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Rud, R

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Authors

Nigon, T.J

Rosen, C

Mulla, D

Cohen, Y

Alchanatis, V

Rud, R

Cohen, Y

Alchanatis, V

Heuer, B

Lemcoff, H

Sprintsin, M

Rosen, C

Mulla, D

Nigon, T

Dar, Z

Cohen, A

Levi, A

Brikman, R

Markovits, T

Rud, R

Beeri, O

Mey-tal , S

Beeri, O

May-tal, S

Rud, R

Raz, Y

Pelta, R

Beeri, O

May-tal, S

Raz, J

Rud, R

Topics

Remote Sensing Applications in Precision Agriculture

Proximal and Remote Sensing of Soil and Crop (including Phenotyping)

Decision Support Systems

Type

Poster

Oral

Year

2012

2018

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Authors

Filter results5 paper(s) found.
1. Hyperspectral Imagery for the Detection of Nitrogen Stress in Potato for In-season Management ... T.J. Nigon, C. Rosen, D. Mulla, Y. Cohen, V. Alchanatis, R. Rud Download paper
2. Evaluating Water Status in Potato Fields Using Combined Information from RGB and Thermal Aerial Images Potato yield and quality are highly dependent on an adequate supply of water. In this study the combined information from RGB and thermal aerial images to evaluate... Y. Cohen, V. Alchanatis, B. Heuer, H. Lemcoff, M. Sprintsin, C. Rosen, D. Mulla, T. Nigon, Z. Dar, A. Cohen, A. Levi, R. Brikman, T. Markovits, R. Rud Download paper
3. Designated Value for a Field Polygon Based on Imagery Data: A Case Study of Crop Vigor in Agricultural Application for Irrigation Any irrigation action for a field management zone, which is based on images, requires a transformation into single value. Since data distribution is ab-normal in an image, using a mean value to estimate the crop coefficient (Kc), an overlaid polygon may not represent properly its water demand. Therefore, this project’s aim was to examine to which extent different statistics of potential designated values will affect an estimated Kc, and consequently affect irrigation practices. Satellite... R. Rud, O. Beeri, S. Mey-tal Download paper
4. Detecting Variability in Plant Water Potential with Multi-Spectral Satellite Imagery Irrigation 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 Download paper
5. Field Test of a Satellite-Based Model for Irrigation Scheduling in Cotton Cotton irrigation in Israel began in the mid-1950s. It is based on an irrigation protocol developed over dozens of years of cotton farming in Israel, and proved to provide among the world's best cotton yield results. In this experiment, we examined the use of an irrigation recommendation system that is based on satellite imagery and hyper-local meteorological data, "Manna treatment", compared to the common irrigation protocols in Israel, which use a crop coefficient (Kc) table and... O. Beeri, S. May-tal, J. Raz, R. Rud

Filter results5 paper(s) found.

1. Hyperspectral Imagery for the Detection of Nitrogen Stress in Potato for In-season Management

... T.J. Nigon, C. Rosen, D. Mulla, Y. Cohen, V. Alchanatis, R. Rud

Download paper

2. Evaluating Water Status in Potato Fields Using Combined Information from RGB and Thermal Aerial Images

Potato yield and quality are highly dependent on an adequate supply of water. In this study the combined information from RGB and thermal aerial images to evaluate... Y. Cohen, V. Alchanatis, B. Heuer, H. Lemcoff, M. Sprintsin, C. Rosen, D. Mulla, T. Nigon, Z. Dar, A. Cohen, A. Levi, R. Brikman, T. Markovits, R. Rud

Download paper

3. Designated Value for a Field Polygon Based on Imagery Data: A Case Study of Crop Vigor in Agricultural Application for Irrigation

Any irrigation action for a field management zone, which is based on images, requires a transformation into single value. Since data distribution is ab-normal in an image, using a mean value to estimate the crop coefficient (Kc), an overlaid polygon may not represent properly its water demand. Therefore, this project’s aim was to examine to which extent different statistics of potential designated values will affect an estimated Kc, and consequently affect irrigation practices. Satellite... R. Rud, O. Beeri, S. Mey-tal

Download paper

4. Detecting Variability in Plant Water Potential with Multi-Spectral Satellite Imagery

Irrigation 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

Download paper

5. Field Test of a Satellite-Based Model for Irrigation Scheduling in Cotton

Cotton irrigation in Israel began in the mid-1950s. It is based on an irrigation protocol developed over dozens of years of cotton farming in Israel, and proved to provide among the world's best cotton yield results. In this experiment, we examined the use of an irrigation recommendation system that is based on satellite imagery and hyper-local meteorological data, "Manna treatment", compared to the common irrigation protocols in Israel, which use a crop coefficient (Kc) table and... O. Beeri, S. May-tal, J. Raz, R. Rud