scholarly journals BEYOND INDONESIA FOREST WILDFIRES 2019

2019 ◽  
Vol 5 (3) ◽  
pp. 71-72
Author(s):  
Joko Gunawan
Keyword(s):  
Forest Wildfires

N/A

scholarly journals A Hybrid GIS and AHP Approach for Modelling Actual and Future Forest Fire Risk Under Climate Change Accounting Water Resources Attenuation Role

2019 ◽  
Vol 11 (24) ◽  
pp. 7166 ◽  
Author(s):  
Gianluigi Busico ◽  
Elisabetta Giuditta ◽  
Nerantzis Kazakis ◽  
Nicolò Colombani
Keyword(s):  
Forest Fire ◽  
Anthropogenic Activities ◽  
Fire Risk ◽  
Volcanic Eruptions ◽  
Evaluation Methodology ◽  
Climate Projections ◽  
Analytic Hierarchy ◽  
Campania Region ◽  
Forest Fire Risk ◽  
Forest Wildfires

Forest wildfires usually occur due to natural processes such as lightning and volcanic eruptions, but at the same time they are also an effect of uncontrolled and illegal anthropogenic activities. Different factors can influence forest wildfires, like the type of vegetation, morphology, climate, and proximity to human activities. A precise evaluation of forest fire issues and of the countermeasures needed to limit their impact could be satisfactory especially when forest fire risk (FFR) mapping is available. Here, we proposed an FFR evaluation methodology based on Geographic Information System (GIS) and the analytic hierarchy process (AHP). The study area is the Campania region (Southern Italy) that, for the last 30 years, has been affected by numerous wildfires. The proposed methodology analyzed 12 factors, and AHP was used for weight assignment, offering a new approach to some parameters. The method divided the study area into five risk classes, from very low to very high. Validation with fire alerts showed a good correlation between observed and predicted fires (0.79 R2). Analyzing the climate projections, a future FFR for 2040 was also assessed. The proposed methodology represents a reliable screening tool to identify areas under forest fire risk, and can help authorities to direct preventive actions.

scholarly journals Responses of leaf-litter ant communities to tropical forest wildfires vary with season

2012 ◽  
Vol 28 (5) ◽  
pp. 515-518 ◽  
Author(s):  
Juliana M. Silveira ◽  
Jos Barlow ◽  
Rafael B. Andrade ◽  
Luiz A. M. Mestre ◽  
Sébastien Lacau ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Leaf Litter ◽  
Land Management ◽  
Forest Fires ◽  
Selective Logging ◽  
Management Tool ◽  
Forest Biodiversity ◽  
Ant Communities ◽  
Agriculture Expansion ◽  
Forest Wildfires

Fire is an important land-management tool in tropical forest landscapes. However, these fires sometimes escape into surrounding forests (Uhl & Buschbacker 1985), and are one of the most severe disturbances threatening tropical forest biodiversity (Barlowet al2006). These forest fires have become more frequent over the last decades due to the combined effect of selective logging, fragmentation and abnormal droughts that increase the flammability of forests, and agriculture expansion that brings the ignition sources (Aragão & Shimabukuro 2010).

scholarly journals Visible and Thermal Image-Based Trunk Detection with Deep Learning for Forestry Mobile Robotics

2021 ◽  
Vol 7 (9) ◽  
pp. 176
Author(s):  
Daniel Queirós da Silva ◽  
Filipe Neves dos Santos ◽  
Armando Jorge Sousa ◽  
Vítor Filipe
Keyword(s):  
Deep Learning ◽  
Object Detection ◽  
Forest Inventory ◽  
Mobile Robotics ◽  
Ground Level ◽  
Forest Tree ◽  
Thermal Image ◽  
Detection Methods ◽  
Site Management ◽  
Forest Wildfires

Mobile robotics in forests is currently a hugely important topic due to the recurring appearance of forest wildfires. Thus, in-site management of forest inventory and biomass is required. To tackle this issue, this work presents a study on detection at the ground level of forest tree trunks in visible and thermal images using deep learning-based object detection methods. For this purpose, a forestry dataset composed of 2895 images was built and made publicly available. Using this dataset, five models were trained and benchmarked to detect the tree trunks. The selected models were SSD MobileNetV2, SSD Inception-v2, SSD ResNet50, SSDLite MobileDet and YOLOv4 Tiny. Promising results were obtained; for instance, YOLOv4 Tiny was the best model that achieved the highest AP (90%) and F1 score (89%). The inference time was also evaluated, for these models, on CPU and GPU. The results showed that YOLOv4 Tiny was the fastest detector running on GPU (8 ms). This work will enhance the development of vision perception systems for smarter forestry robots.

Inorganic and organic N pools in soils burned or heated: immediate alterations and evolution after forest wildfires

Geoderma ◽  
2004 ◽  
Vol 121 (3-4) ◽  
pp. 291-306 ◽  
Author(s):  
Ángeles Prieto-Fernández ◽  
Modesto Carballas ◽  
Tarsy Carballas
Keyword(s):  
Organic N ◽  
Forest Wildfires ◽  
Inorganic And Organic

Design of forest biomass energetic maps as a tool to fight forest wildfires

1999 ◽  
Vol 328 (1-2) ◽  
pp. 111-120 ◽  
Author(s):  
Lisardo Núñez-Regueira ◽  
J Rodrı́guez ◽  
J Proupı́n ◽  
B Mouriño
Keyword(s):  
Forest Biomass ◽  
Forest Wildfires

scholarly journals Assemblages of myxomycetes associated with three different substrates affected by forest wildfires

2021 ◽  
Vol 154 (1) ◽  
pp. 15-27
Author(s):  
Steven L. Stephenson ◽  
Nazrana Payal ◽  
Gurpreet Kaur ◽  
Carlos Rojas
Keyword(s):  
National Park ◽  
Culture Technique ◽  
Forest Recovery ◽  
Fire Intensity ◽  
Lower Intensity ◽  
Great Smoky Mountains ◽  
Smoky Mountains ◽  
Similarity Indices ◽  
The Impact ◽  
Forest Wildfires

Background and aims – In late November and early December of 2016, forest wildfires occurred over portions of the Great Smoky Mountains National Park (USA) and more than 4 000 ha were affected. Previous studies have shown that myxomycete assemblages can be greatly impacted as a result of this type of disturbance; after which, the recovery of the forest determines the availability of substrates for new colonisation. The objective of the project reported herein was to assess the impact of wildfires on the recovery of the assemblages of myxomycetes associated with three different substrates (forest floor leaf litter, the bark of living trees, and woody twigs) in two areas with different fire intensity.Material and methods – Two study areas subjected to different fire intensity were selected and sampled 30 months after the wildfires. Myxomycetes were studied using the moist chamber culture technique as it applies to these organisms. Satellite imagery was used to determine forest recovery and similarity indices were used to compare experimental myxomycete assemblages among study areas and substrates. Historical data were used as a reference to contextualise the results.Key results – A total of 38 species of myxomycetes representing 17 different genera were recorded from the two study areas. Samples from the lower intensity burn area yielded more myxomycetes than samples from the higher intensity burn area, with values of 84% and 59%, respectively. This same pattern was also observed for the number of recorded specimens (133 and 93, respectively). The comparison of experimental assemblages with previous data suggested that ground litter assemblages were still in early stages of recovery, whereas the assemblages associated with bark and twigs had recovered much faster.Conclusion – The relatively higher intensity fire had more of an effect on myxomycetes than the relatively lower intensity fire. Myxomycete assemblages are resilient to wildfires and they recover differentially depending on the substrate they grow on.

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