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Assessing the feasibility of sub-pixel burned area mapping in miombo woodlands of northern Mozambique using MODIS imagery
Authors:A C L Sá  J M C Pereira  M J P Vasconcelos  J M N Silva  N Ribeiro  A Awasse
Affiliation:1. Department of Forestry , Instituto Superior de Agronomia , Tapada da Ajuda, Lisboa, 1349-017, Portugal E-mail: anasa@isa.utl.pt;2. Department of Forestry , Instituto Superior de Agronomia , Tapada da Ajuda, Lisboa, 1349-017, Portugal E-mail: anasa@isa.utl.pt;3. Tropical Research Institute , Travessa do Conde da Ribeira 9, Lisboa, 1300-142, Portugal E-mail: mperestrelo@clix.pt;4. Tropical Research Institute , Travessa do Conde da Ribeira 9, Lisboa, 1300-142, Portugal E-mail: mperestrelo@clix.pt;5. Faculty of Agronomy and Forestry , Universidade Eduardo Mondlane , Campus Universit@rio edificio 1, C.P.257, Maputo, Mozambique E-mail: ldinis@topical.co.mz;6. Servi@os Provinciais de Florestas e Fauna Bravia , C.P.36 Nampula, Mozambique
Abstract:

The goal of this study was to evaluate the feasibility of sub-pixel burned area detection in the miombo woodlands of northern Mozambique, using imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS). Multitemporal Landsat-7 ETM+ data were acquired to produce a high spatial resolution map of areas burned between mid-August and late September 2000, and a field campaign was conducted in early November 2000 to gather ground truth data. Mapping of burned areas was performed with an ensemble of classification trees and yielded a kappa value of 0.896. This map was subsequently degraded to a spatial resolution of 500 m, to produce an estimate of burned area fraction, at the MODIS pixel size. Correlation analysis between the sub-pixel burned area fraction map and the MODIS reflective channels 1-7 yielded low but statistically significant correlations for all channels. The better correlations were obtained for MODIS channels 2 (0.86 µm), 5 (1.24 µm) and 6 (1.64 µm). A regression tree was constructed to predict sub-pixel burned area fraction as a function of those MODIS channels. The resulting tree has nine terminal nodes and an overall root mean square error of 0.252. The regression tree analysis confirmed that MODIS channels 2, 5, and 6 are the best predictors of burned area fraction. It may be possible to improve these results considering, as an alternative to individual channels, some appropriate spectral indices used to enhance the burnt scar signal, and by including MODIS thermal data in the analysis. It may also be possible to improve the accuracy of sub-pixel burned area fraction using MODIS imagery by allowing the regression tree to automatically create linear combinations of individual channels, and by using ensembles of trees.
Keywords:
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