Nonlinear vegetation phenology shifts over northern China during 1982-2006

Youzhi An; Wenbo Liu; Wei Gao; Zhiqiang Gao; Chaoshun Liu; Runhe Shi

doi:10.1117/12.2235858

Nonlinear vegetation phenology shifts over northern China during 1982-2006

Youzhi An
, Wenbo Liu
, Wei Gao
, Zhiqiang Gao
, Chaoshun Liu
, Runhe Shi

School of Geographic Sciences

East China Normal University
Guizhou Education University
Zhejiang Tourism Group
Colorado State University
CAS - Yantai Institute of Coastal Research for Sustainable Development

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The response of vegetation phenology change to climate change effects in the Northern China has been reported in the past several decades. Phenological change is a critical understanding in terrestrial carbon cycling. This study aims to investigate linear and nonlinear change trends and nonlinear response change trends in climate in vegetation phenology over Northern China in the last three decades. We analyzed the vegetation phenology over the Northern China by the new released Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVIg) dataset from 1982 to 2006.Results show that based on linear method, we can found that SOS was gradually advanced, EOS gradually delayed, and then LOS gradually lengthened. But on the basis of nonlinear method, phenological trends in the SOS, EOS and LOS are not continuous, we can found extended LOS with advanced SOS and delayed EOS before the turning point (TP) of spring SOS and autumn EOS trends and shortened LOS with delayed SOS and advanced EOS after the turning point (TP) of spring SOS and autumn EOS trends.

Original language	English
Title of host publication	Remote Sensing and Modeling of Ecosystems for Sustainability XIII
Editors	Wei Gao, Ni-Bin Chang
Publisher	SPIE
ISBN (Electronic)	9781510603417
DOIs	https://doi.org/10.1117/12.2235858
State	Published - 2016
Event	Remote Sensing and Modeling of Ecosystems for Sustainability XIII - San Diego, United States Duration: 31 Aug 2016 → …

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	9975
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	Remote Sensing and Modeling of Ecosystems for Sustainability XIII
Country/Territory	United States
City	San Diego
Period	31/08/16 → …

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

Keywords

GIMMS NDVIg
Global Warming
Growing Season
Phenology
Piecewise linear regression

Access to Document

10.1117/12.2235858

Cite this

An, Y., Liu, W., Gao, W., Gao, Z., Liu, C., & Shi, R. (2016). Nonlinear vegetation phenology shifts over northern China during 1982-2006. In W. Gao, & N.-B. Chang (Eds.), Remote Sensing and Modeling of Ecosystems for Sustainability XIII Article 99750N (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9975). SPIE. https://doi.org/10.1117/12.2235858

@inproceedings{a8e9f0bc78fd47529a34524bfa996f9d,

title = "Nonlinear vegetation phenology shifts over northern China during 1982-2006",

abstract = "The response of vegetation phenology change to climate change effects in the Northern China has been reported in the past several decades. Phenological change is a critical understanding in terrestrial carbon cycling. This study aims to investigate linear and nonlinear change trends and nonlinear response change trends in climate in vegetation phenology over Northern China in the last three decades. We analyzed the vegetation phenology over the Northern China by the new released Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVIg) dataset from 1982 to 2006.Results show that based on linear method, we can found that SOS was gradually advanced, EOS gradually delayed, and then LOS gradually lengthened. But on the basis of nonlinear method, phenological trends in the SOS, EOS and LOS are not continuous, we can found extended LOS with advanced SOS and delayed EOS before the turning point (TP) of spring SOS and autumn EOS trends and shortened LOS with delayed SOS and advanced EOS after the turning point (TP) of spring SOS and autumn EOS trends.",

keywords = "GIMMS NDVIg, Global Warming, Growing Season, Phenology, Piecewise linear regression",

author = "Youzhi An and Wenbo Liu and Wei Gao and Zhiqiang Gao and Chaoshun Liu and Runhe Shi",

note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Remote Sensing and Modeling of Ecosystems for Sustainability XIII ; Conference date: 31-08-2016",

year = "2016",

doi = "10.1117/12.2235858",

language = "英语",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

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}

An, Y, Liu, W, Gao, W, Gao, Z, Liu, C & Shi, R 2016, Nonlinear vegetation phenology shifts over northern China during 1982-2006. in W Gao & N-B Chang (eds), Remote Sensing and Modeling of Ecosystems for Sustainability XIII., 99750N, Proceedings of SPIE - The International Society for Optical Engineering, vol. 9975, SPIE, Remote Sensing and Modeling of Ecosystems for Sustainability XIII, San Diego, United States, 31/08/16. https://doi.org/10.1117/12.2235858

Nonlinear vegetation phenology shifts over northern China during 1982-2006. / An, Youzhi; Liu, Wenbo; Gao, Wei et al.
Remote Sensing and Modeling of Ecosystems for Sustainability XIII. ed. / Wei Gao; Ni-Bin Chang. SPIE, 2016. 99750N (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9975).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - An, Youzhi

AU - Liu, Wenbo

AU - Gao, Wei

AU - Gao, Zhiqiang

AU - Liu, Chaoshun

AU - Shi, Runhe

PY - 2016

Y1 - 2016

N2 - The response of vegetation phenology change to climate change effects in the Northern China has been reported in the past several decades. Phenological change is a critical understanding in terrestrial carbon cycling. This study aims to investigate linear and nonlinear change trends and nonlinear response change trends in climate in vegetation phenology over Northern China in the last three decades. We analyzed the vegetation phenology over the Northern China by the new released Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVIg) dataset from 1982 to 2006.Results show that based on linear method, we can found that SOS was gradually advanced, EOS gradually delayed, and then LOS gradually lengthened. But on the basis of nonlinear method, phenological trends in the SOS, EOS and LOS are not continuous, we can found extended LOS with advanced SOS and delayed EOS before the turning point (TP) of spring SOS and autumn EOS trends and shortened LOS with delayed SOS and advanced EOS after the turning point (TP) of spring SOS and autumn EOS trends.

AB - The response of vegetation phenology change to climate change effects in the Northern China has been reported in the past several decades. Phenological change is a critical understanding in terrestrial carbon cycling. This study aims to investigate linear and nonlinear change trends and nonlinear response change trends in climate in vegetation phenology over Northern China in the last three decades. We analyzed the vegetation phenology over the Northern China by the new released Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVIg) dataset from 1982 to 2006.Results show that based on linear method, we can found that SOS was gradually advanced, EOS gradually delayed, and then LOS gradually lengthened. But on the basis of nonlinear method, phenological trends in the SOS, EOS and LOS are not continuous, we can found extended LOS with advanced SOS and delayed EOS before the turning point (TP) of spring SOS and autumn EOS trends and shortened LOS with delayed SOS and advanced EOS after the turning point (TP) of spring SOS and autumn EOS trends.

KW - GIMMS NDVIg

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KW - Growing Season

KW - Phenology

KW - Piecewise linear regression

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ER -

Nonlinear vegetation phenology shifts over northern China during 1982-2006

Abstract

Publication series

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UN SDGs

Keywords

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