An intercomparison of Satellite Burned Area Maps derived from MODIS, MERIS, SPOT-VEGETATION, and ATSR images. An application to the August 2006 Galicia (Spain) forest fires (original) (raw)
Related papers
Forest Ecology and Management, 2011
Forest fires throughout the world result in tree mortality that can cause substantial timber and carbon losses. There is a critical need to map the areas burned by such fires to guide forest management decisions. Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery provides inexpensive and frequent coverage over large areas, facilitating forest health monitoring. In this study a MODIS post-fire image at a spatial resolution of 250 m serves as the starting point of an image mining based method. It involves three algorithms: modeling as a sum of Gaussian functions, kernel based smoothing, and adaptive thresholding. Adaptive thresholding serves as the reference to be compared to the image mining based method. Three spectral indices specifically designed for burned area identification have been used: the Burned Area Index (BAI), the Burned Area Index adapted to MODIS bands (BAIM), and the Normalized Burn Ratio (NBR). The j statistic is applied to quantify the accuracy of the burned areas estimations by relating the estimated area with burned area perimeters measured on the ground by Global Positioning System (GPS). In addition, the j statistic allows us to identify both the optimal spectral index and the optimal algorithms' parameters. In this work, an accurate estimation (j > 0.8) of areas burned by forest fires in Mediterranean countries is achieved, in particular if the BAIM index is used. The accuracy of these estimates is compared with the accuracy obtained by using the reference method by a McNemar's test. Results show that our image mining based method allows a higher accuracy (the average increase of j equals to 16%) than the reference method. We conclude that this method adequately maps burned areas, and that it may help management agencies to better understand of landscape-scale burn patterns.
Forest Ecology and Management, 2006
The European Commission, Joint Research Centre (JRC) has established within its Institute for Environment and Sustainability (IES) the European Forest Fires Information System (EFFIS). A number of exceptionally large uncontrolled fires that occurred during 2003 and destroyed important parts of the land resources led to the development of the Rapid Damage Assessment (RDA) module within EFFIS. In this paper we present the different steps of the implementation of the RDA module that was built in order to map the extent of burned areas during the summer fire season. Burned areas of at least 50 ha were mapped from 2003 to 2006. The data used for the burned area mapping are both TERRA and AQUA MODIS images at 250 meters resolution, although the use of the 500 meters short-infrared bands is also foreseen. During 2003 only a selected number of images were used and the burned areas were visually classified. In 2004 the system was improved using an automatic method for scene identification and Quick Look retrieval followed by a visual inspection of these Quick Looks before downloading the full data sets. In 2005 the image selection was further improved by automating the Quick Look analyses considering the percentage of cloud free land in each scene. Selected images were then automatically downloaded, geo-coded and used to compile time series in 8 different tiles covering most of Europe. In 2006 the system was set to receive the MODIS imagery through direct broadcast allowing for a better time response and to have an European tailored service. The results of the burned area mapping of 2006 in a number of European countries are presented and compared with official statistics from each analysed country. An alternative to visual classification that relies on imagery time series analysis is also presented; this method is based on abrupt post-fire vegetation change detected from MODIS daily time series that will allow for a better and less user-dependent classification of the burned areas
Multi-scale burned area mapping in EUMed using historical series of satellite images
Burned area maps permit knowing the extent and location of fire affected areas at different spatial and temporal scales. Remote sensing has shown to be an appropriate tool to detect and map fire-affected areas and monitor the succession and recovery of burned surfaces. This information enables scientists, managers and policy makers to understand how fire is influencing vegetation and other relevant processes at short- or long-term scales. In FUME project, multisource satellite data was used to reconstruct recent fire history and characterize fire regimes at multiple spatial and temporal scales in Mediterranean Europe; producing time series of burned area maps relevant for fire-impact assessments, environmental planning and management.
Evaluation of satellite-derived burned area products for the fynbos, a Mediterranean shrubland
International Journal of Wildland Fire, 2012
Fire is a critical ecological process in the fynbos of the south-western area of South Africa, as it is for all dwarf Mediterranean shrublands. We evaluated the potential of current publicly available MODIS burned area products to contribute to an accurate fire history of the fynbos. To this end, we compared the Meraka Institute’s MODIS burned area product, based on the Giglio algorithm (termed the ‘WAMIS’ product) as well as the standard MODIS MCD45A1 burned area product, based on the Roy algorithm, with comprehensive manager-mapped fire boundary data. We used standard inventory accuracy assessment (number and size of individual burn scars) and confusion matrix techniques. Results showed promise for both burned area products, depending on the intended use. The MCD45A1 had low errors of commission (8.1–19.1%) and high consumer’s accuracy (80.9–91.9%), but relatively common errors of omission, making it useful for studies that need to identify burned pixels with a high degree of cert...
Analyzing the Resilience of Mediterranean Forest Systems to Wildfire Using Satellite Imagery
2011
The objective is to monitor vegetation recovery after the large fires of 2003 in Portugal using a time-series of MODIS Terra Enhanced Vegetation Index (EVI) data. Post-fire vegetation regeneration rate was estimated using Olson's model. We attempted to model it as a function of fire history, including number of times burned prior to 2003. This study shows that satellite imagery can be very valuable for studying post-fire vegetation response, and this can contribute to a better understanding of wildfires, lead to improved management strategies for prevention, or even improve allocation of firefighting resources.
An improved algorithm for mapping burnt areas in the Mediterranean forest landscape of Morocco
Journal of Forestry Research, 2018
The identification of burnt forests and their monitoring provide essential information for the suitable management and conservation of these ecosystems. This research focuses on the use of remote sensing with MODIS sensor data in a Mediterranean environment, precisely in the Rif region known for its high occurrence of forest fires and the largest burnt areas in Morocco. It mapped the burnt areas during the summer of 2016 using spectral indices from MODIS images, namely the Normalized Burn Ratio (NBR) and the Burnt Area Index for MODIS (BAIM). Two field surveys were used to calibrate spectral indices and validate the maps. First, a monotemporal analysis using a single pre-fire image determined the appropriate threshold of the spectral indices (BAIM and NBR) for burn detecting. Secondly, a multitemporal method was applied based on dBAIM and dNBR images which represented pre-fire and postfire differences of the BAIM and NBR images, respectively. The results show that separate use of monotemporal postfire and multitemporal methods produced an overestimation of the burnt areas. Finally, we propose a new algorithm combining both methods for burnt area mapping that we name Burnt Area Algorithm. MCD45A1 and MCD64A1 MODIS burnt area products were compared to the proposed algorithm. Validation of the estimated burnt areas using reference data of the Moroccan High Commission for Water, Forests and Fight against Desertification showed satisfactory results using the proposed algorithm, with a determination coefficient of 0.68 and a root mean square error of 44.0 ha.
Remote Sensing
In Mediterranean countries, in the year 2017, extensive surfaces of forests were damaged by wildfires. In the Vesuvius National Park, multiple summer wildfires burned 88% of the Mediterranean forest. This unprecedented event in an environmentally vulnerable area suggests conducting spatial assessment of the mixed-severity fire effects for identifying priority areas and support decision-making in post-fire restoration. The main objective of this study was to compare the ability of the delta Normalized Burn Ratio (dNBR) spectral index obtained from Landsat-8 and Sentinel-2A satellites in retrieving burn severity levels. Burn severity levels experienced by the Mediterranean forest communities were defined by using two quali-quantitative field-based composite burn indices (FBIs), namely the Composite Burn Index (CBI), its geometrically modified version CBI (GeoCBI), and the dNBR derived from the two medium-resolution multispectral remote sensors. The accuracy of the burn severity map pr...