scholarly journals Wildfires: an Application of Remote Sensing and OBIA

2021 ◽  
Vol 17 ◽  
pp. 282-296
Author(s):  
Giuliana Bilotta ◽  
Salvatore Calcagno ◽  
Stefano Bonfa
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Information System ◽  
Forest Fires ◽  
Fire Risk ◽  
Soil Stability ◽  
Environmental Damage ◽  
Remotely Sensed Data ◽  
Burnt Areas ◽  
Processing Techniques

- To maintain soil stability and integrity, it is important to distinguish between soil covered by thick vegetation and that made arid and barren by fire, particularly when considering growing climate change. The safeguarding of these territories and the fight against its progressive environmental degradation requires great attention be paid to forest fires, particularly when considering the enormous environmental damage that fires have caused to important and widespread areas of the globe. The purpose of the contribution here is to compare processing techniques of high-resolution remotely sensed data from optical satellites to determine the best method of automatic discrimination of fire areas, thereby allowing the management of burnt areas in the context of subsequent fire risk. These integrated techniques were developed in a Geographic Information System (GIS) to get an accurate perimeter, and in general to analyze and manage data, geographic and otherwise, with spatial and geostatistical queries and analyzes. In a such a way that has an immediate reflection in the capability of immediately preparing acts, such as orders, decrees and other provisions, both for the protection of properties and territories and to lay a basis also for the prosecution and repression of crimes

scholarly journals INTEGRATED GIS SYSTEM FOR POST-FIRE HAZARD ASSESSMENTS WITH REMOTE SENSING

2020 ◽  
Vol XLIV-3/W1-2020 ◽  
pp. 13-20
Author(s):  
V. Barrile ◽  
G. Bilotta ◽  
A. Fotia ◽  
E. Bernardo
Keyword(s):  
Remote Sensing ◽  
Forest Fires ◽  
Fossil Fuels ◽  
Fire Hazard ◽  
Remote Sensing Data ◽  
Fire Risk ◽  
Software Tool ◽  
Environmental Damage ◽  
Burnt Areas ◽  
Climate Crisis

Abstract. Fires continue to devour hundreds of thousands of hectares of forest even in 2020, generating gigantic damage to the ecosystem, if we think that we are in the midst of a climate crisis caused precisely by CO2 emissions into the atmosphere by man, due to burning of fossil fuels. The action to safeguard the territory and the fight against its progressive environmental degradation focus a great attention towards forest fires, also considering the enormous environmental damage that these have caused to important and very large areas of the globe. The aim of the contribution that we here propose is the design and implementation of a software tool that performs predictive functions of triggering possible forest fires, thanks to the integration and manipulation of data from different sources and processed by predictive mathematical models, to support decisions; the comparison of techniques for the processing of high-resolution remote sensing data from optical satellites for the best automatic discrimination of the areas covered by fire plays a fundamental role in the analysis. This allows managing the burnt areas also considering subsequent fire risks, and the integration of the techniques developed in a GIS in order to obtain an accurate perimeter and a fire risk map prevision.

Remote sensing and GIS integration for land cover analysis, a case study: Bozcaada Island

2005 ◽  
Vol 51 (11) ◽  
pp. 239-244 ◽  
Author(s):  
F. Bektas ◽  
C. Goksel
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Land Cover ◽  
Land Cover Change ◽  
Geographic Information ◽  
Remotely Sensed Data ◽  
Change Analysis ◽  
Processing Techniques

In this study, remote sensing and geographic information system (GIS) techniques were used in order to accomplish land cover change of Bozcaada Island, Turkey, by using multitemporal Landsat Thematic Mapper data. Digital image processing techniques were conducted for the processes of image enhancement, manipulation, registration and classification for land cover change analysis. The land cover changes between two different dates were visualized and analyzed by using Geographic Information System techniques. The results showed that remotely sensed data and GIS are effective and powerful tools for carrying out changes on land cover of the island and monitoring of its impact on the environment.

scholarly journals ROLE OF REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEM TO ANALYZE THE IMPACT OF CLIMATE CHANGE ON FOREST ECOSYSTEMS

2015 ◽  
Vol 3 (8) ◽  
pp. 61-68
Author(s):  
Shahid Mohommad ◽  
Shambhu Prasad Joshi
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Forest Ecosystem ◽  
Forest Fires ◽  
Geographic Information ◽  
Substantial Impact ◽  
The Impact

Climate change is an inevitable process impacting the forest ecosystem. Various impacts like treeline shift, forest fires, and Species distribution are due to the effect of climate change. Green House Gases concentration in the atmosphere is increasing day by day due to anthropogenic activities. The pace of climate change is very alarming which will have the substantial impact on the forest ecosystem. Role of remote sensing and geographic information system in observing the forest ecosystem was reviewed. Spatio-temporal analysis of change in forest structure can be proficiently done with the help of remote sensing and geographic information system. Climate Change Mitigation programmes like Reducing Emissions from Deforestation and Forest Degradation (REDD-plus) can be implemented with the help of remote sensing and geographic information system. Baseline data generation using remote sensing and geographic information system can be useful in designing the policies for forest management and monitoring.

scholarly journals Climate change and forest management affect forest fire risk in Fennoscandia

2021 ◽  
Author(s):  
Keyword(s):  
Climate Change ◽  
Forest Management ◽  
Black Carbon ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Risk ◽  
The Arctic ◽  
Large Fires ◽  
Forest Fire Risk ◽  
Fire Ignition

Forest and wildland fires are a natural part of ecosystems worldwide, but large fires in particular can cause societal, economic and ecological disruption. Fires are an important source of greenhouse gases and black carbon that can further amplify and accelerate climate change. In recent years, large forest fires in Sweden demonstrate that the issue should also be considered in other parts of Fennoscandia. This final report of the project “Forest fires in Fennoscandia under changing climate and forest cover (IBA ForestFires)” funded by the Ministry for Foreign Affairs of Finland, synthesises current knowledge of the occurrence, monitoring, modelling and suppression of forest fires in Fennoscandia. The report also focuses on elaborating the role of forest fires as a source of black carbon (BC) emissions over the Arctic and discussing the importance of international collaboration in tackling forest fires. The report explains the factors regulating fire ignition, spread and intensity in Fennoscandian conditions. It highlights that the climate in Fennoscandia is characterised by large inter-annual variability, which is reflected in forest fire risk. Here, the majority of forest fires are caused by human activities such as careless handling of fire and ignitions related to forest harvesting. In addition to weather and climate, fuel characteristics in forests influence fire ignition, intensity and spread. In the report, long-term fire statistics are presented for Finland, Sweden and the Republic of Karelia. The statistics indicate that the amount of annually burnt forest has decreased in Fennoscandia. However, with the exception of recent large fires in Sweden, during the past 25 years the annually burnt area and number of fires have been fairly stable, which is mainly due to effective fire mitigation. Land surface models were used to investigate how climate change and forest management can influence forest fires in the future. The simulations were conducted using different regional climate models and greenhouse gas emission scenarios. Simulations, extending to 2100, indicate that forest fire risk is likely to increase over the coming decades. The report also highlights that globally, forest fires are a significant source of BC in the Arctic, having adverse health effects and further amplifying climate warming. However, simulations made using an atmospheric dispersion model indicate that the impact of forest fires in Fennoscandia on the environment and air quality is relatively minor and highly seasonal. Efficient forest fire mitigation requires the development of forest fire detection tools including satellites and drones, high spatial resolution modelling of fire risk and fire spreading that account for detailed terrain and weather information. Moreover, increasing the general preparedness and operational efficiency of firefighting is highly important. Forest fires are a large challenge requiring multidisciplinary research and close cooperation between the various administrative operators, e.g. rescue services, weather services, forest organisations and forest owners is required at both the national and international level.

scholarly journals USO DE GEOTECNOLOGIAS NA LOCAÇÃO ESPACIAL DE TORRES PARA DETECÇÃO DE INCÊNDIOS FLORESTAIS NO SEMIÁRIDO NORDESTINO

FLORESTA ◽  
2014 ◽  
Vol 44 (1) ◽  
pp. 133 ◽  
Author(s):  
Fellipe Ragner Vicente de Assis ◽  
Izaque Francisco Candeia de Mendonça ◽  
José Evanaldo Rangel da Silva ◽  
Joedla Rodrigues de Lima
Keyword(s):  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Environmental Analysis ◽  
Large Volume ◽  
Potential Risk ◽  
Forest Fires ◽  
Fire Risk ◽  
Test Efficiency ◽  
Extreme Risk

A possibilidade de manipular um grande volume de informações faz do SIG uma ótima ferramenta para análises ambientais. O objetivo do estudo foi identificar locais ideais para implantação de torres de vigilância de incêndios florestais, avaliar a potencialidade do SIG utilizado e testar a eficiência da metodologia proposta em áreas de caatinga. O estudo foi realizado na microbacia do rio do Saco, Santa Luzia, PB, Brasil. Foram gerados mapas de declividade, uso da terra, orientação das encostas, altimetria, temperatura, precipitação e risco potencial de incêndios, sendo correlacionados com as cotas de maior altitude e a proximidade de estradas para alocação das torres. Os resultados mostraram que5863,1 ha(61,6%) da área possuem elevado risco de incêndio. A torre 1 (T1) proporcionou a maior visualização (41,2%) das áreas de alto a extremo risco. Já a combinação de T1 + T5 proporcionou a maior visualização da área (74,9%). Para o uso de uma torre, foi indicada a instalação de T1; para combinação entre torres, a melhor associação foi T1 + T5. A metodologia se mostrou aplicável em outras áreas com características fisiográficas semelhantes. As rotinas do Sistema de Informações Geográficas Idrisi (SIG Idrisi) foram capazes de atender satisfatoriamente aos procedimentos metodológicos utilizados.Palavras-chave: Bacia hidrográfica; geoprocessamento; risco de incêndio. AbstractUse of geotechnology for towers placement in order to detect forest fires in northeastern Semiarid. The ability to handle a large volume of information makes GIS a great tool for environmental analysis. This research aims to identify ideal sites for installation of watchtowers forest fires, in order to evaluate the potential of SIG as well as to test efficiency of the proposed methodology in areas of Caatinga. The study was conducted in the watershed of the Saco River, Santa Luzia - PB, Brazil. We generated maps of slope, land use, orientation of slopes, altitude, temperature, precipitation and potential risk of fire, correlated with the dimensions of higher altitude and proximity of roads to towers installation. The results revealed that 5863.1 ha (61.6%) of  the area is at high fire risk. Tower 1 (T1) presented the better visualization (41.2%) of areas of high to extreme risk. The combination of T1 + T5 had as result better visualization of the area (74.9%). For the use of one only tower, it was indicated T1, in relation to combination the best one was the association of T1 + T5. The methodology proved its applicability in other areas with similar physiographic characteristics. Geographic Information System Idrisi (SIG Idrisi) routines were able to meet satisfactorily the methodological procedures.Keywords: Watershed; geoprocessing; risk of fire.

Potential changes in monthly fire risk in the eastern Canadian boreal forest under future climate change

2009 ◽  
Vol 39 (12) ◽  
pp. 2369-2380 ◽  
Author(s):  
Héloïse Le Goff ◽  
Mike D. Flannigan ◽  
Yves Bergeron
Keyword(s):  
Climate Change ◽  
Forest Fires ◽  
Fire Risk ◽  
Weather Conditions ◽  
Future Climate ◽  
Fire Season ◽  
Future Climate Change ◽  
Change Scenario ◽  
Fire Weather Index ◽  
Fire Activity

The main objective of this paper is to evaluate whether future climate change would trigger an increase in the fire activity of the Waswanipi area, central Quebec. First, we used regression analyses to model the historical (1973–2002) link between weather conditions and fire activity. Then, we calculated Fire Weather Index system components using 1961–2100 daily weather variables from the Canadian Regional Climate Model for the A2 climate change scenario. We tested linear trends in 1961–2100 fire activity and calculated rates of change in fire activity between 1975–2005, 2030–2060, and 2070–2100. Our results suggest that the August fire risk would double (+110%) for 2100, while the May fire risk would slightly decrease (–20%), moving the fire season peak later in the season. Future climate change would trigger weather conditions more favourable to forest fires and a slight increase in regional fire activity (+7%). While considering this long-term increase, interannual variations of fire activity remain a major challenge for the development of sustainable forest management.

scholarly journals Fires Monitoring by Means of Spectral Indices from Sentinel-2 Data: the Case Study of the Vesuvius and Lattari Mountains, Campania (Italy)

2020 ◽  
Author(s):  
Domenico Antonio Giuseppe Dell'Aglio ◽  
Carmine Gambardella ◽  
Massimiliano Gargiulo ◽  
Antonio Iodice ◽  
Rosaria Parente ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Forest Fires ◽  
European Space Agency ◽  
Fire Risk ◽  
Fire Detection ◽  
Spectral Indices ◽  
Active Fire ◽  
Space Agency ◽  
Repeat Time ◽  
Sentinel 2

Forest fires are part of a set of natural disasters that have always affected regions of the world typically characterized by a tropical climate with long periods of drought. However, due to climate change in recent years, other regions of our planet have also been affected by this phenomenon, never seen before. One of them is certainly the Italian peninsula, and especially the regions of southern Italy. For this reason, the scientific community, as well as remote sensing one, is highly concerned in developing reliable techniques to provide useful support to the competent authorities. In particular, three specific tasks have been carried out in this work: (i) fire risk prevention, (ii) active fire detection, and (iii) post-fire area assessment. To accomplish these analyses, the capability of a set of spectral indices, derived from spaceborne remote sensing (RS) data, is assessed to monitor the forest fires. The spectral indices are obtained from Sentinel-2 multispectral images of the European Space Agency (ESA), which are free of charge and openly accessible. Moreover, the twin Sentinel-2 sensors allow to overcome some restrictions on time delivery and observation repeat time. The performance of the proposed analyses were assessed experimentally to monitor the forest fires occurred in two specific study areas during the summer of 2017: the volcano Vesuvius, near Naples, and the Lattari mountains, near Sorrento (both in Campania, Italy).

scholarly journals Evaluating Models and Effective Factors Obtained from Remote Sensing (RS) and Geographic Information System (GIS) in the Prediction of Forest Fire Risk, Structured Review

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Akram Karimi ◽  
Sara Abdollahi ◽  
Kaveh Ostad-Ali-Askari ◽  
Vijay P. Singh ◽  
Saeid Eslamian ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Risk Prediction ◽  
Stress Measurement ◽  
Fire Risk ◽  
Moisture Stress ◽  
Geographic Information ◽  
Risk Modeling ◽  
Over Time

Fire is a phenomenon occurs in most parts of the world and causes severe financial losses and sometimes, irreparable damages. Many parameters are involved in the occurrence of a fire; some of which are constant over time (at least in a fire cycle), but the others are dynamic and vary over time. Unlike the earthquake, the disturbance of fire depends on a set of physical, chemical, and biological relations. Monitoring the changes to predict the occurrence of fire is efficient in forest management.Method: In this research, the Persian and English databases were structurally searched using the keywords of fire risk modeling, fire risk, fire risk prediction, and remote sensing and the reviewed papers that reviewed predicted the fire risk in the field of Remote Sensing and Geographic Information System were retrieved. Then, the modeling and zoning data of fire risk prediction were extracted and analyzed in a descriptive manner. Accordingly, the study was conducted in 1995-2017. Findings: Fuzzy Analytic Hierarchy Process(AHP) zoning method was more practical among the applied methods and the plant moisture stress measurement was the most efficient among the remote sensing indices.Discussion and Conclusion: The findings of the study indicate that RS and GIS are an effective tool in the study of fire risk prediction. 

scholarly journals Remote Sensing Mapping of Peat-Fire-Burnt Areas: Identification among Other Wildfires

2022 ◽  
Vol 14 (1) ◽  
pp. 194
Author(s):  
Andrey Sirin ◽  
Maria Medvedeva
Keyword(s):  
Remote Sensing ◽  
Forest Fires ◽  
Radiation Power ◽  
Fire Detection ◽  
Moisture Index ◽  
Peat Fire ◽  
Landsat 5 Tm ◽  
Burnt Areas ◽  
Peat Fires ◽  
Carbon Losses

Peat fires differ from other wildfires in their duration, carbon losses, emissions of greenhouse gases and highly hazardous products of combustion and other environmental impacts. Moreover, it is difficult to identify peat fires using ground-based methods and to distinguish peat fires from forest fires and other wildfires by remote sensing. Using the example of catastrophic fires in July–August 2010 in the Moscow region (the center of European Russia), in the present study, we consider the results of peat-fire detection using Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) hotspots, peat maps, and analysis of land cover pre- and post-fire according to Landsat-5 TM data. A comparison of specific (for detecting fires) and non-specific vegetation indices showed the difference index ΔNDMI (pre- and post-fire normalized difference moisture Index) to be the most effective for detecting burns in peatlands according to Landsat-5 TM data. In combination with classification (both unsupervised and supervised), this index offered 95% accuracy (by ground verification) in identifying burnt areas in peatlands. At the same time, most peatland fires were not detected by Terra/Aqua MODIS data. A comparison of peatland and other wildfires showed the clearest differences between them in terms of duration and the maximum value of the fire radiation power index. The present results may help in identifying peat (underground) fires and their burnt areas, as well as accounting for carbon losses and greenhouse gas emissions.

scholarly journals GISCIENCE FOR FOREST FIRE MODELING: NEW ADVANCES IN WILDLAND FIRES WITH MANAGEMENT

2021 ◽  
Vol 21 (no 1) ◽  
Author(s):  
Jagpal Singh Tomar ◽  
Shruti Kanga ◽  
Suraj Kumar Singh
Keyword(s):  
Climate Change ◽  
Forest Fire ◽  
Spatial Data ◽  
Forest Fires ◽  
Fire Risk ◽  
Fire Regimes ◽  
Spatial Data Analysis ◽  
Mitigation And Adaptation ◽  
The World ◽  
Urban Rural

Wildfire is one of the complex and damaging natural phenomena in the world. Wildfires pose an enormous challenge to predict and monitor complicated integration chemistry with the physical aspects of solid-gas stage combustion and heat transmission spatially diverse vegetations, topography, and detailed time and space conditions at various spatial and time scales. The research community has greatly enhanced its efforts in the last 25 years to better understand wildfires by improving observation, measurement, analysis and modelling. The fast development of spatial data analysis and computer technology has been facilitated. This combination allowed new decision promotion systems, information collection, analysis methods, growth, and existing fire management instruments. In several countries, despite this activity, forest fires remain a serious problem. Factors that raise the world risk of wildfires are climate change, urban-rural migration and the creation of the interface between urban and wildlands. These events demonstrate the tremendous destructive force of wildfires of great magnitude, sometimes well beyond our concrete containment and control capability. In addition to firefighters, foresters and other organised systems, the scientific community is key to addressing the problems of fire recognition in the countryside. Advances in our understanding of fire-fighting mechanisms and the relationship between fire activity and the natural and constructed environment can lead to successful fire risk decision support systems, the predictions for fire propagation and the reduction of fire risk. The convergence of forest ecosystems and forest fires has become the growing threat posed by human influences and other factors to ecosystems, resources and even human lives. Climate change will change forest fire regimes to enhance forest fire understanding and to build strategies for mitigation and adaptation. The study highlights broad aspects of forest fire in combination with

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