Datasets

subject: Remote Sensing type: dataset

Total is 133 Results
Purdue Agronomy Farm Corn Cultural Practices (791803)

10.4231/R72B8VZN

Craig S. T. Daughtry

04/06/2015

The objectives of this experiment are to determine (1) the threshold of early season spectral detection of corn, (2) the spectral response of corn as a function of growth and amount of vegetation, and (3) the effect of soil background differences.

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

Purdue Agronomy Farm Soybean Cultural Practices (791804)

10.4231/R79W0CDB

Craig S. T. Daughtry

04/06/2015

The objectives of this experiment are to determine the threshold of early season spectral detection of soybeans, the spectral response of soybeans as a function of growth and amount of vegetation, and the effect of soil background differences.

Agriculture Crop Science Crops Exotech 100 Exotech 20C-SW LARS radiometer Remote Sensing soil Soil Science solar illumination Soybeans spectral observations spectrometer

Row Selection in Remote Sensing for Maize and Sorghum

10.4231/PF9S-4G38

Mitchell R Tuinstra ORCID logo , Seth A Tolley ORCID logo

07/26/2023

Remote sensing data evaluates all row segments of a plot, but the repeatability of traits from different row segments has not been evaluated. We evaluated which row segments provide the best repeatability and yield prediction of remote sensing traits.

Border effect High-throughput Phenotyping hyperspectral LiDAR Maize Plot trimming Predictive modelling Remote Sensing RGB Sorghum UAV

Modeling density surfaces of intraspecific classes using camera-trap distance sampling

10.4231/RF5H-C895

Rob Swihart ORCID logo , Zackary Delisle ORCID logo

02/07/2023

Density surface modelling of intraspecific classes using camera-trap-distance-sampling data and hierarchical generalized additive modelling.

abundance deer density surface modelling Forestry and Natural Resources generalized additive model precision recruitment Remote Sensing ungulate

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

Indiana Statewide Digital Surface Model (2016-2019)

10.4231/0D14-5Q79

Jinha Jung ORCID logo , Sungchan Oh

02/16/2021

Digital Surface Model generated from the Indiana Statewide LiDAR data (2016 - 2019)

Civil Engineering Data Science High Performance Computing LiDAR Remote Sensing

Indiana Statewide Normalized Digital Height Model (2016-2019)

10.4231/QAA5-6J29

Jinha Jung ORCID logo , Sungchan Oh

02/16/2021

Normalized Digital Height Model generated from the Indiana Statewide LiDAR data (2016 - 2019)

Civil Engineering Data Science High Performance Computing LiDAR Remote Sensing

R Pipeline for Calculation of APSIM Parameters and Generating the XML File

10.4231/69H7-CV75

Kai-Wei Yang , Mitchell Tuinstra ORCID logo , Scott Chapman

12/15/2020

A pipeline to generate the XML parameter file for APSIM was developed in R. The files and R codes are reported in "R Pipeline for Calculation of APSIM Parameters and Generating the XML File".

Agronomy APSIM Crop Growth Models APSIM Pipeline Remote Sensing

2018 West Lafayette Simulation of 18 Sorghum Hybrids

10.4231/KMK0-J993

Kai-Wei Yang , Mitchell Tuinstra ORCID logo , Scott Chapman

12/15/2020

The model calibration step compares the APSIM simulated results with measured phenotypes in field trials. Parameter adjustments are reported in “SorghumXMLOutputUQ”.

2018 Sorghum Simulation Agronomy APSIM Crop Model Remote Sensing

2015 West Lafayette Simulation of 18 Sorghum Hybrids

10.4231/0NX5-RT34

Kai-Wei Yang , Mitchell Tuinstra ORCID logo , Scott Chapman

12/15/2020

The APSIM models from 2018 West Lafayette were validated by comparing simulated and observed results of experiments conducted in 2015 West Lafayette.

2015 Sorghum Crop Simulation Agronomy Biophysical crop models Remote Sensing

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