Proceedings :: International Society of Precision Agriculture

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Taubinger, L

Snevajs, H

Sanchez, S

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Authors

Amaral, L.R

Molin, J.P

Taubinger, L

Osann, A

Campos, I

Calera, M

Plaza, C

Bodas, V

Calera, A

Villodre, J

Campoy, J

Sanchez, S

Jimenez, N

Lopez, H

Charvat, K

Berzins, R

Bergheim, R

Zadrazil, F

Macura, J

Langovskis, D

Snevajs, H

Kubickova, H

Horakova, S

Charvat Jr., K

Topics

Proximal Sensing in Precision Agriculture

In-Season Nitrogen Management

Geospatial Data

Type

Poster

Oral

Year

2012

2018

2022

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Filter results3 paper(s) found.
1. Vegetation Indices from Active Crop Canopy Sensor and Their Potential Interference Factors on Sugarcane Among the inputs usually used in the sugarcane production the nitrogen (N) is the most significant. With the use of ground-based canopy sensors to obtain vegetation indexes (VI), it is possible to obtain recommendations of nutrient supply in... L.R. Amaral, J.P. Molin, L. Taubinger Download paper
2. Practical Prescription of Variable Rate Fertilization Maps Using Remote Sensing Based Yield Potential This paper describes a practical approach for the prescription of variable rate fertilization maps using remote sensing data (RS) based on satellite platforms, Landsat 8 and Sentinel-2 constellation. The methodology has been developed and evaluated in Albacete, Spain, in the framework of the project FATIMA (http://fatima-h2020.eu/). The global approach considers the prescription of N management prior to the growing season, based on a spatially distributed N balance. Although the diagnosis of N... A. Osann, I. Campos, M. Calera, C. Plaza, V. Bodas, A. Calera, J. Villodre, J. Campoy, S. Sanchez, N. Jimenez, H. Lopez Download paper
3. Map Whiteboard As Collaboration Tool for Smart Farming Advisory Services Precision agriculture, a branch of smart farming, holds great promise for modernization of European agriculture both in terms of environmental sustainability and economic outlook. The vast data archives made available through Copernicus and related infrastructures, combined with a low entry threshold into the domain of AI-technologies has made it possible, if not outright easy, to make meaningful predictions that divides individual agricultural fields into zones where variable rates... K. Charvat, R. Berzins, R. Bergheim, F. Zadrazil, J. Macura, D. Langovskis, H. Snevajs, H. Kubickova, S. Horakova, K. Charvat jr. Download paper

Filter results3 paper(s) found.

1. Vegetation Indices from Active Crop Canopy Sensor and Their Potential Interference Factors on Sugarcane

Among the inputs usually used in the sugarcane production the nitrogen (N) is the most significant. With the use of ground-based canopy sensors to obtain vegetation indexes (VI), it is possible to obtain recommendations of nutrient supply in... L.R. Amaral, J.P. Molin, L. Taubinger

Download paper

2. Practical Prescription of Variable Rate Fertilization Maps Using Remote Sensing Based Yield Potential

This paper describes a practical approach for the prescription of variable rate fertilization maps using remote sensing data (RS) based on satellite platforms, Landsat 8 and Sentinel-2 constellation. The methodology has been developed and evaluated in Albacete, Spain, in the framework of the project FATIMA (http://fatima-h2020.eu/). The global approach considers the prescription of N management prior to the growing season, based on a spatially distributed N balance. Although the diagnosis of N... A. Osann, I. Campos, M. Calera, C. Plaza, V. Bodas, A. Calera, J. Villodre, J. Campoy, S. Sanchez, N. Jimenez, H. Lopez

Download paper

3. Map Whiteboard As Collaboration Tool for Smart Farming Advisory Services

Precision agriculture, a branch of smart farming, holds great promise for modernization of European agriculture both in terms of environmental sustainability and economic outlook. The vast data archives made available through Copernicus and related infrastructures, combined with a low entry threshold into the domain of AI-technologies has made it possible, if not outright easy, to make meaningful predictions that divides individual agricultural fields into zones where variable rates... K. Charvat, R. Berzins, R. Bergheim, F. Zadrazil, J. Macura, D. Langovskis, H. Snevajs, H. Kubickova, S. Horakova, K. Charvat jr.

Download paper