• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.1
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• pp.32-44
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• 1999

Texture features can be incorporated in classification procedure to resolve class confusions. However, there have been few application-oriented studies made to evaluate the relative powers of texture analysis methods in a particular environment. This study evaluates the increases in the land-cover classification accuracy of the SPOT HRV multispectral data of Pusan Metropolitan area from texture processing. Twenty-four texture measures were derived from the SPOT HRV band 3 image. Each of these features were used in combination with the three spectral images in the classification of 10 land-cover classes. Supervised training and a Gaussian maximum likelihood classifier were used in the classification. It was found that while entropy produces the best empirical results in terms of the overall classification, other texture features can also largely improve the classification accuracies obtained by the use of the spectral images only. With the inclusion of texture, the classification for each category improves. Specially, urban built-up areas had much increase in accuracy. The results indicate that texture size 5 by 5 and 7 by 7 may be suitable at land cover classification of Pusan Metropolitan area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.2
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• pp.153-158
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• 2006

A new High Resolution Geometry or HRG imaging instrument is developed by CNES to be carried on-board SPOT 5. The HRG instrument offers a higher ground resolution than that of the HRV/HRVIR on SPOT 1 - 4 satellites. The field width of HRG is 60 km, same as SPOT constellation. With two HRG instruments, a maximum swath of 120 km at 5 m resolution can be achieved. The generation of Digital Elevation Models (DEMs) from satellite stereo images scores over conventional methods of DEM generation using topographic maps and aerial photographs. This global availability of satellite images allows for quicker data processing for an equivalent area. In this study, a HRG stereo images of SPOT 5 over JECHEON has been used with Leica Photogrammetry Suite OrthoBASE Pro tool for the creation of a digital elevation model (DEM). The extracted DEM was compared to the reference DEM obtained from the contours of digital topographic map.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.531-536
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• 2003

In this paper, a camera modeling method that utilizes ephemeris data and imaging geometry is presented. The proposed method constructs a mathematical model only with parameters that are contained in the leader file and does not require any ground control points for model construction. Control points are only needed to eliminate geolocation error of the model that is originated from errors in the parameters that are used in model construction. With few (one or two) of control points, RMS error of less than pixel size can be obtained and control points are not necessarily uniformly distributed over the entire scene. This advantage is crucial in large project and will enable to reduce project cost dramatically.

• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.87-99
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• 2006

The Median Resolution Sensors (MRSs) for land observation such as Landsat-ETM+ and SPOT-HRV are more effective than Ocean Color Sensors (OCSs) for studying of detailed ecological and biogeochemical components of the coastal waters. In this study, we developed suspended sediment algorithm for Landsat TM/ETM+ by considering the spectral response curve of each band. To estimate suspended sediment concentration (SS) from satellite image data, there are two difference types of algorithms, that are derived for enhancing the accuracy of SS from Landsat imagery. Both empirical and remote sensing reflectance model (hereafter referred to as $R_{rs}$ model) are used here. This study tried to compare two algorithm, and verified using in situ SS data. It was found that the empirical SS algorithm using band 2 produced the best result. $R_{rs}$ model-based SS algorithm estimated higher values than empirical SS algorithm. In this study we used $R_{rs}$ model developed by Ahn (2000) focused on the Mediterranean coastal area. That's owing to the difference of oceanic characteristics between Mediterranean and Korean coastal area. In the future we will improve that $R_{rs}$ model for the Korean coastal area, then the result will be advanced.