• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.583-590
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• 2012

This study proposes fusion image matching method according to land cover property to generate a detailed DEM using the high resolution IKONOS-2 stereo pair. A classified image, consists of building, crop-land, forest, road and shadow-water, is produced by color image with four bands. Edges and points are also extracted from panchromatic image. Matching is performed by the cross-correlation computing after five classes are automatically selected in a reference image. In each of building class, crop-land class, forest class and road class, matching was performed by the grid and edge, only grid, only grid, grid and point, respectively. Shadow-water class was excepted in the matching because this area causes excessive error of the DEM. As the results, edge line, building and residential area could be expressed more dense than DEM by the conventional method.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.214-222
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• 2022

Convolutional Neural networks (CNNs) are a category of deep learning networks that have proven very effective in computer vision tasks such as image classification. Notwithstanding, not much has been seen in its use for remote sensing image classification in developing countries. This is majorly due to the scarcity of training data. Recently, transfer learning technique has successfully been used to develop state-of-the art models for remote sensing (RS) image classification tasks using training and testing data from well-known RS data repositories. However, the ability of such model to classify RS test data from a different dataset has not been sufficiently investigated. In this paper, we propose a deep CNN model that can classify RS test data from a dataset different from the training dataset. To achieve our objective, we first, re-trained a ResNet-50 model using EuroSAT, a large-scale RS dataset to develop a base model then we integrated Augmentation and Ensemble learning to improve its generalization ability. We further experimented on the ability of this model to classify a novel dataset (Nig_Images). The final classification results shows that our model achieves a 96% and 80% accuracy on EuroSAT and Nig_Images test data respectively. Adequate knowledge and usage of this framework is expected to encourage research and the usage of deep CNNs for land cover mapping in cases of lack of training data as obtainable in developing countries.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.98-106
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• 2016

Remote sensing is an efficient technology for observing and monitoring the land surfaces inaccessible to humans. This research proposes a methodology for improving the accuracy of the land cover classification using the Landsat-8 operational land imager(OLI) image. The proposed methodology consists of the following steps. First, the normalized difference vegetation index(NDVI) and normalized difference water index(NDWI) images are generated from the given Landsat-8 OLI image. Then, a new image is generated by adding both NDVI and NDWI images to the original Landsat-8 OLI image using the layer-stacking method. Finally, the maximum likelihood classification(MLC), and support vector machine(SVM) methods are separately applied to the original Landsat-8 OLI image and new image to identify the five classes namely water, forest, cropland, bare soil, and artificial structure. The comparison of the results shows that the utilization of the layer-stacking method improves the accuracy of the land cover classification by 8% for the MLC method and by 1.6% for the SVM method. This research proposes a methodology for improving the accuracy of the land cover classification by using the layer-stacking method.

• Proceedings of the KSRS Conference
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• v.2
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• pp.555-558
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• 2006

In recent years, urban development has expanded rapidly in Nawabshah City of Pakistan. A major effect associated with this population trend is transformation of the landscape from natural cover types to increasingly impervious urban land. The core objective of this study are to provide time-series information to define and measure the urban land cover changes of Nawabshah, Pakistan between the years 1992 and 2002, and to examine related urbanization impacts on air quality of the study area. Two multi-temporal Landsat images acquired in 1992 and 2002 together with standard topographical maps to measure land cover changes were used in this study. The image processing and data manipulation were conducted using algorithms supplied with the ERDAS Imagine software. An unsupervised classification approach, which uses a minimum spectral distance to assign pixels to clusters, was used with the overall accuracy ranging from 84 percent to 92 percent. Land cover statistics demonstrate that during the study period (1992-2002) extensive transformation of barren and vegetated lands into urban land have taken place in Nawabshah City. Results revealed that land cover changes due to urbanization has not only contaminated the air quality of the study area but also raised the health concerns for the local residents.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.11
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• pp.1586-1597
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• 2007

This study is an attempt to examine fashion elements appearing in the cover-page design of fashion magazines published in Korea and aims to find Korea#s own fashion identity in fashion styling and designing of those fashion magazines. In order to do so, the study reviewed the related literature and analyzed the issues of Vogue and Harper#s Bazaar magazines published between 2004 and 2006. The results of the study can be summarized as follows: In case of fashion photographs, the largest number of 72 sampled cover-model photographs is in approximately three-quarter cut size. For the items, most take the form of one-piece dress and feature the use of a variety of accessories. In case of dresses, most are the creations of foreign designers and famous fashion models or celebrities show up, mostly alone, as features on the cover pages. Because of the nature of fashion magazines, their primary emphasis is put on the dress among other things, but on the other hand some of those magazines have differential cover pages where the model#s face is highlighted with the look of makeup or a famous female actress stands out. However, the fashion in designing the cover pages of magazines is, rather than to show the dress itself, to create a new combination of different elements as total fashion or convey an image based on such a fashion style.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.105-113
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• 2011

Since existing thematic maps have been made with medium- to low-resolution satellite images, they have several shortcomings including low positional accuracy and low precision of presented thematic information. Digital aerial photo image taken recently can express panchromatic and color bands as well as NIR (Near Infrared) bands which can be used in interpreting forest areas. High resolution images are also available, so it would be possible to conduct precision land cover classification. In this context, this paper implemented object-based land cover classification by using digital aerial photos with 0.12m GSD (Ground Sample Distance) resolution and IKONOS satellite images with 1m GSD resolution, both of which were taken on the same area, and also executed qualitative analysis with ortho images and existing land cover maps to check the possibility of object-based land cover classification using digital aerial photos and to present usability of digital aerial photos. Also, the accuracy of such classification was analyzed by generating TTA(Training and Test Area) masks and also analyzed their accuracy through comparison of classified areas using screen digitizing. The result showed that it was possible to make a land cover map with digital aerial photos, which allows more detailed classification compared to satellite images.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.357-360
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• 2005

Soil loss is widely recognized as a threat to farm livelihoods and ecosystem integrity worldwide. Soil loss prediction models can help address long-range land management planning under natural and agricultural conditions. Even though it is hard to find a model that considers all forms of erosion, some models were developed specifically to aid conservation planners in identifying areas where introducing soil conservation measures will have the most impact on reducing soil loss. Revised Universal Soil Loss Equation (RUSLE) computes the average annual erosion expected on hillslopes by multiplying several factors together: rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C), and support practice (P). The value of these factors is determined from field and laboratory experiments. This study calculated soil erosion using GIS-based RUSLE model in Imha basin and examined soil erosion source area using SPOT 5 high-resolution satellite image and land cover map. As a result of analysis, dry field showed high-density soil erosion area and we could easily investigate source area using satellite image. Also we could examine the suitability of soil erosion area applying field survey method in common areas (dry field & orchard area) that are difficult to confirm soil erosion source area using satellite image.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.378-381
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• 2008

The regulating and relaxing targets in the Land Use Regulation and Total Maximum Daily Loads are influenced by Land cover information. For the providing more accurate land information, this study attempted to generate an impervious surface map using KOMPSAT-2 image which a Korea manufactured high resolution satellite image. The classification progress of this study carried out by tasseled-cap spectral enhancement through each class extraction technique neither existing classification method. KOMPSAT-2 image of this study is enhanced by Soil Brightness Index(SBI), Green vegetation Index(GVI), None-Such wetness Index(NWI). Then ranges of extracted each index in enhanced image are determined. And then, Confidence Interval of classes was determined through the calculating Non-exceedance Probability. Spectral distributions of each class are changed according to changing of Control coefficient(${\alpha}$) at the calculated Non-exceedance Probability. Previously, Land cover classification map was generated based on established ranges of classes, and then, pervious and impervious surface was reclassified. Finally, impervious ratio of reclassified impervious surface map was calculated with blocks in the study area.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.23-30
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• 2012

This paper proposes an improved steganalysis method to detect the existence of secret message. Firstly, we magnify the small stego noise by multiplying the speckle noise to a given image and then we estimate the denoised image by using the soft thresholding method. Because the noises are not perfectly eliminated, some noises exist in the estimated cover image. If the given image is the cover image, then the remained noise will be very small, but if it is the stego image, the remained noise will be relatively large. The parent-child relationship in the wavelet domain will be slighty broken in the stego image. From this characteristic, we extract the joint statistical moments from the difference image between the given image and the denoised image. Additionally, four statistical moments are extracted from the denoised image for the proposed steganalysis method. All extracted features are used as the input of MLP(multilayer perceptron) classifier. Experimental results show that the proposed scheme outperforms previous methods in terms of detection rates and accuracy.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1251-1260
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• 2019

Existing environmental spatial information, which has been concentrated on spatial resolution, has limitations in solving realistic environmental problems that must be accompanied by physical and chemical characterization. Accordingly, there is a need for an image radar capable of identifying physical characteristics of an object regardless of weather conditions, day and night, and sunlight. Image radar is used in various fields in the United States and Europe. The next generation of medium-sized satellite No. 5 in Korea, which is under development with the aim of monitoring water disasters, is also looking for ways to expand the scope to various applications based on the existing application range. To this end, we analyzed domestic and international papers (100 works) using image radar, and reviewed KEI 2016 report, domestic papers, and foreign papers. Based on this, various environmental issues were summarized and the effects of when the image radar was used were analyzed and land cover was selected as an environmental issue. In the future, we will embody the technology to improve the accuracy of the land cover map, which is the environmental issue selected in this study, and build the foundation system for the stable use of the land cover map.