• Journal of Wetlands Research
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• v.7 no.2
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• pp.121-132
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• 2005

To classify the surface sedimentary facies using IKONOS image collected over Hwangdo tidal flat in Cheonsu Bay, the optical reflectance was compared for characterizing various sedimentary environments such as grain size, tidal channel pattern and area ratio of surface remnant water. The intertidal DEM (Digital Elevation Model) was generated by echo-sounder for analyzing the relationship between IKONOS image and sedimentary environments including topography. The boundary of the optical reflectance between mud-mixed facies and sand facies was distinct, and discrimination of the associated sandbar feature was also possible. The mud-mixed facies coupled with intricate tidal channels is confined to the relatively hi호 topography of Hwangdo tidal flat. The boundary between mud and mixed flat was indistinct in IKONOS optical reflectance but it would have a difference in the area ratio of surface remnant water. The dark area in the image represented the well developed sand facies having a lot of surface remnant water due to the relatively low surface topography. The overall accuracy of characterizing the surface sediment facies by maximum likelihood classification method was 86.2 %. These results demonstrate that high spatial resolution satellite imagery such as IKONOS coupled with knowledge of grain size, surface remnant water and tidal channel network can be effectively used to characterize the surface sedimentary facies (mud, mixed and sand) network of the tidal flat environments.

• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.135-143
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• 2005

RPC(Rational Polynomial Camera) models have become the replacement model of choice for a number of high resolution satellite imagery providers. RPCs(Rational Polynomial Coefficients) provide a compact accurate representation of the ground to image geometry, allowing users to perform full photogrammetric processing of satellite imagery including block adjustment, 3D feature extraction and orthorectification. This paper presents an algorithm for 3D feature extraction using downhill simpler method which requires only function evaluations, not derivatives. The algorithm was implemented as an executable software program and tested using stereo IKONOS images of Seoul city. The results showed that the proposed algorithm was fast and accurate enough to be used as a practical method for the 3D feature extraction from stereo images with RPCs.

• Proceedings of the KSRS Conference
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• v.1
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• pp.426-429
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• 2006

Flood caused by Typhoon and severe rain during summer is the most destructive natural disasters in Korea. Almost every year flood has resulted in a big lost of national infrastructure and loss of civilian lives. It usually takes time and great efforts to estimate the flood-related damages. Government also has pursued proper standard and tool for using state-of-art technologies. High resolution satellite imagery is one of the most promising sources of ground truth information since it provides detailed and current ground information such as building, road, and bare ground. Once high resolution imagery is utilized, it can greatly reduce the amount of field work and cost for flood related damage assessment. The classification of high resolution image is pre-required step to be utilized for the damage assessment. The classified image combined with additional data such as DEM and DSM can help to estimate the flooded areas per each classified land use. This paper applied object-oriented classification scheme to interpret an image not based in a single pixel but in meaningful image objects and their mutual relations. When comparing it with other classification algorithms, object-oriented classification was very effective and accurate. In this paper, IKONOS image is used, but similar level of high resolution Korean KOMPSAT series can be investigated once they are available.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_2
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• pp.587-597
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• 2007

This study determines matching size for digital elevation model (DEM) production according to land cover property from IKONOS Geo-level stereo image. We applied area based matching method using correlation coefficient of pixel brightness value between the two images. After matching line (where "matching line" implies straight line that is approximated to complex non-linear epipolar geometry) is established by exterior orientation parameters to minimize search area, the matching is carried out based on this line. The experiment is performed according to land cover property, which is divided off into four areas (water, urban land, forest land and agricultural land). In each of the test areas, matching size is selected using a correlation-coefficient image and parallax image. As the results, optimum matching size of the images was selected as $81{\times}81$ pixels window, $21{\times}21$ pixels window, $119{\times}119$ pixels window and $51{\times}51$ pixels window in the water area, urban land, forest land and agricultural land, respectively.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.121-128
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• 2014

This study investigated the accuracy of DEM generated by heterogeneous stereo satellite images based on RPC. Heterogeneous sensor images with different spatial resolution are SPOT-5 panchromatic and IKONOS images. For the accuracy evaluation of the DEM, we compared the DEMs generated from two kinds of sensors and that produced using homogeneous SPOT-5 and IKONOS stereo images. As results of the evaluation, accuracy of 3D positioning by heterogeneous images was substantially similar to that of homogeneous stereo images for exact conjugate points. But, in terms of quality of the DEM, DEM generated by heterogeneous sensor showed a lower accuracy about twice in RMSE and about 3 times in LE90 than that of homogeneous sensors. As a result, DEM can be generated by using heterogenous satellite imagery. But if we use a stereo image with different spatial resolution, the performance of image matching was very important factor for the production of high-quality DEM.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.113-117
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• 2007

In this paper, we propose a new method for determining automatically the size of the matching window using histogram of the gradient in order to improve the performance of stereo matching using one-meter resolution satellite imagery. For each pixel, we generate Flatness Index Image by calculating the mean value of the vertical or horizontal intensity gradients of the 4-neighbors of every pixel in the entire image. The edge pixel has high flatness index value, while the non-edge pixel has low flatness index value. By using the histogram of the Flatness Index Image, we find a flatness threshold value to determine whether a pixel is edge pixel or non-edge pixel. If a pixel has higher flatness index value than the flatness threshold value, we classify the pixel into edge pixel, otherwise we classify the pixel into non-edge pixel. If the ratio of the number of non-edge pixels in initial matching window is low, then we consider the pixel to be in homogeneous region and enlarge the size of the matching window We repeat this process until the size of matching window reaches to a maximum size. In the experiment, we used IKONOS satellite stereo imagery and obtained more improved matching results than the matching method using fixed matching window size.

• Proceedings of the KSRS Conference
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• v.2
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• pp.772-775
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• 2006

Muilti-dimensional feature vector matching algorithm uses multiple features such as intensity, gradient, variance, first or second derivative of a pixel to find correspondence pixels in stereo images. In this paper, we proposed a new method for adjusting automatically the weight of feature in multi-dimensional feature vector matching considering sharpeness of a pixel in feature vector distance curve. The sharpeness consists of minimum and maximum vector distances of a small window mask. In the experiment we used IKONOS satellite stereo imagery and obtained accurate matching results comparable to the manual weight-adjusting method.

• Proceedings of the KSRS Conference
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• v.2
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• pp.606-609
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• 2006

Extraction of building is one of essential issues for the 3D city models generation. In recent years, high-resolution satellite imagery has become widely available, and this shows an opportunity for the urban mapping. In this paper, we have developed a semi-automatic algorithm to extract 3D buildings in urban settlements areas from high-spatial resolution panchromatic imagery. The proposed algorithm determines building height interactively by projecting shadow regions for a given building height onto image space and by adjusting the building height until the shadow region and actual shadow in the image match. Proposed algorithm is tested with IKONOS images over Deajeon city and the algorithm showed promising results.┌阀؀䭏佈䉌ᔀ鳪떭臬隑駭验耀

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.3-11
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• 2009

This study aims at proposing that high resolution satellite images could be used to form an urban management plan by calculating the amount of green areas and detecting land use changes in each zoning region within urban planning jurisdiction of Jinju in Gyeongsangnam-do selected as a case study area, analysing imagery of IKONOS and KOMPSAT-2 that are high resolution satellite images. In conclusion, application possibilities of high resolution satellite images as assessment data of urban management administration that help to assess changes in each zoning region are indicated after developing modules based on ArcGIS for calculation and detection of green areas and land use changes and then analysing land use changes and spatial distribution of green areas by using those modules.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.4 s.22
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• pp.41-50
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• 2002

RPM is the one of the sensor models which is proposed by Open GIS Consortium (OGC) as image transfer standard. And it is the sensor model for end-users using IKONOS, a commercial pushbroom satellite, imagery which provide about 1m ground resolution. Parameters called RPC which is IKONOS RFM coefficients are serviced to end-users. But if some users try to make additional effort to get rigorous geo-spatial information, it is necessary to apply mathematic or abstract sensor models, because vendors don't offer any ancillary data for physical sensor models such as satellite orbit and navigation. Abstract sensor models such as pushbroom Direct Linear Transform (DLT) require many GCPs well distributed in imagery, and mathematic sensor model such as RFM, polynomials need much more GCPs. Therefore RPC modification using additional a few GCPs is the best solution. In this paper, two methods are proposed to modify RPC. One is method to use pseudo GCPs generated in normalized cubic, and another method uses parameters observations and a few GCPs. Through two methods, we get improvement of accuracy 50% and over.