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. 2022 Dec;29(57):86362-86373.
doi: 10.1007/s11356-022-19711-z. Epub 2022 Mar 22.

Impact of climate on vegetation in Pindari watershed of Western Himalayas, Kumaun, India, using spatiotemporal analysis: 1972-2018

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Impact of climate on vegetation in Pindari watershed of Western Himalayas, Kumaun, India, using spatiotemporal analysis: 1972-2018

Arvind Pandey et al. Environ Sci Pollut Res Int. 2022 Dec.

Abstract

Vegetation dynamics is an important aspect for determining climate change trends. The present study delineates to examine spatiotemporal changes of vegetation cover in Pindari valley (Kumaun Himalaya) from the 1972 to 2018 timeline. The study includes the calculation of vegetation spectral indices of normalized vegetation index (NDVI), extraction of different vegetation classes, and statistical analysis of the Mann-Kendall (MK) test on historical metrological data (especially precipitation and temperature) of the study site. For the statistical analysis of metrological data, the power data access viewer datasets have been used. The central feature classes of the study are grassland, scrubland, and forest cover. The results revealed that the region's forest cover significantly decreased by 24.74 sq. km from 1972 to 2018, increased in grassland cover by 17.84 sq. km, respectively, and a slight increase in scrubland class by 3.13 sq. km for the study period. The calculated NDVI shows significant changes over the study location; it has been noticed that the maximum values of the NDVI decreased by 0.24, and the minimum values show growth of about 0.047. The analysis indicates that climatic parameters such as precipitation and temperature are the main limiting factors affecting vegetation growth. The annual mean maximum temperature showed a decreasing trend. The estimated results show an increase in annual rainfall and annual minimum temperature, while the decreasing trend is observed in the case of maximum annual temperature. Objectives of the study are (1) spatiotemporal analysis of the vegetation cover, (2) identification of the main causes of change in the vegetation cover, and (3) statistical trend analysis of long-term metrological data. The outcome of the presented research work would be beneficial for the proper management and monitoring of the forest ecosystem.

Keywords: Landsat; Normalized vegetation index; Power data access viewer; Remote sensing; Statistical analysis; Vegetation cover.

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