• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1185-1193
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• 2023

The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

• Journal of Biosystems Engineering
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• v.12 no.3
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• pp.1-6
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• 1987

The objective of this study is to develop a soil hardness tester which can estimate tillage resistance with tae travelling cone-penetrometer. For the study, a series of tests was performed using the cone penetrating in the horizontal direction. Based on the tests above, soil hardness was represented by travelling cone-index vs depth of cone penetration, travelling speed and moisture contents of the soil Resistance characteristics obtained from the experiments were compared with those by a vertical cone-penetrometer and the Yamanaka's soil hardness tester. Following conclusions were made from the study. 1. 8 to 9 peaks per one meter were detected in the resistance curve of cone penetration regardless of the travelling speed of cone-penetrometer when it penetrated the soil in the horizontal direction. This phenomenon seemed to be a similar one noticed in shearing pitch of plowing. 2. Cone index increased as travelling speed increased from 0.08m/sec to 0.5m/sec. 3. Linear relationship was found between the cone indices measured by the travelling coe-penetrometer and Yamanaka's hardness tester. 4. Increasing rate of the cone indices measured by vertical cone-penetrometer decreased as the depth of soil increased while the cone indices by the travelling cone-pentrometer increased linearly.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.183-197
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• 2006

Combinations of visible and near-infrared (NIR) bands in an image are widely used for estimating vegetation vigor and productivity. Using this approach to understand within-field grain crop variability could allow pre-harvest estimates of yield, and might enable mapping of yield variations without use of a combine yield monitor. The objective of this study was to estimate within-field variations in crop yield using vegetation indices derived from hyperspectral images. Hyperspectral images were acquired using an aerial sensor on multiple dates during the 2003 and 2004 cropping seasons for corn and soybean fields in central Missouri. Vegetation indices, including intensity normalized red (NR), intensity normalized green (NG), normalized difference vegetation index (NDVI), green NDVI (gNDVI), and soil-adjusted vegetation index (SAVI), were derived from the images using wavelengths from 440 nm to 850 nm, with bands selected using an iterative procedure. Accuracy of yield estimation models based on these vegetation indices was assessed by comparison with combine yield monitor data. In 2003, late-season NG provided the best estimation of both corn $(r^2\;=\;0.632)$ and soybean $(r^2\;=\;0.467)$ yields. Stepwise multiple linear regression using multiple hyperspectral bands was also used to estimate yield, and explained similar amounts of yield variation. Corn yield variability was better modeled than was soybean yield variability. Remote sensing was better able to estimate yields in the 2003 season when crop growth was limited by water availability, especially on drought-prone portions of the fields. In 2004, when timely rains during the growing season provided adequate moisture across entire fields and yield variability was less, remote sensing estimates of yield were much poorer $(r^2<0.3)$.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.3
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• pp.161-170
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• 2013

Spatio-temporal distribution of soil moisture was studied to improve understanding of hydrological processes at hillslope scale. Using field measurements for three designated periods during the spring, summer and autumn seasons in 2010 obtained from Beomryunsa hillslope located at the Sulmachun watershed, correlation analysis was performed between soil moisture measurements and 18 different terrain attributes (e.g., curvatures and topographic index). The results of correlation analysis demonstrated distinct seasonal variation features of soil moisture in different depths with different terrain attributes and rainfall amount. The relationship between predicted flow lines and distribution of the soil moisture provided appropriate model structures and terrain indices.

• Food Engineering Progress
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• v.15 no.2
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• pp.148-154
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• 2011

The objective of this study was to determine the effect of die geometry on expansion index of extruded corn flour. Water solubility index, water absorption index and specific mechanical energy (SME) input were analyzed to observe the relationship with die geometry. The feed moisture content was 20 and 25%. Die dimensions were tapered angle (57, 95o) and length/diameter (L/D) ratio of die land (0.67, 1.67 and 2.67). The SME input was the highest at 20% moisture content and 2.23E-10 m3 die constant. The sectional and volumetric expansion indices at 20% moisture were increased with increase in die constant. However, die constant did not influence sectional expansion index of corn flour extrudate at 25% moisture content. The extruded corn flour at 25% moisture content had higher longitudinal expansion index than those of extruded corn flour at 20% moisture content. Sectional expansion and longitudinal expansion index were negatively correlated. The water absorption index and water solubility index were not affected with the die constant.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.6-12
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• 2010

일반적으로 가뭄은 기상학적 가뭄, 농업적 가뭄, 수문학적 가뭄의 유형 등으로 분류한다. 본 연구에서는 우리나라에 적합한 수문학적 가뭄 지수인 물가용지수(Water Availability Index)를 개발하였다. 또한 다각적인 가뭄평가를 위해 기상학적 가뭄의 평가할 수 있는 표준강수지수(Standard Precipitation Index)와 농업적 가뭄을 평가할 수 있는 토양수분지수(Soil Moisture Index) 그리고 개발한 물가용지수(Water Availability Index)를 지수의 가뭄에 대한 등급을 통일시키기 위해 새롭게 산정하였다. 또한 기상청에서 제시하고 있는 월간기상정보 자료를 이용하여 가뭄전망을 할 수 있는 기법을 개발하였다.

• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

• Journal of Korea Water Resources Association
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• v.53 no.4
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• pp.285-291
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• 2020

The Noah 3.3 Land Surface Model (LSM) was used to estimate the global soil moisture in this study and these soil moisture datasets were assessed against satellite-based and reanalysis soil moisture products. The Noah 3.3 LSM simulated soil moistures in four soil layers and root-zone soil moistures defined as a depth-weighted average in the first three soil layers (i.e., up to 1.0 m deep). The Noah LSM soil moisture products were then compared with a satellite-based soil moisture dataset (European Space Agency Climate Change Initiatives (ESA CCI) SM v04.4) and reanalysis soil moisture datasets (ERA-interim). In addition, the five major basins (Yangtze, Mekong, Mississippi, Murray-Darling, Amazon) were selected for the assesment with the Gravity Recovery and Climate Experiment (GRACE)-based Total Water Storage Anomaly (TWSA) and TWS Change (TWSC). The results revealed that high anomaly correlations were found in most of the Asia-Pacific regions including East Asia, South Asia, Australia, and Noth and South America. While the anomaly correlations in the Murray-Darling basin were somewhat low, relatively higher anomaly correlations in the other basins were found. It is concluded that this study can be useful for the development of soil moisture based drought indices and subsequently can be helpful to reduce damages from drought by timely providing an efficacious strategy.

• Journal of Aquaculture
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• v.17 no.3
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• pp.228-232
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• 2004

This study evaluates red seabream quality using physicochemical and chemoenzymatic indices. Breaking strength was correlated with moisture content and lipid content of red seabram by a precedent experiment. Moisture content (X$_1$), lipid content (X$_2$) and breaking strength (Y) were optimized with multiple regression as, Y= -2.53539＋0.05544X$_1$-0.00161X$_2$. To test the equation, red seabream (n=13) were randomly purchased and measured moisture content, lipid content and breaking strength. The calculated breaking strength using the equation was similar to breaking strength measured using Rheo meter. Adenylate energy charge (AEC), a general biochemical index of stress, values of all sample were higher than 0.8 expect two fish. Fish's condition was a good. The equation developed in this study predicts breaking strength with moisture and lipid content measured. Moreover the equation may be used in grading cultured red seabream with calculated breaking strength. Grade according to breaking strength, when it came to over 1.4 kg, was measured as high grade; when it came to below 1.2 kg, was measured as low grade. Grade according to AEC, when it came to over 0.8, was measured as high grade.

• Journal of the Korean Society of Hazard Mitigation
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• v.5 no.4 s.19
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• pp.59-69
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• 2005

Drought is difficult to detect and monitor, but it is easy to interpret through the drought index. The Palmer Drought Severity Index(PDSI), which is most commonly used as one of drought indices, have been widely used, however, the index have limitation as operational tools and triggers for policy responses. Recently, a new index, the Standardized Precipitation Index(SPI), was developed to improve drought detection and monitoring capabilities. The SPI has an improvement over previous indices md has several characteristics including its simplicity and temporal flexibility that allow its application for water resources on all timescales. Keetch-Byram Dought Index(KBDI) was defined as a number representing the net effect of evapotranspiration and precipitation in producing cumulative moisture deficiency in deep duff or upper soil layer. The purpose of this study is to analyze drought in Korea by using PDSI, SPI and KBDI. The result of this study suggests standard drought index by comparing of estimated drought indices. The data are obtained from Korea Meteorological Administration 56 stations over 30 years in each of the 8 sub-basins covering the whole nation. It is found that the PDSI had the advantage to detect the stage of drought resulting from cumulative shortage of rainfall, while SPI and KBDI had the advantage to detect the stage of drought resulting from short-term shortage of rainfall.