A long-term spatiotemporal analysis of vegetation greenness over the himalayan region using google earth engine

Kumari, N; Srivastava, A; Dumka, UC

A long-term spatiotemporal analysis of vegetation greenness over the himalayan region using google earth engine

Kumari, N Srivastava, A

Dumka, UC

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Publisher:: MDPI AG
Publication Type:: Journal Article
Citation:: Climate, 2021, 9, (7), pp. 109
Issue Date:: 2021-07-01

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Field	Value	Language
dc.contributor.author	Kumari, N
dc.contributor.author	Srivastava, A https://orcid.org/0000-0002-3963-265X
dc.contributor.author	Dumka, UC
dc.date.accessioned	2022-01-27T21:37:46Z
dc.date.available	2022-01-27T21:37:46Z
dc.date.issued	2021-07-01
dc.identifier.citation	Climate, 2021, 9, (7), pp. 109
dc.identifier.issn	2225-1154
dc.identifier.issn	2225-1154
dc.identifier.uri	http://hdl.handle.net/10453/153669
dc.description.abstract	The Himalayas constitute one of the richest and most diverse ecosystems in the Indian sub-continent. Vegetation greenness driven by climate in the Himalayan region is often overlooked as field-based studies are challenging due to high altitude and complex topography. Although the basic information about vegetation cover and its interactions with different hydroclimatic factors is vital, limited attention has been given to understanding the response of vegetation to different climatic factors. The main aim of the present study is to analyse the relationship between the spatio-temporal variability of vegetation greenness and associated climatic and hydrological drivers within the Upper Khoh River (UKR) Basin of the Himalayas at annual and seasonal scales. We analysed two vegetation indices, namely, normalised difference vegetation index (NDVI) and enhanced vegetation index (EVI) time-series data, for the last 20 years (2001–2020) using Google Earth Engine. We found that both the NDVI and EVI showed increasing trends in the vegetation greening during the period under consideration, with the NDVI being consistently higher than the EVI. The mean NDVI and EVI increased from 0.54 and 0.31 (2001), respectively, to 0.65 and 0.36 (2020). Further, the EVI tends to correlate better with the different hydroclimatic factors in comparison to the NDVI. The EVI is strongly correlated with ET with R2 = 0.73 whereas the NDVI showed satisfactory performance with R2 = 0.45. On the other hand, the relationship between the EVI and precipitation yielded R2 = 0.34, whereas there was no relationship was observed between the NDVI and precipi-tation. These findings show that there exists a strong correlation between the EVI and hydroclimatic factors, which shows that changes in vegetation phenology can be better captured using the EVI than the NDVI.
dc.language	en
dc.publisher	MDPI AG
dc.relation.ispartof	Climate
dc.relation.isbasedon	10.3390/cli9070109
dc.rights	info:eu-repo/semantics/openAccess
dc.title	A long-term spatiotemporal analysis of vegetation greenness over the himalayan region using google earth engine
dc.type	Journal Article
utslib.citation.volume	9
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	open_access	*
dc.date.updated	2022-01-27T21:37:44Z
pubs.issue	7
pubs.publication-status	Published
pubs.volume	9
utslib.citation.issue	7

Abstract:

The Himalayas constitute one of the richest and most diverse ecosystems in the Indian sub-continent. Vegetation greenness driven by climate in the Himalayan region is often overlooked as field-based studies are challenging due to high altitude and complex topography. Although the basic information about vegetation cover and its interactions with different hydroclimatic factors is vital, limited attention has been given to understanding the response of vegetation to different climatic factors. The main aim of the present study is to analyse the relationship between the spatio-temporal variability of vegetation greenness and associated climatic and hydrological drivers within the Upper Khoh River (UKR) Basin of the Himalayas at annual and seasonal scales. We analysed two vegetation indices, namely, normalised difference vegetation index (NDVI) and enhanced vegetation index (EVI) time-series data, for the last 20 years (2001–2020) using Google Earth Engine. We found that both the NDVI and EVI showed increasing trends in the vegetation greening during the period under consideration, with the NDVI being consistently higher than the EVI. The mean NDVI and EVI increased from 0.54 and 0.31 (2001), respectively, to 0.65 and 0.36 (2020). Further, the EVI tends to correlate better with the different hydroclimatic factors in comparison to the NDVI. The EVI is strongly correlated with ET with R2 = 0.73 whereas the NDVI showed satisfactory performance with R2 = 0.45. On the other hand, the relationship between the EVI and precipitation yielded R2 = 0.34, whereas there was no relationship was observed between the NDVI and precipi-tation. These findings show that there exists a strong correlation between the EVI and hydroclimatic factors, which shows that changes in vegetation phenology can be better captured using the EVI than the NDVI.

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http://hdl.handle.net/10453/153669