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| Filter results3 paper(s) found. |
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1. Estimating greensnap yield damage with canopy reflectance: a case studyGrain yield reduction caused by storm-induced plant breakage (green snap) occurs often in corn fields. With climate change and an increasing frequency in the occurrence of extreme weather events, it is essential to develop methods that can accurately estimate green snap damage, so growers can be properly compensated by insurance companies for yield loss. Because plant breakage also affects crop canopy reflectance, this case study aimed to characterize the changes in crop canopy reflectance... G. Dias Paiao, T.J. Nigon, F.G. Fernández, C. Cummings, S.L. Naeve |
2. Remote Sensing: from Plot Towards Landscape ScalesThe agricultural research sector is working to develop new technologies and decision support tools to sustainably increase food productivity, ensure global food security and decrease poverty. Precision Agriculture (PA) and specially Remote Sensing (RS) technologies have become more affordable in recent years. Cameras have become more compact and lighter, with improved spectral and spatial resolutions. The use of incoming light sensors allows for images to be automatically calibrated to surface... F. Rodrigues |
3. Assessment of Nitrogen and Phosphorus Content (NP) in Citrus Trees Using UAV-imagery Derived Vegetation Indices and Machine Learning AlgorithmsMonitoring nutrient status of citrus trees is fundamental to ensure optimum fruit yield and quality. However, this task is traditionally time-consuming and laborious. Unmanned Aerial Vehicles (UAVs), with their high temporal and spatial resolution imagery, are demonstrating a great potential to substitute traditional methods in assessing nutrient status of several crops, including citrus. In this study, we evaluated the performance of vegetation indices (VIs) derived from UAV multispectral images... Z. Abail, H. Benaouda, M. Chikhaoui, H. Benyahia, O. Iben Halima, M. Baraka, A. Douaik, H. Iaaich, A. Zouahri, F. Omari |
