scholarly journals Tree Cover Loss in the Mediterranean Region—An Increasingly Serious Environmental Issue

Forests ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1341
Author(s):  
Ana-Maria Ciobotaru ◽  
Nilanchal Patel ◽  
Radu-Daniel Pintilii
Keyword(s):  
Forest Fires ◽  
Mediterranean Region ◽  
Landsat Imagery ◽  
Tree Cover ◽  
Mediterranean Country ◽  
Forest Change ◽  
Livestock Farming ◽  
Normality Test ◽  
Distribution Mapping ◽  
The Mediterranean

The Mediterranean Region currently faces major environmental issues that require constant analysis and monitoring. This study presents a thorough approach based on the application of Landsat imagery from Global Forest Change during 2001–2019. Spatial distribution mapping was one of the objectives of the study. We approached the analysis of tree cover loss areas by analyzing the cumulative tree cover loss and Tree Cover Loss Rate. This indicator offers information about the trend of tree cover loss in each Mediterranean country. A total of 581 Mha of deforested area was mapped during the analyzed period. Analysis was further supplemented by some statistical operations (distributions shown via histograms, validation via Shapiro–Wilk normality test, and testing via one-sample t-test). Agricultural expansion, intense forest fires, illegal logging, overgrazing (especially in the northern part of Africa), and extensive livestock farming have influenced the Mediterranean forest ecosystem’s stability. The continuation of these activities could cause extreme climatic events, severe degradation, and desertification.

Modeling mercury emissions from forest fires in the Mediterranean region

2007 ◽  
Vol 8 (2) ◽  
pp. 129-145 ◽  
Author(s):  
Sergio Cinnirella ◽  
Nicola Pirrone ◽  
Alessia Allegrini ◽  
Daniela Guglietta
Keyword(s):  
Forest Fires ◽  
Mediterranean Region ◽  
Mercury Emissions ◽  
The Mediterranean

Performance Evaluation of Fire Risk Map from LSA-SAF over Mediterranean region in 2020

2021 ◽  
Author(s):  
Catarina Alonso ◽  
Célia Gouveia
Keyword(s):  
Forest Fires ◽  
Mediterranean Region ◽  
Prescribed Burning ◽  
Fire Risk ◽  
Radiative Energy ◽  
Fire Season ◽  
Risk Map ◽  
Fire Weather Index ◽  
The Mediterranean ◽  
Burnt Areas

<p>Forest fires have always been present in Mediterranean ecosystems; as such, they constitute a major ecological and socioeconomical issue. Despite being mostly of anthropogenic origin, the influence of the recent increase in temperature and evapotranspiration is associated with an increase in the frequency and severity of wildfires in the region. Large fires are promoted by the occurrence of high temperatures and episodes of drought that may lead to total burnt areas being several times larger than the average, such as the burnt areas in Portugal in 2003 and 2005, and Greece in 2007. The fire season of 2017 in Portugal has been catastrophic by most accounts. The authorities reported more than 100 human fatalities, with about 500.000ha of estimated burnt area, which corresponds to the maximum record since 1980. </p><p>The Land Surface Analysis Satellite Applications Facility (LSA SAF) from EUMETSAT operationally disseminates a set of fire related products for the Mediterranean region. The Fire Radiative Power product (FRP-PIXEL) is delivered in near real-time since 2004 with a 15-min temporal resolution. In this work, daily Fire Radiative Energy (FRE) is computed for the Mediterranean region. The Fire Risk Map (FRM) product combines information from the operational forecasts from ECMWF and vegetation state from SEVIRI to derive forecasts of the risk of fire for the Mediterranean region. The FRM algorithm computes the daily values of the set of components of the Canadian Forest Fire Weather Index System (CFFWIS) for Mediterranean Europe, together with levels of fire danger associated with probabilities of occurrence of fires exceeding specified magnitudes. The FRM can be an important tool to support the management of forest fires and the decision making of prescribed burning within the framework of agricultural and forest management practices.</p><p>This work aims to assess the performance of the FRM product during 2020 over the Mediterranean region using FRE estimates. In particular, we aim to evaluate if the more severe and intense fires occurred in areas of high fire risk and high probability of occurrence of extreme fires, as obtained using FRM products. This analysis is made for different countries in the Mediterranean Basin, namely Portugal, Spain, Italy, and Greece. Results reveal a good performance of FRM over the Mediterranean region during 2020; however, better results were observed for the fire season in the Iberian Peninsula than for Italy.</p><p><strong>Acknowledgements:</strong> This study was performed within the framework of the LSA-SAF, co-funded by EUMETSAT This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under projects FIRECAST (PCIF/GRF/0204/2017) and IMPECAF (PTDC/CTA-CLI/28902/2017).</p>

scholarly journals A comparison of mono-seasonal and multiseasonal Landsat images for vegetation cover classification in the Mediterranean region: a case study in Latakia, Syria

2021 ◽  
Vol 310 ◽  
pp. 05001
Author(s):  
Vasiliy Malinnikov ◽  
Assem Khatib
Keyword(s):  
Vegetation Cover ◽  
Mediterranean Region ◽  
Satellite Images ◽  
Landsat Imagery ◽  
Google Earth ◽  
Landsat Images ◽  
Significance Level ◽  
The Mediterranean ◽  
Spectral Channels

Providing constantly updated information on vegetation serves as a basis for studies of natural resources and ecological issues. This paper discusses the question related to an appropriate season(s) for classification vegetation cover in the Mediterranean region and detecting its changes using Landsat imagery. Autumn, spring, and multi-seasonal satellite images, captured in 2017, were used to classify vegetation cover in a part of the Lattakia province, Syria. The satellite images were classified using the random forest algorithm, and high spatial resolution satellite images Google Earth Pro were used as reference data. The results indicate better effectiveness of the autumn images over spring ones for vegetation cover classification with 73.6% and 62.4% overall accuracy, respectively. In addition, a comparison of autumn and multi-seasonal Landsat images indicates no significant statistical difference in the accuracy of vegetation cover classification at the significance level of 0.05, which illustrates the effectiveness of using autumn images to classify the vegetation cover of the Mediterranean region. Furthermore, the obtained results show the necessity of using additional features as the spectral channels may not be sufficient for mapping vegetation cover in the Mediterranean region with high accuracy.

Existing areas and past changes of wetland extent in the Mediterranean region: an overview

2012 ◽  
Vol 38 (2) ◽  
pp. 53-66 ◽  
Author(s):  
Christian Perennou ◽  
Coralie Beltrame ◽  
Anis Guelmami ◽  
Pere Tomàs Vives ◽  
Pierre Caessteker
Keyword(s):  
Mediterranean Region ◽  
Wetland Extent ◽  
The Mediterranean

scholarly journals Evaluating Forest Cover and Fragmentation in Costa Rica with a Corrected Global Tree Cover Map

2020 ◽  
Vol 12 (19) ◽  
pp. 3226
Author(s):  
Daniel Cunningham ◽  
Paul Cunningham ◽  
Matthew E. Fagan
Keyword(s):  
Costa Rica ◽  
Forest Cover ◽  
Agricultural Land ◽  
Forest Area ◽  
Tree Cover ◽  
Agricultural Crop ◽  
Forest Change ◽  
Alos Palsar ◽  
Tropical Regions ◽  
The Impact

Global tree cover products face challenges in accurately predicting tree cover across biophysical gradients, such as precipitation or agricultural cover. To generate a natural forest cover map for Costa Rica, biases in tree cover estimation in the most widely used tree cover product (the Global Forest Change product (GFC) were quantified and corrected, and the impact of map biases on estimates of forest cover and fragmentation was examined. First, a forest reference dataset was developed to examine how the difference between reference and GFC-predicted tree cover estimates varied along gradients of precipitation and elevation, and nonlinear statistical models were fit to predict the bias. Next, an agricultural land cover map was generated by classifying Landsat and ALOS PalSAR imagery (overall accuracy of 97%) to allow removing six common agricultural crops from estimates of tree cover. Finally, the GFC product was corrected through an integrated process using the nonlinear predictions of precipitation and elevation biases and the agricultural crop map as inputs. The accuracy of tree cover prediction increased by ≈29% over the original global forest change product (the R2 rose from 0.416 to 0.538). Using an optimized 89% tree cover threshold to create a forest/nonforest map, we found that fragmentation declined and core forest area and connectivity increased in the corrected forest cover map, especially in dry tropical forests, protected areas, and designated habitat corridors. By contrast, the core forest area decreased locally where agricultural fields were removed from estimates of natural tree cover. This research demonstrates a simple, transferable methodology to correct for observed biases in the Global Forest Change product. The use of uncorrected tree cover products may markedly over- or underestimate forest cover and fragmentation, especially in tropical regions with low precipitation, significant topography, and/or perennial agricultural production.

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