A study on the classification of forest ecological recovery types using vegetation index based vegetation recovery rate and shannon index

This study aims to classify and analyze forest ecosystem recovery patterns in the regions of Busan and Gyeongsangnam-do, South Korea, that were affected by landslides caused by Typhoon Sanba in 2012. To evaluate both the structural and functional recovery of the forest ecosystems, we employed two complementary indicators: the Vegetation Recovery Rate (VRR), derived from time-series NDVI (Normalized Differenced Vegetation Index) data, and the Shannon Diversity Index, calculated from the 1st and 2nd national forest health management surveys. VRR quantified the recovery of vegetation cover based on NDVI changes before and after the disturbance, while the change in the Shannon Index represented functional recovery based on Shannon Index variation. Each indicator was interpreted using the median value as a relative threshold (VRR: 100.26%, Shannon Index difference: 0.1431), allowing spatial classification into four recovery types (A ~ D). Type A (high VRR and high Shannon Index difference) indicates full structural and functional recovery, while Type D (low VRR and low Shannon Index difference) signifies areas requiring priority ecological restoration. Spatial distribution patterns of recovery types revealed that Type A areas were concentrated in Ulsan and Miryang, whereas Type D areas were predominantly found in western Gyeongnam such as Hadong, Geochang, and Sancheong. This classification framework provides a basis for developing region-specific forest restoration strategies and highlights the necessity of integrating both remote sensing and field-based ecological indicators for comprehensive post-disaster assessment

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Publication Details

Journal
Journal of Climate Change Research
Published
2025-10-31
DOI
https://doi.org/10.15531/ksccr.2025.16.5.833
Primary Topic
Diverse Approaches in Healthcare and Education Studies
Type
article
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article

A study on the classification of forest ecological recovery types using vegetation index based vegetation recovery rate and shannon index

Sunjoo Lee, Jun‐Hee Lee, Kyoung-Min Kim
Journal of Climate Change Research
Diverse Approaches in Healthcare and Education Studies
article

A study on the classification of forest ecological recovery types using vegetation index based vegetation recovery rate and shannon index

Sunjoo Lee, Jun‐Hee Lee, Kyoung-Min Kim
article en

Abstract

This study aims to classify and analyze forest ecosystem recovery patterns in the regions of Busan and Gyeongsangnam-do, South Korea, that were affected by landslides caused by Typhoon Sanba in 2012. To evaluate both the structural and functional recovery of the forest ecosystems, we employed two complementary indicators: the Vegetation Recovery Rate (VRR), derived from time-series NDVI (Normalized Differenced Vegetation Index) data, and the Shannon Diversity Index, calculated from the 1st and 2nd national forest health management surveys. VRR quantified the recovery of vegetation cover based on NDVI changes before and after the disturbance, while the change in the Shannon Index represented functional recovery based on Shannon Index variation. Each indicator was interpreted using the median value as a relative threshold (VRR: 100.26%, Shannon Index difference: 0.1431), allowing spatial classification into four recovery types (A ~ D). Type A (high VRR and high Shannon Index difference) indicates full structural and functional recovery, while Type D (low VRR and low Shannon Index difference) signifies areas requiring priority ecological restoration. Spatial distribution patterns of recovery types revealed that Type A areas were concentrated in Ulsan and Miryang, whereas Type D areas were predominantly found in western Gyeongnam such as Hadong, Geochang, and Sancheong. This classification framework provides a basis for developing region-specific forest restoration strategies and highlights the necessity of integrating both remote sensing and field-based ecological indicators for comprehensive post-disaster assessment

Journal of Climate Change ResearchVol. 16(5-1)
Openalex Percentile: Top 56%
Diverse Approaches in Healthcare and Education Studies
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