Khalesi Fatemeh, Ahmed Imran, Daponte Pasquale, Picariello Francesco, De Vito Luca, Tudosa Ioan
Department of Engineering, University of Sannio, 82100 Benevento, Italy.
Sensors (Basel). 2024 Apr 24;24(9):2696. doi: 10.3390/s24092696.
This paper proposes a workflow to assess the uncertainty of the Normalized Difference Vegetation Index (NDVI), a critical index used in precision agriculture to determine plant health. From a metrological perspective, it is crucial to evaluate the quality of vegetation indices, which are usually obtained by processing multispectral images for measuring vegetation, soil, and environmental parameters. For this reason, it is important to assess how the NVDI measurement is affected by the camera characteristics, light environmental conditions, as well as atmospheric and seasonal/weather conditions. The proposed study investigates the impact of atmospheric conditions on solar irradiation and vegetation reflection captured by a multispectral UAV camera in the red and near-infrared bands and the variation of the nominal wavelengths of the camera in these bands. Specifically, the study examines the influence of atmospheric conditions in three scenarios: dry-clear, humid-hazy, and a combination of both. Furthermore, this investigation takes into account solar irradiance variability and the signal-to-noise ratio (SNR) of the camera. Through Monte Carlo simulations, a sensitivity analysis is carried out against each of the above-mentioned uncertainty sources and their combination. The obtained results demonstrate that the main contributors to the NVDI uncertainty are the atmospheric conditions, the nominal wavelength tolerance of the camera, and the variability of the NDVI values within the considered leaf conditions (dry and fresh).
本文提出了一种工作流程，用于评估归一化植被指数（NDVI）的不确定性，NDVI是精准农业中用于确定作物健康状况的关键指标。从计量学角度来看，评估植被指数的质量至关重要，植被指数通常是通过处理多光谱图像来测量植被、土壤和环境参数而获得的。因此，评估相机特性、光照环境条件以及大气和季节/天气条件如何影响NDVI测量非常重要。本研究调查了大气条件对多光谱无人机相机在红波段和近红外波段捕获的太阳辐射和植被反射的影响，以及相机在这些波段的标称波长变化。具体而言，该研究考察了三种情况下大气条件的影响：干燥晴朗、潮湿有雾以及二者的组合。此外，该调查还考虑了太阳辐照度的变化和相机的信噪比（SNR）。通过蒙特卡洛模拟，针对上述每个不确定性来源及其组合进行了敏感性分析。所得结果表明，NDVI不确定性的主要来源是大气条件、相机的标称波长容差以及在所考虑的叶片条件（干燥和新鲜）下NDVI值的变化。
