Appraisal of Climate Response to Vegetation Indices over Tropical Climate Region in India

Author:

Awasthi Nitesh1ORCID,Tripathi Jayant Nath1,Petropoulos George P.2ORCID,Gupta Dileep Kumar3,Singh Abhay Kumar3,Kathwas Amar Kumar4,Srivastava Prashant K.5ORCID

Affiliation:

1. Department of Earth & Planetary Sciences, University of Allahabad, Prayagraj 211002, Uttar Pradesh, India

2. Department of Geography, Harokopio University of Athens, El. Venizelou St., 70, Kallithea, 17671 Athens, Greece

3. Department of Physics, Institute of Science, Banaras Hindu University, Varanasi 221005, Uttar Pradesh, India

4. Haryana Space Applications Centre, Hisar 125004, Haryana, India

5. Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi 221005, Uttar Pradesh, India

Abstract

Extreme climate events are becoming increasingly frequent and intense due to the global climate change. The present investigation aims to ascertain the nature of the climatic variables association with the vegetation variables such as Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI). In this study, the impact of climate change with respect to vegetation dynamics has been investigated over the Indian state of Haryana based on the monthly and yearly time-scale during the time period of 2010 to 2020. A time-series analysis of the climatic variables was carried out using the MODIS-derived NDVI and LAI datasets. The spatial mean for all the climatic variables except rainfall (taken sum for rainfall data to compute the accumulated rainfall) and vegetation parameters has been analyzed over the study area on monthly and yearly basis. The liaison of NDVI and LAI with the climatic variables were assessed at multi-temporal scale on the basis of Pearson correlation coefficients. The results obtained from the present investigation reveals that NDVI and LAI has strong significant relationship with climatic variables during the cropping months over study area. In contrast, during the non-cropping months, the relationship weakens but remains significant at the 0.05 significance level. Furthermore, the rainfall and relative humidity depict strong positive relationship with NDVI and LAI. On the other, negative trends were observed in case of other climatic variables due to the limitations of NDVI viz. saturation of values and lower sensitivity at higher LAI. The influence of aerosol optical depth was observed to be much higher on LAI as compared to NDVI. The present findings confirmed that the satellite-derived vegetation indices are significantly useful towards the advancement of knowledge about the association between climate variables and vegetation dynamics.

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

Reference48 articles.

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2. Adams, L., Albright, G., Belshe, K., Boyd, J.D., Brown, M.R., Bryant, C., Cowin, M., Douglas, K., Grueneich, D.M., and Spivey-Weber, F. (2010). Biennial Report, Climate Action Team. Available online: https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=7c8abf982491e80d6e34c411152b51fb1c0d6d94.

3. Effect of rainfall variability on the length of the crop growing period over the past three decades in central Malawi;Fiwa;Clim. Res.,2014

4. Lemma, W.A. (2016). Analysis of Smallholder Farmers’ Perceptions of Climate Change and Adaptation Strategies to Climate Change: The Case of Western Amhara Region, Ethiopia. [Ph.D. Thesis, University of South Africa].

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