Improved Estimation of Aboveground Biomass of Disturbed Grassland through Including Bare Ground and Grazing Intensity

Accurate approaches to aboveground biomass (AGB) estimation are required to support appraisal of the effectiveness of land use measures, which seek to protect grazing-adapted grasslands atop the Qinghai-Tibet Plateau (QTP). This methodological study assesses the effectiveness of one commonly used vi...

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Main Authors: Yan Shi, Jay Gao, Xilai Li, Jiexia Li, Daniel Marc G. dela Torre, Gary John Brierley
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/11/2105
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spelling doaj-5f59a764138e436ea3529dd0acb7a9b22021-06-01T01:22:24ZengMDPI AGRemote Sensing2072-42922021-05-01132105210510.3390/rs13112105Improved Estimation of Aboveground Biomass of Disturbed Grassland through Including Bare Ground and Grazing IntensityYan Shi0Jay Gao1Xilai Li2Jiexia Li3Daniel Marc G. dela Torre4Gary John Brierley5School of Environment, The University of Auckland, Auckland 1142, New ZealandSchool of Environment, The University of Auckland, Auckland 1142, New ZealandState Key Laboratory of Plateau Ecology and Agriculture, College of Agriculture and Animal Husbandry, Qinghai University, Xining 810016, ChinaState Key Laboratory of Plateau Ecology and Agriculture, College of Agriculture and Animal Husbandry, Qinghai University, Xining 810016, ChinaSchool of Environment, The University of Auckland, Auckland 1142, New ZealandSchool of Environment, The University of Auckland, Auckland 1142, New ZealandAccurate approaches to aboveground biomass (AGB) estimation are required to support appraisal of the effectiveness of land use measures, which seek to protect grazing-adapted grasslands atop the Qinghai-Tibet Plateau (QTP). This methodological study assesses the effectiveness of one commonly used visible band vegetation index, Red Green Blue Vegetation Index (RGBVI), obtained from unmanned aerial vehicle (UAV), in estimating AGB timely and accurately at the local scale, seeking to improve the estimation accuracy by taking into account in situ collected information on disturbed grassland. Particular emphasis is placed upon the mapping and quantification of areas disturbed by grazing (simulated via mowing) and plateau pika (<i>Ochotona curzoniae</i>) that have led to the emergence of bare ground. The initial model involving only RGBVI performed poorly in AGB estimation by underestimating high AGB by around 10% and overestimating low AGB by about 10%. The estimation model was modified by the mowing intensity ratio and bare ground metrics. The former almost doubled the estimation accuracy from R<sup>2</sup> = 0.44 to 0.81. However, this modification caused the bare ground AGB to be overestimated by about 38 and 19 g m<sup>−2</sup> for 2018 and 2019, respectively. Although further modification of the model by bare ground metrics improved the accuracy slightly to 0.88, it markedly reduced the overestimation of low AGB values. It is recommended that grazing intensity be incorporated into the micro-scale estimation of AGB, together with the bare ground modification metrics, especially for severely disturbed meadows with a sizable portion of bare ground.https://www.mdpi.com/2072-4292/13/11/2105UAV imagesAGB estimation accuracyvisible band VImeadow disturbancesmowing intensityQinghai-Tibet Plateau
collection DOAJ
language English
format Article
sources DOAJ
author Yan Shi
Jay Gao
Xilai Li
Jiexia Li
Daniel Marc G. dela Torre
Gary John Brierley
spellingShingle Yan Shi
Jay Gao
Xilai Li
Jiexia Li
Daniel Marc G. dela Torre
Gary John Brierley
Improved Estimation of Aboveground Biomass of Disturbed Grassland through Including Bare Ground and Grazing Intensity
Remote Sensing
UAV images
AGB estimation accuracy
visible band VI
meadow disturbances
mowing intensity
Qinghai-Tibet Plateau
author_facet Yan Shi
Jay Gao
Xilai Li
Jiexia Li
Daniel Marc G. dela Torre
Gary John Brierley
author_sort Yan Shi
title Improved Estimation of Aboveground Biomass of Disturbed Grassland through Including Bare Ground and Grazing Intensity
title_short Improved Estimation of Aboveground Biomass of Disturbed Grassland through Including Bare Ground and Grazing Intensity
title_full Improved Estimation of Aboveground Biomass of Disturbed Grassland through Including Bare Ground and Grazing Intensity
title_fullStr Improved Estimation of Aboveground Biomass of Disturbed Grassland through Including Bare Ground and Grazing Intensity
title_full_unstemmed Improved Estimation of Aboveground Biomass of Disturbed Grassland through Including Bare Ground and Grazing Intensity
title_sort improved estimation of aboveground biomass of disturbed grassland through including bare ground and grazing intensity
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-05-01
description Accurate approaches to aboveground biomass (AGB) estimation are required to support appraisal of the effectiveness of land use measures, which seek to protect grazing-adapted grasslands atop the Qinghai-Tibet Plateau (QTP). This methodological study assesses the effectiveness of one commonly used visible band vegetation index, Red Green Blue Vegetation Index (RGBVI), obtained from unmanned aerial vehicle (UAV), in estimating AGB timely and accurately at the local scale, seeking to improve the estimation accuracy by taking into account in situ collected information on disturbed grassland. Particular emphasis is placed upon the mapping and quantification of areas disturbed by grazing (simulated via mowing) and plateau pika (<i>Ochotona curzoniae</i>) that have led to the emergence of bare ground. The initial model involving only RGBVI performed poorly in AGB estimation by underestimating high AGB by around 10% and overestimating low AGB by about 10%. The estimation model was modified by the mowing intensity ratio and bare ground metrics. The former almost doubled the estimation accuracy from R<sup>2</sup> = 0.44 to 0.81. However, this modification caused the bare ground AGB to be overestimated by about 38 and 19 g m<sup>−2</sup> for 2018 and 2019, respectively. Although further modification of the model by bare ground metrics improved the accuracy slightly to 0.88, it markedly reduced the overestimation of low AGB values. It is recommended that grazing intensity be incorporated into the micro-scale estimation of AGB, together with the bare ground modification metrics, especially for severely disturbed meadows with a sizable portion of bare ground.
topic UAV images
AGB estimation accuracy
visible band VI
meadow disturbances
mowing intensity
Qinghai-Tibet Plateau
url https://www.mdpi.com/2072-4292/13/11/2105
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