본 연구는 무인기를 이용한 동계사료의 수량조사시 필요한 검량식의 작성을 위한 식생조사 및 분광측정의 적정 시기와, 작성된 검량식의 적용이 적절한 시기를 판단하기 위하여 고정식 자동 분광 측정장치를 개발하여 호밀, 총체보리, IRG를 대상으로 NDVI를 장기간 측정하였다. 그리고 NDVI가 최댓값이 되는 날을 기준으로 증가기간과 감소시간으로 기간을 나누어 건물수량 예측을 위한 검량식을 작성하고 검량식의 예측정확도를 각각 비교하였다. 조사결과 호밀, 총체보리, IRG는 각각 4월 8일, 4월 9일, 4월 5일에 NDVI가 최대치가 되었으며 NDVI 증가기간의 검량식은 결정계수(R2)는 각각 0.84, 0.84, 0.78로 높은 상관관계를 보였고 NDVI 감소기간에는 각각 0.00, 0.02, 0.27로 매우 낮게 나타났다. 따라서 NDVI 측정을 통한 건물수량 예측을 효율적으로 하기 위해서는 NDVI 변화를 정확히 측정할 필요가 있으며 고정식 자동 분광 측정 방법은 생육에 따른 NDVI의 정밀 측정에 효과적인것으로 판단된다.
본 연구는 무인기를 이용한 동계사료의 수량조사시 필요한 검량식의 작성을 위한 식생조사 및 분광측정의 적정 시기와, 작성된 검량식의 적용이 적절한 시기를 판단하기 위하여 고정식 자동 분광 측정장치를 개발하여 호밀, 총체보리, IRG를 대상으로 NDVI를 장기간 측정하였다. 그리고 NDVI가 최댓값이 되는 날을 기준으로 증가기간과 감소시간으로 기간을 나누어 건물수량 예측을 위한 검량식을 작성하고 검량식의 예측정확도를 각각 비교하였다. 조사결과 호밀, 총체보리, IRG는 각각 4월 8일, 4월 9일, 4월 5일에 NDVI가 최대치가 되었으며 NDVI 증가기간의 검량식은 결정계수(R2)는 각각 0.84, 0.84, 0.78로 높은 상관관계를 보였고 NDVI 감소기간에는 각각 0.00, 0.02, 0.27로 매우 낮게 나타났다. 따라서 NDVI 측정을 통한 건물수량 예측을 효율적으로 하기 위해서는 NDVI 변화를 정확히 측정할 필요가 있으며 고정식 자동 분광 측정 방법은 생육에 따른 NDVI의 정밀 측정에 효과적인것으로 판단된다.
In this study we developed the ground-based multispectral camera system to determine proper period to build and apply the calibration equation for dry matter of winter forage corps monitoring by unmanned aerial vehicle (UAV). Normalized difference vegetation index (NDVI) of rye, whole barley and Ita...
In this study we developed the ground-based multispectral camera system to determine proper period to build and apply the calibration equation for dry matter of winter forage corps monitoring by unmanned aerial vehicle (UAV). Normalized difference vegetation index (NDVI) of rye, whole barley and Italian ryegrass (IRG) were measured and the growth period was divide by NDVI increasing period and decreasing period. Day of the maximum NDVI value of rye, whole barley and IRG were 8th, 9th and 5th April 2020. Regression analysis showed that the correlation coefficients (R2) between dry matter and NDVI were 0.84, 0.84, 0.78 during NDVI increasing period and 0.00, 0.02, 0.27 during NDVI decreasing period. Therefore, detailed NDVI monitoring is required to determine the proper period to build and apply the calibration equation and the ground-based multispectral camera system was effective tool for detailed NDVI monitoring.
In this study we developed the ground-based multispectral camera system to determine proper period to build and apply the calibration equation for dry matter of winter forage corps monitoring by unmanned aerial vehicle (UAV). Normalized difference vegetation index (NDVI) of rye, whole barley and Italian ryegrass (IRG) were measured and the growth period was divide by NDVI increasing period and decreasing period. Day of the maximum NDVI value of rye, whole barley and IRG were 8th, 9th and 5th April 2020. Regression analysis showed that the correlation coefficients (R2) between dry matter and NDVI were 0.84, 0.84, 0.78 during NDVI increasing period and 0.00, 0.02, 0.27 during NDVI decreasing period. Therefore, detailed NDVI monitoring is required to determine the proper period to build and apply the calibration equation and the ground-based multispectral camera system was effective tool for detailed NDVI monitoring.
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