scholarly journals MODELO DE ZONEAMENTO DE RISCO DE INCÊNDIOS PARA UNIDADES DE CONSERVAÇÃO BRASILEIRAS: O CASO DO PARQUE ESTADUAL DO CERRADO (PR)

FLORESTA ◽  
2011 ◽  
Vol 41 (3) ◽  
Author(s):  
Letícia Koproski ◽  
Matheus Pinheiro Ferreira ◽  
Johann Georg Goldammer ◽  
Antonio Carlos Batista
Keyword(s):  
Protected Areas ◽  
Fire History ◽  
Fire Risk ◽  
Geographical Information ◽  
Slope Aspect ◽  
Integrated Analysis ◽  
Risk Map ◽  
Integration Model ◽  
Forest Protection ◽  
Few Data

Este trabalho teve como objetivo estabelecer um modelo de zoneamento de risco de incêndios pela análise dos fatores físicos, associados às fontes de ignição e aos fatores de propagação dos incêndios, que pudesse ser aplicado à realidade da gestão das áreas protegidas em território brasileiro. Para tanto, o Parque Estadual do Cerrado foi selecionado como área de estudo. Foram produzidos mapas de riscos referentes à cobertura vegetal (V), influências humanas (H), declividade (D), orientação das encostas (E) e altimetria (A). O zoneamento foi gerado pela superposição dos mapas de risco, em função da somatória ponderada dos riscos parciais, representado pela equação: RISCO: 4V +3H + 1D + 1E + 1A. A partir do zoneamento, foi possível identificar duas áreas prioritárias para o manejo do fogo com relação ao risco de incêndios na Unidade. O modelo de integração traduziu adequadamente os níveis de risco e pode ser aplicado em outras unidades de conservação, especialmente em locais onde não existam muitos dados disponíveis sobre o histórico do fogo, ou onde existam poucos dados disponíveis sobre as áreas de estudo. Recomenda-se a utilização do modelo em locais onde não existam diferenças climáticas significativas.Palavras-chave: Mapas de risco; incêndios florestais; SIG; proteção florestal; áreas protegidas. AbstractFire risk mapping for Brazilian protected areas: the case of Cerrado State Park (PR). The aim of this research was to develop a model of forest fire risk map for Brazilian protected areas. The Cerrado State Park, located in Jaguariaíva city, State of Paraná, south of Brazil, was the focused area. The fire risk map was built up through the integrated analysis of vegetation cover (V), slope gradient (G), slope aspect (A), elevation (E), and human activities (H). For this analysis the Geographical Information System (GIS) was used. The fire risk map was the result of the overlay of the preliminary risk maps, by the model represented by the equation: RISK: 4V + 3H + 1G + 1A + 1E. The results presented that the integration model worked successfully for the area, properly managing the variables according to local characteristics and indicated two priority fire management areas in the Park. The model can be applied to protected areas with few data about fire history or few data about the area itself. The model is not recommended to be used in areas with significantly different climates.Keywords: Fire risk map; wildfires; GIS; forest protection.

scholarly journals ZONEAMENTO DE RISCO DE INCÊNDIOS FLORESTAIS PARA O ESTADO DO PARANÁ

FLORESTA ◽  
2004 ◽  
Vol 34 (2) ◽  
Author(s):  
Danielle Dos Santos De Oliveira ◽  
Antonio Carlos Batista ◽  
Ronaldo Viana Soares ◽  
Leocádio Grodzki ◽  
Jackson Vosgerau
Keyword(s):  
Information System ◽  
High Risk ◽  
Fire Risk ◽  
Geographical Information ◽  
Integrated Analysis ◽  
Fuel Moisture ◽  
Risk Map ◽  
Slope Gradient ◽  
Moderate Risk ◽  
Forest Fire Risk

O objetivo deste trabalho foi obter o Zoneamento de Risco de Incêndio Florestal para o estado do Paraná (ZRIF-PR), considerando o efeito integrado da presença humana, cobertura vegetal, condições meteorológicas e características topográficas. Para esta análise utilizou-se um Sistema de Informações Geográficas. Foram preparados mapas de risco preliminares para cada uma das variáveis em estudo. Estes mapas foram sobrepostos, e o resultado deste cruzamento de informações resultou no ZRIF-PR. De acordo com o ZRIF-PR, 51,87% da área foi classificada como risco moderado e 30,16% como risco alto. Para a validação do ZRIF-PR, o mesmo foi comparado com o mapa de focos de calor e o mapa das ocorrências de incêndio registradas entre 1991 e 2001. O modelo de integração proposto é o mais indicado para gerar o ZRIF-PR porque emprega maior número de variáveis e foi elaborado a partir de condições ambientais similares às do Paraná. Abstract The objective of this research was develop a forest fire risk map through the integrated analysis of human presence, vegetation cover, meteorological variables, fuel moisture, elevation, slope gradient and aspect. For this analysis the Geographical Information System (GIS) was used. The forest risk map (ZRIF-PR) was the result from the superposition of the thematic maps. The fire risk map obtained showed that 51,8% of the area was under moderate risk and 30,16% under high risk.

scholarly journals Modelagem espacial de risco de incêndio florestal para o município de Inhambupe, Bahia, Brasil

2016 ◽  
Vol 36 (85) ◽  
pp. 41 ◽  
Author(s):  
Larissa Alves Secundo White ◽  
Benjamin Leonardo Alves White ◽  
Genésio Tâmara Ribeiro
Keyword(s):  
Forest Fire ◽  
Fire Risk ◽  
Risk Map ◽  
Map Algebra ◽  
Analytic Hierarchy ◽  
Land Occupation ◽  
Forest Protection ◽  
Burned Areas ◽  
Hierarchy Process ◽  
Forest Fire Risk

A modelagem do risco espacial de incêndios florestais tem o objetivo de determinar as regiões mais susceptíveis ao fogo, baseando-se em variáveis que representam a facilidade de ignição e de propagação do fogo. Nesse contexto, utilizando-se das variáveis: sistema viário, densidade demográfica, uso e ocupação do solo, malha hidrográfica, inclinação e orientação das encostas, foram elaborados mapas de riscos preliminares, que, posteriormente à ponderações das mesmas pelo método AHP, foram integradas por meio da calculadora Raster em um mapa final de risco de incêndio florestal para o município de Inhambupe, Bahia, Brasil. Com base no modelo utilizado, 75,46% da área de estudo apresenta-se classificada como de maior risco, representado pelas classes “alto”, “muito alto” e “extremo”. Ao comparar o mapa final do risco de incêndio florestal para a área de estudo com o histórico de áreas queimadas, verificou-se que 94,83% dos registros de incêndios florestais estão alocados nas áreas de maior risco.Spatial modeling of forest fire risk for the Municipality of Inhambupe, Bahia State, BrazilSpatial modeling of forest fire risk has the aim to determine areas most susceptible to fire based on variables that represent facility of ignition and propagation. This work developed a forest fire risk map for the Municipality of Inhambupe, Bahia State, Brazil, by elaborating thematic maps of the following variables: road system, population density, land occupation and use, watershed network, slope and aspect. These were evaluated by the analytic hierarchy process and integrated with map algebra. Based on the developed model, 75.46% of the studied area was classified as “high”, “very high” and “extreme high” fire risk. When comparing the forest fire risk map with historical data of burned areas, 95% of the fires were in these areas.Index terms: Forest protection; Fire susceptibility; Risk map

scholarly journals PROVIDING THE FIRE RISK MAP IN FOREST AREA USING A GEOGRAPHICALLY WEIGHTED REGRESSION MODEL WITH GAUSSIN KERNEL AND MODIS IMAGES, A CASE STUDY: GOLESTAN PROVINCE

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 477-481
Author(s):  
A. Shah-Heydari pour ◽  
P. Pahlavani ◽  
B. Bigdeli
Keyword(s):  
Regression Model ◽  
Least Squares ◽  
Geographically Weighted Regression ◽  
Fire Risk ◽  
Ordinary Least Squares ◽  
Gaussian Kernel ◽  
Weighted Regression ◽  
Slope Aspect ◽  
Risk Map ◽  
Geographically Weighted Regression Model

According to the industrialization of cities and the apparent increase in pollutants and greenhouse gases, the importance of forests as the natural lungs of the earth is felt more than ever to clean these pollutants. Annually, a large part of the forests is destroyed due to the lack of timely action during the fire. Knowledge about areas with a high-risk of fire and equipping these areas by constructing access routes and allocating the fire-fighting equipment can help to eliminate the destruction of the forest. In this research, the fire risk of region was forecasted and the risk map of that was provided using MODIS images by applying geographically weighted regression model with Gaussian kernel and ordinary least squares over the effective parameters in forest fire including distance from residential areas, distance from the river, distance from the road, height, slope, aspect, soil type, land use, average temperature, wind speed, and rainfall. After the evaluation, it was found that the geographically weighted regression model with Gaussian kernel forecasted 93.4% of the all fire points properly, however the ordinary least squares method could forecast properly only 66% of the fire points.

Modeling cetacean habitat use in an urban coastal area in southeastern Brazil

2020 ◽  
Vol 642 ◽  
pp. 227-240
Author(s):  
L Lodi ◽  
R Tardin ◽  
G Maricato
Keyword(s):  
Habitat Use ◽  
Protected Areas ◽  
Linear Models ◽  
Anthropogenic Activities ◽  
Buffer Zone ◽  
Humpback Whales ◽  
Southeastern Brazil ◽  
Major Influence ◽  
Cetacean Species ◽  
Few Data

Most studies of cetacean habitat use do not consider the influence of anthropogenic activities. We investigated the influence of environmental and anthropogenic variables on habitat use by humpback Megaptera novaeangliae and Bryde’s whales Balaenoptera brydei off the coast of the Brazilian city of Rio de Janeiro. Although there are 2 marine protected areas (MPAs) in this area, few data are available on cetacean habitat use or on the overlap of different cetacean species within these MPAs. Our aim was to evaluate the effectiveness of the MPAs and propose a buffer zone to better protect the biodiversity of the study area. We conducted systematic surveys and developed spatial eigenvector generalized linear models to characterize habitat use by the species in the study area. Habitat use by humpback whales was influenced only by depth, whereas for Bryde’s whales there was the additional influence of anthropogenic variables. For Bryde’s whales, which use the area for feeding, sea surface temperature and the distance to anchorages had a major influence on habitat use. We also showed that neither of the MPAs in the study area adequately protects the hotspots of either whale species. Most of the humpback whale grid cells with high sighting predictions were located within 2 km of the MPAs, while areas of high sighting prediction of Bryde’s whales were located up to 5 km from the MPAs, closer to beaches. Our findings provide important insights for the delimitation of protected areas and zoning of the MPAs.

scholarly journals Using the Landsat Burned Area Products to Derive Fire History Relevant for Fire Management and Conservation in the State of Florida, Southeastern USA

Fire ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 26
Author(s):  
Casey Teske ◽  
Melanie K. Vanderhoof ◽  
Todd J. Hawbaker ◽  
Joe Noble ◽  
John Kevin Hiers
Keyword(s):  
Prescribed Fire ◽  
Spatial Data ◽  
Fire History ◽  
Fire Management ◽  
Fire Behavior ◽  
Fire Risk ◽  
Behavior Modeling ◽  
Burned Area ◽  
Burned Areas ◽  
Burn Probability

Development of comprehensive spatially explicit fire occurrence data remains one of the most critical needs for fire managers globally, and especially for conservation across the southeastern United States. Not only are many endangered species and ecosystems in that region reliant on frequent fire, but fire risk analysis, prescribed fire planning, and fire behavior modeling are sensitive to fire history due to the long growing season and high vegetation productivity. Spatial data that map burned areas over time provide critical information for evaluating management successes. However, existing fire data have undocumented shortcomings that limit their use when detailing the effectiveness of fire management at state and regional scales. Here, we assessed information in existing fire datasets for Florida and the Landsat Burned Area products based on input from the fire management community. We considered the potential of different datasets to track the spatial extents of fires and derive fire history metrics (e.g., time since last burn, fire frequency, and seasonality). We found that burned areas generated by applying a 90% threshold to the Landsat burn probability product matched patterns recorded and observed by fire managers at three pilot areas. We then created fire history metrics for the entire state from the modified Landsat Burned Area product. Finally, to show their potential application for conservation management, we compared fire history metrics across ownerships for natural pinelands, where prescribed fire is frequently applied. Implications of this effort include increased awareness around conservation and fire management planning efforts and an extension of derivative products regionally or globally.

scholarly journals Zakour Forest fire risk map assessment in the commune of Mamounia (Mascara, Algeria)

2021 ◽  
Vol 63 (1) ◽  
pp. 21-35
Author(s):  
Djamel Anteur ◽  
Abdelkrim Benaradj ◽  
Youcef Fekir ◽  
Djillali Baghdadi
Keyword(s):  
Decision Making ◽  
Forest Fires ◽  
Human Activities ◽  
Forest Ecosystems ◽  
Agricultural Land ◽  
Fire Risk ◽  
Risk Map ◽  
Management Plans ◽  
The City ◽  
Forest Fire Risk

Abstract The great forest of Zakour is located north of the commune of Mamounia (department of Mascara). It is considered the lung of the city of Mascara, covers an area of 126.8 ha. It is a forest that is subject to several natural and human constraints. Among them, the fires are a major danger because of their impacts on forest ecosystems. The purpose of this work is to develop a fire risk map of the Zakour Forest through the contribution of geomatics according to natural and anthropogenic conditions (human activities, agglomeration, agricultural land) while integrating information from ground on the physiognomy of the vegetation. For this, the creation of a clearer fire risk map to delimit the zones potentially sensitive to forest fires in the forest area of Zakour. This then allows good implementation of detection management plans, for better prevention and decision-making assistance in protecting and fighting forest fires.

scholarly journals Visualizing When, Where, and How Fires Happen in U.S. Parks and Protected Areas

2020 ◽  
Vol 9 (5) ◽  
pp. 333
Author(s):  
Nicole C. Inglis ◽  
Jelena Vukomanovic
Keyword(s):  
Decision Making ◽  
Protected Areas ◽  
National Park ◽  
Fire History ◽  
National Park Service ◽  
Fire Management ◽  
Fire Regime ◽  
Fire Regimes ◽  
The United States ◽  
Park Service

Fire management in protected areas faces mounting obstacles as climate change alters disturbance regimes, resources are diverted to fighting wildfires, and more people live along the boundaries of parks. Evidence-based prescribed fire management and improved communication with stakeholders is vital to reducing fire risk while maintaining public trust. Numerous national fire databases document when and where natural, prescribed, and human-caused fires have occurred on public lands in the United States. However, these databases are incongruous and non-standardized, making it difficult to visualize spatiotemporal patterns of fire and engage stakeholders in decision-making. We created interactive decision analytics (“VISTAFiRe”) that transform fire history data into clear visualizations of the spatial and temporal dimensions of fire and its management. We demonstrate the utility of our approach using Big Cypress National Preserve and Everglades National Park as examples of protected areas experiencing fire regime change between 1980 and 2017. Our open source visualizations may be applied to any data from the National Park Service Wildland Fire Events Geodatabase, with flexibility to communicate shifts in fire regimes over time, such as the type of ignition, duration and magnitude, and changes in seasonal occurrence. Application of the tool to Everglades and Big Cypress revealed that natural wildfires are occurring earlier in the wildfire season, while human-caused and prescribed wildfires are becoming less and more common, respectively. These new avenues of stakeholder communication are allowing the National Park Service to devise research plans to prepare for environmental change, guide resource allocation, and support decision-making in a clear and timely manner.

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