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Stratified aboveground forest biomass estimation by remote sensing data

Latifi, Hooman and Fassnacht, Fabian E. and Hartig, Florian and Berger, Christian and Hernández, Jaime and Corvalán, Patricio and Koch, Barbara (2015) Stratified aboveground forest biomass estimation by remote sensing data. International Journal of Applied Earth Observation and Geoinformation, 38, pp. 229-241. Elsevier. doi: 10.1016/j.jag.2015.01.016. ISSN 0303-2434.

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Official URL: http://www.sciencedirect.com/science/article/pii/S0303243415000264


Item URL in elib:https://elib.dlr.de/96844/
Document Type:Article
Title:Stratified aboveground forest biomass estimation by remote sensing data
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Latifi, HoomanUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Fassnacht, Fabian E.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Hartig, FlorianUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Berger, ChristianUniversität JenaUNSPECIFIEDUNSPECIFIED
Hernández, JaimeUniversidad de ChileUNSPECIFIEDUNSPECIFIED
Corvalán, PatricioUniversidad de ChileUNSPECIFIEDUNSPECIFIED
Koch, BarbaraUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:2015
Journal or Publication Title:International Journal of Applied Earth Observation and Geoinformation
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:38
DOI:10.1016/j.jag.2015.01.016
Page Range:pp. 229-241
Publisher:Elsevier
ISSN:0303-2434
Status:Published
Keywords:LiDAR and hyperspectral remote sensing, Aboveground biomass, Statistical prediction, Post-stratification, Model performance, Factorial design
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Geoscientific remote sensing and GIS methods
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center
Deposited By: Wöhrl, Monika
Deposited On:18 Aug 2015 09:57
Last Modified:28 Nov 2023 08:29

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