• Journal of Korean Society of Forest Science
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• v.94 no.6
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• pp.431-440
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• 2005

Location, height and clear-length of individual tree can be measured directly by LiDAR Remote Sensing, and dbh(diameter at breast height) can be estimated indirectly by tree height measured by LiDAR. In addition, stand volume and stand biomass are computed from estimated growth factors. In this study, each estimated growth factor was compared to the field measurements to validate accuracy. The coefficient of determination of total tree heights was 0.66 for total trees, 0.68 for Pinus koraiensis, 0.66 for Larix leptolepis and 0.60 for Quercus spp. The coefficient of determination of clear-length was 0.79 for total trees, 0.73 for Pinus koraiensis, 0.79 for Larix leptolepis, 0.68 for Quercus spp. The coefficient of determination of dbh predicted was 0.73 for Pinus koraiensis, 0.73 for Larix leptolepis and 0.85 for Quercus spp. Moreover The coefficient of determination of basal area was 0.82 for Pinus koraiensis, 0.92 for Larix leptolepis and 0.95 for Quercus spp. Biomass per ha computed by growth factor using LiDAR was 40,306 dm/ha for Pinus koraiensis, 94,150 tdm/ha for Larix leptolepis and 94,481 tdm/ha for Quercus spp. by species.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.507-513
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• 2021

GPR (Ground Penetrating RADAR) is a sensor that inspects the pavement state of roads, sinkholes, and underground pipes. It is widely used in road management. MMS (Mobile Mapping System) creates a detailed and accurate road map of the road surface and its surroundings. If both types of data are built in the same area, it is efficient to construct both ground and underground spatial information at the same time. In addition, since it is possible to grasp the road and important facilities around the road, the location of underground pipelines, etc. without special technology, an intuitive understanding of the site is also possible, which is a useful tool in managing the road or facilities. However, overseas equipment to which this latest technology is applied is expensive and does not fit the domestic situation. LiDAR (Light Detection And Raging) and GNSS/INS (Global Navigation Satellite System / Inertial Navigation System) were synchronized in order to replace overseas developed equipment and to secure original technology to develop domestic equipment in the future, and GPR data was also synchronized to the same GNSS/INS. We developed software that performs georeferencing using the location and attitude information from GNSS/INS at the time of acquiring synchronized GPR data. The experiments were conducted on the road site by dividing the open sky and the non-open sky. The road and surrounding facilities on the ground could be easily checked through the 3D point cloud data acquired through LiDAR. Georeferenced GPR data could also be viewed with a 3D viewer along with point cloud data, and the location of underground facilities could be easily and quickly confirmed through GPR data.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.5
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• pp.20-30
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• 2007

Environmental Conservation Value Assessment Map (ECVAM) is the class map to divide the national land into conservation areas and development areas based on legal and ecological assessment criteria. It contributes to enhancements of the efficiency and the scientificity when framing a policy in various fields including the environment. However, it is impossible to understand the multiphase vegetation structure as data on judging the national forest class in ECVAM are restricted to areal information of Ecological Nature Status, Degree of Green Naturality and Forest Map. This point drops the reliability of ECVAM. Therefore we constructed vegetation information using LiDAR (Light Detection And Raging) technology. We generated Biomass Class Maps as final results of this study, to introduce the new forest assessment criterion in ECVAM that alternates or makes up for existing forest assessment criteria. And then, we compared these with Forest Map and Landsat TM NDVI image. As a result, biomass classes are generally higher than stand age classes and DBH classes of Vegetation Map, and lower than NDVI of Landsat TM image because of the difference of time on data construction. However distributions between these classes are mostly similar. Therefore we estimates that it is possible to apply the biomass item to the new forest assessment criterion of ECVAM. The introduction of the biomass in ECVAM makes it useful to detect the vegetation succession, to adjust the class of the changed zone since the production of Vegetation Map and to rectify the class error of Vegetation Map because variations on tree heights, forest area, gaps between trees, vegetation vitality and so on are acquired as interim findings in process of computing biomass.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.543-551
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• 2006

Recently efforts to extract information about forests by using remote sensing techniques for efficient forest management have progressed actively. In terms of extraction of tree information using single remote sensing data, however, the accuracy of tree recognition and the quantity of extracted information is limited. The objective of this study is to carry out tree modeling in domestic environment applying the latest core technique for tree modeling using color aerial photographs and LiDAR data and to estimate the result of tree modeling. A small-scale coniferous forest was investigated in Daejeon. It was 0.77 that the $R^2$ of accuracy test of tree numbers that estimated with color aerial photography and LiDAR data. In terms of tree height, there was no difference between the estimated value and the field measurements in the case of the group accuracy test of the recently unchanged area. Moreover $R^2$ was 0.83 in the case of the individual accuracy test.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.159-171
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• 2012

This study has developed a technology for river basin including the management of the data related with riverbed and the analysis of the riverbed maintenance based on the high-resolution imagery data and LiDAR (Light Detection and Raging) in order to enhance the utilization of river management by using RIMGIS(River Information Management GIS) and to acquire the advanced operation for river management. Using the detailed river topographical map specially designed in the form of LiDAR or high-resolution images, riverbed data and river bank channel information that are dynamically changed were informationized and established in the RIMGIS DB. At this stage, a monitoring techniques that is established in the river management system associated with RIMGIS and minimized the impact of riverbed maintenance (fluctuations) has been studied. In addition, functions and data structure of RIMGIS containing the information of geography and management of the river have been supplemented to make an improvement of the real-time management of the river. Furthermore, a technology that is capable of supplementing RIMGIS has been developed, making it feasible to maintain the river in use of structural method including an structural scheme of cross-section of the river by providing the information of riverbed and cross-section of the river. This is considered to solve an issue of insufficient data on accuracy and based on a lack of information of the river based on the two-dimensional lines, making it feasible to (steadily) improve the function of RIMGIS and to operate management tasks. Therefore, it is highly expected to enhance aforementioned technology of the river information management as a great foundation that maximizes the utilization of the river management to support RIMGIS for the development of national river management data.