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An evaluation model for aboveground biomass based on hyperspectral data from field and TM8 in Khorchin grassland, China
Biomass is an important indicator for monitoring vegetation degradation and productivity. This study tests the applicability of Hyperspectral Remote-Sensing in situ measurements for high-precision estimation aboveground biomass (AGB) on regional scales of Khorchin grassland in Inner Mongolia, China....
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7048406/ https://www.ncbi.nlm.nih.gov/pubmed/32109248 http://dx.doi.org/10.1371/journal.pone.0223934 |
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author | Zhang, Xiaohua Chen, Xiuli Tian, Meirong Fan, Yongjun Ma, Jianjun Xing, Danlu |
author_facet | Zhang, Xiaohua Chen, Xiuli Tian, Meirong Fan, Yongjun Ma, Jianjun Xing, Danlu |
author_sort | Zhang, Xiaohua |
collection | PubMed |
description | Biomass is an important indicator for monitoring vegetation degradation and productivity. This study tests the applicability of Hyperspectral Remote-Sensing in situ measurements for high-precision estimation aboveground biomass (AGB) on regional scales of Khorchin grassland in Inner Mongolia, China. In order to improve prediction accuracy of AGB which is frequently used as an indicator of aboveground net primary productivity (ANPP), this paper combined ground measurement with remote sensing inversion to build the spectral model. The ground normalized difference vegetation index (SOC_NDVI) calculated from ground spectral of grassland vegetation which was measured by a portable visible/NIR hyperspectral spectrometer (SOC 710). Meanwhile, the remote normalized difference vegetation index (TM_NDVI) calculated from remote spectral of grassland vegetation which was measured by Thematic Mapper (TM) from Landsat 8 which launched by National Aeronautics and Space Administration (NASA). According to regression analysis for the relationship between AGB and SOC_NDVI, SOC_NDVI and TM_NDVI, the evaluation model for aboveground biomass was developed (AGB = 12.523×e(3.370×(0.462×TM_NDVI+0.413)), standard error = 24.74 g m(-2), R(2) = 0.636, p < 0.001). The model accuracy verification results show that the correlation between the measured value and the predicted value of biomass was better with low model standard error. The model could make up for the lack of timeliness and comprehensiveness of conventional ground biomass survey, and provide technical support for high-precision large-area productivity estimation and ecological degradation diagnosis of regional scale grassland. |
format | Online Article Text |
id | pubmed-7048406 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-70484062020-03-10 An evaluation model for aboveground biomass based on hyperspectral data from field and TM8 in Khorchin grassland, China Zhang, Xiaohua Chen, Xiuli Tian, Meirong Fan, Yongjun Ma, Jianjun Xing, Danlu PLoS One Research Article Biomass is an important indicator for monitoring vegetation degradation and productivity. This study tests the applicability of Hyperspectral Remote-Sensing in situ measurements for high-precision estimation aboveground biomass (AGB) on regional scales of Khorchin grassland in Inner Mongolia, China. In order to improve prediction accuracy of AGB which is frequently used as an indicator of aboveground net primary productivity (ANPP), this paper combined ground measurement with remote sensing inversion to build the spectral model. The ground normalized difference vegetation index (SOC_NDVI) calculated from ground spectral of grassland vegetation which was measured by a portable visible/NIR hyperspectral spectrometer (SOC 710). Meanwhile, the remote normalized difference vegetation index (TM_NDVI) calculated from remote spectral of grassland vegetation which was measured by Thematic Mapper (TM) from Landsat 8 which launched by National Aeronautics and Space Administration (NASA). According to regression analysis for the relationship between AGB and SOC_NDVI, SOC_NDVI and TM_NDVI, the evaluation model for aboveground biomass was developed (AGB = 12.523×e(3.370×(0.462×TM_NDVI+0.413)), standard error = 24.74 g m(-2), R(2) = 0.636, p < 0.001). The model accuracy verification results show that the correlation between the measured value and the predicted value of biomass was better with low model standard error. The model could make up for the lack of timeliness and comprehensiveness of conventional ground biomass survey, and provide technical support for high-precision large-area productivity estimation and ecological degradation diagnosis of regional scale grassland. Public Library of Science 2020-02-28 /pmc/articles/PMC7048406/ /pubmed/32109248 http://dx.doi.org/10.1371/journal.pone.0223934 Text en © 2020 Zhang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Zhang, Xiaohua Chen, Xiuli Tian, Meirong Fan, Yongjun Ma, Jianjun Xing, Danlu An evaluation model for aboveground biomass based on hyperspectral data from field and TM8 in Khorchin grassland, China |
title | An evaluation model for aboveground biomass based on hyperspectral data from field and TM8 in Khorchin grassland, China |
title_full | An evaluation model for aboveground biomass based on hyperspectral data from field and TM8 in Khorchin grassland, China |
title_fullStr | An evaluation model for aboveground biomass based on hyperspectral data from field and TM8 in Khorchin grassland, China |
title_full_unstemmed | An evaluation model for aboveground biomass based on hyperspectral data from field and TM8 in Khorchin grassland, China |
title_short | An evaluation model for aboveground biomass based on hyperspectral data from field and TM8 in Khorchin grassland, China |
title_sort | evaluation model for aboveground biomass based on hyperspectral data from field and tm8 in khorchin grassland, china |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7048406/ https://www.ncbi.nlm.nih.gov/pubmed/32109248 http://dx.doi.org/10.1371/journal.pone.0223934 |
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