• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.385-387
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• 2005

Polarimetric measurements of the sky radiation by the PSR-I000, which is the multi-spectral polarimeter developed by the Opt Research Corporation and has the same wavelength regions (443nm, 490nm, 565nm, 670nm, 765nm and 865nm) as the ADEOSII/POLDER sensor, have been carried out at the ground station in Kanazawa city, Japan from March to May. First of all, the wavelength dependency of degrees of polarization is examined and it is shown that degrees of polarization measured under the hazy dust cloud are lower than those measured in the clear sky and decrease as the wavelength increases. Next, a new method for estimating optical properties, such as the optical thickness, the number size distribution and the refractive index, of the Asian dust and the ground reflectance from degrees of polarization measured by PSR-I000 is described. Finally, this method is applied to polarization data acquired on April 15,2002. As a result, it is shown that our estimation algorithm provides a good result.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.166-169
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• 2004

NDVI has been used to estimate several ecological variables including leaf area index (LAI). Global MODIS LAI data are partially produced by empirical model that is based on the assumption of high correlation between NDVI and LAI. This study attempts to evaluate the MODIS empirical model by comparing with the result obtained from field LAI measurement and Landsat ETM+ reflectance. MODIS LAI product and ancillary data were analyzed over a small forest watershed near the Seoul metropolitan area. The relationship between NDVI of ETM+ and field measured LAI did not correspond to MODIS LAI estimation. Since the study area is mostly covered by very dense and fully closed forest, the correlation between NDVI and LAI might not be high. Although MODIS LAI product has great potential for global environment studies, it needs to be cautious to use them in regional and local area in particular for the forest of dense canopy situation.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.20-24
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• 2007

센서의 광학 해상력에 따라 센서에 도달하는 에너지의 앙은 영상의 화소값으로 변환되므로，이 관계는 위성 영상의 정량적인 광학적 특성을 이해하기 위한 바탕이 되며，영상의 질을 유지하기 위한 척도가 되기도 한다. 위성영상의 광학적 특성은 ON 값 을 실제 지표물의 반사에너지 값인 Radiance와 Reflectance로 의 변환을 통하여 추정할 수 있으며，이러한 과정을 절대복사보정(Absolute Radiometric Calibration) 이라고 한다. 절대복사보정 과정에서 센서에 도달하는 태양 에너지의 양을 추정하기 위하여 복사전달모델이 사용된다. 태양 에너지가 대기를 통과함에 따라 여러 가지 상호 작용이 일어나게 되므로 복사 전달모델을 사용하기 위해서는 다양한 입력 변수가 필요하게 된다. 이러한 입력 변수로는 지표물의 반사율， 대기자료，그리고 센서의 특성 등이 포함되며， 이 연구에서는 KOMPSAT-2 위성의 MSC 영상의 절대복사보정 과정에서 복사전달모델의 결과에 영향을 미치는 입력 변수의 특성을 살펴보고자 한다.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.89-94
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• 1998

Seasonal variation of attenuation coefficient spectra in Japan sea was extracted from underwater radiance/irradiance spectra observed by a moored buoy system developed by National Space Development Agency of Japan (NASDA). The buoy was deployed 9 months from August 31, 1996 to June 1, 1997. Throughout this period, it was collecting downward irradiance and upward radiance spectra under water at the depth of 1.5m and 6.5m everyday. The dairy averaged diffused attenuation coefficient spectra and underwater reflectance spectra were calculated. The results were compared with the absorption spectra of filtered samples obtained by validation cruises, which carried out 5 times during the moored period. Also, the natural fluorescence of chlorophyll a were extracted from the upward radiance spectra observed at 1.5m depth. The seasonal variation of the calculated attenuation coefficient spectra and the natural fluorescence were examined. The result shows a weak blooming of phytoplankton on November and a large blooming on April.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.690-695
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• 2002

In this forest fire experiment the ThermoViewer was set up on the platform built on a tree and observed the temperature change, before, during and after the fire. The fire experiment had been carried out not only the day of the forest fire experiment but also continued for four months after the forest fire had been gone. The results from the experiment showed that the temperature difference is significant in the afternoon; therefore, afternoon satellite passing is better and suitable time for active forest fires and burnt scars detection; moreover, after 83 days, the burnt and un-burnt vegetation become almost the same condition, fully regenerated and the temperature difference become nearly 0$^{\circ}$ Celsius, so there is not enough temperature different between burnt and un-burnt vegetation for current sensors to distinguish the difference anymore.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1203-1205
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• 2003

To detect dust-loaded air-mass over land and ocean, we propose an index, which is essentially the difference in Rayleigh-corrected reflectance between 412 and 443 nm bands of SeaWiFS. Radiative transfer simulations are conducted to show that the index is linearly related to the optical thickness of modeled dust-contaminated aerosol while showing insensitivity against non-absorbing model aerosols. Asian SeaWiFS data set of 2001 spring is used to produce daily composite imagery of the index, which compares well with TOMS Aerosol Index and with predicted aerosol optical thickness predicted by CFORS chemical weather forecast.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1230-1232
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• 2003

This study aims to extract maximum geological information using the ASTER (Advanced Spaceborne Thermal Emission and Reflection radiometer) images of a part of south India. The area chosen for this study is characterized by rock types such as Migmatite, Magnetite Quartzite, Charnockite, Granite, dykes, Granitoid gneiss and Ultramafic rocks, and minerals such as Bauxite, Magnesite, Iron ores, Calcite etc. Advantage was taken of the characteristic reflectance and absorption phenomenon in the VNIR, SWIR and TIR bands for these rocks and minerals, and they were mapped in detail. Image processing methods such as contrast stretching, PC analysis, band ratios and fusion were used in this study. The results of the processing matched with the field details and showed additional details, thus demonstrating the usefulness of ASTER (especially the SWIR bands) data for better geological mapping.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.257-259
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• 2003

Landuse maps are prepared from satellite imagery and field observations were conducted at various locations in the study area. Compared to the field data and NDVI and RVI thematic maps, NDVI is better than RVI, because it compensates for changing illumination conditions, surface slope, aspect and other factors. Clouds, water and snow have negative values for RVI and NDVI. Rock and bare soils have similar reflectance in both NIR and visible band, so RVI and NDVI are near zero. In forest areas with good vegetation cover, NDVI is high and landslide occurrence is less. But if annual and biennial vegetations are present and if cultivation practices are changed frequently, NDVI is medium and landslide occurrence is moderate. In areas where deforestation and settlement is in progress, NDVI is less and landslide occurrence is more. The NDVI FCC thematic map may be used as an important layer in GIS application for landslide studies. Analyzing other layers such as slope, rainfall, soil, geology, drainage, lineament, etc with NDVI FCC layer will give a better idea about the identity of landslide prone areas.

• Proceedings of the KSRS Conference
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• 2000.04a
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• pp.178-182
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• 2000

본 연구의 목적은 실험실에서 퇴적물의 다분광반사 특성과 물성을 측정하고 이를 위성 영상에 적용하여 영상에서 나타나는 퇴적물의 분광차이의 원인을 해석하고, 위성영상에서의 퇴적물의 분류 가능성을 연구하는데 있다. 연구에서는 Landsat TM위성 영상과 350~2500nm 파장대역에 대한 퇴적물 시료의 분광측정 자료를 사용하였으며, 기존의 조사 자료를 토대로 TM 영상에서 퇴적물을 분류한 후, 현장에서 시료를 채취하여 입도 분류를 실시하였다. 퇴적물의 입도와 함수비에 따른 분광특성변화를 검증하였으며, 입도와 함수비에 대한 회귀식을 구하여 이를 영상에 적용 분류하였다. 분석 결과 다분광자료 측정시 퇴적물입도에 따른 분광차이는 미약하였으며 이를 TM 자료로 재구성하였을 때는 분광특성을 구분할 수 없었다. 퇴적물의 분류는 TM Band 4, 5, 7을 이용한 회귀식을 적용할 때 비교적 정확하게 나타났으나, 영상에서 퇴적물의 분광 차이는 입도 크기가 직접적인 요인이 아니라 입도에 의한 함수비 및 유기물 함량의 차이에 기인한 것으로 해석된다.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.