Institutional Repository
Technical University of Crete
Technical University of Crete
EN
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EL
| URI | http://purl.tuc.gr/dl/dias/94DDBAA2-28F9-4A3A-85A2-1421FF13AAD7 | - |
| Identifier | https://doi.org/10.1007/s00477-007-0199-x | - |
| Language | en | - |
| Extent | 7 pages | en |
| Title | Estimating tree abundance from remotely sensed imagery in semi-arid and arid environments: bringing small trees to the light | en |
| Creator | D.T. Hristopulos | en |
| Creator | A. Moustakas | en |
| Publisher | Springer-Verlag | en |
| Content Summary | 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. | en |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2015-09-25 | - |
| Date of Publication | 2008 | - |
| 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 | en |
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