• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.573-587
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• 2019

A multi-temporal approach using remotely sensed time series data obtained over multiple years is a very useful method for monitoring land covers and land-cover changes. While spectral-based methods at any particular time limits the application utility due to instability of the quality of data obtained at that time, the approach based on the temporal profile can produce more accurate results since data is analyzed from a long-term perspective rather than on one point in time. In this study, a multi-temporal approach applying a multi-periodic harmonic model is proposed for classification of remotely sensed data. A harmonic model characterizes the seasonal variation of a time series by four parameters: average level, frequency, phase, and amplitude. The availability of high-quality data is very important for multi-temporal analysis.An satellite image usually have many unobserved data and bad-quality data due to the influence of observation environment and sensing system, which impede the analysis and might possibly produce inaccurate results. Harmonic analysis is also very useful for real-time data reconstruction. Multi-periodic harmonic model is applied to the reconstructed data to classify land covers and monitor land-cover change by tracking the temporal profiles. The proposed method is tested with the MODIS and GOCI NDVI time series over the Korean Peninsula for 5 years from 2012 to 2016. The results show that the multi-periodic harmonic model has a great potential for classification of land-cover types and monitoring of land-cover changes through characterizing annual temporal dynamics.

• Journal of the Korean GEO-environmental Society
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• v.6 no.1
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• pp.15-21
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• 2005

In this study, the utilization of coal-ash and phosphogypsum was considered as the evapotranspiration final landfill cover(ET cover) material. Cover material considered was the mixture of the weathered granite soil, coal-ash and phosphogypsum and so we sequentially performed the leaching test, column test and field model test to investigate the environmental effects of mixtures of coal-ash and phosphogypsum. In the leaching test, all materials had lower heavy metal concentration than the regulated threshold values. The column test and the review of related regulations were carried out to determine the optimum mixing ratio(OMR) and OMR was soil(4):coal-ash(1): phosphogypsum(1) on the volume base, which was applied to field model test. Field model tests were continued from February to June, 2004 in the soil box that was constructed with cement block. It was verified that coal-ash and phospogypsum mixed with soil was safe environmentally and the mixture of both wastes could improve the water retention capacity of cover materials.

• KCID journal
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• v.14 no.2
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• pp.225-235
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• 2007

The shape of streamflow hydrograph during the early period of spring is very much controlled by the area and depth of snow cover especially in mountainous area. When we simulate the streamfolw of a watershed snowmelt, we need some information for snow cover extent and depth distribution as parameters and input data in the hydrological models. The purpose of this study is to suggest an extraction method of snow cover area and snow depth distribution using Terra MODIS image. Snow cover extent for South Korea was extracted for the period of December 2000 and April 2006. For the snow cover area, the snow depth was interpolated using the snow depth data from 69 meteorological observation stations. With these data, it is necessary to run a hydrological model considering the snow-related data and compare the simulated streamflow with the observed data and check the applicability for the snowmelt simulation.

• Journal of Industrial Technology
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• v.24 no.A
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• pp.227-238
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• 2004

This paper is results of experimental and nunerical works on the behavior of the cut-and-cover tunnel. Centrifuge model tests were performed to simulate the behavior of the cut-and-cover tunnels having cross sections of national road and subway tunnels. Model experiments were carried out with changing the cut slope and the slope of filling ground surface. Displacements of tunnel lining resulted from artificially accelerated gravitational force up to 40g of covered material used in model tests, were measured during centrifuge model tests. In model tests, Jumunjin Standard Sand with the relative density of 80 % and the zinc plates were used for the covered material and the flexible tunnel lining, respectively. Basic soil property tests were performed to obtain it's the property of Jumumjin Standard Sand. Shear strength parameters of Jumunjin Standard Sand were obtained by performing the triaxial compression tests. Direct shear tests were also carried out to find the mechanical properties of the interface between the lining and the covered material. Numerical analysis with the commercially available program of FLAC were performed to compare with results of centrifuge model experiment In numerical modelling. Mohr-Coulomb elasto-plastic constitutive model was used to simulaye the behavoor of Jumunjin Standard Sand and the interface element between the lining and the covered material was implemented to simulate the interaction between them. Compared results between model tests and numerical estimation with respect to displacement of the lining showed in good agreements.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.3
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• pp.25-39
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• 2013

In this study, the change of the discharge according to the land cover change which acts as one of dominant factors for the outlook of future discharge was analyzed using SWAT(Soil and Water Assessment Tool) model for Yongdam and Daecheong Dam Watershed in the Geum River Basin. The land cover maps generated by Landsat TM satellite images in the past 1990 and 1995 were used as observed data to simulate the land cover in 2000 by CA-Markov serial technique and after they were compared and verified, the changes of land cover in 2050 and 2100 in the future were simulated. The discharge before and after the change of land cover by using input data of SWAT model was compared and analyzed under the A1B scenario. As a result of analyzing the trend in the elapses of year on the land cover in the Geum River Basin, the forest and rice paddy class area steadily decreased while the urban, bare ground and grassland classes increased. As a result of analyzing the change of discharge considering the future change of the land cover, it appeared that the discharge considering the change of land cover increases by 1.83~2.87% on the whole compared to the discharge not considering the change of land cover.

• Atmosphere
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• v.15 no.2
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• pp.75-90
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• 2005

This study examines the impacts of land cover changes on the East Asia summer monsoon with the National Center for Atmospheric Research Regional Climate Model (NCAR RegCM2), coupled with Biosphere Atmosphere Transfer Scheme (BATS). To assess the goals, two types of land cover maps were used in the simulation of summer climate. One type was NCAR land cover map (CTL) and the other was current land cover map derived from satellite data (land cover: LCV). Warm and cold surface temperature biases of $1-3^{\circ}C$ occurred over central China and Mongolia in CTL. The model produced excessive precipitation over northern land area but less over southern ocean of the model domain. Changes of biophysical parameters, such as albedo, minimum stomatal resistance and roughness length, due to the land cover changes resulted in the alteration of land-atmosphere interactions. Latent heat flux and wind speed in LCV increased noticeably over central China where deciduous broad leaf trees have been replaced by mixed farm and irrigated crop. As a result, the systematic warm biases over central China were greatly reduced in LCV. Strong cooling of central China decreased pressure gradient between East Asian continent and Pacific Ocean. The decreased pressure gradient suppressed the northward transport of moisture from south China and South China Sea. These changes reduced not only the excessive precipitation over north China and Mongolia but also less precipitation over south China. However, the land cover changes increased the precipitation over the Korean Peninsula and the Japan Islands, especially in July and August.

• Structural Engineering and Mechanics
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• v.30 no.6
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• pp.713-732
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• 2008

Serviceability and durability of the concrete members can be seriously affected by the corrosion of steel rebar. Carbonation front and or chloride ingress can destroy the passive film on rebar and may set the corrosion (oxidation process). Depending on the level of oxidation (expansive corrosion products/rust) damage to the cover concrete takes place in the form of expansion, cracking and spalling or delamination. This makes the concrete unable to develop forces through bond and also become unprotected against further degradation from corrosion; and thus marks the end of service life for corrosion-affected structures. This paper presents an analytical model that predicts the weight loss of steel rebar and the corresponding time from onset of corrosion for the known corrosion rate and thus can be used for the determination of time to cover cracking in corrosion affected RC member. This model uses fully the thick-walled cylinder approach. The gradual crack propagation in radial directions (from inside) is considered when the circumferential tensile stresses at the inner surface of intact concrete have reached the tensile strength of concrete. The analysis is done separately with and without considering the stiffness of reinforcing steel and rust combine along with the assumption of zero residual strength of cracked concrete. The model accounts for the time required for corrosion products to fill a porous zone before they start inducing expansive pressure on the concrete surrounding the steel rebar. The capability of the model to produce the experimental trends is demonstrated by comparing the model's predictions with the results of experimental data published in the literature. The effect of considering the corroded reinforcing steel bar stiffness is demonstrated. A sensitivity analysis has also been carried out to show the influence of the various parameters. It has been found that material properties and their inter-relations significantly influence weight loss of rebar. Time to cover cracking from onset of corrosion for the same weight loss is influenced by corrosion rate and state of oxidation of corrosion product formed. Time to cover cracking from onset of corrosion is useful in making certain decisions pertaining to inspection, repair, rehabilitation, replacement and demolition of RC member/structure in corrosive environment.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1911-1923
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• 2022

The availability of high-resolution satellite images provides precise information without direct observation of the research target. Korea Multi-Purpose Satellite (KOMPSAT), also known as the Arirang satellite, has been developed and utilized for earth observation. The machine learning model was continuously proven as a good classifier in classifying remotely sensed images. This study aimed to compare the performance of the support vector machine (SVM) model in classifying the land cover of the Delaware River port area on high and medium-resolution images. Three optical images, which are KOMPSAT-2, KOMPSAT-3A, and Sentinel-2B, were classified into six land cover classes, including water, road, vegetation, building, vacant, and shadow. The KOMPSAT images are provided by Korea Aerospace Research Institute (KARI), and the Sentinel-2B image was provided by the European Space Agency (ESA). The training samples were manually digitized for each land cover class and considered the reference image. The predicted images were compared to the actual data to obtain the accuracy assessment using a confusion matrix analysis. In addition, the time-consuming training and classifying were recorded to evaluate the model performance. The results showed that the KOMPSAT-3A image has the highest overall accuracy and followed by KOMPSAT-2 and Sentinel-2B results. On the contrary, the model took a long time to classify the higher-resolution image compared to the lower resolution. For that reason, we can conclude that the SVM model performed better in the higher resolution image with the consequence of the longer time-consuming training and classifying data. Thus, this finding might provide consideration for related researchers when selecting satellite imagery for effective and accurate image classification.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1470-1472
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• 2003

Hyperion, as hyperspectral data, is carried on NASA’s EO-1 satellite, can be used in more subtle discrimination on forest cover, with 224 band in 360 ?2580 nm (10nm interval). In this study, Hyperion image is used to investigate the effects of topography on the classification of forest cover, and to assess whether the topographic correction improves the discrimination of species units for practical forest mapping. A publicly available Digital Elevation Model (DEM), at a scale of 1:25,000, is used to model the radiance variation on forest, considering MSR(Mean Spectral Ratio) on antithesis aspects. Hyperion, as hyperspectral data, is corrected on a pixel-by-pixel basis to normalize the scene to a uniform solar illumination and viewing geometry. As a result, the approach on topographic effect normalization in hyperspectral data can effectively reduce the variation in detected radiance due to changes in forest illumination, progress the classification of forest cover.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.269-282
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• 2023

The purpose of this study was to construct land cover maps using a deep learning model and to select the optimal deep learning model for land cover classification by adjusting the dataset such as input image size and Stride application. Two types of deep learning models, the U-net model and the DeeplabV3+ model with an Encoder-Decoder network, were utilized. Also, the combination of the two deep learning models, which is an Ensemble model, was used in this study. The dataset utilized RapidEye satellite images as input images and the label images used Raster images based on the six categories of the land use of Intergovernmental Panel on Climate Change as true value. This study focused on the problem of the quality improvement of the dataset to enhance the accuracy of deep learning model and constructed twelve land cover maps using the combination of three deep learning models (U-net, DeeplabV3+, and Ensemble), two input image sizes (64 × 64 pixel and 256 × 256 pixel), and two Stride application rates (50% and 100%). The evaluation of the accuracy of the label images and the deep learning-based land cover maps showed that the U-net and DeeplabV3+ models had high accuracy, with overall accuracy values of approximately 87.9% and 89.8%, and kappa coefficients of over 72%. In addition, applying the Ensemble and Stride to the deep learning models resulted in a maximum increase of approximately 3% in accuracy and an improvement in the issue of boundary inconsistency, which is a problem associated with Semantic Segmentation based deep learning models.