Το έργο με τίτλο Estimating tree abundance from remotely sensed imagery in semi-arid and arid environments: bringing small trees to the light από τον/τους δημιουργό/ούς D.T. Hristopulos διατίθεται με την άδεια Creative Commons Αναφορά Δημιουργού 4.0 Διεθνές
Βιβλιογραφική Αναφορά
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
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.