• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.481-489
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• 2019

Change detection, one of the main applications of multi-temporal satellite images, is an indicator that directly reflects changes in human activity. Change detection can be divided into pixel-based change detection and object-based change detection. Although pixel-based change detection is traditional method which is mostly used because of its simple algorithms and relatively easy quantitative analysis, applying this method in VHR (Very High Resolution) images cause misdetection or noise. Because of this, pixel-based change detection is less utilized in VHR images. In addition, the sensor of acquisition or geographical characteristics bring registration noise even if co-registration is conducted. Registration noise is a barrier that reduces accuracy when extracting spatial information for utilizing VHR images. In this study object-based change detection of VHR images was performed considering registration noise. In this case, object-based change detection results were derived considering various pixel-based change detection methods, and the major voting technique was applied in the process with segmentation image. The final object-based change detection result applied by the proposed method was compared its performance with other results through reference data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.505-513
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• 2014

The RapidEye can acquire the 6.5m spatial resolution satellite imagery with the high temporal resolution on each day, based on its constellation of five satellites. The image products are available in two processing levels of Basic 1B and Ortho 3A. The Basic 1B image have radiometric and sensor corrections and include RPCs (Rational Polynomial Coefficients) data. In Korea, the geometric accuracy of RapidEye imagery can be improved, based on the scaled national digital maps that had been built. In this paper, we present the fully automated procedures to georegister the 1B data using 1:25,000 digital maps. Those layers of map are selected if the layers appear well in the RapidEye image, and then the selected layers are RPCs-projected into the RapidEye 1B space for generating vector images. The automated edge-based matching between the vector image and RapidEye improves the accuracy of RPCs. The experimental results showed the accuracy improvement from 2.8 to 0.8 pixels in RMSE when compared to the maps.

• Korean Journal of Remote Sensing
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• v.29 no.5
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• pp.555-568
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• 2013

Atmospheric optical thickness during nighttime was estimated in this study using analysis on the images of the moon taken from commercial digital camera. Basically the Langely Regression method was applied to the observations of the moon for the cloudless and optically stable sky conditions. The spectral response functions for the red(R), green(G), and blue(B) channels were employed to derive effective wavelength centers of each channel for the observations of the moon, and the correspondent Rayleigh optical thickness were also calculated. Aerosol optical thickness (AOT) was calculated by subtracting Rayleigh optical thickness from the atmospheric optical thickness derived from the Langley regression method. As there are only handful of nighttime AOT observations, the AOT from the moon observations was compared with the AOT from sun-photometers and the MODIS satellite sensor, which was taken several hours before the moon observations of this study. As a result, the values of AOT from moon observations agree with those from sun-photometers and MODIS within 0.1 for the R, G, B channels of the digital camera. On the other hand, ${\AA}$ngstr$\ddot{o}$m Exponent seems to be subject to larger errors due to its sensitiveness to the spectral errors of AOT. Nevertheless, the results of this study indicate that the method reported in this study is promising as it can provide nighttime AOT relatively easily with a low cost instrument like digital camera. More observations and analyses are warranted to attain improved nighttime AOT observations in the future.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.73-86
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• 2016

In this study, an algorithm to estimate Aerosol Optical Thickness (AOT) over small cities during nighttime has been developed by using the radiance from artificial light sources in small cities measured from Visible Infrared Imaging Radiometer Suite (VIIRS) sensor's Day/Night Band (DNB) aboard the Suomi-National Polar Partnership (Suomi-NPP) satellite. The algorithm is based on Beer's extinction law with the light sources from the artificial lights over small cities. AOT is retrieved for cloud-free pixels over individual cities, and cloud-screening was conducted by using the measurements from M-bands of VIIRS at infrared wavelengths. The retrieved nighttime AOT is compared with the aerosol products from MODerate resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites. As a result, the correlation coefficients over individual cities range from around 0.6 and 0.7 between the retrieved nighttime AOT and MODIS AOT with Root-Mean-Squared Difference (RMSD) ranged from 0.14 to 0.18. In addition, sensitivity tests were conducted for the factors affecting the nighttime AOT to estimate the range of uncertainty in the nighttime AOT retrievals. The results of this study indicate that it is promising to infer AOT using the DNB measaurements over small cities in Korea at night. After further development and refinement in the future, the developed retrieval algorithm is expected to produce nighttime aerosol information which is not operationally available over Korea.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.283-293
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• 2018

We applied PSInSAR to two SAR satellite (ALOS-1 and COSMO-SkyMed) images and analyzed the difference in displacement observation performance according to sensor characteristics. The building layer was extracted from the digital topographic map, and the PS extracted from the SAR image was classified into two groups(building structure and ground surface) for density analysis. The density of PS extracted from the research area was $0.023point/m^2$ for ALOS-1 PALSAR and $0.1point/m^2$ for COSMO-SkyMed, more than 4 times PS was extracted compared to ALOS-1. In addition, not only the PS density in the building, but also the density in the ground were greatly increased. The average displacement velocity of ALOS-1 PALSAR is within ${\pm}1cm/yr$, while for COSMO-SkyMed it is within ${\pm}0.3cm/yr$. Although it is difficult to make quantitative comparisons because it does not use the data for the same period, it can be said that the accuracy of X-band SAR system is very high compared to the L-band. In consideration of PS observation density and observation accuracy of displacement, X-band SAR data is very effective in research where it is important to acquire useful signals from the ground surface, such as ground subsidence and sinkhole.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.94-106
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• 2020

Recently, the radio navigation method utilizing the GPS(Global Positioning System) satellite information is widely used as the method to measure the position of objects. As GPS applications become wider and fields based on various positioning information emerge, new methods for achieving higher accuracy are required. In the case of autonomous vehicles, the INS(Inertial Navigation System) using the IMU(Inertial Measurement Unit), and the DR(Dead Reckoning) algorithm using the in-vehicle sensor, are used for the purpose of preventing degradation of accuracy of the GPS and to measure the position in the shadow area. However, these positioning methods have many elements of problems due not only to the existence of various shaded areas such as building areas that are continually enlarged, tunnels, underground parking lots and but also to the limitations of accumulation-based location estimation methods that increase in error over time. In this paper, an efficient positioning method in a large underground parking space using Fingerprint method is proposed by placing the AP(Access Points) and directional antennas in the form of four anchors using WLAN, a popular means of wireless communication, for positioning the vehicle in the GPS shadow area. The proposed method is proved to be able to produce unchanged positioning results even in an environment where parked vehicles are moved as time passes.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.435-444
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• 2011

The land cover map derived from spectral features of high resolution optical images has low spectral resolution and heterogeneity in the same land cover class. For this reason, despite the same land cover class, the land cover can be classified into various land cover classes especially in vegetation area. In order to overcome these problems, detailed vegetation classification is applied to optical satellite image and SAR(Synthetic Aperture Radar) integrated data in vegetation area which is the result of pre-classification from optical image. The pre-classification and vegetation classification were performed with MLC(Maximum Likelihood Classification) method. The hierarchical land cover classification was proposed from fusion of detailed vegetation classes and non-vegetation classes of pre-classification. We can verify the facts that the proposed method has higher accuracy than not only general SAR data and GLCM(Gray Level Co-occurrence Matrix) texture integrated methods but also hierarchical GLCM integrated method. Especially the proposed method has high accuracy with respect to both vegetation and non-vegetation classification.

• Journal of Korea Water Resources Association
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• v.48 no.10
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• pp.831-843
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• 2015

This study estimates MODIS-derived evapotranspiration data quality by revised RS-PM algorithm in Seolmacheon test basin. We used latent flux with eddy covariance method to evaluate MODIS-derived spatial evapotranspiration and gap-filled these data by three methods (FAO-PM, MDV and Kalman Filter) and to quantify daily evapotranspiration. Gap-filled daily evapotranspiration data was used to evaluate evapotranspiration computed by revised RS-PM algorithm derived MODIS satellite images. For the water budget analysis, we used soil moisture content that is quantified to average individual soil moisture rate observed by TDR (Time Domain Reflectometry) sensor at soil depth. The soil moisture variation is calculated in consideration from initial to final soil moisture content. According to the result of this study, evapotranspiration computed by revised RS-PM algorithm is very larger than eddy covariance data gap-filled by three methods. Also, water budget characteristics is not closed. We could analysis that MODIS-derived spatial evapotranspiration does not represent actual evapotranspiration in Seolmacheon.

• Journal of Korea Water Resources Association
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• v.46 no.11
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• pp.1129-1140
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• 2013

Precipitation is one of the important factors in the hydrological cycle. It needs to understand accurate of spatial precipitation field because it has large spatio-temporal variability. Precipitation data obtained through the Tropical Rainfall Monitoring Mission (TRMM) 3B43 product is inaccurate because it has 25 km space scale. Downscaling of TRMM 3B43 product can increase the accuracy of spatial precipitation field from 25 km to 1 km scale. The relationship between precipitation and the normalized difference vegetation index(NDVI) (1 km space scale) which is obtained from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor loaded in Terra satellite is variable at different scales. Therefore regression equations were established and these equations apply to downscaling. Two renormalization strategies, Geographical Difference Analysis (GDA) and Geographical Ratio Analysis (GRA) are implemented for correcting the differences between remote sensing-derived and rain gauge data. As for considering the GDA method results, biases, the root mean-squared error (RMSE), MAE and Index of agreement (IOA) is equal to 4.26 mm, 172.16 mm, 141.95 mm, 0.64 in 2009 and 17.21 mm, 253.43 mm, 310.56 mm, 0.62 in 2011. In this study, we can see the 1km spatial precipitation field map over Korea. It will be possible to get more accurate spatial analysis of the precipitation field through using the additional rain gauges or radar data.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.359-367
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• 2008

TRMM TMI data were used to investigate a relationship between physical parameters from microwave sensor and typhoon intensities from June to September, 2004. Several data such as 85GHz brightness temperature (TB), polarization corrected temperature (PCT), precipitable water, ice content, rain rate, and latent heat release retrieved from the TMI observation were correlated to the maximum wind speeds in the best-track database by RSMC-Tokyo. Correlation coefficient between TB and typhoon intensity was -0.2 - -0.4 with a maximum value in the 2.5 degree radius circle from the center of tropical cyclone. The value of correlation between in precipitable water, rain, latent heat, and typhoon intensity is in the range of 0.2-0.4. Correlation analysis with respect to storm intensity showed that maximum correlation is observed at 1.0-1.5 degree radius circle from the center of tropical cyclone in the initial stage of tropical cyclone, while maximum correlation is shown in 0.5 degree radius in typhoon stage. Correlation coefficient was used to produce regressed intensities and adopted for typhoon Rusa (2002) and Maemi (2003). Multiple regression with 85GHz TB and precipitable water was found to provide an improved typhoon intensity when taking into account the storm size. The results indicate that it may be possible to use TB and precipitable water from satellite observation as a predictor to estimate the intensity of a tropical cyclone.