• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.4-6
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• 2003

Optical signals from an object may vary at different conditions caused by differences in light source and sensor position. Knowledge of these variations is necessary to enable calibration of the satellite images and confirmation of the sun and sensor angles influences of the spectral signals from the objects. With the use high -resolution Ikonos$^{TM}$ multi-angular images, the bi- directional reflectance effects of mangrove trees were observed when three datasets were compared. The influence of bi- directional reflectance may affect the accuracy of interpreting satellite imagery and obtaining biophysical parameters mangrove and other vegetation by indirect means.

• Korean Journal of Remote Sensing
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• v.6 no.1
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• pp.49-62
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• 1990

The study is aimed to analize the spectral characteristics of igneous and sedimentary rocks in their reflectance curves obtained from CARY 17-D Spectrophotometer, and correlation between chemical complsition and HHRR data. The reflectance is higher in acidic igneous rocks, while lower in basic igneous rocks. Especially acidic plutonic rocks show sharp absorption bands at 1.4 and 1.9 $\mu\textrm{m}$ due to water inclusion in felsic minerals and basic rocks a broad absoption band near 1.mu.m due to Fe$^{++}$ ion in mafic minerals. Sandstones generally have higher reflectance than siltstones and shales, and show strong absorption at 1.4 and 1.9 $\mu\textrm{m}$. Arkosic sandstones have lower reflectance at blue band due to Fe$^{+++}$ ion exsolved from feldspars. The HHRR data have a positive correlation with SiO$_2$ and $K_2$O, while they have a negative correlation with FeO and MgO.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.285-295
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• 2001

We developed a CASE-II water model that will enable the simulation of remote sensing reflectance($R_{rs}$) at the coastal waters for the retrieval of suspended sediments (SS) concentrations from satellite imagery. The model has six components which are: water, chlorophyll, dissolved organic matter (DOM), non-chlorophyllous particles (NC), heterotrophic microorganisms and an unknown component, possibly represented by bubbles or other particulates unrelated to the five first components. We measured $R_{rs}$, concentration of SS and chlorophyll, and absorption of DOM during our field campaigns in Korea. In addition, we generated $R_{rs}$ from different concentrations of SS and chlorophyll, and various absorptions of DOM by random number functions to create a large database to test the model. We assimilated both the computer generated parameters as well as the in-situ measurements in order to reconstruct the reflectance spectra. We validated the model by comparing model-reconstructed spectra with observed spectra. The estimated $R_{rs}$ spectra were used to (1) evaluate the performance of four wavelengths and wavelengths ratios for accurate retrieval of SS. 2) identify the optimum band for SS retrieval, and 3) assess the influence of the SS on the chlorophyll algorithm. The results indicate that single bands at longer wavelengths in visible better results than commonly used channel ratios. The wavelength of 625nm is suggested as a new and optimal wavelength for SS retrieval. Because this wavelength is not available from SeaWiFS, 555nm is offered as an alternative. The presence of SS in coastal areas can lead to overestimation chlorophyll concentrations greater than 20-500%.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.482-484
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• 2003

GLI on boarded ADEOS-II satellite allows us to observe vegetation status in the two different resolutions simultaneously, because of thirty 1km resolution channels and six 250m resolution channels. There are four GLI land higher level products from these channels ; those are PGCP (Precise Geometric Correction Parameter), L2A_LC (TOA reflectance), ACLC (atmospheric corrected reflectance), and VGI (NDVI and EVI). This paper shows ADEOS-II GLI land data processing, and some of the latest results.

• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.487-499
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• 2009

Atmospheric correction of satellite measurements is a major step to estimate accurate surface reflectance of solar spectrum channels. In this study, Simplified Method for the Atmospheric Correction (SMAC) radiative transfer model used to retrieve surface reflectance from MODIS (MODerate resolution Imaging Spectrometer) top of atmosphere (TOA) reflectance. It is fast and simple atmospheric correction method, so it uses for work site operation in various satellite. This study attempts a test of accuracy of SMAC through a sensitivity test to detected error sources and to improve accuracy of surface reflectance using SMAC. The results of SMAC as compared with MODIS surface reflectance (MOD09) was represented that low accuracy ($R^2\;=\;0.6196$, Root Means Square Error (RMSE) = 0.00031, bias = - 0.0859). Thus sensitivity analysis of input parameters and coefficients was conducted to searching error sources. Among the input parameters, Aerosol Optical Depth (AOD) is the most influence input parameter. In order to modify AOD term in SMAC code, Stepwise multiple regression was performed with testing and remove variable in three stages with independent variables of AOD at 550nm, solar zenith angle, viewing zenith angle. Surface reflectance estimation by using Newly proposed AOD term in the study showed that improve accuracy ($R^2\;=\;0.827$, RMSE = 0.00672, bias = - 0.000762).

• 한국지구과학회:학술대회논문집
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• 2005.02a
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• pp.174-175
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• 2005

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.734-738
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• 2002

We present spectral characteristics of tidal flat sediments and algal mat that were tested in the Gomso and Saemangum tidal flats, Korea. The objective of this study is to investigate the spectral reflectance and the radar scattering modeling in the tidal flats. Ground truth data obtained in the tidal flats include grain size, soil moisture content and its variation with time, surface roughness, chlorophyll, ground leveling, and field spectral reflectance measurement. The concept of an effective exposed area (EEA) is introduced to accommodate the effect of remnant surface water, and it seriously affects the reflection of short wavelength infrared and microwave. The nin size of 0.0625 mm has been normally used as a critical size of mud and sand discrimination. But we propose here that 0.25 mm is more practical grain size criterion to discriminate by remote sensing. Algal mat is the primary product in tidal flats, and it is found to be very important to understand spectral characteristics for tidal flat remote sensing. We have also conducted radar scattering modeling, and showed L-band HV-polarization would be the most effective combination.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.175-182
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• 2006

Because of the phenological variation of vegetation growth in temperate region, it is often difficult to accurately assess the surface conditions of agricultural croplands, grasslands, and disturbed forests by multi-spectral remote sensor data. In particular, the spectral similarity between soil and dry vegetation has been a primary problem to correctly appraise the surface conditions during the non-growing seasons in temperature region. This study analyzes the spectral characteristics of the mixture of dry vegetation and soil. The reflectance spectra were obtained from laboratory spectroradiometer measurement (GER-2600) and from EO-1 Hyperion image data. The reflectance spectra of several samples having different level of dry vegetation fractions show similar pattern from both lab measurement and hyperspectral image. Red-edge near 700nm and shortwave IR near 2,200nm are more sensitive to the fraction of dry vegetation. The use of hyperspectral data would allow us for better separation between bare soils and other surfaces covered by dry vegetation during the leaf-off season.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.262-276
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• 1998

The paper first describes the atmospheric correction algorithm for the Ocean Color and Temperature Scanner (OCTS) visible band data used at Earth Observation Center (EOC) of National Space Development Agenrr of japan (NASDA). It uses 10 candidate aerosol models including "Asian dust model" introduced in consideration of the unique feature of aerosols over the east Asian waters. Based on the observations at 670 and 865 nm bands where the reflectance of the water body can be discarded, the algorithm selects a pair of aerosol models that accounts best for the observed spectral reflectances to synthesize the aerosol reflectance in other bands. The paper also evaluates the performance of the algorithm by comparing the satellite estimates of water-leaving radiance and chlorophyll-a concentration with selected buoy- and ship-measured data. In comparison with the old CZCS-type atmospheric correction algorithm where the aerosol reflectance is assumed to be spectrally independent, the OCTS algorithm records factor 2-3 less error in estimating the normalized water-leaving radiances. In terms of chlorophyll-a concentration estimation, however, the accuracy stays very similar compared to that of the CZCS-type algorithm. This is considered to be due to the nature of in-water algorithm which relies on spectral ratio of water-leaving radiances.

• Ocean Science Journal
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• v.42 no.1
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• pp.49-59
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• 2007

Besides empirical algorithms with the blue-green ratio, the algorithms based on fluorescence are also important and valid methods for retrieving chlorophyll-a concentration in the ocean waters, especially for Case II waters and the sea with algal blooming. This study reviews the history of initial cognitions, investigations and detailed approaches towards chlorophyll fluorescence, and then introduces the biological mechanism of fluorescence remote sensing and main spectral characteristics such as the positive correlation between fluorescence and chlorophyll concentration, the red shift phenomena. Meanwhile, there exist many influence factors that increase complexity of fluorescence remote sensing, such as fluorescence quantum yield, physiological status of various algae, substances with related optical property in the ocean, atmospheric absorption etc. Based on these cognitions, scientists have found two ways to calculate the amount of fluorescence detected by ocean color sensors: fluorescence line height and reflectance ratio. These two ways are currently the foundation for retrieval of chlorophyll-a concentration in the ocean. As the in-situ measurements and synchronous satellite data are continuously being accumulated, the fluorescence remote sensing of chlorophyll-a concentration in Case II waters should be recognized more thoroughly and new algorithms could be expected.