Analysis of the Spatial and Temporal Changes of NDVI and Its Driving Factors in the Wei and Jing River Basins

This study aimed to explore the long-term vegetation cover change and its driving factors in the typical watershed of the Yellow River Basin. This research was based on the Google Earth Engine (GEE), a remote sensing cloud platform, and used the Landsat surface reflectance datasets and the Pearson c...

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Autores principales:	Chenlu Huang, Qinke Yang, Weidong Huang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	Wei River Jing River GEE residual analysis random forest classification and regression tree model Medicine R
Acceso en línea:	https://doaj.org/article/23de22dde7db45f59e3e6e15bbc2d6c2
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spelling	oai:doaj.org-article:23de22dde7db45f59e3e6e15bbc2d6c22021-11-25T17:49:02ZAnalysis of the Spatial and Temporal Changes of NDVI and Its Driving Factors in the Wei and Jing River Basins10.3390/ijerph1822118631660-46011661-7827https://doaj.org/article/23de22dde7db45f59e3e6e15bbc2d6c22021-11-01T00:00:00Zhttps://www.mdpi.com/1660-4601/18/22/11863https://doaj.org/toc/1661-7827https://doaj.org/toc/1660-4601This study aimed to explore the long-term vegetation cover change and its driving factors in the typical watershed of the Yellow River Basin. This research was based on the Google Earth Engine (GEE), a remote sensing cloud platform, and used the Landsat surface reflectance datasets and the Pearson correlation method to analyze the vegetation conditions in the areas above Xianyang on the Wei River and above Zhangjiashan on the Jing River. Random forest and decision tree models were used to analyze the effects of various climatic factors (precipitation, temperature, soil moisture, evapotranspiration, and drought index) on NDVI (normalized difference vegetation index). Then, based on the residual analysis method, the effects of human activities on NDVI were explored. The results showed that: (1) From 1987 to 2018, the NDVI of the two watersheds showed an increasing trend; in particular, after 2008, the average increase rate of NDVI in the growing season (April to September) increased from 0.0032/a and 0.003/a in the base period (1987–2008) to 0.0172/a and 0.01/a in the measurement period (2008–2018), for the Wei and Jing basins, respectively. In addition, the NDVI significantly increased from 21.78% and 31.32% in the baseline period (1987–2008) to 83.76% and 92.40% in the measurement period (2008–2018), respectively. (2) The random forest and classification and regression tree model (CART) can assess the contribution and sensitivity of various climate factors to NDVI. Precipitation, soil moisture, and temperature were found to be the three main factors that affect the NDVI of the study area, and their contributions were 37.05%, 26.42%, and 15.72%, respectively. The changes in precipitation and soil moisture in the entire Jing River Basin and the upper and middle reaches of the Wei River above Xianyang caused significant changes in NDVI. Furthermore, changes in precipitation and temperature led to significant changes in NDVI in the lower reaches of the Wei River. (3) The impact of human activities in the Wei and Jing basins on NDVI has gradually changed from negative to positive, which is mainly due to the implementation of soil and water conservation measures. The proportions of areas with positive effects of human activities were 80.88% and 81.95%, of which the proportions of areas with significant positive effects were 11.63% and 7.76%, respectively. These are mainly distributed in the upper reaches of the Wei River and the western and eastern regions of the Jing River. These areas are the key areas where soil and water conservation measures have been implemented in recent years, and the corresponding land use has transformed from cultivated land to forest and grassland. The negative effects accounted for 1.66% and 0.10% of the area, respectively, and were mainly caused by urban expansion and coal mining.Chenlu HuangQinke YangWeidong HuangMDPI AGarticleWei RiverJing RiverGEEresidual analysisrandom forestclassification and regression tree modelMedicineRENInternational Journal of Environmental Research and Public Health, Vol 18, Iss 11863, p 11863 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Wei River Jing River GEE residual analysis random forest classification and regression tree model Medicine R
spellingShingle	Wei River Jing River GEE residual analysis random forest classification and regression tree model Medicine R Chenlu Huang Qinke Yang Weidong Huang Analysis of the Spatial and Temporal Changes of NDVI and Its Driving Factors in the Wei and Jing River Basins
description	This study aimed to explore the long-term vegetation cover change and its driving factors in the typical watershed of the Yellow River Basin. This research was based on the Google Earth Engine (GEE), a remote sensing cloud platform, and used the Landsat surface reflectance datasets and the Pearson correlation method to analyze the vegetation conditions in the areas above Xianyang on the Wei River and above Zhangjiashan on the Jing River. Random forest and decision tree models were used to analyze the effects of various climatic factors (precipitation, temperature, soil moisture, evapotranspiration, and drought index) on NDVI (normalized difference vegetation index). Then, based on the residual analysis method, the effects of human activities on NDVI were explored. The results showed that: (1) From 1987 to 2018, the NDVI of the two watersheds showed an increasing trend; in particular, after 2008, the average increase rate of NDVI in the growing season (April to September) increased from 0.0032/a and 0.003/a in the base period (1987–2008) to 0.0172/a and 0.01/a in the measurement period (2008–2018), for the Wei and Jing basins, respectively. In addition, the NDVI significantly increased from 21.78% and 31.32% in the baseline period (1987–2008) to 83.76% and 92.40% in the measurement period (2008–2018), respectively. (2) The random forest and classification and regression tree model (CART) can assess the contribution and sensitivity of various climate factors to NDVI. Precipitation, soil moisture, and temperature were found to be the three main factors that affect the NDVI of the study area, and their contributions were 37.05%, 26.42%, and 15.72%, respectively. The changes in precipitation and soil moisture in the entire Jing River Basin and the upper and middle reaches of the Wei River above Xianyang caused significant changes in NDVI. Furthermore, changes in precipitation and temperature led to significant changes in NDVI in the lower reaches of the Wei River. (3) The impact of human activities in the Wei and Jing basins on NDVI has gradually changed from negative to positive, which is mainly due to the implementation of soil and water conservation measures. The proportions of areas with positive effects of human activities were 80.88% and 81.95%, of which the proportions of areas with significant positive effects were 11.63% and 7.76%, respectively. These are mainly distributed in the upper reaches of the Wei River and the western and eastern regions of the Jing River. These areas are the key areas where soil and water conservation measures have been implemented in recent years, and the corresponding land use has transformed from cultivated land to forest and grassland. The negative effects accounted for 1.66% and 0.10% of the area, respectively, and were mainly caused by urban expansion and coal mining.
format	article
author	Chenlu Huang Qinke Yang Weidong Huang
author_facet	Chenlu Huang Qinke Yang Weidong Huang
author_sort	Chenlu Huang
title	Analysis of the Spatial and Temporal Changes of NDVI and Its Driving Factors in the Wei and Jing River Basins
title_short	Analysis of the Spatial and Temporal Changes of NDVI and Its Driving Factors in the Wei and Jing River Basins
title_full	Analysis of the Spatial and Temporal Changes of NDVI and Its Driving Factors in the Wei and Jing River Basins
title_fullStr	Analysis of the Spatial and Temporal Changes of NDVI and Its Driving Factors in the Wei and Jing River Basins
title_full_unstemmed	Analysis of the Spatial and Temporal Changes of NDVI and Its Driving Factors in the Wei and Jing River Basins
title_sort	analysis of the spatial and temporal changes of ndvi and its driving factors in the wei and jing river basins
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/23de22dde7db45f59e3e6e15bbc2d6c2
work_keys_str_mv	AT chenluhuang analysisofthespatialandtemporalchangesofndvianditsdrivingfactorsintheweiandjingriverbasins AT qinkeyang analysisofthespatialandtemporalchangesofndvianditsdrivingfactorsintheweiandjingriverbasins AT weidonghuang analysisofthespatialandtemporalchangesofndvianditsdrivingfactorsintheweiandjingriverbasins
_version_	1718411973091131392

Analysis of the Spatial and Temporal Changes of NDVI and Its Driving Factors in the Wei and Jing River Basins

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