Hans-Erik Andersen
Environmental Engineering · 2008–2018
A researcher in the Science corpus: 3 papers; trusts 6 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Environmental Engineering — 28 citations into it; #2,713 of 5,479 by trust here, #3,627 by citations
- Nature and Landscape Conservation — 13 citations into it; #3,253 of 6,941 by trust here, #5,573 by citations
- Ecology — 12 citations into it; #4,831 of 10,717 by trust here, #8,434 by citations
- Insect Science — 11 citations into it
- Global and Planetary Change — 9 citations into it
Whom Hans-Erik Andersen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Hans-Erik Andersen overall
Papers from Hans-Erik Andersen's perspective
Ordered by how strongly the researchers Hans-Erik Andersen trusts endorse each paper. Same corpus, a different order for every researcher.
- High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision
- Hierarchical Modeling and Analysis for Spatial Data
- Nonstationary multivariate process modeling through spatially varying coregionalization
- The origins of kriging
- The human footprint in the carbon cycle of temperate and boreal forests (Nature)
- Statistics For Spatial Data
- A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area-based approach
- A Large and Persistent Carbon Sink in the World’s Forests (Science)
- Prediction of species specific forest inventory attributes using a nonparametric semi-individual tree crown approach based on fused airborne laser scanning and multispectral data
- Boreal forest health and global change (Science)
Their papers
- Quantifying Boreal Forest Structure and Composition Using UAV Structure from Motion (2018) — 110 citations
- Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations (2017) — 60 citations
- A Comparison of Statistical Methods for Estimating Forest Biomass from Light Detection and Ranging Data (2008) — 120 citations