Arne Nothdurft

Nature and Landscape Conservation · 2006–2021

A researcher in the Science corpus: 8 papers; trusts 30 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Nature and Landscape Conservation — 106 citations into it; #2,155 of 6,941 by trust here, #4,257 by citations
• Global and Planetary Change — 79 citations into it; #4,337 of 10,225 by trust here, #8,506 by citations
• Environmental Engineering — 37 citations into it; #1,772 of 5,479 by trust here, #2,867 by citations
• Insect Science — 29 citations into it
• Ecology — 22 citations into it
• Statistics and Probability — 17 citations into it
• Artificial Intelligence — 10 citations into it
• Economics and Econometrics — 6 citations into it

Whom Arne Nothdurft trusts overall

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

1. Erik Næsset
2. N. Crookston
3. Matti Maltamo
4. A. R. Stage
5. Marie Davidian
6. Johannes Breidenbach
7. Torsten Hothorn
8. Chao Chen
9. Marco Heurich
10. Andrew Thomas Hudak

Who trusts Arne Nothdurft overall

1. Hooman Latifi
2. Aaron Weiskittel
3. Barbara Koch
4. Johannes Breidenbach
5. Matthias Schmidt
6. Ronald E. McRoberts
7. Yuqing Yang
8. Liyong Fu
9. Petteri Packalen
10. Andres Kiviste

Papers from Arne Nothdurft's perspective

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

1. Random Forests
2. Imputation of single-tree attributes using airborne laser scanning-based height, intensity, and alpha shape metrics
3. Modern Applied Statistics With S
4. Classification and Regression by randomForest
5. Nonparametric estimation of stem volume using airborne laser scanning, aerial photography, and stand-register data
6. Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data
7. Estimation and mapping of forest stand density, volume, and cover type using the k-nearest neighbors method
8. Partitioning Error Components for Accuracy-Assessment of Near-Neighbor Methods of Imputation (Forestry sciences)
9. Combining ALS and NFI training data for forest management planning: a case study in Kuortane, Western Finland (European Journal of Forest Research)
10. Prediction of species specific forest inventory attributes using a nonparametric semi-individual tree crown approach based on fused airborne laser scanning and multispectral data

Their papers

• The greater resilience of mixed forests to drought mainly depends on their composition: Analysis along a climate gradient across Europe (2021) — 226 citations
• Species mixing reduces drought susceptibility of Scots pine (Pinus sylvestris L.) and oak (Quercus robur L., Quercus petraea (Matt.) Liebl.) – Site water supply and fertility modify the mixing effect (2020) — 122 citations
• Stand growth and structure of mixed-species and monospecific stands of Scots pine (Pinus sylvestris L.) and oak (Q. robur L., Quercus petraea (Matt.) Liebl.) analysed along a productivity gradient through Europe (2019) — 98 citations
• Automatic Mapping of Forest Stands Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning (2017) — 60 citations
• Comparison of nearest neighbour approaches for small area estimation of tree species-specific forest inventory attributes in central Europe using airborne laser scanner data (2010) — 71 citations
• Non-parametric prediction and mapping of standing timber volume and biomass in a temperate forest: application of multiple optical/LiDAR-derived predictors (2010) — 220 citations
• Spatial prediction of forest stand variables (2009) — 48 citations
• A non-linear hierarchical mixed model to describe tree height growth (2006) — 48 citations