Proceedings

Find matching any: Reset
Pal, P
Sanchez, S
Add filter to result:
Authors
Osann, A
Campos, I
Calera, M
Plaza, C
Bodas, V
Calera, A
Villodre, J
Campoy, J
Sanchez, S
Jimenez, N
Lopez, H
Bhandari, M
Landivar, J
Ghansah, B
Zhao, L
Landivar, J
Pal, P
Topics
In-Season Nitrogen Management
Artificial Intelligence (AI) in Agriculture
Type
Oral
Year
2018
2024
Home » Authors » Results

Authors

Filter results2 paper(s) found.

1. 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

2. Cotton Yield Estimation Using High-resolution Satellite Imagery Obtained from Planet SkySat

Satellite images have been used to monitor and estimate crop yield. Over the years, significant improvements on spatial resolution have been made where ortho images can be generated at 30-centimeter resolution. In this study, we wanted to explore the potential use of Planet SKYSAT satellite system for cotton yield predictions. This system provided imagery data at 50 centimeters resolution, and we collected data 14 times during the season. The data were collected from two different cotton... M. Bhandari