Burned area mapping with MERIS post-fire image
Identifiers
Permanent link (URI): http://hdl.handle.net/10017/64428DOI: 10.1080/01431161.2010.489062
ISSN: 01431161
Date
2011-08-11Academic Departments
Universidad de Alcalá. Departamento de Geología, Geografía y Medio Ambiente
Bibliographic citation
Oliva, P., MartíN, P. and Chuvieco, E. (2011) ‘Burned area mapping with MERIS post-fire image’, International journal of remote sensing, 32(15), pp. 4175–4201. Available at: https://doi.org/10.1080/01431161.2010.489062
Document type
info:eu-repo/semantics/article
Version
info:eu-repo/semantics/publishedVersion
Rights
©2011 Taylor & Francis
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Access rights
info:eu-repo/semantics/openAccess
Abstract
MERIS (Medium Resolution Imaging Spectrometer) offers a good balance between spectral, temporal and spatial resolution for mapping burned areas at a regional scale. In this article MERIS images were used to map fire-affected areas in the north-west of Spain, where extensive burning occurred in the summer of 2006. MERIS spectral indices and their ability to discriminate burned area signals have been assessed in this article. Additionally, the potentials of the spectral angle images (SAI) for mapping fire-affected areas were explored. SAI was used to measure the differences between pixels and reference spectra. The reference spectra were obtained from pure burned pixels in the image as well as from field spectral measurements. The MERIS burned area maps were then validated with visually digitized fire perimeters, produced from Advanced Wide Field Sensor, with 60 m pixel size. The Pareto boundary method was used to evaluate the errors from the error matrix, taking into account the spatial resolution of the sensor. This made it possible to discriminate between the errors caused by the spatial resolution and those caused by the limitations of the classification technique. Finally, the Euclidean distance between the errors and the Pareto boundary function was calculated in order to select the best result in an objective way. The ? index, a component of the Global Environmental Monitoring Index, showed the best performance among the input indices, with distance values of 3.3 in the fires related to a reference fire polygon; followed by SAI computed from the spectrum obtained from the image with a distance value of 5.7.
Files in this item
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| oliva_burned_IJRS_2011.pdf | 2.063Mb |
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| oliva_burned_IJRS_2011.pdf | 2.063Mb |
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