Research on wildfires and remote sensing in the last three decades: a bibliometric analysis

Evaluating the impact of wildland fires on landscapes, a pursuit increasingly supported by remote sensing techniques, requires an understanding of wildfire dynamics. This research highlights the main insights from the literature related to “wildfires” and “remote sensing” published between 1991 and 2020. The Scopus database was used as a source of information regarding scientific production on these topics, after which bibliometric tools were employed as a means through which to reveal patterns in this network of journals, terms, countries, and authors. The results suggest that these subject areas have undergone significant developments in the last three decades, having been the focus of growing interest among the scientific community. The most relevant contributions to the literature available have been made by researchers working in the areas of earth and environmental sciences (54% of the publications), primarily in the United States, China, Spain, and Canada. Research trends in this field have undergone a significant evolution in recent decades, explained by the strong relationship between the technological evolution of detection methods and remote sensing data acquisition.This research was funded by Portuguese funds through Fundação para a Ciência e a Tecnologia, I.P., within the scope of the research project “O valor económico dos incêndios florestais como suporte ao comportamento preventivo”, reference PCIF/AGT/0153/2018

Assessment of vegetation regrowth and spatial patterns and severity factors of wildfires in wildland-urban interface - the case of the large wildfire in Baião (2019)

Portugal is one of the countries most affected by forest fires in southern Europe, with recurrent events and frequent impacts. The demographic and social changes that have occurred in rural areas have driven land neglect in recent years, which, in turn, influences forest management and wildland-urban interface (WUI) areas that are related to fires. Therefore, it is the aim of this study to develop a case study in the municipality of Baião, based on the large wildfire (LWF) of 2019, defining and mapping the WUI areas, as well as evaluate, the recurrence, the GIF severity and in a period of 2 years, the regeneration of vegetation, in areas with different land uses and affected by different severities. The study was organized into 4 stages, being that in the first proceeded to the mapping of fire occurrences, the second of the wildland-urban interfaces, the third the characterization of the recurrence of large fires, the fourth corresponded to the evaluation of the severity of the large wildfire of 2019 and the evaluation of the vegetation regeneration, as a function of land use. The WUI represent 26.7% of the territory of the municipality of Baião, during the years 2001 to 2021 the municipality registered 3 770 fire occurrences. The LWF of Baião burned an area corresponding to 853 ha, the burned area in 2019 presented a maximum number of 12 fires between the years of 1975 to 2019, resulting in a maximum degree of 11 recurrences for the same area. We can verify that 2 years after the LWF, the area occupied by forest and scrub classes, which were hit by high severity, already showed significant levels of vegetation regeneration. With this, the main conclusions consider studies in this line contribute to the understanding of the patterns created by the wildfire in different landscapes, being information valuable for forest managers to understand the consequences (beneficial or not) and plan actions of prevention, restoration, and environmental education

Avaliação da regeneração da vegetação pós-incêndio no Parque Nacional da Chapada Diamantina do Brasil através de sensoriamento remoto

Understanding fire dynamics in vegetation is essential for assessing the impacts caused by wildfire action, especially because biomass burning in ecosystems has been indicated as one of the main factors that impact climate and biodiversity. A current alternative to detecting fire via satellite data is cloud processing platforms such as Google Earth Engine (GEE). Given this context, this work aims to assess the degree of vegetation regrowth after a wildfire in an area included in the Chapada Diamantina National Park (Bahia - Brazil) based on applying the Normalized Burn Ratio (NBR) in Landsat Surface Reflectance Tier 1 data sets. The images were accessed and processed on the GEE platform. The NBR index was more sensitive to the pre-and post-fire displacements of the pixels affected by the fires between the Landsat NIR and SWIR image bands. We found that the NBR mean values decreased immediately after the fire occurrence in the entire study area. Then, following the wildfire, the NBR mean values returned to conditions similar to those that preceded the fire. We can conclude that the plant biomass had already recovered considerably nine months after the fire when checking the NBR values. Therefore, this study points out the need to better understand the wildfire dynamics in the Chapada Diamantina National Park region and the impact associated with these events, with respect to fire ecology.A compreensão da dinâmica do fogo na vegetação é essencial para avaliar os impactes causados pela ação dos incêndios florestais, especialmente porque a queima de biomassa nos ecossistemas tem sido indicada como um dos principais fatores que impactam o clima e a biodiversidade. Uma alternativa atual para detetar incêndios através de dados de satélite são as plataformas de processamento em nuvens, como o Google Earth Engine (GEE). Dado este contexto, o presente trabalho visa avaliar o grau de recuperação da vegetação após um evento de incêndio numa área incluída no Parque Nacional da Chapada Diamantina (Bahia - Brasil) com base na aplicação da Razão de Queimada Normalizada (NBR) em conjuntos de dados Landsat Surface Reflectance Tier 1. As imagens foram acessadas e processadas na plataforma GEE. O índice NBR revelou-se mais sensível aos deslocamentos pré e pós-fogo dos pixels afetados pelos incêndios entre as bandas de imagem Landsat NIR e SWIR. Verificou-se que os valores médios do NBR diminuíram imediatamente após a ocorrência do incêndio em toda a área de estudo. Após o incêndio, os valores médios do NBR foram apontando no sentido do retorno a condições similares àquelas que o precederam, indicando os valores de NBR que a biomassa vegetal, nove meses após o incêndio, já apresentava uma considerável recuperação. Neste sentido, este estudo demonstra a necessidade de se conhecer melhor a dinâmica dos incêndios na região do Parque Nacional da Chapada Diamantina e os impactes associado a estes eventos, no que respeita à ecologia do fogo

Avaliação da regeneração da vegetação pós-incêndio no Parque Nacional da Chapada Diamantina do Brasil através de sensoriamento remoto

Understanding fire dynamics in vegetation is essential for assessing the impacts caused by wildfire action, especially because biomass burning in ecosystems has been indicated as one of the main factors that impact climate and biodiversity. A current alternative to detecting fire via satellite data is cloud processing platforms such as Google Earth Engine (GEE). Given this context, this work aims to assess the degree of vegetation regrowth after a wildfire in an area included in the Chapada Diamantina National Park (Bahia - Brazil) based on applying the Normalized Burn Ratio (NBR) in Landsat Surface Reflectance Tier 1 data sets. The images were accessed and processed on the GEE platform. The NBR index was more sensitive to the pre- and post-fire displacements of the pixels affected by the fires between the Landsat NIR and SWIR image bands. We found that the NBR mean values decreased immediately after the fire occurrence in the entire study area. Then, following the wildfire, the NBR mean values returned to conditions similar to those that preceded the fire. We can conclude that the plant biomass had already recovered considerably nine months after the fire when checking the NBR values. Therefore, this study points out the need to better understand the wildfire dynamics in the Chapada Diamantina National Park region and the impact associated with these events, with respect to fire ecology.A compreensão da dinâmica do fogo na vegetação é essencial para avaliar os impactes causados pela ação dos incêndios florestais, especialmente porque a queima de biomassa nos ecossistemas tem sido indicada como um dos principais fatores que impactam o clima e a biodiversidade. Uma alternativa atual para detetar incêndios através de dados de satélite são as plataformas de processamento em nuvens, como o Google Earth Engine (GEE). Dado este contexto, o presente trabalho visa avaliar o grau de recuperação da vegetação após um evento de incêndio numa área incluída no Parque Nacional da Chapada Diamantina (Bahia - Brasil) com base na aplicação da Razão de Queimada Normalizada (NBR) em conjuntos de dados Landsat Surface Reflectance Tier 1. As imagens foram acessadas e processadas na plataforma GEE. O índice NBR revelou-se mais sensível aos deslocamentos pré e pós-fogo dos pixels afetados pelos incêndios entre as bandas de imagem Landsat NIR e SWIR. Verificou-se que os valores médios do NBR diminuíram imediatamente após a ocorrência do incêndio em toda a área de estudo. Após o incêndio, os valores médios do NBR foram apontando no sentido do retorno a condições similares àquelas que o precederam, indicando os valores de NBR que a biomassa vegetal, nove meses após o incêndio, já apresentava uma considerável recuperação. Neste sentido, este estudo demonstra a necessidade de se conhecer melhor a dinâmica dos incêndios na região do Parque Nacional da Chapada Diamantina e os impactes associados a estes eventos, no que respeita à ecologia do fogo

ANÁLISE BIBLIOMÉTRICA DA ESPECTRORRADIOMETRIA E GEOESTATÍSTICA DE SOLOS: UMA DISCUSSÃO EM 10 ANOS

The increase of bibliometric surveys in the measurement of scientific activity has favored the development of important indicators. In this perspective, we intend to analyze the publications in scientific journals on spectroradiometry and soils, geostatistics and soil fertility on a 10-year time scale. Therefore, the SCOPUS platform was used for the analysis, configuring the search data, selecting only the articles, the search limit per year and the knowledge field limit. Subsequently, the general information of all journals including country of publication, authors' names, co-authors, citations, among others, were exported and semantic networks were established in the VOSviewer® program, selecting the period from 2007 to 2017. There was an increase in the number of publications of the two themes surveyed over time, the country that most published on spectroradiometry and soils is the USA, and on geostatistics and soil fertility in China and Brazil.La propagación y disponibilidad de fuentes y recursos de información en formato digital ha favorecido el desarrollo de indicadores importantes, como ejemplo de las investigaciones bibliométricas para la medición de la actividad científica. En esta perspectiva, se pretende analizar multitemporalmente las publicaciones en periódicos científicos sobre espectrorradiometría y suelos, geoestadística de suelos, en una escala temporal de 10 años. En este sentido, se utilizó la plataforma SCOPUS para el análisis, configurando los datos de búsqueda, seleccionando solamente los artículos, el límite de búsqueda por año y el límite de campo de conocimiento. A continuación, la información general de todos los periódicos incluyendo país de publicación, nombre de los autores, coautores, citas, entre otros, fueron exportados y se establecieron las redes semánticas en el programa VOSviewer®, seleccionándose el período de 2007 a 2017. Se observó un crecimiento del número de publicaciones de los dos temas investigados a lo largo del tiempo, los países que más publicaron sobre espectrorradiometría y suelos son Estados Unidos y el Reino Unido y, sobre geoestadística de suelos China y Brasil.A propagação e disponibilidade de fontes e recursos de informação em formato digital tem favorecido o desenvolvimento de indicadores importantes, como exemplo das pesquisas bibliométricas para a mensuração da atividade científica. Nessa perspectiva, pretende-se analisar multitemporalmente as publicações em periódicos científicos sobre espectrorradiometria e solos, geoestatística de solos, em uma escala temporal de 10 anos. Nesse sentido, utilizou-se a plataforma SCOPUS para a análise, configurando os dados de busca, selecionando somente os artigos, o limite de busca por ano e o limite de campo de conhecimento. Logo depois, as informações gerais de todos os periódicos incluindo país de publicação, nome dos autores, coautores, citações, entre outros, foram exportados e estabeleceu-se as redes semânticas no programa VOSviewer®, selecionando-se o período de 2007 a 2017. Observou-se um crescimento do número de publicações dos dois temas pesquisados ao longo do tempo, os países que mais publicaram sobre espectrorradiometria e solos são os EUA e o Reino Unido e, sobre geoestatística de solos a China e o Brasil

Geostatistical Modeling of Larger Elements of Soils of Feira de Santana-Ba Brazil

A variabilidade dos elementos do solo vem sendo estudada por técnicas de modelagem ambiental por meio da geoestatística. Essa pode ser uma ferramenta essencial para o desenvolvimento de projetos relacionados a métodos de interpolação e metodologias estatísticas para validar a correlação entre as características referentes aos solos. Nessa perspectiva, esse trabalho tem como objetivo modelar as características químicas naturais dos elementos maiores P, K, Mg, Ca, e Na dos solos de Feira de Santana-BA. Para tal, realizou-se a coleta das amostras de solos na área de estudo e foram realizadas as análises químicas em laboratório. Posteriormente foram removidos os outliers e efetuou-se a estatística descritiva dos atributos, avaliando também o coeficiente de correlação linear de Pearson entre os elementos. Calculou-se o tamanho do pixel, definiu-se o interpolador Krigagem por meio do cálculo dos resíduos e selecionou-se os critérios para classificação das propriedades. Os semivariogramas experimentais foram ajustados e em seguida produziu-se a Krigagem Ordinária, sendo também gerados mapas 2,5D. Observou-se que na maioria das vezes, as unidades de alta distribuição de elementos maiores estão ao oeste, em contrapartida, as áreas de baixa ao leste do município.A variability of soil elements has been studied by environmental modeling techniques using geostatistics. This can be an essential tool for the development of projects related to interpolation methods and statistical methodologies to validate the correlation between soil characteristics. In this perspective, this work aims to model the natural chemical characteristics of the larger elements P, K, Mg, Ca and Na of the soils of Feira de Santana-BA. To this end, it carried out a collection of solution samples in the study area and they were carried out as chemical analyzes in the laboratory. Subsequently, the outliers were removed and performed with a descriptive statistic of the attributes, also available or Pearson's linear correlation coefficient between the elements. Calculate the pixel size, define the Krigagem interpolator by calculating the residuals and select the standards for classifying properties. The experimental semivariograms were adjusted and followed produced in the Ordinary Krigagem, and 2.5D maps were also generated. It was observed that in most cases, the units of high distribution of larger elements are to the west, in contrast, the areas of low to the east of the municipality

Long-term Landsat-based monthly burned area dataset for the Brazilian biomes using Deep Learning

Fire is a significant agent of landscape transformation on Earth, and a dynamic and ephemeral process that is challenging to map. Difficulties include the seasonality of native vegetation in areas affected by fire, the high levels of spectral heterogeneity due to the spatial and temporal variability of the burned areas, distinct persistence of the fire signal, increase in cloud and smoke cover surrounding burned areas, and difficulty in detecting understory fire signals. To produce a large-scale time-series of burned area, a robust number of observations and a more efficient sampling strategy is needed. In order to overcome these challenges, we used a novel strategy based on a machine-learning algorithm to map monthly burned areas from 1985 to 2020 using Landsat-based annual quality mosaics retrieved from minimum NBR values. The annual mosaics integrated year-round observations of burned and unburned spectral data (i.e., RED, NIR, SWIR-1, and SWIR-2), and used them to train a Deep Neural Network model, which resulted in annual maps of areas burned by land use type for all six Brazilian biomes. The annual dataset was used to retrieve the frequency of the burned area, while the date on which the minimum NBR was captured in a year, was used to reconstruct 36 years of monthly burned area. Results of this effort indicated that 19.6% (1.6 million km2) of the Brazilian territory was burned from 1985 to 2020, with 61% of this area burned at least once. Most of the burning (83%) occurred between July and October. The Amazon and Cerrado, together, accounted for 85% of the area burned at least once in Brazil. Native vegetation was the land cover most affected by fire, representing 65% of the burned area, while the remaining 35% burned in areas dominated by anthropogenic land uses, mainly pasture. This novel dataset is crucial for understanding the spatial and long-term temporal dynamics of fire regimes that are fundamental for designing appropriate public policies for reducing and controlling fires in Brazil