Göran Ståhl

Department of Forest Resource Management

Faculty of Forest Sciences

Email: Goran.Stahl@slu.se
ORCID: 0000-0001-9030-8057

Publications

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2023

Social data: what exists in reporting schemes for different land systems?

Wood, Claire; Sandewall, Mats; Sandström, Stefan et al. 2023. DOI: 10.4324/9781003179245-10

Book chapter (Peer reviewed)

Demands on monitoring

Allard, Anna; Guerrero, Santiago; Aagaard Christensen, Andreas et al. 2023. DOI: 10.4324/9781003179245-3

Book chapter (Peer reviewed)

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. 2023. DOI: 10.1088/1748-9326/acdf03

Research article (Peer reviewed)

Leveraging remotely sensed non-wall-to-wall data for wall-to-wall upscaling in forest inventory

Chen, Fangting; Hou, Zhengyang; Saarela, Svetlana et al. 2023. DOI: 10.1016/j.jag.2023.103314

Research article (Peer 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. 2023. DOI: 10.1016/j.rse.2023.113455

Research article (Peer reviewed)

2022

Data Assimilation of Growing Stock Volume Using a Sequence of Remote Sensing Data from Different Sensors

Lindgren, Nils; Olsson, Hakan; Nystrom, Kenneth et al. 2022. DOI: 10.1080/07038992.2021.1988542

Research article (Peer reviewed)

Multiple drivers of large-scale lichen decline in boreal forest canopies

Esseen, Per-Anders; Ekstrom, Magnus; Grafstrom, Anton et al. 2022. DOI: 10.1111/gcb.16128

Research article (Peer reviewed)

Cross-classes domain inference with network sampling for natural resource inventory

Hou, Zhengyang; McRoberts, Ronald E.; Zhang, Chunyu et al. 2022. DOI: 10.1016/j.fecs.2022.100029

Research article (Peer reviewed)

Comparing frameworks for biomass prediction for the Global Ecosystem Dynamics Investigation

Saarela, Svetlana; Hol, Soren; Healey, Sean P. et al. 2022. DOI: 10.1016/j.rse.2022.113074

Research article (Peer reviewed)

GEDI launches a new era of biomass inference from space

Dubayah, Ralph; Armston, John; Healey, Sean P. et al. 2022. DOI: 10.1088/1748-9326/ac8694

Research article (Peer reviewed)

Importance of Calibration for Improving the Efficiency of Data Assimilation for Predicting Forest Characteristics

Lindgren, Nils; Nystrom, Kenneth; Saarela, Svetlana et al. 2022. DOI: 10.3390/rs14184627

Research article (Peer reviewed)

Quantify and account for field reference errors in forest remote sensing studies

Persson, Henrik Jan; Ekstrom, Magnus; Stahl, Goran. 2022. DOI: 10.1016/j.rse.2022.113302

Research article (Peer reviewed)

2021

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. 2021. DOI: 10.3390/f12040475

Research article (Peer reviewed)

Estimating density from presence/absence data in clustered populations

Ekström, Magnus; Sandring, Saskia; Grafström, Anton et al. 2021.

Conference abstract

The GEDI Gridded Biomass Product: Patterns of Coverage and Precision After Two Years of Operation

Healey, Sean; Armston, John David; Yang, Zhiqiang et al. 2021.

Conference abstract

Generalizing systematic adaptive cluster sampling for forest ecosystem inventory

Xu, Qing; Stahl, Goran; McRoberts, Ronald E. et al. 2021. DOI: 10.1016/j.foreco.2021.119051

Research article (Peer reviewed)

2020

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. 2020. DOI: 10.1186/s40663-020-00245-0

Research article (Peer reviewed)

Presence–absence sampling for estimating plant density using survey data with variable plot size

Ståhl, Göran; Ekström, Magnus; Dahlgren, Jonas et al. 2020. DOI: 10.1111/2041-210X.13348

Research article (Peer reviewed)

Estimating density from presence/absence data in clustered populations

Ekstrom, Magnus; Sandring, Saskia; Grafstrom, Anton et al. 2020. DOI: 10.1111/2041-210X.13347

Research article (Peer reviewed)

Comparison of estimators of variance for forest inventories with systematic sampling-results from artificial populations

Magnussen, Steen; McRoberts, Ronald E.; Breidenbach, Johannes et al. 2020. DOI: 10.1186/s40663-020-00223-6

Research article (Peer reviewed)

Characterizing Uncertainty in Forest Remote Sensing Studies

Persson, Henrik Jan; Stahl, Goeran. 2020. DOI: 10.3390/rs12030505

Research article (Peer reviewed)

2019

Remote sensing-assisted data assimilation and simultaneous inference for forest inventory

Hou, Zhengyang; Mehtatalo, Lauri; McRoberts, Ronald E. et al. 2019. DOI: 10.1016/j.rse.2019.111431

Research article (Peer reviewed)

Forest biomass estimation over three distinct forest types using TanDEM-X InSAR data and simulated GEDI lidar data

Qi, Wenlu; Saarela, Svetlana; Armston, John et al. 2019. DOI: 10.1016/j.rse.2019.111283

Research article (Peer reviewed)

On combining independent probability samples

Grafstrom, Anton; Ekstrom, Magnus; Jonsson, Bengt Gunnar et al. 2019.

Research article (Peer reviewed)

Statistical properties of hybrid estimators proposed for GEDI-NASA's global ecosystem dynamics investigation

Patterson, Paul L.; Healey, Sean P.; Stahl, Goran et al. 2019. DOI: 10.1088/1748-9326/ab18df

Research article (Peer reviewed)

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