The 2019-20 Kangaroo Island bushfires in South Australia burned almost half of the island. To understand how to avoid future severe ‘mega-fires’ and how vegetation may recover from 2019–2020, we can utilize information from the bulk of historical fires in an area. Landsat time-series of vegetation change provide this opportunity, but there has been little analysis of large numbers of fires to build a landscape-level understanding and quantify drivers in an Australian context. In this study, we built a yearly cloud-free surface reflectance normalized burn ratio (NBR) time-series (1988–2020) using all available summer Landsat images over Kangaroo Island. Data were collected in Google Earth Engine and fitted with LandTrendr. Burn severity and post-fire recovery were quantified for 47 fires, with a new recovery metric facilitating comparison where fire frequency is high. Variables representing the current burn, fire history, vegetation structure, and topography were related to severity and yearly recovery with random forest and bivariate analysis. Results show that the 2019–20 bushfires were the most widespread and severe, followed by 2007–08. Vegetation recovers quickly, with NBR stabilizing ten years post-fire on average. Severity is most influenced by fire frequency, vegetation capacity and land use with more severe burns in nature conservation areas with dense vegetation and a history of frequent fires. Influence on recovery varied with time since fire, with initial (year 1–3) faster recovery observed in areas with less surviving vegetation. Later (year 6–10) recovery was most influenced by a variable representing burn year and further investigation indicates that precipitation increases in later post-fire years likely facilitated faster recovery. The relative abundance of eucalypt woodlands also has a positive influence on recovery in middle and later years. These results provide valuable information to land managers on Kangaroo Island and in similar environments, who should consider adjusting practices to limit future mega-fire risk and potential ecosystem shifts if severe fires become more frequent with climate change.

中文翻译：

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将2019–20袋鼠岛森林大火的背景信息化：使用Landsat和Google Earth Engine量化景观水平对过去严重性和恢复的影响

南澳大利亚州的2019-20袋鼠岛森林大火烧毁了该岛的近一半。为了了解如何避免将来发生严重的“特大火灾”以及如何在2019–2020年期间恢复植被，我们可以利用该地区大部分历史火灾的信息。Landsat植被变化的时间序列提供了这一机会，但是很少有大量火灾的分析来建立景观层次的理解并量化澳大利亚环境下的驱动因素。在这项研究中，我们使用袋鼠岛上所有可用的夏季Landsat影像，建立了一个年度无云表面反射率归一化燃烧比（NBR）时间序列（1988–2020）。数据是在Google Earth Engine中收集的，并装有LandTrendr。量化了47次火灾的烧伤严重程度和火灾后恢复，新的恢复指标有助于在高发火频率时进行比较。通过随机森林和双变量分析，代表当前烧伤，火灾历史，植被结构和地形的变量与严重程度和年恢复相关。结果表明，2019-20年度的丛林大火最为普遍和严重，其次是2007-08年度。植被恢复迅速，NBR在火灾后平均稳定十年。严重程度受火灾频率，植被容量和土地利用的影响最大，在植被茂密且有大火历史的自然保护区，烧伤更为严重。自火灾以来，对恢复的影响随时间而变化，在植被存活率较低的地区，最初（1-3年）恢复较快。后期（6-10年）的恢复受表示燃烧年的变量的影响最大，进一步的研究表明，火灾后后期降水增加可能促进了较快的恢复。桉树林地的相对丰富度对中后期的恢复也有积极影响。这些结果为袋鼠岛和类似环境中的土地管理者提供了宝贵的信息，他们应该考虑调整做法，以限制未来的特大火灾风险和潜在的生态系统转移（如果气候变化导致大火更加频繁）。