Lindi J. Quackenbush
Environmental Engineering · 2010–2020
A researcher in the Science corpus: 5 papers; trusts 20 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Environmental Engineering — 39 citations into it; #2,136 of 5,479 by trust here, #2,313 by citations
- Ecology — 34 citations into it; #3,724 of 10,717 by trust here, #6,235 by citations
- Nature and Landscape Conservation — 28 citations into it; #2,877 of 6,941 by trust here, #5,887 by citations
- Media Technology — 23 citations into it
- Insect Science — 17 citations into it
- Computer Vision and Pattern Recognition — 10 citations into it
Whom Lindi J. Quackenbush trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jari Vauhkonen
- Erik Næsset
- Tomas Brandtberg
- Juho Pitkänen
- Pierre Machart
- Yinghai Ke
- Matti Maltamo
- Terje Gobakken
- J. Reitberger
- Sorin C. Popescu
Who trusts Lindi J. Quackenbush overall
Papers from Lindi J. Quackenbush's perspective
Ordered by how strongly the researchers Lindi J. Quackenbush trusts endorse each paper. Same corpus, a different order for every researcher.
- Imputation of single-tree attributes using airborne laser scanning-based height, intensity, and alpha shape metrics
- 3D segmentation of single trees exploiting full waveform LIDAR data
- Prediction of species specific forest inventory attributes using a nonparametric semi-individual tree crown approach based on fused airborne laser scanning and multispectral data
- Random Forests
- Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data
- Effects of pulse density on predicting characteristics of individual trees of Scandinavian commercial species using alpha shape metrics based on airborne laser scanning data
- A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners (IEEE Transactions on Geoscience and Remote Sensing)
- Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales
- A voxel-based lidar method for estimating crown base height for deciduous and pine trees
- Estimating crown base height for Scots pine by means of the 3D geometry of airborne laser scanning data
Their papers
- Google Earth Engine for geo-big data applications: A meta-analysis and systematic review (2020) — 1,126 citations
- Trends in Automatic Individual Tree Crown Detection and Delineation - Evolution of LiDAR Data (2016) — 322 citations
- Impact of training and validation sample selection on classification accuracy and accuracy assessment when using reference polygons in object-based classification (2013) — 86 citations
- A review of methods for automatic individual tree-crown detection and delineation from passive remote sensing (2011) — 354 citations
- Synergistic use of QuickBird multispectral imagery and LIDAR data for object-based forest species classification (2010) — 314 citations