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| Filter results3 paper(s) found. |
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1. Precision Nutrient Management System Based on Ion and Crop Growth SensingAutomated sensing and variable-rate supply of nutrients in hydroponic solutions according to the status of crop growth would allow more efficient nutrient management for crop growth in closed systems. The Structure from Motion (SfM) method has risen as a new image sensing method to obtain 3D images of plants that can be used to estimate their growth, such as leaf cover area (LCA), plant height, and fresh weight. In this sense, sensor fusion technology combining ion-selective electrodes (ISEs)... W. Cho, D. Kim, C. Kang, H. Kim, J. Son, S. Chung, J. Jiang, H. Yun |
2. A Hyperlocal Machine Learning Approach to Estimate NDVI from SAR Images for Agricultural FieldsThe normalized difference vegetation index (NDVI) is a key parameter in precision agriculture used globally since the 1970s. The NDVI is sensitive to the biochemical and physiological properties of the crop and is based on the Red (~650 nm) and NIR (~850 nm) spectral bands. It is used as a proxy to monitor crop growth, correlates to the crop coefficient (Kc), leaf area index (LAI), crop cover, and more. Yet, it is susceptible to clouds and other atmospheric conditions which might alter... R. Pelta, O. Beeri, T. Shilo, R. Tarshish |
3. Multi-sensor Imagery Fusion for Pixel-by-pixel Water Stress MappingEvaluating water stress in agricultural fields is fundamental in irrigation decision-making, especially mapping the in-field water stress variability as it allows real-time detection of system failures or avoiding yield loss in cases of unplanned water stress. Water stress mapping by remote sensing imagery is commonly associated with the thermal or the short-wave-infra-red (SWIR) bands. However, integration of multi-sensors imagery such as radar imagery or sensors with only visible and near-infra-red... O. Beeri, R. Pelta, Z. Sade, T. Shilo |