Browsing Publikasjoner fra CRIStin - NIBIO by Journals "Remote Sensing of Environment"
Now showing items 1-4 of 4
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Above-ground biomass change estimation using national forest inventory data with Sentinel-2 and Landsat
(Peer reviewed; Journal article, 2021-08-25)This study aimed at estimating total forest above-ground net change (ΔAGB; Gg) over five years (2014–2019) based on model-assisted estimation utilizing freely available satellite imagery. The study was conducted for a ... -
Detecting change-point, trend, and seasonality in satellite time series data to track abrupt changes and nonlinear dynamics: A Bayesian ensemble algorithm
(Peer reviewed; Journal article, 2019-10)Satellite time-series data are bolstering global change research, but their use to elucidate land changes and vegetation dynamics is sensitive to algorithmic choices. Different algorithms often give inconsistent or sometimes ... -
Modelling above-ground biomass stock over Norway using national forest inventory data with ArcticDEM and Sentinel-2 data
(Peer reviewed; Journal article, 2019-11-07)Boreal forests constitute a large portion of the global forest area, yet they are undersampled through field surveys, and only a few remotely sensed data sources provide structural information wall-to-wall throughout the ... -
Unit-level and area-level small area estimation under heteroscedasticity using digital aerial photogrammetry data
(Journal article; Peer reviewed, 2018)In many applications, estimates are required for small sub-populations with so few (or no) sample plots that direct estimators that do not utilize auxiliary variables (e.g. remotely sensed data) are not applicable or result ...