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Alchanati, V

Abonyi, J

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Authors

Sisák, I

Benő, A

Szabó, K

Kocsis, M

Abonyi, J

Goldwasser, Y

Alchanati, V

Goldshtein, E

Cohen, Y

Gips, A

Nadav, I

Topics

Decision Support Systems

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

Type

Poster

Oral

Year

2018

2022

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Filter results2 paper(s) found.
1. Reverse Modelling of Yield-Influencing Soil Variables in Case of Few Soil Data Our hypothesis was that simple models can be applied to predict yield by using only those yield data which spatially coincide with the soil data and the remaining yield data and the models can be used to test different sampling and interpolation approaches commonly applied in precision agriculture and to better predict soil variables at not observed locations. Three strategies for composite sample collection were compared in our study. Point samples were taken 1.) along lines within homogenous... I. Sisák, A. Benő, K. Szabó, M. Kocsis, J. Abonyi Download paper
2. The Use of Spatial and Temporal Measures to Enhance the Sensitivity of Satellite-based Spectral Vegetation Indices to (Water) Stress in Maize Fields Climate change and water scarcity are reducing the available irrigation water for agriculture thus turning it into a limited resource. Today calculating and estimating crop water requirements are achieved through the ETc FAO-56 model where the effect of climate on crop water requirement is determined through the water evaporation from the soil and plant (ETref), and a calendar crop coefficient (Kc). Models that... Y. Goldwasser, V. Alchanati, E. Goldshtein, Y. Cohen, A. Gips, I. Nadav Download paper

Filter results2 paper(s) found.

1. Reverse Modelling of Yield-Influencing Soil Variables in Case of Few Soil Data

Our hypothesis was that simple models can be applied to predict yield by using only those yield data which spatially coincide with the soil data and the remaining yield data and the models can be used to test different sampling and interpolation approaches commonly applied in precision agriculture and to better predict soil variables at not observed locations. Three strategies for composite sample collection were compared in our study. Point samples were taken 1.) along lines within homogenous... I. Sisák, A. Benő, K. Szabó, M. Kocsis, J. Abonyi

Download paper

2. The Use of Spatial and Temporal Measures to Enhance the Sensitivity of Satellite-based Spectral Vegetation Indices to (Water) Stress in Maize Fields

Climate change and water scarcity are reducing the available irrigation water for agriculture thus turning it into a limited resource. Today calculating and estimating crop water requirements are achieved through the ETc FAO-56 model where the effect of climate on crop water requirement is determined through the water evaporation from the soil and plant (ETref), and a calendar crop coefficient (Kc). Models that... Y. Goldwasser, V. Alchanati, E. Goldshtein, Y. Cohen, A. Gips, I. Nadav

Download paper