Research article2024Peer reviewedOpen access
Estimation of plant density based on presence/absence data using hybrid inference
Gozé, Léna; Ekström, Magnus; Sandring, Saskia et al.
Göran Ståhl
Department of Forest Resource Management
Email: Goran.Stahl@slu.se
ORCID: 0000-0001-9030-8057
Publications
2024
Research article2024Peer reviewedOpen access
Why ecosystem characteristics predicted from remotely sensed data are unbiased and biased at the same time - and how this affects applications
Stahl, Goran; Gobakken, Terje; Saarela, Svetlana et al.
2023
Book chapter2023Peer reviewedOpen access
Social data: what exists in reporting schemes for different land systems?
Wood, Claire; Sandewall, Mats; Sandström, Stefan et al.
Book chapter2023Peer reviewedOpen access
Demands on monitoring
Allard, Anna; Guerrero, Santiago; Aagaard Christensen, Andreas et al.
Research article2023Peer reviewedOpen access
Estimating aboveground biomass density using hybrid statistical inference with GEDI lidar data and Paraguay's national forest inventory
Bullock, Eric L.; Healey, Sean P.; Yang, Zhiqiang et al.
Research article2023Peer reviewedOpen access
Leveraging remotely sensed non-wall-to-wall data for wall-to-wall upscaling in forest inventory
Chen, Fangting; Hou, Zhengyang; Saarela, Svetlana et al.
Research article2023Peer reviewed
How many bootstrap replications are necessary for estimating remote sensing-assisted, model-based standard errors?
McRoberts, Ronald E.; Naesset, Erik; Hou, Zhengyang et al.
Conference abstract2023
Impact of field reference errors for remote sensing predictions
Persson, Henrik; Ekström, Magnus; Ståhl, Göran.
Research article2023Peer reviewedOpen access
Three-phase hierarchical model-based and hybrid inference
Saarela, Svetlana; Varvia, Petri; Korhonen, Lauri.
Conference abstract2023
Model-based estimation and mapping of plant density based on remote sensing and presence/absence data
Ekström, Magnus; Gozé, Léna; Wallerman, Jörgen et al.
Research article2023Peer reviewed
Conjugating remotely sensed data assimilation and model-assisted estimation for efficient multivariate forest inventory
Hou, Zhengyang; Yuan, Keyan; Stahl, Goran et al.
2022
Research article2022Peer reviewedOpen access
Data Assimilation of Growing Stock Volume Using a Sequence of Remote Sensing Data from Different Sensors
Lindgren, Nils; Olsson, Hakan; Nystrom, Kenneth et al.
Research article2022Peer reviewedOpen access
Multiple drivers of large-scale lichen decline in boreal forest canopies
Esseen, Per-Anders; Ekstrom, Magnus; Grafstrom, Anton et al.
Research article2022Peer reviewedOpen access
Cross-classes domain inference with network sampling for natural resource inventory
Hou, Zhengyang; McRoberts, Ronald E.; Zhang, Chunyu et al.
Research article2022Peer reviewedOpen access
Comparing frameworks for biomass prediction for the Global Ecosystem Dynamics Investigation
Saarela, Svetlana; Hol, Soren; Healey, Sean P. et al.
Research article2022Peer reviewedOpen access
GEDI launches a new era of biomass inference from space
Dubayah, Ralph; Armston, John; Healey, Sean P. et al.
Research article2022Peer reviewedOpen access
Importance of Calibration for Improving the Efficiency of Data Assimilation for Predicting Forest Characteristics
Lindgren, Nils; Nystrom, Kenneth; Saarela, Svetlana et al.
Research article2022Peer reviewedOpen access
Quantify and account for field reference errors in forest remote sensing studies
Persson, Henrik Jan; Ekstrom, Magnus; Stahl, Goran.
2021
Research article2021Peer reviewedOpen access
Rapid Changes in Ground Vegetation of Mature Boreal Forests-An Analysis of Swedish National Forest Inventory Data
Jonsson, Bengt Gunnar; Dahlgren, Jonas; Ekstrom, Magnus et al.
Conference abstract2021
Estimating density from presence/absence data in clustered populations
Ekström, Magnus; Sandring, Saskia; Grafström, Anton et al.
Conference abstract2021
The GEDI Gridded Biomass Product: Patterns of Coverage and Precision After Two Years of Operation
Healey, Sean; Armston, John David; Yang, Zhiqiang et al.
Research article2021Peer reviewed
Generalizing systematic adaptive cluster sampling for forest ecosystem inventory
Xu, Qing; Stahl, Goran; McRoberts, Ronald E. et al.
2020
Research article2020Peer reviewedOpen access
Mapping aboveground biomass and its prediction uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors
Saarela, Svetlana; Wastlund, Andre; Holmstrom, Emma et al.
Research article2020Peer reviewedOpen access
Presence–absence sampling for estimating plant density using survey data with variable plot size
Ståhl, Göran; Ekström, Magnus; Dahlgren, Jonas et al.
Research article2020Peer reviewedOpen access
Estimating density from presence/absence data in clustered populations
Ekstrom, Magnus; Sandring, Saskia; Grafstrom, Anton et al.
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