• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.5
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• pp.30-43
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• 2023

Green infrastructure(GI) is considered a key strategy in establishing sustainable communities. However, research on GI from the perspective of urban system dynamics and resilience lacks depth, as does its integration with physical design. This research addresses two primary causes. First, there is a gap in methods between existing GI planning, which considers static variables, and urban modeling research, which addresses dynamic variables. Second, there is a gap in information between landscape design and urban modeling research. To address these issues, this study proposes an integrated modeling approach in consideration of design decision-making. By combining the LEAM model and MCDA model, this study evaluates the relationship between GI services and socioeconomic growth, while spatially forecasting the geographies of GI demand in 2050. The resulting information reveals a potential degradation in ecosystem services over the region due to Chicago's sub-urbanization. This indicates that there would be a spatial shift in GI demand, emphasizing the need for comprehensive, dynamic GI strategies. This study further discusses the applications of evidence-based design in a studio environment. This study aims to contribute to the GeoDesign literature in terms of the creation of a more resilient urban environment by facilitating efficient evidence-based decision-making.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.283-295
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• 2023

With the development of sensor and satellite technology, numerous high-resolution and multi-spectral satellite images have been available. Due to their wavelength-dependent reflection, transmission, and scattering characteristics, multi-spectral satellite images can provide complementary information for earth observation. In particular, the short-wave infrared (SWIR) band can penetrate certain types of atmospheric aerosols from the benefit of the reduced Rayleigh scattering effect, which allows for a clearer view and more detailed information to be captured from hazed surfaces compared to the visible band. In this study, we proposed a multi-resolution transform-based image fusion method to combine visible and SWIR satellite images. The purpose of the fusion method is to generate a single integrated image that incorporates complementary information such as detailed background information from the visible band and land cover information in the haze region from the SWIR band. For this purpose, this study applied the Laplacian pyramid-based multi-resolution transform method, which is a representative image decomposition approach for image fusion. Additionally, we modified the multiresolution fusion method by combining a haze-guided weight map based on the prior knowledge that SWIR bands contain more information in pixels from the haze region. The proposed method was validated using very high-resolution satellite images from Worldview-3, containing multi-spectral visible and SWIR bands. The experimental data including hazed areas with limited visibility caused by smoke from wildfires was utilized to validate the penetration properties of the proposed fusion method. Both quantitative and visual evaluations were conducted using image quality assessment indices. The results showed that the bright features from the SWIR bands in the hazed areas were successfully fused into the integrated feature maps without any loss of detailed information from the visible bands.

• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.555-562
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• 2004

Both global volume reduction and local shape changes of hippocampus within the brain indicate their abnormal neurological states. Hippocampal shape analysis consists of two main steps. First, construct a hippocampal shape representation model ; second, compute a shape similarity from this representation. This paper proposes a novel method for the analysis of hippocampal shape using integrated Octree-based representation, containing meshes, voxels, and skeletons. First of all, we create multi-level meshes by applying the Marching Cube algorithm to the hippocampal region segmented from MR images. This model is converted to intermediate binary voxel representation. And we extract the 3D skeleton from these voxels using the slice-based skeletonization method. Then, in order to acquire multiresolutional shape representation, we store hierarchically the meshes, voxels, skeletons comprised in nodes of the Octree, and we extract the sample meshes using the ray-tracing based mesh sampling technique. Finally, as a similarity measure between the shapes, we compute $L_2$ Norm and Hausdorff distance for each sam-pled mesh pair by shooting the rays fired from the extracted skeleton. As we use a mouse picking interface for analyzing a local shape inter-actively, we provide an interaction and multiresolution based analysis for the local shape changes. In this paper, our experiment shows that our approach is robust to the rotation and the scale, especially effective to discriminate the changes between local shapes of hippocampus and more-over to increase the speed of analysis without degrading accuracy by using a hierarchical level-of-detail approach.

• Korean Journal of Environmental Agriculture
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• v.34 no.2
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• pp.149-154
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• 2015

BACKGROUND: Yeast isolates associated with the leaves, stems, and flowers of the tiger lily needed to be identified using isolation methods that have previously been used effectively in yeast biotechnology. A culture-based approach was necessary for the isolation of many yeast strains associated with tiger lily. METHODS AND RESULTS: In this study, the homogenized leaves, stems, and flowers of tiger lily were spreaded onto GPY medium containing chloramphenicol, streptomycin, Triton X-100, and L-sorbose. A total of 82 yeast strains from the leaves, 94 and 97 yeast strains from the stems and flowers were isolated, respectively. Yeast isolates were identified by phylogenetic analysis based on internal transcribed spacer region sequencing. The yeast species isolated from the leaves comprised of 31 isolates of the genus Pseudozyma, 28 of Aureobasidium pullulans, and 11 of the genus Cryptococcus. Those isolated from the stems comprised of 40 of A. pullulans and 11 of Cryptococcus, and 95 of A. pullulans While, 1 isolate each of the genera Rhodotorula and Metschnikowia were isolated from the flowers. CONCLUSION: We identified site-specific yeast communities associated with tiger lily. These yeast isolates may have high potential for application in the field of biotechnology.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.1
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• pp.1-12
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• 2020

As one of the essential resources in the agricultural process, soil moisture has been carefully managed by predicting future changes and deficits. In recent years, statistics and machine learning based approach to predict soil moisture has been preferred in academia for its generalizability and ease of use in the field. However, little is known that machine learning based soil moisture prediction is applicable in the situation of South Korea. In this sense, this paper aims to examine 1) whether publicly available weather data generated in South Korea has sufficient quality to predict soil moisture, 2) which machine learning algorithm would perform best in the situation of South Korea, and 3) whether a single machine learning model could be generally applicable in various regions. We used various machine learning methods such as Support Vector Machines (SVM), Random Forest (RF), Extremely Randomized Trees (ET), Gradient Boosting Machines (GBM), and Deep Feedforward Network (DFN) to predict future soil moisture in Andong, Boseong, Cheolwon, Suncheon region with open source weather data. As a result, GBM model showed the lowest prediction error in every data set we used (R squared: 0.96, RMSE: 1.8). Furthermore, GBM showed the lowest variance of prediction error between regions which indicates it has the highest generalizability.

• Journal of the Korean earth science society
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• v.38 no.7
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• pp.496-510
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• 2017

This study presents a new nationwide quantitative precipitation estimation (QPE) based on the hybrid surface rainfall (HSR) technique using the weather radar network of Korea Meteorological Administration (KMA). This new nationwide HSR is characterized by the synthesis of reflectivity at the hybrid surface that is not affected by ground clutter, beam blockage, non-meteorological echoes, and bright band. The nationwide HSR is classified into static (STATIC) and dynamic HSR (DYNAMIC) mosaic depending on employing a quality control process, which is based on the fuzzy logic approach for single-polarization radar and the spatial texture technique for dual-polarization radar. The STATIC and DYNAMIC were evaluated by comparing with official and operational radar rainfall mosaic (MOSAIC) of KMA for 10 rainfall events from May to October 2014. The correlation coefficients within the block region of STATIC, DYNAMIC and MOSAIC are 0.52, 0.78, and 0.69, respectively, and their mean relative errors are 34.08, 30.08, and 40.71%.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.1
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• pp.80-93
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• 2016

Parcel boundary demarcation in agricultural area is commonly performed by terrestrial surveying methods, which have been pointed out as drawbacks to require consuming too much time and heavy expenditure. With the developments of high performance digital aerial cameras, however, studies on cadastral boundary demarcation with an aerial photogrammetric method attract a great attention in recent years. In this paper, an approach is presented to rapidly demarcate parcel boundaries coinciding with real ground ones in agricultural areas by extracting boundaries from the high resolution aerial orthoimages based on aerial targets. In order to investigate the feasibility of the proposed method, the accuracy of coordinates and area of parcel boundaries extracted from the aerial targets appeared in orthoimages compared with that of terrestrial boundary surveying results over the selected two test agricultural areas. Aerial image data were processed taken by a ADS80 digital camera with a GSD of 8cm in Changwon region, and by a DMCII camera with a GSD of 5cm in Suwon respectively. The result shows that the accuracy of parcel demarcation using aerial images is within the tolerance limits of coordinates and areas compared with that of terrestrial surveying. The proposed method using aerial target-based high resolution aerial images is therefore expected to be usefully applied in the agricultural parcel demarcation.

• Journal of Agricultural Extension & Community Development
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• v.20 no.3
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• pp.643-678
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• 2013

The purposes of study are to examine early appearance of rural village development that local administration firstly promoted through the 'Mobum Burak Development' promoted in environment change around the local government in 5 16 military government period and find implications of the current rural village development. During the military government period(1961~1963), rural administration showed lots of changes such as reorganization of administration system whose basic local government are si gun, introduction of national planning system and spread of si gun, reorganization of rural taxation system, diversification of extension caused by the establishment of rural facilities such as new Nong-hyup, RDA, etc. Thus, the main axis of development administration of counties was transferred from central government or American aid organization to local administration. According to the basic operation plan introduced after the 5 16 as a planning system, the Ministry of Home Affairs instructed to write and promote gun construction plan based on all conditions of gun as long-term general plan of rural development. Therefore, each do established general plans such as 'Nongdo Jeonbuk Geundaehwa Plan', 'Yakjin Gyeongbuk Plan', 'Jeonnam Miraesang', etc. and Mobum Burak Development was promoted by all kinds of titles such as 'Bogoganeun Maeul(Jeonbuk)', 'Bitnaneun Maeul(Chungnam)', 'Hyeokmyeong Chon(Gyeonggi)', 'Saemaeul geonseol(Gyeongnam)', etc. as a business of rural village development. But, business contents of gun's 'construction plan' couldn't be mutually connected although Mobum Burak Development and unit business contents were promoted by duplicated plan. It became useless general plan as times went by as business focusing on short-term outcomes rather than construction based on long-term region. Mobum Burak Development also borrowed contents community development business, but military government couldn't approach basic solution of village and regional agriculture by focusing on short-term outcome, without imitation of form and procedure. This study is judged to be utilized as basic data of following studies because rural village development companies focusing on national policies discovered unit rural companies and analyzed them by connecting to environment changes of rural administration.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.109-120
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• 1998

An image segmentation approach based on the fuzzy worm searching and MIN-MAX clustering algorithm is proposed in this paper. This algorithm deals with fuzzy worm value and min-max node at a gross scene level, which investigates the edge information including fuzzy worm action and spatial relationship of the pixels as the parameters of its objective function. But the conventional segmentation methods for edge extraction generally need the mask information for the algebraic model, and take long run times at mask operation, whereas the proposed algorithm has single operation according to active searching of fuzzy worms. In addition, we also propose both genetic fuzzy worm searching and genetic min-max clustering using genetic algorithm to complete clustering and fuzzy searching on grey-histogram of image for the optimum solution, which can automatically determine the size of ranges and has both strong robust and speedy calculation. The simulation results showed that the proposed algorithm adaptively divided the quantized images in histogram region and performed single searching methods, significantly alleviating the increase of the computational load and the memory requirements.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.1 s.6
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• pp.93-102
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• 1996

For an atomatic generation of DEM(Digital Elevation Model) by computer, it is a time-consumed work to determine adquate matches from stereo images. Correlation and evenly distributed area-based method is generally used for matching operation. In this paper, we propose a new approach that computes matches efficiantly by changing the size of mask window and search area according to the given terrain information. For image segmentation, at first edge-preserving smoothing filter is used for preprocessing, and then region growing algorithm is applied for the filterd images. The segmented regions are classifed into mountain, plain and water area by using MRF(Markov Random Filed) model. Maching is composed of predicting parallex and fine matching. Predicted parallex determines the location of search area in fine matching stage. The size of search area and mask window is determined by terrain information for each pixel. The execution time of matching is reduced by lessening the size of search area in the case of plain and water. For the experiments, four images which are covered $10km{\times}10km(1024{\times}1024\;pixel)$ of Taejeon-Kumsan in each are studied. The result of this study shows that the computing time of the proposed method using terrain information for matching operation can be reduced from 25% to 35%.