• Ocean and Polar Research
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• v.35 no.4
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• pp.395-405
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• 2013

The aim of this study is to suggest an optimal survey method for coastal habitat monitoring around Weno Island in Chuuk Atoll, Federated States of Micronesia (FSM). This study was carried out to compare and analyze differences between in situ survey (PHOTS) and high spatial satellite imagery (Worldview-2) with regard to the coastal habitat distribution patterns of Weno Island. The in situ field data showed the following coverage of habitat types: sand 42.4%, seagrass 26.1%, algae 14.9%, rubble 8.9%, hard coral 3.5%, soft coral 2.6%, dead coral 1.5%, others 0.1%. The satellite imagery showed the following coverage of habitat types: sand 26.5%, seagrass 23.3%, sand + seagrass 12.3%, coral 18.1%, rubble 19.0%, rock 0.8% (Accuracy 65.2%). According to the visual interpretation of the habitat map by in situ survey, seagrass, sand, coral and rubble distribution were misaligned compared with the satellite imagery. While, the satellite imagery appear to be a plausible results to identify habitat types, it could not classify habitat types under one pixel in images, which in turn overestimated coral and rubble coverage, underestimated algae and sand. The differences appear to arise primarily because of habitat classification scheme, sampling scale and remote sensing reflectance. The implication of these results is that satellite imagery analysis needs to incorporate in situ survey data to accurately identify habitat. We suggest that satellite imagery must correspond with in situ survey in habitat classification and sampling scale. Subsequently habitat sub-segmentation based on the in situ survey data should be applied to satellite imagery.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.663-663
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• 2002

The National Oceanographic Research Institute of KOREA started to survey for the basic data necessary to territorial sea and EEZ identification and marine development with Multi-Beam Echo Sounder(L3 SeaBeam 2112) since 1996. The Multi-Beam surveys has provided a very new and precise way of describing the morphology and nature of the underwater seabed. Multi-Beam Echo Sounder systems employ sound waves propagating at angles which vary from vertical to nearly horizontal. The locations on the bottom where echoes are generated cover a swath whose port to starboard width may be equal to many times the water depth. Newer Multi-beam bathymetric sonars provide both a beam by beam depth and backscatter amplitude of the bottom. But The backscattered amplitude didn't use for identification of bottom properties because backscatter amplitude effects by the many environmental variables of underwater and seabed. We investigates the utilization of geo-referenced backscatter amplitude and analysis of relationship between The Backscattered Amplitude and Sidescan Sonar imagery from Sea Beam 2112. For the backscattered amplitude imagery mainly represents the properties of sediment, we computed the beam geometry, time-varied amplifier gain, and mainly incidence angle to the topography using bathymetric model at each ping. In this paper, those issues are illustrated, and the angular independent imagery based on swath topographic model is described.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.445-449
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• 2005

Various methods to detect the phytoplankton/red tide blooms in the oceanic waters have been developed and tested on satellite ocean color imagery since the last two and half decades, but accurate detection of blooms with these methods remains challenging in optically complex turbid waters, mainly because of the eventual interference of absorbing and scattering properties of dissolved organic and particulate inorganic matters with these methods. The present study introduces a new method called Red tide Index (Rl), providing indices which behave as a good measure of detecting red tide algal blooms in high scattering and absorbing waters of the Korean South Sea and Yellow Sea. The effectiveness of this method in identifying and locating red tides is compared with the standard Ocean Chlorophyll 4 (OC4) bio-optical algorithm applied to SeaWiFS ocean imagery, acquired during two bloom episodes on 27 March 2002 and 28 September 2003. The result revealed that OC4 bio-optical algorithm falsely identifies red tide blooms in areas abundance in colored dissolved organic and particulate inorganic matter constituents associated with coastal areas, estuaries and river mouths, whereas red tide index provides improved capability of detecting, predicting and monitoring of these blooms in both clear and turbid waters.

• Proceedings of the KSRS Conference
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• v.2
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• pp.598-601
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• 2006

Satellite imagery may contain large regions covered with atmospheric aerosol. A high-resolution satellite imagery affected by non-homogenous aerosol cover should be processed for land cover study and perform the radiometric calibration that will allow its future application for Korea Multi-Purpose Satellite (KOMPSAT) data. In this study, aerosol signal was separated from high resolution satellite data based on the reflectance separation method. Since aerosol removal has a good sensitivity over bright surface such as man-made targets, aerosol optical thickness (AOT) retrieval algorithm could be used. AOT retrieval using Look-up table (LUT) approach for utilizing the transformed image to radiometrically compensate visible band imagery is processed and tested in the correction of satellite scenery. Moderate Resolution Imaging Spectroradiometer (MODIS), EO-1/HYPERION data have been used for aerosol correction and AOT retrieval with different spatial resolution. Results show that an application of the aerosol detection for HYPERION data yields successive aerosol separation from imagery and AOT maps are consistent with MODIS AOT map.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.504-507
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• 2007

The KOMPSAT-2 satellite is a push-broom system with MSC (Multi Spectral Camera) which contains a panchromatic band and four multi-spectral bands covering the spectral range from 450nm to 900nm. The PAN band is composed of six CCD array with 2528 pixels. And the MS band has one CCD array with 3792 pixels. Raw imagery generated from a push-broom sensor contains vertical streaks caused by variability in detector response, variability in lens falloff, pixel area, output amplifiers and especially electrical gain and offset. Relative radiometric calibration is necessary to account for the detector-to-detector non-uniformity in this raw imagery. Non-uniformity correction (NUC) is that the process of performing on-board relative correction of gain and offset for each pixel to improve data compressibility and to reduce banding and streaking from aggregation or re-sampling in the imagery. A relative gain and offset are calculated for each detector using scenes from uniform target area such as a large desert, forest, sea. In the NUC of KOMPSAT-2, The NUC table for each pixel are divided as HF NUC (high frequency NUC) and LF NUC (low frequency NUC) to apply to few restricted facts in the operating system ofKOMPSAT-2. This work presents the algorithm and process of NUC table generation and shows the imagery to compare with and without calibration.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.14-17
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• 2007

To make use of surveying data obtained from different sensors and different techniques in a common reference frame, it is a pre-requite step to register them in a common coordinate system. For this purpose, we have developed a methodology to register IKONOS-2 Satellite Imagery using ALS data. To achieve this, conjugate features from these data should be extracted in advance. In the study, linear features are chosen as conjugate features because they can be accurately extracted from man-made structures in urban area, and more easily than point features from ALS data. Then, observation equations are established from similarity measurements of the extracted features. During the process, considering the characteristics of systematic errors in IKONOS-2 satellite imagery, the transformation function were selected and used. In addition, we also analyzed how the number of linear features and their spatial distribution used as control features affect the accuracy of registration. Finally, the results were evaluated statistically and the results clearly demonstrated that the proposed algorithms are appropriate to register these data.

• 한국공간정보시스템학회:학술대회논문집
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• 2002.03a
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• pp.45-52
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• 2002

Artificial neural networks (ANN) have been successfully used for classifying remotely sensed imagery. However, ANN still is not the preferable choice for classification over the conventional classification methodology such as the maximum likelihood classifier commonly used in the industry production environment. This can be attributed to the ANN characteristic built-in stochastic process that creates difficulties in dealing with unequally represented training classes, and its training performance speed. In this paper we examined some practical aspects of training classes when using a back propagation neural network model for remotely sensed imagery. During the classification process of remotely sensed imagery, representative training patterns for each class are collected by polygons or by using a region-growing methodology over the imagery. The number of collected training patterns for each class may vary from several pixels to thousands. This unequally populated training data may cause the significant problems some neural network empirical models such as back-propagation have experienced. We investigate the effects of training over- or under- represented training patterns in classes and propose the pattern repopulation algorithm, and an adaptive alpha adjustment (AAA) algorithm to handle unequally represented classes. We also show the performance improvement when input patterns are presented in random fashion during the back-propagation training.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.309-312
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• 2004

In mountainous area with high relief, topography may cause cast shadows due to the blocking of direct solar radiation. Remote sensing images of these landscapes display reduced values of reflectance for shadowed areas compared to non-shadowed areas with similar surface cover characteristics. A variety of approaches are possible, though a common step in various active approaches is first to delineate the shadows using automated algorithm and digital surface model (or digital elevation model). This articles demonstrates a common confusion caused by cast shadows

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.295-298
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• 2006

본격적인 지표 피복 분류 수행 전 국내 지형 특성에 부합하는 분석을 위해 위성영상 전처리 과정으로 지형보정 수행이 필요하다. 수치지형도로부터 추출된 수치고도모델과 고분광영상을 이용하여 충청남도 홍성군에 위치한 암반 사면에서의 지형보정을 cosine 보정법, Minnaert 보정법, c 보정법을 이용하여 수행하였다. 세 방법을 사용하여 화강암 단일 암종으로 이루어진 클래스의 화소값 표준편차를 비교 분석한 결과 cosine 보정법, c 보정법보다 Minnaert 보정법을 이용한 방법에서 향상된 결과가 도출되었다.

• 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.