• Journal of Korean Society for Geospatial Information Science
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• v.17 no.2
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• pp.55-60
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• 2009

By applying NDVI(Normalized Difference Vegetation Index) and TCT(Tasseled-Cap Transformation) image algorithm on the basis of KOMSAP-2 MSC(Multi Spectral Camera) image(Jun. 12, 2007) for Naenam-myeon, Gyeongju city in this study, DN distribution map was drawn up. Discrimination analysis of image algorithm for the accuracy improvement of forest type classification was conducted through the comparative analysis between the distribution maps of NDVI and TCT DN, and forest field surveying data, and finally, the accuracy of the forest type classification was verified through the overlay analysis with the forest field surveying data. Through this study, it is thought that low cost and high efficiency will be able to be expected in the process of the examination for the automation practicality of the forest type classification and of the production of the accurate forest type classification map by using KOMPSAT-2 MSC image.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.6
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• pp.51-66
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• 2017

This study was conducted to develop detailed evaluation indicator as a way for evaluating sustainable urban ecosystem health focused on ecological urban elements from an eco-cultural point of view after the appearance of Eco-cultural City to meet various needs. And this study was also conducted to search for ways to utilize the detailed evaluation indicator like institutionalization. Eco-cultural City was defined as a city where ecological environment and cultural environment coexist and was aimed to derive applicable planning indicators in Korea. For this, FGI was executed, planning indicators were derived, and suitability was examined. The weights were calculated based on the selected indicators through AHP expert survey. After getting the result of FGI, experts reviewed the adequacy of definition from Eco-cultural City and its necessity, and the applicability of planning indicators was examined with evaluation of suitability. As a result of evaluating suitability, it was judged that 41 indicators based on an overall average of 4 areas were relatively high on suitability and also important among sectors. As for the analysis result, the priority order in multistage classification was as followed : harmony between human and environment(B) 0.349, environmental resources(A) 0.266, city environment and quality of culture(C) 0.208, and role division and citizen participation(D) 0.177. In the second level of relative importance, environment protection and infra in the role and citizen participation section was the highest, 0.449, harmonization policy and system in calculating weights was the highest.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.5
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• pp.342-349
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• 2001

This study was carried out to classify and evaluate the land cover map using Landsat TM data in Pyeongtaeg City. DGPS data, aerial photography, topographical map were used for selection the training sets and accuracy assessment. The overall accuracy and Kappa coefficient of the land cover classification map(using supervised classification with 13 classes) with Landsat TM data(16 June. 1997) were respectively, 86.8%, 85.4%, but the user's accuracy of urban/village and vinyl-house was below 60%, and the producer's accuracy of read and vinyl-house below 70%. Maybe it was caused the spectral reflectance characteristics, heterogeneity and small distribution area on the artificial things such as urban/village, vinyl_house and road, etc. And then, the agricultural land cover classification system using remote sensing data in Korea was to classify level I and II. Level I consisted of 5 classes such as agricultural land, forest land, water, barren land, urban and built-up land.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.619-629
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• 2023

Recent intensification of climate change has led to an increase in damages caused by droughts. Currently, in Korea, the Standardized Precipitation Index (SPI) is used as a criterion to classify the intensity of droughts. Based on the accumulated precipitation over the past six months (SPI-6), meteorological drought intensities are classified into four categories: concern, caution, alert, and severe. However, there is a limitation in classifying drought intensity solely based on precipitation. To overcome the limitations of the meteorological drought warning criteria based on SPI, this study collected emergency water supply damage data from the National Drought Information Portal (NDIP) to classify drought intensity. Factors of SPI, such as precipitation, and factors used to calculate evapotranspiration, such as temperature and humidity, were indexed using min-max normalization. Coefficients for each factor were determined based on the Genetic Algorithm (GA). The drought intensity based on emergency water supply was used as the dependent variable, and the coefficients of each meteorological factor determined by GA were used as coefficients to derive a new Drought Severity Classification Index (DSCI). After deriving the DSCI, cumulative distribution functions were used to present intensity stage classification boundaries. It is anticipated that using the proposed DSCI in this study will allow for more accurate drought intensity classification than the traditional SPI, supporting decision-making for disaster management personnel.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.235-244
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• 2016

In large-area crop classification with MODIS data, a mixed pixel problem caused by the low resolution of MODIS data has been one of main issues. To mitigate this problem, this paper proposes a hierarchical classification algorithm that selectively classifies the specific crop class of interest by using their spectral characteristics. This selective classification algorithm can reduce mixed pixel effects between crops and improve classification performance. The methodological developments are illustrated via a case study in Jilin city, China with MODIS Normalized Difference Vegetation Index (NDVI) and Near InfRared (NIR) reflectance datasets. First, paddy fields were extracted from unsupervised classification of NIR reflectance. Non-paddy areas were then classified into corn and bean using time-series NDVI datasets. In the case study result, the proposed classification algorithm showed the best classification performance by selectively classifying crops having similar spectral characteristics, compared with traditional direct supervised classification of time-series NDVI and NIR datasets. Thus, it is expected that the proposed selective hierarchical classification algorithm would be effectively used for producing reliable crop maps.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.1
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• pp.1-15
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• 2016

This study aims to develop a model by which city bus drivers who are likely to cause an accident can be figured out based on the information about their actual driving records. For this purpose, from the information about the actual driving records of the drivers who have caused an accident and those who have not caused any, significance variables related to traffic accidents are drawn, and the accuracy between models is compared for the classification models developed, applying a discriminant analysis and logistic regression analysis. In addition, the developed models are applied to the data on other drivers' driving records to verify the accuracy of the models. As a result of developing a model for the classification of drivers who are likely to cause an accident, when deceleration ($X_{deceleration}$) and acceleration to the right ($Y_{right}$) are simultaneously in action, this variable was drawn as the optimal factor variable of the classification of drivers who had caused an accident, and the prediction model by discriminant analysis classified drivers who had caused an accident at a rate up to 62.8%, and the prediction model by logistic regression analysis could classify those who had caused an accident at a rate up to 76.7%. In addition, as a result of the verification of model predictive power of the models showed an accuracy rate of 84.1%.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1233-1242
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• 2021

In this study, a model was developed to determine whether flooding occurred using image data, which is unstructured data. CNN-based VGG16 and VGG19 were used to develop the flood classification model. In order to develop a model, images of flooded and non-flooded images were collected using web crawling method. Since the data collected using the web crawling method contains noise data, data irrelevant to this study was primarily deleted, and secondly, the image size was changed to 224×224 for model application. In addition, image augmentation was performed by changing the angle of the image for diversity of image. Finally, learning was performed using 2,500 images of flooding and 2,500 images of non-flooding. As a result of model evaluation, the average classification performance of the model was found to be 97%. In the future, if the model developed through the results of this study is mounted on the CCTV control center system, it is judged that the respons against flood damage can be done quickly.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.6 no.1
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• pp.65-70
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• 2003

This research aims to classify wetland types and evaluate functions of a wetland created by abandoned rice paddies. The case study area is Ja-un wetland in Daejeon Metropolitan City. In this study, wetland types were classified based on the basic elements of wetlands such as hydrology, vegetation, and soil conditions. This study was carried out based upon field surveys, drawing maps and publication, and modified-RAM which can evaluate the general functions and conservation values of wetlands. The analysis shows that several types of wetlands were identified, such as Palustrine/ Perennial/ Hydrophytes, Palustrine/ Perennial/ Openwater, Palustrine/ Seasonal/Herbal, Palustrine/ Seasonal/ Shrub and Scrub, Palustrine/ Seasonal/ Hydrophye, and Riparian/ Seasonal/ Shrub and Scrub in the Ja-un wetland. The average level of functions of the wetlands is very "HIGH", and it is recommended that prompt conservation measures should be taken.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.419-424
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• 2006

We need the acquisition of accurate geographic information as well as immediate updates of information on the city in order to plan and manage the changes of the cities more systematically. The geographic information for judging the changes of the cities can be used not only in various policies and studies, but also as important data themselves that record the growth of cities. In this paper ore could build the GIS database with attribute data about the classification accuracy and the class and by providing the land cover map by each classification method according to the accuracy that the user requires, we could provide more reliable and various information.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.6
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• pp.79-92
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• 2016

The objective of this study is to classify the types of rural areas (138 $si{\cdot}gun$) considering settlement environment by Decision Tree Method (CHAID). The CHAID method was used for decision tree algorithm and the seven dependant variables and 5 explanatory variables were selected, respectively. By decision tree method, rural areas were finally classified into six groups through three separate processes. City area, lower area in aging rate and higher area in farmland area ratio was analyzed to be relatively rich rather than other area in the case of settlement environment index. In the future, this study will be able to utilize as a reference to the planning of rural development projects.