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Quantifying forest resilience post forest fire disturbances using time-series satellite data.

Sumedha Surbhi Singh1, C Jeganathan2

  • 1Department of Remote Sensing, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India.

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This study introduces a new framework to quantify forest resilience using satellite data, assessing vegetation recovery after disturbances. Findings highlight the northern region of Bandhavgarh National Park

Keywords:
Bandhavgarh National ParkEVIForest fireForest resilienceIndiaMadhya Pradesh

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Area of Science:

  • Ecology
  • Remote Sensing
  • Environmental Science

Background:

  • Forest resilience is vital for biodiversity and ecosystem health amidst environmental changes.
  • Accurate measurement of forest resilience is crucial for sustainable forest management.
  • Existing methods using Landsat data face challenges in continuous monitoring due to cloud cover.

Purpose of the Study:

  • To develop a framework for estimating forest resilience scores after disturbances.
  • To assess vegetation condition and recovery using satellite-derived indices.
  • To investigate the relationship between human occupation and forest resilience.

Main Methods:

  • Utilized MODIS 16-day EVI products (2001-2020) for vegetation health monitoring.
  • Calculated resilience scores based on recovery days, phenological performance, and greenness levels.
  • Applied the framework to Bandhavgarh National Park, India, focusing on a 2018 forest fire event.

Main Results:

  • Developed a novel resilience index incorporating multiple vegetation metrics.
  • Identified the northern part of Bandhavgarh National Park as more vulnerable with slower recovery.
  • Investigated the correlation between local human population and forest resilience.

Conclusions:

  • The proposed framework effectively quantifies forest resilience and post-disturbance recovery.
  • The study provides insights into regional variations in forest vulnerability and recovery rates.
  • Understanding human impact is essential for effective forest resilience management.