Datasets

Subject
Creator
Type
Date

subject: Remote Sensing subject: Corn

Total is 30 Results
Iowa Intensive Test Site 0893 (801237)

10.4231/R7FJ2DQB

Marvin E. Bauer

04/01/2015

The purpose of the experiment is to study the spectral characteristics and separability of corn, soybeans, oats, and pasture as a function of growth stage and cultural practices.

Agriculture Corn Crop Science Crops FSS Grass helicopter mounted Field Spectrometer System Laboratory for Applications of Remote Sensing LARS Remote Sensing soil Soil Science solar illumination Soybeans spectral observations

Purdue Agronomy Farm Corn Hybrid (811801)

10.4231/R76H4FCH

Craig S. T. Daughtry

07/22/2015

Purdue Agronomy Farm Corn Hybrid test

Agriculture Corn Crop Science Crops Exotech 100 LARS radiometer Remote Sensing Soil Science solar illumination spectral observations

Iowa Intensive Test Site 0893 (811237)

10.4231/R7T72FD1

Marvin E. Bauer

07/22/2015

The objective of this experiment was to provide a data set which can be used as an intermediate level of extrapolation between data collected from controlled experimental plots at field research stations and data collection by satellite scanners.

Agriculture Corn Crop Science Crops FSS Grass LARS Remote Sensing soil Soil Science solar illumination Soybeans spectral observations spectrometer

North Dakota Intensive Test Site 0817 (811247)

10.4231/R7PG1PP9

Marvin E. Bauer

07/22/2015

The objective of this experiment was to provide a data set which can be used as an intermediate level of extrapolation between data collected from controlled experimental plots at field research stations and data collection by satellite scanners

Agriculture barley Corn Crop Science Crops durum wheat FSS LARS oats Remote Sensing Soil Science solar illumination Soybeans spectral observations spring wheat sugar beets Sunflower

Purdue Agronomy Farm Corn Hybrid ( 811801)

10.4231/R7JQ0XZK

Craig S. T. Daughtry

07/22/2015

Spectral observation of the Farm Corn Hybrid

Agriculture Corn Crop Science Crops Exotech 100 LARS radiometer Remote Sensing Soil Science solar illumination spectral observations

Purdue Agronomy Corn Sun-View Angle (821802)

10.4231/R78913TM

K. Jon Ranson

07/22/2015

The purpose of this experiment is to characterize a corn field by its reflectance at various view and illumination angles and by its physical and agronomic attributes.

Agriculture Barnes 12-1000 Corn Crop Science Crops LARS radiometer Remote Sensing Soil Science solar illumination spectral observations

Purdue Agronomy Farm Corn Solar Radiation Intercepted (SRI) (831805)

10.4231/R7V122QR

Craig S. T. Daughtry

07/27/2015

The overall objectives of this research are the identification and measurement of corn crop canopy variables which are related to crop growth and final yield and relationships between those variables and remotely sensed canopy spectral reflectance.

Agriculture Barnes 12-1000 Corn Crop Science Crops Exotech 100 LARS radiometer Remote Sensing solar illumination spectral observations

Purdue Agronomy Farm Corn Corn Row Spacing (841803)

10.4231/R75M63M0

Craig S. T. Daughtry

07/27/2015

Purdue Agronomy Farm Corn Corn Row Spacing Experiment

Agriculture Barnes 12-1000 Corn Crop Science Crops Exotech 100 LARS radiometer Remote Sensing Soil Science solar illumination spectral observations

Purdue Agronomy Farm Corn Solar Radiation Intercepted (SRI) (841805)

10.4231/R7B27S7R

Kevin P. Gallo

07/28/2015

The objectives of this research are 1) the identification and measurement of corn crop canopy variables, 2) development of relationships between identified variables, and 3) development and testing of methods in corn crop yield models

Agriculture Barnes 12-1000 Corn Crop Science Crops Exotech 100 LARS radiometer Remote Sensing Soil Science solar illumination spectral observations

Multi-Species Prediction of Physiological Traits with Hyper-Spectral Modeling

10.4231/FPHP-0153

Meng-yang Lin , Mitchell R Tuinstra ORCID logo

02/11/2022

High-throughput hyperspectral imaging in corn and sorghum can be used in multi-species models to predict water and nitrogen status of plants within and across these crop species.

Abiotic stress Agronomy Corn Ecophysiology High-throughput Phenotyping Machine Learning nitrogen content partial least square regression relative water content Remote Sensing Sorghum

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