scholarly journals Socioeconomic Impacts of Forest Fires upon Portugal: An Analysis for the Agricultural and Forestry Sectors

2019 ◽  
Vol 11 (2) ◽  
pp. 374 ◽  
Author(s):  
Vítor Martinho

Recent forest fire activity has resulted in several consequences across different geographic locations where both natural and socioeconomic conditions have promoted a favorable context for what has happened in recent years in a number of countries, including Portugal. As a result, it would be interesting to examine the implications of forest fire activity in terms of the socioeconomic dynamics and performance of the agroforestry sectors in the context of those verified in the Portuguese municipalities. For this purpose, data from Statistics on Portugal was considered for output and employment from the business sector related to agricultural and forestry activities, which were disaggregated at the municipality level, for the period 2008–2015. Data for the burnt area was also considered in order to assess the impact of forest fires. The data was analyzed using econometric models in panel data based on the Keynesian (Kaldor laws) and convergence (conditional approaches) theories. The results from the Keynesian approaches show that there are signs of increasing returns to scale in the Portuguese agroforestry sectors, where the burnt area increased employment growth in agricultural activities and decreased employment in the forestry sector. Forest fires seem to create favorable conditions for agricultural employment in Portuguese municipalities and the inverse occurs for forestry employment. Additionally, some signs of convergence were identified between Portuguese municipalities for agroforestry output and employment, as well for the burnt areas. However, signs of divergence (increasing returns to scale) from the Keynesian models seem to be stronger. On the other hand, the evidence of beta convergence for the burnt areas are stronger than those verified for other variables, showing that the impacts from forest fires are more transversal across the whole country (however not enough to have sigma convergence).

2016 ◽  
Vol 16 (1) ◽  
pp. 239-253 ◽  
Author(s):  
I. Lehtonen ◽  
A. Venäläinen ◽  
M. Kämäräinen ◽  
H. Peltola ◽  
H. Gregow

Abstract. The target of this work was to assess the impact of projected climate change on forest-fire activity in Finland with special emphasis on large-scale fires. In addition, we were particularly interested to examine the inter-model variability of the projected change of fire danger. For this purpose, we utilized fire statistics covering the period 1996–2014 and consisting of almost 20 000 forest fires, as well as daily meteorological data from five global climate models under representative concentration pathway RCP4.5 and RCP8.5 scenarios. The model data were statistically downscaled onto a high-resolution grid using the quantile-mapping method before performing the analysis. In examining the relationship between weather and fire danger, we applied the Canadian fire weather index (FWI) system. Our results suggest that the number of large forest fires may double or even triple during the present century. This would increase the risk that some of the fires could develop into real conflagrations which have become almost extinct in Finland due to active and efficient fire suppression. However, the results reveal substantial inter-model variability in the rate of the projected increase of forest-fire danger, emphasizing the large uncertainty related to the climate change signal in fire activity. We moreover showed that the majority of large fires in Finland occur within a relatively short period in May and June due to human activities and that FWI correlates poorer with the fire activity during this time of year than later in summer when lightning is a more important cause of fires.


Author(s):  
N.-E. Geserbaatar ◽  
E. Nasanbat ◽  
O. Lkhamjav

Abstract. The objective of this study was the impact of forest fire on forest cover types. This study has identified non-forest and forest area that has seven forest class are included with cedar, pine, larch, birch, birch-pine mixed, birch-larch mixed and cedar-larch mixed, additionally, remote sensing imagery is applied. In contrast, Landsat imagery has been used several classification approaches. Moreover, the current classification has developments in segmentation and object-oriented techniques offer the suitable analysis to classify satellite data. In the object-oriented classification approach, images cluster to homogenous area as forest types by suitable parameters in some level. The accuracy analysis revealed that overall accuracy showed a good accuracy of determination (86.33 percent in 2000 and 93.75 percent in 2011) with regard to identify of the forest cover and type. Furthermore, these results suggest that the Landsat TM and ETM+ data can reliable detect the forest type based upon the segmentation and object-oriented techniques. In generally, our study area is high-risky region to forest fires. It is higher influence to forest cover and tree species and other ecosystems. Overall, wildfire of impact results showed that 25239 ha of forests were changed to burnt area and 52603 ha forests were changed to grassland.


2020 ◽  
Vol 12 (24) ◽  
pp. 4169
Author(s):  
Dai Quoc Tran ◽  
Minsoo Park ◽  
Daekyo Jung ◽  
Seunghee Park

Estimating the damaged area after a forest fire is important for responding to this natural catastrophe. With the support of aerial remote sensing, typically with unmanned aerial vehicles (UAVs), the aerial imagery of forest-fire areas can be easily obtained; however, retrieving the burnt area from the image is still a challenge. We implemented a new approach for segmenting burnt areas from UAV images using deep learning algorithms. First, the data were collected from a forest fire in Andong, the Republic of Korea, in April 2020. Then, the proposed two-patch-level deep-learning models were implemented. A patch-level 1 network was trained using the UNet++ architecture. The output prediction of this network was used as a position input for the second network, which used UNet. It took the reference position from the first network as its input and refined the results. Finally, the final performance of our proposed method was compared with a state-of-the-art image-segmentation algorithm to prove its robustness. Comparative research on the loss functions was also performed. Our proposed approach demonstrated its effectiveness in extracting burnt areas from UAV images and can contribute to estimating maps showing the areas damaged by forest fires.


1993 ◽  
Vol 69 (3) ◽  
pp. 290-293 ◽  
Author(s):  
Brian J. Stocks

The looming possibility of global warming raises legitimate concerns for the future of the forest resource in Canada. While evidence of a global warming trend is not conclusive at this time, governments would be wise to anticipate, and begin planning for, such an eventuality. The forest fire business is likely to be affected both early and dramatically by any trend toward warmer and drier conditions in Canada, and fire managers should be aware that the future will likely require new and innovative thinking in forest fire management. This paper summarizes research activities currently underway to assess the impact of global warming on forest fires, and speculates on future fire management problems and strategies.


2017 ◽  
Vol 3 (329) ◽  
Author(s):  
Alicja Anna Olejnik

Recent findings emphasise the importance of localised returns to scale for the regional growth as well as for the agglomeration processes. However, it is still not well established whether returns to scale are constant or increasing, and to what extent. Therefore, in this study we apply specification which describes the productivity growth with the growth of output through the Verdoorn’s law. This study aims to provide some new estimates of the degree of returns to scale for EU regions. Our findings show that the hypothesis of increasing returns to scale is still valid in today’s EU economy. To test the hypothesis, we have employed the Multidimensional Spatial Panel Durbin Model with Spatial Fixed Effects. The research is conducted for 261 regions of the EU 28. The paper concludes that increasing returns to scale in EU regions are substantial.


2004 ◽  
Vol 155 (7) ◽  
pp. 263-277 ◽  
Author(s):  
Marco Conedera ◽  
Gabriele Corti ◽  
Paolo Piccini ◽  
Daniele Ryser ◽  
Francesco Guerini ◽  
...  

The Southern Alps, in particular the Canton Ticino, is the region of Switzerland that is most affected by the phenomenon of forest fires. Therefore, the cantonal authorities are continually confronted with problems of prevention, fire fighting and mitigation of the effects of forest fires. In this article forest fire management in Canton Ticino is analyzed in historical terms, verifying in particular the impact of the methods used and the improvement of technology addressing the frequency of events and the extent of burned surfaces. In this way it has been possible to show how a few structural measures (better organization of fire fighting crews and equipment, introduction of aerial fire fighting techniques, electrification followed by construction of shelters along railway lines, etc.) have rather reduced the extent of burned surfaces, while legislative measures such as restrictions of open fires help to reduce the number of forest fires.


Sign in / Sign up

Export Citation Format

Share Document