What question did this study set out to answer?

To assess the utility of hyperspectral remote sensing data for predicting biomass quantities across various plant functional types and tissue categories in Low Arctic tundra.

January 6, 2017Environmental Research LettersOpen Access

Relationships between hyperspectral data and components of vegetation biomass in Low Arctic tundra communities at Ivotuk, Alaska

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Authors

SBSara Bratsch HEHoward E. Epstein MBMarcel Buchhorn

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Overview

Field remote sensing analysis reveals strong hyperspectral predictive capacity for shrub biomass in Low Arctic tundra, indicating shrub dominance over spectral reflectance.

Key Points

To assess the utility of hyperspectral remote sensing data for predicting biomass quantities across various plant functional types and tissue categories in Low Arctic tundra.
Collected hand-held hyperspectral reflectance and harvested biomass measurements during the 1999 growing season in Ivotuk, Alaska.
Trained predictive regression models using LASSO to address high collinearity among hyperspectral bands and estimate biomass across different vegetation categories.
Shrub categories accounted for 65% of significant biomass–spectra relationships across the growing season, primarily utilizing blue, green, and red edge spectral bands.
The capacity to isolate unique biomass–spectra relationships for understory communities decreased at peak growing season because expanding shrub canopies obscured lower-lying mosses.

Cite This Study

Bratsch et al. (2017) studied this question.

synapsesocial.com/papers/6a80e89d920f8c095a22c7da https://doi.org/10.1088/1748-9326/aa572e

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January 6, 2017Environmental Research LettersOpen Access

Relationships between hyperspectral data and components of vegetation biomass in Low Arctic tundra communities at Ivotuk, Alaska

View Full Paper

Ask AI

Bookmark

Authors

SBSara Bratsch HEHoward E. Epstein MBMarcel Buchhorn

Discussion

Member takes

Overview

Field remote sensing analysis reveals strong hyperspectral predictive capacity for shrub biomass in Low Arctic tundra, indicating shrub dominance over spectral reflectance.

Key Points

To assess the utility of hyperspectral remote sensing data for predicting biomass quantities across various plant functional types and tissue categories in Low Arctic tundra.
Collected hand-held hyperspectral reflectance and harvested biomass measurements during the 1999 growing season in Ivotuk, Alaska.
Trained predictive regression models using LASSO to address high collinearity among hyperspectral bands and estimate biomass across different vegetation categories.
Shrub categories accounted for 65% of significant biomass–spectra relationships across the growing season, primarily utilizing blue, green, and red edge spectral bands.
The capacity to isolate unique biomass–spectra relationships for understory communities decreased at peak growing season because expanding shrub canopies obscured lower-lying mosses.

Cite This Study

Bratsch et al. (2017) studied this question.

synapsesocial.com/papers/6a80e89d920f8c095a22c7da https://doi.org/10.1088/1748-9326/aa572e

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