• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.319-341
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• 2024

The utilization of multispectral imaging systems (MIS) in remote sensing has become crucial for large-scale agricultural operations, particularly for diagnosing plant health, monitoring crop growth, and estimating plant phenotypic traits through vegetation indices (VIs). However, environmental factors can significantly affect the accuracy of multispectral reflectance data, leading to potential errors in VIs and crop status assessments. This paper reviewed the complex interactions between environmental conditions and multispectral sensors emphasizing the importance of accounting for these factors to enhance the reliability of reflectance data in agricultural applications.An overview of the fundamentals of multispectral sensors and the operational principles behind vegetation index (VI) computation was reviewed. The review highlights the impact of environmental conditions, particularly solar zenith angle (SZA), on reflectance data quality. Higher SZA values increase cloud optical thickness and droplet concentration by 40-70%, affecting reflectance in the red (-0.01 to 0.02) and near-infrared (NIR) bands (-0.03 to 0.06), crucial for VI accuracy. An SZA of 45° is optimal for data collection, while atmospheric conditions, such as water vapor and aerosols, greatly influence reflectance data, affecting forest biomass estimates and agricultural assessments. During the COVID-19 lockdown,reduced atmospheric interference improved the accuracy of satellite image reflectance consistency. The NIR/Red edge ratio and water index emerged as the most stable indices, providing consistent measurements across different lighting conditions. Additionally, a simulated environment demonstrated that MIS surface reflectance can vary 10-20% with changes in aerosol optical thickness, 15-30% with water vapor levels, and up to 25% in NIR reflectance due to high wind speeds. Seasonal factors like temperature and humidity can cause up to a 15% change, highlighting the complexity of environmental impacts on remote sensing data. This review indicated the importance of precisely managing environmental factors to maintain the integrity of VIs calculations. Explaining the relationship between environmental variables and multispectral sensors offers valuable insights for optimizing the accuracy and reliability of remote sensing data in various agricultural applications.

• Korean Journal of Remote Sensing
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• v.13 no.2
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• pp.99-120
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• 1997

Solar radiation is scattered and absorbed atmospheric compositions in the atmosphere before it reaches the surface and, then after reflected at the surface, until it reaches the satellite sensor. Therefore, consideration of the radiative transfer through the atmosphere is essential for the quantitave analysis of the satellite sensed data, specially at shortwave region. This study examined a feasibility of using radiative transfer code for estimating the atmospheric effects on satellite remote sensing data. To do this, the flux simulated by LOWTRAN7 is compared with CAGEX data in shortwave region. The CAGEX (CERES/ARM/GEWEX Experiment) data provides a dataset of (1) atmospheric soundings, aerosol optical depth and albedo, (2) ARM(Aerosol Radiation Measurement) radiation flux measured by pyrgeometers, pyrheliometer and shadow pyranometer and (3) broadband shortwave flux simulated by Fu-Liou's radiative transfer code. To simulate aerosol effect using the radiative transfer model, the aerosol optical characteristics were extracted from observed aerosol column optical depth, Spinhirne's experimental vertical distribution of scattering coefficient and D'Almeida's statistical atmospheric aerosols radiative characteristics. Simulation of LOWTRAN7 are performed on 31 sample of completely clear days. LOWTRAN's result and CAGEX data are compared on upward, downward direct, downward diffuse solar flux at the surface and upward solar flux at the top of the atmosphere(TOA). The standard errors in LOWTRAN7 simulation of the above components are within 5% except for the downward diffuse solar flux at the surface(6.9%). The results show that a large part of error in LOWTRAN7 flux simulation appeared in the diffuse component due to scattering mainly by atmispheric aerosol. For improving the accuracy of radiative transfer simulation by model, there is a need to provide better information about the radiative charateristrics of atmospheric aerosols.

• Proceedings of the KSRS Conference
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• v.2
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• pp.794-796
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• 2006

This study investigated the Brightness Temperature Difference threshold as criterion between aerosols and clouds in conjunction with radiative transfer model. Surface temperature is caused by a significant error over 50% in the BTD threshold. In addition, The BTD threshold contains the uncertainties about 20% due to the surface emissivity and 8% due to the satellite zenith angle. Therefore, we have composed the Look-up table for BTD between 11㎛and 12㎛ according to satellite zenith angle, surface temperature, and surface emissivity. The modified BTD show the enhanced signal, especially over bright surface such as desert in China. However, a weak aerosol signal over Ocean remains in the modified BTD.

• Korean Journal of Remote Sensing
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• v.17 no.3
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• pp.211-218
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• 2001

We have performed the calculation of total radiances for the KOMPSAT-2 Multispectral Camera (MSC) using a radiative transfer model of MODTRAN and examined its results. To simulate four seasonal conditions in the model calculation, we used model atmospheres of mid-latitude winter and summer for calculations of January 15 and July 15, and US standard for April 15 and October 15, respectively. Orbital parameters of KOMPSAT-2 and the seasonal solar zenith angles were taken into account. We assumed that the meteorological range is the tropospheric aerosol extinction of 50 km and surface albedo is the global average of clear-sky albedo of 0.135. MSC contract values are found to be considerably greater in the MSC spectral range than the total radiances calculated with the above general conditions. It is also shown that the spectral behavior of model results with the constant surface albedo differs from the pattern of MSC contract values. From these results, it can be inferred that the forthcoming MSC images would be somewhat dark.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1891-1900
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• 2021

Fine particulate matter (FPM; diameter ≤ 2.5 ㎛) is frequently found in metropolitan areas due to activities associated with rapid urbanization and population growth. Many adolescents spend a substantial amount of time at school where, for various reasons, FPM generated outdoors may flow into indoor areas. The aims of this study were to estimate FPM concentrations and categorize types of FPM in schools. Meteorological and chemical variables as well as satellite-based aerosol optical depth were analyzed as input data in a random forest model, which applied 10-fold cross validation and a grid-search method, to estimate school FPM concentrations, with four statistical indicators used to evaluate accuracy. Loose and strict standards were established to categorize types of FPM in schools. Under the former classification scheme, FPM in most schools was classified as type 2 or 3, whereas under strict standards, school FPM was mostly classified as type 3 or 4.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.336-339
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• 2008

Monthly mean data of Angstrom exponent and Aerosol optical thickness (AOT) from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) measurements over the East Asian waters were analyzed. Increasing trend of the satellite-derived Angstrom exponent was found over 1998-2006 while AOT mean was observed stable during the same period. Statistical test showed that annual increase in Angstrom exponent of about 0.01 is statistically significant over three study sub-areas out of six surrounding waters of Japan. Comparison with Aqua/MODIS-derived Angstrom exponent time series over June 2002 through June 2008 showed consistent correlation, with similar statistical significance. The trend of Angstrom exponent was interpreted as increase in fraction of small aerosol particles to give quantitative estimates on the variability of aerosols. The mean increase is evaluated to be about +0.35%/yr or more in terms of the contribution of small particles to the total AOT, or sub-micron fraction (SMF).

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.57-60
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• 2007

Monthly mean data of ${\AA}ngstr{\ddot{o}}m$ exponent and Aerosol optical thickness (AOT) from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) measurements over the East Asian waters were analyzed. Increasing trend of the satellite-derived ${\AA}ngstr{\ddot{o}}m$ exponent from 1998 to 2004 was found while AOT mean was observed stable during the same period. The trend of ${\AA}ngstr{\ddot{o}}m$ exponent is then interpreted as increase in fraction of small aerosol particles to give quantitative estimates on the variability of aerosols. The mean increase is evaluated to be $4{\sim}5%$ over the 7-year period in terms of the contribution of small particles to the total AOT, or sub-micron fraction (SMF). Possibilities of the observed trend arising from the sensor calibration or algorithm performance are carefully checked, which confirm our belief that this observed trend is rather a real fact than an artifact due to data processing. Another time series of SMF data (2000-2005) estimated from the fine-mode fraction (FMF) of Moderate Resolution Imaging Spectroradiometer (MODIS) supports this observation yet with different calibration system and retrieval algorithms.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.413-421
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• 2016

In this study, correlations between Moderate Resolution Imaging Spectroradiometer (MODIS) derived Aerosol Optical Depth (AOD) values and surface-level $PM_{2.5}$ concentrations at Gosan, Korea have been investigated. For this purpose, data from various instruments, such as satellite, sunphotometer, Optical Particle Counter (OPC), and Micro Pulse Lidar (MPL) on 14-24 October 2009 were used. Direct comparison between sunphotometer measured AOD and surface-level $PM_{2.5}$ concentrations showed a $R^2=0.48$. Since the AERONET L2.0 data has significant number of observations with high AOD values paired to low surface-level $PM_{2.5}$ values, which were believed to be the effect of thin cloud or Asian dust. Correlations between MODIS AOD and $PM_{2.5}$ concentration were increased by screening thin clouds and Asian dust cases by use of aerosol profile data on Micro-Pulse Lidar Network (MPLNet) as $R^2$ > 0.60. Our study clearly demonstrates that satellite derived AOD is a good surrogate for monitoring atmospheric PM concentration.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.499-509
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• 2016

The occurrence of sand dust has been steadily increased since 1990 and the amount of damage was also increased. In most of previous studies, ground based observations were used for sand dust analyses, but its high spatio-temporal variability has not been well understood. In this study, satellite aerosol observations were used to overcome current limitations of the sand dust variability in space and time and to estimate associations with morbidity of respiratory and cardiovascular ailments. In general, high AODs were observed in the west part of the Koran peninsula in spring. The reasonable associations between the morbidity and sand dust were observed from April to July with highest positive correlation (~0.6) at three month lags (lag 3). Based on the results, we found a utility of the satellite aerosol observations for sand dust analyses by considering of morbidity effects. In addition, health effect against the sand dust is proved to be examined and smooth medical supplies and prevention of undesired medical expenses would be possible.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.369-379
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• 2008

The aerosol retrieval algorithm for the Moderate Resolution Imaging Spectroradiometer (MODIS) measurements was updated recently. This paper reports on the comparison and validation of two latest versions (Collection 4 and 5, shortly C004 and C005) of the MODIS aerosol product over northeast Asian region. The differences between the aerosol optical thickness (AOT) from the C004 and C005 retrieval algorithms and the correlation with ground based AERONET sunphotometer observations are investigated. Over the study region, spatially averaged annual mean AOT retrieved from C005 algorithm $(AOT_{C005})$ is about 0.035 AOT (5%) less than the C004 counterparts. The linear correlations between MODIS and AERONET AOT also are R=0.89 (slope=0.86) for the C004 and R=0.95 (slope=1.00) for the C005. Moreover, the magnitude of the mean error in $AOT_{C005}$, difference between MODIS AOT and AERONET AOT, is 40% less than that in $AOT_{C004}$.