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Kafe 바로가기주관연구기관 | 국립농업과학원 National Institute of Agricultural Sciences |
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연구책임자 | 이경도 |
참여연구자 | 박찬원 , 나상일 , 박재문 , 강신규 , 서범석 , 이지혜 , 강문평 , 조낭현 , 박노욱 , 유희영 , 김예슬 , 곽근호 , 이호길 , 최지혜 , 설미현 , 박민규 , 허준 , 윤상현 , Nguyen Minh Hieu , 마종원 , 오원섭 , 윤성범 , 주성하 , 이우경 , 김아름 , 김현철 , 김범승 , 송경민 , 이기웅 |
보고서유형 | 최종보고서 |
발행국가 | 대한민국 |
언어 | 한국어 |
발행년월 | 2018-02 |
과제시작연도 | 2017 |
주관부처 | 농촌진흥청 Rural Development Administration(RDA) |
과제관리전문기관 | 농촌진흥청 Rural Development Administration |
등록번호 | TRKO201800043072 |
과제고유번호 | 1395049971 |
사업명 | 농업기후변화대응체계구축 |
DB 구축일자 | 2018-11-24 |
키워드 | 원격탐사.작물 생산량.미국.중국.생물리모형.생육시기.분류.작물.재배면적.주제도.곡물생산량 추정.농업생산환경 서비스.작황정보시스템.통합 프로세스.공간정보.중형위성.탑재체.전략수립.Remote sensing.Crop yield.USA.China.MODIS.crop productivity.Crop growth model.phenology.All-weather meteorological data.Classification.Crop.Cultivation area.Thematic map.Crop yield estimation.Agricultural information service.Crop infromation system.Integrated process.Spatial information.Medium-sized satellite.Payload.Strategy establishment. |
DOI | https://doi.org/10.23000/TRKO201800043072 |
국내외 주요 곡물 생산지대(미국 일리노이, 아이오와주, 중국 동북3성 등)에 대한 작황 정보 생산 기술 개발을 위해 원격탐사 기반 작물 수량 추정 기술을 개발·개선하고, 작물 생육인자 지도 제작 및 생육상황 평가자료 생산 기술을 개발하였다. 국내외 주요 작물 재배지를 대상으로 작물 분류 방법론을 개발하고, 작물 분류를 통한 재배면적 정보를 추출해 이를 분석하였으며 작황 정보 생산을 위한 위성영상 자동 전처리 기술 개발과 농업생산환경 정보시스템 구현 기반을 조성하였다. 이러한 결과와 연계하여 차세대 농림업 중형위성 탑재체 개발 및 활
국내외 주요 곡물 생산지대(미국 일리노이, 아이오와주, 중국 동북3성 등)에 대한 작황 정보 생산 기술 개발을 위해 원격탐사 기반 작물 수량 추정 기술을 개발·개선하고, 작물 생육인자 지도 제작 및 생육상황 평가자료 생산 기술을 개발하였다. 국내외 주요 작물 재배지를 대상으로 작물 분류 방법론을 개발하고, 작물 분류를 통한 재배면적 정보를 추출해 이를 분석하였으며 작황 정보 생산을 위한 위성영상 자동 전처리 기술 개발과 농업생산환경 정보시스템 구현 기반을 조성하였다. 이러한 결과와 연계하여 차세대 농림업 중형위성 탑재체 개발 및 활용 전략과 농림업 중형위성 탑재체 모의운용 성능 분석, 검증을 수행하였다.
(출처 : 보고서 요약서 3p)
1세부과제 : 원격탐사를 활용한 주요 작물 생산지대 작물 생산량 예측
Purpose&Contents
Developing, improving and integrating technology for estimating the yield fo crops using by remote sensing for domestic and overseas major crop production area(USA Illinois, Iowa, China northeast, domestic rice, etc.)
Results
We
1세부과제 : 원격탐사를 활용한 주요 작물 생산지대 작물 생산량 예측
Purpose&Contents
Developing, improving and integrating technology for estimating the yield fo crops using by remote sensing for domestic and overseas major crop production area(USA Illinois, Iowa, China northeast, domestic rice, etc.)
Results
We studied on estimation of wheat yield in Kansas state and improvement of yield estimation model for soybeans and corn in Illinois and Iowa states using remote sensing technology. We developed a model for estimating the yield of major cros (soybeans, corn, wheat, rice) in three northeast China provinces based on satellite images and meteorological data. We conducted agricultural status monitoring using satellite images for agricultural policy demand areas. Also, we analyzed the crop characteristics of main vegetables using surface spectroradiometer. And we established the integration and linkage of the development technology for the integrated report of the technology of crop yield estimation for each region and crops.
Expected Contribution
Providing information on the crop yield of the major crop production countries can contribute to the formulation of food supply stabilization measures
1협동과제 : 원격탐사를 활용한 주요 작물 생육변동 모니터링 기술 개발
Purpose&Contents
High-quality time-series satellite data and all-weather meteorological data using MODIS and AMSR-E images were developed. The satellite remote sensing data and a process-based crop growth model were applied to monitor crop phenology and growth parameters for assessing crop growth conditions.
Results
Satellite-data processing methods were developed for estimating high-quality time-series data and all-weather daily meteorological variables. Crop phenology, biomass, and yield were estimated with a process-based crop growth model for corn, soybean, and rice. Using the crop growth parameters, temporal change of crop growth condition was assessed. The study area includes Corn-belt of USA, Northeastern China, Korea, and more.
Expected Contribution
- Satellite-based detection of crop phenology is useful to monitor responses of crop and forest to climate change.
- High-quality satellite data enhance applicability of satellite information in various fields.
2협동과제 : 원격탐사를 활용한 주요 작물 재배지 분류 및 면적 산정 연구
Purpose&Contents
The purpose of this research is to develop crop classification methodologies targeting major crop cultivation areas in Korea Peninsula and foreign countries, and to extract and analyze cultivation area information through crop classification. For this purpose, we developed remote sensing data based classification methodologies suitable for major crop cultivation areas in USA, China, and agricultural policy demand area. By applying the developed classification methodologies, time-series crop type maps were generated and variabilities of the cultivation areas were analyzed. In Korea Peninsula, the applicability of remote sensing data for extracting crop cultivation information was reviewed targeting main field crop cultivation areas for domestic area and North Korea. Then, crop type maps were generated on a trial basis and cultivation areas were estimated. Also, manuals of crop classification methodology were generated including regional and crop characteristics and processes. In addition, a study for determining the appropriate pixel size of satellite images required for crop area estimation was carried out.
Results
We developed a crop classification methodology in Iowa, Illinois, and Kansas states, USA. By using the crop classification methodology, the crop type maps from 2013 to 2017 were produced early. Also, the time-series variability of cultivation areas for corn, soybean and wheat was analyzed. For the crop classification in Dongbei and Shandong Province, China, we developed crop classification methodologies considering cultivation characteristics and available data, and produced crop type maps from 2002 to 2013.
Also, the crop type maps from 2014 to 2017 were produced early and the time-series variability of cultivation areas of corn, bean, wheat, and paddy was analyzed. For Mato Grosso state, Brazil as agricultural policy demand area, spectral characteristics of major crops in remote sensing data were analyzed and a classification methodology was developed considering these spectral characteristics.
By using the developed classification methodology, crop type maps in 2001, 2007, and 2013 were produced and the time-series variability of cultivation areas for soybean, corn, and non-crop areas which are main classes in Mato Grosso was analyzed. In North Korea, crop type maps targeting Gangnam and Daehongdan, which are main cultivation areas of corn and potato were generated on a trial basis by considering the regional and crop cultivation characteristics. Then, cultivation areas were estimated. We reviewed the applicability of satellite imagery for field crop cultivation area in North Korea and produced the crop methodology manuals including the process of crop classification and the information to be considered. In domestic area, the applicability of satellite imagery was investigated in the main cultivation area of major vegetable crops such as chinese cabbage, radish, garlic, onion, and red pepper . And, crop type maps were generated on a trial basis and cultivation areas of target crops were estimated. Then, we produced a classification methodology manual which contains the whole process and some recommendations for field crop classification. As a basic study on determining a appropriate pixel size, statistical appropriate resolutions were calculated and quantitative analysis of the classification accuracy and area variations according to resolution changes were performed. Based on this, references for determining the appropriate pixel size were derived.
Expected Contribution
The crop type maps and cultivation areas which were derived from this research can be used as a basic data to grasp cultivation status of major grain exporting countries and they can be used as an important input data for predicting crop production. Also, the developed methodologies and various case studies can be references for crop classification in the future. This will contribute to increasing demand for remote sensing technology in agriculture field.
3협동과제 : 위성영상 자료처리 및 생물리모수 추정 알고리즘 통합 및 구현
Purpose&Contents
The main objectives are to develop automatic preprocessing system for estimating crop yield, implementation and integration of algorithms for estimating bio-index, and establishment of infrastructure for agricultural information system.
Results
In this study, preprocessing algorithms for satellite images were selected and automation of those algorithms are implemented.
In addition, in order to develop crop yield estimation models, the study was carried out through five steps: 1) literature review of researches on the estimation of crop yields in advanced countries such as the United States and Europe, 2) estimation of crop yield using satellite images, 3) WARM based crop yield estimation and its analysis, 4) SSAE based rice yield estimation in Jeolla-do region in South Korea, 5) CNN based crop (corn and soybean) yield estimation in the United States (Iowa and Illinois).
Moreover, agricultural information systems developed in other countries are investigated to develop an web-based agricultural information system. Thereafter, agricultural information system was developed which provides a crop report based on the satellite images.
Expected Contribution
The integration of the spatial information production algorithms required for estimating crop yield will effectively integrate the processes and provide a foundation for providing crop information system services. The implementation of bio-index estimation algorithm using satellite images will be an important factor for estimation of crop yield and monitoring of agricultural information environment, and it will contribute to increase efficiency through automated preprocessing of images. Also, it is able to select optimal estimation algorithm for each region and crop by comparative study of applying various algorithms including Deep Learning based algorithm, and thus, it is expected to effectively contribute to agricultural policy decisions. In addition, it will improve the spatial analysis performances through the development of the first web-based agricultural information system in South Korea, and the crop report based on the system will provide useful information to people working in agriculture fields.
4협동과제 : 농림업 중형위성 탑재체 개발을 위한 위성영상 활용 분석 및 전략 수립
Purpose&Contents
Satellite Image Utilization Analysis and Strategy Establishment for the Development of medium-sized Agricultural and Forestry Satellite Payload
Results
○ The main strategy for utilizing the medium-sized satellite in agricultural and forestry is as follows.
- Strategically securing the core technology of medium-sized satellite payload in agricultural and forestry
- Build political consultation system of development
- Build observation system and infrastructure of agricultural and forestry satellite
- Secure capability for development goals of medium-sized agricultural and forestry satellite
○ Simulation to analyze and verify operation performance of medium-sized agricultural and forestry Satellite payload
-The simulated target area is cropland on the Korean peninsula and observation period is 30 days. The results of the simulation, observation cumulative coverage is minimum 73.13% and revisit time is approximately within 2 days.
- In case of multi-sensor with body tilting ability to satellite platform, the single satellite performed 100% observation cumulative coverage within 18 days and the satellite constellation performed 100% observation cumulative coverage within 10 days.
Expected Contribution
- Suggest the practical use technique of satellite observation for the foundation of crop harvest information and production statistics systematized utilizing medium-sized agriculture and forestry satellite
- Analyze domestic and international satellite image utilization levels with current utilization of agricultural and forestry and propose the
(출처 : Summary 8p)
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