• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1207-1217
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• 2022

Vegetation indices using the reflectance of selected wavelength, associating with the monitoring purpose such as identifying the progress of crop growth, on the vegetation canopy surface is widely used in the digital agriculture technology. However, the surface reflectance anisotropy can distort the true value of vegetation index related to the condition of surface, even though the surface property be unchanged. That causes difficulty to observe accurately crop growth on the monitoring system. In this study, a simple type goniometer was designed to measure the reflectance from the anisotropic surface according to various zeniths and azimuths of sun and viewing sensor in the field. On the tarp like as Lambertian surface, the reflectance of Blue, Green, Red, Near-Infrared band was similar to the tarps' reflectance properties. However, the reflectance was slightly overestimated in the cloudy day. The relative difference values of vegetation indices on grass were overestimated for the forward viewing and underestimated for the backward viewing. In addition, enhanced vegetation index (EVI) showed less sensitive according to the positions of sun and sensor viewing. Field observation with a goniometer will be helpful to understand the anisotropy characteristics on the vegetation surface.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1427-1435
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• 2023

Vegetation indices based on selected wavelength reflectance measurements are used to represent crop growth and physiological conditions. However, the anisotropic properties of the crop canopy surface can govern spectral reflectance and vegetation indices. In this study, we applied an ensemble of bidirectional reflectance distribution function (BRDF) models to high-resolution Sentinel-2 satellite imagery and compared the differences between correction results before and after reflectance. In the red and near-infrared (NIR) band reflectance images, BRDF-corrected outlier values appeared in certain urban and paddy fields of farmland areas and forest shadow areas. These effects were equally observed when calculating the normalized difference vegetation index (NDVI) and 2-band enhanced vegetation index (EVI2). Furthermore, the outlier values in corrected NIR band were shown in pixels shadowed by mountain terrain. These results are expected to contribute to the development and improvement of BRDF models in high-resolution satellite images.

• Korean journal of applied entomology
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• v.52 no.4
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• pp.427-430
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• 2013

Recently, climate change scenarios were substituted by the Special Report on Emission Scenarios (SRES) for Representative Concentration Pathway (RCP). Using the RCP scenario, the World Meteorological Organization (WMO) produced new climate change scenarios. Further, the National Institute of Meteorological Research (NIMR) of Korea produced new climate change scenarios for the Korean Peninsula. In this study, emergence time of small brown planthopper (SBPH), Laodelphax striatellus and the number of generations a year were estimated during climatic normal year (1981-2010) with previous studies and they were predicted during 2050s (2045-2054) and 2090s (2085-2094) by means of RCP8.5 climate change scenario. In comparison with $176.0{\pm}0.97$ Julian data in the climatic normal year, the emergence time of overwintering SBPH was predicted to be $13.2{\pm}0.18$ days ($162.8{\pm}0.91$ Julian date) earlier in 2050s and $32.1{\pm}0.61$ days ($143.9{\pm}1.08$ Julian date) earlier in 2090s. The SBPH was expected to produce an additional $2.0{\pm}0.02$ generations in 2050s and $5.2{\pm}0.06$ generations in 2090s.

• Korean journal of applied entomology
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• v.55 no.4
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• pp.501-511
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• 2016

Predicting potential spatial distribution of Monochamus alternatus, a major insect vector of the pine wilt disease, is essential to the spread of the pine wilt disease. The purpose of this study was to predict future domestic spatial distribution of M. alternatus by using the CLIMEX model considering the temperature condition of the vector's life history. To predict current distribution of M. alternatus, the administrative divisions data where the pine wilt spots caused by M. alternatus were found from 2006 to 2014 and the 10-year mean climate observed data in 68 meteorological stations from 2006 to 2015 were used. Eight parameter sets were chosen based on growth temperature range of M. alternatus reported in preceding researches. Error matrix method was utilized to select and simulate the parameter sets showing the highest correlation with the actual distribution. Regarding the future distribution of M. alternatus, two periods of 2050s(2046-2055) and 2090s(2091-2100) were predicted using the projected climate data of RCP 8.5 Scenario generated from Korea Meteorological Administration. Overall results of M. alternatus distribution simulation were fit in the actual distribution; however, overestimation in Seoul Metropolitan area and Chungnam Region were shown. Gradual expansion of M. alternatus would be expected to nationwide from western and southern coastal areas of Korea peninsula.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.637-648
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• 2021

In order to support the establishment of a farming plan, it is important to preemptively evaluate crop changes and to provide precise information. Therefore, it is necessary to provide customized information suitable for decision-making by farming stage through scientific and continuous monitoring using drones. This study was carried out to support the establishment of the farming plan for ground vegetable. The cultivation management map of each information was obtained from preliminary study. Three cultivation management maps include 'field emergence map', 'stress map' and 'productivity map' reflected spatial variation in the plantation by providing information in units of plants based on 3-dimensions. Application fields of the cultivation management map can be summarized as follows: detect miss-planted, replanting decision, fertilization, weeding, pest control, irrigation schedule, market quality evaluation, harvest schedule, etc.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.241-262
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• 2021

This paper reviewed the necessity of a information and communication technology (ICT)-based smart livestock system as a development strategy for the animal life industry in the future. It also predicted the trends of livestock and animal food until 2050, 30 years later. Worldwide, livestock raising and consumption of animal food are rapidly changing in response to population growth, aging, reduction of agriculture population, urbanization, and income growth. Climate change can change the environment and livestock's productivity and reproductive efficiencies. Livestock production can lead to increased greenhouse gas emissions, land degradation, water pollution, animal welfare, and human health problems. To solve these issues, there is a need for a preemptive future response strategy to respond to climate change, improve productivity, animal welfare, and nutritional quality of animal foods, and prevent animal diseases using ICT-based smart livestock system fused with the 4th industrial revolution in various aspects of the animal life industry. The animal life industry of the future needs to integrate automation to improve sustainability and production efficiency. In the digital age, intelligent precision animal feeding with IoT (internet of things) and big data, ICT-based smart livestock system can collect, process, and analyze data from various sources in the animal life industry. It is composed of a digital system that can precisely remote control environmental parameters inside and outside the animal husbandry. The ICT-based smart livestock system can also be used for monitoring animal behavior and welfare, and feeding management of livestock using sensing technology for remote control through the Internet and mobile phones. It can be helpful in the collection, storage, retrieval, and dissemination of a wide range of information that farmers need. It can provide new information services to farmers.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.311-321
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• 2017

Principal component analysis is a popular statistical method to reduce the dimension of the high dimensional climate data and to extract meaningful climate patterns. Based on the principal component analysis, we can further apply a regression approach for the linear prediction of future climate, termed as principal component regression (PCR). In this paper, we develop a new PCR method based on the regularized principal component analysis for spatial data proposed by Wang and Huang (2016) to account spatial feature of the climate data. We apply the proposed method to temperature prediction in the East Asia region and compare the result with conventional PCR results.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.209-220
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• 2010

One of the most difficult tasks in measuring oceanic conditions is to produce oceanic current information. In efforts to overcome the difficulties, various attempts have been carried out to estimate the speed and direction of ocean currents by utilizing sequential satellite images. In this study, we have estimated sea surface current vectors to the south of the Korean Peninsula, based on the maximum cross-correlation method by using sequential ocean color images of SeaWiFS chlorophyll-a. Comparison of surface current vectors estimated by this method with the geostrophic current vectors estimated from satellite altimeter data and in-situ ADCP measurements are good in that current speeds are underestimated by about 15% and current directions are show differences of about $36^{\circ}$ compared with previous results. The technique of estimating current vectors based on maximum cross-correlation applied on sequential images of SeaWiFS is promising for the future application of GOCI data for the ocean studies.

• Korean journal of applied entomology
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• v.60 no.1
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• pp.145-154
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• 2021

Integrated pest management system in Korean apple has significantly advanced for last few decades. However harmful effects of pesticides threats the ecosystem services of natural enemies and pollinators. Apple require cross-pollination and Insect pollination with diversity and abundance is one of the keys to profitable apple production in quantity and quality as well. Thus crop protection tools are to be administered in harmony to meet the pest suppression and protection of beneficial organisms such as natural enemies and pollinators. Adding onto the established IPM system, integrated pollinator-pest management (IPPM) concept is proposed as the future direction of apple IPM. For this, ecological enginnering of creating habitats for pollinators, landscape management and agroecosytem diversification as well as selective soft pesticide uses on time guided by pest monitoring and phenologyand targeted delivery are further proposed. Recent shift of agroecosystem from climate change and new pest outbreaks require new paradigm of pest management for sustainable agricultural production.

• Journal of the Korean Applied Science and Technology
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• v.39 no.1
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• pp.132-145
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• 2022

The emission factor and activity data of fugitive dust in the domestic agricultural field have been applied to the US inventory system without reflecting the domestic environmental conditions (wind speed, humidity, etc.) and agricultural characteristics. In this study, the temporal resolution was improved for each region by deriving a monthly distribution factor through the application of wind speed and dry season and the spatial resolution was improved for each region by subdivided into dong and ri from ci·gun·gu. Through this study, it is judged that it can be used as an important data for improving the emission and activity data of fugitive dust in the agricultural field that currently exist.