• Journal of the Korean Society of Environmental Restoration Technology
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• v.6 no.1
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• pp.34-40
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• 2003

The deterioration of agricultural environment, which is characterized by dryness and desertification of land, is one of the main reasons which explain the recent decrease of land productivity. To solve these environmental problems, it is very important to make clear the mechanism between soil, water, vegetation and temperature. The main objective of this study is to provide a soil surface information, which represent a soil reflectance spectrum, by remote sensing technology. The soil reflectance of the soil was measured using a spectro-radiometer in the wavelength range from 300nm to 1100nm. The results suggest that the reflectance properties of soils are related to their mineral composition and soil moisture. Increasing soil moisture resulted in an decrease in the rate of reflectance which leads to parallel curves of soil reflectance spectra.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.25-28
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• 2002

The aim of the present study was the evaluation of methods for estimating the vegetation information in the field on the basis of spectral reflectance measured farm field, in particular the estimation of Leaf Area Index(LAI). Variability in tissue optical properties was wavelength-dependent. For rice and bean, the lowest variation was in the visible spectral region and the highest in the near-infrared. The structural attributes of ecosystems determine the relative contribution of tissue and canopy factors that drive variation in a reflectance signal.

• Journal of Biosystems Engineering
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• v.17 no.4
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• pp.370-381
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• 1992

Optical properties of fruits can provide information for nondestructive quality evaluation. An attempt is made here to develop an optical method for quality evaluation of apple using the spectral reflectance of its surface. Optical fiber was used to transmit light conveniently from light source to sample and sample to detector. Spectral reflectances of two types of Fuji variety-one of which was exposed to the sunlight directly (non-bagging) and the other was wrapped with bag (bagging) - were investigated from the wavelength ranging of 400nm to 700nm. The relationships between reflectance characteristics and quality indices such as chlorophyll content, anthocyanin content, and soluble solids were analyzed.

• Journal of the Optical Society of Korea
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• v.19 no.6
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• pp.649-657
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• 2015

We present a surface color measurement including quantities of surface color, methods, and uncertainty evaluation. Based on a relation between spectral reflectance and surface color, we study how an uncertainty of spectral reflectance propagates to surface color. In analyzing the uncertainty propagation, we divide the uncertainty into uncorrelated components, fully correlated components, and correlated components with spectrally varying correlations. As an experimental example, we perform spectro-reflectometric measurements for ceramic color plates. With measured spectral reflectance and its uncertainty evaluation, we determine surface color and analyze uncertainties of the ceramic color plates.

• Journal of Biosystems Engineering
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• v.17 no.4
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• pp.382-395
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• 1992

The surface color of several varieties of apples were expressed quantitatively in xyz chromaticity coordinates. The spectral reflectance of 'Fuji' apples were measured in 400-820 nm range by using a spectrophotometer. Based on the spectrophotometer data and the result of visual sensory test, linear regression models were developed to select wavelengths effective for sorting apples. The models utilized reflectance at single wavelength, and the difference and ratio of the reflectance at two distinct wavelengths. The model which best fitted the visual sensory test data was one utilizing the ratio of the reflectance at 618 nm and 514nm. The correlation coefficient for this model was 0.967. Several other models were also described.

• Korean Journal of Remote Sensing
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• v.17 no.2
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• pp.165-181
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• 2001

Using a field spectrometer having a spectral range of 0.4$\mu\textrm{m}$~2.5$\mu\textrm{m}$ with a spectral resolution of 1nm, the researchers measured the reflectance of granite, andesitic rocks, sedimentary rocks, and pyrophyllite ore in the Ungsang area, Kyungsang Basin, South Korea. Spectral characteristics of the geological media were investigated from the analysis. The in-situ measured sites were selected in well exposed rock outcrops. In case of unfavorable weather conditions, rocks were sampled and remeasured under natural solar condition. The reflectance of field data was measurd at three sistes for granite, six sites for andesitic rock three sites for sedimentary rocks, and two sites for pyrophyllite ore. The vibrational absorption bands for pyrophyllite are detected in the spectral range of 2.0$\mu\textrm{m}$~2.5$\mu\textrm{m}$. The absorption band for granites in study area is not distinctive. The reflectance measured under normal field conditions showed strong absorption at wavelengths of 1.4$\mu\textrm{m}$ and 1.9$\mu\textrm{m}$ due to the effect of moisture in the atmosphere. After the bands of 1.4$\mu\textrm{m}$ and 1.9$\mu\textrm{m}$ were removed, Hull Quotient method was applied to characterize absorption bands. The reflectances of field data were calculated to estimate the band ratio corresponding to the Landsat TM and EOS Terra ASTER. The researchers suggest here that the TM band2, band3, band4, and band7 or ASTER band2, band3, band4, and band9 are the best combination for discriminating outcrops. The researchers tested and demonstrated using a Landsat TM image in the study area. For geologic applications, decorrelation stretch is also an effective tool to enhance the exposed rock mass in images.

• Journal of The Geomorphological Association of Korea
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• v.21 no.4
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• pp.121-131
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• 2014

This study analyzed the spectral reflectance characteristics of kaolinite and ASTER(Advanced Spaceborne Thermal Emission and Reflectance Radiometer) image to extract the distribution of kaolin mines in Hadong area, Gyeongsangnam-do. The band ratio model was applied to extract kaolinite using difference of wavelength absorption band distinct feature of minerals from ASTER image which is the major mineral of kaolin mines. According to the spectral reflectance curve of kaolinite, it showed the absorption features around 0.96 and $2.18{\mu}m$ by Al-OH. Also, it affected 1.24 and $1.38{\sim}1.41{\mu}m$ by OH. Applying for new band ratio model from the spectral features of kaolinite to ASTER image, it is possible to make the distribution map of mining traces including present- developing kaolin mines.

• 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.

• Proceedings of the KSRS Conference
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• v.1
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• pp.25-28
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• 2006

We propose a new method of masking cloud-affected pixels in satellite ocean color imageries such as of GLI. Those pixels, mostly found around cloud pixels or in scattered cloud area, have anomalous features in either in chlorophyll-a estimate or in water reflectance. This artifact is most likely caused by residual error of inter-band registration correction. Our method is to check the pixel-wise 'soundness' of the spectral water reflectance Rw retrieved after the atmospheric correction. First, we define two spectral ratio between water reflectance, IRR1 and IRR2, each defined as RW(B1)/RW (B3) RW (B3) and as RW (B2)/RW(B4) respectively, where $B1{\sim}B4$ stand for 4 consecutive visible bands. We show that an almost linear relation holds over log-scaled IRR1 and IRR2 for shipmeasured RW data of SeaBAM in situ data set and for GLI cloud-free Level 2 sub-scenes. The method we propose is to utilize this nature, identifying those pixels that show significant discrepancy from that relationship. We apply this method to ADEOS-II/GLI ocean color data to evaluate the performance over Level-2 data, which includes different water types such as case 1, turbid case 2 and coccolithophore bloom waters.

• Atmosphere
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• v.14 no.2
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• pp.11-22
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• 2004

A technique on atmospheric correction algorithm to the multi-band reflectance of Landsat TM imagery has been developed using an atmospheric radiation transfer model for eliminating the atmospheric and surface diffusion effects. Despite the fact that the technique of satellite image processing has been continually developed, there is still a difference between the radiance value registered by satellite borne detector and the true value registered at the ground surface. Such difference is caused by atmospheric attenuations of radiance energy transfer process which is mostly associated with the presence of aerosol particles in atmospheric suspension and surface irradiance characteristics. The atmospheric reflectance depend on atmospheric optical depth and aerosol concentration, and closely related to geographical and environmental surface characteristics. Therefore, when the effects of surface diffuse and aerosol reflectance are eliminated from the satellite image, it is actually corrected from atmospheric optical conditions. The objective of this study is to develop an algorithm for making atmospheric correction in satellite image. The study is processed with the correction function which is developed for eliminating the effects of atmospheric path scattering and surface adjacent pixel spectral reflectance within an atmospheric radiation model. The diffused radiance of adjacent pixel in the image obtained from accounting the average reflectance in the $7{\times}7$ neighbourhood pixels and using the land cover classification. The atmospheric correction functions are provided by a radiation transfer model of LOWTRAN 7 based on the actual atmospheric soundings over the Korean atmospheric complexity. The model produce the upward radiances of satellite spectral image for a given surface reflectance and aerosol optical thickness.