Índices espectrales de vegetación para la detección de áreas quemadas

The use of remote sensing for the mapping and discrimination of forest fires or burned areas is a key tool for monitoring, prevention and mainly for recovery and organization of pre and post-fire areas, which has proven to be an efficient and essential tool to perform these types of tasks. Numerous remote sensing techniques have been designed for mapping burned areas, highlighting the use and application of vegetation indexes, which have allowed advances in the study and understanding of the spatial and temporal behavior of plant covering. These techniques open up more possibilities to continue with research and new applications in different areas, especially related to the study of terrestrial ecosystems, which allows greater access to information (greater openness of public and private entities). The objective of this article is to define, from the explanations of certain authors, four of the vegetation spectral indexes most commonly used for mapping burned areas: normalized difference vegetation index (NDVI), normalized burned ratio (NBR), global environmental monitoring index (GEMI) and mid-infrared burned index (MIRBI).El uso de la teledetección para la cartografía y discriminación de incendios forestales o áreas quemadas es una herramienta clave para el monitoreo, prevención y sobre todo para la recuperación y organización de áreas pre y post-incendios, la cual ha demostrado ser una herramienta eficiente, útil imprescindible para desempeñar este tipo de tareas. Numerosas técnicas de teledetección se han diseñado para la cartografía de áreas quemadas, donde resalta el uso y aplicación de índices de vegetación, los cuales han permitido avances en el estudio y comprensión del comportamiento espacial y temporal de las coberturas vegetales. Estas técnicas abren más posibilidades para continuar con investigaciones y nuevas aplicaciones en diferentes ámbitos, sobre todo relacionadas al estudio de ecosistemas terrestres, lo que permite mayor acceso a la información (mayor apertura de entidades públicas y privadas). El presente artículo tiene por objetivo definir a partir de las explicaciones de ciertos autores, cuatro de los índices espectrales de vegetación más utilizados para la cartografía de áreas quemadas: índice de vegetación de diferencia normalizada (NDVI), índice de monitoreo ambiental global (GEMI), relación de quemado normalizado (NBR), índice de quemado infrarrojo medio (MIRBI)

Índices espectrales de vegetación para la detección de áreas quemadas

The use of remote sensing for the mapping and discrimination of forest fires or burned areas is a key tool for monitoring, prevention and mainly for recovery and organization of pre and post-fire areas, which has proven to be an efficient and essential tool to perform these types of tasks. Numerous remote sensing techniques have been designed for mapping burned areas, highlighting the use and application of vegetation indexes, which have allowed advances in the study and understanding of the spatial and temporal behavior of plant covering. These techniques open up more possibilities to continue with research and new applications in different areas, especially related to the study of terrestrial ecosystems, which allows greater access to information (greater openness of public and private entities). The objective of this article is to define, from the explanations of certain authors, four of the vegetation spectral indexes most commonly used for mapping burned areas: normalized difference vegetation index (NDVI), normalized burned ratio (NBR), global environmental monitoring index (GEMI) and mid-infrared burned index (MIRBI).El uso de la teledetección para la cartografía y discriminación de incendios forestales o áreas quemadas es una herramienta clave para el monitoreo, prevención y sobre todo para la recuperación y organización de áreas pre y post-incendios, la cual ha demostrado ser una herramienta eficiente, útil imprescindible para desempeñar este tipo de tareas. Numerosas técnicas de teledetección se han diseñado para la cartografía de áreas quemadas, donde resalta el uso y aplicación de índices de vegetación, los cuales han permitido avances en el estudio y comprensión del comportamiento espacial y temporal de las coberturas vegetales. Estas técnicas abren más posibilidades para continuar con investigaciones y nuevas aplicaciones en diferentes ámbitos, sobre todo relacionadas al estudio de ecosistemas terrestres, lo que permite mayor acceso a la información (mayor apertura de entidades públicas y privadas). El presente artículo tiene por objetivo definir a partir de las explicaciones de ciertos autores, cuatro de los índices espectrales de vegetación más utilizados para la cartografía de áreas quemadas: índice de vegetación de diferencia normalizada (NDVI), índice de monitoreo ambiental global (GEMI), relación de quemado normalizado (NBR), índice de quemado infrarrojo medio (MIRBI)

Effects of Fire, Grazing and Agriculture on Carbon Stocks and Biodiversity in the Ruaha-Katavi Landscape

The wildlife corridor between Ruaha and Katavi National Parks is under threat from cultivation and increased fire frequencies. This study evaluated the impacts of protection, fire, and habitat conversion on carbon stocks and biodiversity in the Ruaha-Katavi Landscape. Soil carbon, above-ground woody carbon stocks, herbaceous biomass and insect species richness were determined from 87 plots across a variety of land uses. There were significant differences in carbon stocks among different soil, and land use types (p < 0.001). Sandy soils featured significantly higher woody carbon (p < 0.001) than heavy clay soils. Conversion of woodlands to croplands significantly reduced aboveground woody carbon (p < 0.001) from an average of 72.4 Mg/ha for woodlands compared to 30.9 Mg/ha for croplands. Furthermore, croplands had significantly lower woody carbon than grazed woodland remnants in Open Areas (p = 0.005). Herbaceous plants and Orthoptera species richness did not vary significantly with land use (p > 0.05). Lepidoptera species richness significantly correlated with tree species richness. This study provides some key preliminary information that may justify feasible interventions to slow down conversion of woodlands into croplands to achieve climate-related benefits mainly reduction of greenhouse gas emissions by sequestering carbon in wood and soils

Burned area detection based on Landsat time series in savannas of southern Burkina Faso

West African savannas are subject to regular fires, which have impacts on vegetation structure, biodiversity and carbon balance. An efficient and accurate mapping of burned area associated with seasonal fires can greatly benefit decision making in land management. Since coarse resolution burned area products cannot meet the accuracy needed for fire management and climate modelling at local scales, the medium resolution Landsat data is a promising alternative for local scale studies. In this study, we developed an algorithm for continuous monitoring of annual burned areas using Landsat time series. The algorithm is based on burned pixel detection using harmonic model fitting with Landsat time series and breakpoint identification in the time series data. This approach was tested in a savanna area in southern Burkina Faso using 281 images acquired between October 2000 and April 2016. An overall accuracy of 79.2% was obtained with balanced omission and commission errors. This represents a significant improvement in comparison with MODIS burned area product (67.6%), which had more omission errors than commission errors, indicating underestimation of the total burned area. By observing the spatial distribution of burned areas, we found that the Landsat based method misclassified cropland and cloud shadows as burned areas due to the similar spectral response, and MODIS burned area product omitted small and fragmented burned areas. The proposed algorithm is flexible and robust against decreased data availability caused by clouds and Landsat 7 missing lines, therefore having a high potential for being applied in other landscapes in future studies.Peer reviewe

Anthropogenic modifications to fire regimes in the wider Serengeti‐Mara ecosystem

Fire is a key driver in savannah systems and widely used as a land management tool. Intensifying human land uses are leading to rapid changes in the fire regimes, with consequences for ecosystem functioning and composition. We undertake a novel analysis describing spatial patterns in the fire regime of the Serengeti‐Mara ecosystem, document multidecadal temporal changes and investigate the factors underlying these patterns. We used MODIS active fire and burned area products from 2001 to 2014 to identify individual fires; summarizing four characteristics for each detected fire: size, ignition date, time since last fire and radiative power. Using satellite imagery, we estimated the rate of change in the density of livestock bomas as a proxy for livestock density. We used these metrics to model drivers of variation in the four fire characteristics, as well as total number of fires and total area burned. Fires in the Serengeti‐Mara show high spatial variability—with number of fires and ignition date mirroring mean annual precipitation. The short‐term effect of rainfall decreases fire size and intensity but cumulative rainfall over several years leads to increased standing grass biomass and fuel loads, and, therefore, in larger and hotter fires. Our study reveals dramatic changes over time, with a reduction in total number of fires and total area burned, to the point where some areas now experience virtually no fire. We suggest that increasing livestock numbers are driving this decline, presumably by inhibiting fire spread. These temporal patterns are part of a global decline in total area burned, especially in savannahs, and we caution that ecosystem functioning may have been compromised. Land managers and policy formulators need to factor in rapid fire regime modifications to achieve management objectives and maintain the ecological function of savannah ecosystems

A Disease-Mediated Trophic Cascade in the Serengeti and its Implications for Ecosystem C

The removal of rinderpest had cascading effects on herbivore populations, fire, tree density, and even ecosystem carbon in the Serengeti ecosystem of East Africa

Anthropogenic modifications to fire regimes in the wider Serengeti-Mara ecosystem

Fire is a key driver in savannah systems and widely used as a land management tool. Intensifying human land uses are leading to rapid changes in the fire regimes, with consequences for ecosystem functioning and composition. We undertake a novel analysis describing spatial patterns in the fire regime of the Serengeti‐Mara ecosystem, document multidecadal temporal changes and investigate the factors underlying these patterns. We used MODIS active fire and burned area products from 2001 to 2014 to identify individual fires; summarizing four characteristics for each detected fire: size, ignition date, time since last fire and radiative power. Using satellite imagery, we estimated the rate of change in the density of livestock bomas as a proxy for livestock density. We used these metrics to model drivers of variation in the four fire characteristics, as well as total number of fires and total area burned. Fires in the Serengeti‐Mara show high spatial variability—with number of fires and ignition date mirroring mean annual precipitation. The short‐term effect of rainfall decreases fire size and intensity but cumulative rainfall over several years leads to increased standing grass biomass and fuel loads, and, therefore, in larger and hotter fires. Our study reveals dramatic changes over time, with a reduction in total number of fires and total area burned, to the point where some areas now experience virtually no fire. We suggest that increasing livestock numbers are driving this decline, presumably by inhibiting fire spread. These temporal patterns are part of a global decline in total area burned, especially in savannahs, and we caution that ecosystem functioning may have been compromised. Land managers and policy formulators need to factor in rapid fire regime modifications to achieve management objectives and maintain the ecological function of savannah ecosystems.Natural Environment Research Council, Grant/Award Number: JZG10015; Leverhulme Trust, Grant/Award Number: IN‐2014‐022; Vetenskapsrådet; Sida and Formas, Grant/Award Number: 2016‐06355.http://wileyonlinelibrary.com/journal/gcbhj2019Zoology and Entomolog

Fire Dynamics and Woody Cover Changes in the Serengeti-Mara Ecosystem 2000 to 2005 - A Remote Sensing Approach

The Serengeti-Mara savanna environment in East Africa is characterized by changing levels of woody cover and a dynamic fire regime. The relative proportion of woodland to grassland savanna affects animal habitat, biodiversity, and carbon storage, and is regulated by factors such as the fire regime (frequency, intensity, seasonality), and precipitation. The main objectives of this dissertation are to determine recent changes in woody cover at a regional scale and identify fire regimes and climate associated with these changes. Understanding these relationships is important for the assessment of future trajectories of woody cover under changing climate. Required spatially coherent data layers can only be obtained at the regional scale through the analysis of remote sensing data. Woody cover changes between 2000 and 2005 were derived from field data and a time series of MODIS satellite imagery at 500 m spatial resolution. Data layers on the controlling variables (fire frequency, seasonality, intensity and rainfall) were developed using a combination of remote sensing and model-based approaches. Burned areas were mapped using daily MODIS imagery at 250 m resolution. Outputs were used to make the requisite layers depicting fire frequency and seasonality. Fire intensity was derived using a model based on empirical relationships, mainly estimating fire fuel load as a function of rainfall and grazing. The combined data layers were analyzed using regression and decision tree techniques. Results suggest woody cover in central and northern Serengeti National Park continued to increase after 2000. Woody cover decreases were strongest in the wider Maswa Game Reserve area (MSW) under low precipitation conditions and late season burning. Woody cover losses in burned areas were also higher in the low fire frequency region of the Maasai Mara National Reserve (MNR). Fire seasonality was the most important fire regime parameter controlling woody cover in burned woodland savanna areas while fire intensity was most relevant for grassland savanna areas. Continued late season burning in drought years might cause further decrease of woody cover in MSW. MNR is expected to continue to be dominated by grassland savanna at similar fire frequency and browsing levels

Application of satellite image time series and texture information in land cover characterization and burned area detection

Land cover is critical information to various land management and scientific applications, including biogeochemical and climate modeling. In addition, fire is an essential factor in shaping of vegetation structures, as well as for the functioning of savanna ecosystems. Remote sensing has long been an important and effective means of mapping and monitoring land cover and burned area over large areas in a consistent and robust way. Owing to the free and open Landsat archive and the increasing availability of high spatial resolution imagery, seasonal features from the temporal domain and the use of texture features from the spatial domain create new opportunities for land cover characterization and burned area detection. This thesis examined the application of satellite image time series and texture information in land cover characterization and burned area detection. First, the utility of seasonal features derived from Landsat time series (LTS) in improving accuracies of land cover classification and attribute prediction in a savanna area in southern Burkina Faso was studied. Then, the temporal profiles from LTS were explored for mapping burned areas over a 16 year period, and MODIS burned area product was used for comparison. Finally, the application of texture features derived from high spatial resolution data in land cover classification and attribute predictions was investigated in a savanna area of Burkina Faso and an urban fringe area in Beijing. According to the results, firstly, seasonal features from LTS based on all available imagery during one year as input led to a significant increase in land cover classification accuracy in comparison to the dry and wet season single date imagery. The harmonic model used for time series modeling provided a robust method for extracting seasonal features, and the influence of burned pixels on seasonal features could be considered simultaneously. Secondly, the annual burned area mapping based on a harmonic model and breakpoint identification with LTS was capable of detecting small and patchy burn scars with higher accuracy than MODIS burned area product. The approach demonstrated the potential of LTS for improving burned area detection in savannas, and was robust against data gaps caused by clouds and Landsat 7 missing lines. Thirdly, predictive models of tree crown cover (CC) using RapidEye and LTS imagery achieved similar accuracy, indicating the importance of texture and seasonal features from RapidEye and LTS imagery, respectively. Predictions of aboveground carbon and tree species richness, which were strongly correlated with CC, were promising using RapidEye and LTS imagery. Finally, the optimized window size texture classification improved classification accuracy in comparison to the classifications with single window size texture features and multiple window size texture features in an urban fringe area in Beijing, indicating the importance of multiscale texture information. Keywords: Landsat time series, texture, land cover classification, burned area, savanna, tree crown cove

Monitoramento de queimadas no sudoeste do Pará, a partir de séries temporais do sensor modis

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Humanas, Departamento de Geografia, Programa de Pós-Graduação em Geografia, 2016.As queimadas associadas à expansão da pecuária e agricultura têm se tornado um problema no bioma Amazônico, causando danos severos ao meio ambiente. Imagens de sensoriamento remoto têm sido amplamente utilizadas no monitoramento de queimadas na extensa Floresta Amazônica, porém há a necessidade de aprimoramentos metodológicos para uma detecção automatizada. Esta pesquisa tem como objetivo avaliar séries temporais MODIS para o mapeamento de áreas queimadas no município de Novo Progresso, Pará, e determinar suas ocorrência nos diferentes tipos de uso e cobertura da terra durante o período de 2000-2014. Na detecção de área queimada, os seguintes dados foram comparados: banda do infravermelho próximo e índices espectrais (NBR, NDVI e NBRT), considerando-se imagens diárias e produtos compostos de 8 dias. As séries temporais MODIS foram filtradas e normalizadas temporalmente para eliminar falsos eventos de queimadas. A determinação dos valores limites para a ocorrência de queimadas foi obtida a partir da comparação da série de imagens MODIS com classificações visuais de dados LANDSAT/TM e ETM+ usando o coeficiente Kappa. O melhor resultado alcançado considerou os seguintes fatores: banda de infravermelho próximo, imagens diárias e normalização pela média, obtendo o valor de coeficiente Kappa de 0,72 e Acurácia Geral de 99%. As áreas desmatadas são as responsáveis por mais de 70% dos eventos de incêndios. As propriedades privadas apresentaram maior porcentagem de área queimada, enquanto as Reservas Ambientais Particulares e Terras Indígenas apresentaram as menores taxas. O resultado do método proposto foi melhor do que o disponível pelo produto de áreas queimadas (MCD45), mas ainda apresenta interferências de cobertura de nuvens que devem ser melhoradas em trabalhos futuros.Fires associated with the expansion of cattle ranching and agriculture has become a problem in the Amazon biome, causing severe environmental damages. Remote sensing images have been widely used in the fire monitoring on the extensive Amazon forest, but an accurate automated detection still need improvements. This research aims to evaluate MODIS time series spectral indices for mapping burned areas in the municipality of Novo Progresso, Para, and determine their occurrences in the different types of land use/land cover during the period 2000-2014. In burned area detection, the following data were compared: near-infrared band and spectral indices (NBR, NDVI and NBRT), considering daily images and 8-day composite products. MODIS time series were filtered and standardized temporally to eliminate false fire events. Threshold-value determination for the fire occurrences was obtained from the comparison of MODIS series with visual image classification of Landsat TM and ETM+ data using the Kappa coefficient. The best result considered the following factors: near-infrared band, daily data, and mean standardization, obtaining the Kappa coefficient value of 0.72 and Overall accuracy of 99%. The deforested areas are responsible for more than 70% of fire events. Private properties showed a higher percentage of the burned area, while private and Indigenous Lands Environmental Reserves had the lowest rates. The result of the proposed method was better than the burned area product (MCD45), but still shows cloud cover interference that should be improved in future work