Tracking Post-Fire Vegetation Regrowth and Burned Areas Using Bitemporal Sentinel-1 SAR Data: A Google Earth Engine Approach in Heath Vegetation of Mooloolah River National Park, Queensland, Australia
This study utilizes the unique capabilities of Sentinel-1 C-band synthetic aperture radar (SAR) data to map post-fire burned areas and monitor vegetation recovery in a heath-dominated Queensland National Park. Sentinel-1 SAR data were used due to their cloud-penetrating capability and frequent revis...
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MDPI AG
2025-06-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/12/2031 |
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| author | Harikesh Singh Prashant K. Srivastava Rajendra Prasad Sanjeev Kumar Srivastava |
| author_facet | Harikesh Singh Prashant K. Srivastava Rajendra Prasad Sanjeev Kumar Srivastava |
| author_sort | Harikesh Singh |
| collection | DOAJ |
| description | This study utilizes the unique capabilities of Sentinel-1 C-band synthetic aperture radar (SAR) data to map post-fire burned areas and monitor vegetation recovery in a heath-dominated Queensland National Park. Sentinel-1 SAR data were used due to their cloud-penetrating capability and frequent revisit times. Using Google Earth Engine (GEE), a bitemporal ratio analysis was applied to SAR data from post-fire periods between 2021 and 2023. SAR backscatter changes over time captured fire impacts and subsequent vegetation regrowth. This differentiation was further enhanced with k-means clustering. Validation was supported by Sentinel-2 dNBR and official fire history records. The dNBR provided a quantitative assessment of burn severity and was used alongside the fire history data to evaluate the accuracy of the burned area classification. While Sentinel-2 false-colour composite (FCC) imagery was generated for visualisation and interpretation purposes, the primary validation relied on dNBR and QPWS fire history records. The results highlighted significant vegetation regrowth, with some areas returning to near pre-fire biomass levels by March 2023. This approach demonstrates the sensitivity of Sentinel-1 SAR, especially in VV polarization, for detecting subtle changes in vegetation, providing a cost-effective method for post-fire ecosystem monitoring and informing ecological management strategies amid increasing wildfire events. |
| format | Article |
| id | doaj-art-d48f687bb7bb4a928649134cf9b1a104 |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-d48f687bb7bb4a928649134cf9b1a1042025-08-20T03:16:39ZengMDPI AGRemote Sensing2072-42922025-06-011712203110.3390/rs17122031Tracking Post-Fire Vegetation Regrowth and Burned Areas Using Bitemporal Sentinel-1 SAR Data: A Google Earth Engine Approach in Heath Vegetation of Mooloolah River National Park, Queensland, AustraliaHarikesh Singh0Prashant K. Srivastava1Rajendra Prasad2Sanjeev Kumar Srivastava3Geospatial Analytics for Conservation & Management, School of Science Engineering and Technology, University of the Sunshine Coast, Maroochydore, QLD 4558, AustraliaGeospatial Analytics for Conservation & Management, School of Science Engineering and Technology, University of the Sunshine Coast, Maroochydore, QLD 4558, AustraliaDepartment of Physics, Indian Institute of Technology (BHU), Varanasi 221005, IndiaGeospatial Analytics for Conservation & Management, School of Science Engineering and Technology, University of the Sunshine Coast, Maroochydore, QLD 4558, AustraliaThis study utilizes the unique capabilities of Sentinel-1 C-band synthetic aperture radar (SAR) data to map post-fire burned areas and monitor vegetation recovery in a heath-dominated Queensland National Park. Sentinel-1 SAR data were used due to their cloud-penetrating capability and frequent revisit times. Using Google Earth Engine (GEE), a bitemporal ratio analysis was applied to SAR data from post-fire periods between 2021 and 2023. SAR backscatter changes over time captured fire impacts and subsequent vegetation regrowth. This differentiation was further enhanced with k-means clustering. Validation was supported by Sentinel-2 dNBR and official fire history records. The dNBR provided a quantitative assessment of burn severity and was used alongside the fire history data to evaluate the accuracy of the burned area classification. While Sentinel-2 false-colour composite (FCC) imagery was generated for visualisation and interpretation purposes, the primary validation relied on dNBR and QPWS fire history records. The results highlighted significant vegetation regrowth, with some areas returning to near pre-fire biomass levels by March 2023. This approach demonstrates the sensitivity of Sentinel-1 SAR, especially in VV polarization, for detecting subtle changes in vegetation, providing a cost-effective method for post-fire ecosystem monitoring and informing ecological management strategies amid increasing wildfire events.https://www.mdpi.com/2072-4292/17/12/2031Sentinel-1 SARbitemporal ratio analysispost-fire vegetation recoveryGoogle Earth Engine (GEE)burned area mappingvegetation regrowth |
| spellingShingle | Harikesh Singh Prashant K. Srivastava Rajendra Prasad Sanjeev Kumar Srivastava Tracking Post-Fire Vegetation Regrowth and Burned Areas Using Bitemporal Sentinel-1 SAR Data: A Google Earth Engine Approach in Heath Vegetation of Mooloolah River National Park, Queensland, Australia Remote Sensing Sentinel-1 SAR bitemporal ratio analysis post-fire vegetation recovery Google Earth Engine (GEE) burned area mapping vegetation regrowth |
| title | Tracking Post-Fire Vegetation Regrowth and Burned Areas Using Bitemporal Sentinel-1 SAR Data: A Google Earth Engine Approach in Heath Vegetation of Mooloolah River National Park, Queensland, Australia |
| title_full | Tracking Post-Fire Vegetation Regrowth and Burned Areas Using Bitemporal Sentinel-1 SAR Data: A Google Earth Engine Approach in Heath Vegetation of Mooloolah River National Park, Queensland, Australia |
| title_fullStr | Tracking Post-Fire Vegetation Regrowth and Burned Areas Using Bitemporal Sentinel-1 SAR Data: A Google Earth Engine Approach in Heath Vegetation of Mooloolah River National Park, Queensland, Australia |
| title_full_unstemmed | Tracking Post-Fire Vegetation Regrowth and Burned Areas Using Bitemporal Sentinel-1 SAR Data: A Google Earth Engine Approach in Heath Vegetation of Mooloolah River National Park, Queensland, Australia |
| title_short | Tracking Post-Fire Vegetation Regrowth and Burned Areas Using Bitemporal Sentinel-1 SAR Data: A Google Earth Engine Approach in Heath Vegetation of Mooloolah River National Park, Queensland, Australia |
| title_sort | tracking post fire vegetation regrowth and burned areas using bitemporal sentinel 1 sar data a google earth engine approach in heath vegetation of mooloolah river national park queensland australia |
| topic | Sentinel-1 SAR bitemporal ratio analysis post-fire vegetation recovery Google Earth Engine (GEE) burned area mapping vegetation regrowth |
| url | https://www.mdpi.com/2072-4292/17/12/2031 |
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