• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.563-570
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• 2019

Red tide has caused massive fish kills in Korean coastal waters with devastating economic loss in the aquaculture industry since 1995. Remote sensing technique has shown to be effective for the detection of red tide in wide areas, where the absorption property of red tide water plays a central role in understanding the red tide reflectance. This study analyzed the optical absorption property of sea waters dominated by the dinoflagellate specie of Alexandirum affine, off the Tongyeong area in August, 2017. Water samples collected from 20 stations in the ship-based campaign were measured for absorption by pigment, suspended solid, and dissolved organic matter, with the corresponding water quality variables such as chlorophyll concentration and total suspended solid. The analysis showed that Alexandrium-dominated water exhibits strong absorption in the spectral range below 400 nm unlike that of diatom-dominated waters, and greater fluctuations in the range of 400 nm - 500 nm. The packaging effect in pigment absorption was stronger in Alexandrium-dominated waters, and the exponent in the absorption by detritus and gelbstoff is disparate for diatom and Alexandrium. In the model for the detritus and gelbstoff absorption (a_dg(λ)=a_dg(λ₀)e^-s(λ-λ₀)), the optimal exponent coefficient(s) for the Alexandrium was close to 0.01 rather than to 0.015, which was commonly use for modelling diatom waters.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.5
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• pp.342-349
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• 2001

This study was carried out to classify and evaluate the land cover map using Landsat TM data in Pyeongtaeg City. DGPS data, aerial photography, topographical map were used for selection the training sets and accuracy assessment. The overall accuracy and Kappa coefficient of the land cover classification map(using supervised classification with 13 classes) with Landsat TM data(16 June. 1997) were respectively, 86.8%, 85.4%, but the user's accuracy of urban/village and vinyl-house was below 60%, and the producer's accuracy of read and vinyl-house below 70%. Maybe it was caused the spectral reflectance characteristics, heterogeneity and small distribution area on the artificial things such as urban/village, vinyl_house and road, etc. And then, the agricultural land cover classification system using remote sensing data in Korea was to classify level I and II. Level I consisted of 5 classes such as agricultural land, forest land, water, barren land, urban and built-up land.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.968-974
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• 2010

We assessed the feasibility of discrete wavelet transform (DWT) applied for the spectral processing to enhance the estimation performance quality of soil organic matters using visible-near infrared spectra and mapped their distribution via block Kriging model. Continuum-removal and $1^{st}$ derivative transform as well as Haar and Daubechies DWT were used to enhance spectral variation in terms of soil organic matter contents and those spectra were put into the PLSR (Partial Least Squares Regression) model. Estimation results using raw reflectance and transformed spectra showed similar quality with $R^2$ > 0.6 and RPD> 1.5. These values mean the approximation prediction on soil organic matter contents. The poor performance of estimation using DWT spectra might be caused by coarser approximation of DWT which not enough to express spectral variation based on soil organic matter contents. The distribution maps of soil organic matter were drawn via a spatial information model, Kriging. Organic contents of soil samples made Gaussian distribution centered at around 20 g $kg^{-1}$ and the values in the map were distributed with similar patterns. The estimated organic matter contents had similar distribution to the measured values even though some parts of estimated value map showed slightly higher. If the estimation quality is improved more, estimation model and mapping using spectroscopy may be applied in global soil mapping, soil classification, and remote sensing data analysis as a rapid and cost-effective method.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.251-267
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• 2021

Remotely sensed vegetation indices (VIs) are empirically related with gross primary productivity (GPP) in various spatio-temporal scales. The uncertainties in GPP-VI relationship increase with temporal resolution. Uncertainty also exists in the eddy covariance (EC)-based estimation of GPP, arising from the partitioning of the measured net ecosystem CO2 exchange (NEE) into GPP and ecosystem respiration (RE). For two forests and two agricultural sites, we correlated the EC-derived GPP in various time scales with three different near-surface remotely sensed VIs: (1) normalized difference vegetation index (NDVI), (2) enhanced vegetation index (EVI), and (3) near infrared reflectance from vegetation (NIRv) along with NIRvP (i.e., NIRv multiplied by photosynthetically active radiation, PAR). Among the compared VIs, NIRvP showed highest correlation with half-hourly and monthly GPP at all sites. The NIRvP was used to test the reliability of GPP derived by two different NEE partitioning methods: (1) original KoFlux methods (GPP_Ori) and (2) machine-learning based method (GPP_ANN). GPP_ANN showed higher correlation with NIRvP at half-hourly time scale, but there was no difference at daily time scale. The NIRvP-GPP correlation was lower under clear sky conditions due to co-limitation of GPP by other environmental conditions such as air temperature, vapor pressure deficit and soil moisture. However, under cloudy conditions when photosynthesis is mainly limited by radiation, the use of NIRvP was more promising to test the credibility of NEE partitioning methods. Despite the necessity of further analyses, the results suggest that NIRvP can be used as the proxy of GPP at high temporal-scale. However, for the VIs-based GPP estimation with high temporal resolution to be meaningful, complex systems-based analysis methods (related to systems thinking and self-organization that goes beyond the empirical VIs-GPP relationship) should be developed.