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Temporal dynamics of above ground biomass of Kaimoor Wildlife Sanctuary, Uttar Pradesh, India: conjunctive use of field and Landsat data

Abstract

The present study assesses the temporal dynamics of above ground biomass (AGB) in Kaimoor Wildlife Sanctuary (KWS), Uttar Pradesh, India using series of Landsat data for the years 1989, 2000, 2010 and 2018. The satellite images were preprocessed for surface reflectance, and subsequently we computed Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Enhanced Vegetation Index (EVI). A forest density map was generated by slicing the computed NDVI and this was used as a basis for sampling strategy. A total of 30 sampling locations were randomly identified. Plot size of 30 m × 30 m was established. Tree species were enumerated at each plot and the girth at breast height and tree height measurements were recorded for the year 2018. Tree and plot level AGB (i.e. AGBF, t ha−1) was computed by multiplying the tree volume and specific gravity of wood. AGB (i.e. AGBP) prediction models were developed as linear regression equations for the year 2018 by assessing the vegetation indices and the AGBF. The significant AGBP models (R2 = 0.94; P = 0.0001) were applied for all study years after the data correction among the Landsat sensor series. The AGBP was over estimated (22.67 t ha−1; 7.75%) compared to AGBF (t ha−1). Moreover, EVI (R2 = 0.90) was found to be a better predictor for AGB compared to NDVI (R2 = 0.69) or SAVI (R2 = 0.77). The AGBP of KWS ranged between 289 ± 36 (in 1989) and 292 ± 40 (in 2018) with an average decadal positive change of 1.06%.

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Data availability

The satellite data used in this analysis is available on USGS website. The secondary data used is available on www.vindhyabachao.org.

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Acknowledgements

We thank the USGS (https://earthexplorer.usgs.gov/) for providing Landsat data free-of-cost. We are also grateful to the forest authorities of KWS for permitting forest inventory and data collection.

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No funding in any form has been received by any of the authors.

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Contributions

LG proposed, analyzed the data and prepared a draft, RM contributed in the analysis of field data and preparation of models from remote sensing data. FA helped in collection and preprocessing of satellite data and provided critical analysis for the study and DS provided field related inputs, JSS provided critical analysis and suggestions for the development of the manuscript.

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Correspondence to Laxmi Goparaju.

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Goparaju, L., Madugundu, R., Ahmad, F. et al. Temporal dynamics of above ground biomass of Kaimoor Wildlife Sanctuary, Uttar Pradesh, India: conjunctive use of field and Landsat data. Proc.Indian Natl. Sci. Acad. 87, 499–513 (2021). https://doi.org/10.1007/s43538-021-00046-1

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Keywords

  • Normalized Difference Vegetation Index (NDVI)
  • Enhanced Vegetation Index (EVI)
  • Soil Adjusted Vegetation Index (SAVI)
  • Biomass
  • Kaimoor
  • Tropical forests
  • Regression