Spatio-temporal patterns of optimal Landsat data for burn severity index calculations: Implications for high northern latitudes wildfire research

REMOTE SENSING OF ENVIRONMENT

卷:258

Article

Chen, Dong¹  Fu, Cheng²  Hall, Joanne V.¹  Hoy, Elizabeth E.³  Loboda, Tatiana V.¹ 

[1] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA

[2] Univ Zurich, Dept Geog, Zurich, Switzerland

[3] NASA, Global Sci & Technol Inc, Goddard Space Flight Ctr, Greenbelt, MD USA

关键词: Boreal forest;    Tundra;    Arctic;    Alaska;    Canada;    Remote sensing;    Disturbance;    Wildfire;    Burn severity;    dNBR;    Landsat;    Google Earth Engine;   

DOI  :  10.1016/j.rse.2021.112393

来源: Elsevier

【 摘 要 】

Satellite remote sensing has been widely used for the evaluation of wildfire burn severity in various ecosystems. While a variety of remote sensing-based burn severity indices have been developed, the Landsat-based differenced Normalized Burn Ratio (dNBR) presents the most widely-used approach to burn severity assessment for fire research and management. Although dNBR-based approaches have been continuously updated, including the development of the relative dNBR (RdNBR) and the Relativized Burn Ratio (RBR), one key obstacle for the reliable applications of the burn severity indices in the high northern latitudes has not been adequately addressed. Specifically, optimal Landsat image pairs are very rarely available for the calculation of the burn severity indices in certain regions of the high northern latitudes (HNL), resulting in the burn severity index outputs calculated for a large number of wildfires being considerably affected by non-fire-related factors. The suboptimal selection of image pairs may have partially contributed to the lack of consistency in the performance of the burn severity indices in the HNL regions. In this paper, we systematically evaluated the impacts of sub-optimal image pairs on signal stability through two sets of analyses conducted at different spatial scales. First, at the regional scale, we examined the burn severity indices calculated for a selection of wildfires in Alaska. Here, we demonstrate the inconsistent performance of the same index calculated based on Landsat data that are typically considered as optimal. In addition, we show that the calculated indices may be more prone to the negative impacts of these inconsistencies, thus leading to reduced reliability, when there is limited Landsat data availability. Second, at the continental scale, we show that certain areas in the HNL, especially Alaska during the pre-2000 era, are subject to the potentially strong negative impact associated with the limited data availability. Through systematically analyzing this issue, we hope to not only divert more attention to it but also to provide potential solutions, based on which further improvements that may be of particular importance for research on Arctic wildfires could be made.

【 授权许可】

Free