Leveraging remote sensing and cloud computing for assessing bushfire impacts on forest ecosystems

Ramildo Passos; Xiaoye Liu; Zhenyu Zhang

doi:10.1117/12.3050481

20 December 2024 Leveraging remote sensing and cloud computing for assessing bushfire impacts on forest ecosystems

Ramildo Passos, Xiaoye Liu, Zhenyu Zhang

Author Affiliations +

Proceedings Volume 13266, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications VIII; 1326610 (2024) https://doi.org/10.1117/12.3050481
Event: Asia-Pacific Remote Sensing, 2024, Kaohsiung, Taiwan

Conference Poster

Abstract

Bushfires are key drivers of ecological processes, particularly in fire-prone regions like Australia, where they shape forest ecosystems and affect biodiversity. Monitoring landscape recovery dynamics after bushfires is crucial for understanding ecosystem resilience. This study focuses on monitoring post-bushfire landscape recovery dynamics using remote sensing data and cloud computing. Landsat imagery from 2007 to 2024 was analyzed via Google Earth Engine (GEE) to create cloud-free surface reflectance composites. The primary objective was to assess spectral recovery patterns across different burn severity classes in two areas of Southeast Victoria, Australia. The study utilized Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR) as spectral indices to evaluate the post-fire spectral recovery. Findings revealed that the NBR demonstrated a longer spectral recovery duration compared to NDVI, especially in areas severely affected by bushfires. The results show that remote sensing combined with spectral indices is an effective approach to detecting, mapping, and understanding the recovery processes in post-bushfire landscapes. The study highlights the utility of remote sensing technologies in environmental monitoring and emphasizes the need for further research to refine these methodologies and address limitations, such as the inability to capture sub-canopy dynamics and the effects of topography on recovery. This research provides valuable insights for improving environmental management strategies and enhancing the understanding of landscape recovery following severe fire disturbances.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ramildo Passos, Xiaoye Liu, and Zhenyu Zhang "Leveraging remote sensing and cloud computing for assessing bushfire impacts on forest ecosystems", Proc. SPIE 13266, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications VIII, 1326610 (20 December 2024); https://doi.org/10.1117/12.3050481

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