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How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass?

Varvia, P. and Korhonen, L. and Bruguiere, A. and Toivonen, J. and Packalen, P. and Maltamo, M. and Saarela, Svetlana and Popescu, S. C. (2022). How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass? Remote Sensing of Environment. 280 , 113174
[Research article]

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Abstract

The objective of this study was to explore the effects of (1) the presence/absence of snow and snow depth, (2) solar noise, i.e., day/night and sun angle observations, and (3) strong/weak beam differences on ICESat2 data in the context of data utility for forest AGB estimation. The framework of the study is multiphase modeling, where AGB field data and wall-to-wall airborne laser scanning (ALS) and Sentinel-2 data are used to produce proxy ALS plots on ICESat-2 track positions. Models between the predicted proxy AGB and the ICESat-2 photon data are then formulated and evaluated by subsets, such as only strong beam data captured in snowy conditions.Our results indicate that, if possible, strong beam night data from snowless conditions should be used in AGB estimation, because our models showed clearly smallest RMSE (26.9%) for this data subset. If more data are needed, we recommend using only strong beam data and constructing separate models for the different data subsets. In the order of increasing RMSE%, the next best options were snow/night/strong (30.4%), snow/day/strong (33.5%), and snowless/day/strong (34.1%). Weak beam data from snowy night conditions could also be used if necessary (31.0%).

Authors/Creators:Varvia, P. and Korhonen, L. and Bruguiere, A. and Toivonen, J. and Packalen, P. and Maltamo, M. and Saarela, Svetlana and Popescu, S. C.
Title:How to consider the effects of time of day, beam strength, and snow cover in ICESat-2 based estimation of boreal forest biomass?
Series Name/Journal:Remote Sensing of Environment
Year of publishing :2022
Volume:280
Article number:113174
Number of Pages:10
Publisher:ELSEVIER SCIENCE INC
ISSN:0034-4257
Language:English
Publication Type:Research article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Remote Sensing
(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Forest Science
Keywords:ICESat-2, Above-ground biomass, Boreal forest, Mixed-effect models, Lidar
URN:NBN:urn:nbn:se:slu:epsilon-p-118778
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-118778
Additional ID:
Type of IDID
DOI10.1016/j.rse.2022.113174
Web of Science (WoS)000839328200001
ID Code:28778
Faculty:S - Faculty of Forest Sciences
Department:(S) > Dept. of Forest Resource Management
(NL, NJ) > Dept. of Forest Resource Management
Deposited By: SLUpub Connector
Deposited On:05 Sep 2022 12:29
Metadata Last Modified:05 Sep 2022 12:31

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