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Hopp, Daniel

Publications and source records attributed to Hopp, Daniel.

2020_Experiment_1

An early APPL experiment. Many of the RGB's are blank due to Color Segmentation issues. Partial metadata exists in the level0 directory

APPL↗

2020_Experiment_2

First successful experimental run of APPL from 2020. Demonstrates a raw RGB image, metadata, and a successful mask. A Poplar tree

APPL↗

3D-RGB

An early attempt at using 3D point clouds to scan plants grown in the APPL facility.

3D RGB↗

3_Drought_Experiment_1

This is an early experiment in the APPL facility at ORNL looking at the effect of drought on various Populus genotypes. Nisqually-1, WV-94, BESC-394, BESC-198, BESC-24, BESC-375

APPL↗

Early_Commisioning_Data

This is very early commissioning data (2019) from the newly established APPL facility at ORNL. Instruments, and technologies are in active development at this stage.

APPL↗

PSI_Testing

Testing data for PSI Instrumentation from 2019 - 2022

appl↗

exnehilo7/fielddata-lite-iOS-app

Field Expedition Routing and Navigation (FERN) is an IOS app funded by the Center for Bioenergy Innovation (CBI). It allows an end user to make trips to collect novel data points. It allows user to return to previously surveyed points to collect more data. It calculates the optimal route to use to sample points needed for return trips. A companion php/database application is required for full functionality. Links to this open source project are in the README. FERN can use the default GPS on an Iphone but it also optimized for Arrow Gold GPS. Other external GPS could be supported by modifying this code and adding the proper routines.

Hopp, Daniel↗

HyperKube: A Kubernetes Based System for the Automation of Processing and Analysis of Hyperspectral Data Obtained from Multiple Hyperspectral Imaging Systems

Hyperspectral imagery is an emerging field of technology that has enormous potential for remote and proximal sensing in numerous areas of research. The plant phenotyping community is applying this technology to advance the throughput and accuracy of plant phenotypes based on airborne and lab-based hyperspectral imaging technology. Here we report an automated processing and analysis pipeline for four different hyperspectral imaging platforms, discuss the data issues involved, and present a strategy for computing and data architecture to handle hyperspectral data.

47 OTHER INSTRUMENTATION↗