• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.257-259
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• 2003

Landuse maps are prepared from satellite imagery and field observations were conducted at various locations in the study area. Compared to the field data and NDVI and RVI thematic maps, NDVI is better than RVI, because it compensates for changing illumination conditions, surface slope, aspect and other factors. Clouds, water and snow have negative values for RVI and NDVI. Rock and bare soils have similar reflectance in both NIR and visible band, so RVI and NDVI are near zero. In forest areas with good vegetation cover, NDVI is high and landslide occurrence is less. But if annual and biennial vegetations are present and if cultivation practices are changed frequently, NDVI is medium and landslide occurrence is moderate. In areas where deforestation and settlement is in progress, NDVI is less and landslide occurrence is more. The NDVI FCC thematic map may be used as an important layer in GIS application for landslide studies. Analyzing other layers such as slope, rainfall, soil, geology, drainage, lineament, etc with NDVI FCC layer will give a better idea about the identity of landslide prone areas.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.47-52
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• 2003

Change detection and analysis is a powerful application of remote sensing, in that the spectral resolution of multi-band sensors can be used to advantage in monitoring both significant and subtle land cover changes over time. In this study, the LANDSAT TM data was used to detect the change areas affected by flood from a heavy rainfall. The study area is the Nakdong River located in the Korea peninsular. Among the several change detection techniques, change vector analysis(CVA), principle component analysis(PCA) and image difference approach are utilized in this paper. CVA uses any number of spectral bands from multi-date satellite data to produce change image that yield information of the magnitude and direction of differences pixel values. And accuracy assessment was carried out with a change image produced from three techniques. In result, CVA was found to be the most accurate for detecting areas affected by flood. CVA with the overall accuracy and Kappa coefficient of 97.27 percent and 94.45 percent, respectively.

• Journal of Environmental Science International
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• v.19 no.1
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• pp.115-124
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• 2010

Urban watershed can be found in the visible changes in technology, the most realistic satellite images is to use the data. Satellite image data on the indicators for progress on the nature of the change of land use is consistent and repetitive information, regular observation makes possible the detailed analysis of space-time. These remote sensing techniques and the type of course and, by using the time series history, the past, the dynamic model and the randomized prediction methodology for the conversion process if the city and river basin cooperation of the space changes effectively will be able to extrapolate. For each of the main changes in river flow, depending on the area of urbanization as determined according to reproduce the duration of the relationship between the urbanization of the area and runoff can be represented as a linear polynomial expression was, if a linear expression in the two fast slew rate of 0.858 to 0.861 showed up, and fast slew rate of 0.934 to 0.974 for the polynomial are reported. Change of land use changes in the watershed of the flow is one of the most affecting elements. Therefore, changes in land use of the correct classification of rivers is a more accurate calculation of the amount of the floodgate. In particular, using the Landsat images through the image of the land use category, land use past data and calculated using the Markov Chain model and predict the future land use plan in the water control project will be used for large likely.

• Journal of Korean Society of Water Science and Technology
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• v.26 no.6
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• pp.133-142
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• 2018

Increasing localized torrential rainfall caused by abnormal climate are making higher damage to human and property through urban inundation So The need of preventive measures is being highlighted. In this study, the methodology for calculating flood depth in domestic water map using an interpolation method in order to utilizing the results of flood analysis provided only in the form of a report is suggested. In the Incheon Metropolitan City S area as the test-bed, the flood depth was calculated using the interpolating the actual flood analysis by image and verification was performed. Verification results showed that the error rate was 5.2% for the maximum flooding depth, and that the water depth value was compared to 10 random points, which showed a difference of less than 0.030 m. Also, as the results of the flood analysis were presented in various ways, the flood depth was extracted from the image of the result of the flood analysis, which changed the presentation method, and then compared and analyzed. The results of this study could be available for the use of basic data from the research on the urban penetration of domestic consumption and for decision-making of policy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.5
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• pp.19-24
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• 2024

Global climate change is causing an increase in natural disasters around the world due to long-term temperature increases and changes in rainfall. Among them, forest fires are becoming increasingly large. South Korea experienced an average of 537 forest fires over a 10-year period (2013-2022), burning 3,560 hectares of forest. That's 1,180 soccer fields(approximately 3 hectares) of forest burning every year. This paper proposed an artificial intelligence based wildfire detection method using image and text information. The performance of the proposed method was compared with YOLOv9-C, RT-DETR-Res50, RT-DETR-L, and YOLO-World-S methods for mAP50, mAP75, and FPS, and it was confirmed that the proposed method has higher performance than other methods. The proposed method was demonstrated as a forest fire detection model of the early forest fire detection system in the Gangwon State, and it is planned to be advanced in the direction of fire detection that can include not only forest areas but also urban areas in the future.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.41-47
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• 2017

Recent studies have shown that there are various systems which can be used to monitor hazardous area in a debris flow location, but lack of methodological research on the exact location where each instrument should be installed has hindered the success of this systems. The objective of this study is to suggest the measurement system for monitoring debris-flow and propose the effective method to determine location of measurement system. Previously studied, from 1991 to 2015, were referred and the applied ratio of every instrument was investigated. The measurement information was divided into 8 categories including rainfall, debris-flow velocity, displacement, fluid pore pressure, ground vibration, image processing, impact force and peak flow depth. The result of this study revealed that the most applied instruments to be rain gauge and geophone for measuring average rainfall and ground vibration respectively. The Analytic Hierarchical Process (AHP) method was selected to determine installation location of instrument and the weighting factors were estimated through fine content, soil thickness, porosity, shear strength, elastic modulus, hydraulic conductivity and saturation. The soil thickness shows highest weights and the fine content relatively demonstrates lowest weights. The score of each position can be calculated through the weighting factors and the lowest score position can be judged as the weak point. The weak point denotes the easily affecting area and thus, the point is suitable for installing the measurement system. This study suggests a better method for safely managing the debris-flow through a precise location for installing measurement system.

• Spatial Information Research
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• v.9 no.1
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• pp.125-135
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• 2001

Ground failure such as landslide, rock fall land subsidence by heavy rainfall have damaged to people and property. Especially, the damage to important facility such as dam, bridge, tunnel and industrial complex may be possible. Therefore the ground failure must be assessed and counter plan must be prepared. So, the object of this study is to develop the spatial information system for regional ground stability assessment. For this, the topographic, geologic, soil, forest, land use, rainfall frequency map, and satellite image near 40 dams were collected and constructed to the spatial information system. The spatial information system was developed using Avenue in ArcView 3.2 environment and consists of pull down menus and icons. For application of the spatial information system, regional ground stability was assessed in Andong dam. The assessment was ground failure susceptibility and possibility. The spatial information can be used for regional ground stability assessment, prevention and mitigation of hazard, and management of ground as basic data.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.3
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• pp.69-76
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• 2007

Kangwondo area is mountainous and landslide is easily happened easily during the rainy period in summer time. Especially, when there is torrential downpour caused by the unusual weather change, there will be greater possibility to see landslide. Another reason behind landslide is the continuous forest fire in these several years. Since the surface of the earth has been changed by the fire, when rainfall comes, landslide just happens easily. Also, it is reported that landcover condition, excepted rainfall condition, is the most effect for determining landslide susceptibility area. In this study, it is determined a landslide vulnerable area and landcover information is extracted from four satellite image(Landsat TM), about the landslide vulnerable area, which is pictured for each year. And which distribution change is analyzed. also, NDVI picture is made and distribution change of vegetation vitality is analyzed to study that change of landcover have a effect on landslide. As a result, could know that forest and NDVI are decreasing in landslide vulnerable area.

• The Journal of Engineering Geology
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• v.20 no.4
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• pp.381-390
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• 2010

This study assessed the hydrogeological characteristics of a seepage area of white leachate. The geological characteristics of the leachate were determined by a surface survey, and an electrical resistivity survey and borehole image processing system (BIPS) were applied to estimate the distribution of discontinuities, to assess the geological structure of the seepage areas. Fluctuations in groundwater level within boreholes were measured during periods of precipitation in the dry and wet seasons. The results show that electrical resistivity is lower in the seepage section than in non-seepage sections. The distribution of fracture zones and limestone cavities was inferred from the logging data and BIPS data. Variations in groundwater level and groundwater recharge, related to rainfall events, show the direct effect of rainfall events during the rainy season. We obtained a strong relationship between seepage amount and rainfall (correlation coefficients of 0.83-0.97).

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.857-871
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• 2013

The interest in rainfall observation and forecasting using remote sensing method like RADAR (Radio Detection and Ranging) and satellite image is increased according to increased damage by rapid weather change like regional torrential rain and flash flood. In this study, the basin runoff was calculated using adaptive neuro-fuzzy technique, one of the data driven model and MAPLE (McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as one of the input variables. The flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated. Six rainfall events occurred at flood season in 2010 and 2011 in Chungju Reservoir basin were used for the input data. The flood estimation results according to the rainfall data used as training, checking and testing data in the model setup process were compared. The 15 models were composed of combination of the input variables and the results according to change of clustering methods were compared and analysed. From this study was that using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation. The model using MAPLE forecasted precipitation data showed relatively better result at inflow estimation Chungju Reservoir.