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17 December 1999 Estimation of forest damage in Mediterranean areas by fuzzy classification of Landsat TM images
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In the last decades many forest areas are suffering from conventional and new types of damage, with a consequent loss of valuable ecological and economic resources. The monitoring of these damage has therefore become a primary application of satellite remotely sensed data, and particularly of Landsat TM imagery. Unfortunately, conventional mapping methods based on uni or multivariate regressions between ground measurement and remotely sensed spectral information have often led to unsatisfactory results, especially in complex environments where several disturbing factors can affect the forest spectral signatures. It is here proposed that a new, more flexible estimation method based on fuzzy classification of remotely sensed data can offer several advantages when used for this purpose. After a brief description of its basis, the method is applied together with conventional multivariate regression procedures in two case studies in Tuscany (Central Italy) representative of different forest types affected by damages of different origins. The results show that the new method produces higher accuracies in the estimation of forest damage, particularly in areas with complex environmental situations.
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Fabio Maselli, Lorenzo Bottai, and Arturo Oradini "Estimation of forest damage in Mediterranean areas by fuzzy classification of Landsat TM images", Proc. SPIE 3868, Remote Sensing for Earth Science, Ocean, and Sea Ice Applications, (17 December 1999);

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