Göran Ståhl

Nature and Landscape Conservation · 2001–2022

A researcher in the Science corpus: 14 papers; trusts 10 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Nature and Landscape Conservation — 98 citations into it
• Environmental Engineering — 43 citations into it; #2,670 of 5,479 by trust here, #1,393 by citations
• Global and Planetary Change — 39 citations into it
• Insect Science — 30 citations into it
• Statistics and Probability — 12 citations into it

Whom Göran Ståhl trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Erik Næsset
2. Ross Nelson
3. Tron Eid
4. Ronald E. McRoberts
5. Terje Gobakken
6. Johan Holmgren
7. David W. Hosmer Jr.
8. Jérôme Chave

Who trusts Göran Ståhl overall

1. Ronald E. McRoberts
2. Jonas Fridman
3. Sören Holm
4. Qi Chen
5. Hooman Latifi

Papers from Göran Ståhl's perspective

Ordered by how strongly the researchers Göran Ståhl trusts endorse each paper. Same corpus, a different order for every researcher.

1. Practical large-scale forest stand inventory using a small-footprint airborne scanning laser
2. Prediction of tree height, basal area and stem volume in forest stands using airborne laser scanning
3. Assessing effects of positioning errors and sample plot size on biophysical stand properties derived from airborne laser scanner data.
4. A Multiple Resource Inventory of Delaware Using Airborne Laser Data
5. Model-based mean square error estimators for k-nearest neighbour predictions and applications using remotely sensed data for forest inventories
6. Using satellite imagery as ancillary data for increasing the precision of estimates for the Forest Inventory and Analysis program of the USDA Forest Service
7. Use of uncertain inventory data in forestry scenario models and consequential incorrect harvest decisions.
8. Effects of uncertainty in model predictions of individual tree volume on large area volume estimates
9. Applied Logistic Regression: Hosmer/Applied Logistic Regression
10. Error propagation and scaling for tropical forest biomass estimates. (Philosophical transactions of the Royal Society of London. Series B, Biological sciences)

Their papers

• GEDI launches a new era of biomass inference from space (2022) — 206 citations
• Assessing components of the model-based mean square error estimator for remote sensing assisted forest applications (2018) — 49 citations
• Combining UAV and Sentinel-2 auxiliary data for forest growing stock volume estimation through hierarchical model-based inference (2018) — 151 citations
• Hybrid estimators for mean aboveground carbon per unit area (2016) — 73 citations
• Plant functional traits have globally consistent effects on competition (2015) — 844 citations
• Adapting National Forest Inventories to changing requirements - the case of the Swedish National Forest Inventory at the turn of the 20th century (2014) — 270 citations
• A simulation approach for accuracy assessment of two-phase post-stratified estimation in large-area LiDAR biomass surveys (2013) — 52 citations
• Harmonizing national forest inventories (2012) — 89 citations
• Assessing the accuracy of regional LiDAR-based biomass estimation using a simulation approach (2012) — 98 citations
• Model-assisted estimation of biomass in a LiDAR sample survey in Hedmark County, NorwayThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time. (2011) — 158 citations
• Model-based inference for biomass estimation in a LiDAR sample survey in Hedmark County, Norway (2011) — 181 citations
• Modelling root rot incidence in Sweden using tree, site and stand variables (2005) — 72 citations
• Cost-Plus-Loss Analyses of Forest Inventory Strategies Based on kNN- Assigned Reference Sample Plot Data (2003) — 75 citations
• Simultaneous Estimations of Forest Parameters using Aerial Photograph Interpreted Data and the k Nearest Neighbour Method (2001) — 69 citations