Andrew E. Suyker

Orcid: 0000-0002-4394-1607

Affiliations:
  • University of Nebraska-Lincoln, School of Natural Resources, Lincoln, NE, USA


According to our database1, Andrew E. Suyker authored at least 12 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Effect of Biomass Water Dynamics in Cosmic-Ray Neutron Sensor Observations: A Long-Term Analysis of Maize-Soybean Rotation in Nebraska.
Sensors, July, 2024

2022
Evaluating Optical Remote Sensing Methods for Estimating Leaf Area Index for Corn and Soybean.
Remote. Sens., 2022

2021
Towards Routine Mapping of Crop Emergence within the Season Using the Harmonized Landsat and Sentinel-2 Dataset.
Remote. Sens., 2021

2020
Modeling Gross Primary Production of Midwestern US Maize and Soybean Croplands with Satellite and Gridded Weather Data.
Remote. Sens., 2020

PhenoCrop: An integrated satellite-based framework to estimate physiological growth stages of corn and soybeans.
Int. J. Appl. Earth Obs. Geoinformation, 2020

2019
Net Ecosystem Exchange (NEE) simulation in maize using artificial neural networks.
IFAC J. Syst. Control., 2019

SMAP Vegetation Optical Depth is Directly Proportional to Crop Water in the US Corn Belt.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

2018
Latent heat and sensible heat flux simulation in maize using artificial neural networks.
Comput. Electron. Agric., 2018

Imaging Spectrometry and Fluorometry in Support of Flex: What Can We Learn from Multi-Scale Experiments?
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2016
Effects of the partitioning of diffuse and direct solar radiation on satellite-based modeling of crop gross primary production.
Int. J. Appl. Earth Obs. Geoinformation, 2016

2013
A Production Efficiency Model-Based Method for Satellite Estimates of Corn and Soybean Yields in the Midwestern US.
Remote. Sens., 2013

2008
Synoptic Monitoring of Gross Primary Productivity of Maize Using Landsat Data.
IEEE Geosci. Remote. Sens. Lett., 2008


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