Spatial and temporal patterns of vegetation recovery following sequences of forest fires in a Mediterranean landscape, Mt. Carmel Israel

Wittenberg, Lea; Malkinson, Dan; Beeri, Ofer; Halutzy, Alon; Tesler, Naama

doi:10.1016/j.catena.2006.10.007

Cited by 116 publications

(97 citation statements)

References 28 publications

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“…Remote sensing has been widely used to study Mediterranean ecosystems, namely to evaluate the climate impact on vegetation dynamics (Vicente-Serrano and HerediaLaclaustra, 2004;Julien et al, 2006;, to monitor post-fire vegetation recovery (Wittenberg et al, 2007;Röder et al, 2008;Malkinson et al, 2011) as well as to assess fire risk (Chuvieco et al, 2010) and burn severity (De Santis and Chuvieco, 2007;Fox et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Drought impacts on vegetation in the pre- and post-fire events over Iberian Peninsula

Gouveia¹,

Bastos²,

Trigo³

et al. 2012

Nat. Hazards Earth Syst. Sci.

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Abstract. The present work aims to study the combined effect of drought and large wildfires in the Iberian Peninsula relying on remotely sensed data of vegetation dynamics and leaf moisture content, in particular monthly NDVI, NDWI and NDDI time series from 1999-2009, derived from VEG-ETATION dataset. The impact of the exceptional 2004/2005 drought on vegetation was assessed for vegetation recovering from the extraordinary fire season of 2003 and on the conditions that contributed to the onsetting of the fire season of 2005. Drought severity was estimated by the cumulative negative effect on photosynthetic activity (NDVI) and vegetation dryness (NDDI), with about 2/3 of Iberian Peninsula presenting vegetative stress and low water availability conditions, in spring and early summer of 2005. Furthermore, NDDI has shown to be very useful to assess drought, since it combines information on vegetation and water conditions. Moreover, we show that besides looking at the inter-annual variability of NDVI and NDDI, it is useful to evaluate intraannual changes (δNDVI and δNDDI), as indicators of change in vegetation greenness, allowing a detailed picture of the ability of the different land-cover types to resist to short-term dry conditions. In order to assess drought impact on post-fire regeneration, recovery times were evaluated by a mono-parametric model based on NDVI data and values corresponding to drought months were set to no value. Drought has shown to delay recovery times for several months in all the selected scars from 2003.The analysis of vegetation dynamics and fire selectivity in 2005 suggests that fires tended to occur in pixels presenting lower vegetative and water stress conditions during spring and early summer months. Additionally, pre-fire vegetation dynamics, in particular vegetation density and water availability during spring and early summer, has shown to influence significantly the levels of fire damage. These results stress the role of fuel availability in fire occurrence and impact on the Iberian Peninsula.

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Section: Introductionmentioning

confidence: 99%

Drought impacts on vegetation in the pre- and post-fire events over Iberian Peninsula

Gouveia¹,

Bastos²,

Trigo³

et al. 2012

Nat. Hazards Earth Syst. Sci.

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“…RS has the potential to monitor and detect land cover change at a variety of spatial and temporal scales, especially with high temporal resolution satellite data [3,32]. NDVI has been widely used in biophysical remote sensing studies.…”

Section: Introductionmentioning

confidence: 99%

Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

Hao

Zhang

Ouyang

et al. 2011

Environ Model Assess

102

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Vegetation in the upper catchment of Yellow River is critical for the ecological stability of the whole watershed. The dominant vegetation cover types in this region are grassland and forest, which can strongly influence the eco-environmental status of the whole watershed. The normalized difference vegetation index (NDVI) for grassland and forest has been calculated and its daily correlation models were deduced by Moderate Resolution Imaging Spectroradiometer products on 12 dates in 2000, 2003, and 2006. The responses of the NDVI values with the inter-annual grassland and forest to three climatic indices (i.e., yearly precipitation and highest and lowest temperature) were analyzed showing that, except for the lowest temperature, the yearly precipitation and highest temperature had close correlations with the NDVI values of the two vegetation communities. The value of correlation coefficients ranged from 0.815 to 0.951 (p<0.01). Furthermore, the interactions of NDVI values of vegetation with the climatic indicators at monthly interval were analyzed. The NDVI of vegetation and three climatic indices had strong positive correlations (larger than 0.733, p<0.01). The monthly correlations also provided the threshold values for the three climatic indictors, to be used for simulating vegetation growth grassland under different climate features, which is essential for the assessment of the vegetation growth and for regional environmental management.

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“…Studies performed at various spatial scales and under different ecological conditions indicate that the majority of loss of sediments occur during the first year after fire occurrence (DeBano et al, 1998;Inbar et al, 1998;Cerdà and Doerr, 2005) and that the risk of post-fire soil erosion increases with the time required for vegetation to reach the minimal threshold cover (Shakesby et al, 1993;Inbar et al, 1998). Therefore, a thorough evaluation of vegetation recovery after fire events becomes crucial in land management (Wittenberg et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Post-fire vegetation recovery in Portugal based on spot/vegetation data

Gouveia

DaCamara

Trigo

2010

Nat. Hazards Earth Syst. Sci.

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Abstract.A procedure is presented that allows identifying large burned scars and the monitoring of vegetation recovery in the years following major fire episodes. The procedure relies on 10-day fields of Maximum Value Composites of Normalized Difference Vegetation Index (MVC-NDVI), with a 1 km×1 km spatial resolution obtained from the VEG-ETATION instrument. The identification of fire scars during the extremely severe 2003 fire season is performed based on cluster analysis of NDVI anomalies that persist during the vegetative cycle of the year following the fire event. Two regions containing very large burned scars were selected, located in Central and Southwestern Portugal, respectively, and time series of MVC-NDVI analysed before the fire events took place and throughout the post-fire period. It is shown that post-fire vegetation dynamics in the two selected regions may be characterised based on maps of recovery rates as estimated by fitting a monoparametric model of vegetation recovery to MVC-NDVI data over each burned scar. Results indicated that the recovery process in the region located in Central Portugal is mostly related to fire damage rather than to vegetation density before 2003, whereas the latter seems to have a more prominent role than vegetation conditions after the fire episode, e.g. in the case of the region in Southwestern Portugal. These differences are consistent with the respective predominant types of vegetation. The burned area located in Central Portugal is dominated by Pinus Pinaster whose natural regeneration crucially depends on the destruction of seeds present on the soil surface during the fire, whereas the burned scar in Southwestern Portugal was populated by Eucalyptus that may quickly re-sprout from buds after fire. Besides its simplicity, the monoparametric model of vegeta-

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Spatial and temporal patterns of vegetation recovery following sequences of forest fires in a Mediterranean landscape, Mt. Carmel Israel

Cited by 116 publications

References 28 publications

Drought impacts on vegetation in the pre- and post-fire events over Iberian Peninsula

Drought impacts on vegetation in the pre- and post-fire events over Iberian Peninsula

Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

Post-fire vegetation recovery in Portugal based on spot/vegetation data

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