• Journal of Biosystems Engineering
• /
• v.43 no.2
• /
• pp.148-159
• /
• 2018

Purpose: Unmanned air vehicle (UAV) remote sensing was applied to test various vegetation indices and make prediction models of protein content of rice for monitoring grain quality and proper management practice. Methods: Image acquisition was carried out by using NIR (Green, Red, NIR), RGB and RE (Blue, Green, Red-edge) camera mounted on UAV. Sampling was done synchronously at the geo-referenced points and GPS locations were recorded. Paddy samples were air-dried to 15% moisture content, and then dehulled and milled to 92% milling yield and measured the protein content by near-infrared spectroscopy. Results: Artificial neural network showed the better performance with $R^2$ (coefficient of determination) of 0.740, NSE (Nash-Sutcliffe model efficiency coefficient) of 0.733 and RMSE (root mean square error) of 0.187% considering all 54 samples than the models developed by PR (polynomial regression), SLR (simple linear regression), and PLSR (partial least square regression). PLSR calibration models showed almost similar result with PR as 0.663 ($R^2$) and 0.169% (RMSE) for cloud-free samples and 0.491 ($R^2$) and 0.217% (RMSE) for cloud-shadowed samples. However, the validation models performed poorly. This study revealed that there is a highly significant correlation between NDVI (normalized difference vegetation index) and protein content in rice. For the cloud-free samples, the SLR models showed $R^2=0.553$ and RMSE = 0.210%, and for cloud-shadowed samples showed 0.479 as $R^2$ and 0.225% as RMSE respectively. Conclusion: There is a significant correlation between spectral bands and grain protein content. Artificial neural networks have the strong advantages to fit the nonlinear problem when a sigmoid activation function is used in the hidden layer. Quantitatively, the neural network model obtained a higher precision result with a mean absolute relative error (MARE) of 2.18% and root mean square error (RMSE) of 0.187%.

• Korean Journal of Heritage: History & Science
• /
• v.49 no.4
• /
• pp.52-63
• /
• 2016

The Stupa of Buddhist Monk Soyo in Baegyangsa temple, Jangseong, was erected to pay a tribute to the achievement of the Buddhist monk Soyo, who worked for Baegyangsa temple as a chief monk, and is a bellshaped stupa with the detailed pattern of a Korean traditional buddhist bell. It is composed of pinkish-grey sandstone and the body of the stupa was damaged by longitudinal cracks on the front and back areas and the exfoliation caused break-out in the most part of the sculpture on the left and right areas. According to the ultrasonic test and infrared thermography analysis for physical deterioration diagnosis, most weathering aspects appeared on the body of the stupa and some exfoliated part that could not be seen with the naked eye was detected 6.1% and 5.9% on the left and right side respectively. Hyperspectral imaging analysis was also carried out to assess biological deterioration. According to the result, the surface of the stupa was covered 71.8 ~ 79.9% with vegetation like algae, lichen and moss. NDVI(Normalized Difference Vegetation Index) was higher relatively on the bottom part near the ground, right and back areas of the stupa. Therefore conservation treatment for the exfoliated part and bio-deterioration is necessary and the environment condition needs to be fixed to prevent extra damages on the stupa.

• The Journal of Engineering Geology
• /
• v.9 no.2
• /
• pp.161-176
• /
• 1999

The objectives of this study are to analyze the changes of geo-surface topography in the Siwha embankment and the Ahsan city area by the image processing of Landsat Thematic Mapper data, and to estimate the reclaimed amount of the exposed tidal flat in the Siwha area using the GIS. False color composite, Tasseled cap, NVDI(normalized difference vegetation index), and supervised classification techniques were used to analyze the distribution of sediments and the aspect of topographical variations caused by artificial human actions. The total amount of the exposed tidal flat was estimated on the basis of the database snch as aerial photography, hydrographic chart, geological map, and scheme drawing in the Siwha area. The possible excavation regions for a seawall were predicted analyzing the supervised classification image of Landsat TM data. Tasseled cap images were used to observe the distribution of sediments. The difference of the NDVI images between spring and summer seasons indicates that deciduous and coniferous forests were distributed over the whole areas. The total fill-volume of the exposed Siwha tidal flat and the fill-volume of the construction planning seawall were calculated as $581,485,354\textrm{m}^3{\;}and{\;}3,387,360\textrm{m}^3$, respectively, from the digital terrain analysis. Daebu Island, Sunkam Island, and the part of Songsan-myeon were chosen as the cut area to make the seawall, and their cut-volumes were estimated as $5,229,576\textrm{m}^3,{\;}79,227,072\textrm{m}^3,{\;}and{\;}47,026,008\textrm{m}^3$, respectively. Therefore, the cut-volume of Daebu Island alone among three areas was sufficient to make the seawall.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_2
• /
• pp.1723-1735
• /
• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.23 no.3
• /
• pp.26-67
• /
• 2020

Synthetic Aperture Radar(SAR) is able to photograph the earth's surface regardless of weather conditions, day and night. Because of its possibility to search for hydrological factors such as soil moisture and groundwater, and its importance is gradually increasing in the field of water resources. SAR began to be mounted on satellites in the 1970s, and about 15 or more satellites were launched as of 2020, which around 10 satellites will be launched within the next 5 years. Recently, various types of SAR technologies such as enhancement of observation width and resolution, multiple polarization and multiple frequencies, and diversification of observation angles were being developed and utilized. In this paper, a brief history of the SAR system, as well as studies for estimating soil moisture and hydrological components were investigated. Up to now hydrological components that can be estimated using SAR satellites include soil moisture, subsurface groundwater discharge, precipitation, snow cover area, leaf area index(LAI), and normalized difference vegetation index(NDVI) and among them, soil moisture is being studied in 17 countries in South Korea, North America, Europe, and India by using the physical model, the IEM(Integral Equation Model) and the artificial intelligence-based ANN(Artificial Neural Network). RADARSAT-1, ENVISAT, ASAR, and ERS-1/2 were the most widely used satellite, but the operation has ended, and utilization of RADARSAT-2, Sentinel-1, and SMAP, which are currently in operation, is gradually increasing. Since Korea is developing a medium-sized satellite for water resources and water disasters equipped with C-band SAR with the goal of launching in 2025, various hydrological components estimation researches using SAR are expected to be active.

• Weed & Turfgrass Science
• /
• v.4 no.3
• /
• pp.268-277
• /
• 2015

Organic fertilizer preparation was developed with organic materials to improve growth and qualities of cool-season turfgrass species. Organic fertilizer preparation were contained with essential macronutrient elements and organic matter for growth of cool season turfgrass. Four preparations of organic fertilizers were tested on creeping bentgrass (Agrostis palustris Huds) cultivar Penn-A1 and Kentucky bluegrass (Poa pratensis L.) mixed cultivars (Midnight 33%, Moonlight 33%, and Prosperity 33%) by one time application on fifty days after sowing. Two species of cool season turfgrasses were evaluated on turfgrass coverage, growth on NDVI (Normalized Difference Vegetation Index) and qualities from fall season to spring season in sod producing farm. It were found significantly difference found on turfgrass coverage, turf color, chlorophyll contents and growth increase on two species of cool season turfgrasses. Turfgrass coverage, chlorophyll content, turf color and growth increase of organic fertilizer preparation were significantly increased on creeping bentgrass cultivar and Kentucky bluegrass mixed cultivar for six time investigation in spring season. These results may indicate that the use of some preparation is beneficial for sod producing sod and turfgrass management.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.20 no.1
• /
• pp.135-143
• /
• 2018

The effect of elevated temperature on temperate paddy rice will be significant for dependable food supply in East Asia. Using temperature gradient field chamber (TGFC), which was designed to make the horizontal air temperature gradient by $0^{\circ}C$ to $3^{\circ}C$ higher than outside, we examined the measurement to understand the effects of extremely high temperature on paddy rice. In particular, the data of the year 2016, the worst heat wave in over 22 years, was analyzed in this study. The rice height in the relatively warmed condition was rapidly increased during early growth stage. However, the average grain weight and number of spikelet per panicle in the warmed chamber condition were gradually declined with increasing air temperature averaged for 40 days after first heading in each chamber. In particular, the grain yield was more dramatically decreased by the raising temperature because the percent ripened grain was quickly dropped as getting over the threshold temperature for pollination. Therefore, the surplus photosynthetic product by such lower grain filling rate may disturbed the decreases of the NDVI (Normalized Difference Vegetation Index) and SPAD chlorophyll values after first (normal) heading. In addition, the late-emerging head grain were appeared. However, this yield was too small to recover the normal yields decreased by extremely high temperature condition. Our result represented that the warmed condition in 2016 would be the critical limit for the stable yield of temperate paddy rice.

• Asian Journal of Turfgrass Science
• /
• v.25 no.2
• /
• pp.147-152
• /
• 2011

This study was conducted to evaluate the growth characteristics of creeping bentgrass cultivars for fairway of golf course at Yeoju area in Korea. At germination and coverage rate of creeping bentgrass, 'Shark' and 'CY-2' were excellent, 'L-93', 'Alpha', 'T-1 was in order', respectively. Visual qualities of 'Shark' and 'CY-2' also were excellent. Especially, 'Shark', 'T-1', and 'CY-2' showed excellent visual quality in summer days, the critical times for the bentgrass fairway quality. 'Shark', 'CY-2' and 'T-1' were excellent in Chlorophyll contents throughout the evaluation period. Chlorophyll content of 'T-1' was maintained very high in summer. 'CY-2' and 'Shark' showed the best root growth at the beginning of the study and contained longer and hairy roots. Which might make these two cultivars' water absorption easier than other's. NDVI (normalized difference vegetation index)of 'Shark', 'L-93' and 'CY-2' was excellent, respectively. 'T-1' showed the highest density and 'Shark', 'CY-2', 'Alpha', 'L-93' was followed by. The density of 'T-1' was rather increased in summer season, while those of other cultivars were decreased. Three diseases such as anthracnose, brown patch, and dollar spot, were appeared during the evaluation period. 'T-1' and 'L-93' were very sensitive to anthracnose which occurred at the beginning days of the study. The most susceptible cultivars to brown patch were 'Alpha' and 'L-93'. 'T-1' was the least resistant to dollar spot which occurred at the same time with brown patch.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.14 no.2
• /
• pp.82-95
• /
• 2011

The objective of this paper is to analyze the GIS-based water cycle system: rainfall, evapotranspiration, surface run-off of Gyeongsanam-do for the effective rainwater management. The rainfall(1999~2008) analyzed by a spatial interpolation method, showed relatively higher amount in Hadong-gun, Sanchung-gun, and Sacheon-gun on the southwest coast than in Changnyeong-gun, Miryang-si, and Changwon-si in the mideast inland. The evapotranspiration was calculated by the three independent variables: air temperature, landuse, and NDVI(normalized difference vegetation index). The analysis showed that Namhae-gun had the highest evapotranspiration of 93.71mm, and Jinhae-si and Changwon-si had the lowest values of 81.78mm and 84.37mm. The surface run-off was analysed by a run-off equation based on the SCS hydrologic soil classification and landuse. The amount of surface run-off showed that Hadong-gun had the highest value, of 90.40mm, and Geochang-gun had the lowest, of 46.69mm. The analysis results of the GIS-based water cycle system will be used to support the establishment of the effective rainwater management plan in Gyeongasngnam-do.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_1
• /
• pp.599-608
• /
• 2023

The increasing interest in soil moisture data using satellite data for applications of hydrology, meteorology, and agriculture has led to the development of methods for generating soil moisture maps of variable resolution. This study demonstrated the capability of generating soil moisture maps using Sentinel-1 and Sentinel-2 data provided by Google Earth Engine (GEE). The soil moisture map was derived using synthetic aperture radar (SAR) image and optical image. SAR data provided by the Sentinel-1 analysis ready data in GEE was applied with normalized difference vegetation index (NDVI) based on Sentinel-2 and Environmental Systems Research Institute (ESRI)-based Land Cover map. This study produced a soil moisture map in the research area of Victoria, Australia and compared it with field measurements obtained from a previous study. As for the validation of the applied method's result accuracy, the comparative experimental results showed a meaningful range of consistency as 4-10%p between the values obtained using the algorithm applied in this study and the field-based ones, and they also showed very high consistency with satellite-based soil moisture data as 0.5-2%p. Therefore, public open data provided by GEE and the algorithm applied in this study can be used for high-resolution soil moisture mapping to represent regional land surface characteristics.