Determining maximum entropy in 3D remote sensing height distributions and using it to improve aboveground biomass modelling via stratification

Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid

StandardStandard

Determining maximum entropy in 3D remote sensing height distributions and using it to improve aboveground biomass modelling via stratification. / Adnan, Syed; Maltamo, Matti; Mehtätalo, Lauri et al.
Yn: Remote Sensing of Environment, Cyfrol 260, 07.2021, t. 112464.

Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid

HarvardHarvard

Adnan, S, Maltamo, M, Mehtätalo, L, Ammaturo, RNL, Packalen, P & Valbuena, R 2021, 'Determining maximum entropy in 3D remote sensing height distributions and using it to improve aboveground biomass modelling via stratification', Remote Sensing of Environment, cyfrol. 260, tt. 112464. https://doi.org/10.1016/j.rse.2021.112464

APA

Adnan, S., Maltamo, M., Mehtätalo, L., Ammaturo, R. N. L., Packalen, P., & Valbuena, R. (2021). Determining maximum entropy in 3D remote sensing height distributions and using it to improve aboveground biomass modelling via stratification. Remote Sensing of Environment, 260, 112464. https://doi.org/10.1016/j.rse.2021.112464

CBE

Adnan S, Maltamo M, Mehtätalo L, Ammaturo RNL, Packalen P, Valbuena R. 2021. Determining maximum entropy in 3D remote sensing height distributions and using it to improve aboveground biomass modelling via stratification. Remote Sensing of Environment. 260:112464. https://doi.org/10.1016/j.rse.2021.112464

MLA

Adnan, Syed et al. "Determining maximum entropy in 3D remote sensing height distributions and using it to improve aboveground biomass modelling via stratification". Remote Sensing of Environment. 2021, 260. 112464. https://doi.org/10.1016/j.rse.2021.112464

VancouverVancouver

Adnan S, Maltamo M, Mehtätalo L, Ammaturo RNL, Packalen P, Valbuena R. Determining maximum entropy in 3D remote sensing height distributions and using it to improve aboveground biomass modelling via stratification. Remote Sensing of Environment. 2021 Gor;260:112464. Epub 2021 Ebr 23. doi: 10.1016/j.rse.2021.112464

Author

Adnan, Syed ; Maltamo, Matti ; Mehtätalo, Lauri et al. / Determining maximum entropy in 3D remote sensing height distributions and using it to improve aboveground biomass modelling via stratification. Yn: Remote Sensing of Environment. 2021 ; Cyfrol 260. tt. 112464.

RIS

TY - JOUR

T1 - Determining maximum entropy in 3D remote sensing height distributions and using it to improve aboveground biomass modelling via stratification

AU - Adnan, Syed

AU - Maltamo, Matti

AU - Mehtätalo, Lauri

AU - Ammaturo, Rhei N.L.

AU - Packalen, Petteri

AU - Valbuena, Rubén

PY - 2021/7

Y1 - 2021/7

KW - Forest structure

KW - Forest aboveground biomass

KW - Gini coefficient

KW - L-moments

KW - Airborne laser scanning

U2 - 10.1016/j.rse.2021.112464

DO - 10.1016/j.rse.2021.112464

M3 - Article

VL - 260

SP - 112464

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

SN - 0034-4257

ER -