• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.131-140
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• 2011

In this study, temporal variations of the Advanced Microwave Scanning Radiometer E (AMSR-E) soil moisture products were evaluated using ground based measurements from the Haenam flux monitoring network site for two years (2004 and 2006). Even if there were major comparison issues including spatial resolutions, AMSR-E soil moisture production showed a great potential to replicate temporal variability patterns with ground based measurements. Additional intensive validation efforts should be conducted at a variety of field conditions including vegetation type for better utilization of remotely sensed soil moisture and understanding of the land surface-atmosphere interactions in the view of hydrometeorology.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.422-425
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• 2005

Spectral characteristics depending on soil constituents and their proportion in a soil were firstly studied for monitoring of soil contamination using hyperspectral remote sensing. The reflectance spectra of heavy metals in soils were investigated in the VIS-NIR-SWIR regions (400-2500 nm) to observe spectral variation as a function of constituents and concentrations. Commercial kaolinite soils mixed with lead, copper, arsenic, and cadmium were used as synthetic soil samples for spectral measurement. In case of copper, relatively spectrally active regions was observed with some band shift whereas other heavy metals had only simple spectral variations expected to be related to the sorption phase and the amount of metal onto kaolinite. The reflectance spectrum of each metal on kaolinite could be identified in VIS-NIR region.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.197-205
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• 2004

Wetlands are lands with a mixture of water, herbaceous or woody vegetation and wet soil. And linear spectral mixture analysis (LSMA) is one of the most often used methods in handling the spectral mixture problem. This study aims to test LSMA is an enhanced routine for classification of wetland land-covers in Paldang reservoir and vicinity (paldang Reservoir) using Landsat TM and ETM+ imagery. In the LSMA process, reference endmembers were driven from scatter-plots of Landsat bands 3, 4 and 5, and a series of endmember models were developed based on green vegetation (GV), soil and water endmembers which are the main indicators of wetlands. To consider phenological characteristics of Paldang Reservoir, a soil endmember was subdivided into bright and dark soil endmembers in spring and a green vegetation (GV) endmember was subdivided into GV tree and GV herbaceous endmembers in fall. We found that LSMA fractions improved the classification accuracy of the wetland land-cover. Four endmember models provided better GV and soil discrimination and the root mean squared (RMS) errors were 0.011 and 0.0039, in spring and fall respectively. Phenologically, a fall image is more appropriate to classify wetland land-cover than spring's. The classification result using 4 endmember fractions of a fall image reached 85.2 and 74.2 percent of the producer's and user's accuracy respectively. This study shows that this routine will be an useful tool for identifying and monitoring the status of wetlands in Paldang Reservoir.

• Journal of Microbiology and Biotechnology
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• v.16 no.11
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• pp.1661-1677
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• 2006

Rhizobium and related genera are soil bacteria with great metabolic plasticity. These microorganisms survive in many different environments and are capable of eliciting the formation of nitrogen-fixing nodules on legumes. The successful establishment of symbiosis is precisely regulated and requires a series of signal exchanges between the two partners. Quorum sensing (QS) is a prevalent form of population density-dependent gene regulation. Recently, increasing evidence indicates that rhizobial quorum sensing provides a pervasive regulatory network, which plays a more generalized role in the physiological activity of free-living rhizobia, as well as during symbiosis. Several rhizobia utilize multiple, overlapping quorum sensing systems to regulate diverse properties, including conjugal transfer and copy number control of plasmids, exopolysaccharide biosynthesis, rhizosphere-related functions, and cell growth. Genomic and proteomic analyses have begun to reveal the wide range of functions under quorum-sensing control.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1935-1943
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• 2022

The development and application of a high-resolution soil moisture mapping method using satellite imagery has been considered one of the major research themes in remote sensing. In this study, soil moisture mapping in the test area of Jeju Island was performed. The soil moisture was calculated with optical images using linearly adjusted Synthetic Aperture Radar (SAR) polarization images and incident angle. SAR Backscatter data, Analysis Ready Data (ARD) provided by Google Earth Engine (GEE), was used. In the soil moisture processing process, the optical image was applied to normalized difference vegetation index (NDVI) by surface reflectance of KOMPSAT-3 satellite images and the land cover map of Environmental Systems Research Institute (ESRI). When the SAR image and the optical images are fused, the reliability of the soil moisture product can be improved. To validate the soil moisture mapping product, a comparative analysis was conducted with normalized difference water index (NDWI) products by the KOMPSAT-3 image and those of the Landsat-8 satellite. As a result, it was shown that the soil moisture map and NDWI of the study area were slightly negative correlated, whereas NDWI using the KOMPSAT-3 images and the Landsat-8 satellite showed a highly correlated trend. Finally, it will be possible to produce precise soil moisture using KOMPSAT optical images and KOMPSAT SAR images without other external remotely sensed images, if the soil moisture calculation algorithm used in this study is further developed for the KOMPSAT-5 image.

• Agricultural and Biosystems Engineering
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• v.6 no.2
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• pp.39-46
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• 2005

Because soil compaction is a concern in crop production and environmental pollution, quantification and management of spatial and vertical variability in soil compaction for soil strength) would be a useful aspect of site -specific field management. In this paper, a soil strength profile sensor (SSPS) that could take measurements continuously while traveling across the field was developed and the performance was evaluated through laboratory and field tests. The SSPS obtained data simultaneously at 5 evenly spaced depths up to 50 em using an array of load cells, each of which was interfaced with a soil-cutting tip. Means of soil strength measurements collected in adjacent, parallel transects were not significantly different, confirming the repeatability of soil strength sensing with the SSPS. Maps created with sensor data showed spatial and vertical variability in soil strength. Depth to the restrictive layer was different for different field locations, and only 5 to 16% of the tested field areas were highly compacted.

• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.28-33
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• 2003

Achievements in the real-time soil spectro-photometer are: an improved soil penetrator to ensure a uniform soil surface under high speed conditions, real-time collecting of underground soil reflectance, getting underground soil color images, use of a RTK-GPS, and all units are arranged for compactness. With the soil spectrophotometer, field experiments were conducted in a 0.5 ha paddy field. With the original reflectance, averaging and multiple scatter correction, Kubelka-Munk (KM) transformation as soil absorption, its 1st and 2nd derivatives were calculated. When the spectra was highly correlated with the soil parameters, stepwise regression analysis was conducted. Results include the best prediction models for moisture, soil organic matter (SOM), nitrate nitrogen (NO$_3$-N), pH and electric conductivity (EC), and soil maps obtained by block kriging analysis.

• Korean Journal of Remote Sensing
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• v.13 no.2
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• pp.151-163
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• 1997

In this paper, an algorithm for retrieving soil moisture from measurement of microwave reflection at the end of a coaxial canble is presented. Because the wave reflection from the boundary between air and soil layers depends on the dielectric constant of the soil layer, the dielectric constant can be obtained from measured reflection coefficient. At first, an equivalent circuit for the coaxial probe contaced on the soil surface was chosen with two unknown circuit elements. Then, the unknown circuit elements are obtained experrmentally by measuring the reflection constants of 20 soil samples, and consequently, an empirical formula for computing the dielectric constant from the reflection coefficient is obtained. The dielectric constant is mainly influenced by the soil moisture, and the soil moisture can be computed from the dielecfic constant using an existing empirical formula. HP Network Analyzer 8510C was used to measure the magnitude and the phase of the reflection coeffcient at 4.65 GHz, and the measured data set were used to obtain an empirical formula for computing the dielectric constant. The empirical formula obtained in this study was proven by other soil samples.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.175-188
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• 2004

The objectives of this study were to estimate leaf area index (LAI) as a function of image-derived vegetation indices, and to compare measured and estimated LAI to the results of crop model simulation. Soil moisture, crop phenology, and LAI data were obtained several times during the 2001 growing season at monitoring sites established in two central Missouri experimental fields, one planted to com (Zea mays L.) and the other planted to soybean (Glycine max L.). Hyper- and multi-spectral images at varying spatial. and spectral resolutions were acquired from both airborne and satellite platforms, and data were extracted to calculate standard vegetative indices (normalized difference vegetative index, NDVI; ratio vegetative index, RVI; and soil-adjusted vegetative index, SAVI). When comparing these three indices, regressions for measured LAI were of similar quality $(r^2$ =0.59 to 0.61 for com; $r^2$ =0.66 to 0.68 for soybean) in this single-year dataset. CERES(Crop Environment Resource Synthesis)-Maize and CROPGRO-Soybean models were calibrated to measured soil moisture and yield data and used to simulate LAI over the growing season. The CERES-Maize model over-predicted LAI at all corn monitoring sites. Simulated LAI from CROPGRO-Soybean was similar to observed and image-estimated LA! for most soybean monitoring sites. These results suggest crop growth model predictions might be improved by incorporating image-estimated LAI. Greater improvements might be expected with com than with soybean.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.664-667
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• 2004

This paper is aimed at analyzing the soil erosion hazard zone in farm land. RUSLE was used for an analysis of soil erosion amount, and for the spatial data of basin, soil erosion amount was calculated by extracting the respect topography space related factors of RUSLE using DEM, Landuse, Soil map as base map. As a result of analysis on the calculated soil erosion amount according to land use type, it was analyzed that the most soil erosion occurred in orchard area, i.e., 40.08ton/ha/yr at average. It was classified into 5 classes depending on the calculated soil erosion amount. of which Class V was decided as soil erosion hazard zone, and for this area, 72.5ha or so, $2.4\%$ of the entire farm land was assessed as erosion hazard zone.