Model Assessment Multi-temporal Monitoring of Chinese Cabbage Growth using Low Altitude Remote Sensing System
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초록
It is necessary to monitor growth status of the crops due to continuous change of climatecausing insecurity in crop cultivation. Low altitude remote sensing(LARS) system is utilized toaccurately monitor the growth status of the crops. In this study, models for monitoring freshweight(FW), one of the major growth factors of Chinese cabbage, were developed withstructural indices and simple ratio calculated from bands in remotely sensed canopies by NIR,RE(imaging sensor A) and multispec-4c sensors(imaging sensor B) equipped with fixed-wingUAV depending on vegetation stages of normal planting(NP) and delayed planting(DP) Chinesecabbages. In results of imaging sensor A, the estimation models using structural indices andsimple ratio were divided into NP and DP due to different attribute of reflectance in canopieswith changed environment condition depending on different planting dates. The estimationmodels using simple ratio calculated by red edge and visible bands of NP showed betterperformance than other models, but RMSE was high. The models using simple ratio calculatedby same bands of DP were feasible to accurately estimate FW(R2 of more than 0.946 withRMSE of less than 169.5 g). In results of imaging sensor B, the estimation models usingstructural indices and simple ratio on DP were divided into low to intermediate FW andintermediate to high FW. As a result, estimation models of all structural indices and simpleratio in low to intermediate FW bands were advisable to estimate FW(R2 of more than 0.860with RMSE of less than 104.7 g). Estimation models of those calculated by red edge andvisible bands in intermediate to high FW were only possible to accurately estimate FW(R2 ofmore than 0.532 with RMSE of less than 400.7 g).
Abstract
It is necessary to monitor growth status of the crops due to continuous change of climatecausing insecurity in crop cultivation. Low altitude remote sensing(LARS) system is utilized toaccurately monitor the growth status of the crops. In this study, models for monitoring freshweight(FW), one of the major growth factors of Chinese cabbage, were developed withstructural indices and simple ratio calculated from bands in remotely sensed canopies by NIR,RE(imaging sensor A) and multispec-4c sensors(imaging sensor B) equipped with fixed-wingUAV depending on vegetation stages of normal planting(NP) and delayed planting(DP) Chinesecabbages. In results of imaging sensor A, the estimation models using structural indices andsimple ratio were divided into NP and DP due to different attribute of reflectance in canopieswith changed environment condition depending on different planting dates. The estimationmodels using simple ratio calculated by red edge and visible bands of NP showed betterperformance than other models, but RMSE was high. The models using simple ratio calculatedby same bands of DP were feasible to accurately estimate FW(R2 of more than 0.946 withRMSE of less than 169.5 g). In results of imaging sensor B, the estimation models usingstructural indices and simple ratio on DP were divided into low to intermediate FW andintermediate to high FW. As a result, estimation models of all structural indices and simpleratio in low to intermediate FW bands were advisable to estimate FW(R2 of more than 0.860with RMSE of less than 104.7 g). Estimation models of those calculated by red edge andvisible bands in intermediate to high FW were only possible to accurately estimate FW(R2 ofmore than 0.532 with RMSE of less than 400.7 g).
참고문헌 (14)
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