Fire Recurrence and the Dynamics of the Enhanced Vegetation Index in a Mediterranean Ecosystem

2019 ◽  
pp. 1690-1708
Author(s):  
Dania Abdul Malak ◽  
Juli G. Pausas ◽  
Josep E. Pardo-Pascual ◽  
Luis A. Ruiz
Keyword(s):  
Forest Fires ◽  
Vegetation Index ◽  
Mediterranean Ecosystem ◽  
Climatic Effects ◽  
Vegetation Growth ◽  
Enhanced Vegetation Index ◽  
Spatio Temporal ◽  
Major Factors ◽  
Ecosystem Complex ◽  
Vegetation Regeneration

This study area is located in the eastern littoral of the Iberian Peninsula; its importance resides in its Mediterranean ecosystem, complex topography, extensive land use changes, and intensive forest fires history. The study is done at the landscape level, covering a wide area for an extended period of time. This work uses Geographic Information Systems (GIS) and Satellite Remote Sensing (SRS) techniques to evaluate the impact of spatio-temporal parameters on shaping Mediterranean landscapes. Interacting ecological parameters are analysed and correlated to post-fire vegetation regeneration in an attempt to understand its dynamics. The results provide evidence that the number of fires separated by short time intervals influence vegetation growth negatively measured as Enhanced Vegetation Index (EVI). During this period, micro-climatic effects (soil and environmental humidity) are major factors influencing EVI-measured vegetation regeneration. The conclusions expect shifts in Mediterranean plant communities in heavily burned ecosystems stressing the importance of their correct short and long term post-fire management.

Fire Recurrence and the Dynamics of the Enhanced Vegetation Index in a Mediterranean Ecosystem

2015 ◽  
Vol 6 (2) ◽  
pp. 18-35 ◽  
Author(s):  
Dania Abdul Malak ◽  
Juli G. Pausas ◽  
Josep E. Pardo-Pascual ◽  
Luis A. Ruiz
Keyword(s):  
Forest Fires ◽  
Vegetation Index ◽  
Land Use Changes ◽  
Extended Period ◽  
Mediterranean Ecosystem ◽  
Climatic Effects ◽  
Enhanced Vegetation Index ◽  
Mediterranean Landscapes ◽  
The Impact ◽  
Vegetation Regeneration

This study area is located in the eastern littoral of the Iberian Peninsula; its importance resides in its Mediterranean ecosystem, complex topography, extensive land use changes, and intensive forest fires history. The study is done at the landscape level, covering a wide area for an extended period of time. This work uses Geographic Information Systems (GIS) and Satellite Remote Sensing (SRS) techniques to evaluate the impact of spatio-temporal parameters on shaping Mediterranean landscapes. Interacting ecological parameters are analysed and correlated to post-fire vegetation regeneration in an attempt to understand its dynamics. The results provide evidence that the number of fires separated by short time intervals influence vegetation growth negatively measured as Enhanced Vegetation Index (EVI). During this period, micro-climatic effects (soil and environmental humidity) are major factors influencing EVI-measured vegetation regeneration. The conclusions expect shifts in Mediterranean plant communities in heavily burned ecosystems stressing the importance of their correct short and long term post-fire management.

Fire danger estimation from MODIS Enhanced Vegetation Index data: application to Galicia region (north-west Spain)

2011 ◽  
Vol 20 (3) ◽  
pp. 465 ◽  
Author(s):  
M. M. Bisquert ◽  
J. M. Sánchez ◽  
V. Caselles
Keyword(s):  
Forest Fires ◽  
Vegetation Index ◽  
Estimation Error ◽  
Fire Danger ◽  
Enhanced Vegetation Index ◽  
North West ◽  
Remote Sensing Technique ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Satellite

Galicia, in north-west Spain, is a region especially affected by devastating forest fires. The development of a fire danger prediction model adapted to this particular region is required. In this paper, we focus on changes in the condition of vegetation as an indicator of fire danger. The potential of the Enhanced Vegetation Index (EVI) together with period-of-year to monitor vegetation changes in Galicia is shown. The Moderate Resolution Imaging Spectroradiometer (MODIS), onboard the Terra satellite, was chosen for this study. A 6-year dataset of EVI images, from the product MOD13Q1 (16-day composites), together with fire data in a 10 × 10-km grid basis, were used. Logistic regression was used to assess the relationship between the percentage of fire activity and EVI variations together with period-of-year. The results show the ability of the model obtained to discriminate different levels of fire occurrence danger, with an estimation error of ~5%. This remote sensing technique may contribute to improving the efficiency of the currently used fire prevention systems.

Spatio-temporal mangrove canopy variation (2001–2016) assessed using the MODIS enhanced vegetation index (EVI)

2019 ◽  
Vol 23 (3) ◽  
pp. 589-597 ◽  
Author(s):  
Marta Rocío Nepita-Villanueva ◽  
César Alejandro Berlanga-Robles ◽  
Arturo Ruiz-Luna ◽  
J. Héctor Morales Barcenas
Keyword(s):  
Vegetation Index ◽  
Enhanced Vegetation Index ◽  
Spatio Temporal

Climate-forced changes of bio-productivity of Belorussian terrestrial ecosystems

2019 ◽  
pp. 77-88
Author(s):  
S. A. Lysenko
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Vegetation Index ◽  
Precipitation Amount ◽  
Terrestrial Ecosystems ◽  
Vegetation Period ◽  
Climatic Trend ◽  
Vegetation Growth ◽  
Current Century ◽  
The Impact

The spatial and temporal particularities of Normalized Differential Vegetation Index (NDVI) changes over territory of Belarus in the current century and their relationship with climate change were investigated. The rise of NDVI is observed at approximately 84% of the Belarus area. The statistically significant growth of NDVI has exhibited at nearly 35% of the studied area (t-test at 95% confidence interval), which are mainly forests and undeveloped areas. Croplands vegetation index is largely descending. The main factor of croplands bio-productivity interannual variability is precipitation amount in vegetation period. This factor determines more than 60% of the croplands NDVI dispersion. The long-term changes of NDVI could be explained by combination of two factors: photosynthesis intensifying action of carbon dioxide and vegetation growth suppressing action of air warming with almost unchanged precipitation amount. If the observed climatic trend continues the croplands bio-productivity in many Belarus regions could be decreased at more than 20% in comparison with 2000 year. The impact of climate change on the bio-productivity of undeveloped lands is only slightly noticed on the background of its growth in conditions of rising level of carbon dioxide in the atmosphere.

scholarly journals Comparison of Satellite and Drone-Based Images at Two Spatial Scales to Evaluate Vegetation Regeneration after Post-Fire Treatments in a Mediterranean Forest

2021 ◽  
Vol 11 (12) ◽  
pp. 5423
Author(s):  
Jose Luis Martinez ◽  
Manuel Esteban Lucas-Borja ◽  
Pedro Antonio Plaza-Alvarez ◽  
Pietro Denisi ◽  
Miguel Angel Moreno ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Spatial Scales ◽  
Soil Surface ◽  
Plant Biodiversity ◽  
Mediterranean Forests ◽  
Experimental Conditions ◽  
Vegetation Growth ◽  
Surface Conditions ◽  
Vegetation Regeneration ◽  
Forest Managers

The evaluation of vegetation cover after post-fire treatments of burned lands is important for forest managers to restore soil quality and plant biodiversity in burned ecosystems. Unfortunately, this evaluation may be time consuming and expensive, requiring much fieldwork for surveys. The use of remote sensing, which makes these evaluation activities quicker and easier, have rarely been carried out in the Mediterranean forests, subjected to wildfire and post-fire stabilization techniques. To fill this gap, this study evaluates the feasibility of satellite (using LANDSAT8 images) and drone surveys to evaluate changes in vegetation cover and composition after wildfire and two hillslope stabilization treatments (log erosion barriers, LEBs, and contour-felled log debris, CFDs) in a forest of Central Eastern Spain. Surveys by drone were able to detect the variability of vegetation cover among burned and unburned areas through the Visible Atmospherically Resistant Index (VARI), but gave unrealistic results when the effectiveness of a post-fire treatment must be evaluated. LANDSAT8 images may be instead misleading to evaluate the changes in land cover after wildfire and post-fire treatments, due to the lack of correlation between VARI and vegetation cover. The spatial analysis has shown that: (i) the post-fire restoration strategy of landscape managers that have prioritized steeper slopes for treatments was successful; (ii) vegetation growth, at least in the experimental conditions, played a limited influence on soil surface conditions, since no significant increases in terrain roughness were detected in treated areas.

scholarly journals Coastal Mangrove Response to Marine Erosion: Evaluating the Impacts of Spatial Distribution and Vegetation Growth in Bangkok Bay from 1987 to 2017

2020 ◽  
Vol 12 (2) ◽  
pp. 220 ◽  
Author(s):  
Han Xiao ◽  
Fenzhen Su ◽  
Dongjie Fu ◽  
Qi Wang ◽  
Chong Huang
Keyword(s):  
Spatial Distribution ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Mangrove Ecosystem ◽  
Early Growth ◽  
Growth Stages ◽  
Human Disturbances ◽  
Vegetation Growth ◽  
Two Parameters ◽  
The Impact

Long time-series monitoring of mangroves to marine erosion in the Bay of Bangkok, using Landsat data from 1987 to 2017, shows responses including landward retreat and seaward extension. Quantitative assessment of these responses with respect to spatial distribution and vegetation growth shows differing relationships depending on mangrove growth stage. Using transects perpendicular to the shoreline, we calculated the cross-shore mangrove extent (width) to represent spatial distribution, and the normalized difference vegetation index (NDVI) was used to represent vegetation growth. Correlations were then compared between mangrove seaside changes and the two parameters—mangrove width and NDVI—at yearly and 10-year scales. Both spatial distribution and vegetation growth display positive impacts on mangrove ecosystem stability: At early growth stages, mangrove stability is positively related to spatial distribution, whereas at mature growth the impact of vegetation growth is greater. Thus, we conclude that at early growth stages, planting width and area are more critical for stability, whereas for mature mangroves, management activities should focus on sustaining vegetation health and density. This study provides new rapid insights into monitoring and managing mangroves, based on analyses of parameters from historical satellite-derived information, which succinctly capture the net effect of complex environmental and human disturbances.

Soil water repellency persistence after recurrent forest fires on Mount Carmel, Israel

2013 ◽  
Vol 22 (4) ◽  
pp. 515 ◽  
Author(s):  
Naama Tessler ◽  
Lea Wittenberg ◽  
Noam Greenbaum
Keyword(s):  
Organic Matter ◽  
Soil Water ◽  
Forest Fires ◽  
Water Drop ◽  
Chemical Properties ◽  
Water Repellency ◽  
Mediterranean Ecosystem ◽  
Long Term Effects ◽  
Soil Water Repellency ◽  
Chemical Properties Of Soils

Variations in forest fires regime affect: (1) the natural patterns of community structure and vegetation; (2) the physico-chemical properties of soils and consequently (3) runoff, erosion and sediment yield. In recent decades the Mediterranean ecosystem of Mount Carmel, north-western Israel, is subjected to an increasing number of forest fires, thus, the objectives of the study were to evaluate the long-term effects of single and recurrent fires on soil water repellency (WR) and organic matter (OM) content. Water repellency was studied by applying water drop penetration time (WDPT) tests at sites burnt by single-fire, two fires, three fires and unburnt control sites. Water repellency in the burnt sites was significantly lower than in the unburnt control sites, and the soil maintained its wettability for more than 2 decades, whereas after recurrent fires, the rehabilitation was more complicated and protracted. The OM content was significantly lower after recurrent than after a single fire, causing a clear proportional decrease in WR. The rehabilitation of WR to natural values is highly dependent on restoration of organic matter and revegetation. Recurrent fires may cause a delay in recovery and reduced productivity of the soil for a long period.

scholarly journals Climate Dynamics of the Spatiotemporal Changes of Vegetation NDVI in Northern China from 1982 to 2015

2021 ◽  
Vol 13 (2) ◽  
pp. 187
Author(s):  
Rui Sun ◽  
Shaohui Chen ◽  
Hongbo Su
Keyword(s):  
Solar Radiation ◽  
Vegetation Index ◽  
Global Climate ◽  
Regional Scale ◽  
Northern China ◽  
Climate Dynamics ◽  
High Coverage ◽  
Vegetation Growth ◽  
Temperature And Precipitation ◽  
Precipitation And Temperature

As an important part of a terrestrial ecosystem, vegetation plays an important role in the global carbon-water cycle and energy flow. Based on the Global Inventory Monitoring and Modeling System (GIMMS) third generation of Normalized Difference Vegetation Index (NDVI3g), meteorological station data, climate reanalysis data, and land cover data, this study analyzed the climate dynamics of the spatiotemporal variations of vegetation NDVI in northern China from 1982 to 2015. The results showed that growth season NDVI (NDVIgs) increased significantly at 0.006/10a (p < 0.01) in 1982–2015 on the regional scale. The period from 1982 to 2015 was divided into three periods: the NDVIgs increased by 0.026/10a (p < 0.01) in 1982–1990, decreased by −0.002/10a (p > 0.1) in 1990–2006, and then increased by 0.021/10a (p < 0.01) during 2006–2015. On the pixel scale, the increases in NDVIgs during 1982–2015, 1982–1990, 1990–2006, and 2006–2015 accounted for 74.64%, 85.34%, 48.14%, and 68.78% of the total area, respectively. In general, the dominant climate drivers of vegetation growth had gradually switched from solar radiation, temperature, and precipitation (1982–1990) to precipitation and temperature (1990–2015). For woodland, high coverage grassland, medium coverage grassland, low coverage grassland, the dominant climate drivers had changed from temperature and solar radiation, solar radiation and precipitation, precipitation and solar radiation, solar radiation to precipitation and solar radiation, precipitation, precipitation and temperature, temperature and precipitation. The areas controlled by precipitation increased significantly, mainly distributed in arid, sub-arid, and sub-humid areas. The dominant climate drivers for vegetation growth in the plateau climate zone or high-altitude area changed from solar radiation to temperature and precipitation, and then to temperature, while in cold temperate zone, changed from temperature to solar radiation. These results are helpful to understand the climate dynamics of vegetation growth, and have important guiding significance for vegetation protection and restoration in the context of global climate change.

scholarly journals A comparison of satellite-based indices for hazard assessment of MSW open dumps using spatial analysis

2018 ◽  
Vol 37 (3) ◽  
pp. 219-236 ◽  
Author(s):  
Khalid Mahmood ◽  
Zia Ul-Haq ◽  
Fiza Faizi ◽  
Syeda A. Batol
Keyword(s):  
Hazard Assessment ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Moving Average ◽  
Vegetation Indices ◽  
Temporal Analysis ◽  
Zone Size ◽  
Vegetation Health ◽  
Spatio Temporal ◽  
Hazardous Zone

This study compares the suitability of different satellite-based vegetation indices (VIs) for environmental hazard assessment of municipal solid waste (MSW) open dumps. The compared VIs, as bio-indicators of vegetation health, are normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), and modified soil adjusted vegetation index (MSAVI) that have been subject to spatio-temporal analysis. The comparison has been made based on three criteria: one is the exponential moving average (EMA) bias, second is the ease in visually finding the distance of VI curve flattening, and third is the radius of biohazardous zone in relation to the waste heap dumped at them. NDVI has been found to work well when MSW dumps are surrounded by continuous and dense vegetation, otherwise, MSAVI is a better option due to its ability for adjusting soil signals. The hierarchy of the goodness for least EMA bias is MSAVI> SAVI> NDVI with average bias values of 101 m, 203 m, and 270 m, respectively. Estimations using NDVI have been found unable to satisfy the direct relationship between waste heap and hazardous zone size and have given a false exaggeration of 374 m for relatively smaller dump as compared to the bigger one. The same false exaggeration for SAVI and MSAVI is measured to be 86 m and -14 m, respectively. So MSAVI is the only VI that has shown the true relation of waste heap and hazardous zone size. The best visualization of distance-dependent vegetation health away from the dumps is also provided by MSAVI.

scholarly journals Enhanced Vegetation Index (EVI) na análise da dinâmica da vegetação da reserva biológica de Sooretama, ES

2008 ◽  
Vol 32 (6) ◽  
pp. 1099-1107 ◽  
Author(s):  
André Quintão de Almeida ◽  
Gilson Fernandes da Silva ◽  
José Eduardo Macedo Pezzopane ◽  
Carlos Alexandre Damasceno Ribeiro
Keyword(s):  
Vegetation Index ◽  
Enhanced Vegetation Index ◽  
Espírito Santo ◽  
Espirito Santo

Técnicas de análises de séries temporais são utilizadas para caracterizar o comportamento de fenômenos naturais no domínio do tempo. Neste artigo, segundo a metodologia proposta por Box et al. (1994), 125 observações do Enhanced Vegetation Index (EVI) foram analisadas. Os valores modelados correspondem às variações temporais ocorridas no dossel florestal da reserva biológica de Sooretama, localizada ao Norte do Estado do Espírito Santo, no Município de Linhares. Os resultados indicaram que a metodologia foi adequada. Os resíduos do modelo ajustado são não correlacionados com distribuição normal, média zero e variância s². Com o menor valor do Critério de Informação de Akaike (AIC) -570,51, o modelo ajustado foi o Sazonal Auto-Regressivo Integrado de Médias Móveis (1,0,1)(1,0,1)12.

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