• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.429-438
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• 2005

For the implementation of science and technology based agriculture, one of the domestic rural development strategies, it is essential that we should have an integrated information system for each crop production. This system would be a web-based collaborative system for the local farmer and the advisors who guide the crop production technically, and would be capable of providing the real-time analysis functionalities and expert knowledge. In this thesis, we proposed a component based development methodology called MCPI(Method for Crop Production Information system) which employs and re-organizes Marmi-III, the popular existing component based methodology for the large scale S/W development project. In particular, MCPI is designed to reflect the characteristics of crop production information system and for the small and medium S/W project. To show the applicability in real-world problems, we develop and evaluate a prototype which is based on our proposed methodology for the rice production farmer in mid-Choongnam area.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.751-762
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• 2017

A crop information system can provide information regarding crop distribution, crop growth conditions, crop yield in various forms such as monitoring, forecasting, estimation or analysis. This paper presents the design and construction of a crop information system based on data collected in Korea, USA, and China. Therein, climate data including temperature, precipitation,solar radiation are used to evaluate the impact on crop growth, NDVI (Normalized Difference Vegetation Index) data is used in crop monitoring, and crop map data is utilized for the management of crop distribution. The system has achieved three prominent results: 1) Providing information with high frequency, 2) Automatically creating the report through the analysis of the data, 3) The users to easily approach the system and retrieve the information.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.257-259
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• 2005

A crop management system was developed using Visual Basic and ArcGIS VBA. The system is operated on ArcGlS 8.3 with Microsoft Access MOB. Landsat +ETM, KOMPSAT-l EOC, ASTER VNIR and IKONOS panchromatic (pan) and multi-spectral (MIS) images were included in the system to understand what kind of agriculture-related information can be extracted for each images. Agriculture related data inventories using crop cover information such as texture and average pixel value of the crop based on cultivation calendar were designed ,and implemented. Three IKONOS images (May 25,2001, December 25,2001, October 23,2003) were loaded in the system to show crop cover characteristics such as rice, pear, grape, red pepper, garlic, and surface water cover of reservoir with field surveys. GIS layers such as DEM (Digital Elevation Model), stream, road, soil, land use and administration boundary were also supplied and can be overlaid with images to enhance the understanding the general agricultural characteristics and identifying the location easily.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.7
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• pp.3-9
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• 2005

A computer system for crop information was developed using Visual Basic and ArcGIS VBA. The system is operated on ArcGIS 8.3 with Microsoft Access MDB. Landsat +ETM, KOMPSAT-1 EOC, ASTER VNIR and IKONOS panchromatic (Pan) and multi-spectral (MIS) images were included in the system to extract agricultural land use items identifiable at various spatial resolutions of images. Agriculture related data inventories using crop cover information such as texture and average pixel value of each band based on crop cultivation calendar were designed and implemented. Three IKONOS images were loaded in the system to show crop cover characteristics such as rice, pear, grape, red pepper, garlic, and surface water cover of reservoir with field surveys. GIS layers such as DEM (Digital Elevation Model), stream, road, soil, land use and administration boundary were prepared to understand the related characteristics and identify the location easily.

• Journal of Biosystems Engineering
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• v.24 no.1
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• pp.25-30
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• 1999

The effectiveness of many greenhouse environment control methodologies depends on the growth information of crops. Acquisition of the growth information of crops requires a non-invasive and continuous monitoring method. Crop growth monitoring system using digital imaging technique was developed to conduct non-destructive and intact plant growth analyses. The monitoring system automatically measures crop growth information sends an appropriate control signal to the nutrient solution supplying system. To develop the monitoring system, a linear model that explains the relationship between the fresh weight and the top projected leaf area of a lettuce plant was developed from an experiment. The monitoring system was evaluated buy successive lettuce growing experiments. Results of the experiments showed that the developed system could estimate the fresh weight of lettuce from a lettuce image by using the linear model and generate an EC control signal according to the lettuce growth stage.

• Proceedings of the Korean Society of Crop Science Conference
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• 1998.10a
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• pp.415-445
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• 1998

For effective prevention of the spreading and outbreak of crop insects and disease pests, an intensive Pest surveillance system was established to predict their density changes, and distribution. After their initial establishment by either immigration or overwintering, it is necessary to anticipate how they spread out geographically and predict where/when outbreaks are possible. The two major tools, boundary layer atmospheric model (Blayer) and the geographic information system(GIS), have been being developed to facilitate the prediction of pest occurrence in recent days. We are also developing the PeMos (Pest Monitoring System) that is able to manage the pest surveillance data collected from 152 pest monitoring stations in Korea. These three system related to the pest surveillance should be integrated into an internet based comprehensive database management system to facilitate information resources systematically organized and closely linked. Considering various data types and large data size in each system, a new special information management system is suggested. The integrated system should express complex types of information, such as text, multimedia, and other scientific data under the Internet environment. This paper discussed the major three systems, GIS, Blayer, and PeMos, relevant to the crop pest surveillance, then how they can be integrated in a comprehensive system under the Internet environment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.174-179
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• 2017

Soil parameters are required inputs to crop models, which estimate crop yield under a given environment condition. The Korean Soil Information System (KSIS), which provides detailed soil profile record of 390 soil series in the HTML (HyperText Markup Language) format, would be useful to prepare soil input files. Korean Soil Information System Processing Tool (KSISPT) was developed to aid generation of soil input data based on the KSIS database. Java was used to implement the tool that consists of a set of modules for parsing the HTML document of the KSIS, storing data required for preparing soil input file, calculating additional soil parameter, and writing soil input file to a local disk. Using the automated soil data preparation tool, about 940 soil input data were created for the DSSAT model and the ORYZA 2000 model, respectively. In combination with soil series distribution map at 30m resolution, spatial analysis of crop yield could be projected under climate change, which would help the development of adaptation strategies.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.145-152
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• 2020

In this paper, we propose the Crop Classification Management System (CCMS) that detects changes in growth environment to improve crop production rate. The CCMS consists of two modules. First, the Crop Classification Module (CCM) classifies crops through CNN. Second, the Farm Anomaly Detection Module (FADM) detects abnormal crops by comparing accumulated data of farms. The CCM recognizes crops currently grown on farms and sends them to the FADM, and the FADM picks up the weather data from the past to the present day of the farm growing the crops and applies them to the Nelson rules. The FADM uses the Nelson rules to find out weather data that has occurred and adjust farm conditions through IoT devices. The performance analysis of CCMS showed that the CCM had a crop classification accuracy of about 90%, and the FADM improved the estimated yield by up to about 30%. In other words, managing farms through the CCMS can help increase the yield of smart farms.

• Proceedings of the Korean Society of Crop Science Conference
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• 2004.04a
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• pp.42-50
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• 2004

Societies are important sources of new information for users. However, most of these societies still rely on traditional, or rather ancient methods for gathering and servicing the information. Furthermore, most of the societies are trying to electrify processes such as managing members and paper submission as well as the process managing the information for service but are limited due to financial and technical reasons. Therefore, KISTI(Korea Institute of Science and Technology Information) has developed the ${\ulcorner}$KISTl-ACOMS (KISTI-Article Contribution Management System)${\lrcorner}$ as part of the national project for automating the process of processing academic information by societies, in order to convert journals published by academic societies in Korea into an electronic form and make them accessible on the Internet. This system has been developed in the year 2001 and has since been distributed to societies free of charge. The number of societies requesting the service has risen recently, which prompted us to take more recommendations of the societies that adopt this system into account in expanding and standardizing the area of service being provided by the system.

• Agribusiness and Information Management
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• v.10 no.2
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• pp.8-17
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• 2018

Due to changes in the agricultural market environment and both overseas and domestic farming conditions, uncertainties in agricultural production and management are becoming greater. Hence, there is a stronger need for farmers to choose crops in the optimal condition. This research aims to introduce the result and process of developing a decision support system for selecting crops, aimed to assist farmers in selecting the optimal crops most suitable in the given situation. There are basically three main factors to consider in the decision-making process for farmers when selecting a crop to introduce to their lands. First of all, one must consider how much profit crop A will produce when it is cultivated. Secondly, one must consider which crop to cultivate in order to earn a certain amount of profit. Thirdly, one must consider what is the best way to maximize Farm A's business profit. For instance, a farm may have land as its resource, and one must research which location, type of crop, level of technology, and so forth, to maximize profit.This research creates a database of the profitability of a total of 180 crop types by analyzing Rural Development Administration's survey of agricultural products income of 115 crop types, small land profitability index survey of 53 crop types, and Statistics Korea's survey of production costs of 12 crop types. Furthermore, this research presents the result and developmental process of a web-based crop introduction decision support system that provides overseas cases of new crop introduction support programs, as well as databases of outstanding business success cases of each crop type researched by agricultural institutions.