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Article

A Long-Term Spatiotemporal Analysis of Vegetation Greenness over the Himalayan Region Using Google Earth Engine

1
School of Engineering, The University of Newcastle, Callaghan, NSW 2304, Australia
2
Aryabhatta Research Institute of Observational Sciences (ARIES), Nainital 263002, India
*
Author to whom correspondence should be addressed.
Academic Editors: Jennifer A. Holm, David A. Lutz and Luxon Nham
Received: 3 June 2021 / Revised: 19 June 2021 / Accepted: 28 June 2021 / Published: 30 June 2021
(This article belongs to the Special Issue Forest-Climate Ecosystem Interactions)
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 spatiotemporal 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 precipitation. 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. View Full-Text
Keywords: Himalayas; NDVI; EVI; climate; Google Earth Engine; water resources; Upper Khoh River Himalayas; NDVI; EVI; climate; Google Earth Engine; water resources; Upper Khoh River
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MDPI and ACS Style

Kumari, N.; Srivastava, A.; Dumka, U.C. A Long-Term Spatiotemporal Analysis of Vegetation Greenness over the Himalayan Region Using Google Earth Engine. Climate 2021, 9, 109. https://0-doi-org.brum.beds.ac.uk/10.3390/cli9070109

AMA Style

Kumari N, Srivastava A, Dumka UC. A Long-Term Spatiotemporal Analysis of Vegetation Greenness over the Himalayan Region Using Google Earth Engine. Climate. 2021; 9(7):109. https://0-doi-org.brum.beds.ac.uk/10.3390/cli9070109

Chicago/Turabian Style

Kumari, Nikul, Ankur Srivastava, and Umesh C. Dumka. 2021. "A Long-Term Spatiotemporal Analysis of Vegetation Greenness over the Himalayan Region Using Google Earth Engine" Climate 9, no. 7: 109. https://0-doi-org.brum.beds.ac.uk/10.3390/cli9070109

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