• Journal of Korean Society of Environmental Engineers
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• v.33 no.6
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• pp.439-446
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• 2011

In this research, enhanced land-cover classification methods using high-resolution satellite image (HRSI) and GIS in terms of practicality and accuracy was proposed. It aims for understanding non-point pollutant origin/loading, assessment the efficiency of rainfall storage/infiltration facilities and sounds water-environment management. The result of applying enhanced land-cover classification methods to the urban region verifies that roof and road area are including various vegetations such as roof garden, flower bed in the median strip and street tree. This accounts for 3% of total study area, and more importantly it was counted as impervious area by GIS alone or conventional indoor work. The feasibility of the method was assessed by applying to rainfall-runoff analysis for three weak rainfall in the range of 7.1-10.5 mm events in 2000, Chiba, Japan. A good agreement between simulated and observed runoff hydrograph was obtained. In comparison, the hydrograph simulated with land-use parameters by the detailed land-use information of 10m grid had an error between 31%~71%, while enhanced method showed 4% to 29%, and showed the improvement particularly for reproducing observed peak and recession flow rate of hydrograph in weak rainfall condition.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.343-350
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• 2024

Since the release of Meta's Segment Anything Model (SAM), a large-scale vision transformer generation model with rapid image segmentation capabilities, several studies have been conducted to apply this technology in various fields. In this study, we aimed to investigate the applicability of SAM for water bodies detection and extraction using the QGIS Geo-SAM plugin, which enables the use of SAM with satellite imagery. The experimental data consisted of Compact Advanced Satellite 500 (CAS500)-1 images. The results obtained by applying SAM to these data were compared with manually digitized water objects, Open Street Map (OSM), and water body data from the National Geographic Information Institute (NGII)-based hydrological digital map. The mean Intersection over Union (mIoU) calculated for all features extracted using SAM and these three-comparison data were 0.7490, 0.5905, and 0.4921, respectively. For features commonly appeared or extracted in all datasets, the results were 0.9189, 0.8779, and 0.7715, respectively. Based on analysis of the spatial consistency between SAM results and other comparison data, SAM showed limitations in detecting small-scale or poorly defined streams but provided meaningful segmentation results for water body classification.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.83-98
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• 2021

Urban green space is an important component for enhancing urban ecosystem health. Thus, identifying the spatial structure of urban green space is required to manage a healthy urban ecosystem. The Ministry of Environment has provided the level 3 land cover map(the highest (1m) spatial resolution map) with a total of 41 classes since 2010. However, specific urban green information such as street trees was identified just as grassland or even not classified them as a vegetated area in the map. Therefore, this study classified detailed urban green information(i.e., tree, shrub, and grass), not included in the existing level 3 land cover map, using two types of high-resolution(<1m) remote sensing data(i.e., airborne LiDAR and RGB ortho imagery) in Suwon, South Korea. U-Net, one of image segmentation deep learning approaches, was adopted to classify detailed urban green space. A total of three classification models(i.e., LRGB10, LRGB5, and RGB5) were proposed depending on the target number of classes and the types of input data. The average overall accuracies for test sites were 83.40% (LRGB10), 89.44%(LRGB5), and 74.76%(RGB5). Among three models, LRGB5, which uses both airborne LiDAR and RGB ortho imagery with 5 target classes(i.e., tree, shrub, grass, building, and the others), resulted in the best performance. The area ratio of total urban green space(based on trees, shrub, and grass information) for the entire Suwon was 45.61%(LRGB10), 43.47%(LRGB5), and 44.22%(RGB5). All models were able to provide additional 13.40% of urban tree information on average when compared to the existing level 3 land cover map. Moreover, these urban green classification results are expected to be utilized in various urban green studies or decision making processes, as it provides detailed information on urban green space.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.6
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• pp.687-695
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• 2011

Many internet portals provide maps with spatial information services. Recently, various images including aerial, satellite, street view, and photo-realistic 3D city models are provided as well as maps. This study suggested a method for geometric correction of the panoramic aerial images in the internet portal and 3D building modeling using information which is available in the internet. The key of this study is to obtain all necessary data easily from internet without restrictions. Practically, the ground control coordinates could be available from geo-referenced internet maps, and stereo pairs of the aerial images and close-range photographs for photo-realistic object modeling are provided by the internet service. However, the ground control points are not suitable for accurate mapping. RMSE of the plotting was about 9 meters and reduced upto 4 meters after coordinate transformation. The proposed methods would be applicable to various applications of photo-realistic object modeling which do not require high accuracy.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.506-506
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• 2002

S. Korean Government has accelerating its efforts to enhance the quality of the drinking water. The Ministry of Environment has declared the law of securing water-pollutant buffering zone to minimize the inflow of the point and nonpoint sources into the drinking water sources. As a first phase of installing nationa-wide water-pollutant buffering zone, approximately 300km buffering zone has been delineated along the South and North Han river, the major drinking water sources for the capital area of S. Korea, which has the population of more than 12 millions. The buffering zone has the width of 1,000 meter for the special protection area, and 500 meter for the remaining area from both ends of the river. The major works have been done in three stages. Firstly, the boundaries lines of the buffering zone was delineated on the digital topographic maps. Secondly, the maps were overlayed with the cadastral maps to identify individual land parcels, the street address of the major pollutant discharging facilities, and all different types of pollutants including livestocks. Thirdly, the field work has been done as a verification. Once the buffering zone was generated, all the information for the buffering gone were created or imported from other government agencies including official land price, details of the major manufacturing facilities discharging considerable amount of pollutants, major motels and resorts, not to mention of restaurants, etc. Also, major livestock houses were located to identify the path of the pollutant inflow to the drinking water source. Further works need to be continued such as purchasing private lands within the buffering zone and change the land use in the efforts to decrease the pollutant amount and to provide more environmentally friendly space. Also, high resolution satellite imagery should be utilized in the near future as a cost-effective data source to update all the landuse activities within buffering zone.