Decreased birth weight after prenatal exposure to wildfires on the eastern coast of Korea in 2000

OBJECTIVES: In April 2000, a series of wildfires occurred simultaneously in five adjacent small cities located on the eastern coast of Korea. These wildfires burned approximately 23,794 hectares of forestland over several days. We investigated the effects of prenatal exposure to the by-products generated by wildfire disasters on birth weight. METHODS: Birth weight data were obtained for 1999-2001 from the birth registration database of the Korean National Statistical Office and matched with the zip code and exposed/unexposed pregnancy week for days of the wildfires. Generalized linear models were then used to assess the associations between birth weight and exposure to wildfires after adjusting for fetal sex, gestational age, parity, maternal age, maternal education, paternal education, and average exposed atmospheric temperature. RESULTS: Compared with unexposed pregnancies before and after the wildfires, mean birth weight decreased by 41.4 g (95% confidence interval [CI], -72.4 to -10.4) after wildfire exposure during the first trimester, 23.2 g (95% CI, -59.3 to 13.0) for exposure during the second trimester, and 27.0 g (95% CI, -63.8 to 9.8) during the third trimester. In the adjusted model for infants exposed in utero during any trimester, the mean birth weight decreased by 32.5 g (95% CI, -53.2 to -11.7). CONCLUSIONS: We observed a 1% reduction in birth weight after wildfire exposure. Thus, exposure to by-products generated during a wildfire disaster during pregnancy may slow fetal growth and cause developmental delays

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

Hydrology and Fire History Drive Patterns in Post-Fire Recovery in Everglades Wetland Ecosystem

Although fire-adapted ecosystems in Everglades require regular burning to maintain wetland ecosystems, land management and climate-change have altered natural fire-regime. Due to changes in climate and hydrology, historical fire-regimes may become irrelevant. To understand changing fire return intervals, I look at patterns in ecosystem recovery, where fast recovery is indicative of resilience and adaption with an objective of understanding post-fire recovery time in Everglades. I evaluated how post-fire recovery rates were influenced by hydrology and fire-history (1948-2019) by measuring changes in normalized difference vegetation index following fires that burned between 2005-2019 within Everglades. Hydrology had stronger effect on post-fire recovery compared to fire history. Increasing water-levels by 10% across Everglades either shortened (sawgrass marl prairie) or prolonged (cattail marsh, graminoid marsh, graminoid prairie, halophytic herbaceous prairie and sawgrass marsh) post-fire recovery estimates. Fire return intervals for Everglades were dynamic and fire-management must develop novel approaches to manage fire-regimes

Análisis de la severidad del incendio forestal suscitado en la Granja Porcón, a través de imágenes Sentinel - 2 – periodo 2019 - 2021, Cajamarca

La presente investigación se realizó en la Granja Porcón, con el objetivo de evaluar mediante imágenes Sentinel – 2 la severidad del incendio forestal suscitado en la Granja Porcón, en el Periodo 2019 – 2021, Cajamarca. Para lo cual se descargó y procesó imágenes satelitales en el software QGIS 3.10, con la finalidad de caracterizar las zonas forestales y calcular los índices espectrales: Índice Normalizado de Área quemada (NBR), Índice de Vegetación de Diferencia Normalizada (NDVI) e Índice de Vegetación Ajustado al Suelo (SAVI). La investigación fue de tipo aplicada, con enfoque cuantitativo, diseño no experimental transversal descriptivo. La población estuvo conformada por el área geográfica del distrito de Cajamarca, como muestra se tomó el área geográfica de la Granja Porcón, la cual abarca doce mil hectáreas aproximadamente. Obteniéndose como resultado tres clases de zonas forestales: zona de bosque, zona agrícola y zona sin vegetación, evidenciándose una expansión en el área de las dos primeras zonas, a causa de actividades antrópicas entre los años 2019 y 2021. Se concluye que el índice espectral NBR fue el que permitió identificar con mayor precisión el área siniestrada por el incendio forestal en la Granja Porcón

Satellite-Based Evaluation of the Post-Fire Recovery Process from the Worst Forest Fire Case in South Korea

The worst forest fire in South Korea occurred in April 2000 on the eastern coast. Forest recovery works were conducted until 2005, and the forest has been monitored since the fire. Remote sensing techniques have been used to detect the burned areas and to evaluate the recovery-time point of the post-fire processes during the past 18 years. We used three indices, Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), and Gross Primary Production (GPP), to temporally monitor a burned area in terms of its moisture condition, vegetation biomass, and photosynthetic activity, respectively. The change of those three indices by forest recovery processes was relatively analyzed using an unburned reference area. The selected unburned area had similar characteristics to the burned area prior to the forest fire. The temporal patterns of NBR and NDVI, not only showed the forest recovery process as a result of forest management, but also statistically distinguished the recovery periods at the regions of low, moderate, and high fire severity. The NBR2.1 for all areas, calculated using 2.1 μm wavelengths, reached the unburned state in 2008. The NDVI for areas with low and moderate fire severity levels became significantly equal to the unburned state in 2009 (p > 0.05), but areas with high severity levels did not reach the unburned state until 2017. This indicated that the surface and vegetation moisture conditions recovered to the unburned state about 8 years after the fire event, while vegetation biomass and health required a longer time to recover, particularly for high severity regions. In the case of GPP, it rapidly recovered after about 3 years. Then, the steady increase in GPP surpassed the GPP of the reference area in 2015 because of the rapid growth and high photosynthetic activity of young forests. Therefore, the concluding scientific message is that, because the recovery-time point for each component of the forest ecosystem is different, using only one satellite-based indicator will not be suitable to understand the post-fire recovery process. NBR, NDVI, and GPP can be combined. Further studies will require more approaches using various terms of indices

Satellite-Based Evaluation of the Post-Fire Recovery Process from the Worst Forest Fire Case in South Korea

The worst forest fire in South Korea occurred in April 2000 on the eastern coast. Forest recovery works were conducted until 2005, and the forest has been monitored since the fire. Remote sensing techniques have been used to detect the burned areas and to evaluate the recovery-time point of the post-fire processes during the past 18 years. We used three indices, Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), and Gross Primary Production (GPP), to temporally monitor a burned area in terms of its moisture condition, vegetation biomass, and photosynthetic activity, respectively. The change of those three indices by forest recovery processes was relatively analyzed using an unburned reference area. The selected unburned area had similar characteristics to the burned area prior to the forest fire. The temporal patterns of NBR and NDVI, not only showed the forest recovery process as a result of forest management, but also statistically distinguished the recovery periods at the regions of low, moderate, and high fire severity. The NBR2.1 for all areas, calculated using 2.1 μm wavelengths, reached the unburned state in 2008. The NDVI for areas with low and moderate fire severity levels became significantly equal to the unburned state in 2009 (p > 0.05), but areas with high severity levels did not reach the unburned state until 2017. This indicated that the surface and vegetation moisture conditions recovered to the unburned state about 8 years after the fire event, while vegetation biomass and health required a longer time to recover, particularly for high severity regions. In the case of GPP, it rapidly recovered after about 3 years. Then, the steady increase in GPP surpassed the GPP of the reference area in 2015 because of the rapid growth and high photosynthetic activity of young forests. Therefore, the concluding scientific message is that, because the recovery-time point for each component of the forest ecosystem is different, using only one satellite-based indicator will not be suitable to understand the post-fire recovery process. NBR, NDVI, and GPP can be combined. Further studies will require more approaches using various terms of indices