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Identification of the Optimal Season and Spectral Regions for Shrub Cover Estimation in Grasslands

Woody plant encroachment (WPE), the expansion of native and non-native trees and shrubs into grasslands, is a less studied factor that leads to declines in grassland ecosystem health. With the increasing application of remote sensing in grassland monitoring and measuring, it is still difficult to de...

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Autores principales: Soubry, Irini, Guo, Xulin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124746/
https://www.ncbi.nlm.nih.gov/pubmed/33946795
http://dx.doi.org/10.3390/s21093098
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author Soubry, Irini
Guo, Xulin
author_facet Soubry, Irini
Guo, Xulin
author_sort Soubry, Irini
collection PubMed
description Woody plant encroachment (WPE), the expansion of native and non-native trees and shrubs into grasslands, is a less studied factor that leads to declines in grassland ecosystem health. With the increasing application of remote sensing in grassland monitoring and measuring, it is still difficult to detect WPE at its early stages when its spectral signals are not strong enough. Even at late stages, woody species have strong vegetation characteristics that are commonly categorized as healthy ecosystems. We focus on how shrub encroachment can be detected through remote sensing by looking at the biophysical and spectral properties of the WPE grassland ecosystem, investigating the appropriate season and wavelengths that identify shrub cover, testing the spectral separability of different shrub cover groups and by revealing the lowest shrub cover that can be detected by remote sensing. Biophysical results indicate spring as the best season to distinguish shrubs in our study area. The earliest shrub encroachment can be identified most likely only when the cover reaches between 10% and 25%. A correlation between wavelength spectra and shrub cover indicated four regions that are statistically significant, which differ by season. Furthermore, spectral separability of shrubs increases with their cover; however, good separation is only possible for pure shrub pixels. From the five separability metrics used, Transformed divergence and Jeffries-Matusita distance have better interpretations. The spectral regions for pure shrub pixel separation are slightly different from those derived by correlation and can be explained by the influences from land cover mixtures along our study transect.
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spelling pubmed-81247462021-05-17 Identification of the Optimal Season and Spectral Regions for Shrub Cover Estimation in Grasslands Soubry, Irini Guo, Xulin Sensors (Basel) Article Woody plant encroachment (WPE), the expansion of native and non-native trees and shrubs into grasslands, is a less studied factor that leads to declines in grassland ecosystem health. With the increasing application of remote sensing in grassland monitoring and measuring, it is still difficult to detect WPE at its early stages when its spectral signals are not strong enough. Even at late stages, woody species have strong vegetation characteristics that are commonly categorized as healthy ecosystems. We focus on how shrub encroachment can be detected through remote sensing by looking at the biophysical and spectral properties of the WPE grassland ecosystem, investigating the appropriate season and wavelengths that identify shrub cover, testing the spectral separability of different shrub cover groups and by revealing the lowest shrub cover that can be detected by remote sensing. Biophysical results indicate spring as the best season to distinguish shrubs in our study area. The earliest shrub encroachment can be identified most likely only when the cover reaches between 10% and 25%. A correlation between wavelength spectra and shrub cover indicated four regions that are statistically significant, which differ by season. Furthermore, spectral separability of shrubs increases with their cover; however, good separation is only possible for pure shrub pixels. From the five separability metrics used, Transformed divergence and Jeffries-Matusita distance have better interpretations. The spectral regions for pure shrub pixel separation are slightly different from those derived by correlation and can be explained by the influences from land cover mixtures along our study transect. MDPI 2021-04-29 /pmc/articles/PMC8124746/ /pubmed/33946795 http://dx.doi.org/10.3390/s21093098 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Soubry, Irini
Guo, Xulin
Identification of the Optimal Season and Spectral Regions for Shrub Cover Estimation in Grasslands
title Identification of the Optimal Season and Spectral Regions for Shrub Cover Estimation in Grasslands
title_full Identification of the Optimal Season and Spectral Regions for Shrub Cover Estimation in Grasslands
title_fullStr Identification of the Optimal Season and Spectral Regions for Shrub Cover Estimation in Grasslands
title_full_unstemmed Identification of the Optimal Season and Spectral Regions for Shrub Cover Estimation in Grasslands
title_short Identification of the Optimal Season and Spectral Regions for Shrub Cover Estimation in Grasslands
title_sort identification of the optimal season and spectral regions for shrub cover estimation in grasslands
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124746/
https://www.ncbi.nlm.nih.gov/pubmed/33946795
http://dx.doi.org/10.3390/s21093098
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AT guoxulin identificationoftheoptimalseasonandspectralregionsforshrubcoverestimationingrasslands