• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.305-311
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• 2006

Although there have been several attempts to estimate forest LAI using optical remote sensor data, there are still not enough evidences whether the NDVI is effective to estimate forest LAI, particularly in fully closed canopy situation. In this study, we have conducted a simple correlation analysis between LAI and spectral reflectance at two different settings: 1) laboratory spectral measurements on the multiple-layers of leaf samples and 2) Landsat ETM+ reflectance in the close canopy forest stands with fieldmeasured LAI. In both cases, the correlation coefficients between LAI and spectral reflectance were higher in short-wave infrared (SWIR) and visible wavelength regions. Although the near-IR reflectance showed positive correlations with LAI, the correlations strength is weaker than in SWIR and visible region. The higher correlations were found with the spectral reflectance data measured on the simulated vegetation samples than with the ETM+ reflectance on the actual forests. In addition, there was no significant correlation between the forest.LAI and NDVI, in particular when the LAI values were larger than three. The SWIR reflectance may be important factor to improve the potential of optical remote sensor data to estimate forest LAI in close canopy situation.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.397-418
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• 2024

The Land Surface Temperature (LST) is a crucial parameter in identifying drought. It is essential to identify how LST can increase its accuracy, particularly in mountainous and hill areas. Increasing the LST accuracy can be achieved by applying early data processing in the correction phase, specifically in the context of topographic correction on the Lambertian model. Empirical evidence has demonstrated that this particular stage effectively enhances the process of identifying objects, especially within areas that lack direct illumination. Therefore, this research aims to examine the application of the Lambertian model in estimating LST using the Multi-Channel Method (MCM) across various physiographic regions. Lambertian model is a method that utilizes Lambertian reflectance and specifically addresses the radiance value obtained from Sun-Canopy-Sensor(SCS) and Cosine Correction measurements. Applying topographical adjustment to the LST outcome results in a notable augmentation in the dispersion of LST values. Nevertheless, the area physiography is also significant as the plains terrain tends to have an extreme LST value of ≥ 350 K. In mountainous and hilly terrains, the LST value often falls within the range of 310-325 K. The absence of topographic correction in LST results in varying values: 22 K for the plains area, 12-21 K for hilly and mountainous terrain, and 7-9 K for both plains and mountainous terrains. Furthermore, validation results indicate that employing the Lambertian model with SCS and Cosine Correction methods yields superior outcomes compared to processing without the Lambertian model, particularly in hilly and mountainous terrain. Conversely, in plain areas, the Lambertian model's application proves suboptimal. Additionally, the relationship between physiography and LST derived using the Lambertian model shows a high average R² value of 0.99. The lowest errors(K) and root mean square error values, approximately ±2 K and 0.54, respectively, were achieved using the Lambertian model with the SCS method. Based on the findings, this research concluded that the Lambertian model could increase LST values. These corrected values are often higher than the LST values obtained without the Lambertian model.

• Korean Journal of Agricultural Science
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• v.38 no.4
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• pp.747-752
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• 2011

Wireless technology has enabled farmers monitor and control protected production environment more efficiently. Utilization of USN (Ubiquitous Sensor Network) devices also brought benefits due to reduced wiring and central data handling requirements. However, wireless communication loses signal under unfavorable conditions (e.g., blocked signal path, low signal intensity). In this paper, performance of commercial wireless communication devices were evaluated for application to protected crop production. Two different models of wireless communication devices were tested. Sensors used in the study were weather units installed outside and top of a greenhouse (wind velocity and direction, precipitation, temperature and humidity), inside ambient condition units (temperature, humidity, $CO_2$, and light intensity), and irrigation status units (irrigation flow and pressure, and soil water content). Performance of wireless communication was evaluated with and without crop. For a 2.4 GHz device, communication distance was decreased by about 10% when crops were present between the transmitting and receiving antennas installed on the ground, and the best performance was obtained when the antennas were installed 2 m above the crop canopy. When tested in a greenhouse, center of a greenhouse was chosen as the location of receiving antenna. The results would provide information useful for implementation of wireless environment monitoring system for protected crop production using USN devices.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1207-1217
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• 2022

Vegetation indices using the reflectance of selected wavelength, associating with the monitoring purpose such as identifying the progress of crop growth, on the vegetation canopy surface is widely used in the digital agriculture technology. However, the surface reflectance anisotropy can distort the true value of vegetation index related to the condition of surface, even though the surface property be unchanged. That causes difficulty to observe accurately crop growth on the monitoring system. In this study, a simple type goniometer was designed to measure the reflectance from the anisotropic surface according to various zeniths and azimuths of sun and viewing sensor in the field. On the tarp like as Lambertian surface, the reflectance of Blue, Green, Red, Near-Infrared band was similar to the tarps' reflectance properties. However, the reflectance was slightly overestimated in the cloudy day. The relative difference values of vegetation indices on grass were overestimated for the forward viewing and underestimated for the backward viewing. In addition, enhanced vegetation index (EVI) showed less sensitive according to the positions of sun and sensor viewing. Field observation with a goniometer will be helpful to understand the anisotropy characteristics on the vegetation surface.

• Horticultural Science & Technology
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• v.33 no.3
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• pp.303-308
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• 2015

The consumption of leaf vegetables has been steadily increasing in Korea. Leaf vegetables are used for "Ssam (vegetable wrap-up), eaf vegetables has been steadily increasing in Korea. Leaf vegetables are used for asoned condiments inside several layers of young vegetable leaves. This study investigated the effect of air temperature on the growth and phytochemical contents of beet (Beta vulgaris L.) and Ssamchoo (Brassica lee L. ssp. namai) grown in a closed-type plant factory system where fluorescent lamps were used as an artificial light source. Seeds of beet and Ssamchoo were sown in a peat-lite germination mix. The roots of 20-day-old seedlings were washed, and the seedlings were planted on a styrofoam board and grown in hydroponic beds for 25 days under fluorescent light. Plants were exposed to one of three different air temperature regimes (20, 25 and $30^{\circ}C$ during the day combined with $18^{\circ}C$ during the night), which were monitored with a sensor at 30 cm above the plant canopy. Increased plant height and leaf area were observed in beet at $25^{\circ}C$ and $30^{\circ}C$ compared to $20^{\circ}C$. For Ssamchoo, the greatest plant height, leaf area, fresh weight and dry weight were obtained at $20^{\circ}C$. Ascorbic acid content of beet and Ssamchoo leaves were highest at $30^{\circ}C$. In beet, total polyphenol and flavonoid contents were higher at $20^{\circ}C$ (42.4, $197.0mg{\cdot}g^{-1}DW$) and $25^{\circ}C$ (46.9, $217.0mg{\cdot}g^{-1}DW$) than $30^{\circ}C$ (22.4, $88.0mg{\cdot}g^{-1}DW$). In Ssamchoo, total polyphenol and flavonoid contents were also higher at $20^{\circ}C$ (79.2, $268.2mg{\cdot}g^{-1}DW$) and $25^{\circ}C$ (66.3, $258.3mg{\cdot}g^{-1}DW$), respectively, than $30^{\circ}C$ (53.7, $134.7mg{\cdot}g^{-1}DW$). Hence, the optimum temperature appears to be $20^{\circ}C$ for growing both beet and Ssamchoo in a closed-type plant factory system with fluorescent light.