RT info:eu-repo/semantics/article
T1 Burn severity influence on post-fire vegetation cover resilience from Landsat MESMA fraction images time series in Mediterranean forest ecosystems
A1 Fernández Manso, Alfonso
A1 Quintano Pastor, Carmen
A1 Roberts, Dar A.
A2 Ingenieria Agroforestal
K1 Ingeniería agrícola
K1 MESMA
K1 SMA
K1 Resiliencia (Psicología)
K1 Pinus pinaster
K1 Ecosistemas
K1 Landsat
K1 Incendios forestales
AB Mediterranean ecosystems are adapted to recurrent forest fires by having regeneration mechanisms that overcome theimmediate effects of fire. However, the increasing frequency of fires in most European Mediterranean countries is challengingthe natural regrowth capability of these ecosystems. In this context, monitoring post-fire vegetation recovery is apriority for forest management and soil erosion control. In this work, a 13-year series (1999–2011) of Landsat 5 ThematicMapper (TM)/Landsat 7 Enhanced Thematic Mapper (ETM +) data was used to model post-fire vegetation recovery as afunction of burn severity and to quantify post-fire resilience as a measure of vegetation cover regrowth. We evaluated alarge forest fire located in Spain that burned approximately 30 km2 of Pinus pinaster Ait. in August 1998. 88 field plots offour burn severity levels (unburned, low, moderate and high) were measured in the field a year after the fire. As a variablerepresentative of vegetation, we chose the shade normalized green vegetation fraction image (SGV) obtained by applyingMultiple Endmember Spectral Mixture Analysis (MESMA) to the original Landsat TM/ETM + images. The SGV valueswere extracted for the 88 field plots and, after performing a one-way analysis of variance (ANOVA), a Fisher's LeastSignificant Difference (LSD) test allowed us to estimate resilience of vegetation cover as the number of post-fire yearsexhibiting a statistically significant difference between burned and unburned areas. Next, SGV values were referencedto unburned control plots values and the vegetation recovery index (VRI) was defined. The evolution in time curve ofVRI for low, moderate and highly fire affected vegetation was fit using trend models (specifically, an exponential trendfor VRI in high and moderate burn severity levels; a linear trend for low burn severity level, Root Mean Square Error,RMSE = 0.18, 0.13, and 0.09, respectively). We observed that vegetation cover affected by low severity fire recoveredto its original state after 7 years, and vegetation cover affected by moderate severity recovered after 13 years. Vegetationaffected by high severity fire was estimated to recover after 20 years. We conclude that VRI time series based on multitemporalMESMA fractions from Landsat data can be considered a valuable indicator of the post-fire vegetation coverrecovery. Its temporal evolution represented post-fire vegetation cover regrowth adequately and facilitated the estimateof vegetation cover resilience in Mediterranean forests
PB Elsevier
YR 2017
FD 2017-09-29
LK http://hdl.handle.net/10612/6821
UL http://hdl.handle.net/10612/6821
NO Remote Sensing of Environment, 2016
NO 14 p.
DS BULERIA. Repositorio Institucional de la Universidad de León
RD 25-abr-2024