Datasets

subject: Remote Sensing

Total is 133 Results
Purdue Agronomy Farm Wheat Sun-View Angle (831802)

10.4231/R73J39X2

Craig S. T. Daughtry

07/27/2015

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

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

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

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

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

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

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

HTP-Soy: An Aerial Image Set of Multi-category Soybean for High-Throughput Phenotyping (HTP)

10.4231/ZAD3-MG98

Beichen Lyu , Katy Rainey ORCID logo , Keith Cherkauer ORCID logo , Stuart D Smith

01/06/2020

The publication “HTP-Soy” contains 1,728 aerial images of soybean plots in the field and each image is categorized based on spatial, temporal, and genetic variations. Data is made available to encourage development of HTP applications.

Agricultural and Biological Engineering Computer Vision High-throughput Phenotyping Image Dataset Indiana Plant Breeding Remote Sensing Soybean Unmanned Aerial Systems

Geospatial Image Data for Sorghum Phenotyping

10.4231/MY7W-FH43

Ayman F Habib ORCID logo , Ed Delp ORCID logo , Keith A Cherkauer ORCID logo , Larry L. Biehl ORCID logo , Melba M Crawford , Mitchell Tuinstra ORCID logo

05/27/2021

This publication includes sample rgb and hyperspectral image data collected in 2018 by unmanned aerial systems for a Sorghum Phenotying and Trait Analysis project being conducted at Purdue's Agronomy Center for Research and Education (ACRE).

Agronomy hyperspectral Phenotyping Remote Sensing Sorghum UAS

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

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