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 |