AI Article Synopsis
- Understanding the spectral properties of forest elements is crucial for interpreting remote sensing data from aircraft and satellites.
- This article reports on two datasets collected in Finland during field campaigns in June and July 2023, using a spectrometer to measure the spectra of various understory plants and materials in boreal forests.
- The findings will aid in analyzing vegetation characteristics, improving classification algorithms, and enhancing forest radiative transfer models, with potential applications in using hyperspectral data for distinguishing understory elements.
Article Abstract
Enhancing our understanding of the spectral properties of forest elements is essential for interpreting airborne and satellite-borne remote sensing data. This article presents two datasets on the spectral properties of understory elements in boreal forests collected with close-range hyperspectral measurements. We conducted two field campaigns in June and July 2023 in Finland to acquire spectral measurements at wavelengths from 350 to 2500 nm using an ASD FieldSpec 4 spectrometer for forest understory elements. We measured ferns, decaying wood, common wood sorrel and May lily in situ. In a laboratory, we measured leaves from European fly honeysuckle, alder buckthorn and common hazel. These data support the analysis of vegetation characteristics, training of classification algorithms and improvement of forest radiative transfer models, and could be used to evaluate the potential of hyperspectral data to discriminate the understory elements of boreal forest.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11570963 | PMC |
| http://dx.doi.org/10.1016/j.dib.2024.111068 | DOI Listing |
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