• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.577-589
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• 2021

Drone mapping systems can be applied to many fields such as disaster damage investigation, environmental monitoring, and construction process monitoring. To integrate individual sensors attached to a drone, it was essential to undergo complicated procedures including time synchronization. Recently, a variety of composite sensors are released which consist of visual sensors and GPS/INS. Composite sensors integrate multi-sensory data internally, and they provide geotagged image files to users. Therefore, to use composite sensors in drone mapping systems, mapping accuracies from composite sensors should be examined. In this study, we analyzed the mapping accuracies of a composite sensor, focusing on the data acquisition area and pre-calibration effect. In the first experiment, we analyzed how mapping accuracy varies with the number of ground control points. When 2 GCPs were used for mapping, the total RMSE has been reduced by 40 cm from more than 1 m to about 60 cm. In the second experiment, we assessed mapping accuracies based on whether pre-calibration is conducted or not. Using a few ground control points showed the pre-calibration does not affect mapping accuracies. The formation of weak geometry of the image sequences has resulted that pre-calibration can be essential to decrease possible mapping errors. In the absence of ground control points, pre-calibration also can improve mapping errors. Based on this study, we expect future drone mapping systems using composite sensors will contribute to streamlining a survey and calibration process depending on the data acquisition circumstances.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.2
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• pp.150-157
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• 2006

Spatially resolved remote identification and quantification of trace gases in the atmosphere is desirable in various fields of scientific research as well as in public security and industrial contexts. Environmental observations investigating causes, extent md consequences of air pollution are of fundamental interest. We present an Imaging-DOAS system, a ground based remote sensing instrument that allows spatially resolved mapping of atmospheric trace gases by a differential optical absorption spectroscopy(DOAS) with sun scattered light as the light source. A passive DOAS technique permits the identification and quantification of various gases, e.g., $NO_2,\;SO_2,\;and\;CH_2O$, from their differential absorption structures with high sensitivity. The Imaging-DOAS system consists of a scanning mirror, a focusing lens, a spectrometer, a 2-D CCD, ad the integral control software. An imaging spectrometer simultaneously acquires spectral information on the incident light in one spatial dimension(column) and sequentially scans the next spatial dimension with a motorized scanning mirror. The structure of the signal acquisition system is described in detail and the evaluation method is also briefly discussed. Applications of imaging of the $NO_2$ contents in the exhaust plumes from a power plant are presented.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.961-970
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• 2017

Despite of large demand for high spatial resolution products of aerosol properties from satellite remote sensing, it has been very difficult due to the weak signal by a single pixel and higher noise from clouds. In this study, aerosol retrieval algorithm with the high spatial resolution ($500m{\times}500m$) was developed using Geostationary Ocean Color Imager (GOCI) data during the Korea-US Air Quality (KORUS-AQ) period in May-June, 2016.Currently, conventional GOCI Yonsei aerosol retrieval(YAER) algorithm provides $6km{\times}6km$ spatial resolution product. The algorithm was tested for its best possible resolution of 500 m product based on GOCI YAER version 2 algorithm. With the new additional cloud masking, aerosol optical depth (AOD) is retrieved using the inversion method, aerosol model, and lookup table as in the GOCI YAER algorithm. In some cases, 500 m AOD shows consistent horizontal distribution and magnitude of AOD compared to the 6 km AOD. However, the 500 m AOD has more retrieved pixels than 6 km AOD because of its higher spatial resolution. As a result, the 500 m AOD exists around small clouds and shows finer features of AOD. To validate the accuracy of 500 m AOD, we used dataset from ground-based Aerosol Robotic Network (AERONET) sunphotometer over Korea. Even with the spatial resolution of 500 m, 500 m AOD shows the correlation coefficient of 0.76 against AERONET, and the ratio within Expected Error (EE) of 51.1%, which are comparable to the results of 6 km AOD.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.293-302
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• 2014

Radar systems are used in remote sensing mainly as space-borne, airborne and ground-based Synthetic Aperture Radar (SAR), scatterometer and Doppler radar. Those systems are composed of expensive equipments and require expertise and professional skills for operation. Because of the limitation in getting experiences of the radar and SAR systems and its operations in ordinary universities and institutions, it is difficult to learn and exercise essential principles of radar hardware which are essential to understand and develop new application fields. To overcome those difficulties, in this paper, we present the construction and experiment of a low-cost educational radar system based on the blueprints of the MIT Cantenna system. The radar system was operated in three modes. Firstly, the velocity of moving cars was measured in Doppler radar mode. Secondly, the range of two moving targets were measured in radar mode with range resolution. Lastly, 2D images were constructed in GB-SAR mode to enhance the azimuth resolution. Additionally, we simulated the SAR raw data to compare Deramp-FFT and ${\omega}-k$ algorithms and to analyze the effect of antenna positional error for SAR focusing. We expect the system can be further developed into a light-weight SAR system onboard a unmanned aerial vehicle by improving the system with higher sampling frequency, I/Q acquisition, and more stable circuit design.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1219-1230
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• 2022

Multi-spectral drones in agricultural observation require quantitative and reliable data based on physical quantities such as radiance or reflectance in crop yield analysis. In the case of remote sensing data for crop monitoring, images taken in the same area over time-series are required. In particular, biophysical data such as leaf area index or chlorophyll are analyzed through time-series data under the same reference, it can be directly analyzed. So, comparable reflectance data are required. Orthoimagery using drone images, the entire image pixel values are distorted or there is a difference in pixel values at the junction boundary, which limits accurate physical quantity estimation. In this study, reflectance and vegetation index based on drone images were calculated according to the correction method of drone images for time-series crop monitoring. comparing the drone reflectance and ground measured data for spectral characteristics analysis.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.157-168
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• 2023

Image segmentation and supervised classification techniques are widely used to monitor the ground surface using high-resolution remote sensing images. In order to classify various objects, a process of defining a class corresponding to each object and selecting samples belonging to each class is required. Existing methods for extracting class samples should select a sufficient number of samples having similar intensity characteristics for each class. This process depends on the user's visual identification and takes a lot of time. Representative samples of the class extracted are likely to vary depending on the user, and as a result, the classification performance is greatly affected by the class sample extraction result. In this study, we propose an image classification technique that minimizes user intervention when extracting class samples by applying the histogram back-projection technique and has consistent intensity characteristics of samples belonging to classes. The proposed classification technique using histogram back-projection showed improved classification accuracy in both the experiment using hue subchannels of the hue saturation value transformed image from Compact Advanced Satellite 500-1 imagery and the experiment using the original image compared to the technique that did not use histogram back-projection.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.377-385
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• 2024

We investigated the effect of spectral fitting wavelength interval variations and selection of absorption cross-section on the sulfur dioxide slant column density (SCD) retrievals from the scattered sunlight observation using a UV-Vis hyperspectral instrument. The sulfur dioxide slant column densities were retrieved from the combinations of multiple spectral fitting intervals and absorption cross-sections. The observation was carried out at the site 0.53 km away from a combustion site located in Gimhae from December 1, 2023, to January 23, 2024. The radiances were obtained on the line of measurement sight toward the stack of the combustion facility. The best spectral fitting intervals were found to be from 305.7 to 321.1 nm. In terms of the absorption cross-section dependency, the SO₂ (293 K), O₃ (223 K, 243 K) show the best spectral fitting for the observed radiances with both the smallest fitting residual and SCD error. The effects of the fitting interval and cross sections found in this study can be useful information for improving SO₂ retrievals based on UV hyperspectral measurements.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.191-201
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• 2018

In this present study, we, for the first time, retrieved total column of ozone ($O_3$) and tropospheric ozone vertical profile using the Optimal Estimation (OE) method based on the MAX-DOAS measurement at the Yonsei University in Seoul, Korea. The optical density fitting is carried out using the OE method to calculate ozone columns. The optical density between the MAX-DOAS data obtained by dividing the measured intensities for each viewing elevated angle by those at the zenith angle. The retrieved total columns of the ozone are 375.4 and 412.6 DU in the morning (08:13) and afternoon (17:55) on 23 May, 2017, respectively. In addition, under 10 km altitude, the $O_3$ vertical profile was retrieved with about 5% of retrieval uncertainty. However, above 10 km altitude, the $O_3$ vertical profile retrieval uncertainty was increased (>10%). The spectral fitting errors are 16.8% and 19.1% in the morning and afternoon, respectively. The method suggested in this present study can be useful to measure the total ozone column using the ground-based hyper-spectral UV sensors.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.292-296
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• 2002

This study has been accomplished as a experimental study for field application of 3D Perspective Image Map creation using Digital Topographical Map and based on the Ortho-Projection Image which is generated from Satellite Overlay Images and the precise Relative Coordinates of longitude, latitude and altitude which is corrected by GCP(Ground Control Point). AS to Contour Lines Map which is created by Coordinate conversion of 1:5,000 Topographical Map, we firstly made Satellite Image Map to substitute for Digital Topographical Map through overlapping the original images on top of each Ortho-Projection Image created and checking the accuracy. In addition to 3D Image Map creation for 3D Terrain analysis of a target district, Slope Gradient Analysis, Aspect Analysis and Terrain Elevation Model generation, multidirectional 3D Image generation by DEM can be carried out through this study. This study is to develop a mapping technology with which we can generate 3D Satellite Images of a target district through the composition of Digital Maps and Facility Blueprint and arbitrarily create 3D Perspective Images of the target district from any view point.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.154-157
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• 1999

Microwave polarimetric backscattering from a wet soil surface had been measured using a Ku-band polarimetric scatterometer at the incidence angles ranging from 10$^{\circ}$ to 70$^{\circ}$ Since the accurate target parameters as well as the radar parameters are necessary for radar scattering modeling, a complete and accurate set of ground truth data were also collected, from which accurate measurements were made of the rms height, correlation length, and dielectric constant. The measured polarimetric backscattering coefficients (vv-, hh-, vh-, hv-polarizations) were compared with theoretical models and empirical models. A new semi-empirical model for microwave polarimetric radar backscattering from bare soil surfaces was developed using polarimetric radar measurements and the knowledge based on the theoretical and numerical solutions. The model was found to yield very good agreement with the backscattering measurements of this study.