• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.109-126
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• 2014

We improved the Land Surface Emissivity (LSE) data (Kongju National University LSE v.2: KNULSE_v2) over the Communication, Ocean and Meteorological Satellite (COMS) observation region using recent(2009-2012) Moderate Resolution Imaging Spectroradiometer (MODIS) data. The surface emissivity was derived using the Vegetation Cover Method (VCM) based on the assumption that the pixel is only composed of ground and vegetation. The main issues addressed in this study are as follows: 1) the impacts of snow cover are included using Normalized Difference Snow Index (NDSI) data, 2) the number of channels is extended from two (11, 12 ${\mu}m$) to four channels (3.7, 8.7, 11, 12 ${\mu}m$), 3) the land cover map data is also updated using the optimized remapping of the five state-of-the-art land cover maps, and 4) the latest look-up table for the emissivity of land surface according to the land cover is used. The updated emissivity data showed a strong seasonal variation with high and low values for the summer and winter, respectively. However, the surface emissivity over the desert or evergreen tree areas showed a relatively weak seasonal variation irrespective of the channels. The snow cover generally increases the emissivity of 3.7, 8.7, and 11 ${\mu}m$ but decreases that of 12 ${\mu}m$. As the results show, the pattern correlation between the updated emissivity data and the MODIS LSE data is clearly increased for the winter season, in particular, the 11 ${\mu}m$. However, the differences between the two emissivity data are slightly increased with a maximum increase in the 3.7 ${\mu}m$. The emissivity data updated in this study can be used for the improvement of accuracy of land surface temperature derived from the infrared channel data of COMS.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.709-720
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• 2018

In order to optimize the evaluation of biomass in crop monitoring, accurate and timely data of the crop-field are required. Evaluating above-ground biomass helps to monitor crop vitality and to predict yield. Unmanned Aerial Vehicle (UAV) imagery are being assessed for analyzing within field spatial variability for agricultural precision management, because UAV imagery may be acquired quickly during critical periods of rapid crop growth. This study reports on the development of remote sensing techniques for evaluating the biomass of winter crop. Specific objective was to develop statistical models for estimating the dry weight of barley and wheat using a Excess Green index ($E{\times}G$) based Vegetation Fraction (VF) and a Crop Surface Model (CSM) based Plant Height (PH) value. As a result, the multiple linear regression equations consisting of three independent variables (VF, PH, and $VF{\times}PH$) and above-ground dry weight provided good fits with coefficients of determination ($R^2$) ranging from 0.86 to 0.99 with 5 cultivars. In the case of the barley, the coefficient of determination was 0.91 and the root mean squared error of measurement was $102.09g/m^2$. And for the wheat, the coefficient of determination was 0.90 and the root mean squared error of measurement was $110.87g/m^2$. Therefore, it will be possible to evaluate the biomass of winter crop through the UAV image for the crop growth monitoring.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.4
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• pp.296-301
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• 2005

This study was conducted to get the basic data on an effect of food waste compost for rock cut-slopese vegetation. Two foreign cool-season grasses and native plants were used for this experiment. Cool-season grasses were Festuca ruba and Lolium perene, Native plants were Amorpha fruticosa, and Indigofera pseudo-tinctoria. Amorpha fruticosa, Indigofera psendo-tinctoria, and Lolium perenne decreased in germination rate and plant height at NaCl concentrations of $0.4\%$ or over suddenly. Festuca rubra occurred to the sudden growth hindrance at NaCl concentrations of $0.2\%$ or over. Amorpha fruticosa and Indigofera pseudo-tinctoria appeared for germination of $45\%$ at all experiment plots. Lolium perenne increased in plant height as trial rate of food waste compost was abundant. Ground cover rate was the highest in Mixture III by $89.3\%$ and was fluctuated from $47.0\%$ after 30 days to $64.1\%$ after 45 days in Mixture 1. Descending order of ground cover rates in 4 treatments was Mixture III, Mixture IV, Mixture II, and Mixture I. As the growth

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Journal of the Korean Geosynthetics Society
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• v.14 no.2
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• pp.71-79
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• 2015

This paper describes vegetation based soil-media hydroseeding measures that have been previously applied as slope revegetation methods show problems such as insufficient binding force, drying, and insufficient organic matter. In particular, in the case of slope faces in regions where scattering is severe, a vicious circle exists in which remarkably low vegetation cover rates and increases in withering rates over time lead to further decreases in vegetation cover rates, which lead to further increases in erosion and scattering. Therefore, in the present study, environment friendly soil stabilizers were applied for resistance against erosion or scattering and engineering evaluations such as long-term immersion tests and flow resistance tests were conducted to determine appropriate mixing ratios. According to the results of long-term immersion tests utilizing environment friendly soil stabilizers and existing greening soil based materials, 100% collapse occurred at 30 hours and 40 days in the case of soil stabilizer mixing ratios of 0% and 2%, respectively. While the original form of the samples remained intact until the experiment was completed in the case of mixing ratios exceeding 4% indicating that 2% or higher soil stabilizer mixing ratios could affect the maintenance of forms even under extreme conditions. In addition, artificial rainfall tests were conducted on 40, 45, and 55 degree slope faces to evaluate the structural stability of vegetation based materials. Flow resistance tests were conducted on soil stabilizer mixing ratios of 0, 4, 8% to evaluate erosion resistance capability. Based on the results of the tests, environment friendly soil stabilizers applied for prevention of scattering or resistance against erosion by rainwater are considered to provide large effects to reduce losses and loss rates showed a tendency of decreasing rapidly when soil stabilizers were mixed.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.211-220
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• 2021

Land Surface Temperature (LST) is one of the useful parameters to diagnose the growth and development of crop and to detect crop stress. Unmanned Aerial Vehicle (UAV)-based LST (LSTUAV) can be estimated in the regional spatial scale due to miniaturization of thermal infrared camera and development of UAV. Given that meteorological variable, type of instrument, and surface condition can affect the LSTUAV, the evaluation for accuracy of LSTUAV is required. The purpose of this study is to evaluate the accuracy of LSTUAV using LST measured at ground (LSTGround) under various meteorological conditions and growth phases of garlic crop. To evaluate the accuracy of LSTUAV, Relative humidity (RH), absolute humidity (AH), gust, and vegetation index were considered. Root mean square error (RMSE) after minimizing the bias between LSTUAV and LSTGround was 2.565℃ under above 60% of RH, and it was higher than that of 1.82℃ under the below 60% of RH. Therefore, LSTUAV measurement should be conducted under the below 60% of RH. The error depending on the gust and surface conditions was not statistically significant (p-value < 0.05). LSTUAV had reliable accuracy under the wind speed conditions that allow flight and reflected the crop condition. These results help to comprehend the accuracy of LSTUAV and to utilize it in the agriculture field.

• Asian Journal of Turfgrass Science
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• v.22 no.1
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• pp.75-84
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• 2008

This study was carried out to examine the effects of cornstarch-based absorbent polymer (CAP) on the growth of cool season turfgrasses in sand-based soil mixture. Kentucky bluegrass + perennial ryegrass mixtures seeded at May 18 in 2006 on sand-based soil mixture. Sand + peat (5%, v/v), sand + CAP $20g{\cdot}m^{-2}$, sand + CAP $20g{\cdot}m^{-2}$ + peat (5%, v/v), and sand + CAP $40g{\cdot}m^{-2}$ + peat (5%, v/v) mixtures were compared. Ground coverage of sand + CAP $20g{\cdot}m^{-2}$ + peat (5%, v/v), and sand + CAP $40g{\cdot}m^{-2}$ + peat (5%, v/v) treatments showed 50% at a month after seeding. But the coverage of sand + peat (5%, v/v), sand + CAP $20g{\cdot}m^{-2}$ resulted in 36.7%. Mixing of CAP with sand was considered to be efficient method for increasing ground coverage as much as peat. Dry weight of turfgrass tiller at sand + CAP $20g{\cdot}m^{-2}$ + peat (5%, v/v), and sand + CAP $40g{\cdot}m^{-2}$ + peat (5%, v/v) were also significantly higher than sand + peat (5%, v/v), sand + CAP $20g{\cdot}m^{-2}$ mixtures at a month after seeding. Soil water retention at the sand + CAP $20g{\cdot}m^{-2}$, sand + CAP $40g{\cdot}m^{-2}$ + peat (5%, v/v) mixing were lower than sand + peat (5%, v/v) and sand + CAP $20g{\cdot}m^{-2}$ + peat (5%, v/v) during the dry periods. From the results, the mixing of CAP with sand is useful to increased ground coverage of kentucky bluegrass and perennial ryegrass.

• Korean journal of applied entomology
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• v.60 no.1
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• pp.115-122
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• 2021

Pollinators are not only crucial for plant reproduction, but also important for crop production. These pollinators are affected by the diversity of plants within orchards. Thus, the study investigated the effect of blooming on the ground cover on pollinator diversity, network, fruiting rates and subsequent apple size during harvest season in apple blooming period. Total ten orchards were selected; Five with ground covered mostly by dandelion while the another five without ground cover. The orchards with dandelion bloom showed 16 pollinator groups and 801 pollination network interaction, while 14 pollinator groups and 589 interaction were found from orchards without ground cover blooms. es. Overall pollinators' abundances were not different. But bumble bees and caliphorid flies were more abundant in orchards with ground cover blooming. There was no significant in fruiting rates, but the apple size was significantly bigger in orchards with ground cover. These results may indicate that blooming on the ground cover during apple flowering season would increase pollinator diversity and influence fruit quality later on in apple orchards, and pose importance of floral diversity for sustainable apple production system.

• Journal of Wetlands Research
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• v.19 no.4
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• pp.470-483
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• 2017

Changes in land cover or land use, such as changes in forest area, can cause changes in water and energy circulation, ultimately affecting overall hydrological cycle including stream flow, evapotranspiration, soil moisture, and base flow. In this study, the changes of the hydrological processes over the past long period were simulated by using large-scale surface hydrologic model along with various soil, land use, vegetation, and meteorological data. For this purpose, this study simulated and evaluated the changes in the hydrological cycle for the past 50 years (1955-2010) in East Asia including China, Japan and South Korea. In particular, this study used the land cover maps which can properly reflect the vegetation condition for each simulation period. As results, the mean runoff ratio of China was estimated to be 47.0% over the entiree period, 62.7% in Japan and 49.4% in South Korea. The mean soil moisture of China was estimated to be 22.2%, 35.6% in Japan and 23.9% in South Korea. Finally, the mean evapotranspiration rate was estimated to be 52.7% in China, 37.3% in Japan and 50.4% in South Korea. Especially, in China, the hydrological cycle was found to be changed very much for the entire simulation period. However, in Japan, the hydrological cycle was found to be very stable for the entire simulation period. The hydrological cycle was also found to become stable mainly due to the stabilization of the vegetation.

• Journal of Korea Water Resources Association
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• v.57 no.6
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• pp.421-435
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• 2024

In April 2023, a wildfire broke out in Gangneung located in the east coast region due to the influence of the Yanggang-local wind. In this study, GIS-based RUSLE(Revised Universal Soil Loss Equation) and SEMMA (Soil Erosion Model for Mountain Areas) were used to evaluate the erosion rate due to vegetation recovery in a small watershed of the Gangneung WUI(Wildland-Urban Interface) fire. The small watershed of WUI fire has a low altitude range of 10-30 m and the average slope of 10.0±7.4° which corresponds to a gentle slope. The soil texture was loamy sand with a high organic content and the deep soil depth. As herbaceous layer regenerated profusely in the gully after the wildfire, the NDVI (Normalized Difference Vegetation Index) reached a maximum of 0.55. Simulation results of erosion rates showed that RUSLE ranged from 0.07-94.9 t/ha/storm and SEMMA ranged from 0.24-83.6 t/ha/storm. RUSLE overestimated the average erosion rate by 1.19-1.48 times compared to SEMMA. The erosion rates were estimated to be high in the middle slope where burned pine trees were widely distributed and the slope was steep and to be relatively low in the hollow below the gully where herbaceous layer recovers rapidly. SEMMA showed a rapid increase in erosion sensitivity under at certain vegetation covers with NDVI below 0.25 (Ic = 0.35) on post-fire hillslopes. Gentle slopes with high organic content and rapid recovery of natural vegetation had relatively low erosion rate compared to steep slopes. As subsequent infrastructure and human damages due to sediment disaster by heavy rain is anticipated in WUI fire areas, the research results may be used as basic data for targeted management and decision making on the implementation of emergency treatment after the wildfire.