• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.80-89
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• 2008

Mapping applications using satellite imagery have been possible to quantitative analysis since SPOT satellite with stereo image was launched. Especially, high resolution satellite imagery was efficiently used in the field of digital mapping for the areas which are difficult to produce large-scale maps by aerial photogrammetry or carry out ground control point surveying due to unaccessibility. This study extracted the geospatial information out of consideration for topographic characteristic from ortho imagery of the National Geospatial-intelligence Agency(NGA) in the United States of America and analyzed the accuracy of plane coordinate for ortho imagery. For this purpose, the accuracy according to topographic character by comparison between both extraction data from ortho imagery and the digital topographic maps of 1:5000 scale which were produced by Korea National Geographic Information Institute(NGI) was evaluated. It is expected that the results of this study will be fully used as basic information for ground control point acquisition or digital mapping in unaccessible area.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.2
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• pp.81-90
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• 2002

Remote Sensing has been very useful tool in monitoring of cities and updating of GIS database compare to traditional methods due to its benefit; wide range covering on low cost and advanced data collection. However it had come to a limited method in limited researches because of its relatively poor spatial resolution in scanning. Recently launched satellites are able to produce improved imageries, and new commercial services have been commenced for the use of general public with higher spatial resolution up to $1m{\times}1m$. This study tackled a potential use of these improved satellite imageries in urban planning based on the Multi-temporal satellite imagery with particular reference to monitoring on urban areas, for example urbanization and its expanding. i) Portion of individual features and elements in each pixel of satellite imagery was computed based on 'Endmember' of targeted elements. ii) Urbanized areas were categorized based on the 'Fraction imagery' derived from the 'SMA algorithm'. iii) Alterations and expanding of urban areas were identified based on the Multi-temporal satellite imageries. Tested method showed a strong potential to produce more advanced monitoring skills of urban areas.

• Korean Journal of Remote Sensing
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• v.5 no.1
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• pp.13-27
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• 1989

In recent years satellite data have been increasingly used for the analysis of floodprone areas. This study was carried out to demonstrate the usefulness of repetitive satellite imagery in monitoring flood levels of the Pyungchang watershed. Runoff characteristics parameters were analyzed by Soil Conservation Service(SCS) Runoff Curve Number(RCN) based on Landsat imagery and Digital Terrain Model data. The RCN average within the watershed was calculated from RCN estimates for all the pixels(picture elements) and adjusted by antecedent precipitation conditions. The direct runoff hydrograph was derived from the unit hydrograph using SCS dimensionless unit hydrograph and effective rainfalls estimated by the SCS method. In comparsion of the direct runoff hydrograph with the measured rating curve their peak times differ by one hour and peak discharges differ by 5.9 percents of the discharge from each other. It was shown that repetitive satellite image could be very useful in timely estimating watershed runoffs and evaluating ever-changing surface conditions of a river basin.

• Proceedings of the KSRS Conference
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• v.2
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• pp.586-589
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• 2006

High resolution satellite imagery is regarded as one of the important data sets to engineering application, as well as conventional scientific application. However, despite this general view, there are a few target applications using this information. In this study, the possibility for the future wide uses in associated with smart graphics of this information is investigated. The concept of smart graphics can be termed intelligent graphics with XML-based structure and knowledge related to semantic web, which is a useful component for the data dissemination framework model in a multi-layered web-based application. In the first step in this study, high resolution imagery is transformed to GML (Geographic Markup Language)-based structure with attribute schema and geo-references. In the second, this information is linked with GIS data sets, and this fused data set is represented in the X3D (eXtensible 3D), ISO-based web 3D graphic standard, with styling attributes, in the next stop. The main advantages of this approach using GML and X3D are the flourished representations of a source data according to user/clients’ needs and structured 3D visualization linked with other XML-based application. As for the demonstration of this scheme, 3D urban modelling case with actual data sets is presented.

• Korean Journal of Remote Sensing
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• v.17 no.3
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• pp.275-284
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• 2001

This study was carried out to evaluate high resolution satellite imagery of IKONOS for classifying the land cover, especially forest type. The IKONOS imagery of 11km$\times$11km size was taken on April 24, 2000 in Bong-pyoung Myun Pyungchang-Gun, Kangwon Province. Land cover classes were water, coniferous evergreen, Larix leptolepis, broad-leaved tree, bare land, farm land, grassland, sandy soil and asphalted area. Supervised classification method with algorithm of maximum likelihood was applied for classification. The terrestrial survey was also carried out to collect the reference data in this area. The accuracy of the classification was analyzed with the items of overall accuracy, producer's accuracy, user's accuracy and k for test area through the error matrix. In the accuracy analysis of the test area, overall accuracy was 94.3%, producer's accuracy was 77.0-99.9%, user's accuracy was 71.9-100% and k and 0.93. Classes of bare land, sandy soil and farm land were less clear than other classes, whereas classification result of IKONOS in forest area showed higher performance than that of other resolution(5-30m) satellite data.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.71-79
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• 2014

Most researches have created the impervious surface map by using low-spatial-resolution satellite imagery and are inefficient to generate the object-based impervious map with a broad area. In this study, segment-based impervious surface mapping algorithm is proposed using the RapidEye satellite imagery in order to map impervious area. At first, additional bands are generated by using TOA reflectance conversion RapidEye data. And then, shadow and water class are extracted using training data of converted reflectance image. Object-based impervious surface can be generated by spectral mixture analysis based on land cover map of Ministry of Environment with medium scale, in the case of other classes except shadow and water classes. The experiment shows that result by our method represents high classification accuracy compared to reference data, quantitatively.

• Korean Journal of Remote Sensing
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• v.15 no.4
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• pp.357-365
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• 1999

The optical sensors of Electro-Optical Camera (EOC) and Ocean Scanning Multi-spectral Imager (OSMI) aboard the KOrea Multi-Purpose SATellite (KOMPSAT) will be placed in a sun synchronous orbit in late 1999. The EOC and OSMI sensors are expected to produce the land mapping imagery of Korean territory and the ocean color imagery of world oceans, respectively. Utilization of the EOC and OSMI data would encompass the various fields of science and technology such as land mapping, land use and development, flood monitoring, biological oceanography, fishery, and environmental monitoring. Readiness of data support for user community is thus essential to the success of the KOMPSAT program. As a part of testing such readiness prior to the KOMPSAT launch, we have performed the preliminary acceptance test for the KOMPSAT data processing system using the simulated EOC and OSMI data sets. The purpose of this paper is to demonstrate the readiness of the KOMPSAT data processing system, and to help data users understand how the KOMPSAT EOC and OSMI data are processed, archived, and provided. Test results demonstrate that all requirements described in the data processing specification have been met, and that the image integrity is maintained for all products. It is however noted that since the product accuracy is limited by the simulated sensor data, any quantitative assessment of image products can not be made until actual KOMPSAT images will be acquired.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.304-306
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• 2003

Oceanic pycnocline depth is usually obtained from in situ measurements. As ocean internal waves occur on and propagate along oceanic pycnocline, it is possible to estimate the depth remotely. This paper presents a method for retrieving pycnocline depth from synthetic aperture radar (SAR) imagery where internal waves are visible. This model is constructed by combining a two-layer ocean model and a nonlinear internal wave model. It is also assumed that the observed groups of internal wave packets on SAR imagery are generated by local semidiurnal tides. Case study in East China Sea shows a good agreement with in situ CTD data.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.690-706
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• 2021

Classification is a substantial operation in data mining, and each element is distributed taking into account its feature values in the corresponding class. Metaheuristics have been widely used in attempts to solve satellite image classification problems. This article proposes a hybrid approach, the flower pigeons-inspired optimization algorithm (FPIO), and the local search method of the flower pollination algorithm is integrated into the pigeon-inspired algorithm. The efficiency and power of the proposed FPIO approach are displayed with a series of images, supported by computational results that demonstrate the cogency of the proposed classification method on satellite imagery. For this work, the Davies-Bouldin Index is used as an objective function. FPIO is applied to different types of images (synthetic, Alsat-2B, and Sentinel-2). Moreover, a comparative experiment between FPIO and the genetic algorithm genetic algorithm is conducted. Experimental results showed that GA outperformed FPIO in matters of time computing. However, FPIO provided better quality results with less confusion. The overall experimental results demonstrate that the proposed approach is an efficient method for satellite imagery classification.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.671-674
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• 2005

Atmospheric correction over the ocean part is more important than that over the land because the signal from the ocean is very small about one tenth of that reflected from land. In this study, the Spectral Shape Matching Method (SSMM) developed by Ahn and Shanmugam (2004) is evaluated using Landsat imagery acquired over the highly turbid Saemangeum Coastal Area. The result of SSMM is compared with COST model developed by Chavez (1991 and 1997). In principle, SSMM is simple and easy to implement on any satellite imagery, relying on both field and image properties. To assess the potential use of these methods, several field campaigns were conducted in the Saemangeum coastal area corresponding with Landsat-7 satellite's overpass on 29 May 2005. In-situ data collected from the coastal waters of Saemangeum using optical instruments (ASD field spectroradiometer) consists of ChI, Ap, SS, aooM, F(d). In order to perform SSMM, we use the in-situ water-leaving radiance spectra from clear oceanic waters to estimate the the path radiance from total signal recorded at the top of the atmosphere (TOA), due to the reason that the shape of clear water-leaving radiance spectra is nearly stable than turbid water-leaving radiance spectra. The retrieved water-leaving radiance after subtraction of path signal from TOA signal in this way is compared with that estimated by COST model. The result shows that SSMM enabled retrieval of water-leaving radiance spectra that are consistent with in-situ data obtained from Saemangeum coastal waters. The COST model yielded significantly high errors in these areas.