• Journal of Biosystems Engineering
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• v.31 no.6 s.119
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• pp.463-473
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• 2006

Automated sensing of soil macronutrients would allow more efficient mapping of soil nutrient spatial variability for variable-rate nutrient management. The capabilities of ion-selective electrodes for sensing macronutrients in soil extracts can be affected by the presence of other ions in the soil itself as well as by high concentrations of ions in soil extractants. Adoption of automated, on-the-go sensing of soil nutrients would be enhanced if a single extracting solution could be used for the concurrent extraction of multiple soil macronutrients. This paper reports on the ability of the Kelowna extractant to extract macronutrients (N, P, and K) from US Corn Belt soils and whether previously developed PVC-based nitrate and potassium ion-selective electrodes could determine the nitrate and potassium concentrations in soil extracts obtained using the Kelowna extractant. The extraction efficiencies of nitrate-N and phosphorus obtained with the Kelowna solution for seven US Corn Belt soils were comparable to those obtained with IM KCI and Mehlich III solutions when measured with automated ion and ICP analyzers, respectively. However, the potassium levels extracted with the Kelowna extractant were, on average, 42% less than those obtained with the Mehlich III solution. Nevertheless, it was expected that Kelowna could extract proportional amounts of potassium ion due to a strong linear relationship ($r^2$ = 0.96). Use of the PVC-based nitrate and potassium ion-selective electrodes proved to be feasible in measuring nitrate-N and potassium ions in Kelowna - soil extracts with almost 1 : 1 relationships and high coefficients of determination ($r^2$ > 0.9) between the levels of nitrate-N and potassium obtained with the ion-selective electrodes and standard analytical instruments.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.415-418
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• 2004

The Studying is on developing precision of the moisture information on a soil. We used the data of AQUA AMSR-E which were obtained by Direct Receiving System in Korea Meteorological Administration(KMA). Although we know the Soil Moisture Information(SMI) helps the numerical weather model to produce the realistic results, we couldn't do it for the problem on a spatial resolution of the data is too low to apply. So we've tried to develop in a spatial resolution by using the AMSR-E data with a Digital Elevation Model(DEM) and Normal Difference Vegetation Index(NDVI) from AQUA MODIS and compared the difference between their information in statics. The result is more precise than the simple algorithm by a polarization ratio, and we could get the better result to use in forecast practically, if it's apply to get more detail in the vegetation temperature.

• 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 KSRS Conference
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• 2003.11a
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• pp.1368-1370
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• 2003

Conventional methods investigating soil Hg contamination are time-consuming and expensive. A quicker method is developed to predict soil Hg content with convolved HyMap, ASTER, and TM spectra. The prediction accuracy for each sensor is satisfactory and similar. It suggests that low spectral resolution is not a limitation for predicting soil Hg content. Correlation analysis reveals that Hg -sorption by iron oxides is the mechanism by which to predict spectrally featureless Hg with reflectance spectra. Future study with field measurements and remote sensing data is recommended.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.370-375
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• 1998

Spectral reflectance signatures of upland crops at OSMI bands were collected and evaluated for the feasibility of crop discrimination knowledge-based on crop calendar. Effective bands and their ratio values for discriminating corn from two other legumes were defined with OSMI equivalent bands and their ratio values. June 22 among measurements dates was the best date for corn discrimination from two other legumes, peanut and soybean, because all OSMI equivalent bands and their ratio values in June 22 were highly significant for corn separability. Phenological growth stage of a silage corn (rs510) could be estimated as a function of spectral reflectance signatures in vegetative stage. Five growth stage prediction models were generated by the SAS procedures REG and STEPWISE with OSMI equivalent bands and their ratio values in vegetative stage.

• 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.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1383-1385
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• 2003

Remote sensing has been widely used in the exploration of groundwater. In this paper, on the establishment of empirical function between ground water and soil moisture content 6S code is used to reduce uncertainties in the remote sensing of groundwater. Then ground water levels are calculated using 6S corrected and uncorrected ETM+ image along with isochronous meteorological information. Greater correspondence between field examined and satellite monitoring data is obtained from corrected image than from the uncorrected image.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.6 no.3
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• pp.9-16
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• 2003

In support of remote sensing applications for monitoring processes of the Earth system, research was conducted to analyze the basic spectral response related to background soil and vegetation cover characteristics in the visible and reflective infrared wavelengths. Surface samples of seven stations were examined. Five soils were from land-field and two soils from tideland areas. The vegetation cover experiment was conducted on seven soil samples with known natural moisture content (%) by weight. To study the effect of vegetation cover, spectral measurements were taken on five or six vegetation cover treatments of the seven soils with 3 replications in air dry conditions. For collecting RS base data, used spectro-radiometer that measures reflection characteristics between 300~1,100nm was used and measured the reflection of vegetation from bean leaves. The relationships were evaluated for both a general soil line and for the individual lines of five soils, under air-dried condition as well as different vegetation cover ratio, through the determination of the line parameters. As vegetation cover ratio in bean leaves increases, features of soil reflectance decrease and those of plant reflectance become more and more apparent. In proportion to vegetation cover rate, near-infrared reflectance increased and visible reflectance decreased. Analysis results are compared to commonly used vegetation indices(RVI and NDVI ).

• Proceedings of the Korean Society of Crop Science Conference
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• 2005.08a
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• pp.75-87
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• 2005

Remote sensing(RS)- and geographic information system(GIS)-based information management to measure and assess agri-environment schemes, and to quantify and map environment indicators for nature and land use, climate change, air, water and energy balance, waste and material flow is in high demand because it is very helpful in assisting decision making activities of farmers, government, researchers, and consumers. The versatility and ability of RS and GIS containing huge soil database to assess agricultural environment spatially and temporally at various spatial scales were investigated. Spectral and microwave observations were carried out to characterize crop variables and soil properties. Multiple sources RS data from ground sensors, airborne sensors, and also satellite sensors were collected and analyzed to extract features and land cover/use for soils, crops, and vegetation for support precision agriculture, soil/land suitability, soil property estimation, crop growth estimation, runoff potential estimation, irrigated and the estimation of flooded areas in paddy rice fields. RS and GIS play essential roles in a management and monitoring information system. Biosphere-atmosphere interection should also be further studied to improve synergistic modeling for environment and sustainability in agri-environment schemes.

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.2
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• pp.123-132
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• 1996

The purpose of this study was to clarify the reflectance of soil and plant in order to extract the soil and vegetation informations using the satellite remote sensing data. The influence of soil moisture content and vegetation cover rate on the soil reflectance, and the relationship between vegetation reflectence and its vitality were discussed. The results obtained in this study were summarized as follows; I) The soil reflectance($R_{0.65}$) of wavelength ($0.65{\mu}m$) was closely related to the reflectance((($IR_{0.85}$) of wavelength $0.85{\mu}m$. This relationship could be expressed by soil line. 2) A point on the soil line was affected by the soil moisture ratio and the organic matter content. 3) The vegetation cover rate was formulated in terms of soil and vegetation reflectance at wavelengths pf $0.65{\mu}m$($R_{0.65}$) and ($0.85{\mu}m$) (($IR_{0.85}$). 4) The vegetation reflectence was strongly influenced by its vitality, which was related to the moisture content and the chlorophy [[-a concentration.