Study of mesoscale NDVI prediction models in arid and semiarid regions of China under changing environments

Currently, studies analysing the relationship between climatic factors and vegetation may present some problems, including considering insufficient spatiotemporal characteristics, contradictory results and deficiencies in reflecting vegetation changes in the future. To address this, we first analyse...

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Autores principales:	Xinglong Gong, Shuping Du, Fengyu Li, Yibo Ding
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Changing climate Arid and semiarid regions in China Mesoscale NDVI prediction RCMs Vegetation dynamic analysis Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/c7a55310e3cd48c99ea1687ccc1c2f41
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id	oai:doaj.org-article:c7a55310e3cd48c99ea1687ccc1c2f41
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spelling	oai:doaj.org-article:c7a55310e3cd48c99ea1687ccc1c2f412021-12-01T05:00:34ZStudy of mesoscale NDVI prediction models in arid and semiarid regions of China under changing environments1470-160X10.1016/j.ecolind.2021.108198https://doaj.org/article/c7a55310e3cd48c99ea1687ccc1c2f412021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21008633https://doaj.org/toc/1470-160XCurrently, studies analysing the relationship between climatic factors and vegetation may present some problems, including considering insufficient spatiotemporal characteristics, contradictory results and deficiencies in reflecting vegetation changes in the future. To address this, we first analysed the spatiotemporal characteristics of the impact of climatic factors on the normalized difference vegetation index (NDVI) using a multiple regression model constructed from the perspective of water deficit. Second, the two carbon emission scenarios provided by Coupled Model Inter-comparison Project phase 5 (CMIP5) were combined to predict the future vegetation conditions in China. Finally, trend analysis, Sen's slope and cycle analysis methods were employed to explore the trend of the NDVI and its spatiotemporal characteristics in the arid and semiarid regions of China. The results show that the impact of climate change on vegetation possesses distinct spatiotemporal characteristics, and the influences are different depending on the month and location. Vegetation has greened in most arid and semiarid areas of China during historical periods. In the future, NDVI variation will show a fluctuating tendency, and increasing and declining trends for the NDVI will alternately occur monthly. Although both precipitation and temperature will increase in the future, spring vegetation will be threatened by stress in some areas due to severe drought caused by the increase in evaporation, which is caused by increasing temperature. The impact of climatic factors on the amplitude and cycle of vegetation type zones varies monthly. The impact of carbon concentration on the NDVI in vegetation type zones was not significant but was relatively large in some areas. The influence of the carbon concentration on the NDVI cycle is different each month. Carbon concentration basically has no effect on amplitude.Xinglong GongShuping DuFengyu LiYibo DingElsevierarticleChanging climateArid and semiarid regions in ChinaMesoscale NDVI predictionRCMsVegetation dynamic analysisEcologyQH540-549.5ENEcological Indicators, Vol 131, Iss , Pp 108198- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Changing climate Arid and semiarid regions in China Mesoscale NDVI prediction RCMs Vegetation dynamic analysis Ecology QH540-549.5
spellingShingle	Changing climate Arid and semiarid regions in China Mesoscale NDVI prediction RCMs Vegetation dynamic analysis Ecology QH540-549.5 Xinglong Gong Shuping Du Fengyu Li Yibo Ding Study of mesoscale NDVI prediction models in arid and semiarid regions of China under changing environments
description	Currently, studies analysing the relationship between climatic factors and vegetation may present some problems, including considering insufficient spatiotemporal characteristics, contradictory results and deficiencies in reflecting vegetation changes in the future. To address this, we first analysed the spatiotemporal characteristics of the impact of climatic factors on the normalized difference vegetation index (NDVI) using a multiple regression model constructed from the perspective of water deficit. Second, the two carbon emission scenarios provided by Coupled Model Inter-comparison Project phase 5 (CMIP5) were combined to predict the future vegetation conditions in China. Finally, trend analysis, Sen's slope and cycle analysis methods were employed to explore the trend of the NDVI and its spatiotemporal characteristics in the arid and semiarid regions of China. The results show that the impact of climate change on vegetation possesses distinct spatiotemporal characteristics, and the influences are different depending on the month and location. Vegetation has greened in most arid and semiarid areas of China during historical periods. In the future, NDVI variation will show a fluctuating tendency, and increasing and declining trends for the NDVI will alternately occur monthly. Although both precipitation and temperature will increase in the future, spring vegetation will be threatened by stress in some areas due to severe drought caused by the increase in evaporation, which is caused by increasing temperature. The impact of climatic factors on the amplitude and cycle of vegetation type zones varies monthly. The impact of carbon concentration on the NDVI in vegetation type zones was not significant but was relatively large in some areas. The influence of the carbon concentration on the NDVI cycle is different each month. Carbon concentration basically has no effect on amplitude.
format	article
author	Xinglong Gong Shuping Du Fengyu Li Yibo Ding
author_facet	Xinglong Gong Shuping Du Fengyu Li Yibo Ding
author_sort	Xinglong Gong
title	Study of mesoscale NDVI prediction models in arid and semiarid regions of China under changing environments
title_short	Study of mesoscale NDVI prediction models in arid and semiarid regions of China under changing environments
title_full	Study of mesoscale NDVI prediction models in arid and semiarid regions of China under changing environments
title_fullStr	Study of mesoscale NDVI prediction models in arid and semiarid regions of China under changing environments
title_full_unstemmed	Study of mesoscale NDVI prediction models in arid and semiarid regions of China under changing environments
title_sort	study of mesoscale ndvi prediction models in arid and semiarid regions of china under changing environments
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/c7a55310e3cd48c99ea1687ccc1c2f41
work_keys_str_mv	AT xinglonggong studyofmesoscalendvipredictionmodelsinaridandsemiaridregionsofchinaunderchangingenvironments AT shupingdu studyofmesoscalendvipredictionmodelsinaridandsemiaridregionsofchinaunderchangingenvironments AT fengyuli studyofmesoscalendvipredictionmodelsinaridandsemiaridregionsofchinaunderchangingenvironments AT yiboding studyofmesoscalendvipredictionmodelsinaridandsemiaridregionsofchinaunderchangingenvironments
_version_	1718405627641856000

Study of mesoscale NDVI prediction models in arid and semiarid regions of China under changing environments

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