Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches

•Grassland biomass estimation and uncertainty were analyzed in Northern China.•Uncertainty was traced to data sources, model forms and model parameters.•Biomass allocation was most influential to grassland biomass estimation. Accurate estimation of grassland biomass and its dynamics are crucial not...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Ecological indicators 2016-01, Vol.60, p.1031-1040
Hauptverfasser: Jia, Wenxiao, Liu, Min, Yang, Yuanhe, He, Honglin, Zhu, Xudong, Yang, Fang, Yin, Cai, Xiang, Weining
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1040
container_issue
container_start_page 1031
container_title Ecological indicators
container_volume 60
creator Jia, Wenxiao
Liu, Min
Yang, Yuanhe
He, Honglin
Zhu, Xudong
Yang, Fang
Yin, Cai
Xiang, Weining
description •Grassland biomass estimation and uncertainty were analyzed in Northern China.•Uncertainty was traced to data sources, model forms and model parameters.•Biomass allocation was most influential to grassland biomass estimation. Accurate estimation of grassland biomass and its dynamics are crucial not only for the biogeochemical dynamics of terrestrial ecosystems, but also for the sustainable use of grassland resources. However, estimations of grassland biomass on large spatial scale usually suffer from large variability and mostly lack quantitative uncertainty analyses. In this study, the spatial grassland biomass estimation and its uncertainty were assessed based on 265 field measurements and remote sensing data across Northern China during 2001–2005. Potential sources of uncertainty, including remote sensing data sources (DATsrc), model forms (MODfrm) and model parameters (biomass allocation, BMallo, e.g. root:shoot ratio), were determined and their relative contribution was quantified. The results showed that the annual grassland biomass in Northern China was 1268.37±180.84Tg (i.e., 532.02±99.71g/m2) during 2001–2005, increasing from western to eastern area, with a mean relative uncertainty of 19.8%. There were distinguishable differences among the uncertainty contributions of three sources (BMallo>DATsrc>MODfrm), which contributed 52%, 27% and 13%, respectively. This study highlighted the need to concern the uncertainty in grassland biomass estimation, especially for the uncertainty related to BMallo.
doi_str_mv 10.1016/j.ecolind.2015.09.001
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1778009689</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1470160X15004859</els_id><sourcerecordid>1753471185</sourcerecordid><originalsourceid>FETCH-LOGICAL-c446t-77f6557229b721aa80ae213cb6a8c6828044bf143489c432719cebaf8335737d3</originalsourceid><addsrcrecordid>eNqNkc9u1DAQxiMEEqXwCAgfuWxqJ47_cEFoVaBSBQeoxM1ynMmuV4kdPE6lfRGeF0fbO5w81vzmG833VdVbRmtGmbg51eDi5MNQN5R1NdU1pexZdcWUbHaStvx5qbmkOybor5fVK8RTAYTW4qr6c4vZzzb7GIgNA1mDg5StD_lc_nY6IyCJIzkkizhtRO_jXGriA_kWUz5CCmR_9MF-IPs4LzZ5LFplZF6n7JcJSII5ZiAIAX04kMFmSzCuyRXpTXGOA0xbxy5LitYdAV9XL0Y7Ibx5eq-rh8-3P_dfd_ffv9ztP93vHOci76QcRdfJptG9bJi1ilpoWOt6YZUTqlGU835kvOVKO942kmkHvR1V23aylUN7Xb2_6JbFv1fAbGaPDqZyKcQVDZNSUaqF0v-Bdi2XjKmuoN0FdSkiJhjNkorJ6WwYNVtk5mSeIjNbZIZqUxIpc-8uc6ONxh6Kk-bhRwFEaWraMVWIjxcCiimPHpJB56FkNvgELpsh-n_s-AvVxq3X</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1753471185</pqid></control><display><type>article</type><title>Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches</title><source>Access via ScienceDirect (Elsevier)</source><creator>Jia, Wenxiao ; Liu, Min ; Yang, Yuanhe ; He, Honglin ; Zhu, Xudong ; Yang, Fang ; Yin, Cai ; Xiang, Weining</creator><creatorcontrib>Jia, Wenxiao ; Liu, Min ; Yang, Yuanhe ; He, Honglin ; Zhu, Xudong ; Yang, Fang ; Yin, Cai ; Xiang, Weining</creatorcontrib><description>•Grassland biomass estimation and uncertainty were analyzed in Northern China.•Uncertainty was traced to data sources, model forms and model parameters.•Biomass allocation was most influential to grassland biomass estimation. Accurate estimation of grassland biomass and its dynamics are crucial not only for the biogeochemical dynamics of terrestrial ecosystems, but also for the sustainable use of grassland resources. However, estimations of grassland biomass on large spatial scale usually suffer from large variability and mostly lack quantitative uncertainty analyses. In this study, the spatial grassland biomass estimation and its uncertainty were assessed based on 265 field measurements and remote sensing data across Northern China during 2001–2005. Potential sources of uncertainty, including remote sensing data sources (DATsrc), model forms (MODfrm) and model parameters (biomass allocation, BMallo, e.g. root:shoot ratio), were determined and their relative contribution was quantified. The results showed that the annual grassland biomass in Northern China was 1268.37±180.84Tg (i.e., 532.02±99.71g/m2) during 2001–2005, increasing from western to eastern area, with a mean relative uncertainty of 19.8%. There were distinguishable differences among the uncertainty contributions of three sources (BMallo&gt;DATsrc&gt;MODfrm), which contributed 52%, 27% and 13%, respectively. This study highlighted the need to concern the uncertainty in grassland biomass estimation, especially for the uncertainty related to BMallo.</description><identifier>ISSN: 1470-160X</identifier><identifier>EISSN: 1872-7034</identifier><identifier>DOI: 10.1016/j.ecolind.2015.09.001</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Allocations ; Biomass ; China ; Data sources ; dry matter partitioning ; Dynamics ; Grassland biomass ; Grasslands ; NDVI ; Northern China ; Remote sensing ; root shoot ratio ; Root-to-shoot ratio ; spatial data ; terrestrial ecosystems ; Uncertainty ; Uncertainty analysis</subject><ispartof>Ecological indicators, 2016-01, Vol.60, p.1031-1040</ispartof><rights>2015 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c446t-77f6557229b721aa80ae213cb6a8c6828044bf143489c432719cebaf8335737d3</citedby><cites>FETCH-LOGICAL-c446t-77f6557229b721aa80ae213cb6a8c6828044bf143489c432719cebaf8335737d3</cites><orcidid>0000-0001-5426-7390</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ecolind.2015.09.001$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,4024,27923,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Jia, Wenxiao</creatorcontrib><creatorcontrib>Liu, Min</creatorcontrib><creatorcontrib>Yang, Yuanhe</creatorcontrib><creatorcontrib>He, Honglin</creatorcontrib><creatorcontrib>Zhu, Xudong</creatorcontrib><creatorcontrib>Yang, Fang</creatorcontrib><creatorcontrib>Yin, Cai</creatorcontrib><creatorcontrib>Xiang, Weining</creatorcontrib><title>Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches</title><title>Ecological indicators</title><description>•Grassland biomass estimation and uncertainty were analyzed in Northern China.•Uncertainty was traced to data sources, model forms and model parameters.•Biomass allocation was most influential to grassland biomass estimation. Accurate estimation of grassland biomass and its dynamics are crucial not only for the biogeochemical dynamics of terrestrial ecosystems, but also for the sustainable use of grassland resources. However, estimations of grassland biomass on large spatial scale usually suffer from large variability and mostly lack quantitative uncertainty analyses. In this study, the spatial grassland biomass estimation and its uncertainty were assessed based on 265 field measurements and remote sensing data across Northern China during 2001–2005. Potential sources of uncertainty, including remote sensing data sources (DATsrc), model forms (MODfrm) and model parameters (biomass allocation, BMallo, e.g. root:shoot ratio), were determined and their relative contribution was quantified. The results showed that the annual grassland biomass in Northern China was 1268.37±180.84Tg (i.e., 532.02±99.71g/m2) during 2001–2005, increasing from western to eastern area, with a mean relative uncertainty of 19.8%. There were distinguishable differences among the uncertainty contributions of three sources (BMallo&gt;DATsrc&gt;MODfrm), which contributed 52%, 27% and 13%, respectively. This study highlighted the need to concern the uncertainty in grassland biomass estimation, especially for the uncertainty related to BMallo.</description><subject>Allocations</subject><subject>Biomass</subject><subject>China</subject><subject>Data sources</subject><subject>dry matter partitioning</subject><subject>Dynamics</subject><subject>Grassland biomass</subject><subject>Grasslands</subject><subject>NDVI</subject><subject>Northern China</subject><subject>Remote sensing</subject><subject>root shoot ratio</subject><subject>Root-to-shoot ratio</subject><subject>spatial data</subject><subject>terrestrial ecosystems</subject><subject>Uncertainty</subject><subject>Uncertainty analysis</subject><issn>1470-160X</issn><issn>1872-7034</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqNkc9u1DAQxiMEEqXwCAgfuWxqJ47_cEFoVaBSBQeoxM1ynMmuV4kdPE6lfRGeF0fbO5w81vzmG833VdVbRmtGmbg51eDi5MNQN5R1NdU1pexZdcWUbHaStvx5qbmkOybor5fVK8RTAYTW4qr6c4vZzzb7GIgNA1mDg5StD_lc_nY6IyCJIzkkizhtRO_jXGriA_kWUz5CCmR_9MF-IPs4LzZ5LFplZF6n7JcJSII5ZiAIAX04kMFmSzCuyRXpTXGOA0xbxy5LitYdAV9XL0Y7Ibx5eq-rh8-3P_dfd_ffv9ztP93vHOci76QcRdfJptG9bJi1ilpoWOt6YZUTqlGU835kvOVKO942kmkHvR1V23aylUN7Xb2_6JbFv1fAbGaPDqZyKcQVDZNSUaqF0v-Bdi2XjKmuoN0FdSkiJhjNkorJ6WwYNVtk5mSeIjNbZIZqUxIpc-8uc6ONxh6Kk-bhRwFEaWraMVWIjxcCiimPHpJB56FkNvgELpsh-n_s-AvVxq3X</recordid><startdate>201601</startdate><enddate>201601</enddate><creator>Jia, Wenxiao</creator><creator>Liu, Min</creator><creator>Yang, Yuanhe</creator><creator>He, Honglin</creator><creator>Zhu, Xudong</creator><creator>Yang, Fang</creator><creator>Yin, Cai</creator><creator>Xiang, Weining</creator><general>Elsevier Ltd</general><scope>FBQ</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>7ST</scope><scope>7U6</scope><scope>C1K</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><orcidid>https://orcid.org/0000-0001-5426-7390</orcidid></search><sort><creationdate>201601</creationdate><title>Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches</title><author>Jia, Wenxiao ; Liu, Min ; Yang, Yuanhe ; He, Honglin ; Zhu, Xudong ; Yang, Fang ; Yin, Cai ; Xiang, Weining</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c446t-77f6557229b721aa80ae213cb6a8c6828044bf143489c432719cebaf8335737d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Allocations</topic><topic>Biomass</topic><topic>China</topic><topic>Data sources</topic><topic>dry matter partitioning</topic><topic>Dynamics</topic><topic>Grassland biomass</topic><topic>Grasslands</topic><topic>NDVI</topic><topic>Northern China</topic><topic>Remote sensing</topic><topic>root shoot ratio</topic><topic>Root-to-shoot ratio</topic><topic>spatial data</topic><topic>terrestrial ecosystems</topic><topic>Uncertainty</topic><topic>Uncertainty analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jia, Wenxiao</creatorcontrib><creatorcontrib>Liu, Min</creatorcontrib><creatorcontrib>Yang, Yuanhe</creatorcontrib><creatorcontrib>He, Honglin</creatorcontrib><creatorcontrib>Zhu, Xudong</creatorcontrib><creatorcontrib>Yang, Fang</creatorcontrib><creatorcontrib>Yin, Cai</creatorcontrib><creatorcontrib>Xiang, Weining</creatorcontrib><collection>AGRIS</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Ecological indicators</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jia, Wenxiao</au><au>Liu, Min</au><au>Yang, Yuanhe</au><au>He, Honglin</au><au>Zhu, Xudong</au><au>Yang, Fang</au><au>Yin, Cai</au><au>Xiang, Weining</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches</atitle><jtitle>Ecological indicators</jtitle><date>2016-01</date><risdate>2016</risdate><volume>60</volume><spage>1031</spage><epage>1040</epage><pages>1031-1040</pages><issn>1470-160X</issn><eissn>1872-7034</eissn><abstract>•Grassland biomass estimation and uncertainty were analyzed in Northern China.•Uncertainty was traced to data sources, model forms and model parameters.•Biomass allocation was most influential to grassland biomass estimation. Accurate estimation of grassland biomass and its dynamics are crucial not only for the biogeochemical dynamics of terrestrial ecosystems, but also for the sustainable use of grassland resources. However, estimations of grassland biomass on large spatial scale usually suffer from large variability and mostly lack quantitative uncertainty analyses. In this study, the spatial grassland biomass estimation and its uncertainty were assessed based on 265 field measurements and remote sensing data across Northern China during 2001–2005. Potential sources of uncertainty, including remote sensing data sources (DATsrc), model forms (MODfrm) and model parameters (biomass allocation, BMallo, e.g. root:shoot ratio), were determined and their relative contribution was quantified. The results showed that the annual grassland biomass in Northern China was 1268.37±180.84Tg (i.e., 532.02±99.71g/m2) during 2001–2005, increasing from western to eastern area, with a mean relative uncertainty of 19.8%. There were distinguishable differences among the uncertainty contributions of three sources (BMallo&gt;DATsrc&gt;MODfrm), which contributed 52%, 27% and 13%, respectively. This study highlighted the need to concern the uncertainty in grassland biomass estimation, especially for the uncertainty related to BMallo.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.ecolind.2015.09.001</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-5426-7390</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1470-160X
ispartof Ecological indicators, 2016-01, Vol.60, p.1031-1040
issn 1470-160X
1872-7034
language eng
recordid cdi_proquest_miscellaneous_1778009689
source Access via ScienceDirect (Elsevier)
subjects Allocations
Biomass
China
Data sources
dry matter partitioning
Dynamics
Grassland biomass
Grasslands
NDVI
Northern China
Remote sensing
root shoot ratio
Root-to-shoot ratio
spatial data
terrestrial ecosystems
Uncertainty
Uncertainty analysis
title Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-19T19%3A10%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Estimation%20and%20uncertainty%20analyses%20of%20grassland%20biomass%20in%20Northern%20China:%20Comparison%20of%20multiple%20remote%20sensing%20data%20sources%20and%20modeling%20approaches&rft.jtitle=Ecological%20indicators&rft.au=Jia,%20Wenxiao&rft.date=2016-01&rft.volume=60&rft.spage=1031&rft.epage=1040&rft.pages=1031-1040&rft.issn=1470-160X&rft.eissn=1872-7034&rft_id=info:doi/10.1016/j.ecolind.2015.09.001&rft_dat=%3Cproquest_cross%3E1753471185%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1753471185&rft_id=info:pmid/&rft_els_id=S1470160X15004859&rfr_iscdi=true