• Korean Journal of Remote Sensing
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• v.30 no.3
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• pp.375-381
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• 2014

Soil moisture is an essential satellite-driven variable for understanding hydrologic, pedologic and geomorphic processes. The European Space Agency (ESA) has endorsed soil moisture as one of Climate Change Initiates (CCI) and had merged multi-satellites over 30 years. The $0.25^{\circ}$ coarse resolution soil moisture satellite data showed correlations with variables of a water stress index, Temperature-Vegetation Dryness Index (TVDI), from a stepwise regression analysis. The ancillary data from TVDI, Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) from MODIS were inputted to a multi-regression analysis for estimating the surface soil moisture. The estimated soil moisture was validated with in-situ soil moisture data from April, 2012 to March, 2013 at Andong observation sites in South Korea. The soil moisture estimated using satellite-based LST and NDVI showed a good agreement with the observed ground data that this approach is plausible to define spatial distribution of surface soil moisture.

• Agricultural and Biosystems Engineering
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• v.5 no.1
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• pp.10-20
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• 2004

Precision agriculture aims to minimize costs and environmental damage caused by agriculture and to maximize crop yield and profitability, based on information collected at within-field locations. In this process, quantification of soil physical properties, including soil strength, would be useful. To quantify and manage variability in soil strength, there is need for a strength sensor that can take measurements continuously while traveling across the field. In this paper, preliminary analyses were conducted using two datasets available with current technology, (1) cone penetrometer readings collected at different compaction levels and for different soil textures and (2) tillage draft (TD) collected from an entire field. The objective was to provide information useful for design of an on-the-go soil strength profile sensor and for interpretation of sensor test results. Analysis of cone index (CI) profiles led to the selection of a 0.5-m design sensing depth, 10-MPa maximum expected soil strength, and 0.1-MPa sensing resolution. Compaction level, depth, texture, and water content of the soil all affected CI. The effects of these interacting factors on data obtained with the soil strength sensor should be investigated through experiments. Spatial analyses of CI and TD indicated that the on-the-go soil strength sensor should acquire high spatial-resolution, high-frequency ($\ge$ 4 Hz) measurements to capture within-field spatial variability.

• Korean Journal of Soil Science and Fertilizer
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• v.36 no.2
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• pp.92-103
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• 2003

Research and technological advances in the field of remote sensing have greatly enhanced the ability to detect and quantify physical and biological stresses that affect the productivity of agricultural crops. Reflectance in specific visible and near-infrared regions of the electromagnetic spectrum have proved useful in detection of nutrient deficiencies. Especially crop canopy sensors as a ground remote sensing measure the amount of light reflected from nearby surfaces such as leaf tissue or soil and is in contrast to aircraft or satellite platforms that generate photographs or various types of digital images. Multi-spectral vegetation indices derived from crop canopy reflectance in relatively wide wave band can be used to monitor the growth response of plants in relation to environmental factors. The normalized difference vegetation index (NDVI), where NDVI = (NIR-Red)/(NIR+Red), was originally proposed as a means of estimating green biomass. The basis of this relationship is the strong absorption (low reflectance) of red light by chlorophyll and low absorption (high reflectance and transmittance) in the near infrared (NIR) by green leaves. Thereafter many researchers have proposed the other indices for assessing crop vegetation due to confounding soil background effects in the measurement. The green normalized difference vegetation index (GNDVI), where the green band is substituted for the red band in the NDVI equation, was proved to be more useful for assessing canopy variation in green crop biomass related to nitrogen fertility in soils. Consequently ground remote sensing as a non destructive real-time assessment of nitrogen status in plant was thought to be useful tool for site specific crop nitrogen management providing both spatial and temporal information.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.3-12
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• 2009

Soil is one of the Earth's most important resources. There are many differences among the soils of plains.like and hilly terrains, and therefore, accurate and comprehensive information on soil is essential for optimum and sustainable soil utilization. However, information on the soil of the hilly terrains of the Eastern Ghats of Tamil Nadu, India, is limited or absent. In the present study, Kolli hill, one among the hills of the Eastern Ghats, was soil.inventoried and mapped using a ground survey and remote sensing. Soil samples were collected and their physico.chemical properties analyzed according to the United States Department of Agriculture (USDA) standards. The soils were classified up to the family level. As a result of this study, 30 soil series belonging to ten sub.groups of five great groups and three sub.orders and orders each, were identified (classified to the family level) and mapped. Entisols, Inseptisols and Alfisols were the three orders, among which Entisols was the major one, occupying 75% of the area. Among the five great groups, Ustorthents occupied majority of the area (73%). Lithic Ustorthents and Typic Ustorthents were the two major sub.groups, occupying 40% and 26% of the total area, respectively. The present soil resource mapping of the Eastern Ghats of Tamil Nadu is a pioneer study, which yielded valuable information on the soil in this region.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.684-695
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• 2010

Geographic information system (GIS) is being increasingly used for decision making, planning and agricultural environment management because of its analytical capacity. GIS and remote sensing have been combined with environmental models for many agricultural applications on monitoring of soils, agricultural water quality, microbial activity, vegetation and aquatic insect distribution. This paper introduce principles, vegetation indices, spatial data structure, spatial analysis of GIS and remote sensing in agricultural applications including terrain analysis, soil erosion, and runoff potential. National Academy of Agricultural Science (NAAS), Rural Development Administration (RDA) has a spatial database of agricultural soils, surface and underground water, weeds, aquatic insect, and climate data, and established a web-GIS system providing spatial and temporal variability of agricultural environment information since 2007. GIS-based interactive mapping system would encourage researchers and students to widely utilize spatial information on their studies with regard to agricultural and environmental problem solving combined with other national GIS database. GIS and remote sensing will play an important role to support and make decisions from a national level of conservation and protection to a farm level of management practice in the near future.

• Microbiology and Biotechnology Letters
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• v.41 no.1
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• pp.105-111
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• 2013

Biofilm formation of multifunctional plant growth promoting rhizobacterium (PGPR), Pseudomonas fluorescens 2112 is necessary for P. fluorescens 2112 to have a positive impact on the rhizosphere of red-pepper. This study investigated whether signal molecules of the quorum sensing AHLs are produced in order to confirm biofilm formative ability. Through the use of Petri dish bioassays a blue circle formed evidence of AHLs. It was confirmed that P. fluorescens 2112 produced six-carbon-chain-long AHLs by TLC bioassay. The bacterial density of P. fluorescens 2112 on the top and bottom of pepper plant roots was estimated as $3{\times}10^5$ and $8{\times}10^3$ CFU/g root, respectively. P. fluorescens 2112 exist more with high-density of $3.5{\times}10^6$ CFU/g soil at a depth of 1 cm but at a low-density of $1.1{\times}10$ CFU/g soil at a depth of 5 cm, from the surface of rhizosphere soil. In addition, biofilm formation of P. fluorescens 2112 on the epidermises and the tips of the red-pepper roots were confirmed visually by SEM. Thus, the production of AHLs by P. fluorescens 2112 brings about quorum sensing signaling and the formation of biofilm on the roots which has a positive effect on economically important crops such as red-pepper by additionally producing a variety of antifungal substances and auxin.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.59-64
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• 2010

The second satellite in ESA's Earth Explorer series, the Soil Moisture and Ocean Salinity (SMOS) mission was launched into orbit at November 1, 2009. The SMOS will play a key role in the monitoring of climate change on a global scale using the payload of L-band synthetic aperture radiometer. It is the first ever satellite designed both to map sea surface salinity and to monitor soil moisture on a global scale, and will provide the important data to study the water cycle among oceans, the atmosphere and land. To introduce the operation of the SMOS, this paper shows brief summary of appearance and current operation.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.319-322
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• 1999

Land surface hydrological conditions have been considered to play an important role in the global and regional climate variability. Especially, snow, soil moisture, surface temperature, vegetation and rain are the key parameters which should be observed in the global scale. In this paper, new algorithms for these land surface hydrological parameters have been developed by introducing frequency and polarization dependencies of these parameters in the microwave radiative-transfer equations. The algorithms were applied to the TRMM Microwave Radiometer. (TMI) and validated by using the ground data obtained in the Tibetan Plateau. The estimated snow, soil moisture, surface temperature, water content of vegetation and rain patterns corresponded reasonably to the observed ones.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.3
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• pp.535-542
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• 1994

Remote sensing technique is based on the estimation of land surface characteristics from the measurement of the emitted radiation from the earth. The hydrologically related parameters studied using this approach include surface temperature, evapotranspiration, soil moisture, precipitation and snow. This study introduces a method for estimating moisture content of a bare soil from the observed and simulated brightness temperature. In a bare soil, microwave emission depends on moisture content, soil temperature, and surface roughness. The method is based on a radiative transfer model with some modifications of Fresnel reflection coefficient to take into account the effect of surface roughness. One smooth bare field and two fields with different surface roughness are prepared for the study. The results indicate that the effect of surface roughness is to increase the soil's brightness temperature and to reduce the slope of regression between brightness temperature and moisture contents.

• Journal of Korean Society of Rural Planning
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• v.10 no.1 s.22
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• pp.19-26
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• 2004

In this paper, forestry area change effect on the soil erosion in Asan lake watershed was estimated. Temporal variations of land use in the study watershed were analyzed from Landsat-5 TM remote sensing images. Geographic Information System (GIS) combined with Universal Soil Loss Equation (USLE) was used to estimate the soil erosion of Asan lake watershed. Spatial data for each USLE factors was obtained from the Landsat-5 TM remote sensing images and 1/25,000 scale digital contour maps. Sediment yield to Asan lake was estimated by sediment delivery ratio and sediment accumulation in lake was estimated by trap efficiency. The estimation methods were validated for sediment accumulation in Asan lake. From the hydrographic survey from 1974 to 2003 for Asan lake, sediment accumulation was measured. The estimated accumulation sediment of 303,569ton/yr showed similar value with observed of 295,888ton/yr. From the validated estimation methods, the increasing amount of soil erosion when 1% of forest area in Asan lake watershed decreases was calculated from 12.91 to 1482.05ton/yr.