This study will be used for a basis on biodiversity assessment and proected area selection carried out by Ministry of Environment.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.2
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• pp.47-64
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• 2013

Landscape structure changes over the past three decades were determined with land use and land cover(LULC) maps, and their relationships with mean air temperature time series were the analyzed for the Busan metropolitan area and South Kyeongsang Province, Korea. The geometric structures of the LULC data were quantitatively represented based on FRAGSTATS, a spatial pattern analysis program for quantifying landscape structure. FRAGSTATS-derived landscape metrics confirmed that there were major changes in LULC and landscape fragmentation in the region. Meteorological observation records showed that mean air temperature had increased from $14.1^{\circ}C$ in the 1990's to $14.8^{\circ}C$ in the 2000's in Busan. For South Kyeongsang Province, they increased from $13.2^{\circ}C$ to $13.9^{\circ}C$ during the same time period. These long-term temperature changes are correlated with typical spatial pattern changes of LULC in the southeastern region of the country. Spatial metrics analysis showed that urban area expanded from 9.7% to 26.8% of Busan while forest and agricultural land decreased by 9.6% and 14.9%, respectively over the past thirty years. The significant urbanization are tightly associated with deforestation, removal of agricultural land, and fast temperature increases since the 1990's. The urban area of South Kyeongsang Province rapidly increased, and it became 12 times as large as it was. The degree of temperature increases differed among three different sub-regions. The temperature increasing rate was lowest in the coastal region while the colder mountainous region had the highest figure.