Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/94DDBAA2-28F9-4A3A-85A2-1421FF13AAD7 | ||
| Year | 2008 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
| License |
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| Bibliographic Citation | A. Moustakas , D.T. Hristopulos ," Estimating tree abundance from remotely sensed imagery in semi-arid and arid environments: bringing small trees to the light", Stoch. Env. Re. and Risk As.,vol. 23.no.1,pp.111-118,2008.doi:10.1007/s00477-007-0199-x https://doi.org/10.1007/s00477-007-0199-x | ||
| Appears in Collections |
The analysis of remotely sensed images provides a powerful method for estimating tree abundance. However, a number of trees have sizes that are below the spatial resolution of remote sensing images, and as a result they cannot be observed and classified. We propose a method for estimating the number of such sub-resolution trees on forest stands. The method is based on a backwards extrapolation of the size-class distribution of trees as observed from the remotely sensed images. We apply our method to a tree database containing around 13,000 tree individuals to determine the number of sub-resolution trees. While the proposed method is formulated for estimating tree abundance from remotely sensed images, it is generally applicable to any database containing tree canopy surface area data with a minimum size cut-off.
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