Increasing Spatial Detail of Burned Scar Maps Using IRS‑AWiFS Data for Mediterranean Europe

Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; McInerney, Daniel; Miguel, Jesús San

doi:10.3390/rs4030726

Cited by 20 publications

(15 citation statements)

References 39 publications

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“…of early-season fires is captured from available images acquired at mid-to end-season. Moreover, an increase in the number of available images significantly increases the ability to capture fires because the chances of getting full, cloud-free coverage of the area of interest increase (Sedano et al, 2012) and the large number of acquisitions assists in reducing the between-acquisition period, thus allowing the capture of signals of relatively small fires that otherwise would have faded due to vegetation recovery, particularly in areas reflecting increased summer-precipitation totals (Sedano et al, 2012). Similar arguments also apply for the failure of 'date of the last image' to enter the models as a significant explanatory variable.…”

Section: Modelling the Errorsmentioning

confidence: 99%

“…Similarly, date of image acquisition affects the success of the assessment of burn severity (Hudak et al, 2007). Another parameter that contributes to the underestimation of burned scars is the presence of fires after the image acquisition (Sedano, Kempeneers, Strobl, McInerney, & San Miguel, 2012), revealing the importance of the end-date acquisition. The relative importance of each of the above-mentioned parameters in fire scar mapping has not yet been extensively evaluated.…”

Section: Introductionmentioning

confidence: 99%

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Maps of fire occurrence – spatially explicit reconstruction of recent fire history using satellite remote sensing

et al. 2012

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Maps depicting the spatially explicit fire history of an area, including variables such as fire frequency and fire return interval, are important tools promoting the understanding of processes associated with wildfires (fire ignition and spread), the assessment of the impacts of wildland fires on landscape dynamics, and decisions on appropriate management practices. Remote sensing is a cost-and time-effective alternative to automatically assess a vast amount of spatial information and produce various thematic maps. The aim of this study was to reconstruct the recent fire history of Attica region (Greece), in a spatially explicit mode by means of remote sensing techniques using a series of Landsat images acquired from 1984 to 2011. The results show that the fire scar perimeters were captured with high accuracy. Regression modelling shows that the differences between the area burned estimated from satellite data and that recorded by the forest service can be explained (86.3% of the variance) by the number of satellite images used (standardized coefficient 0.752) followed by the date of the first image (standardized coefficient 0.705). The use of satellite data as the basic source of information alongside automated classification methods should be promoted for the creation of fire history maps. The latter is further supported when considering the long history of data capture from Landsat satellites, which provide a huge, global historical archive of repeat images of the Earth's surface.

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Section: Modelling the Errorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Maps of fire occurrence – spatially explicit reconstruction of recent fire history using satellite remote sensing

et al. 2012

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“…Accurate information of natural and human influences about fire regimes are critical to prevent future events and restore areas already affected. Remote sensing is one of the main techniques for assessing the damage effects from fire events because of its synoptic nature, cost-efficiency, rapid wildfire damage assessments, and acquisition of long-term information about ecosystem dynamics [1][2][3]. Several remote sensing techniques have been proposed to assess burned areas [4,5].…”

Section: Introductionmentioning

confidence: 99%

Standardized Time-Series and Interannual Phenological Deviation: New Techniques for Burned-Area Detection Using Long-Term MODIS-NBR Dataset

et al. 2015

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Typically, digital image processing for burned-areas detection combines the use of a spectral index and the seasonal differencing method. However, the seasonal differencing has many errors when applied to a long-term time series. This article aims to develop and test two methods as an alternative to the traditional seasonal difference. The study area is the Chapada dos Veadeiros National Park (Central Brazil) that comprises different vegetation of the Cerrado biome. We used the MODIS/Terra Surface Reflectance 8-Day composite data, considering a 12-year period. The normalized burn ratio was calculated from the band 2 (250-meter resolution) and the band 7 (500-meter resolution reasampled to 250-meter). In this context, the normalization methods aim to eliminate all possible sources of spectral variation and highlight the burned-area features. The proposed normalization methods were the standardized time-series and the interannual phenological deviation. The standardized time-series calculate for each pixel the z-scores of its temporal curve, obtaining a mean of 0 and a standard deviation of 1. The second method establishes a reference curve for each pixel from the average interannual phenology that is subtracted for every year of its respective time series. Optimal threshold value between burned and unburned area for each method was determined from accuracy assessment curves, which compare different threshold values and its accuracy indices with a reference classification using Landsat TM. The different methods have similar accuracy for the burning event, where the standardized method has slightly better results. However, the seasonal difference OPEN ACCESS Remote Sens. 2015, 7 6951 method has a very false positive error, especially in the period between the rainy and dry seasons. The interannual phenological deviation method minimizes false positive errors, but some remain. In contrast, the standardized time series shows excellent results not containing this type of error. This precision is due to the design method that does not perform a subtraction with a baseline (prior year or average phenological curve). Thus, this method allows a high stability and can be implemented for the automatic detection of burned areas using long-term time series.

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“…Yet, to our knowledge, very few validation studies have established the accuracy at which estimates of burnt area by those products is provided. Such studies have been based primarily on performing either direct comparisons with higherresolution data or intercomparisons between the different datasets (Boschetti et al, 2004Silva et al, 2005;Roy et al, 2008;Roy and Boschetti, 2009;Sedano et al, 2012), despite the fact that it is indispensable to objectively characterise the accuracy of global datasets and their limitations for providing a measure of quality of a dataset, and for understanding their errors and the potential implications in different applications (Silva et al, 2005). What is more, policy and management requests of satellite products for different types of applications place a high priority on providing statements about their accuracy (Morisette et al, 2006).…”

Section: P Kalivas Et Al: An Intercomparison Of Burnt Area Estimmentioning

confidence: 99%

An intercomparison of burnt area estimates derived from key operational products: the Greek wildland fires of 2005–2007

Kalivas

Petropoulos

Athanasiou

et al. 2013

Nonlin. Processes Geophys.

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With the support of new technologies such as of remote sensing, today's societies have been able to map and analyse wildland fires at large observational scales. With regards to burnt area mapping in particular, two of the most widely used operational products are offered today by the United States National Aeronautics and Space Administration (NASA) and the European Forest Fires Information System (EFFIS) of the European Commission. In this study, a rigorous intercomparison of the burnt area estimates derived by these two products is performed in a geographical information system (GIS) environment for the Greek fires that occurred from 2005 to 2007. For the same temporal interval, the relationships of the burnt area estimates by each product are examined with respect to land use/cover and elevation derived from CORINE 2000 and the ASTER global digital elevation model (GDEM), respectively. Generally, noticeable differences were found in the burnt area estimates by the two products both spatially and in absolute numbers. The main findings are described and the differences in the burnt area estimates between the two operational datasets are discussed. The lack of precise agreement between the two products which was found does not necessarily mean that one or the other product is inaccurate. Rather, it underlines the requirement for their calibration and validation using high-resolution remote sensing data in future studies. Our work not only builds upon a series of analogous studies evaluating the accuracy of the same or similar operational products worldwide, but also contributes towards the development of standardised validation methodologies required in objectively evaluating such datasets

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Increasing Spatial Detail of Burned Scar Maps Using IRS‑AWiFS Data for Mediterranean Europe

Cited by 20 publications

References 39 publications

Maps of fire occurrence – spatially explicit reconstruction of recent fire history using satellite remote sensing

Maps of fire occurrence – spatially explicit reconstruction of recent fire history using satellite remote sensing

Standardized Time-Series and Interannual Phenological Deviation: New Techniques for Burned-Area Detection Using Long-Term MODIS-NBR Dataset

An intercomparison of burnt area estimates derived from key operational products: the Greek wildland fires of 2005–2007

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