• Journal of Environmental Impact Assessment
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• v.9 no.3
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• pp.177-183
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• 2000

The Landsat Thematic Mapper (TM) has suggested that spatial and spectral characteristics would be suited to evaluate water quality of lake. But, TM has not been commonly used for the analysis of in-land water quality, such as surface water temperature, chlorophyll-a, suspended sediments, and Secchi depth in domestic research. This paper summarizes the analysis of Landsat 5 - TM image collected on 22 Feb 1996 for evaluation of chlorophyll-a and surface temperature in the Lake Soyang. And, field measurements collected in the Lake Soyang were used to obtain water optical algorithms for calibration of satellite data. It is concluded that we can assess chlorophyll-a with remote sensing reflectance and surface temperature with thermal band in lake Soyang. However, surface temperature calculated with thermal band of Landsat TM are underestimated. Relationship between remote sensing reflectance and chlorophyll-a using the ratio of TM band 1 and band 3 is as follows; Y = 17.206 - 6.4711 * (Rrs(band1) / Rrs(band3)) $R^2$=0.8762 and, using the ratio of TM band 1 and band 2 as follows; Y = 57.77 - 35.771 * (Rrs(band1) / Rrs(band2)) $R^2$=0.8317.

• Journal of the Korean Geotechnical Society
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• v.35 no.11
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• pp.51-62
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• 2019

In this study, a simple method to estimate the soil water content variation in a wide area was proposed using hyperspectral near-infrared images. The reflectance data of a sand, granite soils, and a kaolinite were measured by reflecting the soil samples with different wavelengths in the visible and near-infrared (VNIR) regions using hyperspectral cameras. The measured reflectances and parameters were used to build a water content prediction model using the Partial Least Square Regression (PLSR) analysis. In the water content prediction model, the Area of Reflectance (Near-infrared, NIR) parameter was the most suitable parameter to determine the water content. The parameter was applicable regardless of the soil type, as the coefficient of determination (R²) exceeded 0.9 for each soil sample. Additionally, the mean absolute percentage error (MAPE) was less than 15% when compared with the actual water content of the soil. Therefore, the predictability of water content variation for soils with water content lower than 50% was confirmed. Accordingly through this study, the predictability of water content variation in several soil types using the hyperspectral near-infrared images was confirmed. For further development, a model that incorporates soil classification would be required to improve the accuracy of the model and to predict higher range of water contents.

• Korean Journal of Remote Sensing
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• v.31 no.4
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• pp.281-291
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• 2015

Sun glint correction methods of hyperspectral data that have been developed so far have not considered the various situations and are often adequate for only certain conditions. Also there is an inaccurate assumption that the signal in NIR wavelength is zero. Therefore, this study attempts to analyze the NIR spectral properties of sun glint effect in coastal waters. For the analysis, CASI-1500 airborne hyperspectral data, bathymetry data and in-situ data obtained at coastal area near Sin-Cheon, Jeju Island, South Korea were used. The spectral characteristics of radiance and reflectance at the five NIR wavelengths (744 nm, 758 nm, 772 nm, 786 nm, and 801 nm) are analyzed by using various statistics, spatial and spectral variation of sun-glinted area under conditions of the bottom types of benthos, barren rocks and sand with similar water depth. Through the quantitative analysis, we found that the relation of water depth or bottom type with sun glint is relatively less which is a similar result with the previous studies. However the sun glint are distributed similarly with the patterns of the direction of wave propagation. It is confirmed that the areas with changed direction of wave propagation were not affected by the sun glint. The spatial and spectral variations of radiance and reflectance are mainly caused by the effect of sun glint and waves. The radiance or reflectance of more sun-glinted areas are increased approximately 1.5 times and the standard deviations are also increased three times compared to the less sun glinted areas. Through this study, the further studies of sun glint correction method in coastal water using the patterns of wave propagation and diffraction will be placed.

• 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%.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.615-625
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• 2021

The coastal areas around Palau Island and Tonga Island, near the Pacific equator, consist of coral reefs, mangrove and seaweed. In particular, understanding the optical properties of sea surface water in coral reef habitats helps improve the accuracy of remote sensing based habitat mapping and identify tropical ecosystem characteristics. Here, we collected spectral characteristics of sea surface water of Palau Island and Tonga Island and analyzed the concentration of suspended matters, absorption coefficient, and remote sensing reflectance to understand the seawater characteristics of the coral reef habitats. Based on the results of the suspended matter concentration analysis, we developed and verified an empirical algorithm to derive the concentration from satellite data using remote sensing reflectance of three bands, 555, 625, 660 nm, showed a high determinant coefficient, 0.98. In conclusion, coral reef habitats in tropical regions are characterized by CASE-I water in terms of the marine optics with oligotrophic properties, and require monitoring using continuous collection and analysis of field data.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.173-182
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• 2013

The early Sea-viewing Wide Field-of-view Sensor(SeaWiFS) atmospheric correction algorithm which is the basis of the atmospheric correction algorithm for Geostationary Ocean Color Imager(GOCI) assumes that water-leaving radiances is negligible at near-infrared(NIR) wavelengths. For this reason, all of the satellite measured radiances at the NIR wavelengths are assigned to aerosol radiances. However that assumption would cause underestimation of water-leaving radiances if it were applied to turbid Case-2 waters. To overcome this problem, Management Unit of the North Sea Mathematical Models(MUMM) atmospheric correction algorithm has been developed for turbid waters. This MUMM algorithm introduces new parameter ${\alpha}$, representing the ratio of water-leaving reflectance at the NIR wavelengths. ${\alpha}$ is calculated by statistical method and is assumed to be constant throughout the study area. Using this algorithm, we can obtain comparatively accurate water-leaving radiances in the moderately turbid waters where the NIR water-leaving reflectance is less than approximately 0.01. However, this algorithm still underestimates the water-leaving radiances at the extremely turbid water since the ratio of water-leaving radiance at two NIR wavelengths, ${\alpha}$ is changed with concentration of suspended particles. In this study, we modified the MUMM algorithm to calculate appropriate value for ${\alpha}$ using an iterative technique. As a result, the accuracy of water-leaving reflectance has been significantly improved. Specifically, the results show that the Root Mean Square Error(RMSE) of the modified MUMM algorithm was 0.002 while that of the MUMM algorithm was 0.0048.

• Journal of Biosystems Engineering
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• v.36 no.1
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• pp.33-39
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• 2011

An optical sensing approach based on diffuse reflectance has shown potential for rapid and reliable on-site estimation of soil properties. Important sensing ranges and the resulting regression models useful for soil property estimation have been reported. In this study, a similar approach was applied to investigate the potential of reflectance sensing in estimating soil properties for Korean paddy fields. Soil cores up to a 65-cm depth were collected from 42 paddy fields representing 14 distinct soil series that account for 74% of the total Korean paddy field area. These were analyzed in the laboratory for several important physical and chemical properties. Using air-dried, sieved soil samples, reflectance data were obtained from 350 to 2500 nm on a 3 nm sampling interval with a laboratory spectrometer. Calibrations were developed using partial least squares (PLS) regression, and wavelength bands important for estimating the measured soil properties were identified. PLS regression provided good estimations of Mg ($R^2$ = 0.80), Ca ($R^2$ = 0.77), and total C ($R^2$ = 0.92); fair estimations of pH, EC, $P_2O_5$, K, Na, sand, silt, and clay ($R^2$ = 0.59 to 0.72); and poor estimation of total N. Many wavelengths selected for estimation of the soil properties were identical or similar for multiple soil properties. More important wavelengths were selected in the visible-short NIR range (350-1000 nm) and the long NIR range (1800-2500 nm) than in the intermediate NIR range (1000-1800 nm). These results will be useful for design and application of in-situ close range sensors for paddy field soil properties.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1541-1555
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• 2022

Red tide has potential to harm marine ecology and aquaculture. Research on detecting red tide using various optical remote sensors has been conducted, but most of existing algorithms for detecting red tide has limitations, especially in shallow coastal waters with high levels of suspended sediment. For enhanced understanding of the optical behavior of red tide waters, analysis on remote sensing reflectance and water constituent is becoming increasingly important. This study analyzed the optical remote sensing data and water quality variables(Chl-a_(Spec), SPM, a_ph, a_d, Turbidity, Chl-a_(HPLC), Dominant species) of red tide waters. The data were collected from ship-based campaigns. In addition to the research on detecting red tide, the remote sensing reflectance and extinction coefficients for mesodinium and cochlodinium species were also analyzed. Through the analysis, it was possible to estimate the red tide chlorophyll concentration based on a specific wavelength of the remote sensing reflectance. The study found that chlorophyll concentration and phytoplankton absorption coefficient were highly correlated(R²=0.9), and that the RE_diff formula provided a more accurate estimate of red tide concentration than the B-G ratio.

• Asian Journal of Turfgrass Science
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• v.22 no.1
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• pp.1-12
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• 2008

Remote sensing using multispectral radiometry may be a useful tool to detect drought stress in turf. The objective of this research was to investigate the correlation between drought stress and multispectral reflectance (MSR) from the turf canopy. St. Augustinegrass (Stenotaphrum secundatum[Walt.] Kuntze.) cultivars 'Floratam' and 'Palmetto', 'SeaIsle 1' seashore paspalum Paspalum vaginatum Swartz.), 'Empire' zoysiagrass (Zoysia japonica Steud.), and 'Pensacola' bahiagrass (Paspalum notatumFlugge) were established in lysimeters in the University of Florida Envirotron greenhouse facility in Gainesville. Irrigation was applied at 100%, 80%, 60%, or 40% of evapotranspiration (ET). Weekly evaluations included: a) shoot quality, leaf rolling, leaf firing b) soil moisture, chlorophyll content index; c) photosynthesis and d) multispectral reflectance. All the measurements were correlated with MSR data. Drought stress affected the infrared spectral region more than the visible spectral region. Reflectance sensitivity to water content of leaves was higher in the infrared spectral region than in the visible spectral region. Grasses irrigated at 100% and 80% of ET had no differences in normalized difference vegetation indices (NDVI), leaf area index (LAI), and stress indices. Grasses irrigated at 60% and 40% of ET had differences in NDVI, LAI, and stress indices. All measured wavelengths except 710nm were highly correlated (P < 0.0001) with turf visual quality, leaf firing, leaf rolling, soil moisture, chlorophyll content index, and photosynthesis. MSR could detect drought stress from the turf canopy.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.529-538
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• 2016

This study, multispectral and hyperspectral sensors were utilized to use radiometric cross validation for the purpose of radiometric quality evaluation of a 'KOMPSAT-3'. Images of EO-1 Hyperion and Landsat-8 OLI sensors taken in PICS site were used. 2 sections that have 2 different types of ground coverage respectively were selected as the site of cross validation based on aerial hyperspectral sensor and TOA Reflectance. As a result of comparison between the TOA reflectance figures of KOMPSAT-3, EO-1 Hyperion and CASI-1500, the difference was roughly 4%. It is considered that it satisfies the radiological quality standard when the difference of figure of reflectance in a comparison to the other satellites is found within 5%. The difference in Blue, Green, Red band was approximately 3% as a comparison result of TOA reflectance. However the figure was relatively low in NIR band in a comparison to Landsat-8. It is thought that the relatively low reflectance is because there is a difference of band passes in NIR band of 2 sensors and in a case of KOMPSAT-3 sensor, a section of 940nm, which shows the strong absorption through water vapor, is included in band pass resulting in comparatively low reflectance. To overcome these conditions, more detailed analysis with the application of rescale method as Spectral Bandwidth Adjustment Factor (SBAF) is required.