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Assessment of sal (Shorea robusta) forest phenology and its response to climatic variables in India

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Abstract

Remote sensing-based observation provides an opportunity to study the spatiotemporal variations of plant phenology across the landscapes. This study aims to examine the phenological variations of different types of sal (Shorea robusta) forests in India and also to explore the relationship between phenology metrics and climatic parameters. Sal, one of the main timber-producing species of India, can be categorized into dry, moist, and very moist sal. The phenological metrics of different types of sal forests were extracted from Moderate Resolution Imaging Spectroradiometer (MODIS)-derived Enhanced Vegetation Index (EVI) time series data (2002–2015). During the study period, the average start of season (SOS) was found to be 16 May, 17 July, and 29 June for very moist, moist, and dry sal forests, respectively. The spatial distribution of mean SOS was mapped as well as the impact of climatic variables (temperature and rainfall) on SOS was investigated during the study period. In relation to the rainfall, values of the coefficient of determination (R2) for very moist, moist, and dry sal forests were 0.69, 0.68, and 0.76, respectively. However, with temperature, R2 values were found higher (R2 = 0.97, 0.81, and 0.97 for very moist, moist, and dry sal, respectively). The present study concluded that MODIS EVI is well capable of capturing the phenological metrics of different types of sal forests across different biogeographic provinces of India. SOS and length of season (LOS) were found to be the key phenology metrics to distinguish the different types of sal forests in India and temperature has a greater influence on SOS than rainfall in sal forests of India.

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The MODIS EVI 16-day composite (MOD13A2) is accessible via https://usgs.gov.

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Acknowledgements

The authors sincerely thank the Head, Forestry and Ecology Department, Dean and Director, Indian Institute of Remote Sensing, ISRO, Dehradun for their encouragement and support for this study. The authors are thankful to the MODIS Science Team, NASA, for providing the MODIS EVI data. Thanks are also due to the TIMESAT software development team for providing access to the software. The authors are grateful to the anonymous reviewers for their valuable suggestions which helped to improve the manuscript.

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  1. Indian Institute of Remote Sensing, Indian Space Research Organisation, Department of Space, Government of India, 248001, Dehradun, India

    Subrata Nandy, Surajit Ghosh & Swati Singh

  2. International Water Management Institute, Colombo, Sri Lanka

    Surajit Ghosh

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Nandy, S., Ghosh, S. & Singh, S. Assessment of sal (Shorea robusta) forest phenology and its response to climatic variables in India. Environ Monit Assess 193, 616 (2021). https://doi.org/10.1007/s10661-021-09356-9

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