• The Korean Journal of Ecology
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• v.24 no.6
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• pp.385-394
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• 2001

An attempt to clarify the landscape structure of urban areas was carried out in the greenbelt around Seoul, Korea's metropolis. By means of aerial photographs and a field survey, a vegetation map including land-use pattern was made. Landscape structure was described by analyzing this vegetation map and the results of phytosociological survey. Landscape element types identified were (1) secondary forest, (2) plantation, (3) cultivated field, (4) urbanized area, (5) graveyard, and (6) bare rock. Vegetation units, resulting from the phytosociological analysis, included Quercus mongolica, Q. variabilis, Q. acutissima, Pinus densiflora, Q. aliena, and Alnus japonica communities. Plantations were composed of Robinia pseudoacacia, Populus tomentiglandulosa, P. rigida, Larix leptolepis, P. koraiensis, and Castanea crenata stands. Patches near to human settlements in the lower zones of the mountains were fragmented and small but they became larger towards the higher mountain zones. On the other hand, the number of patches was fewer and their size was larger in Mt. Cheonggye more distant from the principal residential area, larger in size, and higher in elevation compared with the other 2 mountains, Mt. Daemo and Mt. Acha. Floristic composition of Mongolian oak(Q. mongolica) stand distributing in the upper part of each mountain, in which artificial interference is rare, showed a difference among those study areas different in parent rock and disturbance regime. But that of black locust(R. pseudoacacia) stand located in lowland of mountainous area, in which artificial interference is frequent was similar to each other. As the results of analyses on the frequency distribution of diameter classes of major species, dominant landscape elements, Mongolian oak forest showed different responses depending on artificial interference as continuous maintenance and retrogressive succession in the sites far from and near to the residential areas, respectively. On the other hand, black locust stands showed a probability to be restore to the native oak forest through progressive succession.

• The Journal of Engineering Geology
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• v.26 no.1
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• pp.23-32
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• 2016

This study evaluates landslide susceptibility using statistical analysis by SVM (support vector machine) and the illite index of clay minerals extracted from ASTER(advanced spaceborne thermal emission and reflection radiometer) imagery which can be use to create mineralogical mapping. Landslide locations in the study area were identified from aerial photographs and field surveys. A GIS spatial database was compiled containing topographic maps (slope, aspect, curvature, distance to stream, and distance to road), maps of soil properties (thickness, material, topography, and drainage), maps of timber properties (diameter, age, and density), and an ASTER satellite imagery (illite index). The landslide susceptibility map was constructed through factor correlation using SVM to analyze the spatial database. Comparison of area under the curve values showed that using the illite index model provided landslide susceptibility maps that were 76.46% accurate, which compared favorably with 74.09% accuracy achieved without them.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.423-436
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• 2017

This paper presents a deep learning-based road segmentation framework from very high-resolution orthophotos. The proposed method uses Deep Convolutional Autoencoders for end-to-end mapping of orthophotos to road segmentations. In addition, a set of post-processing steps were applied to make the model outputs GIS-ready data that could be useful for various applications. The optimization of the model's parameters is explained which was conducted via grid search method. The model was trained and implemented in Keras, a high-level deep learning framework run on top of Tensorflow. The results show that the proposed model with the best-obtained hyperparameters could segment road objects from orthophotos at an average accuracy of 88.5%. The results of optimization revealed that the best optimization algorithm and activation function for the studied task are Stochastic Gradient Descent (SGD) and Exponential Linear Unit (ELU), respectively. In addition, the best numbers of convolutional filters were found to be 8 for the first and second layers and 128 for the third and fourth layers of the proposed network architecture. Moreover, the analysis on the time complexity of the model showed that the model could be trained in 4 hours and 50 minutes on 1024 high-resolution images of size $106{\times}106pixels$, and segment road objects from similar size and resolution images in around 14 minutes. The results show that the deep learning models such as Convolutional Autoencoders could be a best alternative to traditional machine learning models for road segmentation from aerial photographs.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.1
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• pp.151-158
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• 1992

Topographic mapping from economic SPOT stereo imagery than aerial photographs has become possible. Many of authors have studied the possibility of base map revisions and the accuracy of results. They have concluded that the SPOT image is suitable for 1/50,000 to 1/100,000 topographic map. For topographic map, orthophoto and DTM generation from SPOT imagery, accurate exterior orientation parameters are needed. But since the geometric characteristic of SPOT image is dynamic linear array imagery, the conventional bundle adjustment for photogrammetry can not be directly applied. Reliability is the ability to detect gross error, which is called the internal reliability, and the effect of non-detectable gross error on the results of exterior orientation, which is called the external reliability. This paper shows how the reliability of SPOT imagery depends on the different coordinate systems, presentations of coordinate for flight direction, orders of exterior orientation parameters and distribution of control points, and thus analyses the theoretical reliability of the exterior orientation, which can provide a basis for the planning of SPOT projects.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.4 no.2
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• pp.36-44
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• 2001

The main purpose of this study was to classify forest vegetation effectively using Landsat Thematic Mapper data(June, 1994) in mountainous region. The research area was the Mt. Wolak Experimental Forest of Chungbuk National University, near Chungju and Jecheon city, Chungcheongbuk-do. To classify forest vegetation effectively, Normalized Difference Vegetation Index(NDVI) was used to reduce topographic effects. This NDVI was modified and transformed to the value of 0 to 255, and then the modified values were combined with other Landsat Thematic Mapper bands. To classify forest and land cover types, unsupervised classification method was used. The results of this study are summarized as follows. 1. Combinations of band "3, 5, NDVI" in Landsat Thematic Mapper data showed a good separation with high accuracy. The expected classification accuracy was 95.1% in Landsat Thematic Mapper data. 2. The Land Cover types were classified into six groups : coniferous forest, deciduous forest, mixed forest, paddy and grass, non-forest, and other undetectable areas. As these classified results were compared with the reconnaissance survey and aerial black and white infrared photographs, the overall classification accuracy was 76.5% in Landsat Thematic Mapper data. 3. The portion of non-forest in Mt. Wolak area was 1.9%. The percentages of coniferous, deciduous and mixed forests were 30.9%, 35.7% and 26.4%, respectively. 4. As these classified results were compared with other reference data, the percentages of coniferous, deciduous and mixed forests increased, but the portion of non-forest was exceedingly diminished. These differences are thought to be from the different research method and the different season of received Landsat Thematic Mapper data.

• Journal of the Korean Institute of Rural Architecture
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• v.20 no.3
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• pp.11-18
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• 2018

Suhwa Kim Hwan-gi established his own unique world of art based on Korean-style lyricism with his sophisticated and sublimated formative language as the first generation of Korean abstract artist. He made his name known not only in Korea but New York and Paris, the center of contemporary art. Presently, there is almost no material left for us to examine how Kim Hwan-gi's house looked in the first place. But there is a painting that chef Kim Am-gi possesses where we can find the image of painter Kim Hwan-gi's house drawn by recalling the memories at home in a far-off land. With that, we can see it should be the original looks of that house. To examine the original looks of Kim Hwan-gi's house when it was built, this author studied the closure land registration map. By analyzing 29 land registration maps around Eupdong-ri of Gijwa-myeon in Muan-gun of Jeollanam-do produced in 1917 which National Archives of Korea possesses, this researcher could figure out the status of land registration around Kim Hwan-gi's house with No. 15 and 22 drawing boards. According to the results of considering aerial photographs after the emancipation that National Geographic Information Institute possesses, this author has found that the arrangement of Kim Hwan-gi's house was changed from 1954 up to 2008. In 1954 aerophotos, we can see the main building and studio in Kim Hwan-gi's house and there was an additional structure between them. Kim Hwan-gi's house was built before 1925. The main building presently designated as a cultural asset and also the sarangchae arranged in the east and the studio, too, were built in the similar period.

• Journal of Korea Water Resources Association
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• v.41 no.4
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• pp.395-404
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• 2008

It is important to understand the complex, various migration features of the alluvial channels for river engineering. In this study, the morphological changes and migration features of alluvial channels were investigated by analyzing the aerial photographs of active channels between 1972 and 2004 in Hapyeong Intake Station, Nakdong river. The lower channels were migrated from left bank to right bank and showed the features of braided channel in 2004. The instability of lower channels was increased due to the increased channel slope and width. The sinuosity of lower channels was decreased with time. As time increased, the increasing rate of lower channel and lateral migration rate were decreased. As a result of meso-scale regime analysis by using bankfull discharge, multiple row bars were developed, and suspended sediment load was governed in the flow as a sand bed channel.

• Journal of Environmental Science International
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• v.16 no.5
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• pp.603-610
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• 2007

Recent urban sprawl has destroyed various kinds of green space in tile city. It has affected duality of people's life in the city, as well as urban ecosystem. Recent study shows the possibilities of roofs as green spaces in urban central site where the land costs are generally high. This research focuses on Jung-Gu district in Daegu Metropolitan city as a study area and calculates possible area of green roof using 2002 Autocad program based on aerial photographs and land registration maps. And the purpose of this research is to analyze environmental and economic effects of green roof. The environmental effects are as follows. It is expected that $91,106m^2$ green spaces, 12.13 % of study site, will be added if green roof is performed in the study site. It is assumed that the expanded areas could reduce the highest temperature to $0.5-1.0^{\circ}C$ during the summer in terms of environmental effect. And the following shows the economic effects. If green roof and greening urban central site are created as a same size of $91,106m^2$, it will be expected that the costs of green roof will be much more in-expensive than about 98 billions won. It will be also found that the expense of cooling energy can be saved out about 8 millions won per day in summer, if grass planting is accomplished on the possible areas of green roof in the study site. Therefore, it is desirable to take legal supports such as enacting regulations to activate green roof for more environmental and economic effects. For instance, green roof for public institutions, school and model area selection are desirable method to publicize the effect of greening program for citizen's participation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.4
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• pp.113-124
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• 1989

In this study, we tried to extract the land-use change information of Seoul city using the multiple date images of the same geographic area. Multiple date image set is MSS('72, '79, '81, '93) and TM('85), and we carried out geometric correction, digitizing(due to the administrative boundary) in pre-processing process. In addition, we performed land-use classification with MLC(Maximum Likelihood Classifier) after improving the predictive accuracy of classification by filtering technique. At the stage of classification, ground truth data, topographic maps, aerial photographs were used to select the training field and statistical data of that time were compared with the classification result to prove the accuracy. As a result, urban area in Seoul has been increased('72 : 25.8 %${\rightarrow}$'81 : 43.0 %${\rightarrow}$'85 : 51.9 %) and Forest area decreased ('72 : 39.0 %${\rightarrow}$'85 : 28.4 %) as we estimated. Finally, it is concluded that the utilzation of satellite imagery is very effective, economical and helpful in the urban land-use/land-cover monitoring.

• Spatial Information Research
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• v.16 no.3
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• pp.373-383
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• 2008

LiDAR, unlike satellite imagery and aerial photographs, which provides irregularly distributed three-dimensional coordinates of ground surface, enables three-dimensional modeling. In this study, urban area was classified based on 3D information collected by LiDAR. Morphological and spatial properties are determined by the ratio of ground and non-ground point that are estimated with the number of ground reflected point data of LiDAR raw data. With this information, the residential and forest area could be classified in terms of height and density of trees. The intensity of the signal is distinguished by a statistical method, Jenk's Natural Break. Vegetative area (high or low density) and non-vegetative area (high or low density) are classified with reflective ratio of ground surface.