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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Korean Journal of Remote Sensing
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Journal DOI :
The Korean Society of Remote Sensing
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Volume & Issues
Volume 24, Issue 6 - Dec 2008
Volume 24, Issue 5 - Oct 2008
Volume 24, Issue 4 - Aug 2008
Volume 24, Issue 3 - Jun 2008
Volume 24, Issue 2 - Apr 2008
Volume 24, Issue 1 - Feb 2008
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Mashup Application for Geo-spatial Feature Generation on Web Browser using Google Maps API
Park, Yong-Jae ; Lee, Ki-Won ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 389~396
In these days, various kinds of web applications based on web 2.0 paradigm have been developed. In web 2.0 paradigm pursuing participation, sharing, and openness on the web-as-platform, web mapping or web GIS application are regarded as top most applications, so that web applications, handling geo-spatial contents, with user-interaction interface and search engine of high performance have been provided for both public users and expert users in the special domains. Public and industrial needs for web mapping mashup application by open API, linked with the practical web computing technologies, are gradually increasing. In this study, a user interface in mashup for geo-spatial feature generation was implemented by using mainly Google maps API. Spatial database resources in this implementation are those of Google mapping server. As the results, public users on web client can create their own geo-spatial data sets in web vector formats, without the help of any GIS tools or access to proprietary databases. It is concluded that web-based mashup application in client-side using open API can be used as an alternative for geo-browsing system or portable feature generation system.
Development and Verification of the Compact Airborne Imaging Spectrometer System
Lee, Kwang-Jae ; Yong, Sang-Soon ; Kim, Yong-Seung ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 397~408
A wide variety of applications of imaging spectrometer have been proved using data from airborne systems. The Compact Airborne Imaging Spectrometer System (CAISS) was jointly designed and developed as the airborne hyperspectral imaging system by Korea Aerospace Research Institute (KARI) and ELOP inc., Israel. The primary mission of the CAISS is to acquire and provide full contiguous spectral information with high spatial resolution for advanced applications in the field of remote sensing. The CAISS consists of six physical units; the camera system, the gyro-stabilized mount, the jig, the GPS/INS, the power inverter and distributor, and the operating system. These subsystems are to be tested and verified in the laboratory before the flight. Especially the camera system of the CAISS has to be calibrated and validated with the calibration equipments such as the integrating sphere and spectral lamps. To improve data quality and its availability, it is the most important to understand the mechanism of imaging spectrometer system and the radiometric and spectral characteristics. The several performance tests of the CAISS were conducted in the camera system level. This paper presents the major characteristics of the CAISS, and summarizes the results of performance tests in the camera system level.
KOMPSAT-2 Terminal for Polar Station (K2PS) Development by KARI
Koo, In-Hoi ; Kang, Ji-Hoon ; Bae, Hee-Jin ; Ahn, Sang-Il ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 409~416
Recently, KARI developed "KOMPSAT-2 Terminal for Polar Station" which is high performance system newly required for stimulating KOMPSAT-2 application. The KOMPSAT-2 Terminal for Polar Station consists of one receiving system and two processing systems. The receiving system has been installed at Svalbard Satellite Station located at Norwegian Svalbard island. and the two receiving systems have been installed at Kongsberg Satellite Service AS located at Tromso Norway and Spot Image SA located at Toulouse France respectively. In this paper overall items of KOMPSAT-2 Terminal for Polar Station, which includes requirements, designs and operation concepts, are to be addressed with the verification result on its performance.
ATC: An Image-based Atmospheric Correction Software in MATLAB and SML
Choi, Jae-Won ; Won, Joong-Sun ; Lee, Sa-Ro ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 417~425
An image-based atmospheric correction software ATC is implemented using MATLAB and SML (Spatial Modeler Language in ERDAS IMAGINE), and it was tested using Landsat TM/ETM+ data. This ATC has two main functional modules, which are composed of a semiautomatic type and an automatic type. The semi-automatic functional module includes the Julian day (JD), Earth-Sun distance (ESD), solar zenith angle (SZA) and path radiance (PR), which are programmed as individual small functions. For the automatic functional module, these parameters are computed by using the header file of Landsat TM/ETM+. Three atmospheric correction algorithms are included: The apparent reflectance model (AR), one-percent dark object subtraction technique (DOS), and cosine approximation model (COST). The ACT is efficient as well as easy to use in a system with MATLAB and SML.
Radar Remote Sensing of Soil Moisture and Surface Roughness for Vegetated Surfaces
Oh, Yi-Sok ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 427~436
This paper presents radar remote sensing of soil moisture and surface roughness for vegetated surfaces. A precise volume scattering model for a vegetated surface is derived based on the first-order radiative transfer technique. At first, the scattering mechanisms of the scattering model are analyzed for various conditions of the vegetation canopies. Then, the scattering model is simplified step by step for developing an appropriate inversion algorithm. For verifying the scattering model and the inversion algorithm, the polarimetric backscattering coefficients at 1.85 GHz, as well as the ground truth data, of a tall-grass field are measured for various soil moisture conditions. The genetic algorithm is employed in the inversion algorithm for retrieving soil moisture and surface roughness from the radar measurements. It is found that the scattering model agrees quite well with the measurements. It is also found that the retrieved soil moisture and surface roughness parameters agree well with the field-measured ground truth data.
Selecting Optimal Basis Function with Energy Parameter in Image Classification Based on Wavelet Coefficients
Yoo, Hee-Young ; Lee, Ki-Won ; Jin, Hong-Sung ; Kwon, Byung-Doo ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 437~444
Land-use or land-cover classification of satellite images is one of the important tasks in remote sensing application and many researchers have tried to enhance classification accuracy. Previous studies have shown that the classification technique based on wavelet transform is more effective than traditional techniques based on original pixel values, especially in complicated imagery. Various basis functions such as Haar, daubechies, coiflets and symlets are mainly used in 20 image processing based on wavelet transform. Selecting adequate wavelet is very important because different results could be obtained according to the type of basis function in classification. However, it is not easy to choose the basis function which is effective to improve classification accuracy. In this study, we first computed the wavelet coefficients of satellite image using ten different basis functions, and then classified images. After evaluating classification results, we tried to ascertain which basis function is the most effective for image classification. We also tried to see if the optimum basis function is decided by energy parameter before classifying the image using all basis functions. The energy parameters of wavelet detail bands and overall accuracy are clearly correlated. The decision of optimum basis function using energy parameter in the wavelet based image classification is expected to be helpful for saving time and improving classification accuracy effectively.
Study on Ship Detection Using SAR Dual-polarization Data: ENVISAT ASAR AP Mode
Yang, Chan-Su ; Ouchi, Kazuo ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 445~452
Preliminary results are reported on ship detection using coherence images computed from cross-correlating images of multi-look-processed dual-polarization data (HH and HV) of ENVISAT ASAR. The traditional techniques of ship detection by radars such as CFAR (Constant False Alarm Rate) rely on the amplitude data, and therefore the detection tends to become difficult when the amplitudes of ships images are at similar level as the mean amplitude of surrounding sea clutter. The proposed method utilizes the property that the multi-look images of ships are correlated with each other. Because the inter-look images of sea surface are covered by uncorrelated speckle, cross-correlation of multi-look images yields the different degrees of coherence between the images and water. In this paper, the polarimetric information of ships, land and intertidal zone are first compared based on the cross-correlation between HH and HV images, In the next step, we examine the technique when the dual-polarization data are split into two multi-look images, It was shown that the inter-look cross-correlation method could be applicable in the performance improvement of small ship detection and the land masking, It was also found that a simple combination of coherence images from each co-polarised (HH) inter-look and cross-polarised (HV) inter-look data can provide much higher target-detection possibilities
Geostatistical Integration of Different Sources of Elevation and its Effect on Landslide Hazard Mapping
Park, No-Wook ; Kyriakidis, Phaedon C. ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 453~462
The objective of this paper is to compare the prediction performances of different landslide hazard maps based on topographic data stemming from different sources of elevation. The geostatistical framework of kriging, which can properly integrate spatial data with different accuracy, is applied for generating more reliable elevation estimates from both sparse elevation spot heights and exhaustive ASTER-based elevation values. A case study from Boeun, Korea illustrates that the integration of elevation and slope maps derived from different data yielded different prediction performances for landslide hazard mapping. The landslide hazard map constructed by using the elevation and the associated slope maps based on geostatistical integration of spot heights and ASTER-based elevation resulted in the best prediction performance. Landslide hazard mapping using elevation and slope maps derived from the interpolation of only sparse spot heights showed the worst prediction performance.
Ortho-rectification of a Digital Aerial Image using LiDAR-derived Elevation Model in Forested Area
Yoon, Jong-Suk ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 463~471
The quality of orthoimages mainly depends on the elevation information and exterior orientation (EO) parameters. Since LiDAR data directly provides the elevation information over the earth's surface including buildings and trees, the concept of true orthorectification has been rapidly developed and implemented. If a LiDAR-driven digital surface model (DSM) is used for orthorectification, the displacements caused by trees and buildings are effectively removed when compared with the conventional orthoimages processed with a digital elevation model (DEM). This study utilized LiDAR data to generate orthorectified digital aerial images. Experimental orthoimages were produced using digital terrain model (DTM) and DSM. For the preparation of orthorectification, EO components, one of the inputs for orthorectification, were adjusted with the ground control points (GCPs) collected from the LiDAR point data, and the ground points were extracted by a filtering method used in a previous research. The orthoimage generated by DSM corresponded more closely to non-ground LiDAR points than the orthoimage produced by DTM.
The Application of BP and RBF Neural Network Methods on Vehicle Detection in Aerial Imagery
Choi, Jae-Young ; Jang, Hyoung-Jong ; Yang, Young-Kyu ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 473~481
This paper presents an approach to Back-propagation and Radial Basis Function neural network method with various training set for automatic vehicle detection from aerial images. The initial extraction of candidate object is based on Mean-shift algorithm with symmetric property of a vehicle structure. By fusing the density and the symmetry, the method can remove the ambiguous objects and reduce the cost of processing in the next stage. To extract features from the detected object, we describe the object as a log-polar shape histogram using edge strengths of object and represent the orientation and distance from its center. The spatial histogram is used for calculating the momentum of object and compensating the direction of object. BPNN and RBFNN are applied to verify the object as a vehicle using a variety of non-car training sets. The proposed algorithm shows the results which are according to the training data. By comparing the training sets, advantages and disadvantages of them have been discussed.
Validation and selection of GCPs obtained from ERS SAR and the SRTM DEM: Application to SPOT DEM Construction
Jung, Hyung-Sup ; Hong, Sang-Hoon ; Won, Joong-Sun ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 483~496
Qualified ground control points (GCPs) are required to construct a digital elevation model (DEM) from a pushbroom stereo pair. An inverse geolocation algorithm for extracting GCPs from ERS SAR data and the SRTM DEM was recently developed. However, not all GCPs established by this method are accurate enough for direct application to the geometric correction of pushbroom images such as SPOT, IRS, etc, and thus a method for selecting and removing inaccurate points from the sets of GCPs is needed. In this study, we propose a method for evaluating GCP accuracy and winnowing sets of GCPs through orientation modeling of pushbroom image and validate performance of this method using SPOT stereo pair of Daejon City. It has been found that the statistical distribution of GCP positional errors is approximately Gaussian without bias, and that the residual errors estimated by orientation modeling have a linear relationship with the positional errors. Inaccurate GCPs have large positional errors and can be iteratively eliminated by thresholding the residual errors. Forty-one GCPs were initially extracted for the test, with mean the positional error values of 25.6m, 2.5m and -6.1m in the X-, Y- and Z-directions, respectively, and standard deviations of 62.4m, 37.6m and 15.0m. Twenty-one GCPs were eliminated by the proposed method, resulting in the standard deviations of the positional errors of the 20 final GCPs being reduced to 13.9m, 8.5m and 7.5m in the X-, Y- and Z-directions, respectively. Orientation modeling of the SPOT stereo pair was performed using the 20 GCPs, and the model was checked against 15 map-based points. The root mean square errors (RMSEs) of the model were 10.4m, 7.1m and 12.1m in X-, Y- and Z-directions, respectively. A SPOT DEM with a 20m ground resolution was successfully constructed using a automatic matching procedure.
An Open Standard-based Terrain Tile Production Chain for Geo-referenced Simulation
Yoo, Byoung-Hyun ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 497~506
The needs for digital models of real environment such as 3D terrain or cyber city model are increasing. Most of applications related with modeling and simulation require virtual environment constructed from geospatial information of real world in order to guarantee reliability and accuracy of the simulation. The most fundamental data for building virtual environment, terrain elevation and orthogonal imagery is acquired from optical sensor of satellite or airplane. Providing interoperable and reusable digital model is important to promote practical application of high-resolution satellite imagery. This paper presents the new research regarding representation of geospatial information, especially for 3D shape and appearance of virtual terrain. and describe framework for constructing real-time 3D model of large terrain based on high-resolution satellite imagery. It provides infrastructure of 3D simulation with geographical context. Web architecture, XML language and open protocols to build a standard based 3D terrain are presented. Details of standard-based approach for providing infrastructure of real-time 3D simulation using high-resolution satellite imagery are also presented. This work would facilitate interchange and interoperability across diverse systems and be usable by governments, industry scientists and general public.
Support Vector Machine Classification Using Training Sets of Small Mixed Pixels: An Appropriateness Assessment of IKONOS Imagery
Yu, Byeong-Hyeok ; Chi, Kwang-Hoon ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 507~515
Many studies have generally used a large number of pure pixels as an approach to training set design. The training set are used, however, varies between classifiers. In the recent research, it was reported that small mixed pixels between classes are actually more useful than larger pure pixels of each class in Support Vector Machine (SVM) classification. We evaluated a usability of small mixed pixels as a training set for the classification of high-resolution satellite imagery. We presented an advanced approach to obtain a mixed pixel readily, and evaluated the appropriateness with the land cover classification from IKONOS satellite imagery. The results showed that the accuracy of the classification based on small mixed pixels is nearly identical to the accuracy of the classification based on large pure pixels. However, it also showed a limitation that small mixed pixels used may provide insufficient information to separate the classes. Small mixed pixels of the class border region provide cost-effective training sets, but its use with other pixels must be considered in use of high-resolution satellite imagery or relatively complex land cover situations.
Supervised Classification Using Training Parameters and Prior Probability Generated from VITD - The Case of QuickBird Multispectral Imagery
Eo, Yang-Dam ; Lee, Gyeong-Wook ; Park, Doo-Youl ; Park, Wang-Yong ; Lee, Chang-No ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 517~524
In order to classify an satellite imagery into geospatial features of interest, the supervised classification needs to be trained to distinguish these features through training sampling. However, even though an imagery is classified, different results of classification could be generated according to operator's experience and expertise in training process. Users who practically exploit an classification result to their applications need the research accomplishment for the consistent result as well as the accuracy improvement. The experiment includes the classification results for training process used VITD polygons as a prior probability and training parameter, instead of manual sampling. As results, classification accuracy using VITD polygons as prior probabilities shows the highest results in several methods. The training using unsupervised classification with VITD have produced similar classification results as manual training and/or with prior probability.
Fitting to Panchromatic Image for Pansharpening Combining Point-Jacobian MAP Estimation
Lee, Sang-Hoon ;
Korean Journal of Remote Sensing, volume 24, issue 5, 2008, Pages 525~533
This study presents a pansharpening method, so called FitPAN, to synthesize multispectral images at a higher resolution by exploiting a high-resolution image acquired in panchromatic modality. FitPAN is a modified version of the quadratic programming approach proposed in (Lee, 2008), which is designed to generate synthesized multispectral images similar to the multispectral images that would have been observed by the corresponding sensor at the same high resolution. The proposed scheme aims at reconstructing the multispectral images at the higher resolution with as less spectral distortion as possible. This study also proposes a sharpening process to eliminate some distortions appeared in the fused image of the higher resolution. It employs the Point-Jacobian MAP iteration utilizing the contextual information of the original panchromatic image. In this study, the new method was applied to the IKONOS 1m panchromatic and 4m multispectral data, and the results were compared with them of several current approaches. Experimental results demonstrate that the proposed scheme can achieve significant improvement in both spectral and block distortion.