A Framework for Multi-Dimensional Assessment of Wildfire Disturbance Severity from Remotely Sensed Ecosystem Functioning Attributes
نویسندگان
چکیده
Wildfire disturbances can cause modifications in different dimensions of ecosystem functioning, i.e., the flows matter and energy. There is an increasing need for methods to assess such changes, as functional approaches offer advantages over those focused solely on structural or compositional attributes. In this regard, remote sensing support indicators estimating a wide variety effects fire beyond burn severity assessment. These be described using intra-annual metrics quantity, seasonality, timing, called Ecosystem Functioning Attributes (EFAs). Here, we propose satellite-based framework evaluate impacts, at short medium term (i.e., from year second after), wildfires four functioning: (i) primary productivity, (ii) vegetation water content, (iii) albedo, (iv) sensible heat. We illustrated our approach by comparing inter-annual anomalies EFAs northwest Iberian Peninsula, 2000 2018. Random Forest models were used ability discriminate burned vs. unburned areas rank predictive importance EFAs. Together with effect sizes, ranking was select parsimonious set analyzing main wildfire both whole study area regional scale), well selected patches environmental conditions local scale). With high accuracies (area under receiver operating characteristic curve (AUC) > 0.98) sizes (Cohen’s |d| 0.8), found important all dimensions, especially productivity heat, best performance quantity metrics. Different spatiotemporal patterns across further highlighted considering multi-dimensional key aspects functioning timeframes, which allowed us diagnose abrupt lagged effects. Finally, discuss applicability potential proposed more comprehensive assessments severity.
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2021
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs13040780