Proceedings
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| Filter results8 paper(s) found. |
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1. Multi, Super Or Hyper Spectral Data, The Right Way From Research Toward Application In AgricultureRemote sensing provides opportunities for diverse applications in agriculture. One consideration of maximizing the utility of these applications, is the need to choose the most efficient spectral resolution. Picking the optimal spectral resolutions (multi, super or hyper) for a specific application is also influenced by other factors (e.g., spatial and temporal resolutions) of the utilized device. This work focuses mainly on... D.J. Bonfil, I. Herrmann, A. Pimstein, A. Karnieli |
2. Weeds Detection By Ground-level Hyperspectral ImagingWeeds are a severe pest in agriculture, causing extensive yield loss. Weed control of grass and broadleaf weeds is commonly performed by applying selective herbicides homogeneously all over the field. As presented in several studies, applying the herbicide only where needed has economical as well as environmental benefits. Combining remote sensing tools and techniques with the concept of precision agriculture has the potential to automatically... U. Shapira , I. Herrmann, A. Karnieli, D.J. Bonfil |
3. Assessment Of Field Crops Leaf Area Index By The Red-edge Inflection Point Derived From Venus BandsThe red-edge region of leaves spectrum (700-800 nm) corresponds to the spectral region that connects the chlorophyll absorption in the red and the amplified reflectance caused by the leaf structure in the near infrared (NIR) parts of the spectrum. At the canopy level, the inflection point of the red-edge slope is influenced by the plant’s condition that is related to several properties, including Leaf Area Index (LAI) and plant nutritional status.... I. Herrmann, A. Pimstein, A. Karnieli, Y. Cohen, V. Alchanatis , D.J. Bonfil |
4. Typology Of Farms And Regions In EU States Assessing The Impacts Of Precision Farming-technologiesA typology is developed describing the typical farms and the agricultural regions in Europe which presumably would apply Precision Farming technologies (PFT) and how. The typology focuses on the potential agronomic (cropping practices) benefits of PFT in crop production. Precision Farming covers a wide range of technologies for different sectors in agriculture. They differ in techniques, equipment and procedures and form core elements of information oriented production of various crops .... L. Herold, B. Poelling, A. Wurbs, A. Werner |
5. Ground Level Hyperspectral Imagery For Weeds Detection In Wheat FieldsWeeds are a severe pest in agriculture resulting in extensive yield loss. Applying precise weed control has economical as well as environmental benefits. Combining remote sensing tools and techniques with the concept of precision agriculture has the potential to automatically locate and identify weeds in order to allow precise control. The objective of the current work is to detect annual... D.J. Bonfil, U. Shapira, A. Karnieli, I. Herrmann, S. Kinast |
6. Application of RS, GPS & GIS in a National Monitoring System for Accurate Range AssessmentSustainable use of rangelands requires information on vegetation cover and its changes through time, condition trend and the effect of climate as well as management practices. The main objective of this research was showing variation of vegetation parameters,... H.P. Arzani, M.S. Azimi, S.D. kaboli, H.M. mirdavodi, M.M. Borhani, J.M. Abdollahi, M.D. farahpour |
7. Rapidscan And CropCircle Radiometers: Opportunities And Limitation In Assessing Wheat Biomass And NitrogenRemote sensing is a promising technology that provides information about the crop's physiological and phenological status. This information is based on the spectral absorption and scattering features of the plants. Many different vegetation indices (VI) have been developed, and are in use to estimate quantitatively the relationship between multi and hyper-spectral reflectance and effective crop physiological parameters, i.e. nitrogen (N) content, biomass, leaf area index (LAI). The CropCircle... A.A. Gitelson, D.J. Bonfil |
8. Data-driven Agriculture and Sustainable Farming: Friends or Foes?Sustainability in our food and fiber agriculture systems is inherently knowledge intensive. It is more likely to be achieved by using all the knowledge, technology, and resources available, including data-driven agricultural technology and precision agriculture methods, than by relying entirely on human powers of observation, analysis, and memory following practical experience. Data collected by sensors and digested by artificial intelligence (AI) can help farmers learn about synergies... O. Rozenstein, Y. Cohen, V. Alchanatis , K. Behrendt, D.J. Bonfil, G. Eshel, A. Harari, W.E. Harris, I. Klapp, Y. Laor, R. Linker, T. Paz-kagan, S. Peets, M.S. Rutter, Y. Salzer, J. Lowenberg-deboer |