A Comparison of Several UAV-Based Multispectral Imageries in Monitoring Rice Paddy (A Case Study in Paddy Fields in Tottori Prefecture, Japan)

Abstract

In recent years, unmanned aerial vehicles (UAVs) have been actively applied in the agricultural sector. Several UAVs equipped with multispectral cameras have become available on the consumer market. Multispectral data are informative and practical for evaluating the greenness and growth status of vegetation as well as agricultural crops. The precise monitoring of rice paddy, especially in the Asian region, is crucial for optimizing profitability, sustainability, and protection of agro-ecological services. This paper reports and discusses our findings from experiments conducted to test four different commercially available multispectral cameras (Micesense RedEdge-M, Sentera Single NDVI, Mapir Survey3, and Bizworks Yubaflex), which can be mounted on a UAV in monitoring rice paddy. The survey has conducted in the typical paddy field area located in the alluvial plain in Tottori Prefecture, Japan. Six different vegetation indices (NDVI, BNDVI, GNDVI, VARI, NDRE and MCARI) captured by UAVs were also compared and evaluated monitoring contribution at three different rice cropping phases. The results showed that the spatial distribution of NDVI collected by each camera is almost similar in paddy fields, but the absolute values of NDVI differed significantly from each other. Among them, the Sentera camera showed the most reasonable NDVI values of each growing phase, indicating 0.49 in the early reproductive phase, 0.62 in the late reproductive stage, and 0.38 in the ripening phase. On the other hand, compared to the most commonly used NDVI, VARI which can be calculated from only visible RGB bands, can be used as an easy and effective index for rice paddy monitoring.

Yield Prediction Using NDVI Values from GreenSeeker and MicaSense Cameras at Different Stages of Winter Wheat Phenology

“…The hypersensitivity of a camera can be a disadvantage in cases where a plant has too high biomass, and the NDVI values produced by the MicaSense camera can no longer monitor changes in biomass after a certain period [53]. Dimyati et al [54] examined paddy fields at different phenological stages in 2023 using four different multispectral cameras, and the data collected were compared using five different vegetation indices and NDVI. The NDVI values obtained with the MicaSense camera were by far the highest in all three phenological stages, i.e., 0.9 in the heading stage and 0.8 at the ripening phase [54].…”

“…Dimyati et al [54] examined paddy fields at different phenological stages in 2023 using four different multispectral cameras, and the data collected were compared using five different vegetation indices and NDVI. The NDVI values obtained with the MicaSense camera were by far the highest in all three phenological stages, i.e., 0.9 in the heading stage and 0.8 at the ripening phase [54]. According to our measurements and results, the highest NDVI values were also at the booting stage; moreover, in the two systems that have been compared, MicaSense images resulted in higher values than GreenSeeker data.…”

Analisis Usia Tanaman Padi Berdasarkan Berbagai Indeks Vegetasi Menggunakan Citra Kamera

“…Metode tersebut dapat mendeteksi perubahan akibat akumulasi biomassa dan sensitif terhadap jumlah klorofil pada daun. Hasil penelitian dari (Dimyati et al, 2023) menyatakan bahwa pola distribusi spasial dari nilai indeks VARI di lahan padi sangat mirip dengan NDVI, dan sangat berkorelasi pada setiap tahap pertumbuhan. Sehingga secara signifikan, indeks VARI berbasis RGB dan juga NDVI dapat digunakan untuk pemantauan fase pertumbuhan tanaman padi.…”

Monitoring of a Productive Blue-Green Roof Using Low-Cost Sensors

“…To monitor crop growth, various investigations on nondestructive techniques have been investigated, some utilizing the 2D or 3D image-based system [ 24 , 30 , 31 ]. Stereo vision [ 32 ], LiDAR [ 33 ], multispectral [ 34 , 35 , 36 , 37 , 38 ], and hyperspectral [ 37 , 38 , 39 , 40 ] imaging have also been explored by the mentioned research and applications, although their expenses are quite high in terms of instrumentation costs. Depth cameras have also been recently used by studies [ 28 , 41 , 42 , 43 ] in laboratory settings to estimate plant height and measure leaf area, leaf length, or plant biomass.…”