• Journal of Food Hygiene and Safety
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• v.36 no.5
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• pp.392-399
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• 2021

This study was conducted to research the status of pesticide residues in a total of 114 herbs and spices obtained from January to October 2020. 341 pesticide residues were analyzed by the multi class pesticide multiresidue methods using GC-MSMS, GC-ECD, GC-NPD, LC-MSMS, LC-PDA, and LC-CAS. As a result of analysis, 36 pesticide residues were found, and detection rate was 31.6%. Of them, seven samples were detected over Maximum Residue Limits (MRLs) and the unsuitable level in pesticide was 6.1%. The herbs and spices exceeding MRLs include coriander (2 times), mint (2 times), basil (once), rosemary (once), and boraye (once). According to an analysis of 341 pesticide residues, 22 pesticides were detected 52 times and 8 pesticides were found to exceed the MRLs. The pesticides exceeding MRLs were ingredients such as etofenprox, flufenoxuron, fluquinconazole, iprodione, lufenuron, paclobutrazol, phenthoate, and spiromesifen.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.947-958
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• 2021

This study was conducted to provide basic data for crop monitoring by comparing and analyzing changes in reflectance and vegetation index by sensor of multi-spectral sensors mounted on unmanned aerial vehicles. For four types of unmanned aerial vehicle-mounted multispectral sensors, such as RedEdge-MX, S110 NIR, Sequioa, and P4M, on September 14 and September 15, 2020, aerial images were taken, once in the morning and in the afternoon, a total of 4 times, and reflectance and vegetation index were calculated and compared. In the case of reflectance, the time-series coefficient of variation of all sensors showed an average value of about 10% or more, indicating that there is a limit to its use. The coefficient of variation of the vegetation index by sensor for the crop test group showed an average value of 1.2 to 3.6% in the crop experimental sites with high vitality due to thick vegetation, showing variability within 5%. However, this was a higher value than the coefficient of variation on a clear day, and it is estimated that the weather conditions such as clouds were different in the morning and afternoon during the experiment period. It is thought that it is necessary to establish and implement a UAV flight plan. As a result of comparing the NDVI between the multi-spectral sensors of the unmanned aerial vehicle, in this experiment, it is thought that the RedEdeg-MX sensor can be used together without special correction of the NDVI value even if several sensors of the same type are used in a stable light environment. RedEdge-MX, P4M, and Sequioa sensors showed a linear relationship with each other, but supplementary experiments are needed to evaluate joint utilization through off-set correction between vegetation indices.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.989-998
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• 2021

In the utilization of optical satellite imagery, which is greatly affected by clouds, periodic composite technique is a useful method to minimize the influence of clouds. Recently, a technique for selecting the optimal pixel that is least affected by the cloud and shadow during a certain period by directly inputting cloud and cloud shadow information during period compositing has been proposed. Accurate extraction of clouds and cloud shadowsis essential in order to derive optimal composite results. Also, in the case of an surface targets where spectral information is important, such as crops, the loss of spectral information should be minimized during cloud-free compositing. In thisstudy, clouds using two spectral indicators (Haze Optimized Tranformation and MeanVis) were used to derive a detection technique with low loss ofspectral information while maintaining high detection accuracy of clouds and cloud shadowsfor cabbage fieldsin the highlands of Gangwon-do. These detection results were compared and analyzed with cloud and cloud shadow information provided by Sentinel-2A/B. As a result of analyzing data from 2019 to 2021, cloud information from Sentinel-2A/B satellites showed detection accuracy with an F1 value of 0.91, but bright artifacts were falsely detected as clouds. On the other hand, the cloud detection result obtained by applying the threshold (=0.05) to the HOT showed relatively low detection accuracy (F1=0.72), but the loss ofspectral information was minimized due to the small number of false positives. In the case of cloud shadows, only minimal shadows were detected in the Sentinel-2A/B additional layer, but when a threshold (= 0.015) was applied to MeanVis, cloud shadowsthat could be distinguished from the topographically generated shadows could be detected. By inputting spectral indicators-based cloud and shadow information,stable monthly cloud-free composited vegetation index results were obtained, and in the future, high-accuracy cloud information of Sentinel-2A/B will be input to periodic cloud-free composite for comparison.

• Korean journal of applied entomology
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• v.60 no.4
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• pp.387-401
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• 2021

Thrips infesting hot peppers were monitored in greenhouses using yellow sticky traps. In addition, the hot peppers infected with tomato spotted wilt virus (TSWV) were observed during the monitoring period. The flower thrips (Frankliniella intonsa) were initially trapped at a low density just after transplanting seedlings of hot peppers at late March. The western flower thrips (Frankliniella occidentalis) were trapped after mid April. These two thrips represented more than 98% of the total thrips attracted to the traps after May, in which F. intonsa showed higher occurrence frequency than F. occidentalis. The total number of thrips had two peaks at mid May with a small and short-term peak and at June-July with a large and long-term peak. The trapped thrips exhibited inconsistent sex ratios, suggesting a seasonal parthenogenesis. Different geographical populations were varied in cytochrome oxidase I sequences, in which local populations in Andong shared a high sequence similarity. TSWV-infected hot peppers, which might be mediated by these two thrips species, were observed and confirmed by an immunoassay kit and a molecular diagnosis using RT-PCR. In addition, the TSWV was detected in F. occidentalis collected from the infected hot peppers. Three open reading frames (NS_S, N, and NS_M) of the isolated TSWV genomes were sequenced and showed multiple point mutations containing missense mutations among geographical variants. When the isolated TSWV was fed to nonvirulent thrips of F. occidentalis, the virus was detected in both larvae and adults. However, the viral replication occurred in larvae, but not in adults.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1657-1667
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• 2021

Anthropogenic activities and natural processes have been causes of land subsidence which is sudden sinking or gradual settlement of the earth's solid surface. Mexico City, the capital of Mexico, is one of the most severe land subsidence areas which are resulted from excessive groundwater extraction. Because groundwater is the primary water resource occupies almost 70% of total water usage in the city. Traditional terrestrial observations like the Global Navigation Satellite System (GNSS) or leveling survey have been preferred to measure land subsidence accurately. Although the GNSS observations have highly accurate information of the surfaces' displacement with a very high temporal resolution, it has often been limited due to its sparse spatial resolution and highly time-consuming and high cost. However, space-based synthetic aperture radar (SAR) interferometry has been widely used as a powerful tool to monitor surfaces' displacement with high spatial resolution and high accuracy from mm to cm-scale, regardless of day-or-night and weather conditions. In this paper, advanced interferometric approaches have been applied to get a time-series of land subsidence of Mexico City using four-year-long twenty ALOS PALSAR L-band observations acquired from Feb-11, 2007 to Feb-22, 2011. We utilized persistent scatterer interferometry (PSI) and small baseline subset (SBAS) techniques to suppress atmospheric artifacts and topography errors. The results show that the maximum subsidence rates of the PSI and SBAS method were -29.5 cm/year and -27.0 cm/year, respectively. In addition, we discuss the different subsidence rates where the study area is discriminated into three districts according to distinctive geotechnical characteristics. The significant subsidence rate occurred in the lacustrine sediments with higher compressibility than harder bedrock.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1819-1827
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• 2021

Land-use/cover change caused by rapid urbanization in South Korea is one of the concerns in flood risk management because groundwater recharge by precipitation hardly occurs due to an increase in impermeable surfaces in urban areas. This study investigated the hydrologic effects of land-use/cover on groundwater recharge in the Yeonje-gu district of Busan, South Korea. A statistical time series analysis was conducted with temporal variations of precipitation and groundwater level to estimate lag-time based on correlation coefficients calculated from auto-correlation function (ACF), cross-correlation function (CCF), and moving average (MA) at five sites. Landform and land-use/cover within 250 m radius of the monitoring wells(GW01, GW02, GW03, GW04, and GW05) at five sites were identified by land cover and digital map using Arc-GIS software. Long lag-times (CCF: 42-71 days and MA: 148-161 days) were calculated at the sites covered by mainly impermeable surfaces(GW01, GW03, and GW05) while short lag-times(CCF: 4 days and MA: 67 days) were calculated at GW04 consisting of mainly permeable surfaces. The results suggest that lag-time would be one of the good indicators to evaluate the effects of land-use/cover on estimating groundwater recharge. The results of this study also provide guidance on the application of statistical time series analysis to environmentally important issues on creating an urban green space for natural groundwater recharge from precipitation in the city and developing a management plan for hydrological disaster prevention.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.

• Journal of Bio-Environment Control
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• v.30 no.3
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• pp.188-195
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• 2021

This study was conducted to investigate the growth and quality characteristics of melon (Cucumis melo L.) cultivars and the irrigation requirements for cultivars. In our previous study in 2019, twelve melon cultivars including 'Dalgona' were examined for their cultivar characteristics under the same irrigation condition for all cultivars, and sorted into several groups based on different growth condition; for the internode length (from 0 to 20th node), leaf area, and fruit weight, 'Kingstar' belonged to the largest group, 'Worldstar' the middle group, and 'Dalgona' the smallest group. After analyzing the results of the previous experiment, 'Dalgona', 'Worldstar', 'Kingstar', and 'Rubyball' were selected as test cultivars for the growth group in 2020, and irrigated according to different irrigation levels for each cultivar. The control of the irrigation volume for each melon cultivar by monitoring the drainage rate during the cultivation periods showed that all four cultivars required a similar amount of irrigation in the 'early growth' stage where crops grew at about the same rate. From 'flowering time', however, the change in irrigation requirements showed a similar tendency for 'Worldstar' and 'Kingstar' and for 'Rubyball' and 'Dalgona' respectively. A sudden change in each irrigation volume was observed from the fruit set; 'Dalgona' began first to decline and 'Rubyball' was second, followed by 'Worldstar' and 'Kingstar'. In conclusion, the irrigation volume was the largest in 'Kingstar', followed by 'Worldstar', 'Rubyball', and 'Dalgona' in the same order as the growing amount of plant length, leaf area, and fruit weight. Therefore, it is necessary to control exactly the irrigation volume by reflecting the unique growth characteristics of each cultivar for the production of high-quality fruit in melon hydroponics, and especially to use great care when different cultivars are cultivated together.

• Korean Journal of Environment and Ecology
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• v.32 no.6
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• pp.557-565
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• 2018

We examined the nutrient dynamics during the leaf litter decomposition rate and process of Pinus rigida and Pinus koraiensis in Gongju for 21 months from December 2014 to September 2016 as a part of National Long-Term Ecological Research Program in Korea. The remaining weight rate of P. rigida and P. koraiensis leaf litter was $58.27{\pm}4.13$ and $54.08{\pm}4.32%$, respectively, indicating that the P. koraiensis leaf litter decomposed faster than P. rigida leaf litter. The decay constant (k) of P. rigida leaf litter and P.koraiensis leaf litter after 21 months was 0.95 and 1.08, respectively, indicating that P. koraiensis leaf litter decayed faster than P. rigida leaf litter probably due to the difference of nitrogen concentration between the two. The C/N ratio of P. rigida and P. koraiensis leaf litter was 64.4 and 40.6, respectively, initially, and then decreased to 41.0 and 18.9, respectively, after 21 months. The C/P ratio of P. rigida and P. koraiensis leaf litter was 529.8 and 236.5, respectively, and then decreased to 384.1, 205.2, respectively, after 21 months. The contents of N, P, K, Ca, and Mg were 6.78, 0.83, 2.84, 0.99, and 2.59 mg/g, respectively, in the P. rigida leaf litter and 10.90, 1.87, 5.82, 4.79, and 2.00 mg/g, respectively, in the P. koraiensis leaf litter, indicating that the elements except the magnesium showed higher contents in P. koraiensis. After 21 months elapsed, remaining N, P, K, Ca, and Mg was 88.4, 77.6, 26.7, 50.5 and 44.5%, respectively, in decomposing P. rigida, and 114.4, 61.3, 7.6, 115.2 and 72.0%, respectively, decomposing P. koraiensis leaf litter.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.79-98
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• 2018

The purpose of this study is to suggest a model analysing spatio-temporal characteristics of the civil complaints for the officially assessed land price based on big data mining. Specifically, in this study, the underlying reasons for the civil complaints were found from the spatio-temporal perspectives, rather than the institutional factors, and a model was suggested monitoring a trend of the occurrence of such complaints. The official documents of 6,481 civil complaints for the officially assessed land price in the district of Jung-gu of Incheon Metropolitan City over the period from 2006 to 2015 along with their temporal and spatial poperties were collected and used for the analysis. Frequencies of major key words were examined by using a text mining method. Correlations among mafor key words were studied through the social network analysis. By calculating term frequency(TF) and term frequency-inverse document frequency(TF-IDF), which correspond to the weighted value of key words, I identified the major key words for the occurrence of the civil complaint for the officially assessed land price. Then the spatio-temporal characteristics of the civil complaints were examined by analysing hot spot based on the statistics of Getis-Ord $Gi^*$. It was found that the characteristic of civil complaints for the officially assessed land price were changing, forming a cluster that is linked spatio-temporally. Using text mining and social network analysis method, we could find out that the occurrence reason of civil complaints for the officially assessed land price could be identified quantitatively based on natural language. TF and TF-IDF, the weighted averages of key words, can be used as main explanatory variables to analyze spatio-temporal characteristics of civil complaints for the officially assessed land price since these statistics are different over time across different regions.