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Processing and Assessment of Spectrometric, Stereoscopic Imagery Collected Using a Lightweight UAV Spectral Camera for Precision Agriculture

机译:使用轻型无人机光谱相机对精密农业收集的光谱立体影像进行处理和评估

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Imaging using lightweight, unmanned airborne vehicles (UAVs) is one of the most rapidly developing fields in remote sensing technology. The new, tunable, Fabry-Perot interferometer-based (FPI) spectral camera, which weighs less than 700 g, makes it possible to collect spectrometric image blocks with stereoscopic overlaps using light-weight UAV platforms. This new technology is highly relevant, because it opens up new possibilities for measuring and monitoring the environment, which is becoming increasingly important for many environmental challenges. Our objectives were to investigate the processing and use of this new type of image data in precision agriculture. We developed the entire processing chain from raw images up to georeferenced reflectance images, digital surface models and biomass estimates. The processing integrates photogrammetric and quantitative remote sensing approaches. We carried out an empirical assessment using FPI spectral imagery collected at an agricultural wheat test site in the summer of 2012. Poor weather conditions during the campaign complicated the data processing, but this is one of the challenges that are faced in operational applications. The results indicated that the camera performed consistently and that the data processing was consistent, as well. During the agricultural experiments, promising results were obtained for biomass estimation when the spectral data was used and when an appropriate radiometric correction was applied to the data. Our results showed that the new FPI technology has a great potential in precision agriculture and indicated many possible future research topics.
机译:使用轻型无人飞行器(UAV)进行成像是遥感技术中发展最快的领域之一。新型,可调式,基于Fabry-Perot干涉仪(FPI)的光谱相机重量不到700克,可以使用轻型无人机平台收集具有立体重叠的光谱图像块。这项新技术具有很高的实用性,因为它为测量和监视环境开辟了新的可能性,这对于许多环境挑战而言变得越来越重要。我们的目标是研究精密农业中这种新型图像数据的处理和使用。我们开发了从原始图像到地理参考反射率图像,数字表面模型和生物量估计的整个处理链。该处理过程集成了摄影测量和定量遥感方法。我们使用2012年夏季在农业小麦试验场收集的FPI光谱图像进行了实证评估。活动期间恶劣的天气条件使数据处理复杂化,但这是操作应用程序面临的挑战之一。结果表明相机性能一致,数据处理也一致。在农业实验中,当使用光谱数据并且对数据进行了适当的辐射校正时,对于生物量估计获得了可喜的结果。我们的结果表明,新的FPI技术在精密农业中具有巨大潜力,并指出了许多可能的未来研究主题。

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