• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1367-1375
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• 2017

Recently, the use of land cover maps has been continuously increasing to analyze spatial patterns such as spatial compositions, functions and changes of landscape mosaics. In this paper, we propose a landscape analysis system that extracts patches, which is an element of landscape mosaics, in the land cover map using region-based image processing technique, and computes patch-based measures at patch level and class level. Also we propose a patch-based spatial pattern that can represent spatial relations using the computed measures. To validate the proposed system's effectiveness, we apply to Gwangju metropolitan city and analyze Gwangju's land use and spatial patterns.

• Journal of Environmental Science International
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• v.20 no.6
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• pp.737-753
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• 2011

The typical characteristics of seasonal winds were studied around the Pohang using two-stage (average linkage then k-means) clustering technique based on u- and v-component wind at 850 hpa from 2004 to 2006 (obtained the Pohang station) and a high-resolution (0.5 km grid for the finest domain) WRF-UCM model along with an up-to-date detailed land use data during the most predominant pattern in each season. The clustering analysis identified statistically distinct wind patterns (7, 4, 5, and 3 clusters) representing each spring, summer, fall, and winter. During the spring, the prevailed pattern (80 days) showed weak upper northwesterly flow and late sea-breeze. Especially at night, land-breeze developed along the shoreline was converged around Yeongil Bay. The representative pattern (92 days) in summer was weak upper southerly flow and intensified sea-breeze combined with sea surface wind. In addition, convergence zone between the large scale background flow and well-developed land-breeze was transported around inland (industrial and residential areas). The predominant wind distribution (94 days) in fall was similar to that of spring showing weak upper-level flow and distinct sea-land breeze circulation. On the other hand, the wind pattern (117 days) of high frequency in winter showed upper northwesterly and surface westerly flows, which was no change in daily wind direction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.2
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• pp.133-140
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• 2007

In this study we did the monitor the change of a urban land coverage to forecast and to deal with various city problems according to urban development. The amount of change of a land coverage used the landsat satellite image and was calculated by analyzing the situation and the distribution aspect of land cover of the road circumstance by time series. We interpreted two images which are taken picture different time and calculated the amount of the area change through integration of the spatial analysis technique of remote sensing and GIS for this study. We could create the development model of the urban area by continuous analysis of satellite and geographic data.

• ETRI Journal
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• v.21 no.4
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• pp.41-51
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• 1999

This research is an attempt to obtain more accurate land cover information from LANDSAT images. Canonical correlation analysis, which has not been widely used in the image classification community, was applied to the classification of a LANDSAT images. It was found that it is easy to select training areas on the classification using canonical correlation analysis in comparison with the maximum likelihood classifier of $ERDAS^{(R)}$ software. In other words, the selected positions of training areas hardly affect the classification results using canonical correlation analysis. when the same training areas are used, the mapping accuracy of the canonical correlation classification results compared with the ground truth data is not lower than that of the maximum likelihood classifier. The kappa analysis for the canonical correlation classifier and the maximum likelihood classifier showed that the two methods are alike in classification accuracy. However, the canonical correlation classifier has better points than the maximum likelihood classifier in classification characteristics. Therefore, the classification using canonical correlation analysis applied in this research is effective for the extraction of land cover information from LANDSAT images and will be able to be put to practical use.

• Journal of the Korean Institute of Landscape Architecture
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• v.33 no.6 s.113
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• pp.40-50
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• 2006

This study was carried out to examine the tree-ring growth characteristics of Zelkova serrata Makino after replanting, for the built-up planting founds for stability of landscaped trees in the reclaimed land from the sea. the factors, many affecting the growths of Zelkova serrata Makino, were the replanting stress and drought. The growth reduction due to replanting and drought occurred in the replanting year and the following year. The mean sensitivity(year-to-year variation) and the coefficient of variation(tree-to-tree variation in a certain year) in tree rings of Zelkova serrate Makino, were higher in the poor soil sites than in the favourable soil ones. And the poor soil sites were the filled ground of improve soil and the covered ground of improve soil and the top ground of big mounding than mounding ground sites, especially soil hardness, alkali soil, high $Na^+\;and\;K^+,\;low\;Ca^{++}\;and\;Mg^{++}$ and T-C were the most crucial. We suggest technique development of the built-up planting ground for stability in the reclaimed land from the sea. The built-up planting grounds in reclaimed land from the sea, should be considered for the use of fair soil with the physical and chemical soil properties, -high level foundation of planting ground, and the prevention of disturbed soil-.

• Journal of Korean Society of Rural Planning
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• v.3 no.2
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• pp.50-61
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• 1997

As one of methodological approaches for objective and systematic evaluation for rural resources, a sequential system for significance determination of resources items was formulated using AHP (Analytic Hierarchy Process) as the base technique. By the system constructed in this study, the significance values were calculated for all items of standard goal system which had been presented in the first phase- paper of research works for rural resources evaluation. The results analysed and obtained in the study are summarized as follows; 1. In case that the number of resources items for evaluation are relatively large, stepwise matrix method is considered as the better one for pair-comparison works in view of evaluator's convenience and consistency. 2. The significance valuing results for most resources items showed a considerable difference between characteristic areas, especially in aspects of land and human resources, so being considered as wet reflecting the specific areal varieties, 3. On land resources, the items for industrial development and land use showed higher significance value, while natural environment resources the items for ecological varieties and on human resources the items for artificial facilities. However, lower-valued ones were the items for mineral stocks in land resources, for control and protection in natural environment resources and for lower-level culture heritage respectively.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1771-1777
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• 2023

With the advancements of deep learning, many semantic segmentation-based methods for land cover classification have been proposed. However, existing deep learning-based models only use image information and cannot guarantee spatiotemporal consistency. In this study, we propose a land cover classification model using geographical coordinates. First, the coordinate features are extracted through the Coordinate Hash Encoder, which is an extension of the Multi-resolution Hash Encoder, an implicit neural representation technique, to the longitude-latitude coordinate system. Next, we propose an architecture that combines the extracted coordinate features with different levels of U-net decoder. Experimental results show that the proposed method improves the mean intersection over union by about 32% and improves the spatiotemporal consistency.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.3
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• pp.293-301
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• 2004

This study analyzes the interrelationship with air pollution quality and land used patterns, and analyzes the history and optimal allocation of TMS using GIS. Seasonal air pollution map are maded of TMS data in study area, and land used patterns based on Land Cover Classification Map are reclassified as residential area, commercial area, industrial area, traffic concentrated area, and non-Polluted area. Pollution sources can be identified through analyzing the correlation of air pollution and land used patterns by GIS spatial overlaying technique. Hence, the result shows that it coincides with the characteristics of conventional air pollution. Air pollution quality measured by TMS shows similar to that of its near stations or the same land used patterns, through the history and allocation analysis of TMS. Therefore, it is need to consider these characteristics in setting TMS positions in the future.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.11-17
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• 2013

With high social demands for the diverse utilizations of forest lands, the illegal forest land use changes have increased. We studied change detection technique to detect changes in forest land use using an object-oriented segmentation of RED bands differencing in multi-temporal aerial photographs. The new object-oriented segmentation method consists of the 5 steps, "Image Composite - Segmentation - Reshaping - Noise Remover - Change Detection". The method enabled extraction of deforested objects by selecting a suitable threshold to determine whether the objects was divided or merged, based on the relations between the objects, spectral characteristics and contextual information from multi-temporal aerial photographs. The results found that the object-oriented segmentation method detected 12% of changes in forest land use, with 96% of the average detection accuracy compared by visual interpretation. Therefore this research showed that the spatial data by the object-oriented segmentation method can be complementary to the one by a visual interpretation method, and proved the possibility of automatically detecting and extracting changes in forest land use from multi-temporal aerial photographs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1370-1376
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• 2012

This study tried to analyze $CO_2$ emission volume as green-house gases by application of land use patterns and transport policies in District Unit Design. It is postulated a Toy network and various scenarios which are combined land use patterns and transport policies for analyzing $CO_2$ gas reduction. As results, this study shows best District Unit Design technique is the policy that develop mid block and introduction of car free zone to inner 2 way streets. Worst design technique is the policy that make hierarchical network and introduction of access control to outer roads that have been known as a best road policy till nowadays. Therefore, we need more carefully introduce design technique for reduction of $CO_2$ in District Unit.