Transformation and Validation Methods in Allometric Remote Sensing Based Equations (CROSBI ID 694622)
Prilog sa skupa u zborniku | sažetak izlaganja sa skupa | međunarodna recenzija
Podaci o odgovornosti
Tafro, Azra ; Balenović, Ivan ; Jazbec, Anamarija
engleski
Transformation and Validation Methods in Allometric Remote Sensing Based Equations
In addition to classical (time-consuming and labor-intensive) field measurements, remote sensing methods can be used to estimate various forest attributes at individual tree, plot or stand level. Remote sensing methods can reduce field work and improve the efficiency, but the accuracy of obtained results have to be carefully tested and evaluated. In this study, plot level volume of pedunculate oak forest was estimated using metrics extracted from digital surface model derived from aerial images and normalized using digital terrain model derived from airborne laser scanning. Traditional allometric equations for volume estimation are developed using linear regression on log- transformed data, which often causes bias in the estimation when errors are not additive. Several correction methods have been proposed to varying degrees of success, depending on the quantity of interest. Additionally, smaller sample sizes can cause poor goodness of fit, and greater variance in model error estimation. In this paper, the authors study bias in volume estimation, using multiple assessment and validation methods, to propose the optimal model for this type of data.
allometry ; nonlinear regression ; log-linear regression ; validation
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Podaci o prilogu
46-47.
2020.
objavljeno
Podaci o matičnoj publikaciji
Book of Abstracts 18th International Conference on Operational Research
Arnerić, Josip ; Čeh Časni, Anita
1849-5141
Podaci o skupu
18th International Conference on Operational Research (KOI 2020)
predavanje
23.09.2020-25.09.2020
Šibenik, Hrvatska