• Journal of Korean Society of Rural Planning
• /
• v.28 no.2
• /
• pp.87-96
• /
• 2022

As part of strengthening energy security and responding to climate change, the government has promoted various renewable energy measures to increase the development of renewable energy facilities. As a result, small-scale solar installations in rural areas have increased rapidly. The number of complaints from local residents is increasing. Therefore, in this study, deep learning technology is applied to high-resolution aerial images on the internet to detect solar power plants installed in rural areas to determine whether or not solar power plants are installed. Specifically, I examined the solar facility detector generated by training the YOLO(You Only Look Once) v2 object detector and looked at its usability. As a result, about 800 pieces of training data showed a high object detection rate of 93%. By constructing such an object detection model, it is expected that it can be utilized for land use monitoring in rural areas, and it can be utilized as a spatial data construction plan for rural areas using technology for detecting small-scale agricultural facilities.

• Journal of Korean Society of Rural Planning
• /
• v.29 no.1
• /
• pp.37-49
• /
• 2023

Active attention and effort are needed to develop an integrated water management system in response to climate change. In this study, it proposed models for cross-use of agricultural water and river maintenance water using sewage treatment water as an integrated water management system for the Yeongsan River. The impact of the integrated water management models was assessed by applying the concept of Nexus, which is being presented worldwide for sustainable resource management. The target year was set for 2030 and quantitatively analyzed water, energy, land use and carbon emissions and resource availability index by integrated water management models was calculated by applying maximum usable amount by resource. An integrated water management system evaluation model using the Nexus concept developed in this study can play a role that can be viewed in a variety of ways: security and environmental impact assessment of other resources. The results of this research will be used as a foundation for the field of in the establishment of a policy decision support system to evaluate various security policies, as we analyzed changes in other factors according to changes in individual components, taking into account the associations between water, energy, food, and carbon resources. In future studies, additional sub-models need to be built that can be applied flexibly to changes in the future timing of the inter-resource relationship components.

• Journal of Korean Society of Rural Planning
• /
• v.29 no.4
• /
• pp.127-135
• /
• 2023

This study examined the impact of changes in agricultural production methods on society, the economy, and the environment. While traditional open-field farming relied heavily on natural conditions, modern approaches, including greenhouse and smart farming, have emerged to mitigate the effects of climate and seasonal variations. Facility horticulture has been on the rise since the 1990s, and recently, there has been a growing interest in smart farms due to reasons such as climate change adaptation and food security. We compared open-field spinach and greenhouse spinach using agricultural income survey data, and we also compared greenhouse tomato cultivation with smart farming tomato cultivation, utilizing data from the smart farm survey reports. The economic results showed that greenhouse spinach increased yield by 25.8% but experienced a 29% decrease in income due to equipment depreciation. In the case of tomato production in smart farms, both yield and income increased by 36-39% and 34-46%, respectively. In terms of environmental impact, we also compared fertilizer and energy usage. It was found that greenhouse spinach used 29% less fertilizer but 14% more energy compared to open-field spinach. Smart farming for tomatoes saw a negligible decrease in electricity and fuel costs. Regarding the social impact, greenhouse spinach reduced labor hours by 31%, and the introduction of smart farming for tomatoes led to an average 11% reduction in labor hours. This reduction is expected to have a positive effect on sustainable farming. In conclusion, the transition from open-field to greenhouse cultivation and from greenhouse cultivation to smart farming appears to yield positive effects on the economy, environment, and society. Particularly, the reduction in labor hours is beneficial and could potentially contribute to an increase in rural populations.

• Journal of the Semiconductor & Display Technology
• /
• v.23 no.1
• /
• pp.12-18
• /
• 2024

The accelerated pace of climate crisis due to continuous industrialization and greenhouse gas emissions necessitates sustainable solutions that simultaneously address mitigation and adaptation to climate change. Naturebased Solutions (NbS) have gained prominence as viable approaches, with Green Infrastructure being a representative NbS. Green Infrastructure involves securing green spaces within urban areas, providing diverse climate adaptation functions such as removal of various air pollutants, carbon sequestration, and isolation. The proliferation of Green Infrastructure is influenced by the quantification of improvement effects related to various projects. To support decision-making by assessing the climate vulnerability of Green Infrastructure, the U.S. Department of Agriculture (USDA) has developed i-Tree Tools. This study proposes a comprehensive evaluation approach for climate change adaptation types by quantifying the climate adaptation performance of urban Green Infrastructure. Using i-Tree Canopy, the analysis focuses on five urban green spaces covering more than 30 hectares, considering the tree ratio relative to the total area. The evaluation encompasses aspects of thermal environment, aquatic environment, and atmospheric environment to assess the overall eco-friendliness in terms of climate change adaptation. The results indicate that an increase in the tree ratio correlates with improved eco-friendliness in terms of thermal, aquatic, and atmospheric environments. In particular, it is necessary to prioritize consideration of the water environment sector in order to realize climate change adaptive green infrastructure, such as increasing green space in urban areas, as it has been confirmed that four out of five target sites are specialized in improving the water environment.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.20 no.1
• /
• pp.18-33
• /
• 2018

A new eddy covariance-based flux tower has been established since June 2016 in a dry direct-seeding rice paddy field in southwestern Korea - Haenam Paddy field KoFlux site (HPK). To assess the competitiveness of direct-seeding agricultural technique in the context of climate-smart agriculture, we have been monitoring the $CO_2$, $CH_4$ and energy fluxes continuously. In this communication, we (1) introduce the HPK site and (2) explain the structure and processes of the HPK-specific data processing and quality control. The latter consists of 10-steps data processing and quality control procedures following the KoFlux standardized protocol and explained each step in layman's term. The final data produced during the data processing were stored in NCAM-DAPS (National Center for AgroMeteorology-Data Acquisition and Processing System, http://daps.ncam.kr). We hope that the introduction of new HPK KoFlux site would serve as a platform to facilitate transdisciplinary efforts in the research and education associated with climate-smart agriculture toward sustainability.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.63 no.5
• /
• pp.83-93
• /
• 2021

Agricultural reservoirs are important facilities for storing or managing water for the purpose of securing agricultural water, creating and expanding agricultural production bases, and using them to increase agricultural production. In particular, the Korea Rural Community Corporation (KRC) manages agricultural reservoirs scattered across the country, and officially recognizes and distributes hydrological data to increase their public utilization and aims to improve the value of water resources. Data on the water level of agricultural reservoirs are important. However, errors such as missing values and outliners limit utilization of the data in various fields of research and industry. Therefore, water quality data measures should be devised to increase reliability. this study categorized different error types and looked at automatic correction methods to enhance the reliability of the vast hydrological data. In addition, the water level data corrected from errors were compared to the reference hydrologic data through expert judgment in accordance with the quality control procedure, and the most appropriate measures were verified. As KRC manages more agricultural reservoirs than any other institution, the proposed method of efficient and automatic water level data correction in this study is expected to increase the availability and reliability of the hydrological data.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.64 no.3
• /
• pp.9-24
• /
• 2022

Currently, a vast amount of hydrologic data is accumulated in real-time through automatic water level measuring instruments in agricultural reservoirs. At the same time, false and missing data points are also increasing. The applicability and reliability of quality control of hydrological data must be secured for efficient agricultural water management through calculation of water supply and disaster management. Considering the characteristics of irregularities in hydrological data caused by irrigation water usage and rainfall pattern, the Korea Rural Community Corporation is currently applying the Hampel filter as a water level data quality management method. This method uses window size as a key parameter, and if window size is large, distortion of data may occur and if window size is small, many outliers are not removed which reduces the reliability of the corrected data. Thus, selection of the optimal window size for individual reservoir is required. To ensure reliability, we compared and analyzed the RMSE (Root Mean Square Error) and NSE (Nash-Sutcliffe model efficiency coefficient) of the corrected data and the daily water level of the RIMS (Rural Infrastructure Management System) data, and the automatic outlier detection standards used by the Ministry of Environment. To select the optimal window size, we used the classification performance evaluation index of the error matrix and the rainfall data of the irrigation period, showing the optimal values at 3 h. The efficient reservoir automatic calibration technique can reduce manpower and time required for manual calibration, and is expected to improve the reliability of water level data and the value of water resources.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.65 no.5
• /
• pp.51-68
• /
• 2023

Due to the recent integrated water management policy, it is important to identify a reliable supply amount for establishing an agricultural water supply plan. In order to identify the amount of agricultural water supply, it is essential to calculate the discharge by measuring the water level and flow velocity of reservoirs and canal agricultural water, and quality control to ensure reliability must be preceded. Unlike agricultural reservoirs, canal agricultural water are more sensitive to the surrounding environment and reservoir irrigation methods (continuous, intermittent irrigation, etc.), making it difficult to estimate general water level patterns and at the same time a lot of erroneous data. The Korea Rural Community Corporation is applying a filter technique as a quality control method capable of processing large quantities and real-time processing of canal agricultural water level data, and applicability evaluation is needed. In this study, the types of errors generated by the automatic water level measurement system were first determined. In addition, by using the manual quality control data, a technique with high applicability is derived by comparing and analyzing data calibrated with Gaussian, Savitzky-Golay, Hampel, and Median filter techniques, RMSE, and NSE, and the optimal parameters of the technique range was derived. As a result, the applicability of the Median filter was evaluated the highest, and the optimal parameters were derived in the range of 120min to 240min. Through the results of this study, it is judged that it can be used for quantitative evaluation to establish an agricultural water supply plan.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.62 no.5
• /
• pp.63-72
• /
• 2020

Solar-sharing, which is an agricultural photovoltaic system installing solar panels on the upper part of crop growing field, has especially drawn attention. Because paddy fields for cultivating crops are large flat areas, there have been various attempts to utilize solar energy for solar photovoltaic as well as growth of crops in agriculture. Solar-sharing was first proposed in Japan, and has been actively studied for optimization and practical uses. The domestic climate differs from the climate conditions in which the solar-sharing has been widely studied, therefore, it is required to develop the solar-sharing technology suitable for the domestic climate. In this study, a simulation model was developed to analyze the change of solar radiation resulted from the solar-sharing installation. Monthly solar illumination intensity and the change of illumination intensity according to the various conditions of solar panel installation were simulated. The results of monthly illumination analysis differed by altitude of the sun, which was related to season. In addition, it was analyzed that the monthly illumination decreased by up to 42% due to solar-sharing. Accordingly, it is recommended that solar-sharing should be installed as a way to maximize the efficiency of solar photovoltaic system while minimizing the decrease in solar radiation reaching the crops.

• Smart Media Journal
• /
• v.5 no.3
• /
• pp.17-24
• /
• 2016

Korean agriculture is currently experiencing difficulties as a cause of rural depopulation, aging of rural population, grain self-sufficiency rate decline, and deepening of climate change. It is necessary to ensure our country's agriculture industrial competitiveness in accordance with opening of FTA imports expanded. To ensure the underdeveloped competitive, Korean government defines the 3rd generation model from 1st generation model to extend the smart farms of Korean types. The agriculture smarting overcomes the growth limitations of agriculture, and efforts to develop 6th + ${\alpha}$ industry. In this paper, We define and verify the IoF(Internet of Farming)-Cloud based substantial services about 2rd generation model, and propose a greenhouse of IoF-Cloud testbed.