A Framework for Multi-Dimensional Assessment of Wildfire Disturbance Severity from Remotely Sensed Ecosystem Functioning Attributes
Metadatos
Mostrar el registro completo del ítemEditorial
MDPI
Materia
Ecological disturbance Ecosystem functioning Ecosystem functioning attributes (EFAs) Fire severity Satellite image time-series Wildfire
Fecha
2021-02-20Referencia bibliográfica
Marcos, B.; Gonçalves, J.; Alcaraz-Segura, D.; Cunha, M.; Honrado, J.P. A Framework for Multi-Dimensional Assessment of Wildfire Disturbance Severity from Remotely Sensed Ecosystem Functioning Attributes. Remote Sens. 2021, 13, 780. [https://doi.org/10.3390/rs13040780]
Patrocinador
Portuguese national funds through FCT-Foundation for Science and Technology, I.P., under the GreenRehab project PCIF/RPG/0077/2017; Junta de Andalucia P18-RT-1927; European Union Funds for Regional Development; Project DETECTOR A-RNM-256-UGR18; European Commission; Portuguese Foundation for Science and Technology European Commission; Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) European Commission; European Social Fund, within the 2014-2020 EU Strategic Framework, through FCT SFRH/BD/99469/2014; Individual Scientific Employment Stimulus Program (2017), through FCT CEECIND/02331/2017Resumen
Wildfire disturbances can cause modifications in different dimensions of ecosystem functioning,
i.e., the flows of 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 can support indicators for estimating a
wide variety of effects of fire on ecosystem functioning, beyond burn severity assessment. These
indicators can be described using intra-annual metrics of quantity, seasonality, and timing, called
Ecosystem Functioning Attributes (EFAs). Here, we propose a satellite-based framework to evaluate
the impacts, at short to medium term (i.e., from the year of fire to the second year after), of wildfires
on four dimensions of ecosystem functioning: (i) primary productivity, (ii) vegetation water content,
(iii) albedo, and (iv) sensible heat. We illustrated our approach by comparing inter-annual anomalies
in satellite-based EFAs in the northwest of the Iberian Peninsula, from 2000 to 2018. Random Forest
models were used to assess the ability of EFAs to discriminate burned vs. unburned areas and to
rank the predictive importance of EFAs. Together with effect sizes, this ranking was used to select a
parsimonious set of indicators for analyzing the main effects of wildfire disturbances on ecosystem
functioning, for both the whole study area (i.e., regional scale), as well as for four selected burned
patches with different environmental conditions (i.e., local scale). With both high accuracies (area
under the receiver operating characteristic curve (AUC) > 0.98) and effect sizes (Cohen’s |d| > 0.8),
we found important effects on all four dimensions, especially on primary productivity and sensible
heat, with the best performance for quantity metrics. Different spatiotemporal patterns of wildfire
severity across the selected burned patches for different dimensions further highlighted the
importance of considering the multi-dimensional effects of wildfire disturbances on key aspects of
ecosystem functioning at different timeframes, which allowed us to diagnose both abrupt and lagged
effects. Finally, we discuss the applicability as well as the potential advantages of the proposed
approach for more comprehensive assessments of fire severity.