• Title/Summary/Keyword: smart farm map

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Satellite Imagery based Winter Crop Classification Mapping using Hierarchica Classification (계층분류 기법을 이용한 위성영상 기반의 동계작물 구분도 작성)

  • Na, Sang-il;Park, Chan-won;So, Kyu-ho;Park, Jae-moon;Lee, Kyung-do
    • Korean Journal of Remote Sensing
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    • v.33 no.5_2
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    • pp.677-687
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    • 2017
  • In this paper, we propose the use of hierarchical classification for winter crop mapping based on satellite imagery. A hierarchical classification is a classifier that maps input data into defined subsumptive output categories. This classification method can reduce mixed pixel effects and improve classification performance. The methodology are illustrated focus on winter cropsin Gimje city, Jeonbuk with Landsat-8 imagery. First, agriculture fields were extracted from Landsat-8 imagery using Smart Farm Map. And then winter crop fields were extracted from agriculture fields using temporal Normalized Difference Vegetation Index (NDVI). Finally, winter crop fields were then classified into wheat, barley, IRG, whole crop barley and mixed crop fields using signature from Unmanned Aerial Vehicle (UAV). The results indicate that hierarchical classifier could effectively identify winter crop fields with an overall classification accuracy of 98.99%. Thus, it is expected that the proposed classification method would be effectively used for crop mapping.

Analysis of soil moisture and drought in agricultural lands based on Terra MODIS using smart farm map and soil physical properties (스마트팜맵과 토양물리특성을 활용한 Terra MODIS 기반의 농지 토양수분 및 가뭄 현황 분석)

  • Jeehun Chung;Yonggwan Lee;Chan Kang;Jonghan Bang;Seongjoon Kim
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.375-375
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    • 2023
  • 본 연구는 농지를 대상으로 토양수분 및 가뭄 현황을 분석하는 데 그 목적이 있다. 토양수분을 파악하기 위해 Terra MODIS(Moderate Resolution Imaging Spectroradiometer) 위성영상기반의 토양수분 산정모형을 개발하였다. 해당 모형은 MODIS LST(Land Surface Temperature) 및 NDVI(Normalized Difference Deficit Index)를 기반으로 SCS-CN(Soil Conservation Service-Curve Number) 방법에서 착안한 수문학적 개념 5일 선행강우 및 무강우일수를 입력자료로 하며, 토양 종류 및 계절에 따른 토양수분의 특성을 고려하였다. 모형의 개발을 위해 MODIS LST 및 NDVI 영상을 2013년부터 2022년까지 각각 일별 및 16일 단위로 구축하였으며, 동 기간에 대해 전국 88개소의 기상청 종관기상관측소의 강수량 및 LST 자료를 수집하였다. MODIS LST는 실측 LST 자료를 활용해 조건부합성기법을 적용하여 상세화하였고, 수집된 강수량자료는 역거리가중법을 활용해 공간 보간을 수행하였다. 토양특성의 구분은 농촌진흥청에서 정밀토양도를 수집하여 활용하였다. 공간 분포된 토양수분에서 농지에 해당하는 토양수분을 추출하기 위해 스마트팜맵을 구축하고, 농지 속성에 해당하는 위치 정보를 조회 후 이를 시군구별로 평균하여 일별 평균 토양수분값을 산정하였다. 토양수분 기반의 가뭄 현황 분석을 위해 구축된 정밀토양도에서 작물 생장과 관련된 영구위조점 및 포장용수량을 활용해 5단계(정상, 관심, 주의, 경계, 심각)의 가뭄 위험도를 산정하였으며, 실제 가뭄 현황과의 비교를 통해 토양수분기반의 가뭄 위험도의 실효성을 검증하고자 한다.

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Sensitivity Analysis of Wake Diffusion Patterns in Mountainous Wind Farms according to Wake Model Characteristics on Computational Fluid Dynamics (전산유체역학 후류모델 특성에 따른 산악지형 풍력발전단지 후류확산 형태 민감도 분석)

  • Kim, Seong-Gyun;Ryu, Geon Hwa;Kim, Young-Gon;Moon, Chae-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.2
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    • pp.265-278
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    • 2022
  • The global energy paradigm is rapidly changing by centering on carbon neutrality, and wind energy is positioning itself as a leader in renewable energy-based power sources. The success of onshore and offshore wind energy projects focuses on securing the economic feasibility of the project, which depends on securing high-quality wind resources and optimal arrangement of wind turbines. In the process of constructing the wind farm, the optimal arrangement method of wind turbines considering the main wind direction is important, and this is related to minimizing the wake effect caused by the fluid passing through the structure located on the windward side. The accuracy of the predictability of the wake effect is determined by the wake model and modeling technique that can properly simulate it. Therefore, in this paper, using WindSim, a commercial CFD model, the wake diffusion pattern is analyzed through the sensitivity study of each wake model of the proposed onshore wind farm located in the mountainous complex terrain in South Korea, and it is intended to be used as basic research data for wind energy projects in complex terrain in the future.

Implementation of a Weather Hazard Warning System at a Catchment Scale (집수역 규모 기상위험 경보체계 구축)

  • Park, Ju Hyun;Kim, Seong Kee;Shin, Yong Soon;Ahn, Mun Il;Han, Yong Kyu
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.16 no.4
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    • pp.389-395
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    • 2014
  • This technical note describes about the base stages of technology implementation for establishing "Early Warning System for Weather Hazard Management in Climate-smart Agriculture" to national onsite service. First of all, a special weather report service at catchment was represented sequential risk of 810 units of catchment by spatial statistical methods to existing 150 counties units special weather report released in KMA. The second, chronic hazard alarm service based on daily data of 76 Synoptic stations was monitor about 810 Catchment of mid-long term lapse weather and represented as a relative risk index chronic hazard risk of this time in preparation for the climatological normal conditions in the same period. Finally, we establish the foundation for delivering individually calculated field specific in hazard risk about volunteer farmer of early warning service demonstration area in seomjin downstream watershed. These three types of information were built a near real-time map service on the VWORLD background map of Ministry of Land as superposed layers nationwide catchment and demonstration areas within the farm unit weather hazard.

Requirement Analysis for Agricultural Meteorology Information Service Systems based on the Fourth Industrial Revolution Technologies (4차 산업혁명 기술에 기반한 농업 기상 정보 시스템의 요구도 분석)

  • Kim, Kwang Soo;Yoo, Byoung Hyun;Hyun, Shinwoo;Kang, DaeGyoon
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.21 no.3
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    • pp.175-186
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    • 2019
  • Efforts have been made to introduce the climate smart agriculture (CSA) for adaptation to future climate conditions, which would require collection and management of site specific meteorological data. The objectives of this study were to identify requirements for construction of agricultural meteorology information service system (AMISS) using technologies that lead to the fourth industrial revolution, e.g., internet of things (IoT), artificial intelligence, and cloud computing. The IoT sensors that require low cost and low operating current would be useful to organize wireless sensor network (WSN) for collection and analysis of weather measurement data, which would help assessment of productivity for an agricultural ecosystem. It would be recommended to extend the spatial extent of the WSN to a rural community, which would benefit a greater number of farms. It is preferred to create the big data for agricultural meteorology in order to produce and evaluate the site specific data in rural areas. The digital climate map can be improved using artificial intelligence such as deep neural networks. Furthermore, cloud computing and fog computing would help reduce costs and enhance the user experience of the AMISS. In addition, it would be advantageous to combine environmental data and farm management data, e.g., price data for the produce of interest. It would also be needed to develop a mobile application whose user interface could meet the needs of stakeholders. These fourth industrial revolution technologies would facilitate the development of the AMISS and wide application of the CSA.