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Results for “hyperspectral tomography”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

TRINIDI (Time-of-Flight Resonance Imaging with Neutrons for Isotopic Density Inference)

This software is an open-source Python library that provides tools for processing hyperspectral neutron time-of-flight radiography data. This type of data allows material decomposed reconstructions to be generated with the use of material characteristic spectral responses and the algorithms provided in this code library. The software library will contain tools for pre-processing the neutron measurement data, estimating measurement system parameters, reconstructing material decomposed radiographs, and computing material decomposed computed tomography (CT). Furthermore, it will have capability to generate and process simulated neutron time-of-flight data with the goal of benchmarking and demonstrating the tools that are provided. The software will include thorough documentation and application examples.

Balke, Thilo↗
DOE OSTI2021

Estimation of soil classes and their relationship to grapevine vigor in a Bordeaux vineyard: advancing the practical joint use of electromagnetic induction (EMI) and NDVI datasets for precision viticulture

Working within a vineyard in the Pessac Léognan Appellation of Bordeaux, France, this study documents the potential of using simple statistical methods with spatially-resolved and increasingly available electromagnetic induction (EMI) geophysical and normalized difference vegetation index (NDVI) datasets to accurately estimate Bordeaux vineyard soil classes and to quantitatively explore the relationship between vineyard soil types and grapevine vigor. First, co-located electrical tomographic tomography (ERT) and EMI datasets were compared to gain confidence about how the EMI method averaged soil properties over the grapevine rooting depth. Then, EMI data were used with core soil texture and soil-pit based interpretations of Bordeaux soil types (Brunisol, Redoxisol, Colluviosol and Calcosol) to estimate the spatial distribution of geophysically-identified Bordeaux soil classes. A strong relationship (r = 0.75, p < 0.01) was revealed between the geophysically-identified Bordeaux soil classes and NDVI (both 2 m resolution), showing that the highest grapevine vigor was associated with the Bordeaux soil classes having the largest clay fraction. The results suggest that within-block variability of grapevine vigor was largely controlled by variability in soil classes, and that carefully collected EMI and NDVI datasets can be exceedingly helpful for providing quantitative estimates of vineyard soil and vigor variability, as well as their covariation. The method is expected to be transferable to other viticultural regions, providing an approach to use easy-to-acquire, high resolution datasets to guide viticultural practices, including routine management and replanting.

54 ENVIRONMENTAL SCIENCES↗