Christoph Kleinn
University of Göttingen
112 Papers
591 Citations
Christoph Kleinn is an academic researcher from University of Göttingen. The author has contributed to research in topics: Forest inventory & Sampling (statistics). The author has an hindex of 27, co-authored 105 publications. Previous affiliations of Christoph Kleinn include Stellenbosch University & Centro Agronómico Tropical de Investigación y Enseñanza.
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Papers
On the site-level suitability of biomass models
César Pérez-Cruzado,Lutz Fehrmann,Paul Magdon,Isabel Cañellas,Hortensia Sixto,Christoph Kleinn +5 more
TL;DR: An alternative approach based on non-parametric techniques to evaluate model suitability based on statistical tests is presented and can improve the transparency of global forest monitoring systems and can be implemented with relatively small effort.
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Land-use intensity and landscape structure drive the acoustic composition of grasslands
Sandra Cristina Müller,Martin M. Gossner,Caterina Penone,Kirsten Jung,Swen C. Renner,Almo Farina,Lisa Anhäuser,Manfred Ayasse,Steffen Boch,Janine Heitzmann,Christoph Kleinn,Paul Magdon,David J. Perović,Nadia Pieretti,Taylor E. Shaw,Juliane Steckel,Marco Tschapka,Juliane Vogt,Catrin Westphal +18 more
TL;DR: In this paper , structural equation models were applied to analyze the direct and indirect drivers of acoustic diversity and composition, including mowing and grazing intensities, landscape diversity, distance to the nearest road, vascular plant species richness as well as bird and orthopteran species richness and composition.
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Triangulation based inclusion probabilities: a design-unbiased sampling approach
TL;DR: In this article, a probabilistic sampling approach for design-unbiased estimation of area-related quantitative characteristics of spatially dispersed population units is proposed, which includes a fixed number of 3 units per sampling location and is based on partial triangulations over their natural neighbors to derive the individual inclusion probabilities.
Towards Tree Green Crown Volume: A Methodological Approach Using Terrestrial Laser Scanning
TL;DR: A methodological approach towards assessing the tree green crown volume (TGCVol), the crown volume with a high density of foliage, which is derived by terrestrial laser scanning in a case study of solitary urban trees.
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