• Journal of Korean Society of Forest Science
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• v.96 no.3
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• pp.251-258
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• 2007

Airborne Lidar (light detection and ranging) can be an effective alternative in forest inventory to overcome the limitations of conventional field survey and aerial photo interpretation. In this study, we attempt to develop methodologies to identify individual trees and to estimate tree height from airborne Lidar data. Initially, digital elevation model (DEM) data representing the exact ground surface were generated by removing non-ground returns from the multiple-return laser point clouds, obtained over the coniferous forest site of rugged terrain. Based on the canopy height model (CHM) data representing non-ground layer, individual tree heights are extracted through pseudo-grid method and moving window filtering algorithm. Comparing with field survey data and aerial photo interpretation on sample plots, the number of trees extracted from Lidar data show over 90% accuracy and tree heights were underestimated within 1.1m in average at two plantation stands of pine (Pinus koraiensis) and larch (Larix leptolepis).

• Journal of Korean Society of Forest Science
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• v.90 no.6
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• pp.742-746
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• 2001

This study was carried out to develop volume equations for Japanese Res Cedar(Cryptomeria japonica D. Don) trees which were widely planted from 1920s throughout the southern regions in south Korea. The 31 trees for stem analysis were selected in 6 different sites in the southern and 29 trees data were used for developing volume equation. The best equation in estimating Japanese Red Cedar trees's volume was suggested as $V=-0.002908+0.000125D^{1.907114}H^{0.645131}$. The simultaneous F-test for this equation revealed that the estimated individual tree volume was not significantly different (p=0.1936) from the observed tree volume for model evaluation. Therefore, this individual tree volume prediction equation could provide basic information for the construction of yield table and forest management.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1145-1153
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• 2023

Urban trees play an important role in absorbing carbon dioxide from the atmosphere, improving air quality, mitigating the urban heat island effect, and providing ecosystem services. To effectively manage and conserve urban trees, accurate spatial information on their location, condition, species, and population is needed. In this study, we propose an algorithm that uses a high-resolution urban tree cover map constructed from deep learning approach to separate trees from the urban land surface and accurately detect tree locations through local maximum filtering. Instead of using a uniform filter size, we improved the tree detection performance by selecting the appropriate filter size according to the tree height in consideration of various urban growth environments. The research output, the location and height of individual trees in human settlement over Suwon, will serve as a basis for sustainable management of urban ecosystems and carbon reduction measures.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.515-518
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• 2005

LiDAR(Light Detection and Ranging) with digital aerial photograph can be used to measure tree growth factors like total height, height of clear-length, dbh(diameter at breast height) and crown projection area. Delineating crown is an important process for identifying and numbering individual trees. Crown delineation can be done by watershed method to segment basin according to elevation values of DSMmax produced by LiDAR. Digital aerial photograph can be used to validate the crown projection area using LiDAR. And tree height can be acquired by image processing using window filter$(3cell\times3cell\;or\;5cell\times5cell)$ that compares grid elevation values of individual crown segmented by watershed.

• Journal of the Korean Institute of Landscape Architecture
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• v.25 no.3
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• pp.210-221
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• 1997

This study was conducted to investigte the visual preference and response between introduced and native trees for utilization of the south native trees in interior space. 1. The intensity of illumination was below 500lux at 24 buildings of interior spaces surveyed. Generally the temperature was 24~$26^{\circ}C$, and humidity was 60~70%. 2. Total number of introduced tree species were 9 familiar, 16 genus, 18 species, especially palm genus were the largest tree among them at these surveyed interior spaces, but native trees were only 2 species. The introduced tree of 2 to 3m in height was 46 percent, and the case of 1.2 to 2m was 42 percent. 3. The mean of visual preference was the highest at Rhapis excelsa and howeia belmoreana, and followed with Neolitsea sericea, Daphniphllum macropodum, Listsea japonicum. In the mean of visual preference for selected tree groups, native tree was not different as compared with introduced tree. 4. Visual image factor of the native and introduced trees at interior spaces was classified by individual factor and emotional factor. These 2 factors were shown 66.5% total variance. The native tree was strongly recognized on individual factor, as , and introduced tree was also strongly recognized on emotional factor. 5. In the analysis of visual preference and image, a difference between the selected groups of the introduced and native trees were not shown significant, and the introduced trees were similar to the native trees on the visual image. This result was as follow There was an analogy between Cinnamomum camphora, Ligustrum japonicum and Ficus retusa, Ficus benjamina. There is an analogy between Castanopsis cuspidata var. sieboldii, Cinnamomum japonicum and Ficus retusa, Ficus benjamina. There was an analogy between Elaeocarpus sylvestris var. ellipticus, Fatsia japonica and Rhapis excelsa, Howeia belmoreana. There was an analogy between Neolitsea sericea, Daphniphyllum macropo여, Listsea japonica and Rhapis excelsa, Howeia belmoreana. There was an analogy between Elaeocarpus sylvestris var. ellipticus, Fatsia japonica and Dracaena fragranse, Ficus elastica, Monstera deliciosa.

• The Korean Journal of Quaternary Research
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• v.17 no.2
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• pp.157-159
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• 2003

Much of northern Asia is lacking in high-resolution palaeoclimatic data coverage. This vast region thus represents a sizeable gap in data sets used to reconstruct hemispheric-scale temperature trends for the past millennium. To improve coverage, we present a regional-scale composite of four tree-ring width records of Siberian pine and Siberian larch from temperature-sensitive alpine timber-line sites in Mongolia. The chronologies load closely in principal components analysis (PCA) with the first eigenvector accounting for over 53% of the variance from ad 1450 to 1998. The 20-year interval from 1974 to 1993 is the highest such growth period in this composite record, and 17 of the 20 highest growth years have occurred since 1946. Thus these trees, unlike those recently described at some northern sites, do not appear to have lost their temperature sensitivity, and suggest that recent decades have been some of the warmest in the past 500 years for this region. There are, however, comparable periods of inferred, local warmth for individual sites, e.g., in 1520-1580 and 1760-1790. The percent common variance between chronologies has increased through time and is highest (66.1%) in the present century. Although there are obvious differences among the individual chronologies, this result suggests a coherent signal which we consider to be related to temperature. The PCA scores show trends which strongly resemble those seen in recent temperature reconstructions for the Northern Hemisphere, very few of which included representation from Eurasia east of the Ural Mountains. The Mongolia series therefore provides independent corroboration for these reconstructions and their indications of unusual wanning during the twentieth century.

• Journal of Korean Society of Forest Science
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• v.98 no.2
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• pp.178-182
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• 2009

A new mixed-effects model was developed that predicts individual-tree total height for Pinus densiflora trees in Gangwon province as a function of individual-tree diameter (cm). The mixed-effects model contains two random-effects parameters. Maximum likelihood estimation was used to fit the model to 560 height-diameter observations of individual trees measured throughout Gwangwon province in 2007 as part of the National Forest Inventory Program in Korea. The new model is an improvement over fixed-effects models because it can be calibrated to a local area, such as an inventory plot or individual stand. The new model also appears to be an improvement over the Forest Resources Evaluation and Prediction Program for the ten calibration trees used in this study. An example is provided that describes how to estimate the random-effects parameters using ten calibration trees.

• Korean Journal of Remote Sensing
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• v.27 no.3
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• pp.389-401
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• 2011

Most nations around the world have expressed significant concern in the climate change due to a rapid increase in green-house gases and thus reach an international agreement to control total amount of these gases for the mitigation of global warming. As the most important absorber of carbon dioxide, one of major green-house gases, forest resources should be more tightly managed with a means to measure their total amount, forest biomass, efficiently and accurately. Forest biomass has close relations with forest areas and tree height. Airborne LiDAR data helps extract biophysical properties on forest resources such as tree height more efficiently by providing detailed spatial information about the wide-range ground surface. Many researchers have thus developed various methods to estimate tree height using LiDAR data, which retain different performance and characteristics depending on forest environment and data characteristics. In this study, we attempted to investigate such various techniques to estimate tree height, elaborate their advantages and limitations, and suggest future research directions. We first examined the characteristics of LiDAR data applied to forest studies and then analyzed methods on filtering, a precedent procedure for tree height estimation. Regarding the methods for tree height estimation, we classified them into two categories: individual tree-based and regression-based method and described the representative methods under each category with a summary of their analysis results. Finally, we reviewed techniques regarding data fusion between LiDAR and other remote sensing data for future work.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.825-836
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• 2003

Based on customer information and financing processes in capital market, we derived individual models by applying multi-layered perceptrons, MDA, and decision tree. Further, the results from the existing single models were compared with the results from the integrated model that was developed using genetic algorithm. This study contributes not only to verifying the existing individual models and but also to overcoming the limitations of the existing approaches. We have depended upon the approaches that compare individual models and search for the best-fit model. However, this study presents a methodology to build an integrated data mining model using genetic algorithm.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.4
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• pp.57-67
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• 2014

The vigor condition of trees is an important indicator for the management of urban forested area. But difficulties in how to assess the tree vigor condition still remain. Previous efforts were limited in the 1) measurement of single indicator rather than using multiple indices, 2) purpose-oriented measurement such as for air-pollution effect or specific pathological symptom, and 3) ordinal-scale evaluations by field crews 4) despite human errors based on his/her experiences or prior knowledge. Therefore, this study attempted to develop a quantitative and objective methodology for assessing tree vigor condition, by measuring multiple modules and building the profile inventory. Furthermore, the possibility and limitations were discussed in terms of schematic frames describing tree vigor condition. The vigor condition of 56 flowering cherry plants in urban park were assessed by in-situ measurements of following eight items; growth of crown(Gc), growth of shoots, individual tree volume(Vol), plant area index, woody area index, leaf area index, leaf chlorophyll content(Lc) and leaf water content(Lw). For validation, these measurements were compared with the ranks of holistic tree vigor condition, which were visually assessed using a 4-point grading scale based on the expert's knowledge. As a result, the measures of each evaluation item successfully highlighted a variety of aspects in tree vigor condition, including the states of both photosynthetic and non-photosynthetic parts. The variation in the results depending on evaluated parts was shown within an individual tree, even though the broad agreement among the results was found. The result of correlation analysis between the tested measurements and 4-point visual assessment, demonstrated that the state of water-stressed foliage of the season (Lw) or the development of plant materials since sapling phase (Vol) could be better viewed from the outer appearance of trees than other symptoms. But only based on the visual assessment, it may be difficult to detect the quality of photosynthesis (Lc) or the recent trend in growth of trees (Gc). To make this methodology simplified for the broad-scale application, the tested eight measurements could be integrated into two components by principal component analysis, which was labelled with 'the amount of plant materials' and 'vigor trend', respectively. In addition, the use of these quantitative and multi-scale indicators underlies the importance of assessing various aspects of tree vigor condition, taking into account the response(s) on different time and spatial scale of pressure(s) shown in each evaluated module. Future study should be advanced for various species at diverse developing stages and environment, and the application to wide areas at a periodic manner.