• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.2
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• pp.92-101
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• 1998

Location patterns of protected horticulture were analyzed using a multiple correspondence analysis(MCA). The analysis could be used in evaluating location suitability of protected horticulture. The location factors of the protected horticulture for MCA include land category, size of protected horticulture, land slope, topography, effictive soil depth, irrigation and drainage condition, distance from roads, and so forth. The results showed that there were three different location patterns of protected horticulture. The first pattern was characterized by their nearness to villages. The facilities of this pattern were mainly located near to residential area. The second pattern was of those found in plain area. The facilities of this pattern were large in scale and located in paddy field far from residential area. The facilities of the last pattern were small in scale and located on nonpaddy fields. They were mostly found in hilly or mountainous area.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.763-776
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• 2021

This paper introduces a method of selecting priority update areas for subdivided land cover maps by training orthoimages and serial cadastral maps in a deep learning model. For the experiment, orthoimages and serial cadastral maps were obtained from the National Spatial Data Infrastructure Portal. Based on the VGG-16 model, 51,470 images were trained on 33 subdivided classifications within the experimental area and an accuracy evaluation was conducted. The overall accuracy was 61.42%. In addition, using the differences in the classification prediction probability of the misclassified polygon and the cosine similarity that numerically expresses the similarity of the land category features with the original subdivided land cover class, the cases were classified and the areas in which the boundary setting was incorrect and in which the image itself was determined to have a problem were identified as the priority update polygons that should be checked by operators.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.121-135
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• 2014

Object-based classification methods provide a valid alternative to traditional pixel-based methods. This study reports the results of an object-based classification to examine land cover in the demilitarized zones(DMZs) of Inje-gun. We used land cover classes(7 classes for main category and 13 classes for sub-category) selected from the criteria by Korea Ministry of Environment. The average and standard deviation of the spectrum values, and homogeneity of GLCM were chosen to map land cover types in an hierarchical approach using the nearest neighborhood method. We then identified the distributional characteristics of land cover by considering 3 topographic characteristics (altitude, slope gradient, distance from the Southern Limited Line(SLL)) within the DMZs. The results showed that scale 72, shape 0.2, color 0.8, compactness 0.5 and smoothness 0.5 were the optimum weight values while scale, shape and color were most influenced parameters in image segmentation. The forests (92%) were main land cover type in the DMZs; the grassland(5%), the urban area (2%) and the forests (broadleaf forest: 44%, mixed forest: 42%, coniferous forest: 6%) also occupied mostly in land cover classes for sub-category. The results also showed that facilities and roads had higher density within 2 km from the SLL, while paddy, field and bare land were distributed largely outside 6 km from the SLL. In addition, there was apparent distinction in land cover by topographic characteristics. The forest had higher density at above altitude 600m and above slope gradient $30^{\circ}$ while agriculture, bare land and grass land were distributed mainly at below altitude 600m and below slope gradient $30^{\circ}$.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.1
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• pp.93-99
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• 2012

This study aims to identify spatio-temporal land price change pattern in Gongju city including the area incorporated and surrounding area depending on the Multifunctional Administrative City Construction. For this, GIS data was built by calculating the average land price each 209 Dong and Ri by the time of the year 2000, 2005 and 2010 based on. The first, the change in the land price was to identify in the 5-year intervals through a kriging interpolation as a kind of geostatistical techniques. The second, a trend analysis was conducted to know directional change pattern of the east-west axis and the north-south axis. Finally, the weighted mean center was calculated by the land price at a weight to examine moving direction on the center point of land price, point of view. The result is that the land price change pattern appeared visible higher growth on the eastern built in the Multifunctional Administrative City, moving direction on the center point of the land price appeared that the phenomenon was concentrated in the northeastern area.

• Journal of Cadastre & Land InformatiX
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• v.54 no.1
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• pp.19-32
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• 2024

This study examined the feasibility of image-based surveys by detecting objects in facilities and agricultural land using the YOLO algorithm based on drone images and comparing them with the land category by law. As a result of detecting objects through the YOLO algorithm, buildings showed a performance of detecting objects corresponding to 96.3% of the buildings provided in the existing digital map. In addition, the YOLO algorithm developed in this study detected 136 additional buildings that were not located in the digital map. Plastic greenhouses detected a total of 297 objects, but the detection rate was low for some plastic greenhouses for fruit trees. Also, agricultural land had the lowest detection rate. This result is because agricultural land has a larger area and irregular shape than buildings, so the accuracy is lower than buildings due to the inconsistency of training data. Therefore, segmentation detection, rather than box-shaped detection, is likely to be more effective for agricultural fields. Comparing the detected objects with the land category by law, it was analyzed that some buildings exist in agricultural and forest areas where it is difficult to locate buildings. It seems that it is necessary to link with administrative information to understand that these buildings are used illegally. Therefore, at the current level, it is possible to objectively determine the existence of buildings in fields where it is difficult to locate buildings.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.159-172
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• 2006

In this study, the series of Landsat TM/ETM+ images was acquired to extract land surface temperature for wide-area and executed geometric correction and radiometric correction. And the land surface temperature was extracted using NASA Model, and achieved the first correction by performing land coverage category for study area and applied characteristic emission rate. Land surface temperature which was acquired by the first correction was analyzed in correlation with Meteorological Administration's temperature data by regression analysis, and established correction formula. And I wished to improve accuracy of land surface temperature extraction using satellite image by second correcting deviations between two data using establishing correction formula. As a result, land surface temperature acquired by 1st and 2st correction could be corrected in mean deviation of about ${\pm}3.0^{\circ}C$ with Meteorological Administration data. Also, I could acquire land surface temperature about study area by higher accuracy by applying to other Landsat images for re-verification of study results.

• Journal of Forest and Environmental Science
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• v.36 no.3
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• pp.187-198
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• 2020

This study extracted deforestation area and degraded forestland area, which are potential REDD+ (Reducing Emissions from Deforestation and Forest Degradation) project candidate areas in Paraguay using Land Cover Map (LCM) and Tree Cover Map (TCM). The REDD+ project objectives scenarios were set three stages: 'afforestation and economic efficiency scenario', 'local capacity reinforcement scenario', and 'Infrastructure-oriented scenario'. And then, we evaluated the project unit suitable area of the REDD+ project. All scenarios selected the evaluation factors for each scenario in addition to the area ratio factors for deforestation area and degraded forestland area and weighted values were extracted by assigning category scores. As a result of the three scenarios comparison analysis, Concepcion state score was the highest. Within Concepcion state, the Belon district had the highest score, making it appropriate as a project unit REDD+ project candidate area in Paraguay, while the San Carlos district had the lowest score. This study can be used as basic data for selecting REDD+ project candidate area in Paraguay, and it is expected to contribute sufficiently to REDD+ project if additional data or information of social, cultural and economic sectors are secured.

• Journal of Korean Society of Rural Planning
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• v.4 no.1
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• pp.86-97
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• 1998

It is neceesary to evaluate the location suitability of protected cultivation facilities to guide reasonable protected cultivation. The evaluation system could help plan new protected cultivation facilities in rural areas. In this study, an assessment was made for the facilities located in three different selected regions: suburban, plain, and mountainous. The assessment was performed based on spatial characteristics of protected cultivation facilities such as land category, size of protected cultivation facilities, land shape, stoniness, land consolidation level, soil drainage, land slope, topography, effective soil depth, zoning or not of agricultural development area, irrigation and drainage condition, distance from roads, and so forth. The results showed that there were significant differences in locational characteristics among the three regions.

• Ecology and Resilient Infrastructure
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• v.5 no.4
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• pp.229-245
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• 2018

This study aims to investigate the changes in the riparian vegetated area in the Naeseong stream, an unregulated river, in order to analyze the main factors leading to these changes. For this purpose, the land surface cover in the channel area of the Naeseong stream was classified into 9 categories using past aerial photographs collected between 1970 and 2016, which recorded the long-term changes of the Naeseong stream. The increase or decrease in the vegetated area was calculated for each category using a pair of before and after images. The changes in the vegetated area were divided into 6 periods: the unvegetated channel period (1970 - 1980), the first rapid increase (1980 - 1986), the period of decrease due to flood (1986 - 1988), the period of repetitive man-induced disturbance and vegetation increase (1988 - 2008), the period of gradual vegetation increase (2008 - 2013), and the period of second rapid increase (2013 - 2016). Multiple regression analysis was performed using independent variables representing hydrology, climate, and geomorphology. The major variables found to be involved in the changes in the vegetated area of the Naeseong stream were the discharge during June - July, channel width, and temperature during April - June. Among the three variables, discharge and temperature were respectively the main independent variables in the downstream and the upstream reaches as per a single variable model. Channel width was the variable that distinguished the upstream and downstream reaches of the stream. The implication of the long-term increase in the vegetated area in the Naeseong stream was discussed based on the result of this study.

• Journal of Environmental Science International
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• v.19 no.8
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• pp.1025-1034
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• 2010

This study was to analyze changes of landuse and environmental value of cultivate land for eight years from 1999 to 2007 year in greenbelt area, Seoul. Greenbelt area decreased from $166.82\;km^2$ in 1999 to $156.50\;km^2$ in 2007 according to removal policy. Regarding landuse status in 2007, forest field area accounted for 64.16 %, dry paddy area 4.10 %, facilitated farming area 3.82 %, rice paddy area 2.95 % out of total greenbelt area. Cultivate land occupied wide spaces with dry paddy area, facilitated farming area, tree nursery in Seocho-gu, Gangnam-gu and Gangdong-gu. Changes of landuse were serious in Seocho-gu. The trend of changes of landuse for eight years is that rice paddy area was changed dry paddy area by laying the ground and dry paddy area was changed facilitated farming area for intensive agriculture. Rice paddy area could change without permission by laying the ground in below 50 cm height and it was changed to green houses due to increase in profit and modern policy of agriculture. It is nessary to monitor landuse regularly, improve regulation for change of landuse, compensate a property loss for maintaining environmental value in greenbelt area.