Comparison of Post-fire Patterns in Brazilian Savanna and Tropical Forest from Remote Sensing Time Series

Monitoring of fire-related changes is essential to understand vegetation dynamics in the medium and long term. Remote sensing time series allows estimating biophysical variables of terrestrial vegetation and interference by extreme fires. This research evaluated fire recurrence in the Amazon and Cerrado regions, using Moderate Resolution Imaging Spectroradiometer (MODIS) albedo time series, enhanced vegetation index (EVI), gross primary productivity (GPP), and surface temperature. The annual aggregated time series (AAT) method recognized each pixel’s slope trend in the 2001–2016 period and its statistical significance. A comparison of time trends of EVI, GPP, and surface temperature with total fire recurrence indicates that time trends in vegetation are highly affected by high fire recurrence scenarios (R2 between 0.52 and 0.90). The fire recurrence and the albedo’s persistent changes do not have a consistent relationship. Areas with the biggest evaluated changes may increase up to 0.25 Kelvin/Year at surface temperature and decrease up to −0.012 EVI/year in vegetation index. Although savannas are resistant to low severity fires, fire regime and forest structure changes tend to make vegetation more vulnerable to wildfires, reducing their regeneration capacity. In the Amazon area, protection of forests in conservation units and indigenous lands helped in the low occurrence of fires in these sensitive areas, resulting in positive vegetation index trends.

Determinant factors of fire recurrence in Cerrado: focus in vegetation recuperation and aids for protected areas management

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Remote sensing time series to assess fire recurrence patterns over Campos Amazônicos National Park

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Likelihood and frequency of recurrent fire ignitions in highly urbanised Mediterranean landscapes

Fire recurrence plays a key role in shaping landscapes in Mediterranean ecosystems. Short-term recurrent fires, in particular, are increasingly affecting highly urbanised landscapes. Studies worldwide have addressed fire recurrence by analysing environmental, climatic and human-driven factors. Current models use fire recurrence polygons as the dependent variable; yet no published study has focused its analysis on fire recurrence considering recurrent ignition points as the response variable. To fill this gap, remote sensing and available local data were combined to analyse the influence of human and biophysical variables in predicting both the likelihood and frequency of recurrent fire ignition points over a 9-year period (2004–12) in southern Italy. For this purpose, we used the Negative Binomial Hurdle model owing to the stochastic nature of the phenomenon of fire recurrence and the (large) number of non-occurrences. Results on the likelihood and frequency of recurrent fire ignition points (dependent variables) suggested that road distance was the strongest predictor, followed by the presence of shrublands and grasslands. The response variable showed a negative relationship with population density and road distance and a positive relationship with land-cover variables. Vegetation indices were also good predictors of fire recurrence. More broadly, this study is intended to be a further experimental step in fire-management analysis characterised by the continuous interaction between human and natural systems. Constant changes between these systems due to causes such as urban sprawl and climate change can create the conditions for short-term-interval recurrent fires.

Fire Recurrence and Normalized Difference Vegetation Index (NDVI) Dynamics in Brazilian Savanna

Fire is one of the main modeling agents of savanna ecosystems, affecting their distribution, physiognomy and species diversity. Changes in the natural fire regime on savannas cause disturbances in the structural characteristics of vegetation. Theses disturbances can be effectively monitored by time series of remote sensing data in different terrestrial ecosystems such as savannas. This study used trend analysis in NDVI (Normalized Difference Vegetation Index)–MODIS (Moderate Resolution Imaging Spectroradiometer) time series to evaluate the influence of different fire recurrences on vegetation phenology of the Brazilian savanna in the period from 2001 to 2016. The trend analysis indicated several factors responsible for changes in vegetation: (a) The absence of fire in savanna phytophysiognomies causes a constant increase in MODIS–NDVI, ranging from 0.001 to 0.002 per year, the moderate presence of fire in these areas does not cause significant changes, while the high recurrence results in decreases of MODIS–NDVI, ranging from −0.002 to −0.008 per year; (b) Forest areas showed a high decrease in NDVI, reaching up to −0.009 MODIS–NDVI per year, but not related to fire recurrence, indicating the high degradation of these phytophysiognomies; (c) Changes in vegetation are highly connected to the protection status of the area, such as areas of integral protection or sustainable use, and consequently their conservation status. Areas with greater vegetation conservation had more than 70% of positive changes in pixels with significant tendencies. Absence or presence of fire are the main agents of vegetation change in areas with lower anthropic influence. These results reinforce the need for a suitable fire management policy for the different types of Cerrado phytophysiognomies, in addition to highlighting the efficiency of remote sensing time series for evaluation of vegetation phenology.