A methods framework for evaluating measurement consistency across spectrometers for multispectral uncrewed aerial system vegetation mapping applications
The U.S. Geological Survey collects remote sensing data to support national scientific assessments of natural resources, hazards, and landscape change. Spectrometers and spectroradiometers are essential for gathering point-based spectral measurements used in applications such as uncrewed aerial systems (UAS) multispectral image calibration, validation, and analysis. Evaluating how different instruments perform in laboratory and field environments helps determine whether they provide consistent, interoperable measurements. Such verification can expand access to spectral ground data during UAS operations by allowing scientists to use alternative instruments when budgets, logistics, or field conditions limit options. We propose and test a methodological framework for evaluating spectrometers for measurement consistency during UAS multispectral vegetation mapping applications. There are three central evaluation components to the framework: laboratory, field, and relative to UAS multispectral imagery. By evaluating the instruments in both relatively controlled and uncontrolled environments, we thoroughly examine measurement consistency and when/why measurements may differ. We opportunistically selected two instruments for a case study in a coastal marsh setting: a compact laboratory spectrometer we modified for field use and a field-ready spectroradiometer. The instruments produced consistent measurements in both environments. We found differences between the field spectra and UAS spectra that likely reflect the perspectives of ground vs. aerial data and indicate that further radiometric calibration may be needed.
Citation Information
| Publication Year | 2026 |
|---|---|
| Title | A methods framework for evaluating measurement consistency across spectrometers for multispectral uncrewed aerial system vegetation mapping applications |
| DOI | 10.3390/drones10090674 |
| Authors | Victoria Mary Scholl, Jennifer Marie Cramer, Alexandra Danielle Evans, Evan Cox, Raymond F. Kokaly |
| Publication Type | Article |
| Publication Subtype | Journal Article |
| Series Title | Drones |
| Index ID | 70279860 |
| Record Source | USGS Publications Warehouse |
| USGS Organization | Geosciences and Environmental Change Science Center; Woods Hole Coastal and Marine Science Center; Geology, Geophysics, and Geochemistry Science Center |