시간 안정성 기반 통계학적 방법을 이용한 토양수분 대표지점 선정 연구
Determination of the Representative Location in Soil Moisture Distribution Using Statistical Methods Based on Temporal Stability
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초록
전 세계적으로 급격하게 성장하는 스마트농업의 중요 요소 중 하나인 자동 관개시스템은 토양수분 센서에서 계측한 데이터를 기반으로 관개시점과관개량을 판단하기 때문에 토양수분 센서의 설치가 필수적이다. 하지만 국내의 경우 토양을 고려하지 않고 단순히 포장의 가운데에 센서를 설치하는등 토양수분 센서의 설치 위치에 대한 기준이 마련되어 있지 않아 토양수분 계측 위치에 관한 기준 검토가 필요하다. 본 연구에서 통계학적 방법을이용하여 토양수분의 대표 계측지점을 선정 연구를 수행하였다. 토양은 수직적 또는 수평적으로 불균일성을 갖기에 구명이 쉽지 않다. 따라서포장 전체에 걸쳐 지속해서 편향이 발생하지만 특정 위치에서의 평균 토양수분이 시간에 따라 유지한다는 시간 안정성 개념을 기반으로, 평균토양수분을 나타내는 대표지점 선정 연구를 수행하였다. 토양수분을 측정하기 위한 시스템을 제작하였고, TDR (Time Domain Reflectometry)센서를 이용하여 총 30개 지점을 측정하였다. 2023년 5월부터 8월까지 측정한 날짜·지점별 데이터를 이용하여, 지점의 편향을 정량화하여 식별할수 있는 MRD (Mean Relative Difference, 평균상대차이)와 측정의 정밀도를 나타내는 RD (Relative Difference, 상대차이)의 SDRD (StandardDeviation of Relative Difference, 표준편차)를 산출하고, MRD와 SDRD를 통합한 지표로써 RMSE (Root Mean Square Error, 평균제곱근오차)를 구하여, 시간 안정성이 가장 높은 지점인 RMSE의 수치가 최소인 지점을 대표지점으로 선정하였다. 토양수분 센서로 측정한 데이터를 사용하여지점별 RMSE를 산출하고 비교하여, 평균적인 토양수분을 나타내는 대표지점을 선정할 수 있음을 확인하였다.
Abstract
The automatic irrigation system, one of the important elements of smart agriculture that is multiplying worldwide, determines theset point and amount of irrigation based on data measured by soil moisture sensors. Therefore, installing a soil moisture sensor is essential. However, in Korea, there are no standards for the installation location of soil moisture sensors, such as simply installing the sensorin the center of the field without considering the soil. So, it is necessary to review standards regarding the location of soil moisturemeasurement. In this study, a study was conducted to select representative location in soil moisture distribution using statistical methods. Soil is not easy to identify because it is vertically or horizontally heterogeneous. Based on the concept of temporal stability, whichstates that the average soil moisture at a specific location is maintained over time even though the soil moisture bias occurs continuouslythroughout the field, a study was conducted to select the representative location that presents the average soil moisture. A system wasmade to measure soil moisture, and a total of 30 points were measured using TDR sensors. MRD, which can be identified by quantifyingthe soil moisture bias of the location, and SDRD of RD, which indicates the precision of measurement, were calculated using data by date and location measured from May to August 2023. RMSE was calculated as an integrated indicator of MRD and SDRD, andthe location with the highest temporal stability was the location with the minimum RMSE value, and this location was selected as therepresentative location. It was confirmed that a representative location presenting average soil moisture could be selected by calculatingand comparing RMSE for each location using data measured by soil moisture sensors.
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