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| Filter results7 paper(s) found. |
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1. sUAVS Technology For Better Monitoring Crop Status For Winter CanolaThe small-unmanned aircraft vehicles (sUAVS) are currently gaining more popularity in agriculture with uses including identification of weeds and crop production issues, diagnosing nutrient deficiencies, detection of chemical drift, scouting for pests, identification of biotic or abiotic stresses, and prediction of biomass and yield. Research information on the use of sUAVS have been published and conducted in crops such as rice, wheat, and corn, but the development of... I.A. Ciampitti, K. Shroyer, V. Prasad, A. Sharda, M.J. Stamm, H. Wang, K. Price, D. Mangus |
2. Data Fusion of Imagery from Different Satellites for Global and Daily Crop MonitoringSatellite-based Crop Monitoring is an important tool for decision making of irrigation, fertilization, crop protection, damage assessment and more. To allow crop monitoring worldwide, on a daily basis, data fusion of images taken by different satellites is required. So far, most researches on data fusion focus on retrospective analysis, while advanced crop monitoring capabilities mandate the use of data in real time mode. Therefore, our project goals were: (1) to build a data-fusion online system... O. Beeri, R. Pelta, S. Mey-tal, J. Raz |
3. Detecting Variability in Plant Water Potential with Multi-Spectral Satellite ImageryIrrigation Intelligence is a practice of precise irrigation, with the goal of providing crops with the right amount of water, at the right time, for optimized yield. One of the ways to achieve that, on a global scale, is to utilize Landsat-8 and Sentinel-2 images, providing together frequent revisit cycles of less than a week, and an adequate resolution for detection of 1 ha plots. Yet, in order to benefit from these advantages, it is necessary to examine the information that can be extracted... O. Beeri, S. May-tal, R. Rud, Y. Raz, R. Pelta |
4. 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 |
5. Economics of Field Size for Autonomous Crop MachinesField size constrains spatial and temporal management of agriculture with implications for farm profitability, field biodiversity and environmental performance. Large, conventional equipment struggles to farm small, irregularly shaped fields efficiently. The study hypothesized that autonomous crop machines would make it possible to farm small non-rectangular fields profitably, thereby preserving field biodiversity and other environmental benefits. Using the experience of the Hands Free Hectare... A. Al amin, J. Lowenberg‑deboer, K. Franklin, K. Behrendt |
6. 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 |
7. Profitability of Regenerative Cropping with Autonomous Machines: an Ex-ante Assessment of a British Crop-livestock FarmFarmers, agroecological innovators and research have suggested mixed cropping as a way to promote soil health. Mixing areas of different crops in the same field is another form of precision agriculture's spatial and temporal management. The simplest form of mixed cropping is strip cropping. In conventional mechanized farming use of mixed cropping practices (i.e., strip cropping, pixel cropping) is limited by labour availability, rising wage rates, and management complexity. Regenerative agriculture... A. Al amin, J. Lowenberg-deboer, K.F. Franklin, E. Dickin, J. Monaghan, K. Behrendt |