Detecting Burn Severity and Vegetation Recovery After Fire Using dNBR and dNDVI Indices: Insight from the Bosco Difesa Grande, Gravina in Southern Italy

Wildfires serve a paradoxical role in landscapes—supporting biodiversity and nutrient cycling while also threatening ecosystems and economies, especially as climate change intensifies their frequency and severity. This study investigates the impact of wildfires and vegetation recovery in the Bosco D...

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Main Authors: Somayeh Zahabnazouri, Patrick Belmont, Scott David, Peter E. Wigand, Mario Elia, Domenico Capolongo
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Sensors
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Online Access:https://www.mdpi.com/1424-8220/25/10/3097
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author Somayeh Zahabnazouri
Patrick Belmont
Scott David
Peter E. Wigand
Mario Elia
Domenico Capolongo
author_facet Somayeh Zahabnazouri
Patrick Belmont
Scott David
Peter E. Wigand
Mario Elia
Domenico Capolongo
author_sort Somayeh Zahabnazouri
collection DOAJ
description Wildfires serve a paradoxical role in landscapes—supporting biodiversity and nutrient cycling while also threatening ecosystems and economies, especially as climate change intensifies their frequency and severity. This study investigates the impact of wildfires and vegetation recovery in the Bosco Difesa Grande forest in southern Italy, focusing on the 2017 and 2021 fire events. Using Google Earth Engine (GEE) accessed in January 2025, we applied remote sensing techniques to assess burn severity and post-fire regrowth. Sentinel-2 imagery was used to compute the Normalized Burn Ratio (NBR) and Normalized Difference Vegetation Index (NDVI); burn severity was derived from differenced NBR (dNBR), and vegetation recovery was monitored via differenced NDVI (dNDVI) and multi-year NDVI time series. We uniquely compare recovery across four zones with different fire histories—unburned, single-burn (2017 or 2021), and repeated-burn (2017 and 2021)—providing a novel perspective on post-fire dynamics in Mediterranean ecosystems. Results show that low-severity zones recovered more quickly than high-severity areas. Repeated-burn zones experienced the slowest and least complete recovery, while unburned areas remained stable. These findings suggest that repeated fires may shift vegetation from forest to shrubland. This study highlights the importance of remote sensing for post-fire assessment and supports adaptive land management to enhance long-term ecological resilience.
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spelling doaj-art-59cdc1de23ee4371a06cc4ef30a5df3a2025-08-20T03:48:02ZengMDPI AGSensors1424-82202025-05-012510309710.3390/s25103097Detecting Burn Severity and Vegetation Recovery After Fire Using dNBR and dNDVI Indices: Insight from the Bosco Difesa Grande, Gravina in Southern ItalySomayeh Zahabnazouri0Patrick Belmont1Scott David2Peter E. Wigand3Mario Elia4Domenico Capolongo5Department of Earth and Geo-Environmental Sciences, University of Bari Aldo Moro, 70121 Bari, ItalyDepartment of Watershed Sciences, Utah State University, Logan, UT 84322, USADepartment of Watershed Sciences, Utah State University, Logan, UT 84322, USADivision of Earth and Ecosystem Sciences, Desert Research Institute, Reno, NV 89512, USADepartment of Agricultural and Environmental Sciences, University of Bari Aldo Moro, 70121 Bari, ItalyDepartment of Earth and Geo-Environmental Sciences, University of Bari Aldo Moro, 70121 Bari, ItalyWildfires serve a paradoxical role in landscapes—supporting biodiversity and nutrient cycling while also threatening ecosystems and economies, especially as climate change intensifies their frequency and severity. This study investigates the impact of wildfires and vegetation recovery in the Bosco Difesa Grande forest in southern Italy, focusing on the 2017 and 2021 fire events. Using Google Earth Engine (GEE) accessed in January 2025, we applied remote sensing techniques to assess burn severity and post-fire regrowth. Sentinel-2 imagery was used to compute the Normalized Burn Ratio (NBR) and Normalized Difference Vegetation Index (NDVI); burn severity was derived from differenced NBR (dNBR), and vegetation recovery was monitored via differenced NDVI (dNDVI) and multi-year NDVI time series. We uniquely compare recovery across four zones with different fire histories—unburned, single-burn (2017 or 2021), and repeated-burn (2017 and 2021)—providing a novel perspective on post-fire dynamics in Mediterranean ecosystems. Results show that low-severity zones recovered more quickly than high-severity areas. Repeated-burn zones experienced the slowest and least complete recovery, while unburned areas remained stable. These findings suggest that repeated fires may shift vegetation from forest to shrubland. This study highlights the importance of remote sensing for post-fire assessment and supports adaptive land management to enhance long-term ecological resilience.https://www.mdpi.com/1424-8220/25/10/3097wildfireburn severityvegetation recoveryGoogle Earth enginevegetation indicesBosco Difesa Grande
spellingShingle Somayeh Zahabnazouri
Patrick Belmont
Scott David
Peter E. Wigand
Mario Elia
Domenico Capolongo
Detecting Burn Severity and Vegetation Recovery After Fire Using dNBR and dNDVI Indices: Insight from the Bosco Difesa Grande, Gravina in Southern Italy
Sensors
wildfire
burn severity
vegetation recovery
Google Earth engine
vegetation indices
Bosco Difesa Grande
title Detecting Burn Severity and Vegetation Recovery After Fire Using dNBR and dNDVI Indices: Insight from the Bosco Difesa Grande, Gravina in Southern Italy
title_full Detecting Burn Severity and Vegetation Recovery After Fire Using dNBR and dNDVI Indices: Insight from the Bosco Difesa Grande, Gravina in Southern Italy
title_fullStr Detecting Burn Severity and Vegetation Recovery After Fire Using dNBR and dNDVI Indices: Insight from the Bosco Difesa Grande, Gravina in Southern Italy
title_full_unstemmed Detecting Burn Severity and Vegetation Recovery After Fire Using dNBR and dNDVI Indices: Insight from the Bosco Difesa Grande, Gravina in Southern Italy
title_short Detecting Burn Severity and Vegetation Recovery After Fire Using dNBR and dNDVI Indices: Insight from the Bosco Difesa Grande, Gravina in Southern Italy
title_sort detecting burn severity and vegetation recovery after fire using dnbr and dndvi indices insight from the bosco difesa grande gravina in southern italy
topic wildfire
burn severity
vegetation recovery
Google Earth engine
vegetation indices
Bosco Difesa Grande
url https://www.mdpi.com/1424-8220/25/10/3097
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